id	sid	tid	token	lemma	pos
brj-25043	1	1	peer	peer	NOUN
brj-25043	1	2	-	-	PUNCT
brj-25043	1	3	review	review	NOUN
brj-25043	1	4	article	article	NOUN
brj-25043	1	5	peer	peer	NOUN
brj-25043	1	6	-	-	PUNCT
brj-25043	1	7	reviewed	review	VERB
brj-25043	1	8	review	review	NOUN
brj-25043	1	9	article	article	NOUN
brj-25043	1	10	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	1	11	galal	galal	PROPN
brj-25043	1	12	et	et	PROPN
brj-25043	1	13	al	al	PROPN
brj-25043	1	14	.	.	PROPN
brj-25043	2	1	(	(	PUNCT
brj-25043	2	2	2025	2025	NUM
brj-25043	2	3	)	)	PUNCT
brj-25043	2	4	.	.	PUNCT
brj-25043	3	1	“	"	PUNCT
brj-25043	3	2	math	math	NOUN
brj-25043	3	3	modeling	modeling	NOUN
brj-25043	3	4	biogas	biogas	NOUN
brj-25043	3	5	production	production	NOUN
brj-25043	3	6	,	,	PUNCT
brj-25043	3	7	”	"	PUNCT
brj-25043	3	8	bioresources	bioresource	NOUN
brj-25043	3	9	20(4	20(4	NOUN
brj-25043	3	10	)	)	PUNCT
brj-25043	3	11	,	,	PUNCT
brj-25043	3	12	11237	11237	NUM
brj-25043	3	13	-	-	SYM
brj-25043	3	14	11266	11266	NUM
brj-25043	3	15	.	.	PUNCT
brj-25043	4	1	11237	11237	NUM
brj-25043	4	2	mathematical	mathematical	ADJ
brj-25043	4	3	modeling	modeling	NOUN
brj-25043	4	4	and	and	CCONJ
brj-25043	4	5	machine	machine	NOUN
brj-25043	4	6	learning	learning	NOUN
brj-25043	4	7	approaches	approach	NOUN
brj-25043	4	8	for	for	ADP
brj-25043	4	9	biogas	biogas	NOUN
brj-25043	4	10	production	production	NOUN
brj-25043	4	11	from	from	ADP
brj-25043	4	12	anaerobic	anaerobic	ADJ
brj-25043	4	13	digestion	digestion	NOUN
brj-25043	4	14	:	:	PUNCT
brj-25043	4	15	a	a	DET
brj-25043	4	16	review	review	NOUN
brj-25043	4	17	osama	osama	PROPN
brj-25043	4	18	h.	h.	PROPN
brj-25043	4	19	galal	galal	PROPN
brj-25043	4	20	,	,	PUNCT
brj-25043	4	21	a	a	DET
brj-25043	4	22	mahmoud	mahmoud	PROPN
brj-25043	4	23	m.	m.	PROPN
brj-25043	4	24	abdel	abdel	PROPN
brj-25043	4	25	-	-	PUNCT
brj-25043	4	26	daiem	daiem	PROPN
brj-25043	4	27	,	,	PUNCT
brj-25043	4	28	b	b	NOUN
brj-25043	4	29	,	,	PUNCT
brj-25043	4	30	c	c	NOUN
brj-25043	4	31	,	,	PUNCT
brj-25043	4	32	*	*	PUNCT
brj-25043	4	33	hani	hani	PROPN
brj-25043	4	34	s.	s.	PROPN
brj-25043	4	35	alharbi	alharbi	PROPN
brj-25043	4	36	,	,	PUNCT
brj-25043	4	37	c	c	PROPN
brj-25043	4	38	and	and	CCONJ
brj-25043	4	39	noha	noha	PROPN
brj-25043	4	40	said	say	VERB
brj-25043	4	41	,	,	PUNCT
brj-25043	4	42	b	b	NOUN
brj-25043	4	43	anaerobic	anaerobic	ADJ
brj-25043	4	44	digestion	digestion	NOUN
brj-25043	4	45	(	(	PUNCT
brj-25043	4	46	ad	ad	NOUN
brj-25043	4	47	)	)	PUNCT
brj-25043	4	48	is	be	AUX
brj-25043	4	49	a	a	DET
brj-25043	4	50	widely	widely	ADV
brj-25043	4	51	recognized	recognize	VERB
brj-25043	4	52	method	method	NOUN
brj-25043	4	53	for	for	ADP
brj-25043	4	54	converting	convert	VERB
brj-25043	4	55	organic	organic	ADJ
brj-25043	4	56	waste	waste	NOUN
brj-25043	4	57	into	into	ADP
brj-25043	4	58	biogas	biogas	NOUN
brj-25043	4	59	,	,	PUNCT
brj-25043	4	60	offering	offer	VERB
brj-25043	4	61	a	a	DET
brj-25043	4	62	sustainable	sustainable	ADJ
brj-25043	4	63	solution	solution	NOUN
brj-25043	4	64	for	for	ADP
brj-25043	4	65	both	both	CCONJ
brj-25043	4	66	waste	waste	NOUN
brj-25043	4	67	management	management	NOUN
brj-25043	4	68	and	and	CCONJ
brj-25043	4	69	renewable	renewable	ADJ
brj-25043	4	70	energy	energy	NOUN
brj-25043	4	71	generation	generation	NOUN
brj-25043	4	72	.	.	PUNCT
brj-25043	5	1	this	this	DET
brj-25043	5	2	review	review	NOUN
brj-25043	5	3	critically	critically	ADV
brj-25043	5	4	examines	examine	VERB
brj-25043	5	5	recent	recent	ADJ
brj-25043	5	6	advancements	advancement	NOUN
brj-25043	5	7	in	in	ADP
brj-25043	5	8	mathematical	mathematical	ADJ
brj-25043	5	9	modeling	modeling	NOUN
brj-25043	5	10	and	and	CCONJ
brj-25043	5	11	machine	machine	NOUN
brj-25043	5	12	learning	learning	NOUN
brj-25043	5	13	(	(	PUNCT
brj-25043	5	14	ml	ml	NOUN
brj-25043	5	15	)	)	PUNCT
brj-25043	5	16	approaches	approach	NOUN
brj-25043	5	17	applied	apply	VERB
brj-25043	5	18	to	to	ADP
brj-25043	5	19	biogas	biogas	NOUN
brj-25043	5	20	production	production	NOUN
brj-25043	5	21	from	from	ADP
brj-25043	5	22	ad	ad	NOUN
brj-25043	5	23	processes	process	NOUN
brj-25043	5	24	.	.	PUNCT
brj-25043	6	1	the	the	DET
brj-25043	6	2	study	study	NOUN
brj-25043	6	3	categorizes	categorize	VERB
brj-25043	6	4	the	the	DET
brj-25043	6	5	models	model	NOUN
brj-25043	6	6	into	into	ADP
brj-25043	6	7	daily	daily	ADJ
brj-25043	6	8	and	and	CCONJ
brj-25043	6	9	cumulative	cumulative	ADJ
brj-25043	6	10	biogas	biogas	NOUN
brj-25043	6	11	production	production	NOUN
brj-25043	6	12	models	model	NOUN
brj-25043	6	13	,	,	PUNCT
brj-25043	6	14	kinetic	kinetic	NOUN
brj-25043	6	15	models	model	NOUN
brj-25043	6	16	,	,	PUNCT
brj-25043	6	17	and	and	CCONJ
brj-25043	6	18	hybrid	hybrid	ADJ
brj-25043	6	19	ai	ai	NOUN
brj-25043	6	20	-	-	PUNCT
brj-25043	6	21	based	base	VERB
brj-25043	6	22	predictive	predictive	ADJ
brj-25043	6	23	techniques	technique	NOUN
brj-25043	6	24	.	.	PUNCT
brj-25043	7	1	special	special	ADJ
brj-25043	7	2	attention	attention	NOUN
brj-25043	7	3	is	be	AUX
brj-25043	7	4	given	give	VERB
brj-25043	7	5	to	to	ADP
brj-25043	7	6	the	the	DET
brj-25043	7	7	comparative	comparative	ADJ
brj-25043	7	8	evaluation	evaluation	NOUN
brj-25043	7	9	of	of	ADP
brj-25043	7	10	first	first	ADJ
brj-25043	7	11	-	-	PUNCT
brj-25043	7	12	order	order	NOUN
brj-25043	7	13	kinetics	kinetic	NOUN
brj-25043	7	14	,	,	PUNCT
brj-25043	7	15	modified	modified	ADJ
brj-25043	7	16	gompertz	gompertz	NOUN
brj-25043	7	17	,	,	PUNCT
brj-25043	7	18	and	and	CCONJ
brj-25043	7	19	chen	chen	PROPN
brj-25043	7	20	-	-	PUNCT
brj-25043	7	21	hashimoto	hashimoto	NOUN
brj-25043	7	22	models	model	NOUN
brj-25043	7	23	,	,	PUNCT
brj-25043	7	24	highlighting	highlight	VERB
brj-25043	7	25	their	their	PRON
brj-25043	7	26	applicability	applicability	NOUN
brj-25043	7	27	and	and	CCONJ
brj-25043	7	28	limitations	limitation	NOUN
brj-25043	7	29	.	.	PUNCT
brj-25043	8	1	furthermore	furthermore	ADV
brj-25043	8	2	,	,	PUNCT
brj-25043	8	3	the	the	DET
brj-25043	8	4	integration	integration	NOUN
brj-25043	8	5	of	of	ADP
brj-25043	8	6	artificial	artificial	ADJ
brj-25043	8	7	neural	neural	ADJ
brj-25043	8	8	networks	network	NOUN
brj-25043	8	9	(	(	PUNCT
brj-25043	8	10	anns	anns	NOUN
brj-25043	8	11	)	)	PUNCT
brj-25043	8	12	and	and	CCONJ
brj-25043	8	13	other	other	ADJ
brj-25043	8	14	ml	ml	NOUN
brj-25043	8	15	algorithms	algorithm	NOUN
brj-25043	8	16	is	be	AUX
brj-25043	8	17	discussed	discuss	VERB
brj-25043	8	18	in	in	ADP
brj-25043	8	19	the	the	DET
brj-25043	8	20	context	context	NOUN
brj-25043	8	21	of	of	ADP
brj-25043	8	22	optimizing	optimize	VERB
brj-25043	8	23	biogas	biogas	NOUN
brj-25043	8	24	yield	yield	NOUN
brj-25043	8	25	,	,	PUNCT
brj-25043	8	26	understanding	understand	VERB
brj-25043	8	27	system	system	NOUN
brj-25043	8	28	dynamics	dynamic	NOUN
brj-25043	8	29	,	,	PUNCT
brj-25043	8	30	and	and	CCONJ
brj-25043	8	31	reducing	reduce	VERB
brj-25043	8	32	operational	operational	ADJ
brj-25043	8	33	uncertainties	uncertainty	NOUN
brj-25043	8	34	.	.	PUNCT
brj-25043	9	1	research	research	NOUN
brj-25043	9	2	gaps	gap	NOUN
brj-25043	9	3	are	be	AUX
brj-25043	9	4	identified	identify	VERB
brj-25043	9	5	,	,	PUNCT
brj-25043	9	6	including	include	VERB
brj-25043	9	7	the	the	DET
brj-25043	9	8	need	need	NOUN
brj-25043	9	9	for	for	ADP
brj-25043	9	10	more	more	ADV
brj-25043	9	11	robust	robust	ADJ
brj-25043	9	12	hybrid	hybrid	ADJ
brj-25043	9	13	models	model	NOUN
brj-25043	9	14	,	,	PUNCT
brj-25043	9	15	real	real	ADJ
brj-25043	9	16	-	-	PUNCT
brj-25043	9	17	time	time	NOUN
brj-25043	9	18	monitoring	monitoring	NOUN
brj-25043	9	19	systems	system	NOUN
brj-25043	9	20	,	,	PUNCT
brj-25043	9	21	and	and	CCONJ
brj-25043	9	22	studies	study	NOUN
brj-25043	9	23	under	under	ADP
brj-25043	9	24	diverse	diverse	ADJ
brj-25043	9	25	feedstock	feedstock	NOUN
brj-25043	9	26	and	and	CCONJ
brj-25043	9	27	environmental	environmental	ADJ
brj-25043	9	28	conditions	condition	NOUN
brj-25043	9	29	.	.	PUNCT
brj-25043	10	1	the	the	DET
brj-25043	10	2	review	review	NOUN
brj-25043	10	3	emphasizes	emphasize	VERB
brj-25043	10	4	that	that	SCONJ
brj-25043	10	5	combining	combine	VERB
brj-25043	10	6	traditional	traditional	ADJ
brj-25043	10	7	modeling	modeling	NOUN
brj-25043	10	8	with	with	ADP
brj-25043	10	9	intelligent	intelligent	ADJ
brj-25043	10	10	systems	system	NOUN
brj-25043	10	11	offers	offer	VERB
brj-25043	10	12	a	a	DET
brj-25043	10	13	powerful	powerful	ADJ
brj-25043	10	14	approach	approach	NOUN
brj-25043	10	15	to	to	ADP
brj-25043	10	16	enhancing	enhance	VERB
brj-25043	10	17	ad	ad	NOUN
brj-25043	10	18	performance	performance	NOUN
brj-25043	10	19	and	and	CCONJ
brj-25043	10	20	scaling	scale	VERB
brj-25043	10	21	sustainable	sustainable	ADJ
brj-25043	10	22	energy	energy	NOUN
brj-25043	10	23	solutions	solution	NOUN
brj-25043	10	24	.	.	PUNCT
brj-25043	11	1	doi	doi	NOUN
brj-25043	11	2	:	:	PUNCT
brj-25043	11	3	10.15376	10.15376	NUM
brj-25043	11	4	/	/	SYM
brj-25043	11	5	biores.20.4.galal	biores.20.4.galal	PROPN
brj-25043	11	6	keywords	keyword	NOUN
brj-25043	11	7	:	:	PUNCT
brj-25043	11	8	mathematical	mathematical	ADJ
brj-25043	11	9	modeling	modeling	NOUN
brj-25043	11	10	;	;	PUNCT
brj-25043	11	11	anaerobic	anaerobic	ADJ
brj-25043	11	12	digestion	digestion	NOUN
brj-25043	11	13	;	;	PUNCT
brj-25043	11	14	multi	multi	ADJ
brj-25043	11	15	-	-	ADJ
brj-25043	11	16	dimensional	dimensional	ADJ
brj-25043	11	17	models	model	NOUN
brj-25043	11	18	;	;	PUNCT
brj-25043	11	19	machine	machine	NOUN
brj-25043	11	20	learning	learning	NOUN
brj-25043	11	21	;	;	PUNCT
brj-25043	11	22	parameters	parameter	NOUN
brj-25043	11	23	uncertainty	uncertainty	NOUN
brj-25043	11	24	;	;	PUNCT
brj-25043	11	25	renewable	renewable	ADJ
brj-25043	11	26	energy	energy	NOUN
brj-25043	11	27	contact	contact	NOUN
brj-25043	11	28	information	information	NOUN
brj-25043	11	29	:	:	PUNCT
brj-25043	11	30	a	a	X
brj-25043	11	31	:	:	PUNCT
brj-25043	11	32	engineering	engineering	NOUN
brj-25043	11	33	mathematics	mathematics	PROPN
brj-25043	11	34	and	and	CCONJ
brj-25043	11	35	physics	physics	PROPN
brj-25043	11	36	department	department	PROPN
brj-25043	11	37	,	,	PUNCT
brj-25043	11	38	college	college	NOUN
brj-25043	11	39	of	of	ADP
brj-25043	11	40	engineering	engineering	PROPN
brj-25043	11	41	,	,	PUNCT
brj-25043	11	42	fayoum	fayoum	PROPN
brj-25043	11	43	university	university	PROPN
brj-25043	11	44	,	,	PUNCT
brj-25043	11	45	63514	63514	NUM
brj-25043	11	46	,	,	PUNCT
brj-25043	11	47	fayoum	fayoum	PROPN
brj-25043	11	48	,	,	PUNCT
brj-25043	11	49	egypt	egypt	PROPN
brj-25043	11	50	;	;	PUNCT
brj-25043	11	51	b	b	X
brj-25043	11	52	:	:	PUNCT
brj-25043	11	53	environmental	environmental	ADJ
brj-25043	11	54	engineering	engineering	PROPN
brj-25043	11	55	department	department	PROPN
brj-25043	11	56	,	,	PUNCT
brj-25043	11	57	faculty	faculty	NOUN
brj-25043	11	58	of	of	ADP
brj-25043	11	59	engineering	engineering	PROPN
brj-25043	11	60	,	,	PUNCT
brj-25043	11	61	zagazig	zagazig	PROPN
brj-25043	11	62	university	university	PROPN
brj-25043	11	63	,	,	PUNCT
brj-25043	11	64	44519	44519	NUM
brj-25043	11	65	,	,	PUNCT
brj-25043	11	66	zagazig	zagazig	PROPN
brj-25043	11	67	,	,	PUNCT
brj-25043	11	68	egypt	egypt	PROPN
brj-25043	11	69	;	;	PUNCT
brj-25043	11	70	c	c	X
brj-25043	11	71	:	:	PUNCT
brj-25043	11	72	civil	civil	ADJ
brj-25043	11	73	engineering	engineering	NOUN
brj-25043	11	74	department	department	PROPN
brj-25043	11	75	,	,	PUNCT
brj-25043	11	76	college	college	NOUN
brj-25043	11	77	of	of	ADP
brj-25043	11	78	engineering	engineering	PROPN
brj-25043	11	79	,	,	PUNCT
brj-25043	11	80	shaqra	shaqra	PROPN
brj-25043	11	81	university	university	PROPN
brj-25043	11	82	,	,	PUNCT
brj-25043	11	83	11911	11911	NUM
brj-25043	11	84	,	,	PUNCT
brj-25043	11	85	duwadmi	duwadmi	NOUN
brj-25043	11	86	,	,	PUNCT
brj-25043	11	87	riyadh	riyadh	NOUN
brj-25043	11	88	,	,	PUNCT
brj-25043	11	89	saudi	saudi	PROPN
brj-25043	11	90	arabia	arabia	PROPN
brj-25043	11	91	;	;	PUNCT
brj-25043	11	92	*	*	PUNCT
brj-25043	11	93	corresponding	correspond	VERB
brj-25043	11	94	author	author	NOUN
brj-25043	11	95	:	:	PUNCT
brj-25043	11	96	mmabdeldaiem@eng.zu.edu.eg	mmabdeldaiem@eng.zu.edu.eg	NOUN
brj-25043	11	97	introduction	introduction	NOUN
brj-25043	11	98	anaerobic	anaerobic	NOUN
brj-25043	11	99	digestion	digestion	NOUN
brj-25043	11	100	(	(	PUNCT
brj-25043	11	101	ad	ad	NOUN
brj-25043	11	102	)	)	PUNCT
brj-25043	11	103	converts	convert	VERB
brj-25043	11	104	organic	organic	ADJ
brj-25043	11	105	waste	waste	NOUN
brj-25043	11	106	into	into	ADP
brj-25043	11	107	biogas	biogas	NOUN
brj-25043	11	108	(	(	PUNCT
brj-25043	11	109	primarily	primarily	ADV
brj-25043	11	110	ch₄	ch₄	PROPN
brj-25043	11	111	and	and	CCONJ
brj-25043	11	112	co₂	co₂	NOUN
brj-25043	11	113	)	)	PUNCT
brj-25043	11	114	,	,	PUNCT
brj-25043	11	115	delivering	deliver	VERB
brj-25043	11	116	simultaneous	simultaneous	ADJ
brj-25043	11	117	sanitation	sanitation	NOUN
brj-25043	11	118	and	and	CCONJ
brj-25043	11	119	energy	energy	NOUN
brj-25043	11	120	recovery	recovery	NOUN
brj-25043	11	121	,	,	PUNCT
brj-25043	11	122	and	and	CCONJ
brj-25043	11	123	aligning	align	VERB
brj-25043	11	124	with	with	ADP
brj-25043	11	125	circular	circular	ADJ
brj-25043	11	126	economy	economy	NOUN
brj-25043	11	127	goals	goal	NOUN
brj-25043	11	128	(	(	PUNCT
brj-25043	11	129	jameel	jameel	X
brj-25043	11	130	et	et	PROPN
brj-25043	11	131	al	al	PROPN
brj-25043	11	132	.	.	PROPN
brj-25043	11	133	2024	2024	NUM
brj-25043	11	134	;	;	PUNCT
brj-25043	11	135	alengebawy	alengebawy	PROPN
brj-25043	11	136	et	et	PROPN
brj-25043	11	137	al	al	PROPN
brj-25043	11	138	.	.	PROPN
brj-25043	11	139	2024	2024	NUM
brj-25043	11	140	)	)	PUNCT
brj-25043	11	141	.	.	PUNCT
brj-25043	12	1	across	across	ADP
brj-25043	12	2	common	common	ADJ
brj-25043	12	3	feedstocks	feedstock	NOUN
brj-25043	12	4	,	,	PUNCT
brj-25043	12	5	including	include	VERB
brj-25043	12	6	sewage	sewage	NOUN
brj-25043	12	7	sludge	sludge	NOUN
brj-25043	12	8	,	,	PUNCT
brj-25043	12	9	agricultural	agricultural	ADJ
brj-25043	12	10	residues	residue	NOUN
brj-25043	12	11	,	,	PUNCT
brj-25043	12	12	food	food	NOUN
brj-25043	12	13	waste	waste	NOUN
brj-25043	12	14	,	,	PUNCT
brj-25043	12	15	and	and	CCONJ
brj-25043	12	16	manure	manure	NOUN
brj-25043	12	17	co	co	NOUN
brj-25043	12	18	-	-	NOUN
brj-25043	12	19	digestion	digestion	NOUN
brj-25043	12	20	,	,	PUNCT
brj-25043	12	21	as	as	ADV
brj-25043	12	22	well	well	ADV
brj-25043	12	23	as	as	ADP
brj-25043	12	24	process	process	NOUN
brj-25043	12	25	tuning	tuning	NOUN
brj-25043	12	26	(	(	PUNCT
brj-25043	12	27	temperature	temperature	NOUN
brj-25043	12	28	,	,	PUNCT
brj-25043	12	29	ph	ph	ADJ
brj-25043	12	30	,	,	PUNCT
brj-25043	12	31	organic	organic	ADJ
brj-25043	12	32	loading	loading	NOUN
brj-25043	12	33	rate	rate	NOUN
brj-25043	12	34	(	(	PUNCT
brj-25043	12	35	olr	olr	NOUN
brj-25043	12	36	)	)	PUNCT
brj-25043	12	37	,	,	PUNCT
brj-25043	12	38	hydraulic	hydraulic	ADJ
brj-25043	12	39	retention	retention	NOUN
brj-25043	12	40	time	time	NOUN
brj-25043	12	41	(	(	PUNCT
brj-25043	12	42	hrt	hrt	PROPN
brj-25043	12	43	)	)	PUNCT
brj-25043	12	44	)	)	PUNCT
brj-25043	12	45	,	,	PUNCT
brj-25043	12	46	it	it	PRON
brj-25043	12	47	is	be	AUX
brj-25043	12	48	possible	possible	ADJ
brj-25043	12	49	to	to	PART
brj-25043	12	50	enhance	enhance	VERB
brj-25043	12	51	yields	yield	NOUN
brj-25043	12	52	and	and	CCONJ
brj-25043	12	53	stability	stability	NOUN
brj-25043	12	54	when	when	SCONJ
brj-25043	12	55	the	the	DET
brj-25043	12	56	system	system	NOUN
brj-25043	12	57	is	be	AUX
brj-25043	12	58	properly	properly	ADV
brj-25043	12	59	managed	manage	VERB
brj-25043	12	60	(	(	PUNCT
brj-25043	12	61	adnane	adnane	PROPN
brj-25043	12	62	et	et	PROPN
brj-25043	12	63	al	al	PROPN
brj-25043	12	64	.	.	PROPN
brj-25043	12	65	2024	2024	NUM
brj-25043	12	66	;	;	PUNCT
brj-25043	12	67	liu	liu	PROPN
brj-25043	12	68	et	et	PROPN
brj-25043	12	69	al	al	PROPN
brj-25043	12	70	.	.	PROPN
brj-25043	12	71	2025	2025	NUM
brj-25043	12	72	)	)	PUNCT
brj-25043	12	73	.	.	PUNCT
brj-25043	13	1	mathematical	mathematical	ADJ
brj-25043	13	2	modeling	modeling	NOUN
brj-25043	13	3	has	have	AUX
brj-25043	13	4	emerged	emerge	VERB
brj-25043	13	5	as	as	ADP
brj-25043	13	6	a	a	DET
brj-25043	13	7	critical	critical	ADJ
brj-25043	13	8	tool	tool	NOUN
brj-25043	13	9	in	in	ADP
brj-25043	13	10	understanding	understanding	NOUN
brj-25043	13	11	,	,	PUNCT
brj-25043	13	12	simulating	simulate	VERB
brj-25043	13	13	,	,	PUNCT
brj-25043	13	14	and	and	CCONJ
brj-25043	13	15	scaling	scale	VERB
brj-25043	13	16	up	up	ADP
brj-25043	13	17	ad	ad	NOUN
brj-25043	13	18	processes	process	NOUN
brj-25043	13	19	across	across	ADP
brj-25043	13	20	various	various	ADJ
brj-25043	13	21	substrates	substrate	NOUN
brj-25043	13	22	,	,	PUNCT
brj-25043	13	23	including	include	VERB
brj-25043	13	24	sewage	sewage	NOUN
brj-25043	13	25	sludge	sludge	NOUN
brj-25043	13	26	,	,	PUNCT
brj-25043	13	27	agricultural	agricultural	ADJ
brj-25043	13	28	residues	residue	NOUN
brj-25043	13	29	,	,	PUNCT
brj-25043	13	30	and	and	CCONJ
brj-25043	13	31	municipal	municipal	ADJ
brj-25043	13	32	solid	solid	ADJ
brj-25043	13	33	waste	waste	NOUN
brj-25043	13	34	(	(	PUNCT
brj-25043	13	35	abdel	abdel	PROPN
brj-25043	13	36	daiem	daiem	PROPN
brj-25043	13	37	et	et	PROPN
brj-25043	13	38	al	al	PROPN
brj-25043	13	39	.	.	PROPN
brj-25043	13	40	2021	2021	NUM
brj-25043	13	41	)	)	PUNCT
brj-25043	13	42	.	.	PUNCT
brj-25043	14	1	recent	recent	ADJ
brj-25043	14	2	advancements	advancement	NOUN
brj-25043	14	3	in	in	ADP
brj-25043	14	4	kinetic	kinetic	ADJ
brj-25043	14	5	and	and	CCONJ
brj-25043	14	6	mechanistic	mechanistic	ADJ
brj-25043	14	7	modeling	modeling	NOUN
brj-25043	14	8	https://orcid.org/0000-0001-7774-9632	https://orcid.org/0000-0001-7774-9632	PROPN
brj-25043	14	9	https://orcid.org/0000-0002-5023-9963	https://orcid.org/0000-0002-5023-9963	PROPN
brj-25043	14	10	peer	peer	NOUN
brj-25043	14	11	-	-	PUNCT
brj-25043	14	12	reviewed	review	VERB
brj-25043	14	13	review	review	NOUN
brj-25043	14	14	article	article	NOUN
brj-25043	14	15	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	14	16	galal	galal	PROPN
brj-25043	14	17	et	et	PROPN
brj-25043	14	18	al	al	PROPN
brj-25043	14	19	.	.	PROPN
brj-25043	15	1	(	(	PUNCT
brj-25043	15	2	2025	2025	NUM
brj-25043	15	3	)	)	PUNCT
brj-25043	15	4	.	.	PUNCT
brj-25043	16	1	“	"	PUNCT
brj-25043	16	2	math	math	NOUN
brj-25043	16	3	modeling	modeling	NOUN
brj-25043	16	4	biogas	biogas	NOUN
brj-25043	16	5	production	production	NOUN
brj-25043	16	6	,	,	PUNCT
brj-25043	16	7	”	"	PUNCT
brj-25043	16	8	bioresources	bioresource	NOUN
brj-25043	16	9	20(4	20(4	NOUN
brj-25043	16	10	)	)	PUNCT
brj-25043	16	11	,	,	PUNCT
brj-25043	16	12	11237	11237	NUM
brj-25043	16	13	-	-	SYM
brj-25043	16	14	11266	11266	NUM
brj-25043	16	15	.	.	PUNCT
brj-25043	17	1	11238	11238	NUM
brj-25043	17	2	approaches	approach	NOUN
brj-25043	17	3	have	have	AUX
brj-25043	17	4	significantly	significantly	ADV
brj-25043	17	5	improved	improve	VERB
brj-25043	17	6	the	the	DET
brj-25043	17	7	predictive	predictive	ADJ
brj-25043	17	8	accuracy	accuracy	NOUN
brj-25043	17	9	and	and	CCONJ
brj-25043	17	10	control	control	NOUN
brj-25043	17	11	of	of	ADP
brj-25043	17	12	ad	ad	NOUN
brj-25043	17	13	systems	system	NOUN
brj-25043	17	14	(	(	PUNCT
brj-25043	17	15	see	see	VERB
brj-25043	17	16	table	table	NOUN
brj-25043	17	17	1	1	NUM
brj-25043	17	18	)	)	PUNCT
brj-25043	17	19	.	.	PUNCT
brj-25043	18	1	unlike	unlike	ADP
brj-25043	18	2	mathematical	mathematical	ADJ
brj-25043	18	3	models	model	NOUN
brj-25043	18	4	,	,	PUNCT
brj-25043	18	5	machine	machine	NOUN
brj-25043	18	6	learning	learning	NOUN
brj-25043	18	7	(	(	PUNCT
brj-25043	18	8	ml	ml	NOUN
brj-25043	18	9	)	)	PUNCT
brj-25043	18	10	learns	learn	VERB
brj-25043	18	11	patterns	pattern	NOUN
brj-25043	18	12	from	from	ADP
brj-25043	18	13	data	datum	NOUN
brj-25043	18	14	,	,	PUNCT
brj-25043	18	15	enabling	enable	VERB
brj-25043	18	16	flexible	flexible	ADJ
brj-25043	18	17	prediction	prediction	NOUN
brj-25043	18	18	and	and	CCONJ
brj-25043	18	19	optimization	optimization	NOUN
brj-25043	18	20	of	of	ADP
brj-25043	18	21	biogas	biogas	NOUN
brj-25043	18	22	production	production	NOUN
brj-25043	18	23	.	.	PUNCT
brj-25043	19	1	in	in	ADP
brj-25043	19	2	recent	recent	ADJ
brj-25043	19	3	years	year	NOUN
brj-25043	19	4	,	,	PUNCT
brj-25043	19	5	the	the	DET
brj-25043	19	6	application	application	NOUN
brj-25043	19	7	of	of	ADP
brj-25043	19	8	ml	ml	NOUN
brj-25043	19	9	in	in	ADP
brj-25043	19	10	renewable	renewable	ADJ
brj-25043	19	11	energy	energy	NOUN
brj-25043	19	12	has	have	AUX
brj-25043	19	13	gained	gain	VERB
brj-25043	19	14	significant	significant	ADJ
brj-25043	19	15	traction	traction	NOUN
brj-25043	19	16	,	,	PUNCT
brj-25043	19	17	particularly	particularly	ADV
brj-25043	19	18	in	in	ADP
brj-25043	19	19	modelling	model	VERB
brj-25043	19	20	complex	complex	ADJ
brj-25043	19	21	biological	biological	ADJ
brj-25043	19	22	processes	process	NOUN
brj-25043	19	23	such	such	ADJ
brj-25043	19	24	as	as	ADP
brj-25043	19	25	ad	ad	NOUN
brj-25043	19	26	for	for	ADP
brj-25043	19	27	biogas	biogas	NOUN
brj-25043	19	28	production	production	NOUN
brj-25043	19	29	(	(	PUNCT
brj-25043	19	30	najafi	najafi	NOUN
brj-25043	19	31	and	and	CCONJ
brj-25043	19	32	ardabili	ardabili	PROPN
brj-25043	19	33	2018	2018	NUM
brj-25043	19	34	;	;	PUNCT
brj-25043	19	35	beltramo	beltramo	PROPN
brj-25043	19	36	et	et	PROPN
brj-25043	19	37	al	al	PROPN
brj-25043	19	38	.	.	PROPN
brj-25043	19	39	2019	2019	NUM
brj-25043	19	40	;	;	PUNCT
brj-25043	19	41	abdel	abdel	PROPN
brj-25043	19	42	daiem	daiem	PROPN
brj-25043	19	43	et	et	PROPN
brj-25043	19	44	al	al	PROPN
brj-25043	19	45	.	.	PROPN
brj-25043	19	46	2021	2021	NUM
brj-25043	19	47	;	;	PUNCT
brj-25043	19	48	cruz	cruz	PROPN
brj-25043	19	49	et	et	PROPN
brj-25043	19	50	al	al	PROPN
brj-25043	19	51	.	.	PROPN
brj-25043	19	52	2023	2023	NUM
brj-25043	19	53	;	;	PUNCT
brj-25043	19	54	komarysta	komarysta	PROPN
brj-25043	19	55	et	et	PROPN
brj-25043	19	56	al	al	PROPN
brj-25043	19	57	.	.	PROPN
brj-25043	19	58	2023	2023	NUM
brj-25043	19	59	;	;	PUNCT
brj-25043	19	60	shindell	shindell	VERB
brj-25043	19	61	et	et	PROPN
brj-25043	19	62	al	al	PROPN
brj-25043	19	63	.	.	PROPN
brj-25043	19	64	2024	2024	NUM
brj-25043	19	65	;	;	PUNCT
brj-25043	19	66	zhu	zhu	PROPN
brj-25043	19	67	et	et	PROPN
brj-25043	19	68	al	al	PROPN
brj-25043	19	69	.	.	PROPN
brj-25043	19	70	2025	2025	NUM
brj-25043	19	71	)	)	PUNCT
brj-25043	19	72	.	.	PUNCT
brj-25043	20	1	the	the	DET
brj-25043	20	2	nonlinear	nonlinear	ADJ
brj-25043	20	3	and	and	CCONJ
brj-25043	20	4	dynamic	dynamic	ADJ
brj-25043	20	5	nature	nature	NOUN
brj-25043	20	6	of	of	ADP
brj-25043	20	7	biogas	biogas	NOUN
brj-25043	20	8	production	production	NOUN
brj-25043	20	9	processes	process	NOUN
brj-25043	20	10	makes	make	VERB
brj-25043	20	11	conventional	conventional	ADJ
brj-25043	20	12	modelling	modelling	NOUN
brj-25043	20	13	approaches	approach	VERB
brj-25043	20	14	less	less	ADV
brj-25043	20	15	effective	effective	ADJ
brj-25043	20	16	.	.	PUNCT
brj-25043	21	1	in	in	ADP
brj-25043	21	2	contrast	contrast	NOUN
brj-25043	21	3	,	,	PUNCT
brj-25043	21	4	artificial	artificial	ADJ
brj-25043	21	5	neural	neural	ADJ
brj-25043	21	6	networks	network	NOUN
brj-25043	21	7	(	(	PUNCT
brj-25043	21	8	anns	anns	PROPN
brj-25043	21	9	)	)	PUNCT
brj-25043	21	10	offer	offer	VERB
brj-25043	21	11	high	high	ADJ
brj-25043	21	12	adaptability	adaptability	NOUN
brj-25043	21	13	,	,	PUNCT
brj-25043	21	14	pattern	pattern	NOUN
brj-25043	21	15	recognition	recognition	NOUN
brj-25043	21	16	,	,	PUNCT
brj-25043	21	17	and	and	CCONJ
brj-25043	21	18	learning	learn	VERB
brj-25043	21	19	capabilities	capability	NOUN
brj-25043	21	20	,	,	PUNCT
brj-25043	21	21	making	make	VERB
brj-25043	21	22	them	they	PRON
brj-25043	21	23	well	well	ADV
brj-25043	21	24	-	-	PUNCT
brj-25043	21	25	suited	suited	ADJ
brj-25043	21	26	for	for	ADP
brj-25043	21	27	predicting	predict	VERB
brj-25043	21	28	biogas	biogas	NOUN
brj-25043	21	29	yields	yield	NOUN
brj-25043	21	30	from	from	ADP
brj-25043	21	31	various	various	ADJ
brj-25043	21	32	organic	organic	ADJ
brj-25043	21	33	feedstocks	feedstock	NOUN
brj-25043	21	34	(	(	PUNCT
brj-25043	21	35	abdel	abdel	PROPN
brj-25043	21	36	daiem	daiem	PROPN
brj-25043	21	37	et	et	PROPN
brj-25043	21	38	al	al	PROPN
brj-25043	21	39	.	.	PROPN
brj-25043	21	40	2021	2021	NUM
brj-25043	21	41	)	)	PUNCT
brj-25043	21	42	.	.	PUNCT
brj-25043	22	1	this	this	PRON
brj-25043	22	2	is	be	AUX
brj-25043	22	3	especially	especially	ADV
brj-25043	22	4	relevant	relevant	ADJ
brj-25043	22	5	in	in	ADP
brj-25043	22	6	the	the	DET
brj-25043	22	7	context	context	NOUN
brj-25043	22	8	of	of	ADP
brj-25043	22	9	sewage	sewage	NOUN
brj-25043	22	10	sludge	sludge	NOUN
brj-25043	22	11	and	and	CCONJ
brj-25043	22	12	biomass	biomass	NOUN
brj-25043	22	13	residues	residue	NOUN
brj-25043	22	14	,	,	PUNCT
brj-25043	22	15	which	which	PRON
brj-25043	22	16	vary	vary	VERB
brj-25043	22	17	in	in	ADP
brj-25043	22	18	composition	composition	NOUN
brj-25043	22	19	and	and	CCONJ
brj-25043	22	20	behaviour	behaviour	NOUN
brj-25043	22	21	during	during	ADP
brj-25043	22	22	digestion	digestion	NOUN
brj-25043	22	23	.	.	PUNCT
brj-25043	23	1	the	the	DET
brj-25043	23	2	integration	integration	NOUN
brj-25043	23	3	of	of	ADP
brj-25043	23	4	ann	ann	PROPN
brj-25043	23	5	into	into	ADP
brj-25043	23	6	biogas	biogas	NOUN
brj-25043	23	7	research	research	NOUN
brj-25043	23	8	represents	represent	VERB
brj-25043	23	9	a	a	DET
brj-25043	23	10	promising	promising	ADJ
brj-25043	23	11	direction	direction	NOUN
brj-25043	23	12	for	for	ADP
brj-25043	23	13	optimizing	optimize	VERB
brj-25043	23	14	system	system	NOUN
brj-25043	23	15	performance	performance	NOUN
brj-25043	23	16	and	and	CCONJ
brj-25043	23	17	enhancing	enhance	VERB
brj-25043	23	18	energy	energy	NOUN
brj-25043	23	19	recovery	recovery	NOUN
brj-25043	23	20	,	,	PUNCT
brj-25043	23	21	aligning	align	VERB
brj-25043	23	22	with	with	ADP
brj-25043	23	23	global	global	ADJ
brj-25043	23	24	sustainability	sustainability	NOUN
brj-25043	23	25	and	and	CCONJ
brj-25043	23	26	waste	waste	NOUN
brj-25043	23	27	-	-	PUNCT
brj-25043	23	28	to	to	ADP
brj-25043	23	29	-	-	PUNCT
brj-25043	23	30	energy	energy	NOUN
brj-25043	23	31	initiatives	initiative	NOUN
brj-25043	23	32	.	.	PUNCT
brj-25043	24	1	the	the	DET
brj-25043	24	2	ml	ml	PROPN
brj-25043	24	3	techniques	technique	NOUN
brj-25043	24	4	have	have	AUX
brj-25043	24	5	become	become	VERB
brj-25043	24	6	promising	promise	VERB
brj-25043	24	7	alternatives	alternative	NOUN
brj-25043	24	8	and	and	CCONJ
brj-25043	24	9	complement	complement	VERB
brj-25043	24	10	the	the	DET
brj-25043	24	11	traditional	traditional	ADJ
brj-25043	24	12	mathematical	mathematical	ADJ
brj-25043	24	13	models	model	NOUN
brj-25043	24	14	discussed	discuss	VERB
brj-25043	24	15	in	in	ADP
brj-25043	24	16	this	this	DET
brj-25043	24	17	paper	paper	NOUN
brj-25043	24	18	,	,	PUNCT
brj-25043	24	19	especially	especially	ADV
brj-25043	24	20	for	for	ADP
brj-25043	24	21	dealing	deal	VERB
brj-25043	24	22	with	with	ADP
brj-25043	24	23	ad	ad	NOUN
brj-25043	24	24	processes	process	NOUN
brj-25043	24	25	’	'	PUNCT
brj-25043	24	26	non	non	ADJ
brj-25043	24	27	-	-	ADJ
brj-25043	24	28	linear	linear	ADJ
brj-25043	24	29	,	,	PUNCT
brj-25043	24	30	dynamic	dynamic	ADJ
brj-25043	24	31	,	,	PUNCT
brj-25043	24	32	and	and	CCONJ
brj-25043	24	33	uncertain	uncertain	ADJ
brj-25043	24	34	characteristics	characteristic	NOUN
brj-25043	24	35	.	.	PUNCT
brj-25043	25	1	unlike	unlike	ADP
brj-25043	25	2	deterministic	deterministic	ADJ
brj-25043	25	3	models	model	NOUN
brj-25043	25	4	,	,	PUNCT
brj-25043	25	5	such	such	ADJ
brj-25043	25	6	as	as	ADP
brj-25043	25	7	the	the	DET
brj-25043	25	8	modified	modified	ADJ
brj-25043	25	9	gompertz	gompertz	NOUN
brj-25043	25	10	or	or	CCONJ
brj-25043	25	11	logistic	logistic	ADJ
brj-25043	25	12	equations	equation	NOUN
brj-25043	25	13	,	,	PUNCT
brj-25043	25	14	which	which	PRON
brj-25043	25	15	depend	depend	VERB
brj-25043	25	16	on	on	ADP
brj-25043	25	17	specific	specific	ADJ
brj-25043	25	18	kinetic	kinetic	ADJ
brj-25043	25	19	assumptions	assumption	NOUN
brj-25043	25	20	and	and	CCONJ
brj-25043	25	21	can	can	AUX
brj-25043	25	22	have	have	VERB
brj-25043	25	23	difficulty	difficulty	NOUN
brj-25043	25	24	handling	handle	VERB
brj-25043	25	25	variable	variable	ADJ
brj-25043	25	26	feedstocks	feedstock	NOUN
brj-25043	25	27	or	or	CCONJ
brj-25043	25	28	operational	operational	ADJ
brj-25043	25	29	conditions	condition	NOUN
brj-25043	25	30	(	(	PUNCT
brj-25043	25	31	roberts	roberts	PROPN
brj-25043	25	32	et	et	PROPN
brj-25043	25	33	al	al	PROPN
brj-25043	25	34	.	.	PROPN
brj-25043	25	35	2023	2023	NUM
brj-25043	25	36	;	;	PUNCT
brj-25043	25	37	ling	le	VERB
brj-25043	25	38	et	et	PROPN
brj-25043	25	39	al	al	PROPN
brj-25043	25	40	.	.	PROPN
brj-25043	25	41	2024	2024	NUM
brj-25043	25	42	)	)	PUNCT
brj-25043	25	43	,	,	PUNCT
brj-25043	25	44	ml	ml	ADP
brj-25043	25	45	methods	method	NOUN
brj-25043	25	46	are	be	AUX
brj-25043	25	47	data	data	NOUN
brj-25043	25	48	-	-	PUNCT
brj-25043	25	49	driven	drive	VERB
brj-25043	25	50	and	and	CCONJ
brj-25043	25	51	capable	capable	ADJ
brj-25043	25	52	of	of	ADP
brj-25043	25	53	capturing	capture	VERB
brj-25043	25	54	complex	complex	ADJ
brj-25043	25	55	patterns	pattern	NOUN
brj-25043	25	56	from	from	ADP
brj-25043	25	57	high	high	ADJ
brj-25043	25	58	-	-	PUNCT
brj-25043	25	59	dimensional	dimensional	ADJ
brj-25043	25	60	inputs	input	NOUN
brj-25043	25	61	without	without	ADP
brj-25043	25	62	predefined	predefine	VERB
brj-25043	25	63	mechanisms	mechanism	NOUN
brj-25043	25	64	(	(	PUNCT
brj-25043	25	65	ling	ling	NOUN
brj-25043	25	66	et	et	PROPN
brj-25043	25	67	al	al	PROPN
brj-25043	25	68	.	.	PROPN
brj-25043	25	69	2024	2024	NUM
brj-25043	25	70	)	)	PUNCT
brj-25043	25	71	.	.	PUNCT
brj-25043	26	1	this	this	PRON
brj-25043	26	2	makes	make	VERB
brj-25043	26	3	them	they	PRON
brj-25043	26	4	suitable	suitable	ADJ
brj-25043	26	5	for	for	ADP
brj-25043	26	6	predicting	predict	VERB
brj-25043	26	7	biogas	biogas	NOUN
brj-25043	26	8	yields	yield	NOUN
brj-25043	26	9	,	,	PUNCT
brj-25043	26	10	optimizing	optimize	VERB
brj-25043	26	11	codigestion	codigestion	NOUN
brj-25043	26	12	ratios	ratio	NOUN
brj-25043	26	13	,	,	PUNCT
brj-25043	26	14	estimating	estimate	VERB
brj-25043	26	15	uncertain	uncertain	ADJ
brj-25043	26	16	parameters	parameter	NOUN
brj-25043	26	17	,	,	PUNCT
brj-25043	26	18	and	and	CCONJ
brj-25043	26	19	supporting	support	VERB
brj-25043	26	20	monitoring	monitoring	NOUN
brj-25043	26	21	of	of	ADP
brj-25043	26	22	real	real	ADJ
brj-25043	26	23	-	-	PUNCT
brj-25043	26	24	time	time	NOUN
brj-25043	26	25	(	(	PUNCT
brj-25043	26	26	models	model	NOUN
brj-25043	26	27	that	that	PRON
brj-25043	26	28	continuously	continuously	ADV
brj-25043	26	29	update	update	VERB
brj-25043	26	30	predictions	prediction	NOUN
brj-25043	26	31	and	and	CCONJ
brj-25043	26	32	provide	provide	VERB
brj-25043	26	33	actionable	actionable	ADJ
brj-25043	26	34	outputs	output	NOUN
brj-25043	26	35	during	during	ADP
brj-25043	26	36	ongoing	ongoing	ADJ
brj-25043	26	37	ad	ad	NOUN
brj-25043	26	38	plant	plant	NOUN
brj-25043	26	39	operation	operation	NOUN
brj-25043	26	40	using	use	VERB
brj-25043	26	41	live	live	ADJ
brj-25043	26	42	scada	scada	PROPN
brj-25043	26	43	data	data	PROPN
brj-25043	26	44	streams	stream	NOUN
brj-25043	26	45	)	)	PUNCT
brj-25043	26	46	in	in	ADP
brj-25043	26	47	multi	multi	ADJ
brj-25043	26	48	-	-	ADJ
brj-25043	26	49	dimensional	dimensional	ADJ
brj-25043	26	50	ad	ad	NOUN
brj-25043	26	51	systems	system	NOUN
brj-25043	26	52	(	(	PUNCT
brj-25043	26	53	asadi	asadi	NOUN
brj-25043	26	54	and	and	CCONJ
brj-25043	26	55	mcphedran	mcphedran	ADJ
brj-25043	26	56	2021	2021	NUM
brj-25043	26	57	)	)	PUNCT
brj-25043	26	58	.	.	PUNCT
brj-25043	27	1	recent	recent	ADJ
brj-25043	27	2	studies	study	NOUN
brj-25043	27	3	(	(	PUNCT
brj-25043	27	4	2019	2019	NUM
brj-25043	27	5	to	to	ADP
brj-25043	27	6	2025	2025	NUM
brj-25043	27	7	)	)	PUNCT
brj-25043	27	8	have	have	AUX
brj-25043	27	9	utilized	utilize	VERB
brj-25043	27	10	ml	ml	NOUN
brj-25043	27	11	algorithms	algorithm	NOUN
brj-25043	27	12	,	,	PUNCT
brj-25043	27	13	such	such	ADJ
brj-25043	27	14	as	as	ADP
brj-25043	27	15	anns	anns	NOUN
brj-25043	27	16	(	(	PUNCT
brj-25043	27	17	cruz	cruz	PROPN
brj-25043	27	18	et	et	PROPN
brj-25043	27	19	al	al	PROPN
brj-25043	27	20	.	.	PROPN
brj-25043	27	21	2023	2023	NUM
brj-25043	27	22	;	;	PUNCT
brj-25043	27	23	komarysta	komarysta	PROPN
brj-25043	27	24	et	et	PROPN
brj-25043	27	25	al	al	PROPN
brj-25043	27	26	.	.	PROPN
brj-25043	27	27	2023	2023	NUM
brj-25043	27	28	)	)	PUNCT
brj-25043	27	29	,	,	PUNCT
brj-25043	27	30	random	random	ADJ
brj-25043	27	31	forests	forest	NOUN
brj-25043	27	32	(	(	PUNCT
brj-25043	27	33	rf	rf	NOUN
brj-25043	27	34	)	)	PUNCT
brj-25043	27	35	,	,	PUNCT
brj-25043	27	36	support	support	VERB
brj-25043	27	37	vector	vector	NOUN
brj-25043	27	38	machines	machine	NOUN
brj-25043	27	39	(	(	PUNCT
brj-25043	27	40	svm	svm	PROPN
brj-25043	27	41	)	)	PUNCT
brj-25043	27	42	,	,	PUNCT
brj-25043	27	43	and	and	CCONJ
brj-25043	27	44	deep	deep	ADJ
brj-25043	27	45	learning	learning	NOUN
brj-25043	27	46	models	model	NOUN
brj-25043	27	47	(	(	PUNCT
brj-25043	27	48	lstm	lstm	NOUN
brj-25043	27	49	)	)	PUNCT
brj-25043	27	50	for	for	ADP
brj-25043	27	51	ad	ad	NOUN
brj-25043	27	52	,	,	PUNCT
brj-25043	27	53	often	often	ADV
brj-25043	27	54	comparing	compare	VERB
brj-25043	27	55	their	their	PRON
brj-25043	27	56	performance	performance	NOUN
brj-25043	27	57	favourably	favourably	ADV
brj-25043	27	58	to	to	ADP
brj-25043	27	59	traditional	traditional	ADJ
brj-25043	27	60	models	model	NOUN
brj-25043	27	61	(	(	PUNCT
brj-25043	27	62	yildirim	yildirim	NOUN
brj-25043	27	63	and	and	CCONJ
brj-25043	27	64	ozkaya	ozkaya	NOUN
brj-25043	27	65	2023	2023	NUM
brj-25043	27	66	)	)	PUNCT
brj-25043	27	67	.	.	PUNCT
brj-25043	28	1	these	these	DET
brj-25043	28	2	approaches	approach	NOUN
brj-25043	28	3	address	address	VERB
brj-25043	28	4	research	research	NOUN
brj-25043	28	5	gaps	gap	NOUN
brj-25043	28	6	,	,	PUNCT
brj-25043	28	7	such	such	ADJ
brj-25043	28	8	as	as	ADP
brj-25043	28	9	incorporating	incorporate	VERB
brj-25043	28	10	parameter	parameter	NOUN
brj-25043	28	11	uncertainty	uncertainty	NOUN
brj-25043	28	12	through	through	ADP
brj-25043	28	13	probabilistic	probabilistic	ADJ
brj-25043	28	14	predictions	prediction	NOUN
brj-25043	28	15	and	and	CCONJ
brj-25043	28	16	extending	extend	VERB
brj-25043	28	17	to	to	ADP
brj-25043	28	18	multi	multi	ADJ
brj-25043	28	19	-	-	ADJ
brj-25043	28	20	dimensional	dimensional	ADJ
brj-25043	28	21	inputs	input	NOUN
brj-25043	28	22	via	via	ADP
brj-25043	28	23	feature	feature	NOUN
brj-25043	28	24	engineering	engineering	NOUN
brj-25043	28	25	and	and	CCONJ
brj-25043	28	26	hybrid	hybrid	NOUN
brj-25043	28	27	models	model	NOUN
brj-25043	28	28	(	(	PUNCT
brj-25043	28	29	sappl	sappl	NOUN
brj-25043	28	30	et	et	PROPN
brj-25043	28	31	al	al	PROPN
brj-25043	28	32	.	.	PROPN
brj-25043	28	33	2023	2023	NUM
brj-25043	28	34	)	)	PUNCT
brj-25043	28	35	.	.	PUNCT
brj-25043	29	1	this	this	DET
brj-25043	29	2	review	review	NOUN
brj-25043	29	3	article	article	NOUN
brj-25043	29	4	presents	present	VERB
brj-25043	29	5	a	a	DET
brj-25043	29	6	novel	novel	NOUN
brj-25043	29	7	,	,	PUNCT
brj-25043	29	8	integrative	integrative	ADJ
brj-25043	29	9	synthesis	synthesis	NOUN
brj-25043	29	10	of	of	ADP
brj-25043	29	11	recent	recent	ADJ
brj-25043	29	12	advancements	advancement	NOUN
brj-25043	29	13	in	in	ADP
brj-25043	29	14	the	the	DET
brj-25043	29	15	modelling	modelling	NOUN
brj-25043	29	16	and	and	CCONJ
brj-25043	29	17	optimization	optimization	NOUN
brj-25043	29	18	of	of	ADP
brj-25043	29	19	ad	ad	NOUN
brj-25043	29	20	processes	process	NOUN
brj-25043	29	21	for	for	ADP
brj-25043	29	22	biogas	biogas	NOUN
brj-25043	29	23	production	production	NOUN
brj-25043	29	24	,	,	PUNCT
brj-25043	29	25	focusing	focus	VERB
brj-25043	29	26	on	on	ADP
brj-25043	29	27	the	the	DET
brj-25043	29	28	convergence	convergence	NOUN
brj-25043	29	29	of	of	ADP
brj-25043	29	30	mathematical	mathematical	ADJ
brj-25043	29	31	modelling	modelling	NOUN
brj-25043	29	32	and	and	CCONJ
brj-25043	29	33	ml	ml	NOUN
brj-25043	29	34	techniques	technique	NOUN
brj-25043	29	35	.	.	PUNCT
brj-25043	30	1	while	while	SCONJ
brj-25043	30	2	prior	prior	ADJ
brj-25043	30	3	reviews	review	NOUN
brj-25043	30	4	have	have	AUX
brj-25043	30	5	addressed	address	VERB
brj-25043	30	6	modelling	model	VERB
brj-25043	30	7	frameworks	framework	NOUN
brj-25043	30	8	in	in	ADP
brj-25043	30	9	isolation	isolation	NOUN
brj-25043	30	10	,	,	PUNCT
brj-25043	30	11	this	this	DET
brj-25043	30	12	work	work	NOUN
brj-25043	30	13	uniquely	uniquely	ADV
brj-25043	30	14	bridges	bridge	VERB
brj-25043	30	15	deterministic	deterministic	ADJ
brj-25043	30	16	kinetic	kinetic	NOUN
brj-25043	30	17	models	model	NOUN
brj-25043	30	18	with	with	ADP
brj-25043	30	19	data	data	NOUN
brj-25043	30	20	-	-	PUNCT
brj-25043	30	21	driven	drive	VERB
brj-25043	30	22	approaches	approach	NOUN
brj-25043	30	23	,	,	PUNCT
brj-25043	30	24	offering	offer	VERB
brj-25043	30	25	a	a	DET
brj-25043	30	26	comparative	comparative	ADJ
brj-25043	30	27	assessment	assessment	NOUN
brj-25043	30	28	of	of	ADP
brj-25043	30	29	their	their	PRON
brj-25043	30	30	capabilities	capability	NOUN
brj-25043	30	31	,	,	PUNCT
brj-25043	30	32	limitations	limitation	NOUN
brj-25043	30	33	,	,	PUNCT
brj-25043	30	34	and	and	CCONJ
brj-25043	30	35	future	future	ADJ
brj-25043	30	36	trajectories	trajectory	NOUN
brj-25043	30	37	.	.	PUNCT
brj-25043	31	1	thus	thus	ADV
brj-25043	31	2	,	,	PUNCT
brj-25043	31	3	the	the	DET
brj-25043	31	4	purpose	purpose	NOUN
brj-25043	31	5	of	of	ADP
brj-25043	31	6	this	this	DET
brj-25043	31	7	study	study	NOUN
brj-25043	31	8	is	be	AUX
brj-25043	31	9	to	to	PART
brj-25043	31	10	evaluate	evaluate	VERB
brj-25043	31	11	the	the	DET
brj-25043	31	12	predictive	predictive	ADJ
brj-25043	31	13	performance	performance	NOUN
brj-25043	31	14	of	of	ADP
brj-25043	31	15	widely	widely	ADV
brj-25043	31	16	used	use	VERB
brj-25043	31	17	mathematical	mathematical	ADJ
brj-25043	31	18	models	model	NOUN
brj-25043	31	19	,	,	PUNCT
brj-25043	31	20	such	such	ADJ
brj-25043	31	21	as	as	ADP
brj-25043	31	22	firstorder	firstorder	NOUN
brj-25043	31	23	kinetics	kinetic	NOUN
brj-25043	31	24	,	,	PUNCT
brj-25043	31	25	modified	modified	ADJ
brj-25043	31	26	gompertz	gompertz	NOUN
brj-25043	31	27	,	,	PUNCT
brj-25043	31	28	and	and	CCONJ
brj-25043	31	29	chen	chen	PROPN
brj-25043	31	30	–	–	PUNCT
brj-25043	31	31	hashimoto	hashimoto	NOUN
brj-25043	31	32	models	model	NOUN
brj-25043	31	33	,	,	PUNCT
brj-25043	31	34	alongside	alongside	ADP
brj-25043	31	35	ann	ann	PROPN
brj-25043	31	36	and	and	CCONJ
brj-25043	31	37	hybrid	hybrid	ADJ
brj-25043	31	38	ml	ml	NOUN
brj-25043	31	39	models	model	NOUN
brj-25043	31	40	,	,	PUNCT
brj-25043	31	41	including	include	VERB
brj-25043	31	42	random	random	ADJ
brj-25043	31	43	forests	forest	NOUN
brj-25043	31	44	,	,	PUNCT
brj-25043	31	45	svms	svms	NOUN
brj-25043	31	46	,	,	PUNCT
brj-25043	31	47	and	and	CCONJ
brj-25043	31	48	deep	deep	ADJ
brj-25043	31	49	learning	learning	NOUN
brj-25043	31	50	architectures	architecture	NOUN
brj-25043	31	51	.	.	PUNCT
brj-25043	32	1	the	the	DET
brj-25043	32	2	review	review	NOUN
brj-25043	32	3	highlights	highlight	VERB
brj-25043	32	4	how	how	SCONJ
brj-25043	32	5	ml	ml	AUX
brj-25043	32	6	algorithms	algorithm	NOUN
brj-25043	32	7	increasingly	increasingly	ADV
brj-25043	32	8	address	address	VERB
brj-25043	32	9	the	the	DET
brj-25043	32	10	nonlinearities	nonlinearitie	NOUN
brj-25043	32	11	and	and	CCONJ
brj-25043	32	12	uncertainties	uncertainty	NOUN
brj-25043	32	13	inherent	inherent	ADJ
brj-25043	32	14	in	in	ADP
brj-25043	32	15	ad	ad	NOUN
brj-25043	32	16	systems	system	NOUN
brj-25043	32	17	,	,	PUNCT
brj-25043	32	18	particularly	particularly	ADV
brj-25043	32	19	for	for	ADP
brj-25043	32	20	complex	complex	ADJ
brj-25043	32	21	substrates	substrate	NOUN
brj-25043	32	22	such	such	ADJ
brj-25043	32	23	as	as	ADP
brj-25043	32	24	sewage	sewage	NOUN
brj-25043	32	25	sludge	sludge	NOUN
brj-25043	32	26	,	,	PUNCT
brj-25043	32	27	food	food	NOUN
brj-25043	32	28	waste	waste	NOUN
brj-25043	32	29	,	,	PUNCT
brj-25043	32	30	and	and	CCONJ
brj-25043	32	31	co	co	ADJ
brj-25043	32	32	-	-	ADJ
brj-25043	32	33	digested	digested	ADJ
brj-25043	32	34	residues	residue	NOUN
brj-25043	32	35	.	.	PUNCT
brj-25043	33	1	moreover	moreover	ADV
brj-25043	33	2	,	,	PUNCT
brj-25043	33	3	it	it	PRON
brj-25043	33	4	outlines	outline	VERB
brj-25043	33	5	gaps	gap	NOUN
brj-25043	33	6	in	in	ADP
brj-25043	33	7	current	current	ADJ
brj-25043	33	8	modelling	modelling	NOUN
brj-25043	33	9	practices	practice	NOUN
brj-25043	33	10	,	,	PUNCT
brj-25043	33	11	including	include	VERB
brj-25043	33	12	limited	limit	VERB
brj-25043	33	13	real	real	ADJ
brj-25043	33	14	-	-	PUNCT
brj-25043	33	15	time	time	NOUN
brj-25043	33	16	adaptability	adaptability	NOUN
brj-25043	33	17	,	,	PUNCT
brj-25043	33	18	feature	feature	NOUN
brj-25043	33	19	selection	selection	NOUN
brj-25043	33	20	,	,	PUNCT
brj-25043	33	21	and	and	CCONJ
brj-25043	33	22	peer	peer	NOUN
brj-25043	33	23	-	-	PUNCT
brj-25043	33	24	reviewed	review	VERB
brj-25043	33	25	review	review	NOUN
brj-25043	33	26	article	article	NOUN
brj-25043	33	27	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	33	28	galal	galal	PROPN
brj-25043	33	29	et	et	PROPN
brj-25043	33	30	al	al	PROPN
brj-25043	33	31	.	.	PROPN
brj-25043	34	1	(	(	PUNCT
brj-25043	34	2	2025	2025	NUM
brj-25043	34	3	)	)	PUNCT
brj-25043	34	4	.	.	PUNCT
brj-25043	35	1	“	"	PUNCT
brj-25043	35	2	math	math	NOUN
brj-25043	35	3	modeling	modeling	NOUN
brj-25043	35	4	biogas	biogas	NOUN
brj-25043	35	5	production	production	NOUN
brj-25043	35	6	,	,	PUNCT
brj-25043	35	7	”	"	PUNCT
brj-25043	35	8	bioresources	bioresource	NOUN
brj-25043	35	9	20(4	20(4	NOUN
brj-25043	35	10	)	)	PUNCT
brj-25043	35	11	,	,	PUNCT
brj-25043	35	12	11237	11237	NUM
brj-25043	35	13	-	-	SYM
brj-25043	35	14	11266	11266	NUM
brj-25043	35	15	.	.	PUNCT
brj-25043	36	1	11239	11239	NUM
brj-25043	36	2	parameter	parameter	NOUN
brj-25043	36	3	sensitivity	sensitivity	NOUN
brj-25043	36	4	analysis	analysis	NOUN
brj-25043	36	5	.	.	PUNCT
brj-25043	37	1	it	it	PRON
brj-25043	37	2	proposes	propose	VERB
brj-25043	37	3	future	future	ADJ
brj-25043	37	4	extensions	extension	NOUN
brj-25043	37	5	involving	involve	VERB
brj-25043	37	6	hybrid	hybrid	ADJ
brj-25043	37	7	modelling	modelling	NOUN
brj-25043	37	8	frameworks	framework	NOUN
brj-25043	37	9	and	and	CCONJ
brj-25043	37	10	smart	smart	ADJ
brj-25043	37	11	digesters	digester	NOUN
brj-25043	37	12	.	.	PUNCT
brj-25043	38	1	through	through	ADP
brj-25043	38	2	integrating	integrate	VERB
brj-25043	38	3	insights	insight	NOUN
brj-25043	38	4	across	across	ADP
brj-25043	38	5	computational	computational	ADJ
brj-25043	38	6	and	and	CCONJ
brj-25043	38	7	engineering	engineering	NOUN
brj-25043	38	8	domains	domain	NOUN
brj-25043	38	9	,	,	PUNCT
brj-25043	38	10	this	this	DET
brj-25043	38	11	review	review	NOUN
brj-25043	38	12	advances	advance	VERB
brj-25043	38	13	a	a	DET
brj-25043	38	14	comprehensive	comprehensive	ADJ
brj-25043	38	15	understanding	understanding	NOUN
brj-25043	38	16	of	of	ADP
brj-25043	38	17	biogas	biogas	NOUN
brj-25043	38	18	system	system	NOUN
brj-25043	38	19	optimization	optimization	NOUN
brj-25043	38	20	,	,	PUNCT
brj-25043	38	21	promoting	promote	VERB
brj-25043	38	22	scalable	scalable	ADJ
brj-25043	38	23	and	and	CCONJ
brj-25043	38	24	intelligent	intelligent	ADJ
brj-25043	38	25	waste	waste	NOUN
brj-25043	38	26	-	-	PUNCT
brj-25043	38	27	to	to	ADP
brj-25043	38	28	-	-	PUNCT
brj-25043	38	29	energy	energy	NOUN
brj-25043	38	30	solutions	solution	NOUN
brj-25043	38	31	aligned	align	VERB
brj-25043	38	32	with	with	ADP
brj-25043	38	33	sustainability	sustainability	NOUN
brj-25043	38	34	goals	goal	NOUN
brj-25043	38	35	.	.	PUNCT
brj-25043	39	1	table	table	NOUN
brj-25043	39	2	1	1	NUM
brj-25043	39	3	.	.	PUNCT
brj-25043	40	1	summary	summary	NOUN
brj-25043	40	2	of	of	ADP
brj-25043	40	3	key	key	ADJ
brj-25043	40	4	studies	study	NOUN
brj-25043	40	5	on	on	ADP
brj-25043	40	6	anaerobic	anaerobic	ADJ
brj-25043	40	7	co	co	NOUN
brj-25043	40	8	-	-	NOUN
brj-25043	40	9	digestion	digestion	NOUN
brj-25043	40	10	,	,	PUNCT
brj-25043	40	11	highlighting	highlighting	NOUN
brj-25043	40	12	substrates	substrate	NOUN
brj-25043	40	13	,	,	PUNCT
brj-25043	40	14	operating	operating	NOUN
brj-25043	40	15	conditions	condition	NOUN
brj-25043	40	16	,	,	PUNCT
brj-25043	40	17	biogas	biogas	NOUN
brj-25043	40	18	/	/	SYM
brj-25043	40	19	methane	methane	NOUN
brj-25043	40	20	yields	yield	NOUN
brj-25043	40	21	,	,	PUNCT
brj-25043	40	22	and	and	CCONJ
brj-25043	40	23	kinetic	kinetic	ADJ
brj-25043	40	24	/	/	SYM
brj-25043	40	25	statistical	statistical	ADJ
brj-25043	40	26	model	model	NOUN
brj-25043	40	27	performance	performance	NOUN
brj-25043	40	28	substrate(s	substrate(s	NOUN
brj-25043	40	29	)	)	PUNCT
brj-25043	40	30	codigestion	codigestion	NOUN
brj-25043	40	31	ratio	ratio	NOUN
brj-25043	40	32	/	/	SYM
brj-25043	40	33	conditions	condition	NOUN
brj-25043	40	34	key	key	ADJ
brj-25043	40	35	findings	finding	NOUN
brj-25043	40	36	kinetic	kinetic	ADJ
brj-25043	40	37	/	/	SYM
brj-25043	40	38	statistical	statistical	ADJ
brj-25043	40	39	model	model	NOUN
brj-25043	40	40	r²	r²	NOUN
brj-25043	40	41	/	/	SYM
brj-25043	40	42	accuracy	accuracy	NOUN
brj-25043	40	43	study	study	NOUN
brj-25043	40	44	/	/	SYM
brj-25043	40	45	reference	reference	NOUN
brj-25043	40	46	sewage	sewage	NOUN
brj-25043	40	47	sludge	sludge	NOUN
brj-25043	40	48	,	,	PUNCT
brj-25043	40	49	agricultural	agricultural	ADJ
brj-25043	40	50	residues	residue	NOUN
brj-25043	40	51	,	,	PUNCT
brj-25043	40	52	municipal	municipal	ADJ
brj-25043	40	53	solid	solid	ADJ
brj-25043	40	54	waste	waste	NOUN
brj-25043	40	55	n	n	CCONJ
brj-25043	40	56	/	/	SYM
brj-25043	40	57	a	a	PRON
brj-25043	40	58	highlighted	highlight	VERB
brj-25043	40	59	the	the	DET
brj-25043	40	60	importance	importance	NOUN
brj-25043	40	61	of	of	ADP
brj-25043	40	62	mathematical	mathematical	ADJ
brj-25043	40	63	modeling	modeling	NOUN
brj-25043	40	64	in	in	ADP
brj-25043	40	65	understanding	understanding	NOUN
brj-25043	40	66	and	and	CCONJ
brj-25043	40	67	scaling	scale	VERB
brj-25043	40	68	ad	ad	NOUN
brj-25043	40	69	processes	process	NOUN
brj-25043	40	70	general	general	ADJ
brj-25043	40	71	kinetic	kinetic	NOUN
brj-25043	40	72	&	&	CCONJ
brj-25043	40	73	mechanistic	mechanistic	ADJ
brj-25043	40	74	modeling	modeling	NOUN
brj-25043	40	75	n	n	CCONJ
brj-25043	40	76	/	/	SYM
brj-25043	40	77	a	a	DET
brj-25043	40	78	abdel	abdel	PROPN
brj-25043	40	79	daiem	daiem	PROPN
brj-25043	40	80	et	et	PROPN
brj-25043	40	81	al	al	PROPN
brj-25043	40	82	.	.	PROPN
brj-25043	40	83	2021	2021	NUM
brj-25043	40	84	food	food	NOUN
brj-25043	40	85	waste	waste	NOUN
brj-25043	40	86	+	+	CCONJ
brj-25043	40	87	groundnut	groundnut	NOUN
brj-25043	40	88	shells	shell	NOUN
brj-25043	40	89	50:50:00	50:50:00	NUM
brj-25043	40	90	32.28	32.28	NUM
brj-25043	40	91	%	%	NOUN
brj-25043	40	92	increase	increase	NOUN
brj-25043	40	93	in	in	ADP
brj-25043	40	94	biomethane	biomethane	NOUN
brj-25043	40	95	yield	yield	NOUN
brj-25043	40	96	vs	vs	ADP
brj-25043	40	97	monodigestion	monodigestion	NOUN
brj-25043	40	98	gompertz	gompertz	NOUN
brj-25043	40	99	,	,	PUNCT
brj-25043	40	100	modified	modified	ADJ
brj-25043	40	101	gompertz	gompertz	NOUN
brj-25043	40	102	,	,	PUNCT
brj-25043	40	103	schunte	schunte	PROPN
brj-25043	40	104	0.97–0.99	0.97–0.99	NUM
brj-25043	40	105	olatunji	olatunji	NOUN
brj-25043	40	106	et	et	PROPN
brj-25043	40	107	al	al	PROPN
brj-25043	40	108	.	.	PROPN
brj-25043	40	109	2025	2025	NUM
brj-25043	40	110	sewage	sewage	NOUN
brj-25043	40	111	sludge	sludge	NOUN
brj-25043	40	112	+	+	CCONJ
brj-25043	40	113	wheat	wheat	NOUN
brj-25043	40	114	husk	husk	NOUN
brj-25043	40	115	n	n	CCONJ
brj-25043	40	116	/	/	SYM
brj-25043	40	117	a	a	DET
brj-25043	40	118	chenhashimoto	chenhashimoto	NOUN
brj-25043	40	119	showed	show	VERB
brj-25043	40	120	superior	superior	ADJ
brj-25043	40	121	predictive	predictive	ADJ
brj-25043	40	122	accuracy	accuracy	NOUN
brj-25043	40	123	and	and	CCONJ
brj-25043	40	124	robustness	robustness	NOUN
brj-25043	40	125	;	;	PUNCT
brj-25043	40	126	the	the	DET
brj-25043	40	127	ultimate	ultimate	ADJ
brj-25043	40	128	biogas	biogas	NOUN
brj-25043	40	129	potential	potential	NOUN
brj-25043	40	130	most	most	ADV
brj-25043	40	131	sensitive	sensitive	ADJ
brj-25043	40	132	first	first	ADJ
brj-25043	40	133	-	-	PUNCT
brj-25043	40	134	order	order	NOUN
brj-25043	40	135	,	,	PUNCT
brj-25043	40	136	modified	modified	ADJ
brj-25043	40	137	gompertz	gompertz	NOUN
brj-25043	40	138	,	,	PUNCT
brj-25043	40	139	chenhashimoto	chenhashimoto	ADJ
brj-25043	40	140	highest	high	ADJ
brj-25043	40	141	accuracy	accuracy	NOUN
brj-25043	40	142	(	(	PUNCT
brj-25043	40	143	not	not	PART
brj-25043	40	144	specified	specify	VERB
brj-25043	40	145	)	)	PUNCT
brj-25043	40	146	tiwari	tiwari	NOUN
brj-25043	40	147	et	et	PROPN
brj-25043	40	148	al	al	PROPN
brj-25043	40	149	.	.	PROPN
brj-25043	40	150	2025	2025	NUM
brj-25043	40	151	food	food	NOUN
brj-25043	40	152	waste	waste	NOUN
brj-25043	40	153	+	+	CCONJ
brj-25043	40	154	sewage	sewage	NOUN
brj-25043	40	155	sludge	sludge	NOUN
brj-25043	40	156	+	+	CCONJ
brj-25043	40	157	poultry	poultry	NOUN
brj-25043	40	158	litter	litter	NOUN
brj-25043	40	159	2:1:1	2:1:1	NUM
brj-25043	40	160	,	,	PUNCT
brj-25043	40	161	ambient	ambient	NOUN
brj-25043	40	162	,	,	PUNCT
brj-25043	40	163	summer	summer	NOUN
brj-25043	40	164	highest	high	ADJ
brj-25043	40	165	biogas	biogas	NOUN
brj-25043	40	166	output	output	NOUN
brj-25043	40	167	640	640	NUM
brj-25043	40	168	l	l	NOUN
brj-25043	40	169	/	/	SYM
brj-25043	40	170	kgvs	kgv	NOUN
brj-25043	40	171	,	,	PUNCT
brj-25043	40	172	65	65	NUM
brj-25043	40	173	%	%	NOUN
brj-25043	40	174	ch₄	ch₄	NOUN
brj-25043	40	175	;	;	PUNCT
brj-25043	40	176	temperature	temperature	NOUN
brj-25043	40	177	critical	critical	ADJ
brj-25043	40	178	for	for	ADP
brj-25043	40	179	seasonal	seasonal	ADJ
brj-25043	40	180	optimization	optimization	NOUN
brj-25043	40	181	gompertz	gompertz	NOUN
brj-25043	40	182	,	,	PUNCT
brj-25043	40	183	first	first	ADJ
brj-25043	40	184	-	-	PUNCT
brj-25043	40	185	order	order	NOUN
brj-25043	40	186	confirmed	confirm	VERB
brj-25043	40	187	experimental	experimental	ADJ
brj-25043	40	188	results	result	NOUN
brj-25043	40	189	lohani	lohani	PROPN
brj-25043	40	190	et	et	PROPN
brj-25043	40	191	al	al	PROPN
brj-25043	40	192	.	.	PROPN
brj-25043	40	193	2025	2025	NUM
brj-25043	40	194	sewage	sewage	NOUN
brj-25043	40	195	sludge	sludge	NOUN
brj-25043	40	196	+	+	CCONJ
brj-25043	40	197	agro	agro	ADJ
brj-25043	40	198	-	-	PUNCT
brj-25043	40	199	industrial	industrial	ADJ
brj-25043	40	200	fruit	fruit	NOUN
brj-25043	40	201	&	&	CCONJ
brj-25043	40	202	vegetable	vegetable	PROPN
brj-25043	40	203	waste	waste	PROPN
brj-25043	40	204	70:30	70:30	NUM
brj-25043	40	205	,	,	PUNCT
brj-25043	40	206	mesophilic	mesophilic	ADJ
brj-25043	40	207	optimal	optimal	ADJ
brj-25043	40	208	methane	methane	NOUN
brj-25043	40	209	yield	yield	NOUN
brj-25043	40	210	542.88	542.88	NUM
brj-25043	40	211	 	 	SPACE
brj-25043	40	212	ml	ml	ADP
brj-25043	41	1	ch₄/g	ch₄/g	NOUN
brj-25043	41	2	vs	vs	ADP
brj-25043	41	3	;	;	PUNCT
brj-25043	41	4	improved	improve	VERB
brj-25043	41	5	biodegradability	biodegradability	NOUN
brj-25043	41	6	&	&	CCONJ
brj-25043	41	7	pathogen	pathogen	NOUN
brj-25043	41	8	reduction	reduction	NOUN
brj-25043	41	9	cone	cone	NOUN
brj-25043	41	10	model	model	NOUN
brj-25043	41	11	>	>	X
brj-25043	41	12	0.98	0.98	NUM
brj-25043	41	13	pulgarínmuñoz	pulgarínmuñoz	NOUN
brj-25043	41	14	et	et	PROPN
brj-25043	41	15	al	al	PROPN
brj-25043	41	16	.	.	PROPN
brj-25043	41	17	2025	2025	NUM
brj-25043	41	18	peer	peer	NOUN
brj-25043	41	19	-	-	PUNCT
brj-25043	41	20	reviewed	review	VERB
brj-25043	41	21	review	review	NOUN
brj-25043	41	22	article	article	NOUN
brj-25043	41	23	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	41	24	galal	galal	PROPN
brj-25043	41	25	et	et	PROPN
brj-25043	41	26	al	al	PROPN
brj-25043	41	27	.	.	PROPN
brj-25043	42	1	(	(	PUNCT
brj-25043	42	2	2025	2025	NUM
brj-25043	42	3	)	)	PUNCT
brj-25043	42	4	.	.	PUNCT
brj-25043	43	1	“	"	PUNCT
brj-25043	43	2	math	math	NOUN
brj-25043	43	3	modeling	modeling	NOUN
brj-25043	43	4	biogas	biogas	NOUN
brj-25043	43	5	production	production	NOUN
brj-25043	43	6	,	,	PUNCT
brj-25043	43	7	”	"	PUNCT
brj-25043	43	8	bioresources	bioresource	NOUN
brj-25043	43	9	20(4	20(4	NOUN
brj-25043	43	10	)	)	PUNCT
brj-25043	43	11	,	,	PUNCT
brj-25043	43	12	11237	11237	NUM
brj-25043	43	13	-	-	SYM
brj-25043	43	14	11266	11266	NUM
brj-25043	43	15	.	.	PUNCT
brj-25043	44	1	11240	11240	NUM
brj-25043	44	2	novelty	novelty	NOUN
brj-25043	44	3	and	and	CCONJ
brj-25043	44	4	distinctiveness	distinctiveness	NOUN
brj-25043	44	5	this	this	DET
brj-25043	44	6	review	review	NOUN
brj-25043	44	7	differs	differ	VERB
brj-25043	44	8	from	from	ADP
brj-25043	44	9	others	other	NOUN
brj-25043	44	10	in	in	ADP
brj-25043	44	11	the	the	DET
brj-25043	44	12	following	follow	VERB
brj-25043	44	13	respects	respect	NOUN
brj-25043	44	14	:	:	PUNCT
brj-25043	44	15	1	1	X
brj-25043	44	16	.	.	X
brj-25043	44	17	classical	classical	ADJ
brj-25043	44	18	vs.	vs.	ADP
brj-25043	44	19	ml	ml	ADP
brj-25043	44	20	modeling	modeling	NOUN
brj-25043	44	21	:	:	PUNCT
brj-25043	44	22	the	the	DET
brj-25043	44	23	review	review	NOUN
brj-25043	44	24	compares	compare	VERB
brj-25043	44	25	classical	classical	ADJ
brj-25043	44	26	kinetic	kinetic	NOUN
brj-25043	44	27	models	model	NOUN
brj-25043	44	28	(	(	PUNCT
brj-25043	44	29	firstorder	firstorder	NOUN
brj-25043	44	30	,	,	PUNCT
brj-25043	44	31	gompertz	gompertz	NOUN
brj-25043	44	32	,	,	PUNCT
brj-25043	44	33	chen	chen	NOUN
brj-25043	44	34	-	-	PUNCT
brj-25043	44	35	hashimoto	hashimoto	NOUN
brj-25043	44	36	)	)	PUNCT
brj-25043	44	37	with	with	ADP
brj-25043	44	38	ml	ml	NOUN
brj-25043	44	39	approaches	approach	NOUN
brj-25043	44	40	across	across	ADP
brj-25043	44	41	daily	daily	ADJ
brj-25043	44	42	-	-	PUNCT
brj-25043	44	43	rate	rate	NOUN
brj-25043	44	44	and	and	CCONJ
brj-25043	44	45	cumulativeyield	cumulativeyield	ADJ
brj-25043	44	46	frameworks	framework	NOUN
brj-25043	44	47	.	.	PUNCT
brj-25043	45	1	findings	finding	NOUN
brj-25043	45	2	highlight	highlight	VERB
brj-25043	45	3	where	where	SCONJ
brj-25043	45	4	traditional	traditional	ADJ
brj-25043	45	5	kinetics	kinetic	NOUN
brj-25043	45	6	remain	remain	VERB
brj-25043	45	7	useful	useful	ADJ
brj-25043	45	8	and	and	CCONJ
brj-25043	45	9	where	where	SCONJ
brj-25043	45	10	ml	ml	AUX
brj-25043	45	11	achieves	achieve	VERB
brj-25043	45	12	better	well	ADJ
brj-25043	45	13	predictive	predictive	ADJ
brj-25043	45	14	accuracy	accuracy	NOUN
brj-25043	45	15	.	.	PUNCT
brj-25043	46	1	2	2	X
brj-25043	46	2	.	.	X
brj-25043	46	3	multidimensional	multidimensional	ADJ
brj-25043	46	4	kinetic	kinetic	ADJ
brj-25043	46	5	framework	framework	NOUN
brj-25043	46	6	:	:	PUNCT
brj-25043	46	7	a	a	DET
brj-25043	46	8	multidimensional	multidimensional	ADJ
brj-25043	46	9	framework	framework	NOUN
brj-25043	46	10	is	be	AUX
brj-25043	46	11	introduced	introduce	VERB
brj-25043	46	12	,	,	PUNCT
brj-25043	46	13	treating	treat	VERB
brj-25043	46	14	kinetic	kinetic	ADJ
brj-25043	46	15	parameters	parameter	NOUN
brj-25043	46	16	as	as	ADP
brj-25043	46	17	functions	function	NOUN
brj-25043	46	18	of	of	ADP
brj-25043	46	19	operational	operational	ADJ
brj-25043	46	20	variables	variable	NOUN
brj-25043	46	21	such	such	ADJ
brj-25043	46	22	as	as	ADP
brj-25043	46	23	temperature	temperature	NOUN
brj-25043	46	24	and	and	CCONJ
brj-25043	46	25	mixing	mix	VERB
brj-25043	46	26	ratio	ratio	NOUN
brj-25043	46	27	.	.	PUNCT
brj-25043	47	1	this	this	PRON
brj-25043	47	2	enables	enable	VERB
brj-25043	47	3	response	response	NOUN
brj-25043	47	4	surfaces	surface	NOUN
brj-25043	47	5	that	that	PRON
brj-25043	47	6	support	support	VERB
brj-25043	47	7	scenario	scenario	NOUN
brj-25043	47	8	mapping	mapping	NOUN
brj-25043	47	9	and	and	CCONJ
brj-25043	47	10	process	process	NOUN
brj-25043	47	11	optimization	optimization	NOUN
brj-25043	47	12	,	,	PUNCT
brj-25043	47	13	which	which	PRON
brj-25043	47	14	are	be	AUX
brj-25043	47	15	rarely	rarely	ADV
brj-25043	47	16	discussed	discuss	VERB
brj-25043	47	17	in	in	ADP
brj-25043	47	18	prior	prior	ADJ
brj-25043	47	19	ad	ad	NOUN
brj-25043	47	20	reviews	review	NOUN
brj-25043	47	21	.	.	PUNCT
brj-25043	48	1	3	3	X
brj-25043	48	2	.	.	X
brj-25043	48	3	stochastic	stochastic	ADJ
brj-25043	48	4	parameter	parameter	NOUN
brj-25043	48	5	uncertainty	uncertainty	NOUN
brj-25043	48	6	:	:	PUNCT
brj-25043	48	7	kinetic	kinetic	ADJ
brj-25043	48	8	parameters	parameter	NOUN
brj-25043	48	9	are	be	AUX
brj-25043	48	10	modeled	model	VERB
brj-25043	48	11	as	as	ADP
brj-25043	48	12	random	random	ADJ
brj-25043	48	13	variables	variable	NOUN
brj-25043	48	14	using	use	VERB
brj-25043	48	15	stochastic	stochastic	ADJ
brj-25043	48	16	methods	method	NOUN
brj-25043	48	17	,	,	PUNCT
brj-25043	48	18	including	include	VERB
brj-25043	48	19	karhunen	karhunen	NOUN
brj-25043	48	20	–	–	PUNCT
brj-25043	48	21	loève	loève	NOUN
brj-25043	48	22	expansions	expansion	NOUN
brj-25043	48	23	.	.	PUNCT
brj-25043	49	1	this	this	PRON
brj-25043	49	2	generates	generate	VERB
brj-25043	49	3	probabilistic	probabilistic	ADJ
brj-25043	49	4	biogas	biogas	NOUN
brj-25043	49	5	trajectories	trajectory	NOUN
brj-25043	49	6	with	with	ADP
brj-25043	49	7	means	mean	NOUN
brj-25043	49	8	,	,	PUNCT
brj-25043	49	9	quantiles	quantile	NOUN
brj-25043	49	10	,	,	PUNCT
brj-25043	49	11	and	and	CCONJ
brj-25043	49	12	variances	variance	NOUN
brj-25043	49	13	,	,	PUNCT
brj-25043	49	14	offering	offer	VERB
brj-25043	49	15	a	a	DET
brj-25043	49	16	risk	risk	NOUN
brj-25043	49	17	-	-	PUNCT
brj-25043	49	18	aware	aware	ADJ
brj-25043	49	19	alternative	alternative	NOUN
brj-25043	49	20	to	to	PART
brj-25043	49	21	point	point	NOUN
brj-25043	49	22	estimates	estimate	NOUN
brj-25043	49	23	.	.	PUNCT
brj-25043	50	1	4	4	X
brj-25043	50	2	.	.	NUM
brj-25043	50	3	ml	ml	NOUN
brj-25043	50	4	applications	application	NOUN
brj-25043	50	5	:	:	PUNCT
brj-25043	50	6	advanced	advanced	ADJ
brj-25043	50	7	ml	ml	NOUN
brj-25043	50	8	methods	method	NOUN
brj-25043	50	9	(	(	PUNCT
brj-25043	50	10	lstm	lstm	PROPN
brj-25043	50	11	,	,	PUNCT
brj-25043	50	12	tft	tft	ADV
brj-25043	50	13	,	,	PUNCT
brj-25043	50	14	shap	shap	NOUN
brj-25043	50	15	)	)	PUNCT
brj-25043	50	16	are	be	AUX
brj-25043	50	17	synthesized	synthesize	VERB
brj-25043	50	18	for	for	ADP
brj-25043	50	19	forecasting	forecasting	NOUN
brj-25043	50	20	,	,	PUNCT
brj-25043	50	21	optimization	optimization	NOUN
brj-25043	50	22	,	,	PUNCT
brj-25043	50	23	and	and	CCONJ
brj-25043	50	24	stability	stability	NOUN
brj-25043	50	25	control	control	NOUN
brj-25043	50	26	in	in	ADP
brj-25043	50	27	ad	ad	NOUN
brj-25043	50	28	systems	system	NOUN
brj-25043	50	29	.	.	PUNCT
brj-25043	51	1	their	their	PRON
brj-25043	51	2	performance	performance	NOUN
brj-25043	51	3	is	be	AUX
brj-25043	51	4	benchmarked	benchmarke	VERB
brj-25043	51	5	against	against	ADP
brj-25043	51	6	kinetic	kinetic	ADJ
brj-25043	51	7	baselines	baseline	NOUN
brj-25043	51	8	,	,	PUNCT
brj-25043	51	9	emphasizing	emphasize	VERB
brj-25043	51	10	practical	practical	ADJ
brj-25043	51	11	deployment	deployment	NOUN
brj-25043	51	12	guidance	guidance	NOUN
brj-25043	51	13	.	.	PUNCT
brj-25043	52	1	5	5	X
brj-25043	52	2	.	.	X
brj-25043	52	3	hybrid	hybrid	ADJ
brj-25043	52	4	mechanistic	mechanistic	ADJ
brj-25043	52	5	–	–	PUNCT
brj-25043	52	6	ml	ml	NOUN
brj-25043	52	7	framework	framework	NOUN
brj-25043	52	8	:	:	PUNCT
brj-25043	52	9	a	a	DET
brj-25043	52	10	hybrid	hybrid	ADJ
brj-25043	52	11	framework	framework	NOUN
brj-25043	52	12	integrates	integrate	VERB
brj-25043	52	13	mechanistic	mechanistic	ADJ
brj-25043	52	14	kinetics	kinetic	NOUN
brj-25043	52	15	with	with	ADP
brj-25043	52	16	ml	ml	ADP
brj-25043	52	17	residual	residual	ADJ
brj-25043	52	18	learning	learning	NOUN
brj-25043	52	19	,	,	PUNCT
brj-25043	52	20	enabling	enable	VERB
brj-25043	52	21	iot	iot	NOUN
brj-25043	52	22	-	-	PUNCT
brj-25043	52	23	based	base	VERB
brj-25043	52	24	smart	smart	ADJ
brj-25043	52	25	digesters	digester	NOUN
brj-25043	52	26	.	.	PUNCT
brj-25043	53	1	recommendations	recommendation	NOUN
brj-25043	53	2	for	for	ADP
brj-25043	53	3	dataset	dataset	ADJ
brj-25043	53	4	standardization	standardization	NOUN
brj-25043	53	5	and	and	CCONJ
brj-25043	53	6	cross	cross	ADJ
brj-25043	53	7	-	-	ADJ
brj-25043	53	8	validation	validation	ADJ
brj-25043	53	9	strengthen	strengthen	NOUN
brj-25043	53	10	pathways	pathway	NOUN
brj-25043	53	11	toward	toward	ADP
brj-25043	53	12	real	real	ADJ
brj-25043	53	13	-	-	PUNCT
brj-25043	53	14	world	world	NOUN
brj-25043	53	15	implementation	implementation	NOUN
brj-25043	53	16	.	.	PUNCT
brj-25043	54	1	6	6	NUM
brj-25043	54	2	.	.	X
brj-25043	54	3	up	up	ADP
brj-25043	54	4	-	-	PUNCT
brj-25043	54	5	to	to	ADP
brj-25043	54	6	-	-	PUNCT
brj-25043	54	7	date	date	NOUN
brj-25043	54	8	coverage	coverage	NOUN
brj-25043	54	9	:	:	PUNCT
brj-25043	54	10	the	the	DET
brj-25043	54	11	article	article	NOUN
brj-25043	54	12	emphasizes	emphasize	VERB
brj-25043	54	13	the	the	DET
brj-25043	54	14	most	most	ADV
brj-25043	54	15	recent	recent	ADJ
brj-25043	54	16	advances	advance	NOUN
brj-25043	54	17	(	(	PUNCT
brj-25043	54	18	2023	2023	NUM
brj-25043	54	19	–	–	PUNCT
brj-25043	54	20	2025	2025	NUM
brj-25043	54	21	)	)	PUNCT
brj-25043	54	22	,	,	PUNCT
brj-25043	54	23	including	include	VERB
brj-25043	54	24	emerging	emerge	VERB
brj-25043	54	25	algorithms	algorithm	NOUN
brj-25043	54	26	(	(	PUNCT
brj-25043	54	27	lstm	lstm	PROPN
brj-25043	54	28	,	,	PUNCT
brj-25043	54	29	hybrid	hybrid	ADJ
brj-25043	54	30	ml	ml	NOUN
brj-25043	54	31	models	model	NOUN
brj-25043	54	32	)	)	PUNCT
brj-25043	54	33	and	and	CCONJ
brj-25043	54	34	updated	update	VERB
brj-25043	54	35	kinetic	kinetic	ADJ
brj-25043	54	36	formulations	formulation	NOUN
brj-25043	54	37	,	,	PUNCT
brj-25043	54	38	which	which	PRON
brj-25043	54	39	have	have	AUX
brj-25043	54	40	not	not	PART
brj-25043	54	41	been	be	AUX
brj-25043	54	42	synthesized	synthesize	VERB
brj-25043	54	43	elsewhere	elsewhere	ADV
brj-25043	54	44	.	.	PUNCT
brj-25043	55	1	mathematical	mathematical	ADJ
brj-25043	55	2	models	model	NOUN
brj-25043	55	3	daily	daily	ADJ
brj-25043	55	4	biogas	biogas	NOUN
brj-25043	55	5	production	production	NOUN
brj-25043	55	6	models	model	NOUN
brj-25043	55	7	table	table	VERB
brj-25043	55	8	2	2	NUM
brj-25043	55	9	identifies	identify	VERB
brj-25043	55	10	the	the	DET
brj-25043	55	11	parameters	parameter	NOUN
brj-25043	55	12	and	and	CCONJ
brj-25043	55	13	their	their	PRON
brj-25043	55	14	goodness	goodness	NOUN
brj-25043	55	15	of	of	ADP
brj-25043	55	16	fit	fit	ADJ
brj-25043	55	17	using	use	VERB
brj-25043	55	18	daily	daily	ADJ
brj-25043	55	19	biogas	biogas	NOUN
brj-25043	55	20	production	production	NOUN
brj-25043	55	21	models	model	NOUN
brj-25043	55	22	(	(	PUNCT
brj-25043	55	23	linear	linear	ADJ
brj-25043	55	24	,	,	PUNCT
brj-25043	55	25	exponential	exponential	NOUN
brj-25043	55	26	,	,	PUNCT
brj-25043	55	27	and	and	CCONJ
brj-25043	55	28	gaussian	gaussian	ADJ
brj-25043	55	29	models	model	NOUN
brj-25043	55	30	)	)	PUNCT
brj-25043	55	31	.	.	PUNCT
brj-25043	56	1	among	among	ADP
brj-25043	56	2	the	the	DET
brj-25043	56	3	case	case	NOUN
brj-25043	56	4	studies	study	NOUN
brj-25043	56	5	summarized	summarize	VERB
brj-25043	56	6	in	in	ADP
brj-25043	56	7	table	table	NOUN
brj-25043	56	8	2	2	NUM
brj-25043	56	9	,	,	PUNCT
brj-25043	56	10	exponential	exponential	ADJ
brj-25043	56	11	daily	daily	ADJ
brj-25043	56	12	-	-	PUNCT
brj-25043	56	13	rate	rate	NOUN
brj-25043	56	14	functions	function	NOUN
brj-25043	56	15	consistently	consistently	ADV
brj-25043	56	16	achieved	achieve	VERB
brj-25043	56	17	the	the	DET
brj-25043	56	18	highest	high	ADJ
brj-25043	56	19	goodness	goodness	NOUN
brj-25043	56	20	-	-	PUNCT
brj-25043	56	21	of	of	ADP
brj-25043	56	22	-	-	PUNCT
brj-25043	56	23	fit	fit	NOUN
brj-25043	56	24	on	on	ADP
brj-25043	56	25	both	both	PRON
brj-25043	56	26	rising	rise	VERB
brj-25043	56	27	and	and	CCONJ
brj-25043	56	28	falling	fall	VERB
brj-25043	56	29	limbs	limb	NOUN
brj-25043	56	30	(	(	PUNCT
brj-25043	56	31	r²	r²	VERB
brj-25043	56	32	≈	≈	PROPN
brj-25043	56	33	0.960–0.999	0.960–0.999	NOUN
brj-25043	56	34	)	)	PUNCT
brj-25043	56	35	,	,	PUNCT
brj-25043	56	36	followed	follow	VERB
brj-25043	56	37	by	by	ADP
brj-25043	56	38	gaussian	gaussian	ADJ
brj-25043	56	39	profiles	profile	NOUN
brj-25043	56	40	when	when	SCONJ
brj-25043	56	41	a	a	DET
brj-25043	56	42	single	single	ADJ
brj-25043	56	43	,	,	PUNCT
brj-25043	56	44	roughly	roughly	ADV
brj-25043	56	45	symmetric	symmetric	ADJ
brj-25043	56	46	peak	peak	NOUN
brj-25043	56	47	was	be	AUX
brj-25043	56	48	present	present	ADJ
brj-25043	56	49	(	(	PUNCT
brj-25043	56	50	r²	r²	VERB
brj-25043	56	51	≈	≈	PROPN
brj-25043	56	52	0.95	0.95	NUM
brj-25043	56	53	)	)	PUNCT
brj-25043	56	54	.	.	PUNCT
brj-25043	57	1	linear	linear	PROPN
brj-25043	57	2	fits	fit	NOUN
brj-25043	57	3	were	be	AUX
brj-25043	57	4	acceptable	acceptable	ADJ
brj-25043	57	5	mainly	mainly	ADV
brj-25043	57	6	for	for	ADP
brj-25043	57	7	descending	descend	VERB
brj-25043	57	8	limbs	limb	NOUN
brj-25043	57	9	or	or	CCONJ
brj-25043	57	10	simple	simple	ADJ
brj-25043	57	11	substrates	substrate	NOUN
brj-25043	57	12	but	but	CCONJ
brj-25043	57	13	tended	tend	VERB
brj-25043	57	14	to	to	PART
brj-25043	57	15	underfit	underfit	VERB
brj-25043	57	16	peak	peak	NOUN
brj-25043	57	17	regions	region	NOUN
brj-25043	57	18	and	and	CCONJ
brj-25043	57	19	onset	onset	NOUN
brj-25043	57	20	dynamics	dynamic	NOUN
brj-25043	57	21	.	.	PUNCT
brj-25043	58	1	practically	practically	ADV
brj-25043	58	2	,	,	PUNCT
brj-25043	58	3	daily	daily	ADJ
brj-25043	58	4	-	-	PUNCT
brj-25043	58	5	rate	rate	NOUN
brj-25043	58	6	forecasting	forecasting	NOUN
brj-25043	58	7	should	should	AUX
brj-25043	58	8	default	default	VERB
brj-25043	58	9	to	to	ADP
brj-25043	58	10	exponential	exponential	ADJ
brj-25043	58	11	models	model	NOUN
brj-25043	58	12	unless	unless	SCONJ
brj-25043	58	13	there	there	PRON
brj-25043	58	14	is	be	VERB
brj-25043	58	15	strong	strong	ADJ
brj-25043	58	16	peak	peak	NOUN
brj-25043	58	17	asymmetry	asymmetry	NOUN
brj-25043	58	18	or	or	CCONJ
brj-25043	58	19	multi	multi	ADJ
brj-25043	58	20	-	-	ADJ
brj-25043	58	21	modal	modal	ADJ
brj-25043	58	22	behavior	behavior	NOUN
brj-25043	58	23	;	;	PUNCT
brj-25043	58	24	linear	linear	NOUN
brj-25043	58	25	fits	fit	NOUN
brj-25043	58	26	are	be	AUX
brj-25043	58	27	best	well	ADV
brj-25043	58	28	used	use	VERB
brj-25043	58	29	for	for	ADP
brj-25043	58	30	quick	quick	ADJ
brj-25043	58	31	,	,	PUNCT
brj-25043	58	32	conservative	conservative	ADJ
brj-25043	58	33	screening	screening	NOUN
brj-25043	58	34	.	.	PUNCT
brj-25043	59	1	exponential	exponential	ADJ
brj-25043	59	2	daily	daily	ADJ
brj-25043	59	3	-	-	PUNCT
brj-25043	59	4	rate	rate	NOUN
brj-25043	59	5	models	model	NOUN
brj-25043	59	6	are	be	AUX
brj-25043	59	7	the	the	DET
brj-25043	59	8	most	most	ADV
brj-25043	59	9	reliable	reliable	ADJ
brj-25043	59	10	across	across	ADP
brj-25043	59	11	substrates	substrate	NOUN
brj-25043	59	12	and	and	CCONJ
brj-25043	59	13	digestion	digestion	NOUN
brj-25043	59	14	stages	stage	NOUN
brj-25043	59	15	,	,	PUNCT
brj-25043	59	16	with	with	ADP
brj-25043	59	17	gaussian	gaussian	ADJ
brj-25043	59	18	profiles	profile	NOUN
brj-25043	59	19	competitive	competitive	ADJ
brj-25043	59	20	when	when	SCONJ
brj-25043	59	21	production	production	NOUN
brj-25043	59	22	exhibits	exhibit	VERB
brj-25043	59	23	a	a	DET
brj-25043	59	24	single	single	ADJ
brj-25043	59	25	,	,	PUNCT
brj-25043	59	26	symmetric	symmetric	ADJ
brj-25043	59	27	peak	peak	NOUN
brj-25043	59	28	;	;	PUNCT
brj-25043	59	29	linear	linear	PROPN
brj-25043	59	30	fits	fit	VERB
brj-25043	59	31	chiefly	chiefly	ADV
brj-25043	59	32	succeed	succeed	VERB
brj-25043	59	33	on	on	ADP
brj-25043	59	34	descending	descend	VERB
brj-25043	59	35	limbs	limb	NOUN
brj-25043	59	36	and	and	CCONJ
brj-25043	59	37	under	under	ADP
brj-25043	59	38	simple	simple	ADJ
brj-25043	59	39	matrices	matrix	NOUN
brj-25043	59	40	.	.	PUNCT
brj-25043	60	1	lo	lo	NOUN
brj-25043	60	2	et	et	PROPN
brj-25043	60	3	al	al	PROPN
brj-25043	60	4	.	.	PROPN
brj-25043	60	5	(	(	PUNCT
brj-25043	60	6	2010	2010	NUM
brj-25043	60	7	)	)	PUNCT
brj-25043	60	8	and	and	CCONJ
brj-25043	60	9	latinwo	latinwo	NOUN
brj-25043	60	10	and	and	CCONJ
brj-25043	60	11	agarry	agarry	PROPN
brj-25043	60	12	(	(	PUNCT
brj-25043	60	13	2015	2015	NUM
brj-25043	60	14	)	)	PUNCT
brj-25043	60	15	illustrate	illustrate	VERB
brj-25043	60	16	this	this	DET
brj-25043	60	17	pattern	pattern	NOUN
brj-25043	60	18	:	:	PUNCT
brj-25043	60	19	exponential	exponential	NOUN
brj-25043	60	20	fits	fit	VERB
brj-25043	60	21	track	track	NOUN
brj-25043	60	22	both	both	PRON
brj-25043	60	23	rise	rise	VERB
brj-25043	60	24	and	and	CCONJ
brj-25043	60	25	fall	fall	VERB
brj-25043	60	26	with	with	ADP
brj-25043	60	27	the	the	DET
brj-25043	60	28	highest	high	ADJ
brj-25043	60	29	r²	r²	NOUN
brj-25043	60	30	,	,	PUNCT
brj-25043	60	31	gaussian	gaussian	NOUN
brj-25043	60	32	captures	capture	VERB
brj-25043	60	33	unimodal	unimodal	ADJ
brj-25043	60	34	curves	curve	NOUN
brj-25043	60	35	,	,	PUNCT
brj-25043	60	36	and	and	CCONJ
brj-25043	60	37	linear	linear	PROPN
brj-25043	60	38	underestimates	underestimate	VERB
brj-25043	60	39	peak	peak	NOUN
brj-25043	60	40	curvature	curvature	NOUN
brj-25043	60	41	.	.	PUNCT
brj-25043	61	1	practically	practically	ADV
brj-25043	61	2	,	,	PUNCT
brj-25043	61	3	investigators	investigator	NOUN
brj-25043	61	4	often	often	ADV
brj-25043	61	5	default	default	VERB
brj-25043	61	6	to	to	ADP
brj-25043	61	7	using	use	VERB
brj-25043	61	8	exponential	exponential	ADJ
brj-25043	61	9	approaches	approach	NOUN
brj-25043	61	10	for	for	ADP
brj-25043	61	11	short	short	ADJ
brj-25043	61	12	-	-	PUNCT
brj-25043	61	13	horizon	horizon	NOUN
brj-25043	61	14	forecasting	forecasting	NOUN
brj-25043	61	15	and	and	CCONJ
brj-25043	61	16	reserve	reserve	PROPN
brj-25043	61	17	gaussian	gaussian	NOUN
brj-25043	61	18	approaches	approach	NOUN
brj-25043	61	19	for	for	ADP
brj-25043	61	20	pronounced	pronounce	VERB
brj-25043	61	21	single	single	ADJ
brj-25043	61	22	-	-	PUNCT
brj-25043	61	23	peak	peak	NOUN
brj-25043	61	24	shapes	shape	NOUN
brj-25043	61	25	;	;	PUNCT
brj-25043	61	26	they	they	PRON
brj-25043	61	27	use	use	VERB
brj-25043	61	28	linear	linear	NOUN
brj-25043	61	29	fitting	fit	VERB
brj-25043	61	30	only	only	ADV
brj-25043	61	31	for	for	ADP
brj-25043	61	32	conservative	conservative	ADJ
brj-25043	61	33	trend	trend	NOUN
brj-25043	61	34	screening	screen	VERB
brj-25043	61	35	.	.	PUNCT
brj-25043	62	1	peer	peer	NOUN
brj-25043	62	2	-	-	PUNCT
brj-25043	62	3	reviewed	review	VERB
brj-25043	62	4	review	review	NOUN
brj-25043	62	5	article	article	NOUN
brj-25043	62	6	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	62	7	galal	galal	PROPN
brj-25043	62	8	et	et	PROPN
brj-25043	62	9	al	al	PROPN
brj-25043	62	10	.	.	PROPN
brj-25043	63	1	(	(	PUNCT
brj-25043	63	2	2025	2025	NUM
brj-25043	63	3	)	)	PUNCT
brj-25043	63	4	.	.	PUNCT
brj-25043	64	1	“	"	PUNCT
brj-25043	64	2	math	math	NOUN
brj-25043	64	3	modeling	modeling	NOUN
brj-25043	64	4	biogas	biogas	NOUN
brj-25043	64	5	production	production	NOUN
brj-25043	64	6	,	,	PUNCT
brj-25043	64	7	”	"	PUNCT
brj-25043	64	8	bioresources	bioresource	NOUN
brj-25043	64	9	20(4	20(4	NOUN
brj-25043	64	10	)	)	PUNCT
brj-25043	64	11	,	,	PUNCT
brj-25043	64	12	11237	11237	NUM
brj-25043	64	13	-	-	SYM
brj-25043	64	14	11266	11266	NUM
brj-25043	64	15	.	.	PUNCT
brj-25043	65	1	11241	11241	NUM
brj-25043	65	2	table	table	NOUN
brj-25043	65	3	2	2	NUM
brj-25043	65	4	.	.	PUNCT
brj-25043	65	5	daily	daily	ADJ
brj-25043	65	6	biogas	biogas	NOUN
brj-25043	65	7	production	production	NOUN
brj-25043	65	8	models	model	NOUN
brj-25043	65	9	(	(	PUNCT
brj-25043	65	10	linear	linear	ADJ
brj-25043	65	11	,	,	PUNCT
brj-25043	65	12	exponential	exponential	NOUN
brj-25043	65	13	,	,	PUNCT
brj-25043	65	14	and	and	CCONJ
brj-25043	65	15	gaussian	gaussian	ADJ
brj-25043	65	16	)	)	PUNCT
brj-25043	65	17	applied	apply	VERB
brj-25043	65	18	to	to	ADP
brj-25043	65	19	diverse	diverse	ADJ
brj-25043	65	20	feedstock	feedstock	NOUN
brj-25043	65	21	,	,	PUNCT
brj-25043	65	22	with	with	ADP
brj-25043	65	23	key	key	ADJ
brj-25043	65	24	parameters	parameter	NOUN
brj-25043	65	25	and	and	CCONJ
brj-25043	65	26	r²	r²	VERB
brj-25043	65	27	values	value	NOUN
brj-25043	65	28	.	.	PUNCT
brj-25043	66	1	all	all	DET
brj-25043	66	2	models	model	NOUN
brj-25043	66	3	show	show	VERB
brj-25043	66	4	strong	strong	ADJ
brj-25043	66	5	predictive	predictive	ADJ
brj-25043	66	6	accuracy	accuracy	NOUN
brj-25043	66	7	(	(	PUNCT
brj-25043	66	8	r²	r²	VERB
brj-25043	66	9	>	>	X
brj-25043	66	10	0.90	0.90	NUM
brj-25043	66	11	)	)	PUNCT
brj-25043	66	12	,	,	PUNCT
brj-25043	66	13	with	with	ADP
brj-25043	66	14	exponential	exponential	ADJ
brj-25043	66	15	models	model	NOUN
brj-25043	66	16	excelling	excel	VERB
brj-25043	66	17	in	in	ADP
brj-25043	66	18	dynamic	dynamic	ADJ
brj-25043	66	19	phases	phase	NOUN
brj-25043	66	20	and	and	CCONJ
brj-25043	66	21	gaussian	gaussian	NOUN
brj-25043	66	22	models	model	NOUN
brj-25043	66	23	performing	perform	VERB
brj-25043	66	24	well	well	ADV
brj-25043	66	25	for	for	ADP
brj-25043	66	26	heterogeneous	heterogeneous	ADJ
brj-25043	66	27	wastes	waste	NOUN
brj-25043	66	28	model	model	NOUN
brj-25043	66	29	main	main	ADJ
brj-25043	66	30	target	target	NOUN
brj-25043	66	31	model	model	NOUN
brj-25043	66	32	parameters	parameter	NOUN
brj-25043	66	33	goodness	goodness	PROPN
brj-25043	66	34	of	of	ADP
brj-25043	66	35	fit	fit	ADJ
brj-25043	66	36	r2	r2	PROPN
brj-25043	66	37	sub	sub	NOUN
brj-25043	66	38	-	-	NOUN
brj-25043	66	39	target	target	NOUN
brj-25043	66	40	(	(	PUNCT
brj-25043	66	41	if	if	SCONJ
brj-25043	66	42	it	it	PRON
brj-25043	66	43	exists	exist	VERB
brj-25043	66	44	)	)	PUNCT
brj-25043	66	45	references	reference	NOUN
brj-25043	66	46	l	l	NOUN
brj-25043	66	47	in	in	ADP
brj-25043	66	48	e	e	PROPN
brj-25043	66	49	a	a	DET
brj-25043	66	50	r	r	NOUN
brj-25043	66	51	organic	organic	ADJ
brj-25043	66	52	fraction	fraction	NOUN
brj-25043	66	53	of	of	ADP
brj-25043	66	54	msw	msw	NOUN
brj-25043	66	55	codigested	codigeste	VERB
brj-25043	66	56	with	with	ADP
brj-25043	66	57	mswi	mswi	NOUN
brj-25043	66	58	ashes	ashe	NOUN
brj-25043	66	59	𝒂	𝒂	PRON
brj-25043	66	60	=	=	SYM
brj-25043	66	61	0.8360	0.8360	NUM
brj-25043	66	62	,	,	PUNCT
brj-25043	66	63	𝒃	𝒃	ADP
brj-25043	66	64	=	=	NUM
brj-25043	66	65	0.1641	0.1641	NUM
brj-25043	66	66	𝒂	𝒂	NOUN
brj-25043	66	67	=	=	SYM
brj-25043	66	68	𝟏𝟔.	𝟏𝟔.	PROPN
brj-25043	66	69	𝟕𝟎𝟖𝟓	𝟕𝟎𝟖𝟓	NUM
brj-25043	66	70	,	,	PUNCT
brj-25043	66	71	𝒃	𝒃	ADP
brj-25043	66	72	=	=	SYM
brj-25043	66	73	0.4283	0.4283	NUM
brj-25043	66	74	the	the	DET
brj-25043	66	75	best	good	ADJ
brj-25043	66	76	r2	r2	NOUN
brj-25043	66	77	=	=	SYM
brj-25043	66	78	0.9579	0.9579	NUM
brj-25043	66	79	(	(	PUNCT
brj-25043	66	80	for	for	ADP
brj-25043	66	81	the	the	DET
brj-25043	66	82	ascending	ascend	VERB
brj-25043	66	83	limb	limb	NOUN
brj-25043	66	84	)	)	PUNCT
brj-25043	66	85	the	the	DET
brj-25043	66	86	best	good	ADJ
brj-25043	66	87	r2	r2	NOUN
brj-25043	66	88	=	=	NOUN
brj-25043	66	89	0.9211	0.9211	NUM
brj-25043	66	90	(	(	PUNCT
brj-25043	66	91	for	for	ADP
brj-25043	66	92	the	the	DET
brj-25043	66	93	descending	descend	VERB
brj-25043	66	94	limb	limb	NOUN
brj-25043	66	95	)	)	PUNCT
brj-25043	66	96	fa	fa	NOUN
brj-25043	66	97	/	/	SYM
brj-25043	66	98	msw	msw	NOUN
brj-25043	66	99	:	:	PUNCT
brj-25043	66	100	10	10	NUM
brj-25043	66	101	g	g	NOUN
brj-25043	66	102	l	l	NOUN
brj-25043	66	103	-1	-1	NOUN
brj-25043	66	104	bioreactor	bioreactor	NOUN
brj-25043	66	105	ba	ba	PROPN
brj-25043	66	106	/	/	SYM
brj-25043	66	107	msw	msw	NOUN
brj-25043	66	108	:	:	PUNCT
brj-25043	66	109	100	100	NUM
brj-25043	66	110	g	g	NOUN
brj-25043	66	111	l	l	NOUN
brj-25043	66	112	-1	-1	NOUN
brj-25043	66	113	bioreactor	bioreactor	NOUN
brj-25043	66	114	lo	lo	PROPN
brj-25043	66	115	et	et	PROPN
brj-25043	66	116	al	al	PROPN
brj-25043	66	117	.	.	PROPN
brj-25043	66	118	2010	2010	NUM
brj-25043	66	119	cow	cow	NOUN
brj-25043	66	120	dung	dung	NOUN
brj-25043	66	121	only	only	ADV
brj-25043	66	122	n	n	CCONJ
brj-25043	66	123	/	/	SYM
brj-25043	66	124	a	a	DET
brj-25043	66	125	r2	r2	NOUN
brj-25043	66	126	=	=	SYM
brj-25043	66	127	0.8850	0.8850	NUM
brj-25043	66	128	(	(	PUNCT
brj-25043	66	129	ascending	ascend	VERB
brj-25043	66	130	limb	limb	NOUN
brj-25043	66	131	)	)	PUNCT
brj-25043	66	132	r2	r2	NOUN
brj-25043	66	133	=	=	NOUN
brj-25043	66	134	0.9950	0.9950	NUM
brj-25043	66	135	(	(	PUNCT
brj-25043	66	136	descending	descend	VERB
brj-25043	66	137	limb	limb	NOUN
brj-25043	66	138	)	)	PUNCT
brj-25043	66	139	—	—	PUNCT
brj-25043	66	140	latinwo	latinwo	NOUN
brj-25043	66	141	and	and	CCONJ
brj-25043	66	142	agarry	agarry	PROPN
brj-25043	66	143	2015	2015	NUM
brj-25043	66	144	mixture	mixture	NOUN
brj-25043	66	145	of	of	ADP
brj-25043	66	146	cow	cow	NOUN
brj-25043	66	147	dung	dung	NOUN
brj-25043	66	148	and	and	CCONJ
brj-25043	66	149	plantain	plantain	NOUN
brj-25043	66	150	peels	peel	NOUN
brj-25043	66	151	n	n	CCONJ
brj-25043	66	152	/	/	SYM
brj-25043	66	153	a	a	DET
brj-25043	66	154	r2	r2	NOUN
brj-25043	66	155	=	=	SYM
brj-25043	66	156	0.8790	0.8790	NUM
brj-25043	66	157	(	(	PUNCT
brj-25043	66	158	ascending	ascend	VERB
brj-25043	66	159	limb	limb	NOUN
brj-25043	66	160	)	)	PUNCT
brj-25043	66	161	r2	r2	NOUN
brj-25043	66	162	=	=	PUNCT
brj-25043	67	1	0.9970	0.9970	NUM
brj-25043	67	2	(	(	PUNCT
brj-25043	67	3	descending	descend	VERB
brj-25043	67	4	limb	limb	NOUN
brj-25043	67	5	)	)	PUNCT
brj-25043	68	1	e	e	NOUN
brj-25043	68	2	x	x	PUNCT
brj-25043	68	3	p	p	X
brj-25043	68	4	o	o	X
brj-25043	68	5	n	n	ADP
brj-25043	68	6	e	e	NOUN
brj-25043	68	7	n	n	X
brj-25043	68	8	ti	ti	PROPN
brj-25043	68	9	a	a	DET
brj-25043	68	10	l	l	NOUN
brj-25043	68	11	landfill	landfill	NOUN
brj-25043	68	12	gas	gas	NOUN
brj-25043	68	13	generation	generation	NOUN
brj-25043	68	14	of	of	ADP
brj-25043	68	15	municipal	municipal	ADJ
brj-25043	68	16	solid	solid	ADJ
brj-25043	68	17	waste	waste	NOUN
brj-25043	68	18	after	after	ADP
brj-25043	68	19	mechanical	mechanical	ADJ
brj-25043	68	20	-	-	PUNCT
brj-25043	68	21	biological	biological	ADJ
brj-25043	68	22	treatment	treatment	NOUN
brj-25043	68	23	eight	eight	NUM
brj-25043	68	24	weeks	week	NOUN
brj-25043	68	25	,	,	PUNCT
brj-25043	68	26	rising	rise	VERB
brj-25043	68	27	limb	limb	NOUN
brj-25043	68	28	𝒂	𝒂	X
brj-25043	68	29	=	=	SYM
brj-25043	68	30	𝟎	𝟎	PROPN
brj-25043	68	31	,	,	PUNCT
brj-25043	68	32	𝒃	𝒃	NOUN
brj-25043	68	33	=	=	PUNCT
brj-25043	68	34	𝒆𝟎.𝟎𝟏𝟏𝟑	𝒆𝟎.𝟎𝟏𝟏𝟑	NUM
brj-25043	68	35	,	,	PUNCT
brj-25043	68	36	c	c	X
brj-25043	68	37	=	=	SYM
brj-25043	68	38	0.0803	0.0803	NUM
brj-25043	68	39	eight	eight	NUM
brj-25043	68	40	weeks	week	NOUN
brj-25043	68	41	,	,	PUNCT
brj-25043	68	42	falling	fall	VERB
brj-25043	68	43	limb	limb	NOUN
brj-25043	68	44	𝒂	𝒂	X
brj-25043	68	45	=	=	SYM
brj-25043	68	46	𝟎	𝟎	PROPN
brj-25043	68	47	,	,	PUNCT
brj-25043	68	48	𝒃	𝒃	NOUN
brj-25043	68	49	=	=	SYM
brj-25043	68	50	𝒆𝟎.𝟎𝟎𝟔𝟔	𝒆𝟎.𝟎𝟎𝟔𝟔	PROPN
brj-25043	68	51	,	,	PUNCT
brj-25043	68	52	c	c	NOUN
brj-25043	68	53	=	=	SYM
brj-25043	68	54	-0.0348	-0.0348	NOUN
brj-25043	68	55	15	15	NUM
brj-25043	68	56	weeks	week	NOUN
brj-25043	68	57	,	,	PUNCT
brj-25043	68	58	rising	rise	VERB
brj-25043	68	59	limb	limb	NOUN
brj-25043	68	60	𝒂	𝒂	X
brj-25043	68	61	=	=	SYM
brj-25043	68	62	𝟎	𝟎	PROPN
brj-25043	68	63	,	,	PUNCT
brj-25043	68	64	𝒃	𝒃	PROPN
brj-25043	68	65	=	=	SYM
brj-25043	68	66	𝒆𝟎.𝟎𝟏𝟎𝟖	𝒆𝟎.𝟎𝟏𝟎𝟖	PROPN
brj-25043	68	67	,	,	PUNCT
brj-25043	68	68	c	c	X
brj-25043	68	69	=	=	SYM
brj-25043	68	70	0.0773	0.0773	NUM
brj-25043	68	71	15	15	NUM
brj-25043	68	72	weeks	week	NOUN
brj-25043	68	73	,	,	PUNCT
brj-25043	68	74	falling	fall	VERB
brj-25043	68	75	limb	limb	NOUN
brj-25043	68	76	𝒂	𝒂	X
brj-25043	68	77	=	=	SYM
brj-25043	68	78	𝟎	𝟎	PROPN
brj-25043	68	79	,	,	PUNCT
brj-25043	68	80	𝒃	𝒃	NOUN
brj-25043	68	81	=	=	SYM
brj-25043	68	82	𝒆𝟎.𝟎𝟎𝟔𝟏	𝒆𝟎.𝟎𝟎𝟔𝟏	PROPN
brj-25043	68	83	,	,	PUNCT
brj-25043	68	84	c	c	NOUN
brj-25043	68	85	=	=	SYM
brj-25043	68	86	-0.0347	-0.0347	NOUN
brj-25043	68	87	r2	r2	NOUN
brj-25043	68	88	=	=	PUNCT
brj-25043	68	89	0.84	0.84	NUM
brj-25043	68	90	r2	r2	NOUN
brj-25043	68	91	=	=	PUNCT
brj-25043	68	92	0.90	0.90	NUM
brj-25043	68	93	r2	r2	NOUN
brj-25043	68	94	=	=	PUNCT
brj-25043	68	95	0.81	0.81	NUM
brj-25043	68	96	r2	r2	NOUN
brj-25043	68	97	=	=	NOUN
brj-25043	68	98	0.95	0.95	NUM
brj-25043	68	99	—	—	PUNCT
brj-25043	68	100	de	de	X
brj-25043	68	101	gioannis	gioannis	X
brj-25043	68	102	et	et	PROPN
brj-25043	68	103	al	al	PROPN
brj-25043	68	104	.	.	PROPN
brj-25043	68	105	2009	2009	NUM
brj-25043	68	106	organic	organic	ADJ
brj-25043	68	107	fraction	fraction	NOUN
brj-25043	68	108	of	of	ADP
brj-25043	68	109	msw	msw	NOUN
brj-25043	68	110	codigested	codigeste	VERB
brj-25043	68	111	with	with	ADP
brj-25043	68	112	mswi	mswi	NOUN
brj-25043	68	113	ashes	ashe	NOUN
brj-25043	68	114	rising	rise	VERB
brj-25043	68	115	limb	limb	NOUN
brj-25043	68	116	𝒂	𝒂	X
brj-25043	68	117	=	=	PUNCT
brj-25043	68	118	𝟐𝟎𝟏𝟔𝟎	𝟐𝟎𝟏𝟔𝟎	NUM
brj-25043	68	119	,	,	PUNCT
brj-25043	68	120	𝒃	𝒃	PROPN
brj-25043	68	121	=	=	SYM
brj-25043	68	122	𝟐𝟎𝟏𝟔𝟎	𝟐𝟎𝟏𝟔𝟎	NUM
brj-25043	68	123	,	,	PUNCT
brj-25043	68	124	c	c	X
brj-25043	68	125	=	=	SYM
brj-25043	68	126	8.135	8.135	NUM
brj-25043	68	127	×	×	NOUN
brj-25043	68	128	𝟏𝟎−𝟔	𝟏𝟎−𝟔	NOUN
brj-25043	68	129	falling	fall	VERB
brj-25043	68	130	limb	limb	NOUN
brj-25043	68	131	𝒂	𝒂	ADP
brj-25043	68	132	=	=	PUNCT
brj-25043	68	133	𝟎.	𝟎.	NOUN
brj-25043	68	134	𝟎𝟎𝟒𝟕	𝟎𝟎𝟒𝟕	NUM
brj-25043	68	135	,	,	PUNCT
brj-25043	68	136	𝒃	𝒃	ADP
brj-25043	68	137	=	=	SYM
brj-25043	68	138	𝟏𝟕𝟐.	𝟏𝟕𝟐.	PROPN
brj-25043	68	139	𝟔𝟓	𝟔𝟓	NUM
brj-25043	68	140	,	,	PUNCT
brj-25043	68	141	c	c	X
brj-25043	68	142	=	=	SYM
brj-25043	68	143	0.0936	0.0936	NUM
brj-25043	68	144	r2	r2	NOUN
brj-25043	68	145	=	=	PUNCT
brj-25043	68	146	0.9579	0.9579	NUM
brj-25043	68	147	r2	r2	NOUN
brj-25043	68	148	=	=	SYM
brj-25043	68	149	0.9288	0.9288	NUM
brj-25043	68	150	fa	fa	NOUN
brj-25043	68	151	/	/	SYM
brj-25043	68	152	msw	msw	NOUN
brj-25043	68	153	:	:	PUNCT
brj-25043	68	154	10	10	NUM
brj-25043	68	155	g	g	NOUN
brj-25043	68	156	l-1	l-1	NUM
brj-25043	68	157	fa	fa	PROPN
brj-25043	68	158	/	/	SYM
brj-25043	68	159	msw	msw	NOUN
brj-25043	68	160	:	:	PUNCT
brj-25043	68	161	10	10	NUM
brj-25043	68	162	g	g	NOUN
brj-25043	68	163	l-1	l-1	NOUN
brj-25043	69	1	lo	lo	PROPN
brj-25043	69	2	et	et	PROPN
brj-25043	69	3	al	al	PROPN
brj-25043	69	4	.	.	PROPN
brj-25043	69	5	2010	2010	NUM
brj-25043	69	6	cow	cow	NOUN
brj-25043	69	7	dung	dung	NOUN
brj-25043	69	8	only	only	ADV
brj-25043	69	9	n	n	CCONJ
brj-25043	69	10	/	/	SYM
brj-25043	69	11	a	a	DET
brj-25043	69	12	r2	r2	NOUN
brj-25043	69	13	=	=	PUNCT
brj-25043	70	1	0.9988	0.9988	NUM
brj-25043	70	2	(	(	PUNCT
brj-25043	70	3	rising	rise	VERB
brj-25043	70	4	limb	limb	NOUN
brj-25043	70	5	)	)	PUNCT
brj-25043	70	6	r2	r2	NOUN
brj-25043	70	7	=	=	SYM
brj-25043	70	8	0.9969	0.9969	NUM
brj-25043	70	9	(	(	PUNCT
brj-25043	70	10	falling	fall	VERB
brj-25043	70	11	limb	limb	NOUN
brj-25043	70	12	)	)	PUNCT
brj-25043	70	13	—	—	PUNCT
brj-25043	70	14	latinwo	latinwo	NOUN
brj-25043	70	15	and	and	CCONJ
brj-25043	70	16	agarry	agarry	PROPN
brj-25043	70	17	2015	2015	NUM
brj-25043	70	18	mixture	mixture	NOUN
brj-25043	70	19	of	of	ADP
brj-25043	70	20	cow	cow	NOUN
brj-25043	70	21	dung	dung	NOUN
brj-25043	70	22	and	and	CCONJ
brj-25043	70	23	plantain	plantain	NOUN
brj-25043	70	24	peels	peel	NOUN
brj-25043	70	25	n	n	CCONJ
brj-25043	70	26	/	/	SYM
brj-25043	70	27	a	a	DET
brj-25043	70	28	r2	r2	NOUN
brj-25043	70	29	=	=	PUNCT
brj-25043	70	30	0.9951	0.9951	NUM
brj-25043	70	31	(	(	PUNCT
brj-25043	70	32	rising	rise	VERB
brj-25043	70	33	limb	limb	NOUN
brj-25043	70	34	)	)	PUNCT
brj-25043	70	35	r2	r2	NOUN
brj-25043	70	36	=	=	SYM
brj-25043	70	37	0.9969	0.9969	NUM
brj-25043	70	38	(	(	PUNCT
brj-25043	70	39	falling	fall	VERB
brj-25043	70	40	limb	limb	NOUN
brj-25043	70	41	)	)	PUNCT
brj-25043	70	42	peer	peer	NOUN
brj-25043	70	43	-	-	PUNCT
brj-25043	70	44	reviewed	review	VERB
brj-25043	70	45	review	review	NOUN
brj-25043	70	46	article	article	NOUN
brj-25043	70	47	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	70	48	galal	galal	PROPN
brj-25043	70	49	et	et	PROPN
brj-25043	70	50	al	al	PROPN
brj-25043	70	51	.	.	PROPN
brj-25043	71	1	(	(	PUNCT
brj-25043	71	2	2025	2025	NUM
brj-25043	71	3	)	)	PUNCT
brj-25043	71	4	.	.	PUNCT
brj-25043	72	1	“	"	PUNCT
brj-25043	72	2	math	math	NOUN
brj-25043	72	3	modeling	modeling	NOUN
brj-25043	72	4	biogas	biogas	NOUN
brj-25043	72	5	production	production	NOUN
brj-25043	72	6	,	,	PUNCT
brj-25043	72	7	”	"	PUNCT
brj-25043	72	8	bioresources	bioresource	NOUN
brj-25043	72	9	20(4	20(4	NOUN
brj-25043	72	10	)	)	PUNCT
brj-25043	72	11	,	,	PUNCT
brj-25043	72	12	11237	11237	NUM
brj-25043	72	13	-	-	SYM
brj-25043	72	14	11266	11266	NUM
brj-25043	72	15	.	.	PUNCT
brj-25043	73	1	11242	11242	NUM
brj-25043	73	2	model	model	NOUN
brj-25043	73	3	main	main	ADJ
brj-25043	73	4	target	target	NOUN
brj-25043	73	5	model	model	NOUN
brj-25043	73	6	parameters	parameter	NOUN
brj-25043	73	7	goodness	goodness	PROPN
brj-25043	73	8	of	of	ADP
brj-25043	73	9	fit	fit	ADJ
brj-25043	73	10	r2	r2	PROPN
brj-25043	73	11	sub	sub	NOUN
brj-25043	73	12	-	-	NOUN
brj-25043	73	13	target	target	NOUN
brj-25043	73	14	(	(	PUNCT
brj-25043	73	15	if	if	SCONJ
brj-25043	73	16	it	it	PRON
brj-25043	73	17	exists	exist	VERB
brj-25043	73	18	)	)	PUNCT
brj-25043	73	19	references	reference	VERB
brj-25043	73	20	g	g	PROPN
brj-25043	73	21	a	a	DET
brj-25043	73	22	u	u	NOUN
brj-25043	73	23	s	s	PROPN
brj-25043	73	24	s	s	X
brj-25043	73	25	ia	ia	NOUN
brj-25043	73	26	n	n	ADV
brj-25043	73	27	m	m	NOUN
brj-25043	73	28	o	o	NOUN
brj-25043	73	29	d	d	X
brj-25043	73	30	e	e	X
brj-25043	73	31	l	l	X
brj-25043	73	32	organic	organic	ADJ
brj-25043	73	33	fraction	fraction	NOUN
brj-25043	73	34	of	of	ADP
brj-25043	73	35	msw	msw	NOUN
brj-25043	73	36	codigested	codigeste	VERB
brj-25043	73	37	with	with	ADP
brj-25043	73	38	mswi	mswi	NOUN
brj-25043	73	39	ashes	ashe	NOUN
brj-25043	73	40	𝒂	𝒂	X
brj-25043	73	41	=	=	SYM
brj-25043	73	42	𝟓.	𝟓.	X
brj-25043	73	43	𝟑𝟏𝟐	𝟑𝟏𝟐	NUM
brj-25043	73	44	,	,	PUNCT
brj-25043	73	45	t𝒎	t𝒎	X
brj-25043	73	46	=	=	SYM
brj-25043	73	47	𝟑𝟐.	𝟑𝟐.	PROPN
brj-25043	73	48	𝟔𝟖	𝟔𝟖	PROPN
brj-25043	73	49	,	,	PUNCT
brj-25043	73	50	b	b	X
brj-25043	73	51	=	=	SYM
brj-25043	73	52	3.05696	3.05696	NUM
brj-25043	73	53	the	the	DET
brj-25043	73	54	best	good	ADJ
brj-25043	73	55	r2	r2	NOUN
brj-25043	73	56	=	=	NOUN
brj-25043	73	57	0.9486	0.9486	NUM
brj-25043	73	58	fa	fa	NOUN
brj-25043	73	59	/	/	SYM
brj-25043	73	60	msw	msw	NOUN
brj-25043	73	61	:	:	PUNCT
brj-25043	73	62	20	20	NUM
brj-25043	73	63	g	g	NOUN
brj-25043	73	64	l-1	l-1	NOUN
brj-25043	74	1	lo	lo	PROPN
brj-25043	74	2	et	et	PROPN
brj-25043	74	3	al	al	PROPN
brj-25043	74	4	.	.	PROPN
brj-25043	74	5	2010	2010	NUM
brj-25043	74	6	heterogeneous	heterogeneous	ADJ
brj-25043	74	7	organic	organic	ADJ
brj-25043	74	8	and	and	CCONJ
brj-25043	74	9	inorganic	inorganic	ADJ
brj-25043	74	10	wastes	waste	NOUN
brj-25043	74	11	with	with	ADP
brj-25043	74	12	the	the	DET
brj-25043	74	13	organic	organic	ADJ
brj-25043	74	14	fraction	fraction	NOUN
brj-25043	74	15	of	of	ADP
brj-25043	74	16	municipal	municipal	ADJ
brj-25043	74	17	solid	solid	ADJ
brj-25043	74	18	waste	waste	NOUN
brj-25043	74	19	(	(	PUNCT
brj-25043	74	20	ofmsw	ofmsw	NOUN
brj-25043	74	21	)	)	PUNCT
brj-25043	74	22	𝑎	𝑎	PRON
brj-25043	74	23	=	=	SYM
brj-25043	74	24	57	57	NUM
brj-25043	74	25	,	,	PUNCT
brj-25043	74	26	t𝑚	t𝑚	NOUN
brj-25043	74	27	=	=	SYM
brj-25043	74	28	n	n	CCONJ
brj-25043	74	29	/	/	SYM
brj-25043	74	30	a	a	NOUN
brj-25043	74	31	,	,	PUNCT
brj-25043	74	32	b	b	NOUN
brj-25043	74	33	=	=	SYM
brj-25043	74	34	17.24	17.24	NUM
brj-25043	74	35	the	the	DET
brj-25043	74	36	best	good	ADJ
brj-25043	74	37	r2	r2	NOUN
brj-25043	74	38	=	=	NOUN
brj-25043	74	39	0.95	0.95	NUM
brj-25043	74	40	garden	garden	NOUN
brj-25043	74	41	wastes	waste	NOUN
brj-25043	74	42	(	(	PUNCT
brj-25043	74	43	9	9	NUM
brj-25043	74	44	–	–	SYM
brj-25043	74	45	11%vs	11%vs	ADJ
brj-25043	74	46	)	)	PUNCT
brj-25043	74	47	mixture	mixture	NOUN
brj-25043	74	48	with	with	ADP
brj-25043	74	49	the	the	DET
brj-25043	74	50	ofmsw	ofmsw	NOUN
brj-25043	74	51	(	(	PUNCT
brj-25043	74	52	2.5%vs	2.5%vs	NUM
brj-25043	74	53	)	)	PUNCT
brj-25043	74	54	nielfa	nielfa	NOUN
brj-25043	74	55	et	et	PROPN
brj-25043	74	56	al	al	PROPN
brj-25043	74	57	.	.	PROPN
brj-25043	74	58	2015	2015	NUM
brj-25043	74	59	peer	peer	NOUN
brj-25043	74	60	-	-	PUNCT
brj-25043	74	61	reviewed	review	VERB
brj-25043	74	62	review	review	NOUN
brj-25043	74	63	article	article	NOUN
brj-25043	74	64	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	74	65	galal	galal	PROPN
brj-25043	74	66	et	et	PROPN
brj-25043	74	67	al	al	PROPN
brj-25043	74	68	.	.	PROPN
brj-25043	75	1	(	(	PUNCT
brj-25043	75	2	2025	2025	NUM
brj-25043	75	3	)	)	PUNCT
brj-25043	75	4	.	.	PUNCT
brj-25043	76	1	“	"	PUNCT
brj-25043	76	2	math	math	NOUN
brj-25043	76	3	modeling	modeling	NOUN
brj-25043	76	4	biogas	biogas	NOUN
brj-25043	76	5	production	production	NOUN
brj-25043	76	6	,	,	PUNCT
brj-25043	76	7	”	"	PUNCT
brj-25043	76	8	bioresources	bioresource	NOUN
brj-25043	76	9	20(4	20(4	NOUN
brj-25043	76	10	)	)	PUNCT
brj-25043	76	11	,	,	PUNCT
brj-25043	76	12	11237	11237	NUM
brj-25043	76	13	-	-	SYM
brj-25043	76	14	11266	11266	NUM
brj-25043	76	15	.	.	PUNCT
brj-25043	77	1	11243	11243	NUM
brj-25043	77	2	linear	linear	PROPN
brj-25043	77	3	model	model	NOUN
brj-25043	77	4	the	the	DET
brj-25043	77	5	linear	linear	ADJ
brj-25043	77	6	model	model	NOUN
brj-25043	77	7	has	have	AUX
brj-25043	77	8	been	be	AUX
brj-25043	77	9	used	use	VERB
brj-25043	77	10	to	to	PART
brj-25043	77	11	simulate	simulate	VERB
brj-25043	77	12	and	and	CCONJ
brj-25043	77	13	predict	predict	VERB
brj-25043	77	14	the	the	DET
brj-25043	77	15	daily	daily	ADJ
brj-25043	77	16	biogas	biogas	NOUN
brj-25043	77	17	production	production	NOUN
brj-25043	77	18	resulting	result	VERB
brj-25043	77	19	from	from	ADP
brj-25043	77	20	ad	ad	NOUN
brj-25043	77	21	(	(	PUNCT
brj-25043	77	22	rossi	rossi	PROPN
brj-25043	77	23	et	et	PROPN
brj-25043	77	24	al	al	PROPN
brj-25043	77	25	.	.	PROPN
brj-25043	77	26	2022	2022	NUM
brj-25043	77	27	)	)	PUNCT
brj-25043	77	28	.	.	PUNCT
brj-25043	78	1	this	this	DET
brj-25043	78	2	model	model	NOUN
brj-25043	78	3	assumes	assume	VERB
brj-25043	78	4	that	that	SCONJ
brj-25043	78	5	the	the	DET
brj-25043	78	6	biogas	biogas	NOUN
brj-25043	78	7	production	production	NOUN
brj-25043	78	8	starts	start	VERB
brj-25043	78	9	at	at	ADP
brj-25043	78	10	an	an	DET
brj-25043	78	11	initial	initial	ADJ
brj-25043	78	12	time	time	NOUN
brj-25043	78	13	,	,	PUNCT
brj-25043	78	14	t𝒐	t𝒐	NOUN
brj-25043	78	15	with	with	ADP
brj-25043	78	16	a	a	DET
brj-25043	78	17	value	value	NOUN
brj-25043	78	18	p𝒐	p𝒐	NOUN
brj-25043	78	19	,	,	PUNCT
brj-25043	78	20	and	and	CCONJ
brj-25043	78	21	then	then	ADV
brj-25043	78	22	increases	increase	VERB
brj-25043	78	23	linearly	linearly	ADV
brj-25043	78	24	up	up	ADP
brj-25043	78	25	to	to	ADP
brj-25043	78	26	a	a	DET
brj-25043	78	27	maximum	maximum	ADJ
brj-25043	78	28	value	value	NOUN
brj-25043	78	29	p𝒎𝒂𝒙	p𝒎𝒂𝒙	NOUN
brj-25043	78	30	at	at	ADP
brj-25043	78	31	time	time	NOUN
brj-25043	78	32	t𝒎	t𝒎	ADP
brj-25043	78	33	,	,	PUNCT
brj-25043	78	34	after	after	ADP
brj-25043	78	35	which	which	PRON
brj-25043	78	36	it	it	PRON
brj-25043	78	37	decreases	decrease	VERB
brj-25043	78	38	linearly	linearly	ADV
brj-25043	78	39	to	to	ADP
brj-25043	78	40	a	a	DET
brj-25043	78	41	final	final	ADJ
brj-25043	78	42	value	value	NOUN
brj-25043	78	43	,	,	PUNCT
brj-25043	78	44	p𝒇	p𝒇	NOUN
brj-25043	78	45	at	at	ADP
brj-25043	78	46	time	time	NOUN
brj-25043	78	47	t𝒇.	t𝒇.	ADP
brj-25043	78	48	this	this	DET
brj-25043	78	49	plot	plot	NOUN
brj-25043	78	50	has	have	VERB
brj-25043	78	51	two	two	NUM
brj-25043	78	52	limbs	limb	NOUN
brj-25043	78	53	,	,	PUNCT
brj-25043	78	54	an	an	DET
brj-25043	78	55	ascending	ascend	VERB
brj-25043	78	56	limb	limb	NOUN
brj-25043	78	57	for	for	ADP
brj-25043	78	58	t𝒐	t𝒐	PRON
brj-25043	78	59	≤	≤	NUM
brj-25043	78	60	𝑡	𝑡	PROPN
brj-25043	78	61	≤	≤	ADV
brj-25043	78	62	t𝒎	t𝒎	NOUN
brj-25043	78	63	and	and	CCONJ
brj-25043	78	64	a	a	DET
brj-25043	78	65	descending	descend	VERB
brj-25043	78	66	one	one	NUM
brj-25043	78	67	for	for	ADP
brj-25043	78	68	t𝒎	t𝒎	NOUN
brj-25043	78	69	≤	≤	NUM
brj-25043	78	70	𝑡	𝑡	PROPN
brj-25043	78	71	≤	≤	ADJ
brj-25043	78	72	t𝒇	t𝒇	NOUN
brj-25043	78	73	.	.	PUNCT
brj-25043	79	1	assuming	assume	VERB
brj-25043	79	2	the	the	DET
brj-25043	79	3	plot	plot	NOUN
brj-25043	79	4	similarity	similarity	NOUN
brj-25043	79	5	about	about	ADP
brj-25043	79	6	the	the	DET
brj-25043	79	7	maximum	maximum	ADJ
brj-25043	79	8	value	value	NOUN
brj-25043	79	9	,	,	PUNCT
brj-25043	79	10	the	the	DET
brj-25043	79	11	model	model	NOUN
brj-25043	79	12	equation	equation	NOUN
brj-25043	79	13	can	can	AUX
brj-25043	79	14	be	be	AUX
brj-25043	79	15	written	write	VERB
brj-25043	79	16	as	as	ADP
brj-25043	79	17	,	,	PUNCT
brj-25043	79	18	p𝒃𝒈	p𝒃𝒈	ADJ
brj-25043	79	19	=	=	PUNCT
brj-25043	79	20	{	{	PUNCT
brj-25043	80	1	𝑎	𝑎	PRON
brj-25043	80	2	+	+	PROPN
brj-25043	80	3	b	b	X
brj-25043	80	4	(	(	PUNCT
brj-25043	80	5	t	t	PROPN
brj-25043	80	6	−	−	PROPN
brj-25043	80	7	t𝒐	t𝒐	PROPN
brj-25043	80	8	)	)	PUNCT
brj-25043	80	9	,	,	PUNCT
brj-25043	80	10	t𝒐	t𝒐	PROPN
brj-25043	80	11	≤	≤	NUM
brj-25043	80	12	𝑡	𝑡	VERB
brj-25043	80	13	≤	≤	NUM
brj-25043	80	14	t𝒎	t𝒎	ADP
brj-25043	80	15	𝑎	𝑎	NOUN
brj-25043	80	16	+	+	X
brj-25043	80	17	𝑏	𝑏	NOUN
brj-25043	80	18	(	(	PUNCT
brj-25043	80	19	t	t	PROPN
brj-25043	80	20	−	−	PROPN
brj-25043	80	21	t𝒎	t𝒎	NOUN
brj-25043	80	22	)	)	PUNCT
brj-25043	80	23	,	,	PUNCT
brj-25043	80	24	t𝒎	t𝒎	VERB
brj-25043	80	25	≤	≤	NUM
brj-25043	80	26	𝑡	𝑡	PROPN
brj-25043	80	27	≤	≤	ADJ
brj-25043	80	28	t𝒇	t𝒇	DET
brj-25043	80	29	(	(	PUNCT
brj-25043	80	30	1	1	NUM
brj-25043	80	31	)	)	PUNCT
brj-25043	80	32	where	where	SCONJ
brj-25043	80	33	𝑎	𝑎	NOUN
brj-25043	80	34	and	and	CCONJ
brj-25043	80	35	𝑏	𝑏	NOUN
brj-25043	80	36	are	be	AUX
brj-25043	80	37	two	two	NUM
brj-25043	80	38	dimensionless	dimensionless	NOUN
brj-25043	80	39	constants	constant	NOUN
brj-25043	80	40	to	to	PART
brj-25043	80	41	be	be	AUX
brj-25043	80	42	determined	determine	VERB
brj-25043	80	43	for	for	ADP
brj-25043	80	44	the	the	DET
brj-25043	80	45	best	good	ADJ
brj-25043	80	46	fitting	fitting	NOUN
brj-25043	80	47	of	of	ADP
brj-25043	80	48	the	the	DET
brj-25043	80	49	experimental	experimental	ADJ
brj-25043	80	50	data	datum	NOUN
brj-25043	80	51	.	.	PUNCT
brj-25043	81	1	they	they	PRON
brj-25043	81	2	may	may	AUX
brj-25043	81	3	be	be	AUX
brj-25043	81	4	expressed	express	VERB
brj-25043	81	5	as	as	ADP
brj-25043	81	6	some	some	DET
brj-25043	81	7	other	other	ADJ
brj-25043	81	8	constants	constant	NOUN
brj-25043	81	9	multiplied	multiply	VERB
brj-25043	81	10	by	by	ADP
brj-25043	81	11	p𝒐	p𝒐	NOUN
brj-25043	81	12	and	and	CCONJ
brj-25043	81	13	(	(	PUNCT
brj-25043	81	14	p𝒎𝒂𝒙−p𝒐	p𝒎𝒂𝒙−p𝒐	NOUN
brj-25043	81	15	t𝒎−t𝒐	t𝒎−t𝒐	NOUN
brj-25043	81	16	)	)	PUNCT
brj-25043	81	17	,	,	PUNCT
brj-25043	81	18	respectively	respectively	ADV
brj-25043	81	19	.	.	PUNCT
brj-25043	82	1	generally	generally	ADV
brj-25043	82	2	,	,	PUNCT
brj-25043	82	3	this	this	DET
brj-25043	82	4	model	model	NOUN
brj-25043	82	5	is	be	AUX
brj-25043	82	6	considered	consider	VERB
brj-25043	82	7	the	the	DET
brj-25043	82	8	simplest	simple	ADJ
brj-25043	82	9	one	one	NOUN
brj-25043	82	10	,	,	PUNCT
brj-25043	82	11	but	but	CCONJ
brj-25043	82	12	its	its	PRON
brj-25043	82	13	statistical	statistical	ADJ
brj-25043	82	14	indices	index	NOUN
brj-25043	82	15	are	be	AUX
brj-25043	82	16	not	not	PART
brj-25043	82	17	as	as	ADV
brj-25043	82	18	satisfying	satisfying	ADJ
brj-25043	82	19	as	as	ADP
brj-25043	82	20	those	those	PRON
brj-25043	82	21	of	of	ADP
brj-25043	82	22	some	some	DET
brj-25043	82	23	other	other	ADJ
brj-25043	82	24	models	model	NOUN
brj-25043	82	25	.	.	PUNCT
brj-25043	83	1	however	however	ADV
brj-25043	83	2	,	,	PUNCT
brj-25043	83	3	this	this	DET
brj-25043	83	4	model	model	NOUN
brj-25043	83	5	,	,	PUNCT
brj-25043	83	6	along	along	ADP
brj-25043	83	7	with	with	ADP
brj-25043	83	8	the	the	DET
brj-25043	83	9	exponential	exponential	ADJ
brj-25043	83	10	one	one	NOUN
brj-25043	83	11	,	,	PUNCT
brj-25043	83	12	was	be	AUX
brj-25043	83	13	shown	show	VERB
brj-25043	83	14	by	by	ADP
brj-25043	83	15	lo	lo	PROPN
brj-25043	83	16	et	et	PROPN
brj-25043	83	17	al	al	PROPN
brj-25043	83	18	.	.	PROPN
brj-25043	84	1	(	(	PUNCT
brj-25043	84	2	2010	2010	NUM
brj-25043	84	3	)	)	PUNCT
brj-25043	85	1	to	to	PART
brj-25043	85	2	have	have	VERB
brj-25043	85	3	a	a	DET
brj-25043	85	4	better	well	ADJ
brj-25043	85	5	plot	plot	NOUN
brj-25043	85	6	for	for	ADP
brj-25043	85	7	the	the	DET
brj-25043	85	8	descending	descend	VERB
brj-25043	85	9	limb	limb	NOUN
brj-25043	85	10	for	for	ADP
brj-25043	85	11	the	the	DET
brj-25043	85	12	ba	ba	PROPN
brj-25043	85	13	/	/	SYM
brj-25043	85	14	msw	msw	NOUN
brj-25043	85	15	100	100	NUM
brj-25043	85	16	g	g	NOUN
brj-25043	85	17	l	l	NOUN
brj-25043	85	18	-1	-1	NOUN
brj-25043	85	19	bioreactor	bioreactor	NOUN
brj-25043	85	20	in	in	ADP
brj-25043	85	21	the	the	DET
brj-25043	85	22	process	process	NOUN
brj-25043	85	23	of	of	ADP
brj-25043	85	24	biogas	biogas	NOUN
brj-25043	85	25	production	production	NOUN
brj-25043	85	26	from	from	ADP
brj-25043	85	27	the	the	DET
brj-25043	85	28	organic	organic	ADJ
brj-25043	85	29	fraction	fraction	NOUN
brj-25043	85	30	of	of	ADP
brj-25043	85	31	msw	msw	NOUN
brj-25043	85	32	co	co	VERB
brj-25043	85	33	-	-	VERB
brj-25043	85	34	digested	digested	ADJ
brj-25043	85	35	with	with	ADP
brj-25043	85	36	mswi	mswi	NOUN
brj-25043	85	37	ashes	ashe	NOUN
brj-25043	85	38	.	.	PUNCT
brj-25043	86	1	moreover	moreover	ADV
brj-25043	86	2	,	,	PUNCT
brj-25043	86	3	this	this	DET
brj-25043	86	4	model	model	NOUN
brj-25043	86	5	was	be	AUX
brj-25043	86	6	employed	employ	VERB
brj-25043	86	7	to	to	PART
brj-25043	86	8	simulate	simulate	VERB
brj-25043	86	9	the	the	DET
brj-25043	86	10	biogas	biogas	NOUN
brj-25043	86	11	production	production	NOUN
brj-25043	86	12	resulting	result	VERB
brj-25043	86	13	from	from	ADP
brj-25043	86	14	cow	cow	NOUN
brj-25043	86	15	dung	dung	NOUN
brj-25043	86	16	only	only	ADV
brj-25043	86	17	and	and	CCONJ
brj-25043	86	18	cow	cow	NOUN
brj-25043	86	19	dung	dung	NOUN
brj-25043	86	20	with	with	ADP
brj-25043	86	21	plantain	plantain	NOUN
brj-25043	86	22	peels	peel	NOUN
brj-25043	86	23	(	(	PUNCT
brj-25043	86	24	latinwo	latinwo	NOUN
brj-25043	86	25	and	and	CCONJ
brj-25043	86	26	agarry	agarry	NOUN
brj-25043	86	27	2015	2015	NUM
brj-25043	86	28	)	)	PUNCT
brj-25043	86	29	.	.	PUNCT
brj-25043	87	1	it	it	PRON
brj-25043	87	2	showed	show	VERB
brj-25043	87	3	an	an	DET
brj-25043	87	4	r2	r2	NOUN
brj-25043	87	5	of	of	ADP
brj-25043	87	6	0.885	0.885	NUM
brj-25043	87	7	for	for	ADP
brj-25043	87	8	the	the	DET
brj-25043	87	9	ascending	ascend	VERB
brj-25043	87	10	limb	limb	NOUN
brj-25043	87	11	and	and	CCONJ
brj-25043	87	12	0.995	0.995	NUM
brj-25043	87	13	for	for	ADP
brj-25043	87	14	the	the	DET
brj-25043	87	15	descending	descend	VERB
brj-25043	87	16	one	one	NUM
brj-25043	87	17	in	in	ADP
brj-25043	87	18	the	the	DET
brj-25043	87	19	first	first	ADJ
brj-25043	87	20	case	case	NOUN
brj-25043	87	21	,	,	PUNCT
brj-25043	87	22	while	while	SCONJ
brj-25043	87	23	it	it	PRON
brj-25043	87	24	was	be	AUX
brj-25043	87	25	0.879	0.879	NUM
brj-25043	87	26	and	and	CCONJ
brj-25043	87	27	0.997	0.997	NUM
brj-25043	87	28	for	for	ADP
brj-25043	87	29	the	the	DET
brj-25043	87	30	ascending	ascend	VERB
brj-25043	87	31	and	and	CCONJ
brj-25043	87	32	descending	descend	VERB
brj-25043	87	33	limbs	limb	NOUN
brj-25043	87	34	,	,	PUNCT
brj-25043	87	35	respectively	respectively	ADV
brj-25043	87	36	,	,	PUNCT
brj-25043	87	37	in	in	ADP
brj-25043	87	38	the	the	DET
brj-25043	87	39	second	second	ADJ
brj-25043	87	40	case	case	NOUN
brj-25043	87	41	.	.	PUNCT
brj-25043	88	1	these	these	DET
brj-25043	88	2	correlation	correlation	NOUN
brj-25043	88	3	values	value	NOUN
brj-25043	88	4	are	be	AUX
brj-25043	88	5	not	not	PART
brj-25043	88	6	that	that	PRON
brj-25043	88	7	satisfying	satisfy	VERB
brj-25043	88	8	in	in	ADP
brj-25043	88	9	comparison	comparison	NOUN
brj-25043	88	10	with	with	ADP
brj-25043	88	11	the	the	DET
brj-25043	88	12	other	other	ADJ
brj-25043	88	13	models	model	NOUN
brj-25043	88	14	used	use	VERB
brj-25043	88	15	in	in	ADP
brj-25043	88	16	the	the	DET
brj-25043	88	17	same	same	ADJ
brj-25043	88	18	study	study	NOUN
brj-25043	88	19	.	.	PUNCT
brj-25043	89	1	nevertheless	nevertheless	ADV
brj-25043	89	2	,	,	PUNCT
brj-25043	89	3	linear	linear	ADJ
brj-25043	89	4	models	model	NOUN
brj-25043	89	5	can	can	AUX
brj-25043	89	6	still	still	ADV
brj-25043	89	7	be	be	AUX
brj-25043	89	8	valuable	valuable	ADJ
brj-25043	89	9	for	for	ADP
brj-25043	89	10	first‑cut	first‑cut	VERB
brj-25043	89	11	assessments	assessment	NOUN
brj-25043	89	12	or	or	CCONJ
brj-25043	89	13	when	when	SCONJ
brj-25043	89	14	computational	computational	ADJ
brj-25043	89	15	simplicity	simplicity	NOUN
brj-25043	89	16	is	be	AUX
brj-25043	89	17	paramount	paramount	ADJ
brj-25043	89	18	.	.	PUNCT
brj-25043	90	1	exponential	exponential	ADJ
brj-25043	90	2	model	model	NOUN
brj-25043	90	3	this	this	DET
brj-25043	90	4	model	model	NOUN
brj-25043	90	5	proposes	propose	VERB
brj-25043	90	6	an	an	DET
brj-25043	90	7	exponential	exponential	ADJ
brj-25043	90	8	increase	increase	NOUN
brj-25043	90	9	in	in	ADP
brj-25043	90	10	the	the	DET
brj-25043	90	11	daily	daily	ADJ
brj-25043	90	12	biogas	biogas	NOUN
brj-25043	90	13	production	production	NOUN
brj-25043	90	14	with	with	ADP
brj-25043	90	15	time	time	NOUN
brj-25043	90	16	up	up	ADP
brj-25043	90	17	to	to	ADP
brj-25043	90	18	an	an	DET
brj-25043	90	19	inevitable	inevitable	ADJ
brj-25043	90	20	climax	climax	NOUN
brj-25043	90	21	,	,	PUNCT
brj-25043	90	22	and	and	CCONJ
brj-25043	90	23	then	then	ADV
brj-25043	90	24	it	it	PRON
brj-25043	90	25	would	would	AUX
brj-25043	90	26	decrease	decrease	VERB
brj-25043	90	27	exponentially	exponentially	ADV
brj-25043	90	28	to	to	ADP
brj-25043	90	29	zero	zero	NUM
brj-25043	90	30	(	(	PUNCT
brj-25043	90	31	de	de	X
brj-25043	90	32	gioannis	gioannis	X
brj-25043	90	33	et	et	PROPN
brj-25043	90	34	al	al	PROPN
brj-25043	90	35	.	.	PROPN
brj-25043	90	36	2009	2009	NUM
brj-25043	90	37	;	;	PUNCT
brj-25043	90	38	lo	lo	PROPN
brj-25043	90	39	et	et	PROPN
brj-25043	90	40	al	al	PROPN
brj-25043	90	41	.	.	PROPN
brj-25043	90	42	2010	2010	NUM
brj-25043	90	43	;	;	PUNCT
brj-25043	90	44	latinwo	latinwo	NOUN
brj-25043	90	45	and	and	CCONJ
brj-25043	90	46	agarry	agarry	NOUN
brj-25043	90	47	2015	2015	NUM
brj-25043	90	48	)	)	PUNCT
brj-25043	90	49	.	.	PUNCT
brj-25043	91	1	the	the	DET
brj-25043	91	2	model	model	NOUN
brj-25043	91	3	equation	equation	NOUN
brj-25043	91	4	is	be	AUX
brj-25043	91	5	given	give	VERB
brj-25043	91	6	by	by	ADP
brj-25043	91	7	eq	eq	ADJ
brj-25043	91	8	.	.	PROPN
brj-25043	91	9	2	2	NUM
brj-25043	91	10	,	,	PUNCT
brj-25043	91	11	p𝒃𝒈	p𝒃𝒈	VERB
brj-25043	91	12	=	=	PUNCT
brj-25043	91	13	a	a	DET
brj-25043	91	14	+	+	NUM
brj-25043	91	15	b	b	NOUN
brj-25043	91	16	exp	exp	NOUN
brj-25043	91	17	(	(	PUNCT
brj-25043	91	18	𝑐𝑡	𝑐𝑡	PROPN
brj-25043	91	19	)	)	PUNCT
brj-25043	91	20	(	(	PUNCT
brj-25043	91	21	2	2	X
brj-25043	91	22	)	)	PUNCT
brj-25043	91	23	where	where	SCONJ
brj-25043	91	24	a	a	PRON
brj-25043	91	25	and	and	CCONJ
brj-25043	91	26	b	b	NOUN
brj-25043	91	27	are	be	AUX
brj-25043	91	28	two	two	NUM
brj-25043	91	29	constants	constant	NOUN
brj-25043	91	30	(	(	PUNCT
brj-25043	91	31	𝐿	𝐿	PROPN
brj-25043	91	32	𝐾𝑔−1𝑑−1	𝐾𝑔−1𝑑−1	PROPN
brj-25043	91	33	)	)	PUNCT
brj-25043	91	34	while	while	SCONJ
brj-25043	91	35	c	c	PROPN
brj-25043	91	36	is	be	AUX
brj-25043	91	37	another	another	DET
brj-25043	91	38	constant	constant	ADJ
brj-25043	91	39	(	(	PUNCT
brj-25043	91	40	𝑑−1	𝑑−1	PROPN
brj-25043	91	41	)	)	PUNCT
brj-25043	91	42	,	,	PUNCT
brj-25043	91	43	the	the	DET
brj-25043	91	44	latter	latter	NOUN
brj-25043	91	45	has	have	VERB
brj-25043	91	46	a	a	DET
brj-25043	91	47	positive	positive	ADJ
brj-25043	91	48	value	value	NOUN
brj-25043	91	49	for	for	ADP
brj-25043	91	50	the	the	DET
brj-25043	91	51	rising	rise	VERB
brj-25043	91	52	limb	limb	NOUN
brj-25043	91	53	and	and	CCONJ
brj-25043	91	54	a	a	DET
brj-25043	91	55	negative	negative	ADJ
brj-25043	91	56	value	value	NOUN
brj-25043	91	57	for	for	ADP
brj-25043	91	58	the	the	DET
brj-25043	91	59	falling	fall	VERB
brj-25043	91	60	one	one	NUM
brj-25043	91	61	.	.	PUNCT
brj-25043	92	1	de	de	X
brj-25043	92	2	gioannis	gioannis	X
brj-25043	92	3	et	et	PROPN
brj-25043	92	4	al	al	PROPN
brj-25043	92	5	.	.	PROPN
brj-25043	92	6	(	(	PUNCT
brj-25043	92	7	2009	2009	NUM
brj-25043	92	8	)	)	PUNCT
brj-25043	92	9	used	use	VERB
brj-25043	92	10	this	this	DET
brj-25043	92	11	model	model	NOUN
brj-25043	92	12	in	in	ADP
brj-25043	92	13	its	its	PRON
brj-25043	92	14	differential	differential	ADJ
brj-25043	92	15	form	form	NOUN
brj-25043	92	16	to	to	PART
brj-25043	92	17	simulate	simulate	VERB
brj-25043	92	18	municipal	municipal	ADJ
brj-25043	92	19	solid	solid	ADJ
brj-25043	92	20	waste	waste	NOUN
brj-25043	92	21	(	(	PUNCT
brj-25043	92	22	msw	msw	NOUN
brj-25043	92	23	)	)	PUNCT
brj-25043	92	24	landfill	landfill	NOUN
brj-25043	92	25	gas	gas	NOUN
brj-25043	92	26	generation	generation	NOUN
brj-25043	92	27	after	after	ADP
brj-25043	92	28	mechanical	mechanical	ADJ
brj-25043	92	29	biological	biological	ADJ
brj-25043	92	30	treatment	treatment	NOUN
brj-25043	92	31	.	.	PUNCT
brj-25043	93	1	their	their	PRON
brj-25043	93	2	study	study	NOUN
brj-25043	93	3	aimed	aim	VERB
brj-25043	93	4	to	to	PART
brj-25043	93	5	estimate	estimate	VERB
brj-25043	93	6	the	the	DET
brj-25043	93	7	model	model	NOUN
brj-25043	93	8	constants	constant	NOUN
brj-25043	93	9	after	after	ADP
brj-25043	93	10	8	8	NUM
brj-25043	93	11	and	and	CCONJ
brj-25043	93	12	15	15	NUM
brj-25043	93	13	weeks	week	NOUN
brj-25043	93	14	.	.	PUNCT
brj-25043	94	1	regarding	regard	VERB
brj-25043	94	2	r2	r2	PROPN
brj-25043	94	3	,	,	PUNCT
brj-25043	94	4	the	the	DET
brj-25043	94	5	model	model	NOUN
brj-25043	94	6	accuracy	accuracy	NOUN
brj-25043	94	7	showed	show	VERB
brj-25043	94	8	0.84	0.84	NUM
brj-25043	94	9	and	and	CCONJ
brj-25043	94	10	0.90	0.90	NUM
brj-25043	94	11	for	for	ADP
brj-25043	94	12	the	the	DET
brj-25043	94	13	rising	rise	VERB
brj-25043	94	14	and	and	CCONJ
brj-25043	94	15	falling	fall	VERB
brj-25043	94	16	limbs	limb	NOUN
brj-25043	94	17	,	,	PUNCT
brj-25043	94	18	respectively	respectively	ADV
brj-25043	94	19	,	,	PUNCT
brj-25043	94	20	in	in	ADP
brj-25043	94	21	the	the	DET
brj-25043	94	22	case	case	NOUN
brj-25043	94	23	of	of	ADP
brj-25043	94	24	eight	eight	NUM
brj-25043	94	25	weeks	week	NOUN
brj-25043	94	26	of	of	ADP
brj-25043	94	27	gasification	gasification	NOUN
brj-25043	94	28	,	,	PUNCT
brj-25043	94	29	while	while	SCONJ
brj-25043	94	30	it	it	PRON
brj-25043	94	31	was	be	AUX
brj-25043	94	32	0.81	0.81	NUM
brj-25043	94	33	and	and	CCONJ
brj-25043	94	34	0.95	0.95	NUM
brj-25043	94	35	for	for	ADP
brj-25043	94	36	15	15	NUM
brj-25043	94	37	weeks	week	NOUN
brj-25043	94	38	.	.	PUNCT
brj-25043	95	1	moreover	moreover	ADV
brj-25043	95	2	,	,	PUNCT
brj-25043	95	3	lo	lo	PROPN
brj-25043	95	4	et	et	PROPN
brj-25043	95	5	al	al	PROPN
brj-25043	95	6	.	.	PROPN
brj-25043	95	7	(	(	PUNCT
brj-25043	95	8	2010	2010	NUM
brj-25043	95	9	)	)	PUNCT
brj-25043	95	10	utilized	utilize	VERB
brj-25043	95	11	the	the	DET
brj-25043	95	12	exponential	exponential	ADJ
brj-25043	95	13	model	model	NOUN
brj-25043	95	14	in	in	ADP
brj-25043	95	15	their	their	PRON
brj-25043	95	16	work	work	NOUN
brj-25043	95	17	mentioned	mention	VERB
brj-25043	95	18	above	above	ADV
brj-25043	95	19	,	,	PUNCT
brj-25043	95	20	where	where	SCONJ
brj-25043	95	21	the	the	DET
brj-25043	95	22	best	good	ADJ
brj-25043	95	23	r2	r2	NOUN
brj-25043	95	24	values	value	NOUN
brj-25043	95	25	were	be	AUX
brj-25043	95	26	0.9579	0.9579	NUM
brj-25043	95	27	and	and	CCONJ
brj-25043	95	28	0.9288	0.9288	NUM
brj-25043	95	29	for	for	ADP
brj-25043	95	30	the	the	DET
brj-25043	95	31	rising	rise	VERB
brj-25043	95	32	and	and	CCONJ
brj-25043	95	33	falling	fall	VERB
brj-25043	95	34	limbs	limb	NOUN
brj-25043	95	35	,	,	PUNCT
brj-25043	95	36	respectively	respectively	ADV
brj-25043	95	37	,	,	PUNCT
brj-25043	95	38	and	and	CCONJ
brj-25043	95	39	both	both	PRON
brj-25043	95	40	were	be	AUX
brj-25043	95	41	achieved	achieve	VERB
brj-25043	95	42	in	in	ADP
brj-25043	95	43	the	the	DET
brj-25043	95	44	case	case	NOUN
brj-25043	95	45	of	of	ADP
brj-25043	95	46	fa	fa	PROPN
brj-25043	95	47	/	/	SYM
brj-25043	95	48	msw	msw	NOUN
brj-25043	95	49	10	10	NUM
brj-25043	95	50	g	g	PROPN
brj-25043	95	51	l-1	l-1	NOUN
brj-25043	95	52	.	.	PUNCT
brj-25043	96	1	furthermore	furthermore	ADV
brj-25043	96	2	,	,	PUNCT
brj-25043	96	3	latinwo	latinwo	NOUN
brj-25043	96	4	and	and	CCONJ
brj-25043	96	5	agarry	agarry	PROPN
brj-25043	96	6	(	(	PUNCT
brj-25043	96	7	2015	2015	NUM
brj-25043	96	8	)	)	PUNCT
brj-25043	96	9	have	have	AUX
brj-25043	96	10	employed	employ	VERB
brj-25043	96	11	this	this	DET
brj-25043	96	12	model	model	NOUN
brj-25043	96	13	to	to	PART
brj-25043	96	14	simulate	simulate	VERB
brj-25043	96	15	biogas	biogas	NOUN
brj-25043	96	16	production	production	NOUN
brj-25043	96	17	resulting	result	VERB
brj-25043	96	18	from	from	ADP
brj-25043	96	19	both	both	DET
brj-25043	96	20	cow	cow	NOUN
brj-25043	96	21	dung	dung	NOUN
brj-25043	96	22	and	and	CCONJ
brj-25043	96	23	cow	cow	NOUN
brj-25043	96	24	dung	dung	NOUN
brj-25043	96	25	activated	activate	VERB
brj-25043	96	26	by	by	ADP
brj-25043	96	27	plantain	plantain	NOUN
brj-25043	96	28	peels	peel	NOUN
brj-25043	96	29	,	,	PUNCT
brj-25043	96	30	showing	show	VERB
brj-25043	96	31	outstanding	outstanding	ADJ
brj-25043	96	32	representation	representation	NOUN
brj-25043	96	33	in	in	ADP
brj-25043	96	34	both	both	DET
brj-25043	96	35	cases	case	NOUN
brj-25043	96	36	.	.	PUNCT
brj-25043	97	1	the	the	DET
brj-25043	97	2	r2	r2	PROPN
brj-25043	97	3	peer	peer	NOUN
brj-25043	97	4	-	-	PUNCT
brj-25043	97	5	reviewed	review	VERB
brj-25043	97	6	review	review	NOUN
brj-25043	97	7	article	article	NOUN
brj-25043	97	8	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	97	9	galal	galal	PROPN
brj-25043	97	10	et	et	PROPN
brj-25043	97	11	al	al	PROPN
brj-25043	97	12	.	.	PROPN
brj-25043	98	1	(	(	PUNCT
brj-25043	98	2	2025	2025	NUM
brj-25043	98	3	)	)	PUNCT
brj-25043	98	4	.	.	PUNCT
brj-25043	99	1	“	"	PUNCT
brj-25043	99	2	math	math	NOUN
brj-25043	99	3	modeling	modeling	NOUN
brj-25043	99	4	biogas	biogas	NOUN
brj-25043	99	5	production	production	NOUN
brj-25043	99	6	,	,	PUNCT
brj-25043	99	7	”	"	PUNCT
brj-25043	99	8	bioresources	bioresource	NOUN
brj-25043	99	9	20(4	20(4	NOUN
brj-25043	99	10	)	)	PUNCT
brj-25043	99	11	,	,	PUNCT
brj-25043	99	12	11237	11237	NUM
brj-25043	99	13	-	-	SYM
brj-25043	99	14	11266	11266	NUM
brj-25043	99	15	.	.	PUNCT
brj-25043	100	1	11244	11244	NUM
brj-25043	100	2	for	for	ADP
brj-25043	100	3	the	the	DET
brj-25043	100	4	ascending	ascend	VERB
brj-25043	100	5	and	and	CCONJ
brj-25043	100	6	descending	descend	VERB
brj-25043	100	7	limb	limb	NOUN
brj-25043	100	8	was	be	AUX
brj-25043	100	9	0.9988	0.9988	NUM
brj-25043	100	10	and	and	CCONJ
brj-25043	100	11	0.9969	0.9969	NUM
brj-25043	100	12	in	in	ADP
brj-25043	100	13	the	the	DET
brj-25043	100	14	first	first	ADJ
brj-25043	100	15	case	case	NOUN
brj-25043	100	16	,	,	PUNCT
brj-25043	100	17	while	while	SCONJ
brj-25043	100	18	0.9951	0.9951	NUM
brj-25043	100	19	and	and	CCONJ
brj-25043	100	20	0.9969	0.9969	NUM
brj-25043	100	21	for	for	ADP
brj-25043	100	22	the	the	DET
brj-25043	100	23	second	second	ADJ
brj-25043	100	24	.	.	PUNCT
brj-25043	101	1	gaussian	gaussian	ADJ
brj-25043	101	2	model	model	NOUN
brj-25043	101	3	the	the	DET
brj-25043	101	4	gaussian	gaussian	ADJ
brj-25043	101	5	distribution	distribution	NOUN
brj-25043	101	6	is	be	AUX
brj-25043	101	7	usually	usually	ADV
brj-25043	101	8	used	use	VERB
brj-25043	101	9	to	to	PART
brj-25043	101	10	plot	plot	VERB
brj-25043	101	11	numerous	numerous	ADJ
brj-25043	101	12	natural	natural	ADJ
brj-25043	101	13	phenomena	phenomenon	NOUN
brj-25043	101	14	(	(	PUNCT
brj-25043	101	15	simon	simon	PROPN
brj-25043	101	16	2002	2002	NUM
brj-25043	101	17	;	;	PUNCT
brj-25043	101	18	lo	lo	PROPN
brj-25043	101	19	et	et	PROPN
brj-25043	101	20	al	al	PROPN
brj-25043	101	21	.	.	PROPN
brj-25043	101	22	2010	2010	NUM
brj-25043	101	23	)	)	PUNCT
brj-25043	101	24	.	.	PUNCT
brj-25043	102	1	it	it	PRON
brj-25043	102	2	has	have	AUX
brj-25043	102	3	also	also	ADV
brj-25043	102	4	been	be	AUX
brj-25043	102	5	used	use	VERB
brj-25043	102	6	to	to	PART
brj-25043	102	7	describe	describe	VERB
brj-25043	102	8	bacterial	bacterial	ADJ
brj-25043	102	9	growth	growth	NOUN
brj-25043	102	10	,	,	PUNCT
brj-25043	102	11	resulting	result	VERB
brj-25043	102	12	in	in	ADP
brj-25043	102	13	biogas	biogas	NOUN
brj-25043	102	14	production	production	NOUN
brj-25043	102	15	during	during	ADP
brj-25043	102	16	ad	ad	NOUN
brj-25043	102	17	.	.	PUNCT
brj-25043	103	1	therefore	therefore	ADV
brj-25043	103	2	,	,	PUNCT
brj-25043	103	3	this	this	DET
brj-25043	103	4	model	model	NOUN
brj-25043	103	5	and	and	CCONJ
brj-25043	103	6	some	some	DET
brj-25043	103	7	other	other	ADJ
brj-25043	103	8	models	model	NOUN
brj-25043	103	9	for	for	ADP
brj-25043	103	10	growth	growth	NOUN
brj-25043	103	11	and	and	CCONJ
brj-25043	103	12	decay	decay	NOUN
brj-25043	103	13	can	can	AUX
brj-25043	103	14	be	be	AUX
brj-25043	103	15	used	use	VERB
brj-25043	103	16	to	to	PART
brj-25043	103	17	simulate	simulate	VERB
brj-25043	103	18	the	the	DET
brj-25043	103	19	daily	daily	ADJ
brj-25043	103	20	production	production	NOUN
brj-25043	103	21	process	process	NOUN
brj-25043	103	22	.	.	PUNCT
brj-25043	104	1	the	the	DET
brj-25043	104	2	gaussian	gaussian	ADJ
brj-25043	104	3	model	model	NOUN
brj-25043	104	4	is	be	AUX
brj-25043	104	5	given	give	VERB
brj-25043	104	6	as	as	ADP
brj-25043	104	7	eq	eq	NOUN
brj-25043	104	8	.	.	PROPN
brj-25043	104	9	3	3	NUM
brj-25043	104	10	,	,	PUNCT
brj-25043	104	11	p𝒃𝒈	p𝒃𝒈	VERB
brj-25043	104	12	=	=	PUNCT
brj-25043	104	13	a	a	DET
brj-25043	104	14	exp	exp	NOUN
brj-25043	104	15	(	(	PUNCT
brj-25043	104	16	−	−	PROPN
brj-25043	104	17	(	(	PUNCT
brj-25043	104	18	𝑡	𝑡	X
brj-25043	104	19	−	−	NOUN
brj-25043	104	20	t𝒎)2/2𝑏2	t𝒎)2/2𝑏2	PROPN
brj-25043	104	21	)	)	PUNCT
brj-25043	104	22	(	(	PUNCT
brj-25043	104	23	3	3	X
brj-25043	104	24	)	)	PUNCT
brj-25043	104	25	where	where	SCONJ
brj-25043	104	26	a	a	PRON
brj-25043	104	27	is	be	AUX
brj-25043	104	28	a	a	DET
brj-25043	104	29	constant	constant	ADJ
brj-25043	104	30	(	(	PUNCT
brj-25043	104	31	𝐿	𝐿	PROPN
brj-25043	104	32	𝐾𝑔−1𝑑−1	𝐾𝑔−1𝑑−1	PROPN
brj-25043	104	33	)	)	PUNCT
brj-25043	104	34	,	,	PUNCT
brj-25043	104	35	while	while	SCONJ
brj-25043	104	36	t𝒎	t𝒎	NOUN
brj-25043	104	37	and	and	CCONJ
brj-25043	104	38	𝑏	𝑏	PROPN
brj-25043	104	39	are	be	AUX
brj-25043	104	40	the	the	DET
brj-25043	104	41	mean	mean	ADJ
brj-25043	104	42	and	and	CCONJ
brj-25043	104	43	standard	standard	ADJ
brj-25043	104	44	deviation	deviation	NOUN
brj-25043	104	45	,	,	PUNCT
brj-25043	104	46	respectively	respectively	ADV
brj-25043	104	47	,	,	PUNCT
brj-25043	104	48	in	in	ADP
brj-25043	104	49	(	(	PUNCT
brj-25043	104	50	𝑑	𝑑	NOUN
brj-25043	104	51	)	)	PUNCT
brj-25043	104	52	,	,	PUNCT
brj-25043	104	53	this	this	DET
brj-25043	104	54	model	model	NOUN
brj-25043	104	55	has	have	AUX
brj-25043	104	56	been	be	AUX
brj-25043	104	57	investigated	investigate	VERB
brj-25043	104	58	by	by	ADP
brj-25043	104	59	tonner	tonner	PROPN
brj-25043	104	60	et	et	PROPN
brj-25043	104	61	al	al	PROPN
brj-25043	104	62	.	.	PROPN
brj-25043	105	1	(	(	PUNCT
brj-25043	105	2	2017	2017	NUM
brj-25043	105	3	)	)	PUNCT
brj-25043	106	1	to	to	PART
brj-25043	106	2	simulate	simulate	VERB
brj-25043	106	3	the	the	DET
brj-25043	106	4	differential	differential	ADJ
brj-25043	106	5	effects	effect	NOUN
brj-25043	106	6	of	of	ADP
brj-25043	106	7	media	medium	NOUN
brj-25043	106	8	,	,	PUNCT
brj-25043	106	9	genetics	genetic	NOUN
brj-25043	106	10	,	,	PUNCT
brj-25043	106	11	and	and	CCONJ
brj-25043	106	12	stress	stress	NOUN
brj-25043	106	13	on	on	ADP
brj-25043	106	14	microbial	microbial	ADJ
brj-25043	106	15	population	population	NOUN
brj-25043	106	16	growth	growth	NOUN
brj-25043	106	17	.	.	PUNCT
brj-25043	107	1	moreover	moreover	ADV
brj-25043	107	2	,	,	PUNCT
brj-25043	107	3	it	it	PRON
brj-25043	107	4	was	be	AUX
brj-25043	107	5	utilized	utilize	VERB
brj-25043	107	6	to	to	PART
brj-25043	107	7	simulate	simulate	VERB
brj-25043	107	8	and	and	CCONJ
brj-25043	107	9	predict	predict	VERB
brj-25043	107	10	the	the	DET
brj-25043	107	11	biogas	biogas	NOUN
brj-25043	107	12	production	production	NOUN
brj-25043	107	13	evaluated	evaluate	VERB
brj-25043	107	14	by	by	ADP
brj-25043	107	15	lo	lo	PROPN
brj-25043	107	16	et	et	PROPN
brj-25043	107	17	al	al	PROPN
brj-25043	107	18	.	.	PROPN
brj-25043	108	1	(	(	PUNCT
brj-25043	108	2	2010	2010	NUM
brj-25043	108	3	)	)	PUNCT
brj-25043	108	4	,	,	PUNCT
brj-25043	108	5	where	where	SCONJ
brj-25043	108	6	the	the	DET
brj-25043	108	7	best	good	ADJ
brj-25043	108	8	r2	r2	NOUN
brj-25043	108	9	was	be	AUX
brj-25043	108	10	0.9486	0.9486	NUM
brj-25043	108	11	in	in	ADP
brj-25043	108	12	the	the	DET
brj-25043	108	13	case	case	NOUN
brj-25043	108	14	of	of	ADP
brj-25043	108	15	fa	fa	PROPN
brj-25043	108	16	/	/	SYM
brj-25043	108	17	msw	msw	NOUN
brj-25043	108	18	20	20	NUM
brj-25043	108	19	g	g	PROPN
brj-25043	108	20	l-1	l-1	PROPN
brj-25043	108	21	.	.	PUNCT
brj-25043	109	1	in	in	ADP
brj-25043	109	2	addition	addition	NOUN
brj-25043	109	3	,	,	PUNCT
brj-25043	109	4	nielfa	nielfa	NOUN
brj-25043	109	5	et	et	PROPN
brj-25043	109	6	al	al	PROPN
brj-25043	109	7	.	.	PROPN
brj-25043	110	1	(	(	PUNCT
brj-25043	110	2	2015	2015	NUM
brj-25043	110	3	)	)	PUNCT
brj-25043	110	4	used	use	VERB
brj-25043	110	5	this	this	DET
brj-25043	110	6	model	model	NOUN
brj-25043	110	7	to	to	PART
brj-25043	110	8	simulate	simulate	VERB
brj-25043	110	9	methane	methane	NOUN
brj-25043	110	10	production	production	NOUN
brj-25043	110	11	resulting	result	VERB
brj-25043	110	12	from	from	ADP
brj-25043	110	13	the	the	DET
brj-25043	110	14	composition	composition	NOUN
brj-25043	110	15	of	of	ADP
brj-25043	110	16	heterogeneous	heterogeneous	ADJ
brj-25043	110	17	organic	organic	ADJ
brj-25043	110	18	and	and	CCONJ
brj-25043	110	19	inorganic	inorganic	ADJ
brj-25043	110	20	wastes	waste	NOUN
brj-25043	110	21	with	with	ADP
brj-25043	110	22	ofmsw	ofmsw	NOUN
brj-25043	110	23	.	.	PUNCT
brj-25043	111	1	the	the	DET
brj-25043	111	2	highest	high	ADJ
brj-25043	111	3	r²	r²	NOUN
brj-25043	111	4	was	be	AUX
brj-25043	111	5	achieved	achieve	VERB
brj-25043	111	6	in	in	ADP
brj-25043	111	7	the	the	DET
brj-25043	111	8	case	case	NOUN
brj-25043	111	9	of	of	ADP
brj-25043	111	10	a	a	DET
brj-25043	111	11	garden	garden	NOUN
brj-25043	111	12	waste	waste	NOUN
brj-25043	111	13	mixture	mixture	NOUN
brj-25043	111	14	with	with	ADP
brj-25043	111	15	the	the	DET
brj-25043	111	16	ofmsw	ofmsw	NOUN
brj-25043	111	17	,	,	PUNCT
brj-25043	111	18	where	where	SCONJ
brj-25043	111	19	it	it	PRON
brj-25043	111	20	was	be	AUX
brj-25043	111	21	0.95	0.95	NUM
brj-25043	111	22	.	.	PUNCT
brj-25043	112	1	however	however	ADV
brj-25043	112	2	,	,	PUNCT
brj-25043	112	3	ad	ad	NOUN
brj-25043	112	4	operational	operational	ADJ
brj-25043	112	5	monitoring	monitoring	NOUN
brj-25043	112	6	and	and	CCONJ
brj-25043	112	7	management	management	NOUN
brj-25043	112	8	depend	depend	VERB
brj-25043	112	9	heavily	heavily	ADV
brj-25043	112	10	on	on	ADP
brj-25043	112	11	daily	daily	ADJ
brj-25043	112	12	biogas	biogas	NOUN
brj-25043	112	13	output	output	NOUN
brj-25043	112	14	models	model	NOUN
brj-25043	112	15	.	.	PUNCT
brj-25043	113	1	data	datum	NOUN
brj-25043	113	2	in	in	ADP
brj-25043	113	3	table	table	NOUN
brj-25043	113	4	2	2	NUM
brj-25043	113	5	,	,	PUNCT
brj-25043	113	6	together	together	ADV
brj-25043	113	7	with	with	ADP
brj-25043	113	8	eqs	eqs	PROPN
brj-25043	113	9	.	.	PROPN
brj-25043	113	10	1	1	NUM
brj-25043	113	11	to	to	ADP
brj-25043	113	12	3	3	NUM
brj-25043	113	13	,	,	PUNCT
brj-25043	113	14	indicate	indicate	VERB
brj-25043	113	15	that	that	SCONJ
brj-25043	113	16	although	although	SCONJ
brj-25043	113	17	basic	basic	ADJ
brj-25043	113	18	models	model	NOUN
brj-25043	113	19	such	such	ADJ
brj-25043	113	20	as	as	ADP
brj-25043	113	21	gaussian	gaussian	ADJ
brj-25043	113	22	,	,	PUNCT
brj-25043	113	23	exponential	exponential	NOUN
brj-25043	113	24	,	,	PUNCT
brj-25043	113	25	and	and	CCONJ
brj-25043	113	26	linear	linear	PROPN
brj-25043	113	27	can	can	AUX
brj-25043	113	28	fit	fit	VERB
brj-25043	113	29	the	the	DET
brj-25043	113	30	ascending	ascend	VERB
brj-25043	113	31	and	and	CCONJ
brj-25043	113	32	descending	descend	VERB
brj-25043	113	33	limbs	limb	NOUN
brj-25043	113	34	of	of	ADP
brj-25043	113	35	daily	daily	ADJ
brj-25043	113	36	production	production	NOUN
brj-25043	113	37	,	,	PUNCT
brj-25043	113	38	their	their	PRON
brj-25043	113	39	accuracy	accuracy	NOUN
brj-25043	113	40	is	be	AUX
brj-25043	113	41	strongly	strongly	ADV
brj-25043	113	42	influenced	influence	VERB
brj-25043	113	43	by	by	ADP
brj-25043	113	44	the	the	DET
brj-25043	113	45	substrate	substrate	NOUN
brj-25043	113	46	and	and	CCONJ
brj-25043	113	47	process	process	NOUN
brj-25043	113	48	conditions	condition	NOUN
brj-25043	113	49	.	.	PUNCT
brj-25043	114	1	for	for	ADP
brj-25043	114	2	example	example	NOUN
brj-25043	114	3	,	,	PUNCT
brj-25043	114	4	the	the	DET
brj-25043	114	5	exponential	exponential	ADJ
brj-25043	114	6	model	model	NOUN
brj-25043	114	7	can	can	AUX
brj-25043	114	8	achieve	achieve	VERB
brj-25043	114	9	excellent	excellent	ADJ
brj-25043	114	10	fits	fit	NOUN
brj-25043	114	11	(	(	PUNCT
brj-25043	114	12	r²	r²	VERB
brj-25043	114	13	up	up	ADP
brj-25043	114	14	to	to	ADP
brj-25043	114	15	0.9988	0.9988	NUM
brj-25043	114	16	)	)	PUNCT
brj-25043	114	17	for	for	ADP
brj-25043	114	18	certain	certain	ADJ
brj-25043	114	19	organic	organic	ADJ
brj-25043	114	20	fractions	fraction	NOUN
brj-25043	114	21	and	and	CCONJ
brj-25043	114	22	waste	waste	NOUN
brj-25043	114	23	combinations	combination	NOUN
brj-25043	114	24	,	,	PUNCT
brj-25043	114	25	while	while	SCONJ
brj-25043	114	26	the	the	DET
brj-25043	114	27	linear	linear	ADJ
brj-25043	114	28	model	model	NOUN
brj-25043	114	29	performs	perform	VERB
brj-25043	114	30	reasonably	reasonably	ADV
brj-25043	114	31	well	well	ADV
brj-25043	114	32	(	(	PUNCT
brj-25043	114	33	r²	r²	VERB
brj-25043	114	34	up	up	ADP
brj-25043	114	35	to	to	ADP
brj-25043	114	36	0.96	0.96	NUM
brj-25043	114	37	)	)	PUNCT
brj-25043	114	38	but	but	CCONJ
brj-25043	114	39	is	be	AUX
brj-25043	114	40	often	often	ADV
brj-25043	114	41	outperformed	outperform	VERB
brj-25043	114	42	.	.	PUNCT
brj-25043	115	1	the	the	DET
brj-25043	115	2	gaussian	gaussian	ADJ
brj-25043	115	3	model	model	NOUN
brj-25043	115	4	,	,	PUNCT
brj-25043	115	5	with	with	ADP
brj-25043	115	6	good	good	ADJ
brj-25043	115	7	fits	fit	NOUN
brj-25043	115	8	(	(	PUNCT
brj-25043	115	9	r²	r²	NOUN
brj-25043	115	10	=	=	NOUN
brj-25043	115	11	0.95	0.95	NUM
brj-25043	115	12	)	)	PUNCT
brj-25043	115	13	for	for	ADP
brj-25043	115	14	heterogeneous	heterogeneous	ADJ
brj-25043	115	15	organic	organic	ADJ
brj-25043	115	16	wastes	waste	NOUN
brj-25043	115	17	,	,	PUNCT
brj-25043	115	18	also	also	ADV
brj-25043	115	19	demonstrates	demonstrate	VERB
brj-25043	115	20	robustness	robustness	NOUN
brj-25043	115	21	and	and	CCONJ
brj-25043	115	22	usefulness	usefulness	NOUN
brj-25043	115	23	in	in	ADP
brj-25043	115	24	simulating	simulate	VERB
brj-25043	115	25	the	the	DET
brj-25043	115	26	symmetric	symmetric	ADJ
brj-25043	115	27	rise	rise	NOUN
brj-25043	115	28	and	and	CCONJ
brj-25043	115	29	fall	fall	NOUN
brj-25043	115	30	of	of	ADP
brj-25043	115	31	daily	daily	ADJ
brj-25043	115	32	production	production	NOUN
brj-25043	115	33	rates	rate	NOUN
brj-25043	115	34	in	in	ADP
brj-25043	115	35	specific	specific	ADJ
brj-25043	115	36	systems	system	NOUN
brj-25043	115	37	.	.	PUNCT
brj-25043	116	1	for	for	ADP
brj-25043	116	2	operations	operation	NOUN
brj-25043	116	3	,	,	PUNCT
brj-25043	116	4	daily	daily	ADJ
brj-25043	116	5	-	-	PUNCT
brj-25043	116	6	rate	rate	NOUN
brj-25043	116	7	models	model	NOUN
brj-25043	116	8	are	be	AUX
brj-25043	116	9	most	most	ADV
brj-25043	116	10	useful	useful	ADJ
brj-25043	116	11	for	for	ADP
brj-25043	116	12	short	short	ADJ
brj-25043	116	13	-	-	PUNCT
brj-25043	116	14	term	term	NOUN
brj-25043	116	15	scheduling	scheduling	NOUN
brj-25043	116	16	,	,	PUNCT
brj-25043	116	17	diagnosing	diagnose	VERB
brj-25043	116	18	inhibition	inhibition	NOUN
brj-25043	116	19	or	or	CCONJ
brj-25043	116	20	overload	overload	NOUN
brj-25043	116	21	patterns	pattern	NOUN
brj-25043	116	22	,	,	PUNCT
brj-25043	116	23	and	and	CCONJ
brj-25043	116	24	checking	check	VERB
brj-25043	116	25	whether	whether	SCONJ
brj-25043	116	26	a	a	DET
brj-25043	116	27	feeding	feeding	NOUN
brj-25043	116	28	change	change	NOUN
brj-25043	116	29	alters	alter	VERB
brj-25043	116	30	rise	rise	NOUN
brj-25043	116	31	or	or	CCONJ
brj-25043	116	32	fall	fall	VERB
brj-25043	116	33	constants	constant	NOUN
brj-25043	116	34	as	as	SCONJ
brj-25043	116	35	expected	expect	VERB
brj-25043	116	36	.	.	PUNCT
brj-25043	117	1	exponential	exponential	ADJ
brj-25043	117	2	forms	form	NOUN
brj-25043	117	3	are	be	AUX
brj-25043	117	4	a	a	DET
brj-25043	117	5	sensible	sensible	ADJ
brj-25043	117	6	default	default	NOUN
brj-25043	117	7	for	for	ADP
brj-25043	117	8	forecasting	forecast	VERB
brj-25043	117	9	both	both	DET
brj-25043	117	10	sides	side	NOUN
brj-25043	117	11	;	;	PUNCT
brj-25043	117	12	gaussian	gaussian	NOUN
brj-25043	117	13	is	be	AUX
brj-25043	117	14	informative	informative	ADJ
brj-25043	117	15	when	when	SCONJ
brj-25043	117	16	production	production	NOUN
brj-25043	117	17	shows	show	VERB
brj-25043	117	18	a	a	DET
brj-25043	117	19	single	single	ADJ
brj-25043	117	20	,	,	PUNCT
brj-25043	117	21	symmetric	symmetric	ADJ
brj-25043	117	22	peak	peak	NOUN
brj-25043	117	23	,	,	PUNCT
brj-25043	117	24	while	while	SCONJ
brj-25043	117	25	linear	linear	PROPN
brj-25043	117	26	fits	fit	VERB
brj-25043	117	27	act	act	NOUN
brj-25043	117	28	as	as	ADP
brj-25043	117	29	conservative	conservative	ADJ
brj-25043	117	30	trend	trend	NOUN
brj-25043	117	31	indicators	indicator	NOUN
brj-25043	117	32	rather	rather	ADV
brj-25043	117	33	than	than	ADP
brj-25043	117	34	control	control	NOUN
brj-25043	117	35	-	-	PUNCT
brj-25043	117	36	relevant	relevant	ADJ
brj-25043	117	37	predictors	predictor	NOUN
brj-25043	117	38	.	.	PUNCT
brj-25043	118	1	these	these	DET
brj-25043	118	2	choices	choice	NOUN
brj-25043	118	3	help	help	VERB
brj-25043	118	4	operators	operator	NOUN
brj-25043	118	5	prioritize	prioritize	VERB
brj-25043	118	6	sampling	sample	VERB
brj-25043	118	7	frequency	frequency	NOUN
brj-25043	118	8	and	and	CCONJ
brj-25043	118	9	decide	decide	VERB
brj-25043	118	10	if	if	SCONJ
brj-25043	118	11	a	a	DET
brj-25043	118	12	perturbation	perturbation	NOUN
brj-25043	118	13	requires	require	VERB
brj-25043	118	14	adjusting	adjust	VERB
brj-25043	118	15	the	the	DET
brj-25043	118	16	olr	olr	NOUN
brj-25043	118	17	or	or	CCONJ
brj-25043	118	18	mixing	mix	VERB
brj-25043	118	19	strategy	strategy	NOUN
brj-25043	118	20	in	in	ADP
brj-25043	118	21	the	the	DET
brj-25043	118	22	next	next	ADJ
brj-25043	118	23	cycle	cycle	NOUN
brj-25043	118	24	.	.	PUNCT
brj-25043	119	1	linear	linear	ADJ
brj-25043	119	2	,	,	PUNCT
brj-25043	119	3	exponential	exponential	NOUN
brj-25043	119	4	,	,	PUNCT
brj-25043	119	5	and	and	CCONJ
brj-25043	119	6	gaussian	gaussian	ADJ
brj-25043	119	7	daily	daily	ADJ
brj-25043	119	8	-	-	PUNCT
brj-25043	119	9	rate	rate	NOUN
brj-25043	119	10	forms	form	NOUN
brj-25043	119	11	implicitly	implicitly	ADV
brj-25043	119	12	assume	assume	VERB
brj-25043	119	13	a	a	DET
brj-25043	119	14	unimodal	unimodal	ADJ
brj-25043	119	15	production	production	NOUN
brj-25043	119	16	curve	curve	NOUN
brj-25043	119	17	under	under	ADP
brj-25043	119	18	a	a	DET
brj-25043	119	19	stable	stable	ADJ
brj-25043	119	20	operating	operating	NOUN
brj-25043	119	21	regime	regime	NOUN
brj-25043	119	22	over	over	ADP
brj-25043	119	23	the	the	DET
brj-25043	119	24	day	day	NOUN
brj-25043	119	25	,	,	PUNCT
brj-25043	119	26	with	with	ADP
brj-25043	119	27	negligible	negligible	ADJ
brj-25043	119	28	gasholding	gasholding	NOUN
brj-25043	119	29	/	/	SYM
brj-25043	119	30	back	back	ADP
brj-25043	119	31	-	-	PUNCT
brj-25043	119	32	pressure	pressure	NOUN
brj-25043	119	33	effects	effect	NOUN
brj-25043	119	34	.	.	PUNCT
brj-25043	120	1	in	in	ADP
brj-25043	120	2	continuous	continuous	ADJ
brj-25043	120	3	or	or	CCONJ
brj-25043	120	4	semi	semi	ADJ
brj-25043	120	5	-	-	NOUN
brj-25043	120	6	batch	batch	ADJ
brj-25043	120	7	operation	operation	NOUN
brj-25043	120	8	,	,	PUNCT
brj-25043	120	9	feed	feed	NOUN
brj-25043	120	10	pulses	pulse	NOUN
brj-25043	120	11	,	,	PUNCT
brj-25043	120	12	temperature	temperature	NOUN
brj-25043	120	13	swings	swing	NOUN
brj-25043	120	14	,	,	PUNCT
brj-25043	120	15	transient	transient	ADJ
brj-25043	120	16	inhibition	inhibition	NOUN
brj-25043	120	17	(	(	PUNCT
brj-25043	120	18	e.g.	e.g.	ADV
brj-25043	120	19	,	,	PUNCT
brj-25043	120	20	ammonia	ammonia	NOUN
brj-25043	120	21	,	,	PUNCT
brj-25043	120	22	sulfide	sulfide	NOUN
brj-25043	120	23	,	,	PUNCT
brj-25043	120	24	long	long	ADJ
brj-25043	120	25	-	-	PUNCT
brj-25043	120	26	chain	chain	NOUN
brj-25043	120	27	fatty	fatty	NOUN
brj-25043	120	28	acids	acid	NOUN
brj-25043	120	29	)	)	PUNCT
brj-25043	120	30	,	,	PUNCT
brj-25043	120	31	foaming	foaming	NOUN
brj-25043	120	32	,	,	PUNCT
brj-25043	120	33	or	or	CCONJ
brj-25043	120	34	mixing	mix	VERB
brj-25043	120	35	disruptions	disruption	NOUN
brj-25043	120	36	can	can	AUX
brj-25043	120	37	create	create	VERB
brj-25043	120	38	asymmetric	asymmetric	ADJ
brj-25043	120	39	or	or	CCONJ
brj-25043	120	40	multi	multi	ADJ
brj-25043	120	41	-	-	ADJ
brj-25043	120	42	peak	peak	ADJ
brj-25043	120	43	profiles	profile	NOUN
brj-25043	120	44	that	that	PRON
brj-25043	120	45	a	a	DET
brj-25043	120	46	single	single	ADJ
brj-25043	120	47	exponential	exponential	NOUN
brj-25043	120	48	or	or	CCONJ
brj-25043	120	49	gaussian	gaussian	NOUN
brj-25043	120	50	can	can	AUX
brj-25043	120	51	not	not	PART
brj-25043	120	52	reproduce	reproduce	VERB
brj-25043	120	53	,	,	PUNCT
brj-25043	120	54	biasing	bias	VERB
brj-25043	120	55	rise	rise	NOUN
brj-25043	120	56	/	/	SYM
brj-25043	120	57	fall	fall	NOUN
brj-25043	120	58	constants	constant	NOUN
brj-25043	120	59	and	and	CCONJ
brj-25043	120	60	peak	peak	NOUN
brj-25043	120	61	timing	timing	NOUN
brj-25043	120	62	(	(	PUNCT
brj-25043	120	63	lo	lo	NOUN
brj-25043	120	64	et	et	PROPN
brj-25043	120	65	al	al	PROPN
brj-25043	120	66	.	.	PROPN
brj-25043	120	67	2010	2010	NUM
brj-25043	120	68	;	;	PUNCT
brj-25043	120	69	altaş	altaş	NOUN
brj-25043	120	70	2009	2009	NUM
brj-25043	120	71	)	)	PUNCT
brj-25043	120	72	.	.	PUNCT
brj-25043	121	1	in	in	ADP
brj-25043	121	2	such	such	ADJ
brj-25043	121	3	cases	case	NOUN
brj-25043	121	4	,	,	PUNCT
brj-25043	121	5	segmented	segment	VERB
brj-25043	121	6	fits	fit	NOUN
brj-25043	121	7	or	or	CCONJ
brj-25043	121	8	multi	multi	ADJ
brj-25043	121	9	-	-	ADJ
brj-25043	121	10	population	population	ADJ
brj-25043	121	11	kinetics	kinetic	NOUN
brj-25043	121	12	are	be	AUX
brj-25043	121	13	preferable	preferable	ADJ
brj-25043	121	14	;	;	PUNCT
brj-25043	121	15	at	at	ADP
brj-25043	121	16	minimum	minimum	NOUN
brj-25043	121	17	,	,	PUNCT
brj-25043	121	18	re	re	ADJ
brj-25043	121	19	-	-	ADJ
brj-25043	121	20	fit	fit	ADJ
brj-25043	121	21	pre-/post	pre-/post	NOUN
brj-25043	121	22	-	-	NOUN
brj-25043	121	23	perturbation	perturbation	NOUN
brj-25043	121	24	windows	window	NOUN
brj-25043	121	25	and	and	CCONJ
brj-25043	121	26	avoid	avoid	VERB
brj-25043	121	27	extrapolating	extrapolate	VERB
brj-25043	121	28	across	across	ADP
brj-25043	121	29	regime	regime	NOUN
brj-25043	121	30	shifts	shift	NOUN
brj-25043	121	31	(	(	PUNCT
brj-25043	121	32	ling	ling	NOUN
brj-25043	121	33	et	et	PROPN
brj-25043	121	34	al	al	PROPN
brj-25043	121	35	.	.	PROPN
brj-25043	121	36	2024	2024	NUM
brj-25043	121	37	)	)	PUNCT
brj-25043	122	1	.	.	PUNCT
brj-25043	123	1	peer	peer	NOUN
brj-25043	123	2	-	-	PUNCT
brj-25043	123	3	reviewed	review	VERB
brj-25043	123	4	review	review	NOUN
brj-25043	123	5	article	article	NOUN
brj-25043	123	6	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	123	7	galal	galal	PROPN
brj-25043	123	8	et	et	PROPN
brj-25043	123	9	al	al	PROPN
brj-25043	123	10	.	.	PROPN
brj-25043	124	1	(	(	PUNCT
brj-25043	124	2	2025	2025	NUM
brj-25043	124	3	)	)	PUNCT
brj-25043	124	4	.	.	PUNCT
brj-25043	125	1	“	"	PUNCT
brj-25043	125	2	math	math	NOUN
brj-25043	125	3	modeling	modeling	NOUN
brj-25043	125	4	biogas	biogas	NOUN
brj-25043	125	5	production	production	NOUN
brj-25043	125	6	,	,	PUNCT
brj-25043	125	7	”	"	PUNCT
brj-25043	125	8	bioresources	bioresource	NOUN
brj-25043	125	9	20(4	20(4	NOUN
brj-25043	125	10	)	)	PUNCT
brj-25043	125	11	,	,	PUNCT
brj-25043	125	12	11237	11237	NUM
brj-25043	125	13	-	-	SYM
brj-25043	125	14	11266	11266	NUM
brj-25043	125	15	.	.	PUNCT
brj-25043	126	1	11245	11245	NUM
brj-25043	126	2	cumulative	cumulative	ADJ
brj-25043	126	3	biogas	biogas	NOUN
brj-25043	126	4	production	production	NOUN
brj-25043	126	5	models	model	NOUN
brj-25043	126	6	table	table	VERB
brj-25043	126	7	3	3	NUM
brj-25043	126	8	summarizes	summarize	NOUN
brj-25043	126	9	cumulative	cumulative	ADJ
brj-25043	126	10	-	-	PUNCT
brj-25043	126	11	yield	yield	NOUN
brj-25043	126	12	models	model	NOUN
brj-25043	126	13	and	and	CCONJ
brj-25043	126	14	reveals	reveal	VERB
brj-25043	126	15	a	a	DET
brj-25043	126	16	clear	clear	ADJ
brj-25043	126	17	pattern	pattern	NOUN
brj-25043	126	18	:	:	PUNCT
brj-25043	126	19	the	the	DET
brj-25043	126	20	modified	modify	VERB
brj-25043	126	21	gompertz	gompertz	NOUN
brj-25043	126	22	consistently	consistently	ADV
brj-25043	126	23	achieves	achieve	VERB
brj-25043	126	24	near	near	ADV
brj-25043	126	25	-	-	PUNCT
brj-25043	126	26	perfect	perfect	ADJ
brj-25043	126	27	fits	fit	VERB
brj-25043	126	28	across	across	ADP
brj-25043	126	29	various	various	ADJ
brj-25043	126	30	substrates	substrate	NOUN
brj-25043	126	31	and	and	CCONJ
brj-25043	126	32	operating	operating	NOUN
brj-25043	126	33	conditions	condition	NOUN
brj-25043	126	34	(	(	PUNCT
brj-25043	126	35	r²	r²	VERB
brj-25043	126	36	≈	≈	PROPN
brj-25043	126	37	0.98	0.98	NUM
brj-25043	126	38	to	to	ADP
brj-25043	126	39	1.00	1.00	NUM
brj-25043	126	40	)	)	PUNCT
brj-25043	126	41	,	,	PUNCT
brj-25043	126	42	often	often	ADV
brj-25043	126	43	outperforming	outperform	VERB
brj-25043	126	44	the	the	DET
brj-25043	126	45	logistic	logistic	ADJ
brj-25043	126	46	and	and	CCONJ
brj-25043	126	47	modifiedlogistic	modifiedlogistic	ADJ
brj-25043	126	48	models	model	NOUN
brj-25043	126	49	.	.	PUNCT
brj-25043	127	1	the	the	DET
brj-25043	127	2	exponential	exponential	ADJ
brj-25043	127	3	rise	rise	NOUN
brj-25043	127	4	-	-	PUNCT
brj-25043	127	5	to	to	ADP
brj-25043	127	6	-	-	PUNCT
brj-25043	127	7	maximum	maximum	NOUN
brj-25043	127	8	model	model	NOUN
brj-25043	127	9	performs	perform	VERB
brj-25043	127	10	exceptionally	exceptionally	ADV
brj-25043	127	11	well	well	ADV
brj-25043	127	12	in	in	ADP
brj-25043	127	13	landfill	landfill	NOUN
brj-25043	127	14	bmp	bmp	NOUN
brj-25043	127	15	contexts	contexts	PROPN
brj-25043	127	16	(	(	PUNCT
brj-25043	127	17	r²	r²	VERB
brj-25043	127	18	≈	≈	PROPN
brj-25043	127	19	0.99	0.99	NUM
brj-25043	127	20	to	to	ADP
brj-25043	127	21	0.996	0.996	NUM
brj-25043	127	22	)	)	PUNCT
brj-25043	127	23	,	,	PUNCT
brj-25043	127	24	while	while	SCONJ
brj-25043	127	25	simple	simple	ADJ
brj-25043	127	26	logistic	logistic	ADJ
brj-25043	127	27	models	model	NOUN
brj-25043	127	28	are	be	AUX
brj-25043	127	29	mainly	mainly	ADV
brj-25043	127	30	competitive	competitive	ADJ
brj-25043	127	31	for	for	ADP
brj-25043	127	32	more	more	ADV
brj-25043	127	33	homogeneous	homogeneous	ADJ
brj-25043	127	34	feedstocks	feedstock	NOUN
brj-25043	127	35	(	(	PUNCT
brj-25043	127	36	e.g.	e.g.	ADV
brj-25043	127	37	,	,	PUNCT
brj-25043	127	38	manure	manure	NOUN
brj-25043	127	39	)	)	PUNCT
brj-25043	127	40	.	.	PUNCT
brj-25043	128	1	in	in	ADP
brj-25043	128	2	practice	practice	NOUN
brj-25043	128	3	,	,	PUNCT
brj-25043	128	4	a	a	DET
brj-25043	128	5	(	(	PUNCT
brj-25043	128	6	ultimate	ultimate	ADJ
brj-25043	128	7	potential	potential	NOUN
brj-25043	128	8	)	)	PUNCT
brj-25043	128	9	and	and	CCONJ
brj-25043	128	10	λ	λ	PROPN
brj-25043	128	11	(	(	PUNCT
brj-25043	128	12	lag	lag	PROPN
brj-25043	128	13	)	)	PUNCT
brj-25043	128	14	are	be	AUX
brj-25043	128	15	the	the	DET
brj-25043	128	16	most	most	ADV
brj-25043	128	17	influential	influential	ADJ
brj-25043	128	18	parameters	parameter	NOUN
brj-25043	128	19	in	in	ADP
brj-25043	128	20	modified	modify	VERB
brj-25043	128	21	-	-	PUNCT
brj-25043	128	22	gompertz	gompertz	NOUN
brj-25043	128	23	fits	fit	VERB
brj-25043	128	24	,	,	PUNCT
brj-25043	128	25	emphasizing	emphasize	VERB
brj-25043	128	26	the	the	DET
brj-25043	128	27	importance	importance	NOUN
brj-25043	128	28	of	of	ADP
brj-25043	128	29	accurate	accurate	ADJ
brj-25043	128	30	estimation	estimation	NOUN
brj-25043	128	31	or	or	CCONJ
brj-25043	128	32	uncertainty	uncertainty	NOUN
brj-25043	128	33	ranges	range	VERB
brj-25043	128	34	.	.	PUNCT
brj-25043	129	1	engineering	engineering	NOUN
brj-25043	129	2	interpretation	interpretation	NOUN
brj-25043	129	3	of	of	ADP
brj-25043	129	4	cumulative	cumulative	ADJ
brj-25043	129	5	-	-	PUNCT
brj-25043	129	6	yield	yield	NOUN
brj-25043	129	7	parameters	parameter	NOUN
brj-25043	129	8	directly	directly	ADV
brj-25043	129	9	supports	support	VERB
brj-25043	129	10	design	design	NOUN
brj-25043	129	11	and	and	CCONJ
brj-25043	129	12	start	start	NOUN
brj-25043	129	13	-	-	PUNCT
brj-25043	129	14	up	up	NOUN
brj-25043	129	15	.	.	PUNCT
brj-25043	130	1	the	the	DET
brj-25043	130	2	ultimate	ultimate	ADJ
brj-25043	130	3	potential	potential	NOUN
brj-25043	130	4	a	a	DET
brj-25043	130	5	informs	inform	VERB
brj-25043	130	6	gasholder	gasholder	NOUN
brj-25043	130	7	/	/	SYM
brj-25043	130	8	chp	chp	NOUN
brj-25043	130	9	sizing	sizing	NOUN
brj-25043	130	10	and	and	CCONJ
brj-25043	130	11	energy	energy	NOUN
brj-25043	130	12	contracts	contract	NOUN
brj-25043	130	13	;	;	PUNCT
brj-25043	130	14	the	the	DET
brj-25043	130	15	lag	lag	NOUN
brj-25043	130	16	λ	λ	PROPN
brj-25043	130	17	frames	frame	NOUN
brj-25043	130	18	warm	warm	ADJ
brj-25043	130	19	-	-	PUNCT
brj-25043	130	20	up	up	NOUN
brj-25043	130	21	and	and	CCONJ
brj-25043	130	22	acclimation	acclimation	NOUN
brj-25043	130	23	windows	window	NOUN
brj-25043	130	24	;	;	PUNCT
brj-25043	130	25	and	and	CCONJ
brj-25043	130	26	the	the	DET
brj-25043	130	27	maximal	maximal	ADJ
brj-25043	130	28	rate	rate	NOUN
brj-25043	130	29	dm	dm	NOUN
brj-25043	130	30	or	or	CCONJ
brj-25043	130	31	kinetic	kinetic	ADJ
brj-25043	130	32	constant	constant	ADJ
brj-25043	130	33	k	k	ADJ
brj-25043	130	34	links	link	NOUN
brj-25043	130	35	to	to	PART
brj-25043	130	36	target	target	VERB
brj-25043	130	37	hrt	hrt	PROPN
brj-25043	130	38	and	and	CCONJ
brj-25043	130	39	expected	expect	VERB
brj-25043	130	40	time	time	NOUN
brj-25043	130	41	to	to	ADP
brj-25043	130	42	plateau	plateau	NOUN
brj-25043	130	43	.	.	PUNCT
brj-25043	131	1	sensitivity	sensitivity	NOUN
brj-25043	131	2	analyses	analyse	VERB
brj-25043	131	3	around	around	ADP
brj-25043	131	4	a	a	PRON
brj-25043	131	5	and	and	CCONJ
brj-25043	131	6	λ	λ	NOUN
brj-25043	131	7	are	be	AUX
brj-25043	131	8	therefore	therefore	ADV
brj-25043	131	9	recommended	recommend	VERB
brj-25043	131	10	before	before	ADP
brj-25043	131	11	committing	commit	VERB
brj-25043	131	12	to	to	ADP
brj-25043	131	13	co	co	VERB
brj-25043	131	14	-	-	NOUN
brj-25043	131	15	digestion	digestion	NOUN
brj-25043	131	16	ratios	ratio	NOUN
brj-25043	131	17	or	or	CCONJ
brj-25043	131	18	pre	pre	ADJ
brj-25043	131	19	-	-	ADJ
brj-25043	131	20	treatment	treatment	NOUN
brj-25043	131	21	choices	choice	NOUN
brj-25043	131	22	,	,	PUNCT
brj-25043	131	23	especially	especially	ADV
brj-25043	131	24	where	where	SCONJ
brj-25043	131	25	substrate	substrate	NOUN
brj-25043	131	26	supply	supply	NOUN
brj-25043	131	27	is	be	AUX
brj-25043	131	28	seasonal	seasonal	ADJ
brj-25043	131	29	or	or	CCONJ
brj-25043	131	30	heterogeneous	heterogeneous	ADJ
brj-25043	131	31	.	.	PUNCT
brj-25043	132	1	logistic	logistic	ADJ
brj-25043	132	2	kinetic	kinetic	ADJ
brj-25043	132	3	model	model	NOUN
brj-25043	132	4	the	the	DET
brj-25043	132	5	model	model	NOUN
brj-25043	132	6	assumes	assume	VERB
brj-25043	132	7	an	an	DET
brj-25043	132	8	exponential	exponential	ADJ
brj-25043	132	9	increase	increase	NOUN
brj-25043	132	10	up	up	ADP
brj-25043	132	11	to	to	ADP
brj-25043	132	12	a	a	DET
brj-25043	132	13	maximum	maximum	ADJ
brj-25043	132	14	value	value	NOUN
brj-25043	132	15	and	and	CCONJ
brj-25043	132	16	remains	remain	VERB
brj-25043	132	17	constant	constant	ADJ
brj-25043	132	18	(	(	PUNCT
brj-25043	132	19	latinwo	latinwo	NOUN
brj-25043	132	20	and	and	CCONJ
brj-25043	132	21	agarry	agarry	NOUN
brj-25043	132	22	2015	2015	NUM
brj-25043	132	23	)	)	PUNCT
brj-25043	132	24	.	.	PUNCT
brj-25043	133	1	it	it	PRON
brj-25043	133	2	has	have	VERB
brj-25043	133	3	three	three	NUM
brj-25043	133	4	parameters	parameter	NOUN
brj-25043	133	5	:	:	PUNCT
brj-25043	133	6	a	a	X
brj-25043	133	7	,	,	PUNCT
brj-25043	133	8	which	which	PRON
brj-25043	133	9	is	be	AUX
brj-25043	133	10	the	the	DET
brj-25043	133	11	biogas	biogas	NOUN
brj-25043	133	12	production	production	NOUN
brj-25043	133	13	potential	potential	NOUN
brj-25043	133	14	(	(	PUNCT
brj-25043	133	15	𝐿	𝐿	PROPN
brj-25043	133	16	𝐾𝑔−1𝑑−1	𝐾𝑔−1𝑑−1	PROPN
brj-25043	133	17	)	)	PUNCT
brj-25043	133	18	;	;	PUNCT
brj-25043	133	19	b	b	X
brj-25043	133	20	,	,	PUNCT
brj-25043	133	21	a	a	DET
brj-25043	133	22	dimensionless	dimensionless	NOUN
brj-25043	133	23	constant	constant	ADJ
brj-25043	133	24	;	;	PUNCT
brj-25043	133	25	and	and	CCONJ
brj-25043	133	26	k	k	NOUN
brj-25043	133	27	,	,	PUNCT
brj-25043	133	28	another	another	DET
brj-25043	133	29	constant	constant	ADJ
brj-25043	133	30	(	(	PUNCT
brj-25043	133	31	𝑑−1	𝑑−1	PROPN
brj-25043	133	32	)	)	PUNCT
brj-25043	133	33	.	.	PUNCT
brj-25043	134	1	equation	equation	NOUN
brj-25043	134	2	4	4	NUM
brj-25043	134	3	expresses	express	VERB
brj-25043	134	4	this	this	DET
brj-25043	134	5	model	model	NOUN
brj-25043	134	6	:	:	PUNCT
brj-25043	134	7	pbg	pbg	PROPN
brj-25043	134	8	=	=	PROPN
brj-25043	134	9	a	a	NOUN
brj-25043	134	10	/	/	SYM
brj-25043	134	11	(	(	PUNCT
brj-25043	134	12	1	1	NUM
brj-25043	134	13	+	+	SYM
brj-25043	134	14	b	b	NOUN
brj-25043	134	15	exp	exp	NOUN
brj-25043	134	16	(	(	PUNCT
brj-25043	134	17	-k	-k	PROPN
brj-25043	134	18	t	t	PROPN
brj-25043	134	19	)	)	PUNCT
brj-25043	134	20	)	)	PUNCT
brj-25043	134	21	(	(	PUNCT
brj-25043	134	22	4	4	X
brj-25043	134	23	)	)	PUNCT
brj-25043	134	24	the	the	DET
brj-25043	134	25	modified	modify	VERB
brj-25043	134	26	gompertz	gompertz	NOUN
brj-25043	134	27	model	model	NOUN
brj-25043	134	28	most	most	ADV
brj-25043	134	29	consistently	consistently	ADV
brj-25043	134	30	attains	attain	NOUN
brj-25043	134	31	near	near	ADP
brj-25043	134	32	-	-	PUNCT
brj-25043	134	33	perfect	perfect	ADJ
brj-25043	134	34	cumulative	cumulative	ADJ
brj-25043	134	35	fits	fit	VERB
brj-25043	134	36	across	across	ADP
brj-25043	134	37	feedstocks	feedstock	NOUN
brj-25043	134	38	and	and	CCONJ
brj-25043	134	39	operating	operating	NOUN
brj-25043	134	40	regimes	regime	NOUN
brj-25043	134	41	,	,	PUNCT
brj-25043	134	42	with	with	ADP
brj-25043	134	43	a	a	DET
brj-25043	134	44	(	(	PUNCT
brj-25043	134	45	ultimate	ultimate	ADJ
brj-25043	134	46	potential	potential	NOUN
brj-25043	134	47	)	)	PUNCT
brj-25043	134	48	and	and	CCONJ
brj-25043	134	49	λ	λ	PROPN
brj-25043	134	50	(	(	PUNCT
brj-25043	134	51	lag	lag	NOUN
brj-25043	134	52	)	)	PUNCT
brj-25043	134	53	dominating	dominating	NOUN
brj-25043	134	54	sensitivity	sensitivity	NOUN
brj-25043	134	55	;	;	PUNCT
brj-25043	134	56	exponential	exponential	ADJ
brj-25043	134	57	rise	rise	NOUN
brj-25043	134	58	-	-	PUNCT
brj-25043	134	59	to	to	ADP
brj-25043	134	60	-	-	PUNCT
brj-25043	134	61	maximum	maximum	ADJ
brj-25043	134	62	excels	excel	NOUN
brj-25043	134	63	in	in	ADP
brj-25043	134	64	landfill	landfill	NOUN
brj-25043	134	65	/	/	SYM
brj-25043	134	66	bmp	bmp	NOUN
brj-25043	134	67	contexts	context	NOUN
brj-25043	134	68	;	;	PUNCT
brj-25043	134	69	while	while	SCONJ
brj-25043	134	70	logistic	logistic	ADJ
brj-25043	134	71	/	/	SYM
brj-25043	134	72	modified	modify	VERB
brj-25043	134	73	-	-	PUNCT
brj-25043	134	74	logistic	logistic	ADJ
brj-25043	134	75	forms	form	NOUN
brj-25043	134	76	are	be	AUX
brj-25043	134	77	competitive	competitive	ADJ
brj-25043	134	78	for	for	ADP
brj-25043	134	79	homogeneous	homogeneous	ADJ
brj-25043	134	80	manures	manure	NOUN
brj-25043	134	81	.	.	PUNCT
brj-25043	135	1	lo	lo	NOUN
brj-25043	135	2	et	et	PROPN
brj-25043	135	3	al	al	PROPN
brj-25043	135	4	.	.	PROPN
brj-25043	135	5	(	(	PUNCT
brj-25043	135	6	2010	2010	NUM
brj-25043	135	7	)	)	PUNCT
brj-25043	135	8	,	,	PUNCT
brj-25043	135	9	nielfa	nielfa	NOUN
brj-25043	135	10	et	et	PROPN
brj-25043	135	11	al	al	PROPN
brj-25043	135	12	.	.	PROPN
brj-25043	135	13	(	(	PUNCT
brj-25043	135	14	2015	2015	NUM
brj-25043	135	15	)	)	PUNCT
brj-25043	135	16	,	,	PUNCT
brj-25043	135	17	and	and	CCONJ
brj-25043	135	18	deepanraj	deepanraj	VERB
brj-25043	135	19	et	et	PROPN
brj-25043	135	20	al	al	PROPN
brj-25043	135	21	.	.	PROPN
brj-25043	136	1	(	(	PUNCT
brj-25043	136	2	2017	2017	NUM
brj-25043	136	3	)	)	PUNCT
brj-25043	136	4	embody	embody	VERB
brj-25043	136	5	these	these	DET
brj-25043	136	6	trends	trend	NOUN
brj-25043	136	7	,	,	PUNCT
brj-25043	136	8	modified	modify	VERB
brj-25043	136	9	gompertz	gompertz	NOUN
brj-25043	136	10	captures	capture	VERB
brj-25043	136	11	lag	lag	VERB
brj-25043	136	12	and	and	CCONJ
brj-25043	136	13	plateau	plateau	NOUN
brj-25043	136	14	robustly	robustly	ADV
brj-25043	136	15	,	,	PUNCT
brj-25043	136	16	exponential	exponential	ADJ
brj-25043	136	17	rise	rise	NOUN
brj-25043	136	18	-	-	PUNCT
brj-25043	136	19	to	to	ADP
brj-25043	136	20	-	-	PUNCT
brj-25043	136	21	maximum	maximum	ADJ
brj-25043	136	22	performs	perform	NOUN
brj-25043	136	23	in	in	ADP
brj-25043	136	24	mid	mid	ADJ
brj-25043	136	25	-	-	NOUN
brj-25043	136	26	range	range	NOUN
brj-25043	136	27	,	,	PUNCT
brj-25043	136	28	and	and	CCONJ
brj-25043	136	29	simple	simple	ADJ
brj-25043	136	30	logistic	logistic	NOUN
brj-25043	136	31	is	be	AUX
brj-25043	136	32	adequate	adequate	ADJ
brj-25043	136	33	when	when	SCONJ
brj-25043	136	34	variability	variability	NOUN
brj-25043	136	35	is	be	AUX
brj-25043	136	36	low	low	ADJ
brj-25043	136	37	.	.	PUNCT
brj-25043	137	1	design	design	NOUN
brj-25043	137	2	-	-	PUNCT
brj-25043	137	3	wise	wise	ADJ
brj-25043	137	4	,	,	PUNCT
brj-25043	137	5	use	use	VERB
brj-25043	137	6	a	a	PRON
brj-25043	137	7	for	for	ADP
brj-25043	137	8	gasholder	gasholder	NOUN
brj-25043	137	9	/	/	SYM
brj-25043	137	10	chp	chp	NOUN
brj-25043	137	11	sizing	sizing	NOUN
brj-25043	137	12	,	,	PUNCT
brj-25043	137	13	λ	λ	PROPN
brj-25043	137	14	for	for	ADP
brj-25043	137	15	start	start	NOUN
brj-25043	137	16	-	-	PUNCT
brj-25043	137	17	up	up	ADP
brj-25043	137	18	windows	window	NOUN
brj-25043	137	19	,	,	PUNCT
brj-25043	137	20	and	and	CCONJ
brj-25043	137	21	dm	dm	PROPN
brj-25043	137	22	or	or	CCONJ
brj-25043	137	23	k	k	PROPN
brj-25043	137	24	to	to	PART
brj-25043	137	25	inform	inform	VERB
brj-25043	137	26	hrt	hrt	PROPN
brj-25043	137	27	and	and	CCONJ
brj-25043	137	28	time	time	NOUN
brj-25043	137	29	-	-	PUNCT
brj-25043	137	30	toplateau	toplateau	NOUN
brj-25043	137	31	.	.	PUNCT
brj-25043	138	1	modified	modify	VERB
brj-25043	138	2	logistic	logistic	ADJ
brj-25043	138	3	model	model	NOUN
brj-25043	138	4	this	this	DET
brj-25043	138	5	model	model	NOUN
brj-25043	138	6	is	be	AUX
brj-25043	138	7	based	base	VERB
brj-25043	138	8	on	on	ADP
brj-25043	138	9	the	the	DET
brj-25043	138	10	bacterial	bacterial	ADJ
brj-25043	138	11	population	population	NOUN
brj-25043	138	12	growth	growth	NOUN
brj-25043	138	13	,	,	PUNCT
brj-25043	138	14	which	which	PRON
brj-25043	138	15	leads	lead	VERB
brj-25043	138	16	to	to	ADP
brj-25043	138	17	the	the	DET
brj-25043	138	18	biogas	biogas	NOUN
brj-25043	138	19	production	production	NOUN
brj-25043	138	20	during	during	ADP
brj-25043	138	21	the	the	DET
brj-25043	138	22	ad	ad	NOUN
brj-25043	138	23	process	process	NOUN
brj-25043	138	24	using	use	VERB
brj-25043	138	25	eq	eq	ADP
brj-25043	138	26	.	.	PROPN
brj-25043	138	27	5	5	NUM
brj-25043	138	28	(	(	PUNCT
brj-25043	138	29	amleh	amleh	NOUN
brj-25043	138	30	and	and	CCONJ
brj-25043	138	31	al	al	PROPN
brj-25043	138	32	-	-	PROPN
brj-25043	138	33	freihat	freihat	PRON
brj-25043	138	34	2025	2025	NUM
brj-25043	138	35	)	)	PUNCT
brj-25043	138	36	,	,	PUNCT
brj-25043	138	37	pbg	pbg	PROPN
brj-25043	138	38	=	=	PROPN
brj-25043	138	39	a	a	NOUN
brj-25043	138	40	/	/	SYM
brj-25043	138	41	(	(	PUNCT
brj-25043	138	42	1+exp	1+exp	NOUN
brj-25043	138	43	(	(	PUNCT
brj-25043	138	44	4μ	4μ	NOUN
brj-25043	138	45	a	a	DET
brj-25043	138	46	(	(	PUNCT
brj-25043	138	47	λt)+2	λt)+2	NOUN
brj-25043	138	48	)	)	PUNCT
brj-25043	138	49	)	)	PUNCT
brj-25043	139	1	(	(	PUNCT
brj-25043	139	2	5	5	X
brj-25043	139	3	)	)	PUNCT
brj-25043	139	4	where	where	SCONJ
brj-25043	139	5	a	a	PRON
brj-25043	139	6	is	be	AUX
brj-25043	139	7	as	as	ADV
brj-25043	139	8	defined	define	VERB
brj-25043	139	9	before	before	ADV
brj-25043	139	10	,	,	PUNCT
brj-25043	139	11	𝜇	𝜇	X
brj-25043	139	12	is	be	AUX
brj-25043	139	13	the	the	DET
brj-25043	139	14	maximum	maximum	ADJ
brj-25043	139	15	rate	rate	NOUN
brj-25043	139	16	of	of	ADP
brj-25043	139	17	cumulative	cumulative	ADJ
brj-25043	139	18	biogas	biogas	NOUN
brj-25043	139	19	production	production	NOUN
brj-25043	139	20	,	,	PUNCT
brj-25043	139	21	and	and	CCONJ
brj-25043	139	22	λ	λ	PROPN
brj-25043	139	23	is	be	AUX
brj-25043	139	24	the	the	DET
brj-25043	139	25	lag	lag	NOUN
brj-25043	139	26	(	(	PUNCT
brj-25043	139	27	delay	delay	NOUN
brj-25043	139	28	)	)	PUNCT
brj-25043	139	29	time	time	NOUN
brj-25043	139	30	for	for	ADP
brj-25043	139	31	the	the	DET
brj-25043	139	32	start	start	NOUN
brj-25043	139	33	of	of	ADP
brj-25043	139	34	biogas	biogas	NOUN
brj-25043	139	35	production	production	NOUN
brj-25043	139	36	.	.	PUNCT
brj-25043	140	1	this	this	DET
brj-25043	140	2	model	model	NOUN
brj-25043	140	3	was	be	AUX
brj-25043	140	4	studied	study	VERB
brj-25043	140	5	by	by	ADP
brj-25043	140	6	jafarisejahrood	jafarisejahrood	PROPN
brj-25043	140	7	et	et	PROPN
brj-25043	140	8	al	al	PROPN
brj-25043	140	9	.	.	PROPN
brj-25043	141	1	(	(	PUNCT
brj-25043	141	2	2019	2019	NUM
brj-25043	141	3	)	)	PUNCT
brj-25043	141	4	to	to	PART
brj-25043	141	5	plot	plot	VERB
brj-25043	141	6	and	and	CCONJ
brj-25043	141	7	predict	predict	VERB
brj-25043	141	8	the	the	DET
brj-25043	141	9	biogas	biogas	NOUN
brj-25043	141	10	production	production	NOUN
brj-25043	141	11	from	from	ADP
brj-25043	141	12	cow	cow	NOUN
brj-25043	141	13	manure	manure	NOUN
brj-25043	141	14	,	,	PUNCT
brj-25043	141	15	where	where	SCONJ
brj-25043	141	16	its	its	PRON
brj-25043	141	17	r2	r2	NOUN
brj-25043	141	18	was	be	AUX
brj-25043	141	19	0.993	0.993	NUM
brj-25043	141	20	.	.	PUNCT
brj-25043	142	1	moreover	moreover	ADV
brj-25043	142	2	,	,	PUNCT
brj-25043	142	3	the	the	DET
brj-25043	142	4	inhibitory	inhibitory	ADJ
brj-25043	142	5	effect	effect	NOUN
brj-25043	142	6	of	of	ADP
brj-25043	142	7	four	four	NUM
brj-25043	142	8	heavy	heavy	ADJ
brj-25043	142	9	metals	metal	NOUN
brj-25043	142	10	on	on	ADP
brj-25043	142	11	the	the	DET
brj-25043	142	12	methaneproducing	methaneproduce	VERB
brj-25043	142	13	anaerobic	anaerobic	ADJ
brj-25043	142	14	granular	granular	ADJ
brj-25043	142	15	sludge	sludge	NOUN
brj-25043	142	16	was	be	AUX
brj-25043	142	17	studied	study	VERB
brj-25043	142	18	using	use	VERB
brj-25043	142	19	the	the	DET
brj-25043	142	20	same	same	ADJ
brj-25043	142	21	model	model	NOUN
brj-25043	142	22	by	by	ADP
brj-25043	142	23	altaş	altaş	NOUN
brj-25043	142	24	(	(	PUNCT
brj-25043	142	25	2009	2009	NUM
brj-25043	142	26	)	)	PUNCT
brj-25043	142	27	.	.	PUNCT
brj-25043	143	1	peer	peer	NOUN
brj-25043	143	2	-	-	PUNCT
brj-25043	143	3	reviewed	review	VERB
brj-25043	143	4	review	review	NOUN
brj-25043	143	5	article	article	NOUN
brj-25043	143	6	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	143	7	galal	galal	PROPN
brj-25043	143	8	et	et	PROPN
brj-25043	143	9	al	al	PROPN
brj-25043	143	10	.	.	PROPN
brj-25043	144	1	(	(	PUNCT
brj-25043	144	2	2025	2025	NUM
brj-25043	144	3	)	)	PUNCT
brj-25043	144	4	.	.	PUNCT
brj-25043	145	1	“	"	PUNCT
brj-25043	145	2	math	math	NOUN
brj-25043	145	3	modeling	modeling	NOUN
brj-25043	145	4	biogas	biogas	NOUN
brj-25043	145	5	production	production	NOUN
brj-25043	145	6	,	,	PUNCT
brj-25043	145	7	”	"	PUNCT
brj-25043	145	8	bioresources	bioresource	NOUN
brj-25043	145	9	20(4	20(4	NOUN
brj-25043	145	10	)	)	PUNCT
brj-25043	145	11	,	,	PUNCT
brj-25043	145	12	11237	11237	NUM
brj-25043	145	13	-	-	SYM
brj-25043	145	14	11266	11266	NUM
brj-25043	145	15	.	.	PUNCT
brj-25043	146	1	11246	11246	NUM
brj-25043	146	2	table	table	NOUN
brj-25043	146	3	3	3	NUM
brj-25043	146	4	.	.	PUNCT
brj-25043	146	5	biogas	biogas	NOUN
brj-25043	146	6	production	production	NOUN
brj-25043	146	7	kinetic	kinetic	NOUN
brj-25043	146	8	models	model	NOUN
brj-25043	146	9	(	(	PUNCT
brj-25043	146	10	exponential	exponential	NOUN
brj-25043	146	11	,	,	PUNCT
brj-25043	146	12	logistic	logistic	ADJ
brj-25043	146	13	,	,	PUNCT
brj-25043	146	14	modified	modified	ADJ
brj-25043	146	15	gompertz	gompertz	NOUN
brj-25043	146	16	,	,	PUNCT
brj-25043	146	17	modified	modify	VERB
brj-25043	146	18	richards	richard	NOUN
brj-25043	146	19	)	)	PUNCT
brj-25043	146	20	showing	show	VERB
brj-25043	146	21	high	high	ADJ
brj-25043	146	22	predictive	predictive	ADJ
brj-25043	146	23	accuracy	accuracy	NOUN
brj-25043	146	24	across	across	ADP
brj-25043	146	25	substrates	substrate	NOUN
brj-25043	146	26	,	,	PUNCT
brj-25043	146	27	with	with	ADP
brj-25043	146	28	modified	modified	ADJ
brj-25043	146	29	gompertz	gompertz	NOUN
brj-25043	146	30	achieving	achieve	VERB
brj-25043	146	31	r²	r²	VERB
brj-25043	146	32	>	>	X
brj-25043	146	33	0.99	0.99	NUM
brj-25043	146	34	in	in	ADP
brj-25043	146	35	most	most	ADJ
brj-25043	146	36	cases	case	NOUN
brj-25043	146	37	model	model	VERB
brj-25043	146	38	main	main	ADJ
brj-25043	146	39	target	target	NOUN
brj-25043	146	40	model	model	NOUN
brj-25043	146	41	parameters	parameter	NOUN
brj-25043	146	42	goodness	goodness	PROPN
brj-25043	146	43	of	of	ADP
brj-25043	146	44	fit	fit	ADJ
brj-25043	146	45	r2	r2	PROPN
brj-25043	146	46	sub	sub	NOUN
brj-25043	146	47	-	-	NOUN
brj-25043	146	48	target	target	NOUN
brj-25043	146	49	(	(	PUNCT
brj-25043	146	50	if	if	SCONJ
brj-25043	146	51	it	it	PRON
brj-25043	146	52	exists	exist	VERB
brj-25043	146	53	)	)	PUNCT
brj-25043	146	54	references	reference	NOUN
brj-25043	146	55	e	e	NOUN
brj-25043	146	56	x	x	X
brj-25043	146	57	p	p	X
brj-25043	146	58	o	o	X
brj-25043	146	59	n	n	ADP
brj-25043	146	60	e	e	NOUN
brj-25043	146	61	n	n	X
brj-25043	146	62	ti	ti	NOUN
brj-25043	146	63	a	a	DET
brj-25043	146	64	l	l	NOUN
brj-25043	146	65	ri	ri	NOUN
brj-25043	146	66	s	s	X
brj-25043	146	67	e	e	X
brj-25043	146	68	-t	-t	NOUN
brj-25043	146	69	o	o	VERB
brj-25043	146	70	m	m	VERB
brj-25043	146	71	a	a	X
brj-25043	146	72	x	x	X
brj-25043	146	73	i	i	NOUN
brj-25043	146	74	m	m	VERB
brj-25043	146	75	u	u	NOUN
brj-25043	146	76	m	m	VERB
brj-25043	146	77	the	the	DET
brj-25043	146	78	biochemical	biochemical	ADJ
brj-25043	146	79	methane	methane	NOUN
brj-25043	146	80	potential	potential	NOUN
brj-25043	146	81	of	of	ADP
brj-25043	146	82	landfilled	landfille	VERB
brj-25043	146	83	solid	solid	ADJ
brj-25043	146	84	waste	waste	NOUN
brj-25043	146	85	a	a	DET
brj-25043	146	86	=	=	SYM
brj-25043	146	87	0.2327	0.2327	NUM
brj-25043	146	88	,	,	PUNCT
brj-25043	146	89	k	k	X
brj-25043	146	90	=	=	PUNCT
brj-25043	146	91	0.0823	0.0823	NUM
brj-25043	146	92	r2	r2	NOUN
brj-25043	146	93	=	=	VERB
brj-25043	146	94	0.9961	0.9961	NUM
brj-25043	146	95	for	for	ADP
brj-25043	146	96	r1	r1	NOUN
brj-25043	146	97	-bilgili	-bilgili	PROPN
brj-25043	146	98	et	et	PROPN
brj-25043	146	99	al	al	PROPN
brj-25043	146	100	.	.	PROPN
brj-25043	146	101	2009	2009	NUM
brj-25043	146	102	a	a	DET
brj-25043	146	103	=	=	SYM
brj-25043	146	104	0.2768	0.2768	NUM
brj-25043	146	105	,	,	PUNCT
brj-25043	146	106	k	k	X
brj-25043	146	107	=	=	PUNCT
brj-25043	146	108	0.0759	0.0759	NUM
brj-25043	146	109	r2	r2	NOUN
brj-25043	146	110	=	=	NOUN
brj-25043	146	111	0.9942	0.9942	NUM
brj-25043	146	112	for	for	ADP
brj-25043	146	113	r2	r2	NOUN
brj-25043	146	114	organic	organic	ADJ
brj-25043	146	115	fraction	fraction	NOUN
brj-25043	146	116	of	of	ADP
brj-25043	146	117	msw	msw	NOUN
brj-25043	146	118	co	co	VERB
brj-25043	146	119	-	-	VERB
brj-25043	146	120	digested	digested	ADJ
brj-25043	146	121	with	with	ADP
brj-25043	146	122	mswi	mswi	NOUN
brj-25043	146	123	ashes	ashe	NOUN
brj-25043	146	124	a	a	DET
brj-25043	146	125	=	=	SYM
brj-25043	146	126	241.9	241.9	NUM
brj-25043	146	127	,	,	PUNCT
brj-25043	146	128	k	k	X
brj-25043	146	129	=	=	PUNCT
brj-25043	146	130	0.0112	0.0112	NUM
brj-25043	146	131	r2	r2	NOUN
brj-25043	146	132	=	=	PUNCT
brj-25043	146	133	0.9907	0.9907	NUM
brj-25043	146	134	in	in	ADP
brj-25043	146	135	a	a	DET
brj-25043	146	136	case	case	NOUN
brj-25043	146	137	-	-	PUNCT
brj-25043	146	138	control	control	NOUN
brj-25043	146	139	bioreactor	bioreactor	NOUN
brj-25043	146	140	without	without	ADP
brj-25043	146	141	ash	ash	NOUN
brj-25043	146	142	addition	addition	NOUN
brj-25043	146	143	lo	lo	PROPN
brj-25043	146	144	et	et	PROPN
brj-25043	146	145	al	al	PROPN
brj-25043	146	146	.	.	PROPN
brj-25043	146	147	2010	2010	NUM
brj-25043	146	148	cow	cow	NOUN
brj-25043	146	149	dung	dung	NOUN
brj-25043	147	1	only	only	ADV
brj-25043	147	2	a	a	DET
brj-25043	147	3	=	=	SYM
brj-25043	147	4	7.616	7.616	NUM
brj-25043	147	5	×	×	NOUN
brj-25043	147	6	105	105	NUM
brj-25043	147	7	,	,	PUNCT
brj-25043	147	8	k	k	X
brj-25043	147	9	=	=	PUNCT
brj-25043	147	10	1.15	1.15	NUM
brj-25043	147	11	×	×	NOUN
brj-25043	147	12	10	10	NUM
brj-25043	147	13	-	-	SYM
brj-25043	147	14	7	7	NUM
brj-25043	147	15	r2	r2	NOUN
brj-25043	147	16	=	=	NOUN
brj-25043	147	17	0.8543	0.8543	NUM
brj-25043	147	18	a	a	DET
brj-25043	147	19	in	in	ADP
brj-25043	147	20	(	(	PUNCT
brj-25043	147	21	dm3	dm3	PROPN
brj-25043	147	22	/	/	SYM
brj-25043	147	23	gm	gm	PROPN
brj-25043	147	24	)	)	PUNCT
brj-25043	147	25	latinwo	latinwo	NOUN
brj-25043	147	26	and	and	CCONJ
brj-25043	147	27	agarry	agarry	PROPN
brj-25043	147	28	2015	2015	NUM
brj-25043	147	29	mixture	mixture	NOUN
brj-25043	147	30	of	of	ADP
brj-25043	147	31	cow	cow	NOUN
brj-25043	147	32	dung	dung	NOUN
brj-25043	147	33	and	and	CCONJ
brj-25043	147	34	plantain	plantain	NOUN
brj-25043	147	35	peels	peel	NOUN
brj-25043	147	36	a=8.26	a=8.26	ADJ
brj-25043	147	37	×	×	NOUN
brj-25043	147	38	105	105	NUM
brj-25043	147	39	,	,	PUNCT
brj-25043	147	40	k	k	PROPN
brj-25043	148	1	=	=	PUNCT
brj-25043	148	2	1.247	1.247	NUM
brj-25043	148	3	×	×	NOUN
brj-25043	148	4	10	10	NUM
brj-25043	148	5	-	-	SYM
brj-25043	148	6	7	7	NUM
brj-25043	148	7	r2	r2	NOUN
brj-25043	148	8	=	=	SYM
brj-25043	148	9	0.8561	0.8561	NUM
brj-25043	148	10	heterogeneous	heterogeneous	ADJ
brj-25043	148	11	organic	organic	ADJ
brj-25043	148	12	and	and	CCONJ
brj-25043	148	13	inorganic	inorganic	ADJ
brj-25043	148	14	wastes	waste	NOUN
brj-25043	148	15	with	with	ADP
brj-25043	148	16	the	the	DET
brj-25043	148	17	ofmsw	ofmsw	NOUN
brj-25043	148	18	a=	a=	NOUN
brj-25043	148	19	140	140	NUM
brj-25043	148	20	,	,	PUNCT
brj-25043	148	21	k	k	PROPN
brj-25043	148	22	=	=	PUNCT
brj-25043	148	23	0.24	0.24	NUM
brj-25043	148	24	r2	r2	NOUN
brj-25043	148	25	=	=	NOUN
brj-25043	148	26	0.99	0.99	NUM
brj-25043	148	27	ofmsw	ofmsw	NOUN
brj-25043	148	28	only	only	ADV
brj-25043	148	29	nielfa	nielfa	NOUN
brj-25043	148	30	et	et	PROPN
brj-25043	148	31	al	al	PROPN
brj-25043	148	32	.	.	PROPN
brj-25043	148	33	2015	2015	NUM
brj-25043	149	1	l	l	NOUN
brj-25043	149	2	o	o	X
brj-25043	149	3	g	g	NOUN
brj-25043	149	4	is	be	AUX
brj-25043	149	5	ti	ti	X
brj-25043	149	6	c	c	NOUN
brj-25043	149	7	k	k	X
brj-25043	149	8	in	in	ADP
brj-25043	149	9	e	e	X
brj-25043	149	10	ti	ti	NOUN
brj-25043	149	11	c	c	PROPN
brj-25043	149	12	cow	cow	NOUN
brj-25043	149	13	dung	dung	NOUN
brj-25043	149	14	only	only	ADV
brj-25043	149	15	a	a	DET
brj-25043	149	16	=	=	SYM
brj-25043	149	17	10.55	10.55	NUM
brj-25043	149	18	,	,	PUNCT
brj-25043	149	19	b	b	NOUN
brj-25043	149	20	=	=	SYM
brj-25043	149	21	80.15	80.15	NUM
brj-25043	149	22	,	,	PUNCT
brj-25043	149	23	k	k	X
brj-25043	150	1	=	=	PUNCT
brj-25043	150	2	0.1249	0.1249	NUM
brj-25043	150	3	r2	r2	NOUN
brj-25043	150	4	=	=	SYM
brj-25043	150	5	0.9859	0.9859	NUM
brj-25043	150	6	-latinwo	-latinwo	ADJ
brj-25043	150	7	and	and	CCONJ
brj-25043	150	8	agarry	agarry	NOUN
brj-25043	150	9	2015	2015	NUM
brj-25043	150	10	mixture	mixture	NOUN
brj-25043	150	11	of	of	ADP
brj-25043	150	12	cow	cow	NOUN
brj-25043	150	13	dung	dung	NOUN
brj-25043	150	14	and	and	CCONJ
brj-25043	150	15	plantain	plantain	NOUN
brj-25043	150	16	peels	peel	NOUN
brj-25043	150	17	a	a	DET
brj-25043	150	18	=	=	SYM
brj-25043	150	19	4.918	4.918	NUM
brj-25043	150	20	,	,	PUNCT
brj-25043	150	21	b	b	PROPN
brj-25043	150	22	=	=	SYM
brj-25043	150	23	55.12	55.12	NUM
brj-25043	150	24	,	,	PUNCT
brj-25043	150	25	k	k	X
brj-25043	151	1	=	=	PUNCT
brj-25043	151	2	0.1766	0.1766	NUM
brj-25043	151	3	r2	r2	NOUN
brj-25043	151	4	=	=	PUNCT
brj-25043	152	1	0.9775	0.9775	NUM
brj-25043	152	2	m	m	VERB
brj-25043	153	1	o	o	NOUN
brj-25043	153	2	d	d	NOUN
brj-25043	153	3	if	if	SCONJ
brj-25043	153	4	ie	ie	PROPN
brj-25043	153	5	d	d	NOUN
brj-25043	153	6	l	l	NOUN
brj-25043	154	1	o	o	X
brj-25043	154	2	g	g	NOUN
brj-25043	154	3	is	be	AUX
brj-25043	154	4	ti	ti	X
brj-25043	154	5	c	c	NOUN
brj-25043	154	6	biogas	biogas	NOUN
brj-25043	154	7	production	production	NOUN
brj-25043	154	8	from	from	ADP
brj-25043	154	9	cow	cow	NOUN
brj-25043	154	10	manure	manure	NOUN
brj-25043	154	11	a	a	DET
brj-25043	154	12	=	=	X
brj-25043	154	13	𝟏𝟒.	𝟏𝟒.	PROPN
brj-25043	154	14	𝟒𝟖𝟗	𝟒𝟖𝟗	NUM
brj-25043	154	15	,	,	PUNCT
brj-25043	154	16	μ	μ	PROPN
brj-25043	154	17	=	=	SYM
brj-25043	154	18	0.326	0.326	NUM
brj-25043	154	19	,	,	PUNCT
brj-25043	154	20	λ	λ	PROPN
brj-25043	154	21	=	=	SYM
brj-25043	154	22	12.099	12.099	NUM
brj-25043	154	23	r2	r2	NOUN
brj-25043	154	24	=	=	NOUN
brj-25043	155	1	0.9930	0.9930	NUM
brj-25043	155	2	-jafarisejahrood	-jafarisejahrood	NOUN
brj-25043	155	3	et	et	PROPN
brj-25043	155	4	al	al	PROPN
brj-25043	155	5	.	.	PROPN
brj-25043	155	6	2019	2019	NUM
brj-25043	155	7	the	the	DET
brj-25043	155	8	inhibitory	inhibitory	ADJ
brj-25043	155	9	effect	effect	NOUN
brj-25043	155	10	of	of	ADP
brj-25043	155	11	four	four	NUM
brj-25043	155	12	of	of	ADP
brj-25043	155	13	these	these	DET
brj-25043	155	14	metals	metal	NOUN
brj-25043	155	15	on	on	ADP
brj-25043	155	16	the	the	PRON
brj-25043	155	17	on	on	ADP
brj-25043	155	18	methane	methane	NOUN
brj-25043	155	19	-	-	PUNCT
brj-25043	155	20	producing	produce	VERB
brj-25043	155	21	anaerobic	anaerobic	NOUN
brj-25043	155	22	granular	granular	ADJ
brj-25043	155	23	sludge	sludge	NOUN
brj-25043	155	24	a	a	DET
brj-25043	155	25	=	=	NOUN
brj-25043	155	26	0.65	0.65	NUM
brj-25043	155	27	to	to	ADP
brj-25043	155	28	44.14	44.14	NUM
brj-25043	155	29	,	,	PUNCT
brj-25043	155	30	μ	μ	PROPN
brj-25043	155	31	=	=	NOUN
brj-25043	155	32	0.12	0.12	NUM
brj-25043	155	33	to	to	ADP
brj-25043	155	34	3.21	3.21	NUM
brj-25043	155	35	,	,	PUNCT
brj-25043	155	36	λ	λ	X
brj-25043	155	37	=	=	NOUN
brj-25043	155	38	6.40	6.40	NUM
brj-25043	155	39	to	to	ADP
brj-25043	155	40	68.66	68.66	NUM
brj-25043	155	41	--altaş	--altaş	SYM
brj-25043	155	42	2009	2009	NUM
brj-25043	155	43	the	the	DET
brj-25043	155	44	biogas	biogas	NOUN
brj-25043	155	45	production	production	NOUN
brj-25043	155	46	of	of	ADP
brj-25043	155	47	food	food	NOUN
brj-25043	155	48	wastes	waste	NOUN
brj-25043	155	49	codigested	codigeste	VERB
brj-25043	155	50	with	with	ADP
brj-25043	155	51	poultry	poultry	NOUN
brj-25043	155	52	manure	manure	NOUN
brj-25043	155	53	a	a	DET
brj-25043	155	54	=	=	SYM
brj-25043	155	55	9764.9	9764.9	NUM
brj-25043	155	56	,	,	PUNCT
brj-25043	155	57	μ	μ	PROPN
brj-25043	155	58	=	=	SYM
brj-25043	155	59	841.3	841.3	NUM
brj-25043	155	60	,	,	PUNCT
brj-25043	155	61	λ	λ	X
brj-25043	155	62	=	=	SYM
brj-25043	155	63	3.1	3.1	NUM
brj-25043	155	64	r2	r2	NOUN
brj-25043	155	65	=	=	PUNCT
brj-25043	155	66	0.9991	0.9991	NUM
brj-25043	155	67	ultrasonication	ultrasonication	NOUN
brj-25043	155	68	(	(	PUNCT
brj-25043	155	69	us	we	PRON
brj-25043	155	70	)	)	PUNCT
brj-25043	155	71	deepanraj	deepanraj	VERB
brj-25043	155	72	et	et	PROPN
brj-25043	155	73	al	al	PROPN
brj-25043	155	74	.	.	PROPN
brj-25043	156	1	2017	2017	NUM
brj-25043	156	2	m	m	NOUN
brj-25043	157	1	o	o	NOUN
brj-25043	157	2	d	d	NOUN
brj-25043	157	3	if	if	SCONJ
brj-25043	157	4	ie	ie	PROPN
brj-25043	157	5	d	d	NOUN
brj-25043	157	6	g	g	NOUN
brj-25043	157	7	o	o	NOUN
brj-25043	157	8	m	m	VERB
brj-25043	157	9	p	p	X
brj-25043	157	10	e	e	X
brj-25043	157	11	rt	rt	PROPN
brj-25043	157	12	z	z	PROPN
brj-25043	157	13	cow	cow	NOUN
brj-25043	157	14	dung	dung	NOUN
brj-25043	157	15	only	only	ADV
brj-25043	157	16	a	a	DET
brj-25043	157	17	=	=	SYM
brj-25043	157	18	4.733	4.733	NUM
brj-25043	157	19	,	,	PUNCT
brj-25043	157	20	dm	dm	PROPN
brj-25043	157	21	=	=	SYM
brj-25043	157	22	0.0059	0.0059	NUM
brj-25043	157	23	,	,	PUNCT
brj-25043	157	24	λ	λ	X
brj-25043	157	25	=	=	SYM
brj-25043	157	26	7.178	7.178	NUM
brj-25043	157	27	r2	r2	NOUN
brj-25043	157	28	=	=	SYM
brj-25043	157	29	0.9834	0.9834	NUM
brj-25043	157	30	-latinwo	-latinwo	NOUN
brj-25043	157	31	and	and	CCONJ
brj-25043	157	32	agarry	agarry	NOUN
brj-25043	157	33	2015	2015	NUM
brj-25043	157	34	mixture	mixture	NOUN
brj-25043	157	35	of	of	ADP
brj-25043	157	36	cow	cow	NOUN
brj-25043	157	37	dung	dung	NOUN
brj-25043	157	38	and	and	CCONJ
brj-25043	157	39	plantain	plantain	NOUN
brj-25043	157	40	peels	peel	NOUN
brj-25043	157	41	a	a	DET
brj-25043	157	42	=	=	SYM
brj-25043	157	43	5.660	5.660	NUM
brj-25043	157	44	,	,	PUNCT
brj-25043	157	45	dm	dm	PROPN
brj-25043	157	46	=	=	SYM
brj-25043	157	47	0.0134	0.0134	NUM
brj-25043	157	48	,	,	PUNCT
brj-25043	157	49	λ	λ	X
brj-25043	157	50	=	=	NOUN
brj-25043	157	51	6.11	6.11	NUM
brj-25043	157	52	r2	r2	NOUN
brj-25043	157	53	=	=	PUNCT
brj-25043	158	1	0.9895	0.9895	NUM
brj-25043	158	2	inhibition	inhibition	NOUN
brj-25043	158	3	of	of	ADP
brj-25043	158	4	heavy	heavy	ADJ
brj-25043	158	5	metals	metal	NOUN
brj-25043	158	6	on	on	ADP
brj-25043	158	7	fermentative	fermentative	ADJ
brj-25043	158	8	hydrogen	hydrogen	NOUN
brj-25043	158	9	production	production	NOUN
brj-25043	158	10	by	by	ADP
brj-25043	158	11	granular	granular	ADJ
brj-25043	158	12	sludge	sludge	NOUN
brj-25043	158	13	a	a	PRON
brj-25043	158	14	=	=	NOUN
brj-25043	158	15	171	171	NUM
brj-25043	158	16	to	to	PART
brj-25043	158	17	10	10	NUM
brj-25043	158	18	,	,	PUNCT
brj-25043	158	19	dm	dm	PROPN
brj-25043	158	20	=	=	SYM
brj-25043	158	21	4.9	4.9	NUM
brj-25043	158	22	to	to	PART
brj-25043	158	23	0.1	0.1	NUM
brj-25043	158	24	,	,	PUNCT
brj-25043	158	25	λ	λ	X
brj-25043	158	26	=	=	NOUN
brj-25043	158	27	4.6	4.6	NUM
brj-25043	158	28	to	to	PART
brj-25043	158	29	29.9	29.9	NUM
brj-25043	158	30	r2	r2	NOUN
brj-25043	158	31	>	>	PUNCT
brj-25043	158	32	0.95	0.95	NUM
brj-25043	158	33	(	(	PUNCT
brj-25043	158	34	in	in	ADP
brj-25043	158	35	all	all	DET
brj-25043	158	36	cases	case	NOUN
brj-25043	158	37	)	)	PUNCT
brj-25043	158	38	for	for	ADP
brj-25043	158	39	zn	zn	PROPN
brj-25043	158	40	concentrations	concentration	NOUN
brj-25043	158	41	(	(	PUNCT
brj-25043	158	42	0	0	NUM
brj-25043	158	43	to	to	PART
brj-25043	158	44	5000	5000	NUM
brj-25043	158	45	)	)	PUNCT
brj-25043	158	46	li	li	PROPN
brj-25043	158	47	and	and	CCONJ
brj-25043	158	48	fang	fang	PROPN
brj-25043	158	49	2007	2007	NUM
brj-25043	158	50	peer	peer	NOUN
brj-25043	158	51	-	-	PUNCT
brj-25043	158	52	reviewed	review	VERB
brj-25043	158	53	review	review	NOUN
brj-25043	158	54	article	article	NOUN
brj-25043	158	55	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	158	56	galal	galal	PROPN
brj-25043	158	57	et	et	PROPN
brj-25043	158	58	al	al	PROPN
brj-25043	158	59	.	.	PROPN
brj-25043	158	60	(	(	PUNCT
brj-25043	158	61	2025	2025	NUM
brj-25043	158	62	)	)	PUNCT
brj-25043	158	63	.	.	PUNCT
brj-25043	159	1	“	"	PUNCT
brj-25043	159	2	math	math	NOUN
brj-25043	159	3	modeling	modeling	NOUN
brj-25043	159	4	biogas	biogas	NOUN
brj-25043	159	5	production	production	NOUN
brj-25043	159	6	,	,	PUNCT
brj-25043	159	7	”	"	PUNCT
brj-25043	159	8	bioresources	bioresource	NOUN
brj-25043	159	9	20(4	20(4	NOUN
brj-25043	159	10	)	)	PUNCT
brj-25043	159	11	,	,	PUNCT
brj-25043	159	12	11237	11237	NUM
brj-25043	159	13	-	-	SYM
brj-25043	159	14	11266	11266	NUM
brj-25043	159	15	.	.	PUNCT
brj-25043	160	1	11247	11247	NUM
brj-25043	160	2	model	model	NOUN
brj-25043	160	3	main	main	ADJ
brj-25043	160	4	target	target	NOUN
brj-25043	160	5	model	model	NOUN
brj-25043	160	6	parameters	parameter	NOUN
brj-25043	160	7	goodness	goodness	PROPN
brj-25043	160	8	of	of	ADP
brj-25043	160	9	fit	fit	ADJ
brj-25043	160	10	r2	r2	PROPN
brj-25043	160	11	sub	sub	NOUN
brj-25043	160	12	-	-	NOUN
brj-25043	160	13	target	target	NOUN
brj-25043	160	14	(	(	PUNCT
brj-25043	160	15	if	if	SCONJ
brj-25043	160	16	it	it	PRON
brj-25043	160	17	exists	exist	VERB
brj-25043	160	18	)	)	PUNCT
brj-25043	160	19	references	reference	NOUN
brj-25043	160	20	m	m	VERB
brj-25043	160	21	o	o	NOUN
brj-25043	161	1	d	d	NOUN
brj-25043	161	2	if	if	SCONJ
brj-25043	161	3	ie	ie	PROPN
brj-25043	161	4	d	d	NOUN
brj-25043	161	5	g	g	NOUN
brj-25043	161	6	o	o	NOUN
brj-25043	161	7	m	m	VERB
brj-25043	161	8	p	p	X
brj-25043	161	9	e	e	X
brj-25043	161	10	rt	rt	PROPN
brj-25043	161	11	z	z	PROPN
brj-25043	161	12	the	the	DET
brj-25043	161	13	effects	effect	NOUN
brj-25043	161	14	of	of	ADP
brj-25043	161	15	ionic	ionic	ADJ
brj-25043	161	16	cr	cr	PROPN
brj-25043	161	17	,	,	PUNCT
brj-25043	161	18	cu	cu	PROPN
brj-25043	161	19	,	,	PUNCT
brj-25043	161	20	and	and	CCONJ
brj-25043	161	21	zn	zn	X
brj-25043	161	22	on	on	ADP
brj-25043	161	23	the	the	DET
brj-25043	161	24	fermentative	fermentative	ADJ
brj-25043	161	25	hydrogen	hydrogen	NOUN
brj-25043	161	26	production	production	NOUN
brj-25043	161	27	of	of	ADP
brj-25043	161	28	sewage	sewage	NOUN
brj-25043	161	29	sludge	sludge	NOUN
brj-25043	161	30	a	a	DET
brj-25043	161	31	=	=	NOUN
brj-25043	161	32	12.8	12.8	NUM
brj-25043	161	33	to	to	ADP
brj-25043	161	34	177	177	NUM
brj-25043	161	35	,	,	PUNCT
brj-25043	161	36	dm	dm	PROPN
brj-25043	161	37	=	=	NOUN
brj-25043	161	38	0.8	0.8	NUM
brj-25043	161	39	to	to	ADP
brj-25043	161	40	19.2	19.2	NUM
brj-25043	161	41	,	,	PUNCT
brj-25043	161	42	λ	λ	X
brj-25043	161	43	=	=	NOUN
brj-25043	161	44	3	3	NUM
brj-25043	161	45	to	to	ADP
brj-25043	161	46	33.7	33.7	NUM
brj-25043	161	47	r2	r2	NOUN
brj-25043	161	48	=	=	PUNCT
brj-25043	161	49	0.9912	0.9912	NUM
brj-25043	161	50	to	to	ADP
brj-25043	161	51	0.9998	0.9998	NUM
brj-25043	161	52	investigating	investigate	VERB
brj-25043	161	53	the	the	DET
brj-25043	161	54	cu	cu	PROPN
brj-25043	161	55	effect	effect	NOUN
brj-25043	161	56	lin	lin	PROPN
brj-25043	161	57	and	and	CCONJ
brj-25043	161	58	shei	shei	PROPN
brj-25043	161	59	2008	2008	NUM
brj-25043	161	60	bio	bio	PROPN
brj-25043	161	61	-	-	PUNCT
brj-25043	161	62	hydrogen	hydrogen	NOUN
brj-25043	161	63	production	production	NOUN
brj-25043	161	64	from	from	ADP
brj-25043	161	65	food	food	NOUN
brj-25043	161	66	waste	waste	NOUN
brj-25043	161	67	and	and	CCONJ
brj-25043	161	68	sewage	sewage	NOUN
brj-25043	161	69	sludge	sludge	NOUN
brj-25043	161	70	in	in	ADP
brj-25043	161	71	the	the	DET
brj-25043	161	72	presence	presence	NOUN
brj-25043	161	73	of	of	ADP
brj-25043	161	74	aged	aged	ADJ
brj-25043	161	75	refuse	refuse	NOUN
brj-25043	161	76	excavated	excavate	VERB
brj-25043	161	77	from	from	ADP
brj-25043	161	78	the	the	DET
brj-25043	161	79	refuse	refuse	ADJ
brj-25043	161	80	landfill	landfill	NOUN
brj-25043	161	81	a	a	PRON
brj-25043	161	82	=	=	SYM
brj-25043	161	83	193.85	193.85	NUM
brj-25043	161	84	,	,	PUNCT
brj-25043	161	85	dm	dm	PROPN
brj-25043	161	86	=	=	SYM
brj-25043	161	87	94.35	94.35	NUM
brj-25043	161	88	,	,	PUNCT
brj-25043	161	89	λ	λ	X
brj-25043	161	90	=	=	NOUN
brj-25043	161	91	15.28	15.28	NUM
brj-25043	161	92	r2	r2	NOUN
brj-25043	161	93	=	=	SYM
brj-25043	161	94	0.9821	0.9821	NUM
brj-25043	161	95	-li	-li	NOUN
brj-25043	161	96	et	et	PROPN
brj-25043	161	97	al	al	PROPN
brj-25043	161	98	.	.	PROPN
brj-25043	161	99	2008	2008	NUM
brj-25043	161	100	the	the	DET
brj-25043	161	101	inhibitory	inhibitory	ADJ
brj-25043	161	102	effect	effect	NOUN
brj-25043	161	103	of	of	ADP
brj-25043	161	104	four	four	NUM
brj-25043	161	105	of	of	ADP
brj-25043	161	106	these	these	DET
brj-25043	161	107	metals	metal	NOUN
brj-25043	161	108	on	on	ADP
brj-25043	161	109	the	the	PRON
brj-25043	161	110	on	on	ADP
brj-25043	161	111	methane	methane	NOUN
brj-25043	161	112	-	-	PUNCT
brj-25043	161	113	producing	produce	VERB
brj-25043	161	114	anaerobic	anaerobic	NOUN
brj-25043	161	115	granular	granular	ADJ
brj-25043	161	116	sludge	sludge	NOUN
brj-25043	161	117	a	a	DET
brj-25043	161	118	=	=	NOUN
brj-25043	161	119	0.65	0.65	NUM
brj-25043	161	120	to	to	ADP
brj-25043	161	121	38.73	38.73	NUM
brj-25043	161	122	,	,	PUNCT
brj-25043	161	123	dm	dm	PROPN
brj-25043	161	124	=	=	PUNCT
brj-25043	161	125	0.11	0.11	NUM
brj-25043	161	126	to	to	ADP
brj-25043	161	127	2.94	2.94	NUM
brj-25043	161	128	,	,	PUNCT
brj-25043	161	129	λ	λ	X
brj-25043	161	130	=	=	NOUN
brj-25043	161	131	5.57	5.57	NUM
brj-25043	161	132	to	to	ADP
brj-25043	161	133	66.45	66.45	NUM
brj-25043	161	134	r2	r2	NOUN
brj-25043	161	135	>	>	X
brj-25043	161	136	0.99	0.99	NUM
brj-25043	161	137	(	(	PUNCT
brj-25043	161	138	in	in	ADP
brj-25043	161	139	all	all	DET
brj-25043	161	140	cases	case	NOUN
brj-25043	161	141	except	except	SCONJ
brj-25043	161	142	that	that	PRON
brj-25043	161	143	for	for	ADP
brj-25043	161	144	cr	cr	NOUN
brj-25043	161	145	)	)	PUNCT
brj-25043	161	146	-altaş	-altaş	NOUN
brj-25043	161	147	2009	2009	NUM
brj-25043	161	148	kinetics	kinetic	NOUN
brj-25043	161	149	of	of	ADP
brj-25043	161	150	hydrogen	hydrogen	NOUN
brj-25043	161	151	production	production	NOUN
brj-25043	161	152	from	from	ADP
brj-25043	161	153	sucrose	sucrose	NOUN
brj-25043	161	154	by	by	ADP
brj-25043	161	155	mixed	mixed	ADJ
brj-25043	161	156	anaerobic	anaerobic	NOUN
brj-25043	161	157	cultures	culture	NOUN
brj-25043	161	158	n	n	CCONJ
brj-25043	161	159	/	/	SYM
brj-25043	161	160	a	a	DET
brj-25043	161	161	r2	r2	NOUN
brj-25043	161	162	=	=	PUNCT
brj-25043	161	163	0.994	0.994	NUM
brj-25043	161	164	-(mu	-(mu	PUNCT
brj-25043	161	165	et	et	PROPN
brj-25043	161	166	al	al	PROPN
brj-25043	161	167	.	.	PROPN
brj-25043	161	168	2007	2007	NUM
brj-25043	161	169	)	)	PUNCT
brj-25043	161	170	mixture	mixture	NOUN
brj-25043	161	171	of	of	ADP
brj-25043	161	172	manure	manure	NOUN
brj-25043	161	173	and	and	CCONJ
brj-25043	161	174	rumen	ruman	NOUN
brj-25043	161	175	(	(	PUNCT
brj-25043	161	176	ratio	ratio	NOUN
brj-25043	161	177	=	=	SYM
brj-25043	161	178	1:1	1:1	NUM
brj-25043	161	179	)	)	PUNCT
brj-25043	161	180	,	,	PUNCT
brj-25043	161	181	(	(	PUNCT
brj-25043	161	182	mr	mr	PROPN
brj-25043	161	183	11	11	NUM
brj-25043	161	184	)	)	PUNCT
brj-25043	161	185	a	a	DET
brj-25043	161	186	=	=	SYM
brj-25043	161	187	172.51	172.51	NUM
brj-25043	161	188	±	±	NUM
brj-25043	161	189	6.64	6.64	NUM
brj-25043	161	190	,	,	PUNCT
brj-25043	161	191	dm	dm	PROPN
brj-25043	161	192	=	=	SYM
brj-25043	161	193	3.89	3.89	NUM
brj-25043	161	194	±	±	NUM
brj-25043	161	195	0.28	0.28	NUM
brj-25043	161	196	,	,	PUNCT
brj-25043	161	197	λ	λ	X
brj-25043	161	198	=	=	SYM
brj-25043	161	199	7.25	7.25	NUM
brj-25043	161	200	±	±	NUM
brj-25043	161	201	1.65	1.65	NUM
brj-25043	161	202	r2	r2	NOUN
brj-25043	161	203	=	=	PUNCT
brj-25043	161	204	0.9983226	0.9983226	NUM
brj-25043	161	205	-(budiyono	-(budiyono	PROPN
brj-25043	161	206	et	et	PROPN
brj-25043	161	207	al	al	PROPN
brj-25043	161	208	.	.	PROPN
brj-25043	161	209	2010	2010	NUM
brj-25043	161	210	)	)	PUNCT
brj-25043	161	211	mixture	mixture	NOUN
brj-25043	161	212	of	of	ADP
brj-25043	161	213	manure	manure	NOUN
brj-25043	161	214	and	and	CCONJ
brj-25043	161	215	water	water	NOUN
brj-25043	161	216	(	(	PUNCT
brj-25043	161	217	ratio	ratio	NOUN
brj-25043	161	218	=	=	SYM
brj-25043	161	219	1:1	1:1	NUM
brj-25043	161	220	)	)	PUNCT
brj-25043	161	221	,	,	PUNCT
brj-25043	161	222	(	(	PUNCT
brj-25043	161	223	mr	mr	PROPN
brj-25043	161	224	11	11	NUM
brj-25043	161	225	)	)	PUNCT
brj-25043	161	226	a	a	DET
brj-25043	161	227	=	=	SYM
brj-25043	161	228	73.81	73.81	NUM
brj-25043	161	229	±	±	NUM
brj-25043	161	230	4.01	4.01	NUM
brj-25043	161	231	,	,	PUNCT
brj-25043	161	232	dm	dm	PROPN
brj-25043	161	233	=	=	SYM
brj-25043	161	234	1.74	1.74	NUM
brj-25043	161	235	±	±	NUM
brj-25043	161	236	0.13	0.13	NUM
brj-25043	161	237	,	,	PUNCT
brj-25043	161	238	λ	λ	X
brj-25043	161	239	=	=	SYM
brj-25043	161	240	14.75	14.75	NUM
brj-25043	161	241	±	±	NUM
brj-25043	161	242	2.87	2.87	NUM
brj-25043	161	243	r2	r2	NOUN
brj-25043	161	244	=	=	SYM
brj-25043	161	245	0.9987334	0.9987334	NUM
brj-25043	161	246	the	the	DET
brj-25043	161	247	co	co	NOUN
brj-25043	161	248	-	-	NOUN
brj-25043	161	249	digestion	digestion	NOUN
brj-25043	161	250	of	of	ADP
brj-25043	161	251	horse	horse	NOUN
brj-25043	161	252	and	and	CCONJ
brj-25043	161	253	cow	cow	NOUN
brj-25043	161	254	dung	dung	NOUN
brj-25043	161	255	a	a	DET
brj-25043	161	256	=	=	SYM
brj-25043	161	257	360	360	NUM
brj-25043	161	258	,	,	PUNCT
brj-25043	161	259	dm	dm	PROPN
brj-25043	161	260	=	=	SYM
brj-25043	161	261	36.99	36.99	NUM
brj-25043	161	262	,	,	PUNCT
brj-25043	161	263	λ	λ	X
brj-25043	161	264	=	=	NOUN
brj-25043	161	265	8.07	8.07	NUM
brj-25043	161	266	r2	r2	NOUN
brj-25043	161	267	=	=	NOUN
brj-25043	161	268	0.998	0.998	NUM
brj-25043	161	269	case	case	NOUN
brj-25043	161	270	of	of	ADP
brj-25043	161	271	75	75	NUM
brj-25043	161	272	%	%	NOUN
brj-25043	161	273	horse	horse	NOUN
brj-25043	161	274	dung	dung	NOUN
brj-25043	161	275	and	and	CCONJ
brj-25043	161	276	25	25	NUM
brj-25043	161	277	%	%	NOUN
brj-25043	161	278	cow	cow	NOUN
brj-25043	161	279	dung	dung	NOUN
brj-25043	161	280	(	(	PUNCT
brj-25043	161	281	yusuf	yusuf	PROPN
brj-25043	161	282	et	et	PROPN
brj-25043	161	283	al	al	PROPN
brj-25043	161	284	.	.	PROPN
brj-25043	161	285	2011	2011	NUM
brj-25043	161	286	)	)	PUNCT
brj-25043	161	287	organic	organic	ADJ
brj-25043	161	288	fraction	fraction	NOUN
brj-25043	161	289	of	of	ADP
brj-25043	161	290	msw	msw	NOUN
brj-25043	161	291	co	co	VERB
brj-25043	161	292	-	-	VERB
brj-25043	161	293	digested	digested	ADJ
brj-25043	161	294	with	with	ADP
brj-25043	161	295	mswi	mswi	NOUN
brj-25043	161	296	ashes	ashe	NOUN
brj-25043	161	297	a	a	DET
brj-25043	161	298	=	=	SYM
brj-25043	161	299	165.4	165.4	NUM
brj-25043	161	300	,	,	PUNCT
brj-25043	161	301	dm	dm	PROPN
brj-25043	161	302	=	=	SYM
brj-25043	161	303	4.507	4.507	NUM
brj-25043	161	304	,	,	PUNCT
brj-25043	161	305	λ	λ	X
brj-25043	161	306	=	=	NOUN
brj-25043	161	307	5.67	5.67	NUM
brj-25043	161	308	the	the	DET
brj-25043	161	309	best	good	ADJ
brj-25043	161	310	r2	r2	NOUN
brj-25043	161	311	=	=	NOUN
brj-25043	161	312	0.9977	0.9977	NUM
brj-25043	161	313	in	in	ADP
brj-25043	161	314	case	case	NOUN
brj-25043	161	315	of	of	ADP
brj-25043	161	316	fa	fa	PROPN
brj-25043	161	317	/	/	SYM
brj-25043	161	318	msw	msw	NOUN
brj-25043	161	319	10	10	NUM
brj-25043	161	320	g	g	NOUN
brj-25043	161	321	l-1	l-1	NUM
brj-25043	162	1	(	(	PUNCT
brj-25043	162	2	lo	lo	PROPN
brj-25043	162	3	et	et	PROPN
brj-25043	162	4	al	al	PROPN
brj-25043	162	5	.	.	PROPN
brj-25043	162	6	2010	2010	NUM
brj-25043	162	7	)	)	PUNCT
brj-25043	162	8	modeling	model	VERB
brj-25043	162	9	biogas	biogas	NOUN
brj-25043	162	10	production	production	NOUN
brj-25043	162	11	kinetics	kinetic	NOUN
brj-25043	162	12	of	of	ADP
brj-25043	162	13	various	various	ADJ
brj-25043	162	14	heavy	heavy	ADJ
brj-25043	162	15	metals	metal	NOUN
brj-25043	162	16	exposed	expose	VERB
brj-25043	162	17	anaerobic	anaerobic	NOUN
brj-25043	162	18	fermentation	fermentation	NOUN
brj-25043	162	19	process	process	NOUN
brj-25043	162	20	a	a	DET
brj-25043	162	21	=	=	SYM
brj-25043	162	22	34.18	34.18	NUM
brj-25043	162	23	,	,	PUNCT
brj-25043	162	24	dm	dm	PROPN
brj-25043	162	25	=	=	SYM
brj-25043	162	26	2.05	2.05	NUM
brj-25043	162	27	,	,	PUNCT
brj-25043	162	28	λ	λ	X
brj-25043	162	29	=	=	NOUN
brj-25043	162	30	3.99	3.99	NUM
brj-25043	162	31	the	the	DET
brj-25043	162	32	best	good	ADJ
brj-25043	162	33	r2	r2	NOUN
brj-25043	162	34	=	=	SYM
brj-25043	162	35	0.9989	0.9989	NUM
brj-25043	162	36	in	in	ADP
brj-25043	162	37	case	case	NOUN
brj-25043	162	38	of	of	ADP
brj-25043	162	39	cu	cu	PROPN
brj-25043	162	40	with	with	ADP
brj-25043	162	41	concentration	concentration	NOUN
brj-25043	162	42	500	500	NUM
brj-25043	162	43	mg	mg	NOUN
brj-25043	162	44	l-1	l-1	PROPN
brj-25043	162	45	(	(	PUNCT
brj-25043	162	46	tian	tian	PROPN
brj-25043	162	47	et	et	PROPN
brj-25043	162	48	al	al	PROPN
brj-25043	162	49	.	.	PROPN
brj-25043	162	50	2020	2020	NUM
brj-25043	162	51	)	)	PUNCT
brj-25043	162	52	heterogeneous	heterogeneous	ADJ
brj-25043	162	53	organic	organic	ADJ
brj-25043	162	54	and	and	CCONJ
brj-25043	162	55	inorganic	inorganic	ADJ
brj-25043	162	56	wastes	waste	NOUN
brj-25043	162	57	with	with	ADP
brj-25043	162	58	ofmsw	ofmsw	NOUN
brj-25043	163	1	a	a	DET
brj-25043	163	2	=	=	SYM
brj-25043	163	3	299	299	NUM
brj-25043	163	4	,	,	PUNCT
brj-25043	163	5	dm	dm	PROPN
brj-25043	163	6	=	=	SYM
brj-25043	163	7	21.42	21.42	NUM
brj-25043	163	8	,	,	PUNCT
brj-25043	163	9	λ	λ	X
brj-25043	163	10	=	=	NOUN
brj-25043	163	11	2.54	2.54	NUM
brj-25043	163	12	the	the	DET
brj-25043	163	13	best	good	ADJ
brj-25043	163	14	r2	r2	NOUN
brj-25043	163	15	=	=	PUNCT
brj-25043	163	16	1.00	1.00	NUM
brj-25043	163	17	in	in	ADP
brj-25043	163	18	case	case	NOUN
brj-25043	163	19	of	of	ADP
brj-25043	163	20	meat	meat	NOUN
brj-25043	163	21	/	/	SYM
brj-25043	163	22	fish	fish	NOUN
brj-25043	163	23	wastes	waste	NOUN
brj-25043	163	24	(	(	PUNCT
brj-25043	163	25	nielfa	nielfa	NOUN
brj-25043	163	26	et	et	PROPN
brj-25043	163	27	al	al	PROPN
brj-25043	163	28	.	.	PROPN
brj-25043	163	29	2015	2015	NUM
brj-25043	163	30	)	)	PUNCT
brj-25043	163	31	the	the	DET
brj-25043	163	32	biogas	biogas	NOUN
brj-25043	163	33	production	production	NOUN
brj-25043	163	34	of	of	ADP
brj-25043	163	35	food	food	NOUN
brj-25043	163	36	wastes	waste	NOUN
brj-25043	163	37	codigested	codigeste	VERB
brj-25043	163	38	with	with	ADP
brj-25043	163	39	poultry	poultry	NOUN
brj-25043	163	40	manure	manure	NOUN
brj-25043	163	41	a	a	DET
brj-25043	163	42	=	=	SYM
brj-25043	163	43	8964.3	8964.3	NUM
brj-25043	163	44	,	,	PUNCT
brj-25043	163	45	dm	dm	PROPN
brj-25043	163	46	=	=	SYM
brj-25043	163	47	712.6	712.6	NUM
brj-25043	163	48	,	,	PUNCT
brj-25043	163	49	λ	λ	X
brj-25043	163	50	=	=	NOUN
brj-25043	163	51	2.8	2.8	NUM
brj-25043	163	52	the	the	DET
brj-25043	163	53	best	good	ADJ
brj-25043	163	54	r2	r2	NOUN
brj-25043	163	55	=	=	PUNCT
brj-25043	164	1	0.9995	0.9995	NUM
brj-25043	164	2	in	in	ADP
brj-25043	164	3	case	case	NOUN
brj-25043	164	4	of	of	ADP
brj-25043	164	5	nt	not	PART
brj-25043	164	6	(	(	PUNCT
brj-25043	164	7	deepanraj	deepanraj	VERB
brj-25043	164	8	et	et	PROPN
brj-25043	164	9	al	al	PROPN
brj-25043	164	10	.	.	PROPN
brj-25043	164	11	2017	2017	NUM
brj-25043	164	12	)	)	PUNCT
brj-25043	164	13	peer	peer	NOUN
brj-25043	164	14	-	-	PUNCT
brj-25043	164	15	reviewed	review	VERB
brj-25043	164	16	review	review	NOUN
brj-25043	164	17	article	article	NOUN
brj-25043	164	18	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	164	19	galal	galal	PROPN
brj-25043	164	20	et	et	PROPN
brj-25043	164	21	al	al	PROPN
brj-25043	164	22	.	.	PROPN
brj-25043	165	1	(	(	PUNCT
brj-25043	165	2	2025	2025	NUM
brj-25043	165	3	)	)	PUNCT
brj-25043	165	4	.	.	PUNCT
brj-25043	166	1	“	"	PUNCT
brj-25043	166	2	math	math	NOUN
brj-25043	166	3	modeling	modeling	NOUN
brj-25043	166	4	biogas	biogas	NOUN
brj-25043	166	5	production	production	NOUN
brj-25043	166	6	,	,	PUNCT
brj-25043	166	7	”	"	PUNCT
brj-25043	166	8	bioresources	bioresource	NOUN
brj-25043	166	9	20(4	20(4	NOUN
brj-25043	166	10	)	)	PUNCT
brj-25043	166	11	,	,	PUNCT
brj-25043	166	12	11237	11237	NUM
brj-25043	166	13	-	-	SYM
brj-25043	166	14	11266	11266	NUM
brj-25043	166	15	.	.	PUNCT
brj-25043	167	1	11248	11248	NUM
brj-25043	167	2	model	model	NOUN
brj-25043	167	3	main	main	ADJ
brj-25043	167	4	target	target	NOUN
brj-25043	167	5	model	model	NOUN
brj-25043	167	6	parameters	parameter	NOUN
brj-25043	167	7	goodness	goodness	PROPN
brj-25043	167	8	of	of	ADP
brj-25043	167	9	fit	fit	ADJ
brj-25043	167	10	r2	r2	PROPN
brj-25043	167	11	sub	sub	NOUN
brj-25043	167	12	-	-	NOUN
brj-25043	167	13	target	target	NOUN
brj-25043	167	14	(	(	PUNCT
brj-25043	167	15	if	if	SCONJ
brj-25043	167	16	it	it	PRON
brj-25043	167	17	exists	exist	VERB
brj-25043	167	18	)	)	PUNCT
brj-25043	167	19	references	reference	NOUN
brj-25043	167	20	m	m	VERB
brj-25043	167	21	o	o	NOUN
brj-25043	168	1	d	d	NOUN
brj-25043	168	2	if	if	SCONJ
brj-25043	168	3	ie	ie	ADV
brj-25043	168	4	d	d	NOUN
brj-25043	168	5	r	r	NOUN
brj-25043	168	6	ic	ic	PROPN
brj-25043	168	7	h	h	PROPN
brj-25043	168	8	a	a	DET
brj-25043	168	9	rd	rd	NOUN
brj-25043	168	10	s	s	VERB
brj-25043	168	11	the	the	DET
brj-25043	168	12	inhibitory	inhibitory	ADJ
brj-25043	168	13	effect	effect	NOUN
brj-25043	168	14	of	of	ADP
brj-25043	168	15	four	four	NUM
brj-25043	168	16	of	of	ADP
brj-25043	168	17	these	these	DET
brj-25043	168	18	metals	metal	NOUN
brj-25043	168	19	on	on	ADP
brj-25043	168	20	the	the	PRON
brj-25043	168	21	on	on	ADP
brj-25043	168	22	methane	methane	NOUN
brj-25043	168	23	-	-	PUNCT
brj-25043	168	24	producing	produce	VERB
brj-25043	168	25	anaerobic	anaerobic	NOUN
brj-25043	168	26	granular	granular	ADJ
brj-25043	168	27	sludge	sludge	NOUN
brj-25043	168	28	a	a	DET
brj-25043	168	29	=	=	NOUN
brj-25043	168	30	0.65	0.65	NUM
brj-25043	168	31	to	to	ADP
brj-25043	168	32	44.83	44.83	NUM
brj-25043	168	33	,	,	PUNCT
brj-25043	168	34	μ	μ	PROPN
brj-25043	168	35	m	m	NOUN
brj-25043	168	36	=	=	NOUN
brj-25043	168	37	0.11	0.11	NUM
brj-25043	168	38	to	to	ADP
brj-25043	168	39	2.94	2.94	NUM
brj-25043	168	40	,	,	PUNCT
brj-25043	168	41	λ	λ	X
brj-25043	168	42	=	=	NOUN
brj-25043	168	43	5.57	5.57	NUM
brj-25043	168	44	to	to	ADP
brj-25043	168	45	67.24	67.24	NUM
brj-25043	168	46	,	,	PUNCT
brj-25043	168	47	𝝂	𝝂	PROPN
brj-25043	168	48	1,0,1	1,0,1	NUM
brj-25043	168	49	r2	r2	NOUN
brj-25043	168	50	>	>	X
brj-25043	168	51	0.99	0.99	NUM
brj-25043	168	52	(	(	PUNCT
brj-25043	168	53	in	in	ADP
brj-25043	168	54	all	all	DET
brj-25043	168	55	cases	case	NOUN
brj-25043	168	56	except	except	SCONJ
brj-25043	168	57	that	that	PRON
brj-25043	168	58	for	for	ADP
brj-25043	168	59	cr	cr	NOUN
brj-25043	168	60	)	)	PUNCT
brj-25043	168	61	-(altaş	-(altaş	NUM
brj-25043	168	62	2009	2009	NUM
brj-25043	168	63	)	)	PUNCT
brj-25043	168	64	the	the	DET
brj-25043	168	65	kinetics	kinetic	NOUN
brj-25043	168	66	of	of	ADP
brj-25043	168	67	hydrogen	hydrogen	NOUN
brj-25043	168	68	production	production	NOUN
brj-25043	168	69	from	from	ADP
brj-25043	168	70	sucrose	sucrose	NOUN
brj-25043	168	71	by	by	ADP
brj-25043	168	72	mixed	mixed	ADJ
brj-25043	168	73	cultures	culture	NOUN
brj-25043	168	74	n	n	CCONJ
brj-25043	168	75	/	/	SYM
brj-25043	168	76	a	a	DET
brj-25043	168	77	𝑅2	𝑅2	NOUN
brj-25043	168	78	=	=	NOUN
brj-25043	168	79	0.994	0.994	NUM
brj-25043	168	80	-mu	-mu	NOUN
brj-25043	168	81	et	et	PROPN
brj-25043	168	82	al	al	PROPN
brj-25043	168	83	.	.	PROPN
brj-25043	168	84	2007	2007	NUM
brj-25043	168	85	peer	peer	NOUN
brj-25043	168	86	-	-	PUNCT
brj-25043	168	87	reviewed	review	VERB
brj-25043	168	88	review	review	NOUN
brj-25043	168	89	article	article	NOUN
brj-25043	168	90	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	168	91	galal	galal	PROPN
brj-25043	168	92	et	et	PROPN
brj-25043	168	93	al	al	PROPN
brj-25043	168	94	.	.	PROPN
brj-25043	169	1	(	(	PUNCT
brj-25043	169	2	2025	2025	NUM
brj-25043	169	3	)	)	PUNCT
brj-25043	169	4	.	.	PUNCT
brj-25043	170	1	“	"	PUNCT
brj-25043	170	2	math	math	NOUN
brj-25043	170	3	modeling	modeling	NOUN
brj-25043	170	4	biogas	biogas	NOUN
brj-25043	170	5	production	production	NOUN
brj-25043	170	6	,	,	PUNCT
brj-25043	170	7	”	"	PUNCT
brj-25043	170	8	bioresources	bioresource	NOUN
brj-25043	170	9	20(4	20(4	NOUN
brj-25043	170	10	)	)	PUNCT
brj-25043	170	11	,	,	PUNCT
brj-25043	170	12	11237	11237	NUM
brj-25043	170	13	-	-	SYM
brj-25043	170	14	11266	11266	NUM
brj-25043	170	15	.	.	PUNCT
brj-25043	171	1	11249	11249	NUM
brj-25043	171	2	these	these	DET
brj-25043	171	3	studied	study	VERB
brj-25043	171	4	metals	metal	NOUN
brj-25043	171	5	were	be	AUX
brj-25043	171	6	zinc	zinc	NOUN
brj-25043	171	7	,	,	PUNCT
brj-25043	171	8	nickel	nickel	NOUN
brj-25043	171	9	,	,	PUNCT
brj-25043	171	10	cadmium	cadmium	NOUN
brj-25043	171	11	,	,	PUNCT
brj-25043	171	12	and	and	CCONJ
brj-25043	171	13	chromium	chromium	NOUN
brj-25043	171	14	,	,	PUNCT
brj-25043	171	15	where	where	SCONJ
brj-25043	171	16	the	the	DET
brj-25043	171	17	correlation	correlation	NOUN
brj-25043	171	18	coefficient	coefficient	NOUN
brj-25043	171	19	r2	r2	PROPN
brj-25043	171	20	was	be	AUX
brj-25043	171	21	greater	great	ADJ
brj-25043	171	22	than	than	ADP
brj-25043	171	23	0.99	0.99	NUM
brj-25043	171	24	for	for	ADP
brj-25043	171	25	all	all	DET
brj-25043	171	26	metals	metal	NOUN
brj-25043	171	27	except	except	SCONJ
brj-25043	171	28	chromium	chromium	NOUN
brj-25043	171	29	.	.	PUNCT
brj-25043	172	1	in	in	ADP
brj-25043	172	2	addition	addition	NOUN
brj-25043	172	3	,	,	PUNCT
brj-25043	172	4	mu	mu	PROPN
brj-25043	172	5	et	et	PROPN
brj-25043	172	6	al	al	PROPN
brj-25043	172	7	.	.	PROPN
brj-25043	173	1	(	(	PUNCT
brj-25043	173	2	2007	2007	NUM
brj-25043	173	3	)	)	PUNCT
brj-25043	173	4	investigated	investigate	VERB
brj-25043	173	5	the	the	DET
brj-25043	173	6	kinetics	kinetic	NOUN
brj-25043	173	7	of	of	ADP
brj-25043	173	8	hydrogen	hydrogen	NOUN
brj-25043	173	9	production	production	NOUN
brj-25043	173	10	from	from	ADP
brj-25043	173	11	sucrose	sucrose	NOUN
brj-25043	173	12	by	by	ADP
brj-25043	173	13	mixed	mixed	ADJ
brj-25043	173	14	anaerobic	anaerobic	NOUN
brj-25043	173	15	cultures	culture	NOUN
brj-25043	173	16	.	.	PUNCT
brj-25043	174	1	they	they	PRON
brj-25043	174	2	used	use	VERB
brj-25043	174	3	this	this	DET
brj-25043	174	4	model	model	NOUN
brj-25043	174	5	,	,	PUNCT
brj-25043	174	6	which	which	PRON
brj-25043	174	7	shows	show	VERB
brj-25043	174	8	an	an	DET
brj-25043	174	9	r2	r2	NOUN
brj-25043	174	10	of	of	ADP
brj-25043	174	11	0.9916	0.9916	NUM
brj-25043	174	12	.	.	PUNCT
brj-25043	175	1	concerning	concern	VERB
brj-25043	175	2	the	the	DET
brj-25043	175	3	food	food	NOUN
brj-25043	175	4	waste	waste	NOUN
brj-25043	175	5	,	,	PUNCT
brj-25043	175	6	deepanraj	deepanraj	VERB
brj-25043	175	7	et	et	PROPN
brj-25043	175	8	al	al	PROPN
brj-25043	175	9	.	.	PROPN
brj-25043	176	1	(	(	PUNCT
brj-25043	176	2	2017	2017	NUM
brj-25043	176	3	)	)	PUNCT
brj-25043	176	4	studied	study	VERB
brj-25043	176	5	the	the	DET
brj-25043	176	6	biogas	biogas	NOUN
brj-25043	176	7	production	production	NOUN
brj-25043	176	8	of	of	ADP
brj-25043	176	9	food	food	NOUN
brj-25043	176	10	waste	waste	NOUN
brj-25043	176	11	co	co	VERB
brj-25043	176	12	-	-	VERB
brj-25043	176	13	digested	digested	ADJ
brj-25043	176	14	with	with	ADP
brj-25043	176	15	poultry	poultry	NOUN
brj-25043	176	16	manure	manure	NOUN
brj-25043	176	17	.	.	PUNCT
brj-25043	177	1	they	they	PRON
brj-25043	177	2	considered	consider	VERB
brj-25043	177	3	four	four	NUM
brj-25043	177	4	types	type	NOUN
brj-25043	177	5	of	of	ADP
brj-25043	177	6	digestate	digestate	NOUN
brj-25043	177	7	pre	pre	NOUN
brj-25043	177	8	-	-	NOUN
brj-25043	177	9	treatment	treatment	NOUN
brj-25043	177	10	:	:	PUNCT
brj-25043	177	11	autoclave	autoclave	NOUN
brj-25043	177	12	(	(	PUNCT
brj-25043	177	13	ac	ac	PROPN
brj-25043	177	14	)	)	PUNCT
brj-25043	177	15	,	,	PUNCT
brj-25043	177	16	microwave	microwave	NOUN
brj-25043	177	17	(	(	PUNCT
brj-25043	177	18	mw	mw	PROPN
brj-25043	177	19	)	)	PUNCT
brj-25043	177	20	,	,	PUNCT
brj-25043	177	21	ultrasonication	ultrasonication	NOUN
brj-25043	177	22	(	(	PUNCT
brj-25043	177	23	us	us	PROPN
brj-25043	177	24	)	)	PUNCT
brj-25043	177	25	,	,	PUNCT
brj-25043	177	26	and	and	CCONJ
brj-25043	177	27	a	a	DET
brj-25043	177	28	no	no	ADV
brj-25043	177	29	-	-	PUNCT
brj-25043	177	30	pre	pre	ADJ
brj-25043	177	31	-	-	ADJ
brj-25043	177	32	treatment	treatment	NOUN
brj-25043	177	33	case	case	NOUN
brj-25043	177	34	(	(	PUNCT
brj-25043	177	35	nt	not	PART
brj-25043	177	36	)	)	PUNCT
brj-25043	177	37	.	.	PUNCT
brj-25043	178	1	the	the	DET
brj-25043	178	2	best	good	ADJ
brj-25043	178	3	fit	fit	NOUN
brj-25043	178	4	of	of	ADP
brj-25043	178	5	this	this	DET
brj-25043	178	6	model	model	NOUN
brj-25043	178	7	for	for	ADP
brj-25043	178	8	the	the	DET
brj-25043	178	9	us	us	PROPN
brj-25043	178	10	is	be	AUX
brj-25043	178	11	where	where	SCONJ
brj-25043	178	12	r²	r²	NOUN
brj-25043	178	13	=	=	SYM
brj-25043	178	14	0.9991	0.9991	NUM
brj-25043	178	15	.	.	PUNCT
brj-25043	179	1	exponential	exponential	ADJ
brj-25043	179	2	rise	rise	NOUN
brj-25043	179	3	-	-	PUNCT
brj-25043	179	4	to	to	ADP
brj-25043	179	5	-	-	PUNCT
brj-25043	179	6	maximum	maximum	NOUN
brj-25043	179	7	model	model	NOUN
brj-25043	179	8	the	the	DET
brj-25043	179	9	exponential	exponential	ADJ
brj-25043	179	10	rise	rise	NOUN
brj-25043	179	11	to	to	ADP
brj-25043	179	12	maximum	maximum	ADJ
brj-25043	179	13	model	model	NOUN
brj-25043	179	14	describes	describe	VERB
brj-25043	179	15	many	many	ADJ
brj-25043	179	16	physical	physical	ADJ
brj-25043	179	17	phenomena	phenomenon	NOUN
brj-25043	179	18	in	in	ADP
brj-25043	179	19	various	various	ADJ
brj-25043	179	20	fields	field	NOUN
brj-25043	179	21	,	,	PUNCT
brj-25043	179	22	including	include	VERB
brj-25043	179	23	biology	biology	NOUN
brj-25043	179	24	,	,	PUNCT
brj-25043	179	25	physics	physics	NOUN
brj-25043	179	26	,	,	PUNCT
brj-25043	179	27	economics	economic	NOUN
brj-25043	179	28	,	,	PUNCT
brj-25043	179	29	and	and	CCONJ
brj-25043	179	30	finance	finance	NOUN
brj-25043	179	31	.	.	PUNCT
brj-25043	180	1	the	the	DET
brj-25043	180	2	model	model	NOUN
brj-25043	180	3	has	have	VERB
brj-25043	180	4	two	two	NUM
brj-25043	180	5	parameters	parameter	NOUN
brj-25043	180	6	:	:	PUNCT
brj-25043	180	7	a	a	PRON
brj-25043	180	8	and	and	CCONJ
brj-25043	180	9	k.	k.	NOUN
brj-25043	180	10	the	the	DET
brj-25043	180	11	first	first	ADJ
brj-25043	180	12	one	one	NUM
brj-25043	180	13	,	,	PUNCT
brj-25043	180	14	a	a	PRON
brj-25043	180	15	,	,	PUNCT
brj-25043	180	16	is	be	AUX
brj-25043	180	17	the	the	DET
brj-25043	180	18	biogas	biogas	NOUN
brj-25043	180	19	production	production	NOUN
brj-25043	180	20	potential	potential	NOUN
brj-25043	180	21	(	(	PUNCT
brj-25043	180	22	𝐿	𝐿	PROPN
brj-25043	180	23	𝐾𝑔−1𝑑−1	𝐾𝑔−1𝑑−1	PROPN
brj-25043	180	24	)	)	PUNCT
brj-25043	180	25	,	,	PUNCT
brj-25043	180	26	while	while	SCONJ
brj-25043	180	27	k	k	PROPN
brj-25043	180	28	is	be	AUX
brj-25043	180	29	another	another	DET
brj-25043	180	30	constant	constant	ADJ
brj-25043	180	31	(	(	PUNCT
brj-25043	180	32	d-1	d-1	NOUN
brj-25043	180	33	)	)	PUNCT
brj-25043	180	34	,	,	PUNCT
brj-25043	180	35	and	and	CCONJ
brj-25043	180	36	is	be	AUX
brj-25043	180	37	given	give	VERB
brj-25043	180	38	as	as	ADP
brj-25043	180	39	the	the	DET
brj-25043	180	40	following	follow	VERB
brj-25043	180	41	equation	equation	NOUN
brj-25043	180	42	(	(	PUNCT
brj-25043	180	43	bilgili	bilgili	NOUN
brj-25043	180	44	et	et	PROPN
brj-25043	180	45	al	al	PROPN
brj-25043	180	46	.	.	PROPN
brj-25043	180	47	2009	2009	NUM
brj-25043	180	48	):	):	PUNCT
brj-25043	180	49	pbg	pbg	PROPN
brj-25043	180	50	=	=	PROPN
brj-25043	180	51	a	a	PRON
brj-25043	180	52	(	(	PUNCT
brj-25043	180	53	1exp(-k	1exp(-k	NOUN
brj-25043	180	54	t	t	NOUN
brj-25043	180	55	)	)	PUNCT
brj-25043	180	56	)	)	PUNCT
brj-25043	180	57	(	(	PUNCT
brj-25043	180	58	6	6	X
brj-25043	180	59	)	)	PUNCT
brj-25043	180	60	bilgili	bilgili	NOUN
brj-25043	180	61	et	et	PROPN
brj-25043	180	62	al	al	PROPN
brj-25043	180	63	.	.	PROPN
brj-25043	181	1	(	(	PUNCT
brj-25043	181	2	2009	2009	NUM
brj-25043	181	3	)	)	PUNCT
brj-25043	181	4	investigated	investigate	VERB
brj-25043	181	5	the	the	DET
brj-25043	181	6	exponential	exponential	ADJ
brj-25043	181	7	rise	rise	NOUN
brj-25043	181	8	to	to	ADP
brj-25043	181	9	maximum	maximum	ADJ
brj-25043	181	10	model	model	NOUN
brj-25043	181	11	for	for	ADP
brj-25043	181	12	predicting	predict	VERB
brj-25043	181	13	the	the	DET
brj-25043	181	14	biochemical	biochemical	ADJ
brj-25043	181	15	methane	methane	NOUN
brj-25043	181	16	potential	potential	NOUN
brj-25043	181	17	of	of	ADP
brj-25043	181	18	landfilled	landfilled	ADJ
brj-25043	181	19	solid	solid	ADJ
brj-25043	181	20	waste	waste	NOUN
brj-25043	181	21	.	.	PUNCT
brj-25043	182	1	they	they	PRON
brj-25043	182	2	designed	design	VERB
brj-25043	182	3	two	two	NUM
brj-25043	182	4	landfill	landfill	NOUN
brj-25043	182	5	reactors	reactor	NOUN
brj-25043	182	6	;	;	PUNCT
brj-25043	182	7	r1	r1	PROPN
brj-25043	182	8	operated	operate	VERB
brj-25043	182	9	with	with	ADP
brj-25043	182	10	leachate	leachate	NOUN
brj-25043	182	11	recirculation	recirculation	NOUN
brj-25043	182	12	and	and	CCONJ
brj-25043	182	13	r2	r2	NOUN
brj-25043	182	14	without	without	ADP
brj-25043	182	15	it	it	PRON
brj-25043	182	16	.	.	PUNCT
brj-25043	183	1	the	the	DET
brj-25043	183	2	best	good	ADJ
brj-25043	183	3	r2	r2	NOUN
brj-25043	183	4	was	be	AUX
brj-25043	183	5	0.9961	0.9961	NUM
brj-25043	183	6	for	for	ADP
brj-25043	183	7	r1	r1	NOUN
brj-25043	183	8	and	and	CCONJ
brj-25043	183	9	0.9942	0.9942	NUM
brj-25043	183	10	for	for	ADP
brj-25043	183	11	r2	r2	NOUN
brj-25043	183	12	after	after	ADP
brj-25043	183	13	400	400	NUM
brj-25043	183	14	days	day	NOUN
brj-25043	183	15	of	of	ADP
brj-25043	183	16	operation	operation	NOUN
brj-25043	183	17	for	for	ADP
brj-25043	183	18	both	both	DET
brj-25043	183	19	reactors	reactor	NOUN
brj-25043	183	20	.	.	PUNCT
brj-25043	184	1	for	for	ADP
brj-25043	184	2	the	the	DET
brj-25043	184	3	same	same	ADJ
brj-25043	184	4	problem	problem	NOUN
brj-25043	184	5	treated	treat	VERB
brj-25043	184	6	above	above	ADV
brj-25043	184	7	by	by	ADP
brj-25043	184	8	lo	lo	PROPN
brj-25043	184	9	et	et	PROPN
brj-25043	184	10	al	al	PROPN
brj-25043	184	11	.	.	PROPN
brj-25043	185	1	(	(	PUNCT
brj-25043	185	2	2010	2010	NUM
brj-25043	185	3	)	)	PUNCT
brj-25043	185	4	,	,	PUNCT
brj-25043	185	5	this	this	DET
brj-25043	185	6	model	model	NOUN
brj-25043	185	7	was	be	AUX
brj-25043	185	8	applied	apply	VERB
brj-25043	185	9	,	,	PUNCT
brj-25043	185	10	where	where	SCONJ
brj-25043	185	11	the	the	DET
brj-25043	185	12	best	good	ADJ
brj-25043	185	13	r2	r2	NOUN
brj-25043	185	14	was	be	AUX
brj-25043	185	15	0.9907	0.9907	NUM
brj-25043	185	16	in	in	ADP
brj-25043	185	17	the	the	DET
brj-25043	185	18	case	case	NOUN
brj-25043	185	19	of	of	ADP
brj-25043	185	20	the	the	DET
brj-25043	185	21	control	control	NOUN
brj-25043	185	22	bioreactor	bioreactor	NOUN
brj-25043	185	23	without	without	ADP
brj-25043	185	24	ash	ash	NOUN
brj-25043	185	25	addition	addition	NOUN
brj-25043	185	26	.	.	PUNCT
brj-25043	186	1	moreover	moreover	ADV
brj-25043	186	2	,	,	PUNCT
brj-25043	186	3	latinwo	latinwo	NOUN
brj-25043	186	4	and	and	CCONJ
brj-25043	186	5	agarry	agarry	PROPN
brj-25043	186	6	(	(	PUNCT
brj-25043	186	7	2015	2015	NUM
brj-25043	186	8	)	)	PUNCT
brj-25043	186	9	studied	study	VERB
brj-25043	186	10	it	it	PRON
brj-25043	186	11	for	for	ADP
brj-25043	186	12	the	the	DET
brj-25043	186	13	two	two	NUM
brj-25043	186	14	instances	instance	NOUN
brj-25043	186	15	of	of	ADP
brj-25043	186	16	cow	cow	NOUN
brj-25043	186	17	dung	dung	NOUN
brj-25043	186	18	only	only	ADV
brj-25043	186	19	and	and	CCONJ
brj-25043	186	20	cow	cow	NOUN
brj-25043	186	21	dung	dung	NOUN
brj-25043	186	22	with	with	ADP
brj-25043	186	23	plantain	plantain	NOUN
brj-25043	186	24	peels	peel	NOUN
brj-25043	186	25	where	where	SCONJ
brj-25043	186	26	it	it	PRON
brj-25043	186	27	showed	show	VERB
brj-25043	186	28	less	less	ADJ
brj-25043	186	29	r2	r2	NOUN
brj-25043	186	30	of	of	ADP
brj-25043	186	31	0.9907	0.9907	NUM
brj-25043	186	32	in	in	ADP
brj-25043	186	33	the	the	DET
brj-25043	186	34	first	first	ADJ
brj-25043	186	35	case	case	NOUN
brj-25043	186	36	and	and	CCONJ
brj-25043	186	37	0.8543	0.8543	NUM
brj-25043	186	38	for	for	ADP
brj-25043	186	39	the	the	DET
brj-25043	186	40	second	second	ADJ
brj-25043	186	41	case	case	NOUN
brj-25043	186	42	.	.	PUNCT
brj-25043	187	1	gompertz	gompertz	PROPN
brj-25043	187	2	model	model	VERB
brj-25043	187	3	the	the	DET
brj-25043	187	4	gompertz	gompertz	NOUN
brj-25043	187	5	model	model	NOUN
brj-25043	187	6	equation	equation	NOUN
brj-25043	187	7	contains	contain	VERB
brj-25043	187	8	three	three	NUM
brj-25043	187	9	constants	constant	NOUN
brj-25043	187	10	,	,	PUNCT
brj-25043	187	11	a	a	DET
brj-25043	187	12	,	,	PUNCT
brj-25043	187	13	𝑏	𝑏	NOUN
brj-25043	187	14	,	,	PUNCT
brj-25043	187	15	and	and	CCONJ
brj-25043	187	16	𝑐.	𝑐.	VERB
brj-25043	187	17	the	the	DET
brj-25043	187	18	constant	constant	ADJ
brj-25043	188	1	a	a	PRON
brj-25043	188	2	is	be	AUX
brj-25043	188	3	the	the	DET
brj-25043	188	4	biogas	biogas	NOUN
brj-25043	188	5	production	production	NOUN
brj-25043	188	6	potential	potential	NOUN
brj-25043	188	7	(	(	PUNCT
brj-25043	188	8	𝐿	𝐿	PROPN
brj-25043	188	9	𝐾𝑔−1𝑑−1	𝐾𝑔−1𝑑−1	PROPN
brj-25043	188	10	)	)	PUNCT
brj-25043	188	11	,	,	PUNCT
brj-25043	188	12	while	while	SCONJ
brj-25043	188	13	𝑏	𝑏	PRON
brj-25043	188	14	is	be	AUX
brj-25043	188	15	a	a	DET
brj-25043	188	16	dimensionless	dimensionless	NOUN
brj-25043	188	17	constant	constant	ADJ
brj-25043	188	18	,	,	PUNCT
brj-25043	188	19	and	and	CCONJ
brj-25043	188	20	𝑐	𝑐	PROPN
brj-25043	188	21	is	be	AUX
brj-25043	188	22	another	another	DET
brj-25043	188	23	constant	constant	ADJ
brj-25043	188	24	in	in	ADP
brj-25043	188	25	(	(	PUNCT
brj-25043	188	26	𝑑−1	𝑑−1	PROPN
brj-25043	188	27	)	)	PUNCT
brj-25043	188	28	(	(	PUNCT
brj-25043	188	29	zwietering	zwietering	NOUN
brj-25043	188	30	et	et	PROPN
brj-25043	188	31	al	al	PROPN
brj-25043	188	32	.	.	PROPN
brj-25043	188	33	1990	1990	NUM
brj-25043	188	34	;	;	PUNCT
brj-25043	188	35	mueller	mueller	PROPN
brj-25043	188	36	et	et	PROPN
brj-25043	188	37	al	al	PROPN
brj-25043	188	38	.	.	PROPN
brj-25043	188	39	1995	1995	NUM
brj-25043	188	40	;	;	PUNCT
brj-25043	188	41	lo	lo	PROPN
brj-25043	188	42	et	et	PROPN
brj-25043	188	43	al	al	PROPN
brj-25043	188	44	.	.	PROPN
brj-25043	188	45	2010	2010	NUM
brj-25043	188	46	;	;	PUNCT
brj-25043	188	47	peleg	peleg	NOUN
brj-25043	188	48	and	and	CCONJ
brj-25043	188	49	corradini	corradini	NOUN
brj-25043	188	50	2011	2011	NUM
brj-25043	188	51	):	):	PUNCT
brj-25043	188	52	p𝑏𝑔	p𝑏𝑔	PROPN
brj-25043	188	53	=	=	PUNCT
brj-25043	188	54	a	a	DET
brj-25043	188	55	𝑒𝑥𝑝	𝑒𝑥𝑝	INTJ
brj-25043	188	56	(	(	PUNCT
brj-25043	188	57	−exp	−exp	NOUN
brj-25043	188	58	(	(	PUNCT
brj-25043	188	59	𝑏	𝑏	PROPN
brj-25043	188	60	−	−	PROPN
brj-25043	188	61	𝑐𝑡	𝑐𝑡	PROPN
brj-25043	188	62	)	)	PUNCT
brj-25043	188	63	)	)	PUNCT
brj-25043	188	64	(	(	PUNCT
brj-25043	188	65	7	7	X
brj-25043	188	66	)	)	PUNCT
brj-25043	188	67	modified	modify	VERB
brj-25043	188	68	gompertz	gompertz	NOUN
brj-25043	188	69	model	model	NOUN
brj-25043	188	70	the	the	DET
brj-25043	188	71	modified	modify	VERB
brj-25043	188	72	gompertz	gompertz	NOUN
brj-25043	188	73	model	model	NOUN
brj-25043	188	74	is	be	AUX
brj-25043	188	75	one	one	NUM
brj-25043	188	76	of	of	ADP
brj-25043	188	77	the	the	DET
brj-25043	188	78	most	most	ADV
brj-25043	188	79	notable	notable	ADJ
brj-25043	188	80	models	model	NOUN
brj-25043	188	81	and	and	CCONJ
brj-25043	188	82	presented	present	VERB
brj-25043	188	83	by	by	ADP
brj-25043	188	84	eq	eq	PROPN
brj-25043	188	85	.	.	PROPN
brj-25043	188	86	8	8	NUM
brj-25043	188	87	(	(	PUNCT
brj-25043	188	88	zwietering	zwietering	NOUN
brj-25043	188	89	et	et	PROPN
brj-25043	188	90	al	al	PROPN
brj-25043	188	91	.	.	PROPN
brj-25043	188	92	1990	1990	NUM
brj-25043	188	93	;	;	PUNCT
brj-25043	188	94	li	li	PROPN
brj-25043	188	95	and	and	CCONJ
brj-25043	188	96	fang	fang	PROPN
brj-25043	188	97	2007	2007	NUM
brj-25043	188	98	;	;	PUNCT
brj-25043	188	99	budiyono	budiyono	PROPN
brj-25043	188	100	et	et	PROPN
brj-25043	188	101	al	al	PROPN
brj-25043	188	102	.	.	PROPN
brj-25043	188	103	2010	2010	NUM
brj-25043	188	104	;	;	PUNCT
brj-25043	188	105	lo	lo	PROPN
brj-25043	188	106	et	et	PROPN
brj-25043	188	107	al	al	PROPN
brj-25043	188	108	.	.	PROPN
brj-25043	188	109	2010	2010	NUM
brj-25043	188	110	):	):	PUNCT
brj-25043	188	111	p𝑏𝑔	p𝑏𝑔	PROPN
brj-25043	188	112	=	=	PROPN
brj-25043	188	113	a	a	DET
brj-25043	188	114	exp	exp	NOUN
brj-25043	188	115	(	(	PUNCT
brj-25043	188	116	exp	exp	NOUN
brj-25043	188	117	(	(	PUNCT
brj-25043	188	118	dm	dm	PROPN
brj-25043	188	119	e	e	PROPN
brj-25043	188	120	a	a	DET
brj-25043	188	121	(	(	PUNCT
brj-25043	188	122	λt)+1	λt)+1	NOUN
brj-25043	188	123	)	)	PUNCT
brj-25043	188	124	)	)	PUNCT
brj-25043	189	1	(	(	PUNCT
brj-25043	189	2	8)	8)	NUM
brj-25043	189	3	this	this	DET
brj-25043	189	4	model	model	NOUN
brj-25043	189	5	equation	equation	NOUN
brj-25043	189	6	has	have	VERB
brj-25043	189	7	the	the	DET
brj-25043	189	8	constant	constant	ADJ
brj-25043	189	9	a	a	PRON
brj-25043	189	10	as	as	ADV
brj-25043	189	11	defined	define	VERB
brj-25043	189	12	before	before	ADV
brj-25043	189	13	,	,	PUNCT
brj-25043	189	14	dm	dm	PROPN
brj-25043	189	15	is	be	AUX
brj-25043	189	16	the	the	DET
brj-25043	189	17	maximal	maximal	ADJ
brj-25043	189	18	daily	daily	ADJ
brj-25043	189	19	biogas	biogas	NOUN
brj-25043	189	20	production	production	NOUN
brj-25043	189	21	rate	rate	NOUN
brj-25043	189	22	(	(	PUNCT
brj-25043	189	23	𝐿	𝐿	PROPN
brj-25043	189	24	𝐾𝑔−1𝑑−1	𝐾𝑔−1𝑑−1	PROPN
brj-25043	189	25	)	)	PUNCT
brj-25043	189	26	,	,	PUNCT
brj-25043	189	27	λ	λ	PROPN
brj-25043	189	28	is	be	AUX
brj-25043	189	29	the	the	DET
brj-25043	189	30	lag	lag	NOUN
brj-25043	189	31	phase	phase	NOUN
brj-25043	189	32	(	(	PUNCT
brj-25043	189	33	𝑑	𝑑	NOUN
brj-25043	189	34	)	)	PUNCT
brj-25043	189	35	,	,	PUNCT
brj-25043	189	36	and	and	CCONJ
brj-25043	189	37	e	e	NOUN
brj-25043	189	38	is	be	AUX
brj-25043	189	39	euler	euler	NOUN
brj-25043	189	40	’s	’s	PART
brj-25043	189	41	number	number	NOUN
brj-25043	189	42	.	.	PUNCT
brj-25043	190	1	this	this	DET
brj-25043	190	2	model	model	NOUN
brj-25043	190	3	was	be	AUX
brj-25043	190	4	extensively	extensively	ADV
brj-25043	190	5	applied	apply	VERB
brj-25043	190	6	in	in	ADP
brj-25043	190	7	many	many	ADJ
brj-25043	190	8	ad	ad	NOUN
brj-25043	190	9	problems	problem	NOUN
brj-25043	190	10	because	because	SCONJ
brj-25043	190	11	of	of	ADP
brj-25043	190	12	its	its	PRON
brj-25043	190	13	high	high	ADJ
brj-25043	190	14	correlation	correlation	NOUN
brj-25043	190	15	.	.	PUNCT
brj-25043	191	1	li	li	PROPN
brj-25043	191	2	and	and	CCONJ
brj-25043	191	3	fang	fang	X
brj-25043	191	4	(	(	PUNCT
brj-25043	191	5	2007	2007	NUM
brj-25043	191	6	)	)	PUNCT
brj-25043	191	7	used	use	VERB
brj-25043	191	8	this	this	DET
brj-25043	191	9	model	model	NOUN
brj-25043	191	10	to	to	PART
brj-25043	191	11	simulate	simulate	VERB
brj-25043	191	12	the	the	DET
brj-25043	191	13	inhibition	inhibition	NOUN
brj-25043	191	14	of	of	ADP
brj-25043	191	15	h2	h2	NOUN
brj-25043	191	16	production	production	NOUN
brj-25043	191	17	potential	potential	NOUN
brj-25043	191	18	due	due	ADP
brj-25043	191	19	to	to	ADP
brj-25043	191	20	the	the	DET
brj-25043	191	21	effect	effect	NOUN
brj-25043	191	22	of	of	ADP
brj-25043	191	23	six	six	NUM
brj-25043	191	24	heavy	heavy	ADJ
brj-25043	191	25	metals	metal	NOUN
brj-25043	191	26	on	on	ADP
brj-25043	191	27	the	the	DET
brj-25043	191	28	activity	activity	NOUN
brj-25043	191	29	of	of	ADP
brj-25043	191	30	a	a	DET
brj-25043	191	31	granular	granular	ADJ
brj-25043	191	32	sludge	sludge	NOUN
brj-25043	191	33	.	.	PUNCT
brj-25043	192	1	they	they	PRON
brj-25043	192	2	calculated	calculate	VERB
brj-25043	192	3	the	the	DET
brj-25043	192	4	model	model	NOUN
brj-25043	192	5	constants	constant	NOUN
brj-25043	192	6	for	for	ADP
brj-25043	192	7	different	different	ADJ
brj-25043	192	8	concentrations	concentration	NOUN
brj-25043	192	9	of	of	ADP
brj-25043	192	10	these	these	DET
brj-25043	192	11	metals	metal	NOUN
brj-25043	192	12	,	,	PUNCT
brj-25043	192	13	where	where	SCONJ
brj-25043	192	14	𝑅2	𝑅2	NOUN
brj-25043	192	15	>	>	X
brj-25043	192	16	0.95	0.95	NUM
brj-25043	192	17	in	in	ADP
brj-25043	192	18	all	all	DET
brj-25043	192	19	cases	case	NOUN
brj-25043	192	20	.	.	PUNCT
brj-25043	193	1	moreover	moreover	ADV
brj-25043	193	2	,	,	PUNCT
brj-25043	193	3	lin	lin	PROPN
brj-25043	193	4	and	and	CCONJ
brj-25043	193	5	shei	shei	PROPN
brj-25043	193	6	(	(	PUNCT
brj-25043	193	7	2008	2008	NUM
brj-25043	193	8	)	)	PUNCT
brj-25043	193	9	studied	study	VERB
brj-25043	193	10	the	the	DET
brj-25043	193	11	effects	effect	NOUN
brj-25043	193	12	of	of	ADP
brj-25043	193	13	ionic	ionic	ADJ
brj-25043	193	14	cr	cr	PROPN
brj-25043	193	15	,	,	PUNCT
brj-25043	193	16	cu	cu	PROPN
brj-25043	193	17	,	,	PUNCT
brj-25043	193	18	and	and	CCONJ
brj-25043	193	19	zn	zn	X
brj-25043	193	20	on	on	ADP
brj-25043	193	21	the	the	DET
brj-25043	193	22	fermentative	fermentative	ADJ
brj-25043	193	23	hydrogen	hydrogen	NOUN
brj-25043	193	24	production	production	NOUN
brj-25043	193	25	of	of	ADP
brj-25043	193	26	sewage	sewage	NOUN
brj-25043	193	27	sludge	sludge	NOUN
brj-25043	193	28	.	.	PUNCT
brj-25043	194	1	they	they	PRON
brj-25043	194	2	used	use	VERB
brj-25043	194	3	different	different	ADJ
brj-25043	194	4	dosages	dosage	NOUN
brj-25043	194	5	for	for	ADP
brj-25043	194	6	each	each	DET
brj-25043	194	7	peer	peer	NOUN
brj-25043	194	8	-	-	PUNCT
brj-25043	194	9	reviewed	review	VERB
brj-25043	194	10	review	review	NOUN
brj-25043	194	11	article	article	NOUN
brj-25043	194	12	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	194	13	galal	galal	PROPN
brj-25043	194	14	et	et	PROPN
brj-25043	194	15	al	al	PROPN
brj-25043	194	16	.	.	PROPN
brj-25043	195	1	(	(	PUNCT
brj-25043	195	2	2025	2025	NUM
brj-25043	195	3	)	)	PUNCT
brj-25043	195	4	.	.	PUNCT
brj-25043	196	1	“	"	PUNCT
brj-25043	196	2	math	math	NOUN
brj-25043	196	3	modeling	modeling	NOUN
brj-25043	196	4	biogas	biogas	NOUN
brj-25043	196	5	production	production	NOUN
brj-25043	196	6	,	,	PUNCT
brj-25043	196	7	”	"	PUNCT
brj-25043	196	8	bioresources	bioresource	NOUN
brj-25043	196	9	20(4	20(4	NOUN
brj-25043	196	10	)	)	PUNCT
brj-25043	196	11	,	,	PUNCT
brj-25043	196	12	11237	11237	NUM
brj-25043	196	13	-	-	SYM
brj-25043	196	14	11266	11266	NUM
brj-25043	196	15	.	.	PUNCT
brj-25043	197	1	11250	11250	NUM
brj-25043	197	2	metal	metal	NOUN
brj-25043	197	3	and	and	CCONJ
brj-25043	197	4	estimated	estimate	VERB
brj-25043	197	5	the	the	DET
brj-25043	197	6	model	model	NOUN
brj-25043	197	7	constants	constant	NOUN
brj-25043	197	8	and	and	CCONJ
brj-25043	197	9	correlation	correlation	NOUN
brj-25043	197	10	in	in	ADP
brj-25043	197	11	all	all	DET
brj-25043	197	12	cases	case	NOUN
brj-25043	197	13	.	.	PUNCT
brj-25043	198	1	the	the	DET
brj-25043	198	2	model	model	NOUN
brj-25043	198	3	was	be	AUX
brj-25043	198	4	nearly	nearly	ADV
brj-25043	198	5	perfect	perfect	ADJ
brj-25043	198	6	for	for	ADP
brj-25043	198	7	the	the	DET
brj-25043	198	8	experimental	experimental	ADJ
brj-25043	198	9	data	datum	NOUN
brj-25043	198	10	,	,	PUNCT
brj-25043	198	11	with	with	ADP
brj-25043	198	12	the	the	DET
brj-25043	198	13	best	good	ADJ
brj-25043	198	14	r²	r²	NOUN
brj-25043	198	15	values	value	NOUN
brj-25043	198	16	of	of	ADP
brj-25043	198	17	0.9981	0.9981	NUM
brj-25043	198	18	,	,	PUNCT
brj-25043	198	19	0.9998	0.9998	NUM
brj-25043	198	20	,	,	PUNCT
brj-25043	198	21	and	and	CCONJ
brj-25043	198	22	0.9923	0.9923	NUM
brj-25043	198	23	for	for	ADP
brj-25043	198	24	investigating	investigate	VERB
brj-25043	198	25	the	the	DET
brj-25043	198	26	effects	effect	NOUN
brj-25043	198	27	.	.	PUNCT
brj-25043	199	1	combined	combine	VERB
brj-25043	199	2	with	with	ADP
brj-25043	199	3	emerging	emerge	VERB
brj-25043	199	4	data	datum	NOUN
brj-25043	199	5	analytics	analytic	NOUN
brj-25043	199	6	,	,	PUNCT
brj-25043	199	7	these	these	DET
brj-25043	199	8	extensions	extension	NOUN
brj-25043	199	9	promise	promise	VERB
brj-25043	199	10	to	to	PART
brj-25043	199	11	bridge	bridge	VERB
brj-25043	199	12	the	the	DET
brj-25043	199	13	gap	gap	NOUN
brj-25043	199	14	between	between	ADP
brj-25043	199	15	theoretical	theoretical	ADJ
brj-25043	199	16	modelling	modelling	NOUN
brj-25043	199	17	and	and	CCONJ
brj-25043	199	18	practical	practical	ADJ
brj-25043	199	19	implementation	implementation	NOUN
brj-25043	199	20	in	in	ADP
brj-25043	199	21	diverse	diverse	ADJ
brj-25043	199	22	operational	operational	ADJ
brj-25043	199	23	contexts	contexts	NOUN
brj-25043	199	24	of	of	ADP
brj-25043	199	25	cr	cr	PROPN
brj-25043	199	26	,	,	PUNCT
brj-25043	199	27	cu	cu	PROPN
brj-25043	199	28	,	,	PUNCT
brj-25043	199	29	and	and	CCONJ
brj-25043	199	30	zn	zn	NUM
brj-25043	199	31	,	,	PUNCT
brj-25043	199	32	respectively	respectively	ADV
brj-25043	199	33	.	.	PUNCT
brj-25043	200	1	in	in	ADP
brj-25043	200	2	addition	addition	NOUN
brj-25043	200	3	,	,	PUNCT
brj-25043	200	4	altaş	altaş	NOUN
brj-25043	200	5	(	(	PUNCT
brj-25043	200	6	2009	2009	NUM
brj-25043	200	7	)	)	PUNCT
brj-25043	200	8	studied	study	VERB
brj-25043	200	9	the	the	DET
brj-25043	200	10	inhibitory	inhibitory	ADJ
brj-25043	200	11	effect	effect	NOUN
brj-25043	200	12	of	of	ADP
brj-25043	200	13	four	four	NUM
brj-25043	200	14	of	of	ADP
brj-25043	200	15	these	these	DET
brj-25043	200	16	metals	metal	NOUN
brj-25043	200	17	as	as	SCONJ
brj-25043	200	18	mentioned	mention	VERB
brj-25043	200	19	above	above	ADV
brj-25043	200	20	,	,	PUNCT
brj-25043	200	21	where	where	SCONJ
brj-25043	200	22	it	it	PRON
brj-25043	200	23	was	be	AUX
brj-25043	200	24	shown	show	VERB
brj-25043	200	25	that	that	SCONJ
brj-25043	200	26	r2	r2	PROPN
brj-25043	200	27	was	be	AUX
brj-25043	200	28	greater	great	ADJ
brj-25043	200	29	than	than	ADP
brj-25043	200	30	0.99	0.99	NUM
brj-25043	200	31	for	for	ADP
brj-25043	200	32	all	all	DET
brj-25043	200	33	metals	metal	NOUN
brj-25043	200	34	except	except	SCONJ
brj-25043	200	35	cr	cr	PROPN
brj-25043	200	36	.	.	PUNCT
brj-25043	201	1	additionally	additionally	ADV
brj-25043	201	2	,	,	PUNCT
brj-25043	201	3	tian	tian	PROPN
brj-25043	201	4	et	et	PROPN
brj-25043	201	5	al	al	PROPN
brj-25043	201	6	.	.	PROPN
brj-25043	201	7	(	(	PUNCT
brj-25043	201	8	2020	2020	NUM
brj-25043	201	9	)	)	PUNCT
brj-25043	201	10	studied	study	VERB
brj-25043	201	11	the	the	DET
brj-25043	201	12	kinetic	kinetic	ADJ
brj-25043	201	13	evaluation	evaluation	NOUN
brj-25043	201	14	of	of	ADP
brj-25043	201	15	the	the	DET
brj-25043	201	16	biogas	biogas	NOUN
brj-25043	201	17	potential	potential	NOUN
brj-25043	201	18	from	from	ADP
brj-25043	201	19	a	a	DET
brj-25043	201	20	heavy	heavy	ADJ
brj-25043	201	21	-	-	PUNCT
brj-25043	201	22	metal	metal	NOUN
brj-25043	201	23	-	-	PUNCT
brj-25043	201	24	stressed	stress	VERB
brj-25043	201	25	anaerobic	anaerobic	ADJ
brj-25043	201	26	fermentation	fermentation	NOUN
brj-25043	201	27	process	process	NOUN
brj-25043	201	28	.	.	PUNCT
brj-25043	202	1	the	the	DET
brj-25043	202	2	model	model	NOUN
brj-25043	202	3	showed	show	VERB
brj-25043	202	4	good	good	ADJ
brj-25043	202	5	correlation	correlation	NOUN
brj-25043	202	6	for	for	ADP
brj-25043	202	7	most	most	ADJ
brj-25043	202	8	studied	study	VERB
brj-25043	202	9	metals	metal	NOUN
brj-25043	202	10	with	with	ADP
brj-25043	202	11	different	different	ADJ
brj-25043	202	12	concentrations	concentration	NOUN
brj-25043	202	13	,	,	PUNCT
brj-25043	202	14	where	where	SCONJ
brj-25043	202	15	the	the	DET
brj-25043	202	16	best	good	ADJ
brj-25043	202	17	r2	r2	NOUN
brj-25043	202	18	was	be	AUX
brj-25043	202	19	0.9989	0.9989	PRON
brj-25043	202	20	.	.	PUNCT
brj-25043	203	1	furthermore	furthermore	ADV
brj-25043	203	2	,	,	PUNCT
brj-25043	203	3	li	li	PROPN
brj-25043	203	4	et	et	PROPN
brj-25043	203	5	al	al	PROPN
brj-25043	203	6	.	.	PROPN
brj-25043	203	7	(	(	PUNCT
brj-25043	203	8	2008	2008	NUM
brj-25043	203	9	)	)	PUNCT
brj-25043	203	10	investigated	investigate	VERB
brj-25043	203	11	the	the	DET
brj-25043	203	12	enhancement	enhancement	NOUN
brj-25043	203	13	of	of	ADP
brj-25043	203	14	bio	bio	ADJ
brj-25043	203	15	-	-	ADJ
brj-25043	203	16	hydrogen	hydrogen	NOUN
brj-25043	203	17	production	production	NOUN
brj-25043	203	18	from	from	ADP
brj-25043	203	19	food	food	NOUN
brj-25043	203	20	waste	waste	NOUN
brj-25043	203	21	and	and	CCONJ
brj-25043	203	22	sewage	sewage	NOUN
brj-25043	203	23	sludge	sludge	NOUN
brj-25043	203	24	in	in	ADP
brj-25043	203	25	the	the	DET
brj-25043	203	26	presence	presence	NOUN
brj-25043	203	27	of	of	ADP
brj-25043	203	28	aged	aged	ADJ
brj-25043	203	29	refuse	refuse	NOUN
brj-25043	203	30	excavated	excavate	VERB
brj-25043	203	31	from	from	ADP
brj-25043	203	32	a	a	DET
brj-25043	203	33	refuse	refuse	ADJ
brj-25043	203	34	landfill	landfill	NOUN
brj-25043	203	35	.	.	PUNCT
brj-25043	204	1	they	they	PRON
brj-25043	204	2	applied	apply	VERB
brj-25043	204	3	the	the	DET
brj-25043	204	4	modified	modify	VERB
brj-25043	204	5	gompertz	gompertz	NOUN
brj-25043	204	6	model	model	NOUN
brj-25043	204	7	to	to	PART
brj-25043	204	8	plot	plot	VERB
brj-25043	204	9	the	the	DET
brj-25043	204	10	biogas	biogas	NOUN
brj-25043	204	11	production	production	NOUN
brj-25043	204	12	,	,	PUNCT
brj-25043	204	13	which	which	PRON
brj-25043	204	14	showed	show	VERB
brj-25043	204	15	a	a	DET
brj-25043	204	16	relatively	relatively	ADV
brj-25043	204	17	high	high	ADJ
brj-25043	204	18	correlation	correlation	NOUN
brj-25043	204	19	with	with	ADP
brj-25043	204	20	r2	r2	NOUN
brj-25043	204	21	of	of	ADP
brj-25043	204	22	0.9820	0.9820	NUM
brj-25043	204	23	.	.	PUNCT
brj-25043	205	1	in	in	ADP
brj-25043	205	2	another	another	DET
brj-25043	205	3	work	work	NOUN
brj-25043	205	4	concerning	concern	VERB
brj-25043	205	5	food	food	NOUN
brj-25043	205	6	waste	waste	NOUN
brj-25043	205	7	,	,	PUNCT
brj-25043	205	8	deepanraj	deepanraj	VERB
brj-25043	205	9	et	et	PROPN
brj-25043	205	10	al	al	PROPN
brj-25043	205	11	.	.	PROPN
brj-25043	206	1	(	(	PUNCT
brj-25043	206	2	2017	2017	NUM
brj-25043	206	3	)	)	PUNCT
brj-25043	206	4	used	use	VERB
brj-25043	206	5	this	this	DET
brj-25043	206	6	model	model	NOUN
brj-25043	206	7	to	to	PART
brj-25043	206	8	simulate	simulate	VERB
brj-25043	206	9	the	the	DET
brj-25043	206	10	four	four	NUM
brj-25043	206	11	cases	case	NOUN
brj-25043	206	12	of	of	ADP
brj-25043	206	13	digestate	digestate	NOUN
brj-25043	206	14	,	,	PUNCT
brj-25043	206	15	as	as	SCONJ
brj-25043	206	16	mentioned	mention	VERB
brj-25043	206	17	before	before	ADV
brj-25043	206	18	.	.	PUNCT
brj-25043	207	1	the	the	DET
brj-25043	207	2	best	good	ADJ
brj-25043	207	3	was	be	AUX
brj-25043	207	4	0.9995	0.9995	NUM
brj-25043	207	5	in	in	ADP
brj-25043	207	6	the	the	DET
brj-25043	207	7	case	case	NOUN
brj-25043	207	8	of	of	ADP
brj-25043	207	9	nt	not	PART
brj-25043	207	10	.	.	PUNCT
brj-25043	208	1	moreover	moreover	ADV
brj-25043	208	2	,	,	PUNCT
brj-25043	208	3	mu	mu	PROPN
brj-25043	208	4	et	et	PROPN
brj-25043	208	5	al	al	PROPN
brj-25043	208	6	.	.	PROPN
brj-25043	209	1	(	(	PUNCT
brj-25043	209	2	2007	2007	NUM
brj-25043	209	3	)	)	PUNCT
brj-25043	209	4	used	use	VERB
brj-25043	209	5	this	this	DET
brj-25043	209	6	model	model	NOUN
brj-25043	209	7	in	in	ADP
brj-25043	209	8	the	the	DET
brj-25043	209	9	problem	problem	NOUN
brj-25043	209	10	mentioned	mention	VERB
brj-25043	209	11	,	,	PUNCT
brj-25043	209	12	showing	show	VERB
brj-25043	209	13	an	an	DET
brj-25043	209	14	r2	r2	NOUN
brj-25043	209	15	of	of	ADP
brj-25043	209	16	0.9940	0.9940	NUM
brj-25043	209	17	.	.	PUNCT
brj-25043	210	1	budiyono	budiyono	PROPN
brj-25043	210	2	et	et	PROPN
brj-25043	210	3	al	al	PROPN
brj-25043	210	4	.	.	PROPN
brj-25043	211	1	(	(	PUNCT
brj-25043	211	2	2010	2010	NUM
brj-25043	211	3	)	)	PUNCT
brj-25043	211	4	predicted	predict	VERB
brj-25043	211	5	the	the	DET
brj-25043	211	6	biogas	biogas	NOUN
brj-25043	211	7	production	production	NOUN
brj-25043	211	8	rate	rate	NOUN
brj-25043	211	9	from	from	ADP
brj-25043	211	10	cattle	cattle	NOUN
brj-25043	211	11	manure	manure	NOUN
brj-25043	211	12	.	.	PUNCT
brj-25043	212	1	they	they	PRON
brj-25043	212	2	employed	employ	VERB
brj-25043	212	3	this	this	DET
brj-25043	212	4	model	model	NOUN
brj-25043	212	5	for	for	ADP
brj-25043	212	6	two	two	NUM
brj-25043	212	7	substrates	substrate	NOUN
brj-25043	212	8	to	to	PART
brj-25043	212	9	investigate	investigate	VERB
brj-25043	212	10	the	the	DET
brj-25043	212	11	effect	effect	NOUN
brj-25043	212	12	of	of	ADP
brj-25043	212	13	liquid	liquid	ADJ
brj-25043	212	14	rumen	ruman	NOUN
brj-25043	212	15	to	to	PART
brj-25043	212	16	cumulative	cumulative	VERB
brj-25043	212	17	biogas	biogas	NOUN
brj-25043	212	18	production	production	NOUN
brj-25043	212	19	.	.	PUNCT
brj-25043	213	1	the	the	DET
brj-25043	213	2	first	first	ADJ
brj-25043	213	3	substrate	substrate	NOUN
brj-25043	213	4	consisted	consist	VERB
brj-25043	213	5	of	of	ADP
brj-25043	213	6	100	100	NUM
brj-25043	213	7	g	g	NOUN
brj-25043	213	8	manure	manure	NOUN
brj-25043	213	9	and	and	CCONJ
brj-25043	213	10	100	100	NUM
brj-25043	213	11	ml	ml	NOUN
brj-25043	213	12	rumen	ruman	NOUN
brj-25043	213	13	(	(	PUNCT
brj-25043	213	14	mr	mr	PROPN
brj-25043	213	15	11	11	NUM
brj-25043	213	16	)	)	PUNCT
brj-25043	213	17	,	,	PUNCT
brj-25043	213	18	while	while	SCONJ
brj-25043	213	19	the	the	DET
brj-25043	213	20	second	second	ADJ
brj-25043	213	21	one	one	NOUN
brj-25043	213	22	consisted	consist	VERB
brj-25043	213	23	of	of	ADP
brj-25043	213	24	manure	manure	NOUN
brj-25043	213	25	and	and	CCONJ
brj-25043	213	26	water	water	NOUN
brj-25043	213	27	in	in	ADP
brj-25043	213	28	equal	equal	ADJ
brj-25043	213	29	weight	weight	NOUN
brj-25043	213	30	ratio	ratio	NOUN
brj-25043	213	31	(	(	PUNCT
brj-25043	213	32	mw	mw	PROPN
brj-25043	213	33	11	11	NUM
brj-25043	213	34	)	)	PUNCT
brj-25043	213	35	.	.	PUNCT
brj-25043	214	1	the	the	DET
brj-25043	214	2	biogas	biogas	NOUN
brj-25043	214	3	production	production	NOUN
brj-25043	214	4	from	from	ADP
brj-25043	214	5	both	both	DET
brj-25043	214	6	substrates	substrate	NOUN
brj-25043	214	7	was	be	AUX
brj-25043	214	8	studied	study	VERB
brj-25043	214	9	,	,	PUNCT
brj-25043	214	10	the	the	DET
brj-25043	214	11	model	model	NOUN
brj-25043	214	12	parameters	parameter	NOUN
brj-25043	214	13	were	be	AUX
brj-25043	214	14	estimated	estimate	VERB
brj-25043	214	15	and	and	CCONJ
brj-25043	214	16	r2	r2	PROPN
brj-25043	214	17	was	be	AUX
brj-25043	214	18	0.9983	0.9983	NUM
brj-25043	214	19	for	for	ADP
brj-25043	214	20	mr	mr	PROPN
brj-25043	214	21	11	11	NUM
brj-25043	214	22	and	and	CCONJ
brj-25043	214	23	0.9987	0.9987	NUM
brj-25043	214	24	for	for	ADP
brj-25043	214	25	mw	mw	X
brj-25043	214	26	11	11	NUM
brj-25043	214	27	.	.	PUNCT
brj-25043	215	1	in	in	ADP
brj-25043	215	2	addition	addition	NOUN
brj-25043	215	3	,	,	PUNCT
brj-25043	215	4	they	they	PRON
brj-25043	215	5	have	have	AUX
brj-25043	215	6	performed	perform	VERB
brj-25043	215	7	further	further	ADJ
brj-25043	215	8	experiments	experiment	NOUN
brj-25043	215	9	in	in	ADP
brj-25043	215	10	room	room	NOUN
brj-25043	215	11	temperature	temperature	NOUN
brj-25043	215	12	and	and	CCONJ
brj-25043	215	13	38.5	38.5	NUM
brj-25043	215	14	°	°	NOUN
brj-25043	215	15	c	c	NOUN
brj-25043	215	16	to	to	PART
brj-25043	215	17	investigate	investigate	VERB
brj-25043	215	18	the	the	DET
brj-25043	215	19	temperature	temperature	NOUN
brj-25043	215	20	effect	effect	NOUN
brj-25043	215	21	on	on	ADP
brj-25043	215	22	the	the	DET
brj-25043	215	23	biogas	biogas	NOUN
brj-25043	215	24	production	production	NOUN
brj-25043	215	25	from	from	ADP
brj-25043	215	26	both	both	DET
brj-25043	215	27	substrates	substrate	NOUN
brj-25043	215	28	.	.	PUNCT
brj-25043	216	1	furthermore	furthermore	ADV
brj-25043	216	2	,	,	PUNCT
brj-25043	216	3	this	this	DET
brj-25043	216	4	model	model	NOUN
brj-25043	216	5	has	have	AUX
brj-25043	216	6	been	be	AUX
brj-25043	216	7	used	use	VERB
brj-25043	216	8	to	to	PART
brj-25043	216	9	plot	plot	VERB
brj-25043	216	10	the	the	DET
brj-25043	216	11	biogas	biogas	NOUN
brj-25043	216	12	production	production	NOUN
brj-25043	216	13	resulted	result	VERB
brj-25043	216	14	from	from	ADP
brj-25043	216	15	the	the	DET
brj-25043	216	16	co	co	NOUN
brj-25043	216	17	-	-	NOUN
brj-25043	216	18	digestion	digestion	NOUN
brj-25043	216	19	of	of	ADP
brj-25043	216	20	horse	horse	NOUN
brj-25043	216	21	and	and	CCONJ
brj-25043	216	22	cow	cow	NOUN
brj-25043	216	23	dung	dung	NOUN
brj-25043	216	24	(	(	PUNCT
brj-25043	216	25	yusuf	yusuf	PROPN
brj-25043	216	26	et	et	PROPN
brj-25043	216	27	al	al	PROPN
brj-25043	216	28	.	.	PROPN
brj-25043	216	29	2011	2011	NUM
brj-25043	216	30	)	)	PUNCT
brj-25043	216	31	,	,	PUNCT
brj-25043	216	32	where	where	SCONJ
brj-25043	216	33	they	they	PRON
brj-25043	216	34	designed	design	VERB
brj-25043	216	35	five	five	NUM
brj-25043	216	36	different	different	ADJ
brj-25043	216	37	mixtures	mixture	NOUN
brj-25043	216	38	of	of	ADP
brj-25043	216	39	these	these	DET
brj-25043	216	40	dungs	dung	NOUN
brj-25043	216	41	based	base	VERB
brj-25043	216	42	on	on	ADP
brj-25043	216	43	weight	weight	NOUN
brj-25043	216	44	.	.	PUNCT
brj-25043	217	1	the	the	DET
brj-25043	217	2	maximum	maximum	ADJ
brj-25043	217	3	biogas	biogas	NOUN
brj-25043	217	4	production	production	NOUN
brj-25043	217	5	potential	potential	NOUN
brj-25043	217	6	and	and	CCONJ
brj-25043	217	7	the	the	DET
brj-25043	217	8	best	good	ADJ
brj-25043	217	9	r2	r2	NOUN
brj-25043	217	10	were	be	AUX
brj-25043	217	11	achieved	achieve	VERB
brj-25043	217	12	for	for	ADP
brj-25043	217	13	the	the	DET
brj-25043	217	14	ratio	ratio	NOUN
brj-25043	217	15	of	of	ADP
brj-25043	217	16	75	75	NUM
brj-25043	217	17	%	%	NOUN
brj-25043	217	18	horse	horse	NOUN
brj-25043	217	19	dung	dung	NOUN
brj-25043	217	20	and	and	CCONJ
brj-25043	217	21	25	25	NUM
brj-25043	217	22	%	%	NOUN
brj-25043	217	23	cow	cow	NOUN
brj-25043	217	24	dung	dung	NOUN
brj-25043	217	25	,	,	PUNCT
brj-25043	217	26	where	where	SCONJ
brj-25043	217	27	r2	r2	PROPN
brj-25043	217	28	was	be	AUX
brj-25043	217	29	0.998	0.998	NUM
brj-25043	217	30	.	.	PUNCT
brj-25043	218	1	moreover	moreover	ADV
brj-25043	218	2	,	,	PUNCT
brj-25043	218	3	it	it	PRON
brj-25043	218	4	was	be	AUX
brj-25043	218	5	utilized	utilize	VERB
brj-25043	218	6	to	to	PART
brj-25043	218	7	simulate	simulate	VERB
brj-25043	218	8	and	and	CCONJ
brj-25043	218	9	predict	predict	VERB
brj-25043	218	10	the	the	DET
brj-25043	218	11	biogas	biogas	NOUN
brj-25043	218	12	production	production	NOUN
brj-25043	218	13	evaluated	evaluate	VERB
brj-25043	218	14	by	by	ADP
brj-25043	218	15	lo	lo	PROPN
brj-25043	218	16	et	et	PROPN
brj-25043	218	17	al	al	PROPN
brj-25043	218	18	.	.	PROPN
brj-25043	219	1	(	(	PUNCT
brj-25043	219	2	2010	2010	NUM
brj-25043	219	3	)	)	PUNCT
brj-25043	219	4	,	,	PUNCT
brj-25043	219	5	where	where	SCONJ
brj-25043	219	6	the	the	DET
brj-25043	219	7	best	good	ADJ
brj-25043	219	8	r2	r2	NOUN
brj-25043	219	9	was	be	AUX
brj-25043	219	10	0.9977	0.9977	NUM
brj-25043	219	11	in	in	ADP
brj-25043	219	12	case	case	NOUN
brj-25043	219	13	of	of	ADP
brj-25043	219	14	fa	fa	PROPN
brj-25043	219	15	/	/	SYM
brj-25043	219	16	msw	msw	NOUN
brj-25043	219	17	10	10	NUM
brj-25043	219	18	g	g	PROPN
brj-25043	219	19	l-1	l-1	NOUN
brj-25043	219	20	.	.	PUNCT
brj-25043	220	1	furthermore	furthermore	ADV
brj-25043	220	2	,	,	PUNCT
brj-25043	220	3	concerning	concern	VERB
brj-25043	220	4	the	the	DET
brj-25043	220	5	msw	msw	NOUN
brj-25043	220	6	,	,	PUNCT
brj-25043	220	7	nielfa	nielfa	NOUN
brj-25043	220	8	et	et	PROPN
brj-25043	220	9	al	al	PROPN
brj-25043	220	10	.	.	PROPN
brj-25043	221	1	(	(	PUNCT
brj-25043	221	2	2015	2015	NUM
brj-25043	221	3	)	)	PUNCT
brj-25043	221	4	used	use	VERB
brj-25043	221	5	this	this	DET
brj-25043	221	6	model	model	NOUN
brj-25043	221	7	to	to	PART
brj-25043	221	8	simulate	simulate	VERB
brj-25043	221	9	the	the	DET
brj-25043	221	10	methane	methane	NOUN
brj-25043	221	11	production	production	NOUN
brj-25043	221	12	as	as	SCONJ
brj-25043	221	13	mentioned	mention	VERB
brj-25043	221	14	before	before	ADV
brj-25043	221	15	.	.	PUNCT
brj-25043	222	1	the	the	DET
brj-25043	222	2	best	good	ADJ
brj-25043	222	3	r2	r2	NOUN
brj-25043	222	4	was	be	AUX
brj-25043	222	5	achieved	achieve	VERB
brj-25043	222	6	for	for	ADP
brj-25043	222	7	the	the	DET
brj-25043	222	8	meat	meat	NOUN
brj-25043	222	9	/	/	SYM
brj-25043	222	10	fish	fish	NOUN
brj-25043	222	11	mixture	mixture	NOUN
brj-25043	222	12	with	with	ADP
brj-25043	222	13	the	the	DET
brj-25043	222	14	ofmsw	ofmsw	NOUN
brj-25043	222	15	,	,	PUNCT
brj-25043	222	16	which	which	PRON
brj-25043	222	17	was	be	AUX
brj-25043	222	18	1.00	1.00	NUM
brj-25043	222	19	.	.	PUNCT
brj-25043	223	1	furthermore	furthermore	ADV
brj-25043	223	2	,	,	PUNCT
brj-25043	223	3	cumulative	cumulative	ADJ
brj-25043	223	4	biogas	biogas	NOUN
brj-25043	223	5	production	production	NOUN
brj-25043	223	6	models	model	NOUN
brj-25043	223	7	are	be	AUX
brj-25043	223	8	critical	critical	ADJ
brj-25043	223	9	for	for	ADP
brj-25043	223	10	estimating	estimate	VERB
brj-25043	223	11	total	total	ADJ
brj-25043	223	12	biogas	biogas	NOUN
brj-25043	223	13	yield	yield	NOUN
brj-25043	223	14	,	,	PUNCT
brj-25043	223	15	which	which	PRON
brj-25043	223	16	is	be	AUX
brj-25043	223	17	an	an	DET
brj-25043	223	18	essential	essential	ADJ
brj-25043	223	19	parameter	parameter	NOUN
brj-25043	223	20	for	for	ADP
brj-25043	223	21	system	system	NOUN
brj-25043	223	22	design	design	NOUN
brj-25043	223	23	and	and	CCONJ
brj-25043	223	24	economic	economic	ADJ
brj-25043	223	25	viability	viability	NOUN
brj-25043	223	26	.	.	PUNCT
brj-25043	224	1	data	datum	NOUN
brj-25043	224	2	in	in	ADP
brj-25043	224	3	table	table	NOUN
brj-25043	224	4	3	3	NUM
brj-25043	224	5	,	,	PUNCT
brj-25043	224	6	together	together	ADV
brj-25043	224	7	with	with	ADP
brj-25043	224	8	equations	equation	NOUN
brj-25043	224	9	(	(	PUNCT
brj-25043	224	10	4–8	4–8	NOUN
brj-25043	224	11	)	)	PUNCT
brj-25043	224	12	,	,	PUNCT
brj-25043	224	13	indicate	indicate	VERB
brj-25043	224	14	that	that	SCONJ
brj-25043	224	15	the	the	DET
brj-25043	224	16	logistic	logistic	ADJ
brj-25043	224	17	,	,	PUNCT
brj-25043	224	18	modified	modified	ADJ
brj-25043	224	19	gompertz	gompertz	NOUN
brj-25043	224	20	,	,	PUNCT
brj-25043	224	21	and	and	CCONJ
brj-25043	224	22	exponential	exponential	ADJ
brj-25043	224	23	rise	rise	NOUN
brj-25043	224	24	-	-	PUNCT
brj-25043	224	25	to	to	ADP
brj-25043	224	26	-	-	PUNCT
brj-25043	224	27	maximum	maximum	NOUN
brj-25043	224	28	models	model	NOUN
brj-25043	224	29	consistently	consistently	ADV
brj-25043	224	30	achieve	achieve	VERB
brj-25043	224	31	high	high	ADJ
brj-25043	224	32	prediction	prediction	NOUN
brj-25043	224	33	accuracy	accuracy	NOUN
brj-25043	224	34	(	(	PUNCT
brj-25043	224	35	r²	r²	VERB
brj-25043	224	36	typically	typically	ADV
brj-25043	224	37	>	>	ADP
brj-25043	224	38	0.98–0.99	0.98–0.99	NUM
brj-25043	224	39	)	)	PUNCT
brj-25043	224	40	across	across	ADP
brj-25043	224	41	a	a	DET
brj-25043	224	42	variety	variety	NOUN
brj-25043	224	43	of	of	ADP
brj-25043	224	44	substrates	substrate	NOUN
brj-25043	224	45	,	,	PUNCT
brj-25043	224	46	including	include	VERB
brj-25043	224	47	cow	cow	NOUN
brj-25043	224	48	manure	manure	NOUN
brj-25043	224	49	and	and	CCONJ
brj-25043	224	50	complex	complex	ADJ
brj-25043	224	51	industrial	industrial	ADJ
brj-25043	224	52	wastes	waste	NOUN
brj-25043	224	53	.	.	PUNCT
brj-25043	225	1	the	the	DET
brj-25043	225	2	modified	modify	VERB
brj-25043	225	3	gompertz	gompertz	NOUN
brj-25043	225	4	model	model	NOUN
brj-25043	225	5	stands	stand	VERB
brj-25043	225	6	out	out	ADP
brj-25043	225	7	for	for	ADP
brj-25043	225	8	its	its	PRON
brj-25043	225	9	broad	broad	ADJ
brj-25043	225	10	applicability	applicability	NOUN
brj-25043	225	11	and	and	CCONJ
brj-25043	225	12	reliability	reliability	NOUN
brj-25043	225	13	,	,	PUNCT
brj-25043	225	14	successfully	successfully	ADV
brj-25043	225	15	fitting	fitting	ADJ
brj-25043	225	16	data	datum	NOUN
brj-25043	225	17	even	even	ADV
brj-25043	225	18	under	under	ADP
brj-25043	225	19	inhibitory	inhibitory	ADJ
brj-25043	225	20	conditions	condition	NOUN
brj-25043	225	21	such	such	ADJ
brj-25043	225	22	as	as	ADP
brj-25043	225	23	heavy	heavy	ADJ
brj-25043	225	24	metal	metal	NOUN
brj-25043	225	25	exposure	exposure	NOUN
brj-25043	225	26	.	.	PUNCT
brj-25043	226	1	this	this	DET
brj-25043	226	2	consistently	consistently	ADV
brj-25043	226	3	high	high	ADJ
brj-25043	226	4	performance	performance	NOUN
brj-25043	226	5	underscores	underscore	VERB
brj-25043	226	6	its	its	PRON
brj-25043	226	7	prominence	prominence	NOUN
brj-25043	226	8	as	as	ADP
brj-25043	226	9	the	the	DET
brj-25043	226	10	preferred	preferred	ADJ
brj-25043	226	11	kinetic	kinetic	ADJ
brj-25043	226	12	model	model	NOUN
brj-25043	226	13	for	for	ADP
brj-25043	226	14	comprehensively	comprehensively	ADV
brj-25043	226	15	understanding	understand	VERB
brj-25043	226	16	the	the	DET
brj-25043	226	17	digestion	digestion	NOUN
brj-25043	226	18	process	process	NOUN
brj-25043	226	19	and	and	CCONJ
brj-25043	226	20	predicting	predict	VERB
brj-25043	226	21	ultimate	ultimate	ADJ
brj-25043	226	22	gas	gas	NOUN
brj-25043	226	23	potential	potential	NOUN
brj-25043	226	24	.	.	PUNCT
brj-25043	227	1	less	less	ADV
brj-25043	227	2	-	-	PUNCT
brj-25043	227	3	used	use	VERB
brj-25043	227	4	models	model	NOUN
brj-25043	227	5	some	some	DET
brj-25043	227	6	models	model	NOUN
brj-25043	227	7	are	be	AUX
brj-25043	227	8	rarely	rarely	ADV
brj-25043	227	9	used	use	VERB
brj-25043	227	10	to	to	PART
brj-25043	227	11	plot	plot	VERB
brj-25043	227	12	the	the	DET
brj-25043	227	13	biogas	biogas	NOUN
brj-25043	227	14	production	production	NOUN
brj-25043	227	15	resulting	result	VERB
brj-25043	227	16	from	from	ADP
brj-25043	227	17	the	the	DET
brj-25043	227	18	ad	ad	NOUN
brj-25043	227	19	process	process	NOUN
brj-25043	227	20	.	.	PUNCT
brj-25043	228	1	this	this	PRON
brj-25043	228	2	may	may	AUX
brj-25043	228	3	be	be	AUX
brj-25043	228	4	due	due	ADJ
brj-25043	228	5	to	to	ADP
brj-25043	228	6	their	their	PRON
brj-25043	228	7	complicated	complicated	ADJ
brj-25043	228	8	formulas	formula	NOUN
brj-25043	228	9	,	,	PUNCT
brj-25043	228	10	which	which	PRON
brj-25043	228	11	may	may	AUX
brj-25043	228	12	contain	contain	VERB
brj-25043	228	13	more	more	ADJ
brj-25043	228	14	than	than	ADP
brj-25043	228	15	one	one	NUM
brj-25043	228	16	peer	peer	NOUN
brj-25043	228	17	-	-	PUNCT
brj-25043	228	18	reviewed	review	VERB
brj-25043	228	19	review	review	NOUN
brj-25043	228	20	article	article	NOUN
brj-25043	228	21	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	228	22	galal	galal	PROPN
brj-25043	228	23	et	et	PROPN
brj-25043	228	24	al	al	PROPN
brj-25043	228	25	.	.	PROPN
brj-25043	229	1	(	(	PUNCT
brj-25043	229	2	2025	2025	NUM
brj-25043	229	3	)	)	PUNCT
brj-25043	229	4	.	.	PUNCT
brj-25043	230	1	“	"	PUNCT
brj-25043	230	2	math	math	NOUN
brj-25043	230	3	modeling	modeling	NOUN
brj-25043	230	4	biogas	biogas	NOUN
brj-25043	230	5	production	production	NOUN
brj-25043	230	6	,	,	PUNCT
brj-25043	230	7	”	"	PUNCT
brj-25043	230	8	bioresources	bioresource	NOUN
brj-25043	230	9	20(4	20(4	NOUN
brj-25043	230	10	)	)	PUNCT
brj-25043	230	11	,	,	PUNCT
brj-25043	230	12	11237	11237	NUM
brj-25043	230	13	-	-	SYM
brj-25043	230	14	11266	11266	NUM
brj-25043	230	15	.	.	PUNCT
brj-25043	231	1	11251	11251	NUM
brj-25043	231	2	constant	constant	ADJ
brj-25043	231	3	,	,	PUNCT
brj-25043	231	4	and	and	CCONJ
brj-25043	231	5	hence	hence	ADV
brj-25043	231	6	their	their	PRON
brj-25043	231	7	difficulty	difficulty	NOUN
brj-25043	231	8	in	in	ADP
brj-25043	231	9	application	application	NOUN
brj-25043	231	10	.	.	PUNCT
brj-25043	232	1	this	this	DET
brj-25043	232	2	group	group	NOUN
brj-25043	232	3	of	of	ADP
brj-25043	232	4	models	model	NOUN
brj-25043	232	5	includes	include	VERB
brj-25043	232	6	richard	richard	PROPN
brj-25043	232	7	,	,	PUNCT
brj-25043	232	8	stannard	stannard	NOUN
brj-25043	232	9	,	,	PUNCT
brj-25043	232	10	schunte	schunte	NOUN
brj-25043	232	11	,	,	PUNCT
brj-25043	232	12	and	and	CCONJ
brj-25043	232	13	their	their	PRON
brj-25043	232	14	modified	modify	VERB
brj-25043	232	15	versions	version	NOUN
brj-25043	232	16	.	.	PUNCT
brj-25043	233	1	this	this	DET
brj-25043	233	2	model	model	NOUN
brj-25043	233	3	used	use	VERB
brj-25043	233	4	the	the	DET
brj-25043	233	5	equation	equation	NOUN
brj-25043	233	6	of	of	ADP
brj-25043	233	7	richards	richard	NOUN
brj-25043	233	8	’s	’s	PART
brj-25043	233	9	model	model	NOUN
brj-25043	233	10	which	which	PRON
brj-25043	233	11	is	be	AUX
brj-25043	233	12	represented	represent	VERB
brj-25043	233	13	by	by	ADP
brj-25043	233	14	the	the	DET
brj-25043	233	15	following	follow	VERB
brj-25043	233	16	equation	equation	NOUN
brj-25043	233	17	(	(	PUNCT
brj-25043	233	18	hsieh	hsieh	PROPN
brj-25043	233	19	2009	2009	NUM
brj-25043	233	20	)	)	PUNCT
brj-25043	233	21	,	,	PUNCT
brj-25043	233	22	pbg	pbg	PROPN
brj-25043	233	23	=	=	PROPN
brj-25043	233	24	a	a	PRON
brj-25043	233	25	(	(	PUNCT
brj-25043	233	26	1+𝜈	1+𝜈	NUM
brj-25043	233	27	exp	exp	NOUN
brj-25043	233	28	(	(	PUNCT
brj-25043	233	29	−	−	PROPN
brj-25043	233	30	𝑘(𝜏-t	𝑘(𝜏-t	NUM
brj-25043	233	31	)	)	PUNCT
brj-25043	233	32	)	)	PUNCT
brj-25043	233	33	)	)	PUNCT
brj-25043	233	34	(	(	PUNCT
brj-25043	233	35	−1/𝜈	−1/𝜈	PROPN
brj-25043	233	36	)	)	PUNCT
brj-25043	233	37	(	(	PUNCT
brj-25043	233	38	9	9	NUM
brj-25043	233	39	)	)	PUNCT
brj-25043	233	40	where	where	SCONJ
brj-25043	233	41	a	a	DET
brj-25043	233	42	,	,	PUNCT
brj-25043	233	43	k	k	NOUN
brj-25043	233	44	,	,	PUNCT
brj-25043	233	45	and	and	CCONJ
brj-25043	233	46	𝜏	𝜏	NOUN
brj-25043	233	47	are	be	AUX
brj-25043	233	48	the	the	DET
brj-25043	233	49	biogas	biogas	NOUN
brj-25043	233	50	production	production	NOUN
brj-25043	233	51	potential	potential	NOUN
brj-25043	233	52	,	,	PUNCT
brj-25043	233	53	delay	delay	NOUN
brj-25043	233	54	time	time	NOUN
brj-25043	233	55	,	,	PUNCT
brj-25043	233	56	and	and	CCONJ
brj-25043	233	57	a	a	DET
brj-25043	233	58	constant	constant	ADJ
brj-25043	233	59	,	,	PUNCT
brj-25043	233	60	respectively	respectively	ADV
brj-25043	233	61	,	,	PUNCT
brj-25043	233	62	while	while	SCONJ
brj-25043	233	63	𝜈	𝜈	PRON
brj-25043	233	64	is	be	AUX
brj-25043	233	65	an	an	DET
brj-25043	233	66	additional	additional	ADJ
brj-25043	233	67	constant	constant	NOUN
brj-25043	233	68	that	that	PRON
brj-25043	233	69	provides	provide	VERB
brj-25043	233	70	more	more	ADJ
brj-25043	233	71	flexibility	flexibility	NOUN
brj-25043	233	72	for	for	ADP
brj-25043	233	73	the	the	DET
brj-25043	233	74	biogas	biogas	NOUN
brj-25043	233	75	production	production	NOUN
brj-25043	233	76	simulation	simulation	NOUN
brj-25043	233	77	,	,	PUNCT
brj-25043	233	78	as	as	SCONJ
brj-25043	233	79	shown	show	VERB
brj-25043	233	80	by	by	ADP
brj-25043	233	81	eq	eq	PROPN
brj-25043	233	82	.	.	PROPN
brj-25043	233	83	10	10	NUM
brj-25043	233	84	:	:	PUNCT
brj-25043	233	85	pbg	pbg	PROPN
brj-25043	233	86	=	=	PROPN
brj-25043	233	87	a	a	PRON
brj-25043	233	88	(	(	PUNCT
brj-25043	233	89	1+𝜈	1+𝜈	NUM
brj-25043	233	90	exp(1+𝜈	exp(1+𝜈	NOUN
brj-25043	233	91	)	)	PUNCT
brj-25043	233	92	.	.	PUNCT
brj-25043	234	1	exp	exp	NOUN
brj-25043	234	2	(	(	PUNCT
brj-25043	234	3	μm	μm	INTJ
brj-25043	234	4	a	a	DET
brj-25043	234	5	(	(	PUNCT
brj-25043	234	6	1+𝜈	1+𝜈	NUM
brj-25043	234	7	)	)	PUNCT
brj-25043	234	8	(	(	PUNCT
brj-25043	234	9	1	1	NUM
brj-25043	234	10	+	+	SYM
brj-25043	234	11	1	1	NUM
brj-25043	234	12	𝜈	𝜈	NOUN
brj-25043	234	13	)	)	PUNCT
brj-25043	234	14	(	(	PUNCT
brj-25043	234	15	λt	λt	ADP
brj-25043	234	16	)	)	PUNCT
brj-25043	234	17	)	)	PUNCT
brj-25043	234	18	)	)	PUNCT
brj-25043	234	19	(	(	PUNCT
brj-25043	234	20	−1/𝜈	−1/𝜈	PROPN
brj-25043	234	21	)	)	PUNCT
brj-25043	234	22	(	(	PUNCT
brj-25043	234	23	10	10	NUM
brj-25043	234	24	)	)	PUNCT
brj-25043	234	25	consider	consider	VERB
brj-25043	234	26	v	v	NOUN
brj-25043	234	27	=	=	SYM
brj-25043	234	28	m-1	m-1	NOUN
brj-25043	234	29	,	,	PUNCT
brj-25043	234	30	and	and	CCONJ
brj-25043	234	31	depending	depend	VERB
brj-25043	234	32	on	on	ADP
brj-25043	234	33	the	the	DET
brj-25043	234	34	value	value	NOUN
brj-25043	234	35	of	of	ADP
brj-25043	234	36	m	m	PROPN
brj-25043	234	37	,	,	PUNCT
brj-25043	234	38	eq	eq	NOUN
brj-25043	234	39	.	.	PROPN
brj-25043	234	40	10	10	NUM
brj-25043	234	41	will	will	AUX
brj-25043	234	42	be	be	AUX
brj-25043	234	43	reduced	reduce	VERB
brj-25043	234	44	to	to	ADP
brj-25043	234	45	:	:	PUNCT
brj-25043	234	46	the	the	DET
brj-25043	234	47	gompertz	gompertz	NOUN
brj-25043	234	48	equation	equation	NOUN
brj-25043	234	49	if	if	SCONJ
brj-25043	234	50	m→1	m→1	VERB
brj-25043	234	51	,	,	PUNCT
brj-25043	234	52	monomolecular	monomolecular	ADJ
brj-25043	234	53	equation	equation	NOUN
brj-25043	234	54	if	if	SCONJ
brj-25043	234	55	m	m	NOUN
brj-25043	234	56	=	=	NOUN
brj-25043	234	57	1	1	NUM
brj-25043	234	58	,	,	PUNCT
brj-25043	234	59	logistic	logistic	ADJ
brj-25043	234	60	equation	equation	NOUN
brj-25043	234	61	if	if	SCONJ
brj-25043	234	62	m	m	VERB
brj-25043	234	63	=	=	SYM
brj-25043	234	64	2	2	NUM
brj-25043	234	65	,	,	PUNCT
brj-25043	234	66	or	or	CCONJ
brj-25043	234	67	the	the	DET
brj-25043	234	68	von	von	PROPN
brj-25043	234	69	bertalanffy	bertalanffy	PROPN
brj-25043	234	70	if	if	SCONJ
brj-25043	234	71	m	m	PROPN
brj-25043	234	72	=	=	SYM
brj-25043	234	73	2/3	2/3	NUM
brj-25043	234	74	(	(	PUNCT
brj-25043	234	75	fan	fan	NOUN
brj-25043	234	76	et	et	PROPN
brj-25043	234	77	al	al	PROPN
brj-25043	234	78	.	.	PROPN
brj-25043	234	79	2004	2004	NUM
brj-25043	234	80	)	)	PUNCT
brj-25043	234	81	.	.	PUNCT
brj-25043	235	1	this	this	DET
brj-25043	235	2	model	model	NOUN
brj-25043	235	3	was	be	AUX
brj-25043	235	4	used	use	VERB
brj-25043	235	5	by	by	ADP
brj-25043	235	6	mu	mu	PROPN
brj-25043	235	7	et	et	PROPN
brj-25043	235	8	al	al	PROPN
brj-25043	235	9	.	.	PROPN
brj-25043	236	1	(	(	PUNCT
brj-25043	236	2	2007	2007	NUM
brj-25043	236	3	)	)	PUNCT
brj-25043	237	1	to	to	PART
brj-25043	237	2	investigate	investigate	VERB
brj-25043	237	3	the	the	DET
brj-25043	237	4	kinetics	kinetic	NOUN
brj-25043	237	5	of	of	ADP
brj-25043	237	6	hydrogen	hydrogen	NOUN
brj-25043	237	7	production	production	NOUN
brj-25043	237	8	from	from	ADP
brj-25043	237	9	sucrose	sucrose	NOUN
brj-25043	237	10	by	by	ADP
brj-25043	237	11	mixed	mixed	ADJ
brj-25043	237	12	cultures	culture	NOUN
brj-25043	237	13	,	,	PUNCT
brj-25043	237	14	where	where	SCONJ
brj-25043	237	15	it	it	PRON
brj-25043	237	16	showed	show	VERB
brj-25043	237	17	a	a	DET
brj-25043	237	18	good	good	ADJ
brj-25043	237	19	correlation	correlation	NOUN
brj-25043	237	20	to	to	ADP
brj-25043	237	21	the	the	DET
brj-25043	237	22	experimental	experimental	ADJ
brj-25043	237	23	data	datum	NOUN
brj-25043	237	24	,	,	PUNCT
brj-25043	237	25	as	as	SCONJ
brj-25043	237	26	r²	r²	NOUN
brj-25043	237	27	was	be	AUX
brj-25043	237	28	0.994	0.994	NUM
brj-25043	238	1	.	.	PUNCT
brj-25043	239	1	in	in	ADP
brj-25043	239	2	addition	addition	NOUN
brj-25043	239	3	,	,	PUNCT
brj-25043	239	4	it	it	PRON
brj-25043	239	5	was	be	AUX
brj-25043	239	6	utilized	utilize	VERB
brj-25043	239	7	to	to	PART
brj-25043	239	8	investigate	investigate	VERB
brj-25043	239	9	the	the	DET
brj-25043	239	10	inhibitory	inhibitory	ADJ
brj-25043	239	11	effect	effect	NOUN
brj-25043	239	12	of	of	ADP
brj-25043	239	13	four	four	NUM
brj-25043	239	14	heavy	heavy	ADJ
brj-25043	239	15	metals	metal	NOUN
brj-25043	239	16	on	on	ADP
brj-25043	239	17	the	the	DET
brj-25043	239	18	methane	methane	NOUN
brj-25043	239	19	-	-	PUNCT
brj-25043	239	20	producing	produce	VERB
brj-25043	239	21	anaerobic	anaerobic	NOUN
brj-25043	239	22	granular	granular	ADJ
brj-25043	239	23	sludge	sludge	NOUN
brj-25043	239	24	by	by	ADP
brj-25043	239	25	altaş	altaş	NOUN
brj-25043	239	26	(	(	PUNCT
brj-25043	239	27	2009	2009	NUM
brj-25043	239	28	)	)	PUNCT
brj-25043	239	29	,	,	PUNCT
brj-25043	239	30	and	and	CCONJ
brj-25043	239	31	r²	r²	NOUN
brj-25043	239	32	was	be	AUX
brj-25043	239	33	greater	great	ADJ
brj-25043	239	34	than	than	ADP
brj-25043	239	35	0.99	0.99	NUM
brj-25043	239	36	.	.	PUNCT
brj-25043	240	1	in	in	ADP
brj-25043	240	2	contrast	contrast	NOUN
brj-25043	240	3	,	,	PUNCT
brj-25043	240	4	the	the	DET
brj-25043	240	5	stannard	stannard	NOUN
brj-25043	240	6	model	model	NOUN
brj-25043	240	7	equation	equation	NOUN
brj-25043	240	8	is	be	AUX
brj-25043	240	9	represented	represent	VERB
brj-25043	240	10	in	in	ADP
brj-25043	240	11	eq	eq	NOUN
brj-25043	240	12	.	.	PROPN
brj-25043	240	13	11	11	NUM
brj-25043	240	14	(	(	PUNCT
brj-25043	240	15	zwietering	zwietering	NOUN
brj-25043	240	16	et	et	PROPN
brj-25043	240	17	al	al	PROPN
brj-25043	240	18	.	.	PROPN
brj-25043	240	19	1990	1990	NUM
brj-25043	240	20	)	)	PUNCT
brj-25043	240	21	,	,	PUNCT
brj-25043	240	22	pbg	pbg	PROPN
brj-25043	240	23	=	=	SYM
brj-25043	240	24	a	a	PRON
brj-25043	240	25	(	(	PUNCT
brj-25043	240	26	1+exp	1+exp	NOUN
brj-25043	240	27	(	(	PUNCT
brj-25043	240	28	−	−	PROPN
brj-25043	240	29	(	(	PUNCT
brj-25043	240	30	l+kt	l+kt	NOUN
brj-25043	240	31	)	)	PUNCT
brj-25043	240	32	p	p	NOUN
brj-25043	240	33	)	)	PUNCT
brj-25043	240	34	)	)	PUNCT
brj-25043	240	35	−𝑝	−𝑝	INTJ
brj-25043	240	36	(	(	PUNCT
brj-25043	240	37	11	11	NUM
brj-25043	240	38	)	)	PUNCT
brj-25043	240	39	where	where	SCONJ
brj-25043	240	40	l	l	NOUN
brj-25043	240	41	,	,	PUNCT
brj-25043	240	42	k	k	NOUN
brj-25043	240	43	,	,	PUNCT
brj-25043	240	44	and	and	CCONJ
brj-25043	240	45	p	p	NOUN
brj-25043	240	46	are	be	AUX
brj-25043	240	47	constants	constant	NOUN
brj-25043	240	48	.	.	PUNCT
brj-25043	241	1	the	the	DET
brj-25043	241	2	modified	modify	VERB
brj-25043	241	3	version	version	NOUN
brj-25043	241	4	of	of	ADP
brj-25043	241	5	the	the	DET
brj-25043	241	6	stannard	stannard	NOUN
brj-25043	241	7	equation	equation	NOUN
brj-25043	241	8	is	be	AUX
brj-25043	241	9	the	the	DET
brj-25043	241	10	same	same	ADJ
brj-25043	241	11	as	as	ADP
brj-25043	241	12	the	the	DET
brj-25043	241	13	modified	modify	VERB
brj-25043	241	14	richards	richard	NOUN
brj-25043	241	15	'	'	PART
brj-25043	241	16	equation	equation	NOUN
brj-25043	241	17	,	,	PUNCT
brj-25043	241	18	which	which	PRON
brj-25043	241	19	is	be	AUX
brj-25043	241	20	given	give	VERB
brj-25043	241	21	by	by	ADP
brj-25043	241	22	eq	eq	PROPN
brj-25043	241	23	.	.	PROPN
brj-25043	241	24	12	12	NUM
brj-25043	241	25	:	:	PUNCT
brj-25043	241	26	pbg	pbg	PROPN
brj-25043	241	27	=	=	PROPN
brj-25043	241	28	a	a	PRON
brj-25043	241	29	(	(	PUNCT
brj-25043	241	30	1+𝜈	1+𝜈	NUM
brj-25043	241	31	exp(1+𝜈	exp(1+𝜈	NOUN
brj-25043	241	32	)	)	PUNCT
brj-25043	241	33	.	.	PUNCT
brj-25043	242	1	exp	exp	NOUN
brj-25043	242	2	(	(	PUNCT
brj-25043	242	3	μm	μm	INTJ
brj-25043	242	4	a	a	DET
brj-25043	242	5	(	(	PUNCT
brj-25043	242	6	1+𝜈	1+𝜈	NUM
brj-25043	242	7	)	)	PUNCT
brj-25043	242	8	(	(	PUNCT
brj-25043	242	9	1	1	NUM
brj-25043	242	10	+	+	SYM
brj-25043	242	11	1	1	NUM
brj-25043	242	12	𝜈	𝜈	NOUN
brj-25043	242	13	)	)	PUNCT
brj-25043	242	14	(	(	PUNCT
brj-25043	242	15	λt	λt	ADP
brj-25043	242	16	)	)	PUNCT
brj-25043	242	17	)	)	PUNCT
brj-25043	242	18	)	)	PUNCT
brj-25043	242	19	(	(	PUNCT
brj-25043	242	20	−1/𝜈	−1/𝜈	PROPN
brj-25043	242	21	)	)	PUNCT
brj-25043	242	22	(	(	PUNCT
brj-25043	242	23	12	12	NUM
brj-25043	242	24	)	)	PUNCT
brj-25043	242	25	one	one	NUM
brj-25043	242	26	more	more	ADJ
brj-25043	242	27	model	model	NOUN
brj-25043	242	28	that	that	PRON
brj-25043	242	29	belongs	belong	VERB
brj-25043	242	30	to	to	ADP
brj-25043	242	31	this	this	DET
brj-25043	242	32	section	section	NOUN
brj-25043	242	33	is	be	AUX
brj-25043	242	34	the	the	DET
brj-25043	242	35	schunte	schunte	PROPN
brj-25043	242	36	model	model	NOUN
brj-25043	242	37	,	,	PUNCT
brj-25043	242	38	which	which	PRON
brj-25043	242	39	is	be	AUX
brj-25043	242	40	represented	represent	VERB
brj-25043	242	41	by	by	ADP
brj-25043	242	42	eq	eq	PROPN
brj-25043	242	43	.	.	PROPN
brj-25043	242	44	13	13	NUM
brj-25043	242	45	(	(	PUNCT
brj-25043	242	46	zwietering	zwietering	NOUN
brj-25043	242	47	et	et	PROPN
brj-25043	242	48	al	al	PROPN
brj-25043	242	49	.	.	PROPN
brj-25043	242	50	1990	1990	NUM
brj-25043	242	51	)	)	PUNCT
brj-25043	242	52	,	,	PUNCT
brj-25043	242	53	pbg=	pbg=	NUM
brj-25043	242	54	(	(	PUNCT
brj-25043	242	55	𝑦1	𝑦1	PROPN
brj-25043	242	56	𝑏+(𝑦2	𝑏+(𝑦2	VERB
brj-25043	242	57	𝑏-𝑦1	𝑏-𝑦1	PROPN
brj-25043	242	58	𝑏	𝑏	NOUN
brj-25043	242	59	)	)	PUNCT
brj-25043	242	60	.	.	PUNCT
brj-25043	243	1	1exp(-a	1exp(-a	NUM
brj-25043	243	2	(	(	PUNCT
brj-25043	243	3	t−𝜏1	t−𝜏1	NOUN
brj-25043	243	4	)	)	PUNCT
brj-25043	243	5	)	)	PUNCT
brj-25043	244	1	1exp(-a	1exp(-a	X
brj-25043	245	1	(	(	PUNCT
brj-25043	245	2	𝜏2	𝜏2	ADJ
brj-25043	245	3	−𝜏1	−𝜏1	PROPN
brj-25043	245	4	)	)	PUNCT
brj-25043	245	5	)	)	PUNCT
brj-25043	245	6	)	)	PUNCT
brj-25043	246	1	(	(	PUNCT
brj-25043	246	2	1/𝑏	1/𝑏	NUM
brj-25043	246	3	)	)	PUNCT
brj-25043	246	4	(	(	PUNCT
brj-25043	246	5	13	13	NUM
brj-25043	246	6	)	)	PUNCT
brj-25043	246	7	and	and	CCONJ
brj-25043	246	8	its	its	PRON
brj-25043	246	9	modified	modify	VERB
brj-25043	246	10	version	version	NOUN
brj-25043	246	11	equation	equation	NOUN
brj-25043	246	12	is	be	AUX
brj-25043	246	13	given	give	VERB
brj-25043	246	14	by	by	ADP
brj-25043	246	15	eq	eq	PROPN
brj-25043	246	16	.	.	PROPN
brj-25043	246	17	14	14	NUM
brj-25043	246	18	(	(	PUNCT
brj-25043	246	19	zwietering	zwietering	NOUN
brj-25043	246	20	et	et	PROPN
brj-25043	246	21	al	al	PROPN
brj-25043	246	22	.	.	PROPN
brj-25043	246	23	1990	1990	NUM
brj-25043	246	24	):	):	PUNCT
brj-25043	247	1	pbg=	pbg=	NUM
brj-25043	247	2	(	(	PUNCT
brj-25043	247	3	μ	μ	PROPN
brj-25043	247	4	m	m	PROPN
brj-25043	247	5	(	(	PUNCT
brj-25043	247	6	1−𝑏	1−𝑏	NUM
brj-25043	247	7	)	)	PUNCT
brj-25043	247	8	a	a	NOUN
brj-25043	247	9	)	)	PUNCT
brj-25043	247	10	(	(	PUNCT
brj-25043	247	11	.	.	PUNCT
brj-25043	247	12	1b	1b	PROPN
brj-25043	247	13	exp(aλ	exp(aλ	X
brj-25043	247	14	+1−𝑏−𝑎𝑡	+1−𝑏−𝑎𝑡	PROPN
brj-25043	247	15	)	)	PUNCT
brj-25043	247	16	1−𝑏	1−𝑏	NUM
brj-25043	247	17	)	)	PUNCT
brj-25043	247	18	(	(	PUNCT
brj-25043	247	19	1/𝑏	1/𝑏	NUM
brj-25043	247	20	)	)	PUNCT
brj-25043	247	21	(	(	PUNCT
brj-25043	247	22	14	14	NUM
brj-25043	247	23	)	)	PUNCT
brj-25043	247	24	however	however	ADV
brj-25043	247	25	,	,	PUNCT
brj-25043	247	26	no	no	DET
brj-25043	247	27	key	key	ADJ
brj-25043	247	28	works	work	NOUN
brj-25043	247	29	were	be	AUX
brj-25043	247	30	addressed	address	VERB
brj-25043	247	31	in	in	ADP
brj-25043	247	32	the	the	DET
brj-25043	247	33	literature	literature	NOUN
brj-25043	247	34	using	use	VERB
brj-25043	247	35	both	both	CCONJ
brj-25043	247	36	stannard	stannard	NOUN
brj-25043	247	37	and	and	CCONJ
brj-25043	247	38	schunte	schunte	NOUN
brj-25043	247	39	models	model	NOUN
brj-25043	247	40	and	and	CCONJ
brj-25043	247	41	their	their	PRON
brj-25043	247	42	modified	modify	VERB
brj-25043	247	43	versions	version	NOUN
brj-25043	247	44	.	.	PUNCT
brj-25043	248	1	sigmoidal	sigmoidal	NOUN
brj-25043	248	2	equations	equation	NOUN
brj-25043	248	3	(	(	PUNCT
brj-25043	248	4	logistic	logistic	ADJ
brj-25043	248	5	/	/	SYM
brj-25043	248	6	modified	modify	VERB
brj-25043	248	7	gompertz	gompertz	NOUN
brj-25043	248	8	,	,	PUNCT
brj-25043	248	9	richards	richards	PROPN
brj-25043	248	10	/	/	SYM
brj-25043	248	11	schunte	schunte	NOUN
brj-25043	248	12	)	)	PUNCT
brj-25043	248	13	presume	presume	VERB
brj-25043	248	14	a	a	DET
brj-25043	248	15	single	single	ADJ
brj-25043	248	16	dominant	dominant	ADJ
brj-25043	248	17	population	population	NOUN
brj-25043	248	18	and	and	CCONJ
brj-25043	248	19	constant	constant	ADJ
brj-25043	248	20	biodegradability	biodegradability	NOUN
brj-25043	248	21	;	;	PUNCT
brj-25043	248	22	co	co	NOUN
brj-25043	248	23	-	-	NOUN
brj-25043	248	24	digestion	digestion	NOUN
brj-25043	248	25	,	,	PUNCT
brj-25043	248	26	pre	pre	ADJ
brj-25043	248	27	-	-	NOUN
brj-25043	248	28	treatment	treatment	NOUN
brj-25043	248	29	,	,	PUNCT
brj-25043	248	30	or	or	CCONJ
brj-25043	248	31	staged	stage	VERB
brj-25043	248	32	hydrolysis	hydrolysis	NOUN
brj-25043	248	33	–	–	PUNCT
brj-25043	248	34	acidogenesis	acidogenesis	NOUN
brj-25043	248	35	–	–	PUNCT
brj-25043	248	36	methanogenesis	methanogenesis	NOUN
brj-25043	248	37	often	often	ADV
brj-25043	248	38	produce	produce	VERB
brj-25043	248	39	shoulders	shoulder	NOUN
brj-25043	248	40	or	or	CCONJ
brj-25043	248	41	long	long	ADJ
brj-25043	248	42	tails	tail	NOUN
brj-25043	248	43	(	(	PUNCT
brj-25043	248	44	multiple	multiple	ADJ
brj-25043	248	45	inflections	inflection	NOUN
brj-25043	248	46	)	)	PUNCT
brj-25043	248	47	that	that	SCONJ
brj-25043	248	48	a	a	DET
brj-25043	248	49	one	one	NUM
brj-25043	248	50	-	-	PUNCT
brj-25043	248	51	sigmoid	sigmoid	NOUN
brj-25043	248	52	curve	curve	NOUN
brj-25043	248	53	can	can	AUX
brj-25043	248	54	not	not	PART
brj-25043	248	55	capture	capture	VERB
brj-25043	248	56	(	(	PUNCT
brj-25043	248	57	nielfa	nielfa	NOUN
brj-25043	248	58	et	et	PROPN
brj-25043	248	59	al	al	PROPN
brj-25043	248	60	.	.	PROPN
brj-25043	248	61	2015	2015	NUM
brj-25043	248	62	;	;	PUNCT
brj-25043	248	63	deepanraj	deepanraj	VERB
brj-25043	248	64	et	et	PROPN
brj-25043	248	65	al	al	PROPN
brj-25043	248	66	.	.	PROPN
brj-25043	248	67	2017	2017	NUM
brj-25043	248	68	)	)	PUNCT
brj-25043	248	69	.	.	PUNCT
brj-25043	249	1	parameter	parameter	NOUN
brj-25043	249	2	equifinality	equifinality	NOUN
brj-25043	249	3	is	be	AUX
brj-25043	249	4	common	common	ADJ
brj-25043	249	5	:	:	PUNCT
brj-25043	249	6	λ	λ	NOUN
brj-25043	249	7	often	often	ADV
brj-25043	249	8	trades	trade	VERB
brj-25043	249	9	off	off	ADP
brj-25043	249	10	with	with	ADP
brj-25043	249	11	dm	dm	PROPN
brj-25043	249	12	or	or	CCONJ
brj-25043	249	13	k	k	PROPN
brj-25043	249	14	peer	peer	NOUN
brj-25043	249	15	-	-	PUNCT
brj-25043	249	16	reviewed	review	VERB
brj-25043	249	17	review	review	NOUN
brj-25043	249	18	article	article	NOUN
brj-25043	249	19	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	249	20	galal	galal	PROPN
brj-25043	249	21	et	et	PROPN
brj-25043	249	22	al	al	PROPN
brj-25043	249	23	.	.	PROPN
brj-25043	250	1	(	(	PUNCT
brj-25043	250	2	2025	2025	NUM
brj-25043	250	3	)	)	PUNCT
brj-25043	250	4	.	.	PUNCT
brj-25043	251	1	“	"	PUNCT
brj-25043	251	2	math	math	NOUN
brj-25043	251	3	modeling	modeling	NOUN
brj-25043	251	4	biogas	biogas	NOUN
brj-25043	251	5	production	production	NOUN
brj-25043	251	6	,	,	PUNCT
brj-25043	251	7	”	"	PUNCT
brj-25043	251	8	bioresources	bioresource	NOUN
brj-25043	251	9	20(4	20(4	NOUN
brj-25043	251	10	)	)	PUNCT
brj-25043	251	11	,	,	PUNCT
brj-25043	251	12	11237	11237	NUM
brj-25043	251	13	-	-	SYM
brj-25043	251	14	11266	11266	NUM
brj-25043	251	15	.	.	PUNCT
brj-25043	252	1	11252	11252	NUM
brj-25043	252	2	when	when	SCONJ
brj-25043	252	3	sampling	sample	VERB
brj-25043	252	4	is	be	AUX
brj-25043	252	5	sparse	sparse	ADJ
brj-25043	252	6	(	(	PUNCT
brj-25043	252	7	e.g.	e.g.	ADV
brj-25043	252	8	,	,	PUNCT
brj-25043	252	9	<	<	X
brj-25043	252	10	daily	daily	ADJ
brj-25043	252	11	)	)	PUNCT
brj-25043	252	12	,	,	PUNCT
brj-25043	252	13	and	and	CCONJ
brj-25043	252	14	a	a	PRON
brj-25043	252	15	can	can	AUX
brj-25043	252	16	absorb	absorb	VERB
brj-25043	252	17	gas	gas	NOUN
brj-25043	252	18	losses	loss	NOUN
brj-25043	252	19	,	,	PUNCT
brj-25043	252	20	leakage	leakage	NOUN
brj-25043	252	21	,	,	PUNCT
brj-25043	252	22	or	or	CCONJ
brj-25043	252	23	incomplete	incomplete	ADJ
brj-25043	252	24	degassing	degassing	NOUN
brj-25043	252	25	,	,	PUNCT
brj-25043	252	26	inflating	inflate	VERB
brj-25043	252	27	uncertainty	uncertainty	NOUN
brj-25043	252	28	(	(	PUNCT
brj-25043	252	29	bilgili	bilgili	NOUN
brj-25043	252	30	et	et	PROPN
brj-25043	252	31	al	al	PROPN
brj-25043	252	32	.	.	PROPN
brj-25043	252	33	2009	2009	NUM
brj-25043	252	34	;	;	PUNCT
brj-25043	252	35	lo	lo	PROPN
brj-25043	252	36	et	et	PROPN
brj-25043	252	37	al	al	PROPN
brj-25043	252	38	.	.	PROPN
brj-25043	252	39	2010	2010	NUM
brj-25043	252	40	)	)	PUNCT
brj-25043	252	41	.	.	PUNCT
brj-25043	253	1	inhibition	inhibition	NOUN
brj-25043	253	2	episodes	episode	NOUN
brj-25043	253	3	flatten	flatten	VERB
brj-25043	253	4	mid	mid	ADJ
brj-25043	253	5	-	-	NOUN
brj-25043	253	6	slope	slope	NOUN
brj-25043	253	7	and	and	CCONJ
brj-25043	253	8	shift	shift	VERB
brj-25043	253	9	apparent	apparent	ADJ
brj-25043	253	10	lag	lag	NOUN
brj-25043	253	11	(	(	PUNCT
brj-25043	253	12	altaş	altaş	NOUN
brj-25043	253	13	2009	2009	NUM
brj-25043	253	14	;	;	PUNCT
brj-25043	253	15	tian	tian	PROPN
brj-25043	253	16	et	et	PROPN
brj-25043	253	17	al	al	PROPN
brj-25043	253	18	.	.	PROPN
brj-25043	253	19	2020	2020	NUM
brj-25043	253	20	)	)	PUNCT
brj-25043	253	21	.	.	PUNCT
brj-25043	254	1	mitigations	mitigation	NOUN
brj-25043	254	2	include	include	VERB
brj-25043	254	3	higher	high	ADJ
brj-25043	254	4	early	early	ADJ
brj-25043	254	5	-	-	PUNCT
brj-25043	254	6	phase	phase	NOUN
brj-25043	254	7	sampling	sampling	NOUN
brj-25043	254	8	,	,	PUNCT
brj-25043	254	9	consistent	consistent	ADJ
brj-25043	254	10	methane	methane	NOUN
brj-25043	254	11	normalization	normalization	NOUN
brj-25043	254	12	(	(	PUNCT
brj-25043	254	13	stp	stp	ADJ
brj-25043	254	14	,	,	PUNCT
brj-25043	254	15	dry	dry	ADJ
brj-25043	254	16	gas	gas	NOUN
brj-25043	254	17	,	,	PUNCT
brj-25043	254	18	per	per	ADP
brj-25043	254	19	gvs	gvs	PROPN
brj-25043	254	20	)	)	PUNCT
brj-25043	254	21	,	,	PUNCT
brj-25043	254	22	mass	mass	ADJ
brj-25043	254	23	-	-	PUNCT
brj-25043	254	24	balance	balance	NOUN
brj-25043	254	25	checks	check	NOUN
brj-25043	254	26	,	,	PUNCT
brj-25043	254	27	and	and	CCONJ
brj-25043	254	28	reporting	report	VERB
brj-25043	254	29	parameter	parameter	NOUN
brj-25043	254	30	cis	cis	NOUN
brj-25043	254	31	or	or	CCONJ
brj-25043	254	32	bayesian	bayesian	NOUN
brj-25043	254	33	posteriors	posterior	NOUN
brj-25043	254	34	rather	rather	ADV
brj-25043	254	35	than	than	ADP
brj-25043	254	36	single	single	ADJ
brj-25043	254	37	best	good	ADJ
brj-25043	254	38	fits	fit	NOUN
brj-25043	254	39	.	.	PUNCT
brj-25043	255	1	machine	machine	NOUN
brj-25043	255	2	learning	learn	VERB
brj-25043	255	3	approaches	approach	VERB
brj-25043	255	4	table	table	NOUN
brj-25043	255	5	4	4	NUM
brj-25043	255	6	summarizes	summarize	NOUN
brj-25043	255	7	key	key	ADJ
brj-25043	255	8	peer	peer	NOUN
brj-25043	255	9	-	-	PUNCT
brj-25043	255	10	reviewed	review	VERB
brj-25043	255	11	studies	study	NOUN
brj-25043	255	12	emphasizing	emphasize	VERB
brj-25043	255	13	ml	ml	ADP
brj-25043	255	14	applications	application	NOUN
brj-25043	255	15	related	relate	VERB
brj-25043	255	16	to	to	ADP
brj-25043	255	17	biogas	biogas	NOUN
brj-25043	255	18	production	production	NOUN
brj-25043	255	19	in	in	ADP
brj-25043	255	20	ad	ad	NOUN
brj-25043	255	21	.	.	PUNCT
brj-25043	256	1	table	table	NOUN
brj-25043	256	2	4	4	NUM
brj-25043	256	3	details	detail	NOUN
brj-25043	256	4	the	the	DET
brj-25043	256	5	algorithms	algorithm	NOUN
brj-25043	256	6	used	use	VERB
brj-25043	256	7	,	,	PUNCT
brj-25043	256	8	data	datum	NOUN
brj-25043	256	9	sources	source	NOUN
brj-25043	256	10	,	,	PUNCT
brj-25043	256	11	performance	performance	NOUN
brj-25043	256	12	metrics	metric	NOUN
brj-25043	256	13	(	(	PUNCT
brj-25043	256	14	e.g.	e.g.	ADV
brj-25043	256	15	,	,	PUNCT
brj-25043	256	16	correlation	correlation	NOUN
brj-25043	256	17	coefficient	coefficient	NOUN
brj-25043	256	18	(	(	PUNCT
brj-25043	256	19	r²	r²	NOUN
brj-25043	256	20	)	)	PUNCT
brj-25043	256	21	and	and	CCONJ
brj-25043	256	22	root	root	NOUN
brj-25043	256	23	mean	mean	NOUN
brj-25043	256	24	square	square	ADJ
brj-25043	256	25	error	error	NOUN
brj-25043	256	26	(	(	PUNCT
brj-25043	256	27	rmse	rmse	NOUN
brj-25043	256	28	)	)	PUNCT
brj-25043	256	29	)	)	PUNCT
brj-25043	256	30	,	,	PUNCT
brj-25043	256	31	comparisons	comparison	NOUN
brj-25043	256	32	with	with	ADP
brj-25043	256	33	traditional	traditional	ADJ
brj-25043	256	34	models	model	NOUN
brj-25043	256	35	when	when	SCONJ
brj-25043	256	36	available	available	ADJ
brj-25043	256	37	,	,	PUNCT
brj-25043	256	38	and	and	CCONJ
brj-25043	256	39	specific	specific	ADJ
brj-25043	256	40	ad	ad	NOUN
brj-25043	256	41	contexts	contexts	NOUN
brj-25043	256	42	.	.	PUNCT
brj-25043	257	1	the	the	DET
brj-25043	257	2	studies	study	NOUN
brj-25043	257	3	reviewed	review	VERB
brj-25043	257	4	show	show	VERB
brj-25043	257	5	a	a	DET
brj-25043	257	6	shift	shift	NOUN
brj-25043	257	7	from	from	ADP
brj-25043	257	8	mechanistic	mechanistic	ADJ
brj-25043	257	9	to	to	ADP
brj-25043	257	10	data	data	NOUN
brj-25043	257	11	-	-	PUNCT
brj-25043	257	12	driven	drive	VERB
brj-25043	257	13	modelling	modelling	NOUN
brj-25043	257	14	,	,	PUNCT
brj-25043	257	15	with	with	ADP
brj-25043	257	16	ml	ml	PART
brj-25043	257	17	consistently	consistently	ADV
brj-25043	257	18	achieving	achieve	VERB
brj-25043	257	19	higher	high	ADJ
brj-25043	257	20	accuracy	accuracy	NOUN
brj-25043	257	21	(	(	PUNCT
brj-25043	257	22	r²	r²	VERB
brj-25043	257	23	often	often	ADV
brj-25043	257	24	above	above	ADP
brj-25043	257	25	0.90	0.90	NUM
brj-25043	257	26	)	)	PUNCT
brj-25043	257	27	than	than	ADP
brj-25043	257	28	traditional	traditional	ADJ
brj-25043	257	29	kinetic	kinetic	ADJ
brj-25043	257	30	models	model	NOUN
brj-25043	257	31	like	like	ADP
brj-25043	257	32	gompertz	gompertz	NOUN
brj-25043	257	33	or	or	CCONJ
brj-25043	257	34	logistic	logistic	ADJ
brj-25043	257	35	,	,	PUNCT
brj-25043	257	36	especially	especially	ADV
brj-25043	257	37	in	in	ADP
brj-25043	257	38	co	co	NOUN
brj-25043	257	39	-	-	NOUN
brj-25043	257	40	digestion	digestion	NOUN
brj-25043	257	41	scenarios	scenario	NOUN
brj-25043	257	42	involving	involve	VERB
brj-25043	257	43	sewage	sewage	NOUN
brj-25043	257	44	sludge	sludge	NOUN
brj-25043	257	45	,	,	PUNCT
brj-25043	257	46	agricultural	agricultural	ADJ
brj-25043	257	47	waste	waste	NOUN
brj-25043	257	48	,	,	PUNCT
brj-25043	257	49	or	or	CCONJ
brj-25043	257	50	food	food	NOUN
brj-25043	257	51	waste	waste	NOUN
brj-25043	257	52	(	(	PUNCT
brj-25043	257	53	asadi	asadi	NOUN
brj-25043	257	54	and	and	CCONJ
brj-25043	257	55	mcphedran	mcphedran	ADJ
brj-25043	257	56	2021	2021	NUM
brj-25043	257	57	;	;	PUNCT
brj-25043	257	58	ling	le	VERB
brj-25043	257	59	et	et	PROPN
brj-25043	257	60	al	al	PROPN
brj-25043	257	61	.	.	PROPN
brj-25043	257	62	2024	2024	NUM
brj-25043	257	63	)	)	PUNCT
brj-25043	257	64	.	.	PUNCT
brj-25043	258	1	for	for	ADP
brj-25043	258	2	example	example	NOUN
brj-25043	258	3	,	,	PUNCT
brj-25043	258	4	tree	tree	NOUN
brj-25043	258	5	-	-	PUNCT
brj-25043	258	6	based	base	VERB
brj-25043	258	7	models	model	NOUN
brj-25043	258	8	(	(	PUNCT
brj-25043	258	9	rf	rf	ADJ
brj-25043	258	10	,	,	PUNCT
brj-25043	258	11	xgboost	xgboost	PRON
brj-25043	258	12	)	)	PUNCT
brj-25043	258	13	perform	perform	VERB
brj-25043	258	14	well	well	ADV
brj-25043	258	15	in	in	ADP
brj-25043	258	16	full	full	ADJ
brj-25043	258	17	-	-	PUNCT
brj-25043	258	18	scale	scale	NOUN
brj-25043	258	19	systems	system	NOUN
brj-25043	258	20	because	because	SCONJ
brj-25043	258	21	they	they	PRON
brj-25043	258	22	handle	handle	VERB
brj-25043	258	23	non	non	ADJ
brj-25043	258	24	-	-	ADJ
brj-25043	258	25	linearity	linearity	ADJ
brj-25043	258	26	and	and	CCONJ
brj-25043	258	27	feature	feature	NOUN
brj-25043	258	28	importance	importance	NOUN
brj-25043	258	29	through	through	ADP
brj-25043	258	30	shap	shap	NOUN
brj-25043	258	31	,	,	PUNCT
brj-25043	258	32	highlighting	highlight	VERB
brj-25043	258	33	key	key	ADJ
brj-25043	258	34	variables	variable	NOUN
brj-25043	258	35	like	like	ADP
brj-25043	258	36	olr	olr	NOUN
brj-25043	258	37	,	,	PUNCT
brj-25043	258	38	ph	ph	VERB
brj-25043	258	39	,	,	PUNCT
brj-25043	258	40	and	and	CCONJ
brj-25043	258	41	biomass	biomass	NOUN
brj-25043	258	42	input	input	NOUN
brj-25043	258	43	(	(	PUNCT
brj-25043	258	44	zou	zou	NOUN
brj-25043	258	45	et	et	PROPN
brj-25043	258	46	al	al	PROPN
brj-25043	258	47	.	.	PROPN
brj-25043	258	48	2024	2024	NUM
brj-25043	258	49	)	)	PUNCT
brj-25043	258	50	.	.	PUNCT
brj-25043	259	1	deep	deep	ADJ
brj-25043	259	2	learning	learning	NOUN
brj-25043	259	3	methods	method	NOUN
brj-25043	259	4	,	,	PUNCT
brj-25043	259	5	such	such	ADJ
brj-25043	259	6	as	as	ADP
brj-25043	259	7	lstm	lstm	NOUN
brj-25043	259	8	with	with	ADP
brj-25043	259	9	attention	attention	NOUN
brj-25043	259	10	or	or	CCONJ
brj-25043	259	11	tft	tft	ADV
brj-25043	259	12	,	,	PUNCT
brj-25043	259	13	provide	provide	VERB
brj-25043	259	14	probabilistic	probabilistic	ADJ
brj-25043	259	15	forecasts	forecast	NOUN
brj-25043	259	16	and	and	CCONJ
brj-25043	259	17	capture	capture	VERB
brj-25043	259	18	long	long	ADJ
brj-25043	259	19	-	-	PUNCT
brj-25043	259	20	term	term	NOUN
brj-25043	259	21	dependencies	dependency	NOUN
brj-25043	259	22	,	,	PUNCT
brj-25043	259	23	addressing	address	VERB
brj-25043	259	24	parameter	parameter	NOUN
brj-25043	259	25	uncertainty	uncertainty	NOUN
brj-25043	259	26	with	with	ADP
brj-25043	259	27	quantile	quantile	ADJ
brj-25043	259	28	regression	regression	NOUN
brj-25043	259	29	and	and	CCONJ
brj-25043	259	30	data	datum	NOUN
brj-25043	259	31	augmentation	augmentation	NOUN
brj-25043	259	32	(	(	PUNCT
brj-25043	259	33	jeong	jeong	PROPN
brj-25043	259	34	et	et	PROPN
brj-25043	259	35	al	al	PROPN
brj-25043	259	36	.	.	PROPN
brj-25043	259	37	2021	2021	NUM
brj-25043	259	38	)	)	PUNCT
brj-25043	259	39	.	.	PUNCT
brj-25043	260	1	the	the	DET
brj-25043	260	2	regression	regression	NOUN
brj-25043	260	3	-	-	PUNCT
brj-25043	260	4	based	base	VERB
brj-25043	260	5	models	model	NOUN
brj-25043	260	6	can	can	AUX
brj-25043	260	7	be	be	AUX
brj-25043	260	8	updated	update	VERB
brj-25043	260	9	with	with	ADP
brj-25043	260	10	new	new	ADJ
brj-25043	260	11	data	datum	NOUN
brj-25043	260	12	,	,	PUNCT
brj-25043	260	13	but	but	CCONJ
brj-25043	260	14	they	they	PRON
brj-25043	260	15	usually	usually	ADV
brj-25043	260	16	require	require	VERB
brj-25043	260	17	explicit	explicit	ADJ
brj-25043	260	18	recalibration	recalibration	NOUN
brj-25043	260	19	or	or	CCONJ
brj-25043	260	20	retraining	retraining	NOUN
brj-25043	260	21	,	,	PUNCT
brj-25043	260	22	whereas	whereas	SCONJ
brj-25043	260	23	ml	ml	INTJ
brj-25043	260	24	(	(	PUNCT
brj-25043	260	25	especially	especially	ADV
brj-25043	260	26	online	online	ADJ
brj-25043	260	27	learning	learning	NOUN
brj-25043	260	28	or	or	CCONJ
brj-25043	260	29	adaptive	adaptive	ADJ
brj-25043	260	30	ml	ml	NOUN
brj-25043	260	31	)	)	PUNCT
brj-25043	260	32	.	.	PUNCT
brj-25043	261	1	hybrid	hybrid	ADJ
brj-25043	261	2	techniques	technique	NOUN
brj-25043	261	3	incorporating	incorporate	VERB
brj-25043	261	4	ga	ga	PROPN
brj-25043	261	5	or	or	CCONJ
brj-25043	261	6	pso	pso	NOUN
brj-25043	261	7	for	for	ADP
brj-25043	261	8	optimization	optimization	NOUN
brj-25043	261	9	improve	improve	VERB
brj-25043	261	10	biogas	biogas	NOUN
brj-25043	261	11	yield	yield	NOUN
brj-25043	261	12	and	and	CCONJ
brj-25043	261	13	stability	stability	NOUN
brj-25043	261	14	management	management	NOUN
brj-25043	261	15	(	(	PUNCT
brj-25043	261	16	salamattalab	salamattalab	NOUN
brj-25043	261	17	et	et	PROPN
brj-25043	261	18	al	al	PROPN
brj-25043	261	19	.	.	PROPN
brj-25043	261	20	2024	2024	NUM
brj-25043	261	21	)	)	PUNCT
brj-25043	261	22	.	.	PUNCT
brj-25043	262	1	feature	feature	NOUN
brj-25043	262	2	engineering	engineering	NOUN
brj-25043	262	3	and	and	CCONJ
brj-25043	262	4	data	datum	NOUN
brj-25043	262	5	quality	quality	NOUN
brj-25043	262	6	are	be	AUX
brj-25043	262	7	crucial	crucial	ADJ
brj-25043	262	8	,	,	PUNCT
brj-25043	262	9	as	as	SCONJ
brj-25043	262	10	high	high	ADJ
brj-25043	262	11	-	-	PUNCT
brj-25043	262	12	frequency	frequency	NOUN
brj-25043	262	13	scada	scada	PROPN
brj-25043	262	14	data	data	PROPN
brj-25043	262	15	or	or	CCONJ
brj-25043	262	16	derived	derived	ADJ
brj-25043	262	17	indices	index	NOUN
brj-25043	262	18	(	(	PUNCT
brj-25043	262	19	e.g.	e.g.	ADV
brj-25043	262	20	,	,	PUNCT
brj-25043	262	21	vfa	vfa	PROPN
brj-25043	262	22	/	/	SYM
brj-25043	262	23	alk	alk	PROPN
brj-25043	262	24	)	)	PUNCT
brj-25043	262	25	improve	improve	VERB
brj-25043	262	26	predictions	prediction	NOUN
brj-25043	262	27	without	without	ADP
brj-25043	262	28	needing	need	VERB
brj-25043	262	29	extensive	extensive	ADJ
brj-25043	262	30	lab	lab	NOUN
brj-25043	262	31	measurements	measurement	NOUN
brj-25043	262	32	(	(	PUNCT
brj-25043	262	33	zou	zou	X
brj-25043	262	34	et	et	PROPN
brj-25043	262	35	al	al	PROPN
brj-25043	262	36	.	.	PROPN
brj-25043	262	37	2024	2024	NUM
brj-25043	262	38	)	)	PUNCT
brj-25043	262	39	.	.	PUNCT
brj-25043	263	1	incorporating	incorporate	VERB
brj-25043	263	2	genomics	genomic	NOUN
brj-25043	263	3	or	or	CCONJ
brj-25043	263	4	pre	pre	ADJ
brj-25043	263	5	-	-	ADJ
brj-25043	263	6	treatment	treatment	ADJ
brj-25043	263	7	data	datum	NOUN
brj-25043	263	8	expands	expand	VERB
brj-25043	263	9	the	the	DET
brj-25043	263	10	input	input	NOUN
brj-25043	263	11	space	space	NOUN
brj-25043	263	12	,	,	PUNCT
brj-25043	263	13	connecting	connect	VERB
brj-25043	263	14	microbial	microbial	ADJ
brj-25043	263	15	communities	community	NOUN
brj-25043	263	16	to	to	ADP
brj-25043	263	17	performance	performance	NOUN
brj-25043	263	18	(	(	PUNCT
brj-25043	263	19	adeleke	adeleke	VERB
brj-25043	263	20	et	et	PROPN
brj-25043	263	21	al	al	PROPN
brj-25043	263	22	.	.	PROPN
brj-25043	263	23	2025	2025	NUM
brj-25043	263	24	)	)	PUNCT
brj-25043	263	25	.	.	PUNCT
brj-25043	264	1	explainable	explainable	ADJ
brj-25043	264	2	ai	ai	NOUN
brj-25043	264	3	tools	tool	NOUN
brj-25043	264	4	address	address	VERB
brj-25043	264	5	the	the	DET
brj-25043	264	6	"	"	PUNCT
brj-25043	264	7	black	black	ADJ
brj-25043	264	8	-	-	PUNCT
brj-25043	264	9	box	box	NOUN
brj-25043	264	10	"	"	PUNCT
brj-25043	264	11	issue	issue	NOUN
brj-25043	264	12	,	,	PUNCT
brj-25043	264	13	building	build	VERB
brj-25043	264	14	trust	trust	NOUN
brj-25043	264	15	and	and	CCONJ
brj-25043	264	16	enabling	enable	VERB
brj-25043	264	17	integration	integration	NOUN
brj-25043	264	18	with	with	ADP
brj-25043	264	19	biokinetic	biokinetic	ADJ
brj-25043	264	20	equations	equation	NOUN
brj-25043	264	21	for	for	ADP
brj-25043	264	22	physics	physics	NOUN
brj-25043	264	23	-	-	PUNCT
brj-25043	264	24	informed	inform	VERB
brj-25043	264	25	hybrids	hybrid	NOUN
brj-25043	264	26	(	(	PUNCT
brj-25043	264	27	gupta	gupta	PROPN
brj-25043	264	28	et	et	PROPN
brj-25043	264	29	al	al	PROPN
brj-25043	264	30	.	.	PROPN
brj-25043	264	31	2023	2023	NUM
brj-25043	264	32	)	)	PUNCT
brj-25043	264	33	.	.	PUNCT
brj-25043	265	1	this	this	DET
brj-25043	265	2	extension	extension	NOUN
brj-25043	265	3	fills	fill	VERB
brj-25043	265	4	gaps	gap	NOUN
brj-25043	265	5	in	in	ADP
brj-25043	265	6	traditional	traditional	ADJ
brj-25043	265	7	models	model	NOUN
brj-25043	265	8	by	by	ADP
brj-25043	265	9	enabling	enable	VERB
brj-25043	265	10	multi	multi	ADJ
brj-25043	265	11	-	-	ADJ
brj-25043	265	12	dimensional	dimensional	ADJ
brj-25043	265	13	simulations	simulation	NOUN
brj-25043	265	14	,	,	PUNCT
brj-25043	265	15	such	such	ADJ
brj-25043	265	16	as	as	ADP
brj-25043	265	17	with	with	ADP
brj-25043	265	18	variable	variable	ADJ
brj-25043	265	19	selection	selection	NOUN
brj-25043	265	20	networks	network	NOUN
brj-25043	265	21	,	,	PUNCT
brj-25043	265	22	and	and	CCONJ
brj-25043	265	23	managing	manage	VERB
brj-25043	265	24	stochastic	stochastic	ADJ
brj-25043	265	25	parameters	parameter	NOUN
brj-25043	265	26	,	,	PUNCT
brj-25043	265	27	for	for	ADP
brj-25043	265	28	instance	instance	NOUN
brj-25043	265	29	,	,	PUNCT
brj-25043	265	30	through	through	ADP
brj-25043	265	31	ensembles	ensemble	NOUN
brj-25043	265	32	.	.	PUNCT
brj-25043	266	1	future	future	ADJ
brj-25043	266	2	research	research	NOUN
brj-25043	266	3	should	should	AUX
brj-25043	266	4	focus	focus	VERB
brj-25043	266	5	on	on	ADP
brj-25043	266	6	creating	create	VERB
brj-25043	266	7	standardized	standardized	ADJ
brj-25043	266	8	datasets	dataset	NOUN
brj-25043	266	9	,	,	PUNCT
brj-25043	266	10	facilitating	facilitate	VERB
brj-25043	266	11	real	real	ADJ
brj-25043	266	12	-	-	PUNCT
brj-25043	266	13	time	time	NOUN
brj-25043	266	14	iot	iot	NOUN
brj-25043	266	15	integration	integration	NOUN
brj-25043	266	16	,	,	PUNCT
brj-25043	266	17	and	and	CCONJ
brj-25043	266	18	developing	develop	VERB
brj-25043	266	19	hybrid	hybrid	ADJ
brj-25043	266	20	ml	ml	NOUN
brj-25043	266	21	-	-	PUNCT
brj-25043	266	22	mechanistic	mechanistic	ADJ
brj-25043	266	23	frameworks	framework	NOUN
brj-25043	266	24	to	to	PART
brj-25043	266	25	deploy	deploy	VERB
brj-25043	266	26	robust	robust	ADJ
brj-25043	266	27	ad	ad	NOUN
brj-25043	266	28	systems	system	NOUN
brj-25043	266	29	on	on	ADP
brj-25043	266	30	a	a	DET
brj-25043	266	31	large	large	ADJ
brj-25043	266	32	scale	scale	NOUN
brj-25043	266	33	.	.	PUNCT
brj-25043	267	1	therefore	therefore	ADV
brj-25043	267	2	,	,	PUNCT
brj-25043	267	3	table	table	NOUN
brj-25043	267	4	4	4	NUM
brj-25043	267	5	shows	show	VERB
brj-25043	267	6	that	that	SCONJ
brj-25043	267	7	ml	ml	NOUN
brj-25043	267	8	methods	method	NOUN
brj-25043	267	9	consistently	consistently	ADV
brj-25043	267	10	outperform	outperform	VERB
brj-25043	267	11	traditional	traditional	ADJ
brj-25043	267	12	kinetic	kinetic	ADJ
brj-25043	267	13	models	model	NOUN
brj-25043	267	14	in	in	ADP
brj-25043	267	15	predicting	predict	VERB
brj-25043	267	16	biogas	biogas	NOUN
brj-25043	267	17	production	production	NOUN
brj-25043	267	18	,	,	PUNCT
brj-25043	267	19	particularly	particularly	ADV
brj-25043	267	20	for	for	ADP
brj-25043	267	21	the	the	DET
brj-25043	267	22	co	co	NOUN
brj-25043	267	23	-	-	NOUN
brj-25043	267	24	digestion	digestion	NOUN
brj-25043	267	25	of	of	ADP
brj-25043	267	26	diverse	diverse	ADJ
brj-25043	267	27	wastes	waste	NOUN
brj-25043	267	28	.	.	PUNCT
brj-25043	268	1	tree	tree	NOUN
brj-25043	268	2	-	-	PUNCT
brj-25043	268	3	based	base	VERB
brj-25043	268	4	models	model	NOUN
brj-25043	268	5	(	(	PUNCT
brj-25043	268	6	rf	rf	ADJ
brj-25043	268	7	,	,	PUNCT
brj-25043	268	8	xgboost	xgboost	NUM
brj-25043	268	9	)	)	PUNCT
brj-25043	268	10	and	and	CCONJ
brj-25043	268	11	deep	deep	ADJ
brj-25043	268	12	learning	learning	NOUN
brj-25043	268	13	approaches	approach	NOUN
brj-25043	268	14	(	(	PUNCT
brj-25043	268	15	lstm	lstm	PROPN
brj-25043	268	16	,	,	PUNCT
brj-25043	268	17	tft	tft	ADV
brj-25043	268	18	)	)	PUNCT
brj-25043	268	19	effectively	effectively	ADV
brj-25043	268	20	handle	handle	VERB
brj-25043	268	21	non	non	ADJ
brj-25043	268	22	-	-	ADJ
brj-25043	268	23	linearity	linearity	ADJ
brj-25043	268	24	,	,	PUNCT
brj-25043	268	25	probabilistic	probabilistic	ADJ
brj-25043	268	26	forecasting	forecasting	NOUN
brj-25043	268	27	,	,	PUNCT
brj-25043	268	28	and	and	CCONJ
brj-25043	268	29	feature	feature	NOUN
brj-25043	268	30	importance	importance	NOUN
brj-25043	268	31	.	.	PUNCT
brj-25043	269	1	hybrid	hybrid	ADJ
brj-25043	269	2	optimization	optimization	NOUN
brj-25043	269	3	techniques	technique	NOUN
brj-25043	269	4	(	(	PUNCT
brj-25043	269	5	ga	ga	PROPN
brj-25043	269	6	,	,	PUNCT
brj-25043	269	7	pso	pso	NOUN
brj-25043	269	8	)	)	PUNCT
brj-25043	269	9	further	far	ADV
brj-25043	269	10	improve	improve	VERB
brj-25043	269	11	biogas	biogas	NOUN
brj-25043	269	12	yield	yield	NOUN
brj-25043	269	13	and	and	CCONJ
brj-25043	269	14	process	process	NOUN
brj-25043	269	15	stability	stability	NOUN
brj-25043	269	16	.	.	PUNCT
brj-25043	270	1	high	high	ADJ
brj-25043	270	2	-	-	PUNCT
brj-25043	270	3	frequency	frequency	NOUN
brj-25043	270	4	scada	scada	PROPN
brj-25043	270	5	data	data	PROPN
brj-25043	270	6	,	,	PUNCT
brj-25043	270	7	feature	feature	NOUN
brj-25043	270	8	engineering	engineering	NOUN
brj-25043	270	9	,	,	PUNCT
brj-25043	270	10	and	and	CCONJ
brj-25043	270	11	genomics	genomic	NOUN
brj-25043	270	12	enhance	enhance	VERB
brj-25043	270	13	prediction	prediction	NOUN
brj-25043	270	14	accuracy	accuracy	NOUN
brj-25043	270	15	,	,	PUNCT
brj-25043	270	16	while	while	SCONJ
brj-25043	270	17	explainable	explainable	ADJ
brj-25043	270	18	ai	ai	NOUN
brj-25043	270	19	tools	tool	NOUN
brj-25043	270	20	(	(	PUNCT
brj-25043	270	21	e.g.	e.g.	ADV
brj-25043	270	22	,	,	PUNCT
brj-25043	270	23	shap	shap	NOUN
brj-25043	270	24	)	)	PUNCT
brj-25043	270	25	increase	increase	VERB
brj-25043	270	26	operational	operational	ADJ
brj-25043	270	27	trust	trust	NOUN
brj-25043	270	28	and	and	CCONJ
brj-25043	270	29	allow	allow	VERB
brj-25043	270	30	integration	integration	NOUN
brj-25043	270	31	with	with	ADP
brj-25043	270	32	biokinetic	biokinetic	ADJ
brj-25043	270	33	models	model	NOUN
brj-25043	270	34	.	.	PUNCT
brj-25043	271	1	these	these	DET
brj-25043	271	2	advancements	advancement	NOUN
brj-25043	271	3	fill	fill	NOUN
brj-25043	271	4	gaps	gap	NOUN
brj-25043	271	5	in	in	ADP
brj-25043	271	6	traditional	traditional	ADJ
brj-25043	271	7	approaches	approach	NOUN
brj-25043	271	8	and	and	CCONJ
brj-25043	271	9	enable	enable	VERB
brj-25043	271	10	multi	multi	ADJ
brj-25043	271	11	-	-	ADJ
brj-25043	271	12	dimensional	dimensional	ADJ
brj-25043	271	13	simulations	simulation	NOUN
brj-25043	271	14	.	.	PUNCT
brj-25043	272	1	peer	peer	NOUN
brj-25043	272	2	-	-	PUNCT
brj-25043	272	3	reviewed	review	VERB
brj-25043	272	4	review	review	NOUN
brj-25043	272	5	article	article	NOUN
brj-25043	272	6	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	272	7	galal	galal	PROPN
brj-25043	272	8	et	et	PROPN
brj-25043	272	9	al	al	PROPN
brj-25043	272	10	.	.	PROPN
brj-25043	273	1	(	(	PUNCT
brj-25043	273	2	2025	2025	NUM
brj-25043	273	3	)	)	PUNCT
brj-25043	273	4	.	.	PUNCT
brj-25043	274	1	“	"	PUNCT
brj-25043	274	2	math	math	NOUN
brj-25043	274	3	modeling	modeling	NOUN
brj-25043	274	4	biogas	biogas	NOUN
brj-25043	274	5	production	production	NOUN
brj-25043	274	6	,	,	PUNCT
brj-25043	274	7	”	"	PUNCT
brj-25043	274	8	bioresources	bioresource	NOUN
brj-25043	274	9	20(4	20(4	NOUN
brj-25043	274	10	)	)	PUNCT
brj-25043	274	11	,	,	PUNCT
brj-25043	274	12	11237	11237	NUM
brj-25043	274	13	-	-	SYM
brj-25043	274	14	11266	11266	NUM
brj-25043	274	15	.	.	PUNCT
brj-25043	275	1	11253	11253	NUM
brj-25043	275	2	table	table	NOUN
brj-25043	275	3	4	4	NUM
brj-25043	275	4	.	.	PUNCT
brj-25043	275	5	applications	application	NOUN
brj-25043	275	6	of	of	ADP
brj-25043	275	7	ml	ml	NOUN
brj-25043	275	8	in	in	ADP
brj-25043	275	9	ad	ad	NOUN
brj-25043	275	10	(	(	PUNCT
brj-25043	275	11	ann	ann	PROPN
brj-25043	275	12	,	,	PUNCT
brj-25043	275	13	lstm	lstm	PROPN
brj-25043	275	14	,	,	PUNCT
brj-25043	275	15	tft	tft	ADV
brj-25043	275	16	,	,	PUNCT
brj-25043	275	17	rf	rf	NOUN
brj-25043	275	18	,	,	PUNCT
brj-25043	275	19	etc	etc	X
brj-25043	275	20	.	.	X
brj-25043	275	21	)	)	PUNCT
brj-25043	276	1	showing	show	VERB
brj-25043	276	2	high	high	ADJ
brj-25043	276	3	predictive	predictive	ADJ
brj-25043	276	4	performance	performance	NOUN
brj-25043	276	5	across	across	ADP
brj-25043	276	6	substrates	substrate	NOUN
brj-25043	276	7	and	and	CCONJ
brj-25043	276	8	processes	process	NOUN
brj-25043	276	9	,	,	PUNCT
brj-25043	276	10	often	often	ADV
brj-25043	276	11	surpassing	surpass	VERB
brj-25043	276	12	classical	classical	ADJ
brj-25043	276	13	kinetic	kinetic	NOUN
brj-25043	276	14	models	model	NOUN
brj-25043	276	15	and	and	CCONJ
brj-25043	276	16	enabling	enable	VERB
brj-25043	276	17	real	real	ADJ
brj-25043	276	18	-	-	PUNCT
brj-25043	276	19	time	time	NOUN
brj-25043	276	20	optimization	optimization	NOUN
brj-25043	276	21	and	and	CCONJ
brj-25043	276	22	decision	decision	NOUN
brj-25043	276	23	support	support	NOUN
brj-25043	276	24	ad	ad	NOUN
brj-25043	276	25	application	application	NOUN
brj-25043	276	26	ml	ml	ADP
brj-25043	276	27	algorithms	algorithm	NOUN
brj-25043	276	28	and	and	CCONJ
brj-25043	276	29	data	datum	NOUN
brj-25043	276	30	key	key	ADJ
brj-25043	276	31	outcomes	outcome	NOUN
brj-25043	276	32	(	(	PUNCT
brj-25043	276	33	metrics	metric	NOUN
brj-25043	276	34	,	,	PUNCT
brj-25043	276	35	comparison	comparison	NOUN
brj-25043	276	36	)	)	PUNCT
brj-25043	276	37	references	reference	NOUN
brj-25043	276	38	combined	combine	VERB
brj-25043	276	39	microbial	microbial	ADJ
brj-25043	276	40	electrolysis	electrolysis	NOUN
brj-25043	276	41	–	–	PUNCT
brj-25043	276	42	ad	ad	NOUN
brj-25043	276	43	system	system	NOUN
brj-25043	276	44	;	;	PUNCT
brj-25043	276	45	real	real	ADJ
brj-25043	276	46	-	-	PUNCT
brj-25043	276	47	time	time	NOUN
brj-25043	276	48	optimization	optimization	PROPN
brj-25043	276	49	ann	ann	PROPN
brj-25043	276	50	,	,	PUNCT
brj-25043	276	51	anfis	anfis	PROPN
brj-25043	276	52	;	;	PUNCT
brj-25043	276	53	ph	ph	ADJ
brj-25043	276	54	,	,	PUNCT
brj-25043	276	55	oxidation	oxidation	NOUN
brj-25043	276	56	-	-	PUNCT
brj-25043	276	57	reduction	reduction	NOUN
brj-25043	276	58	potential	potential	NOUN
brj-25043	276	59	,	,	PUNCT
brj-25043	276	60	solids	solid	NOUN
brj-25043	276	61	,	,	PUNCT
brj-25043	276	62	hrt	hrt	PROPN
brj-25043	276	63	,	,	PUNCT
brj-25043	276	64	olr	olr	NOUN
brj-25043	276	65	,	,	PUNCT
brj-25043	276	66	voltage	voltage	NOUN
brj-25043	276	67	,	,	PUNCT
brj-25043	276	68	current	current	ADJ
brj-25043	276	69	r²	r²	NOUN
brj-25043	276	70	≈	≈	PROPN
brj-25043	276	71	0.984	0.984	NUM
brj-25043	276	72	(	(	PUNCT
brj-25043	276	73	ann	ann	PROPN
brj-25043	276	74	)	)	PUNCT
brj-25043	276	75	;	;	PUNCT
brj-25043	276	76	rmse	rmse	PROPN
brj-25043	276	77	≈	≈	PROPN
brj-25043	276	78	188	188	NUM
brj-25043	276	79	ml	ml	NOUN
brj-25043	276	80	day⁻¹	day⁻¹	NOUN
brj-25043	276	81	(	(	PUNCT
brj-25043	276	82	anfis	anfis	PROPN
brj-25043	276	83	)	)	PUNCT
brj-25043	276	84	;	;	PUNCT
brj-25043	276	85	outperforms	outperform	VERB
brj-25043	276	86	deterministic	deterministic	ADJ
brj-25043	276	87	models	model	NOUN
brj-25043	276	88	tufaner	tufaner	VERB
brj-25043	276	89	et	et	PROPN
brj-25043	276	90	al	al	PROPN
brj-25043	276	91	.	.	PROPN
brj-25043	276	92	2025	2025	NUM
brj-25043	276	93	lignocellulosic	lignocellulosic	ADJ
brj-25043	276	94	biomass	biomass	NOUN
brj-25043	276	95	pretreatment	pretreatment	NOUN
brj-25043	276	96	;	;	PUNCT
brj-25043	276	97	biomethane	biomethane	NOUN
brj-25043	276	98	yield	yield	NOUN
brj-25043	276	99	optimization	optimization	PROPN
brj-25043	276	100	ann	ann	PROPN
brj-25043	276	101	,	,	PUNCT
brj-25043	276	102	rf	rf	NOUN
brj-25043	276	103	,	,	PUNCT
brj-25043	276	104	svm	svm	ADJ
brj-25043	276	105	,	,	PUNCT
brj-25043	276	106	dt	dt	X
brj-25043	276	107	;	;	PUNCT
brj-25043	276	108	naoh	naoh	NOUN
brj-25043	276	109	-	-	PUNCT
brj-25043	276	110	pretreated	pretreate	VERB
brj-25043	276	111	xyris	xyris	PROPN
brj-25043	276	112	capensis	capensis	NOUN
brj-25043	276	113	biomass	biomass	NOUN
brj-25043	276	114	;	;	PUNCT
brj-25043	276	115	shap	shap	NOUN
brj-25043	276	116	,	,	PUNCT
brj-25043	276	117	k	k	NOUN
brj-25043	276	118	-	-	PUNCT
brj-25043	276	119	means	means	NOUN
brj-25043	276	120	rf	rf	NOUN
brj-25043	276	121	:	:	PUNCT
brj-25043	277	1	rmse	rmse	PROPN
brj-25043	278	1	≈	≈	PROPN
brj-25043	278	2	3.15	3.15	NUM
brj-25043	278	3	,	,	PUNCT
brj-25043	278	4	mape	mape	NOUN
brj-25043	278	5	≈	≈	PROPN
brj-25043	278	6	5.75	5.75	NUM
brj-25043	278	7	%	%	NOUN
brj-25043	278	8	;	;	PUNCT
brj-25043	278	9	superior	superior	ADJ
brj-25043	278	10	to	to	ADP
brj-25043	278	11	kinetic	kinetic	ADJ
brj-25043	278	12	models	model	NOUN
brj-25043	278	13	;	;	PUNCT
brj-25043	278	14	exposure	exposure	NOUN
brj-25043	278	15	time	time	NOUN
brj-25043	278	16	key	key	NOUN
brj-25043	278	17	adeleke	adeleke	PROPN
brj-25043	278	18	et	et	PROPN
brj-25043	278	19	al	al	PROPN
brj-25043	278	20	.	.	PROPN
brj-25043	278	21	2025	2025	NUM
brj-25043	278	22	global	global	ADJ
brj-25043	278	23	ad	ad	NOUN
brj-25043	278	24	review	review	NOUN
brj-25043	278	25	;	;	PUNCT
brj-25043	278	26	perturbation	perturbation	NOUN
brj-25043	278	27	detection	detection	NOUN
brj-25043	278	28	,	,	PUNCT
brj-25043	278	29	parameter	parameter	NOUN
brj-25043	278	30	estimation	estimation	PROPN
brj-25043	278	31	ann	ann	PROPN
brj-25043	278	32	,	,	PUNCT
brj-25043	278	33	fl	fl	PROPN
brj-25043	278	34	,	,	PUNCT
brj-25043	278	35	anfis	anfis	ADJ
brj-25043	278	36	,	,	PUNCT
brj-25043	278	37	svm	svm	PROPN
brj-25043	278	38	,	,	PUNCT
brj-25043	278	39	rf	rf	PROPN
brj-25043	278	40	,	,	PUNCT
brj-25043	278	41	ga	ga	PROPN
brj-25043	278	42	,	,	PUNCT
brj-25043	278	43	pso	pso	NOUN
brj-25043	278	44	;	;	PUNCT
brj-25043	279	1	hybrid	hybrid	PROPN
brj-25043	279	2	ga	ga	PROPN
brj-25043	279	3	-	-	PROPN
brj-25043	279	4	ann	ann	PROPN
brj-25043	279	5	r²	r²	NOUN
brj-25043	279	6	≈	≈	PROPN
brj-25043	279	7	0.9986	0.9986	NUM
brj-25043	279	8	(	(	PUNCT
brj-25043	279	9	ga	ga	PROPN
brj-25043	279	10	-	-	PROPN
brj-25043	279	11	ann	ann	PROPN
brj-25043	279	12	)	)	PUNCT
brj-25043	279	13	;	;	PUNCT
brj-25043	279	14	ml	ml	PART
brj-25043	279	15	outperforms	outperform	VERB
brj-25043	279	16	deterministic	deterministic	ADJ
brj-25043	279	17	models	model	NOUN
brj-25043	279	18	;	;	PUNCT
brj-25043	279	19	scada	scada	PROPN
brj-25043	279	20	integration	integration	PROPN
brj-25043	279	21	ling	ling	PROPN
brj-25043	279	22	et	et	PROPN
brj-25043	279	23	al	al	PROPN
brj-25043	279	24	.	.	PROPN
brj-25043	279	25	2024	2024	NUM
brj-25043	279	26	dry	dry	ADJ
brj-25043	279	27	ad	ad	NOUN
brj-25043	279	28	of	of	ADP
brj-25043	279	29	kitchen	kitchen	NOUN
brj-25043	279	30	waste	waste	NOUN
brj-25043	279	31	;	;	PUNCT
brj-25043	279	32	real	real	ADJ
brj-25043	279	33	-	-	PUNCT
brj-25043	279	34	time	time	NOUN
brj-25043	279	35	stability	stability	NOUN
brj-25043	279	36	control	control	VERB
brj-25043	279	37	eight	eight	NUM
brj-25043	279	38	algorithms	algorithm	NOUN
brj-25043	279	39	(	(	PUNCT
brj-25043	279	40	catboost	catboost	NOUN
brj-25043	279	41	)	)	PUNCT
brj-25043	279	42	;	;	PUNCT
brj-25043	279	43	data	datum	NOUN
brj-25043	279	44	from	from	ADP
brj-25043	279	45	four	four	NUM
brj-25043	279	46	dry	dry	ADJ
brj-25043	279	47	ad	ad	NOUN
brj-25043	279	48	plants	plant	NOUN
brj-25043	279	49	;	;	PUNCT
brj-25043	279	50	shap	shap	PROPN
brj-25043	279	51	catboost	catboost	PROPN
brj-25043	279	52	:	:	PUNCT
brj-25043	279	53	r²	r²	NOUN
brj-25043	279	54	=	=	SYM
brj-25043	279	55	0.604–0.915	0.604–0.915	NUM
brj-25043	279	56	(	(	PUNCT
brj-25043	279	57	biogas	biogas	NOUN
brj-25043	279	58	)	)	PUNCT
brj-25043	279	59	,	,	PUNCT
brj-25043	279	60	0.618–0.768	0.618–0.768	NUM
brj-25043	279	61	(	(	PUNCT
brj-25043	279	62	vfa	vfa	PROPN
brj-25043	279	63	/	/	SYM
brj-25043	279	64	alk	alk	PROPN
brj-25043	279	65	)	)	PUNCT
brj-25043	279	66	;	;	PUNCT
brj-25043	279	67	soft	soft	ADJ
brj-25043	279	68	sensors	sensor	NOUN
brj-25043	279	69	zou	zou	PROPN
brj-25043	279	70	et	et	PROPN
brj-25043	279	71	al	al	PROPN
brj-25043	279	72	.	.	PROPN
brj-25043	279	73	2024	2024	NUM
brj-25043	279	74	municipal	municipal	ADJ
brj-25043	279	75	wastewater	wastewater	NOUN
brj-25043	279	76	ad	ad	NOUN
brj-25043	279	77	;	;	PUNCT
brj-25043	279	78	emission	emission	NOUN
brj-25043	279	79	prediction	prediction	NOUN
brj-25043	279	80	non	non	ADJ
brj-25043	279	81	-	-	ADJ
brj-25043	279	82	linear	linear	ADJ
brj-25043	279	83	regression	regression	NOUN
brj-25043	279	84	vs.	vs.	X
brj-25043	279	85	ann	ann	PROPN
brj-25043	279	86	,	,	PUNCT
brj-25043	279	87	anfis	anfis	PROPN
brj-25043	279	88	,	,	PUNCT
brj-25043	279	89	ga	ga	PROPN
brj-25043	279	90	,	,	PUNCT
brj-25043	279	91	vfa	vfa	PROPN
brj-25043	279	92	,	,	PUNCT
brj-25043	279	93	solids	solid	NOUN
brj-25043	279	94	,	,	PUNCT
brj-25043	279	95	ph	ph	VERB
brj-25043	279	96	,	,	PUNCT
brj-25043	279	97	flow	flow	NOUN
brj-25043	279	98	r	r	NOUN
brj-25043	279	99	≈	≈	PROPN
brj-25043	279	100	0.81	0.81	NUM
brj-25043	279	101	(	(	PUNCT
brj-25043	279	102	regression	regression	NOUN
brj-25043	279	103	)	)	PUNCT
brj-25043	279	104	;	;	PUNCT
brj-25043	279	105	ann	ann	PROPN
brj-25043	279	106	/	/	SYM
brj-25043	279	107	anfis	anfi	VERB
brj-25043	279	108	higher	high	ADJ
brj-25043	279	109	but	but	CCONJ
brj-25043	279	110	uncertain	uncertain	ADJ
brj-25043	279	111	;	;	PUNCT
brj-25043	279	112	rates	rate	NOUN
brj-25043	279	113	22.0	22.0	NUM
brj-25043	279	114	to	to	PART
brj-25043	279	115	28.6	28.6	NUM
brj-25043	279	116	m³	m³	VERB
brj-25043	279	117	min⁻¹	min⁻¹	NOUN
brj-25043	279	118	asadi	asadi	NOUN
brj-25043	279	119	and	and	CCONJ
brj-25043	279	120	mcphedran	mcphedran	VERB
brj-25043	279	121	2021	2021	NUM
brj-25043	279	122	full	full	ADJ
brj-25043	279	123	-	-	PUNCT
brj-25043	279	124	scale	scale	NOUN
brj-25043	279	125	co	co	NOUN
brj-25043	279	126	-	-	NOUN
brj-25043	279	127	digestion	digestion	NOUN
brj-25043	279	128	;	;	PUNCT
brj-25043	279	129	raw	raw	ADJ
brj-25043	279	130	wastewater	wastewater	NOUN
brj-25043	279	131	influence	influence	NOUN
brj-25043	279	132	lstm	lstm	PROPN
brj-25043	279	133	with	with	ADP
brj-25043	279	134	ga	ga	PROPN
brj-25043	279	135	feature	feature	NOUN
brj-25043	279	136	selection	selection	NOUN
brj-25043	279	137	;	;	PUNCT
brj-25043	279	138	raw	raw	ADJ
brj-25043	279	139	wastewater	wastewater	NOUN
brj-25043	279	140	,	,	PUNCT
brj-25043	279	141	sludge	sludge	NOUN
brj-25043	279	142	data	datum	NOUN
brj-25043	279	143	;	;	PUNCT
brj-25043	279	144	bod₅	bod₅	PROPN
brj-25043	279	145	,	,	PUNCT
brj-25043	279	146	cod	cod	NOUN
brj-25043	279	147	,	,	PUNCT
brj-25043	279	148	tss	tss	NOUN
brj-25043	279	149	r²	r²	NOUN
brj-25043	279	150	≈	≈	PROPN
brj-25043	279	151	0.84	0.84	NUM
brj-25043	279	152	to	to	ADP
brj-25043	279	153	0.90	0.90	NUM
brj-25043	279	154	;	;	PUNCT
brj-25043	279	155	ga	ga	PROPN
brj-25043	279	156	improves	improve	VERB
brj-25043	279	157	lstm	lstm	NOUN
brj-25043	279	158	;	;	PUNCT
brj-25043	279	159	hrt	hrt	PROPN
brj-25043	279	160	essential	essential	ADJ
brj-25043	279	161	salamattalab	salamattalab	NOUN
brj-25043	279	162	et	et	PROPN
brj-25043	279	163	al	al	PROPN
brj-25043	279	164	.	.	PROPN
brj-25043	280	1	2024	2024	NUM
brj-25043	280	2	food	food	NOUN
brj-25043	280	3	-	-	PUNCT
brj-25043	280	4	waste	waste	NOUN
brj-25043	280	5	ad	ad	NOUN
brj-25043	280	6	;	;	PUNCT
brj-25043	280	7	feedstock	feedstock	NOUN
brj-25043	280	8	configuration	configuration	NOUN
brj-25043	280	9	mixup	mixup	NOUN
brj-25043	280	10	augmentation	augmentation	NOUN
brj-25043	280	11	+	+	CCONJ
brj-25043	280	12	global	global	ADJ
brj-25043	280	13	-	-	PUNCT
brj-25043	280	14	attention	attention	NOUN
brj-25043	280	15	lstm	lstm	NOUN
brj-25043	280	16	;	;	PUNCT
brj-25043	280	17	food	food	NOUN
brj-25043	280	18	-	-	PUNCT
brj-25043	280	19	waste	waste	NOUN
brj-25043	280	20	data	datum	NOUN
brj-25043	280	21	accuracy	accuracy	NOUN
brj-25043	280	22	≈	≈	PROPN
brj-25043	280	23	0.988	0.988	NUM
brj-25043	280	24	;	;	PUNCT
brj-25043	280	25	prevents	prevent	VERB
brj-25043	280	26	overfitting	overfitting	NOUN
brj-25043	280	27	;	;	PUNCT
brj-25043	280	28	better	well	ADJ
brj-25043	280	29	than	than	ADP
brj-25043	280	30	classical	classical	ADJ
brj-25043	280	31	models	model	NOUN
brj-25043	280	32	geng	geng	PROPN
brj-25043	280	33	et	et	PROPN
brj-25043	280	34	al	al	PROPN
brj-25043	280	35	.	.	PROPN
brj-25043	280	36	2024	2024	NUM
brj-25043	280	37	time	time	NOUN
brj-25043	280	38	-	-	PUNCT
brj-25043	280	39	series	series	NOUN
brj-25043	280	40	quantile	quantile	NOUN
brj-25043	280	41	prediction	prediction	NOUN
brj-25043	280	42	;	;	PUNCT
brj-25043	280	43	operational	operational	ADJ
brj-25043	280	44	planning	planning	NOUN
brj-25043	280	45	temporal	temporal	ADJ
brj-25043	280	46	fusion	fusion	NOUN
brj-25043	280	47	transformer	transformer	NOUN
brj-25043	280	48	(	(	PUNCT
brj-25043	280	49	tft	tft	ADJ
brj-25043	280	50	)	)	PUNCT
brj-25043	280	51	;	;	PUNCT
brj-25043	280	52	highfrequency	highfrequency	NOUN
brj-25043	280	53	data	data	PROPN
brj-25043	280	54	,	,	PUNCT
brj-25043	280	55	categorical	categorical	ADJ
brj-25043	280	56	features	feature	NOUN
brj-25043	280	57	mape	mape	NOUN
brj-25043	280	58	<	<	X
brj-25043	280	59	8	8	NUM
brj-25043	280	60	%	%	NOUN
brj-25043	280	61	(	(	PUNCT
brj-25043	280	62	7	7	NUM
brj-25043	280	63	-	-	PUNCT
brj-25043	280	64	day	day	NOUN
brj-25043	280	65	)	)	PUNCT
brj-25043	280	66	;	;	PUNCT
brj-25043	280	67	probabilistic	probabilistic	ADJ
brj-25043	280	68	quantiles	quantile	NOUN
brj-25043	280	69	;	;	PUNCT
brj-25043	280	70	interpretability	interpretability	NOUN
brj-25043	280	71	via	via	ADP
brj-25043	280	72	attention	attention	NOUN
brj-25043	280	73	sappl	sappl	NOUN
brj-25043	280	74	et	et	PROPN
brj-25043	280	75	al	al	PROPN
brj-25043	280	76	.	.	PROPN
brj-25043	280	77	2023	2023	NUM
brj-25043	280	78	wwtp	wwtp	PROPN
brj-25043	280	79	biogas	biogas	NOUN
brj-25043	280	80	prediction	prediction	NOUN
brj-25043	280	81	;	;	PUNCT
brj-25043	280	82	decision	decision	NOUN
brj-25043	280	83	support	support	NOUN
brj-25043	280	84	under	under	ADP
brj-25043	280	85	limited	limited	ADJ
brj-25043	280	86	input	input	NOUN
brj-25043	280	87	data	datum	NOUN
brj-25043	280	88	eight	eight	NUM
brj-25043	280	89	ml	ml	NOUN
brj-25043	280	90	models	model	NOUN
brj-25043	280	91	tested	test	VERB
brj-25043	280	92	;	;	PUNCT
brj-25043	280	93	3	3	NUM
brj-25043	280	94	-	-	PUNCT
brj-25043	280	95	model	model	NOUN
brj-25043	280	96	voting	voting	NOUN
brj-25043	280	97	ensemble	ensemble	ADJ
brj-25043	280	98	;	;	PUNCT
brj-25043	280	99	full	full	ADJ
brj-25043	280	100	-	-	PUNCT
brj-25043	280	101	scale	scale	NOUN
brj-25043	280	102	wwtp	wwtp	NOUN
brj-25043	280	103	sludge	sludge	NOUN
brj-25043	280	104	data	datum	NOUN
brj-25043	280	105	;	;	PUNCT
brj-25043	280	106	shap	shap	NOUN
brj-25043	280	107	for	for	ADP
brj-25043	280	108	feature	feature	NOUN
brj-25043	280	109	importance	importance	NOUN
brj-25043	280	110	r²	r²	NOUN
brj-25043	280	111	=	=	SYM
brj-25043	280	112	0.778	0.778	NUM
brj-25043	280	113	,	,	PUNCT
brj-25043	280	114	rmse	rmse	NOUN
brj-25043	280	115	=	=	NOUN
brj-25043	280	116	0.306	0.306	NUM
brj-25043	280	117	;	;	PUNCT
brj-25043	280	118	return	return	VERB
brj-25043	280	119	sludge	sludge	NOUN
brj-25043	280	120	and	and	CCONJ
brj-25043	280	121	influent	influent	NOUN
brj-25043	280	122	temperature	temperature	NOUN
brj-25043	280	123	key	key	NOUN
brj-25043	280	124	features	feature	NOUN
brj-25043	280	125	sun	sun	PROPN
brj-25043	280	126	et	et	PROPN
brj-25043	280	127	al	al	PROPN
brj-25043	280	128	.	.	PROPN
brj-25043	280	129	2023	2023	NUM
brj-25043	280	130	municipal	municipal	ADJ
brj-25043	280	131	co	co	NOUN
brj-25043	280	132	-	-	NOUN
brj-25043	280	133	digestion	digestion	NOUN
brj-25043	280	134	;	;	PUNCT
brj-25043	280	135	short	short	ADJ
brj-25043	280	136	-	-	PUNCT
brj-25043	280	137	term	term	NOUN
brj-25043	280	138	forecasting	forecasting	NOUN
brj-25043	280	139	mlp	mlp	NOUN
brj-25043	280	140	;	;	PUNCT
brj-25043	280	141	daily	daily	ADJ
brj-25043	280	142	lab	lab	NOUN
brj-25043	280	143	+	+	CCONJ
brj-25043	280	144	minute	minute	NOUN
brj-25043	280	145	-	-	PUNCT
brj-25043	280	146	scada	scada	PROPN
brj-25043	280	147	data	datum	NOUN
brj-25043	280	148	;	;	PUNCT
brj-25043	280	149	11	11	NUM
brj-25043	280	150	derived	derive	VERB
brj-25043	280	151	features	feature	NOUN
brj-25043	280	152	adjusted	adjust	VERB
brj-25043	280	153	r²	r²	NOUN
brj-25043	280	154	≈	≈	PROPN
brj-25043	280	155	0.78	0.78	NUM
brj-25043	280	156	,	,	PUNCT
brj-25043	280	157	mape	mape	NOUN
brj-25043	280	158	≈	≈	PROPN
brj-25043	280	159	13.4	13.4	NUM
brj-25043	280	160	%	%	NOUN
brj-25043	280	161	;	;	PUNCT
brj-25043	280	162	scada	scada	PROPN
brj-25043	280	163	nearly	nearly	ADV
brj-25043	280	164	as	as	ADV
brj-25043	280	165	good	good	ADJ
brj-25043	280	166	as	as	ADP
brj-25043	280	167	lab	lab	NOUN
brj-25043	280	168	;	;	PUNCT
brj-25043	280	169	outperforms	outperform	VERB
brj-25043	280	170	others	other	NOUN
brj-25043	280	171	schroer	schroer	NOUN
brj-25043	280	172	and	and	CCONJ
brj-25043	280	173	just	just	ADV
brj-25043	280	174	2023	2023	NUM
brj-25043	280	175	industrial	industrial	ADJ
brj-25043	280	176	ad	ad	NOUN
brj-25043	280	177	;	;	PUNCT
brj-25043	280	178	continuous	continuous	ADJ
brj-25043	280	179	monitoring	monitoring	NOUN
brj-25043	280	180	and	and	CCONJ
brj-25043	280	181	stability	stability	NOUN
brj-25043	280	182	rf	rf	PROPN
brj-25043	280	183	,	,	PUNCT
brj-25043	280	184	ann	ann	PROPN
brj-25043	280	185	,	,	PUNCT
brj-25043	280	186	knn	knn	PROPN
brj-25043	280	187	,	,	PUNCT
brj-25043	280	188	svr	svr	PROPN
brj-25043	280	189	,	,	PUNCT
brj-25043	280	190	xgboost	xgboost	ADV
brj-25043	280	191	;	;	PUNCT
brj-25043	280	192	industrialscale	industrialscale	NOUN
brj-25043	280	193	ad	ad	NOUN
brj-25043	280	194	data	datum	NOUN
brj-25043	280	195	rf	rf	VERB
brj-25043	280	196	best	well	ADV
brj-25043	280	197	:	:	PUNCT
brj-25043	280	198	r²	r²	VERB
brj-25043	280	199	≈	≈	PROPN
brj-25043	280	200	0.924	0.924	NUM
brj-25043	280	201	;	;	PUNCT
brj-25043	280	202	suggests	suggest	VERB
brj-25043	280	203	iot	iot	ADJ
brj-25043	280	204	integration	integration	NOUN
brj-25043	280	205	;	;	PUNCT
brj-25043	280	206	tree	tree	NOUN
brj-25043	280	207	-	-	PUNCT
brj-25043	280	208	based	base	VERB
brj-25043	280	209	superior	superior	NOUN
brj-25043	280	210	for	for	ADP
brj-25043	280	211	large	large	ADJ
brj-25043	280	212	datasets	dataset	NOUN
brj-25043	280	213	yildirim	yildirim	NOUN
brj-25043	280	214	and	and	CCONJ
brj-25043	280	215	ozkaya	ozkaya	PROPN
brj-25043	280	216	2023	2023	NUM
brj-25043	280	217	municipal	municipal	ADJ
brj-25043	280	218	wastewater	wastewater	NOUN
brj-25043	280	219	acod	acod	NOUN
brj-25043	280	220	;	;	PUNCT
brj-25043	280	221	process	process	NOUN
brj-25043	280	222	optimization	optimization	NOUN
brj-25043	280	223	and	and	CCONJ
brj-25043	280	224	prediction	prediction	NOUN
brj-25043	280	225	under	under	ADP
brj-25043	280	226	missing	miss	VERB
brj-25043	280	227	data	datum	NOUN
brj-25043	280	228	hybrid	hybrid	ADJ
brj-25043	280	229	dl	dl	PROPN
brj-25043	280	230	:	:	PUNCT
brj-25043	280	231	da	da	ADJ
brj-25043	280	232	-	-	PUNCT
brj-25043	280	233	lstm	lstm	ADJ
brj-25043	280	234	+	+	CCONJ
brj-25043	280	235	variable	variable	ADJ
brj-25043	280	236	selection	selection	NOUN
brj-25043	280	237	network	network	NOUN
brj-25043	280	238	(	(	PUNCT
brj-25043	280	239	vsn	vsn	PROPN
brj-25043	280	240	)	)	PUNCT
brj-25043	280	241	;	;	PUNCT
brj-25043	280	242	2	2	NUM
brj-25043	280	243	-	-	PUNCT
brj-25043	280	244	year	year	NOUN
brj-25043	280	245	acod	acod	NOUN
brj-25043	280	246	data	datum	NOUN
brj-25043	280	247	r²	r²	NOUN
brj-25043	280	248	:	:	PUNCT
brj-25043	280	249	lstm	lstm	NOUN
brj-25043	280	250	=	=	NOUN
brj-25043	280	251	0.38	0.38	NUM
brj-25043	280	252	→	→	SYM
brj-25043	280	253	da	da	ADJ
brj-25043	280	254	-	-	PUNCT
brj-25043	280	255	lstm	lstm	NOUN
brj-25043	280	256	=	=	NOUN
brj-25043	280	257	0.68	0.68	NUM
brj-25043	280	258	→	→	SYM
brj-25043	280	259	da	da	ADJ
brj-25043	280	260	-	-	PUNCT
brj-25043	280	261	lstm	lstm	PROPN
brj-25043	280	262	-	-	PROPN
brj-25043	280	263	vsn	vsn	NOUN
brj-25043	280	264	=	=	NOUN
brj-25043	280	265	0.76	0.76	NUM
brj-25043	280	266	;	;	PUNCT
brj-25043	280	267	vsn	vsn	NUM
brj-25043	280	268	improves	improve	VERB
brj-25043	280	269	interpretability	interpretability	NOUN
brj-25043	280	270	via	via	ADP
brj-25043	280	271	feature	feature	NOUN
brj-25043	280	272	importance	importance	NOUN
brj-25043	280	273	jeong	jeong	PROPN
brj-25043	280	274	et	et	PROPN
brj-25043	280	275	al	al	PROPN
brj-25043	280	276	.	.	PROPN
brj-25043	280	277	2021	2021	NUM
brj-25043	280	278	peer	peer	NOUN
brj-25043	280	279	-	-	PUNCT
brj-25043	280	280	reviewed	review	VERB
brj-25043	280	281	review	review	NOUN
brj-25043	280	282	article	article	NOUN
brj-25043	280	283	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	280	284	galal	galal	PROPN
brj-25043	280	285	et	et	PROPN
brj-25043	280	286	al	al	PROPN
brj-25043	280	287	.	.	PROPN
brj-25043	281	1	(	(	PUNCT
brj-25043	281	2	2025	2025	NUM
brj-25043	281	3	)	)	PUNCT
brj-25043	281	4	.	.	PUNCT
brj-25043	282	1	“	"	PUNCT
brj-25043	282	2	math	math	NOUN
brj-25043	282	3	modeling	modeling	NOUN
brj-25043	282	4	biogas	biogas	NOUN
brj-25043	282	5	production	production	NOUN
brj-25043	282	6	,	,	PUNCT
brj-25043	282	7	”	"	PUNCT
brj-25043	282	8	bioresources	bioresource	NOUN
brj-25043	282	9	20(4	20(4	NOUN
brj-25043	282	10	)	)	PUNCT
brj-25043	282	11	,	,	PUNCT
brj-25043	282	12	11237	11237	NUM
brj-25043	282	13	-	-	SYM
brj-25043	282	14	11266	11266	NUM
brj-25043	282	15	.	.	PUNCT
brj-25043	283	1	11254	11254	NUM
brj-25043	283	2	across	across	ADP
brj-25043	283	3	pilot	pilot	NOUN
brj-25043	283	4	and	and	CCONJ
brj-25043	283	5	full	full	ADJ
brj-25043	283	6	-	-	PUNCT
brj-25043	283	7	scale	scale	NOUN
brj-25043	283	8	settings	setting	NOUN
brj-25043	283	9	,	,	PUNCT
brj-25043	283	10	ml	ml	ADP
brj-25043	283	11	methods	method	NOUN
brj-25043	283	12	generally	generally	ADV
brj-25043	283	13	outperform	outperform	VERB
brj-25043	283	14	classical	classical	ADJ
brj-25043	283	15	kinetic	kinetic	ADJ
brj-25043	283	16	baselines	baseline	NOUN
brj-25043	283	17	for	for	ADP
brj-25043	283	18	short	short	ADJ
brj-25043	283	19	-	-	PUNCT
brj-25043	283	20	term	term	NOUN
brj-25043	283	21	forecasting	forecasting	NOUN
brj-25043	283	22	and	and	CCONJ
brj-25043	283	23	stability	stability	NOUN
brj-25043	283	24	proxies	proxy	NOUN
brj-25043	283	25	,	,	PUNCT
brj-25043	283	26	with	with	ADP
brj-25043	283	27	many	many	ADJ
brj-25043	283	28	studies	study	NOUN
brj-25043	283	29	reporting	report	VERB
brj-25043	283	30	usable	usable	ADJ
brj-25043	283	31	accuracy	accuracy	NOUN
brj-25043	283	32	(	(	PUNCT
brj-25043	283	33	often	often	ADV
brj-25043	283	34	r²	r²	VERB
brj-25043	283	35	≥	≥	NOUN
brj-25043	283	36	0.80	0.80	NUM
brj-25043	283	37	)	)	PUNCT
brj-25043	283	38	for	for	ADP
brj-25043	283	39	operational	operational	ADJ
brj-25043	283	40	decision	decision	NOUN
brj-25043	283	41	-	-	PUNCT
brj-25043	283	42	making	making	NOUN
brj-25043	283	43	.	.	PUNCT
brj-25043	284	1	tree	tree	NOUN
brj-25043	284	2	-	-	PUNCT
brj-25043	284	3	based	base	VERB
brj-25043	284	4	ensembles	ensemble	NOUN
brj-25043	284	5	(	(	PUNCT
brj-25043	284	6	rf	rf	ADJ
brj-25043	284	7	,	,	PUNCT
brj-25043	284	8	xgboost	xgboost	ADJ
brj-25043	284	9	/	/	SYM
brj-25043	284	10	catboost	catboost	ADJ
brj-25043	284	11	)	)	PUNCT
brj-25043	284	12	are	be	AUX
brj-25043	284	13	the	the	DET
brj-25043	284	14	most	most	ADV
brj-25043	284	15	reliable	reliable	ADJ
brj-25043	284	16	with	with	ADP
brj-25043	284	17	tabular	tabular	PROPN
brj-25043	284	18	scada	scada	PROPN
brj-25043	284	19	inputs	inputs	PROPN
brj-25043	284	20	,	,	PUNCT
brj-25043	284	21	while	while	SCONJ
brj-25043	284	22	sequence	sequence	NOUN
brj-25043	284	23	models	model	NOUN
brj-25043	284	24	(	(	PUNCT
brj-25043	284	25	lstm	lstm	NOUN
brj-25043	284	26	/	/	SYM
brj-25043	284	27	tft	tft	ADJ
brj-25043	284	28	)	)	PUNCT
brj-25043	284	29	capture	capture	VERB
brj-25043	284	30	temporal	temporal	ADJ
brj-25043	284	31	dependencies	dependency	NOUN
brj-25043	284	32	and	and	CCONJ
brj-25043	284	33	enable	enable	VERB
brj-25043	284	34	probabilistic	probabilistic	ADJ
brj-25043	284	35	(	(	PUNCT
brj-25043	284	36	quantile	quantile	ADJ
brj-25043	284	37	)	)	PUNCT
brj-25043	284	38	forecasts	forecast	NOUN
brj-25043	284	39	.	.	PUNCT
brj-25043	285	1	explainability	explainability	NOUN
brj-25043	285	2	tools	tool	NOUN
brj-25043	285	3	(	(	PUNCT
brj-25043	285	4	shap	shap	NOUN
brj-25043	285	5	/	/	SYM
brj-25043	285	6	attention	attention	NOUN
brj-25043	285	7	)	)	PUNCT
brj-25043	285	8	consistently	consistently	ADV
brj-25043	285	9	identify	identify	VERB
brj-25043	285	10	olr	olr	NOUN
brj-25043	285	11	,	,	PUNCT
brj-25043	285	12	ph	ph	ADJ
brj-25043	285	13	,	,	PUNCT
brj-25043	285	14	temperature	temperature	NOUN
brj-25043	285	15	,	,	PUNCT
brj-25043	285	16	and	and	CCONJ
brj-25043	285	17	feed	feed	NOUN
brj-25043	285	18	configuration	configuration	NOUN
brj-25043	285	19	as	as	ADP
brj-25043	285	20	primary	primary	ADJ
brj-25043	285	21	levers	lever	NOUN
brj-25043	285	22	,	,	PUNCT
brj-25043	285	23	and	and	CCONJ
brj-25043	285	24	soft	soft	ADJ
brj-25043	285	25	-	-	PUNCT
brj-25043	285	26	sensor	sensor	NOUN
brj-25043	285	27	surrogates	surrogate	NOUN
brj-25043	285	28	(	(	PUNCT
brj-25043	285	29	e.g.	e.g.	ADV
brj-25043	285	30	,	,	PUNCT
brj-25043	285	31	vfa	vfa	PROPN
brj-25043	285	32	/	/	SYM
brj-25043	285	33	alk	alk	PROPN
brj-25043	285	34	)	)	PUNCT
brj-25043	285	35	enhance	enhance	VERB
brj-25043	285	36	early	early	ADJ
brj-25043	285	37	warning	warning	NOUN
brj-25043	285	38	.	.	PUNCT
brj-25043	286	1	practically	practically	ADV
brj-25043	286	2	,	,	PUNCT
brj-25043	286	3	plants	plant	NOUN
brj-25043	286	4	can	can	AUX
brj-25043	286	5	retain	retain	VERB
brj-25043	286	6	modified	modify	VERB
brj-25043	286	7	-	-	PUNCT
brj-25043	286	8	gompertz	gompertz	NOUN
brj-25043	286	9	-	-	PUNCT
brj-25043	286	10	type	type	NOUN
brj-25043	286	11	fits	fit	VERB
brj-25043	286	12	for	for	ADP
brj-25043	286	13	design	design	NOUN
brj-25043	286	14	/	/	SYM
brj-25043	286	15	batch	batch	NOUN
brj-25043	286	16	contexts	contexts	NOUN
brj-25043	286	17	and	and	CCONJ
brj-25043	286	18	layer	layer	NOUN
brj-25043	286	19	ml	ml	NOUN
brj-25043	286	20	for	for	ADP
brj-25043	286	21	online	online	ADJ
brj-25043	286	22	supervision	supervision	NOUN
brj-25043	286	23	,	,	PUNCT
brj-25043	286	24	provided	provide	VERB
brj-25043	286	25	basic	basic	ADJ
brj-25043	286	26	hygiene	hygiene	NOUN
brj-25043	286	27	(	(	PUNCT
brj-25043	286	28	outlier	outlier	NOUN
brj-25043	286	29	handling	handling	NOUN
brj-25043	286	30	,	,	PUNCT
brj-25043	286	31	rolling	rolling	ADJ
brj-25043	286	32	/	/	SYM
brj-25043	286	33	external	external	ADJ
brj-25043	286	34	validation	validation	NOUN
brj-25043	286	35	)	)	PUNCT
brj-25043	286	36	is	be	AUX
brj-25043	286	37	in	in	ADP
brj-25043	286	38	place	place	NOUN
brj-25043	286	39	to	to	PART
brj-25043	286	40	limit	limit	VERB
brj-25043	286	41	overfitting	overfitting	NOUN
brj-25043	286	42	and	and	CCONJ
brj-25043	286	43	improve	improve	VERB
brj-25043	286	44	transferability	transferability	NOUN
brj-25043	286	45	.	.	PUNCT
brj-25043	287	1	in	in	ADP
brj-25043	287	2	practice	practice	NOUN
brj-25043	287	3	,	,	PUNCT
brj-25043	287	4	ann	ann	PROPN
brj-25043	287	5	models	model	NOUN
brj-25043	287	6	may	may	AUX
brj-25043	287	7	overfit	overfit	VERB
brj-25043	287	8	small	small	ADJ
brj-25043	287	9	datasets	dataset	NOUN
brj-25043	287	10	and	and	CCONJ
brj-25043	287	11	fail	fail	VERB
brj-25043	287	12	to	to	PART
brj-25043	287	13	generalize	generalize	VERB
brj-25043	287	14	to	to	ADP
brj-25043	287	15	new	new	ADJ
brj-25043	287	16	substrates	substrate	NOUN
brj-25043	287	17	or	or	CCONJ
brj-25043	287	18	variable	variable	ADJ
brj-25043	287	19	operating	operating	NOUN
brj-25043	287	20	conditions	condition	NOUN
brj-25043	287	21	.	.	PUNCT
brj-25043	288	1	industrial	industrial	ADJ
brj-25043	288	2	deployment	deployment	NOUN
brj-25043	288	3	is	be	AUX
brj-25043	288	4	further	far	ADV
brj-25043	288	5	constrained	constrain	VERB
brj-25043	288	6	by	by	ADP
brj-25043	288	7	the	the	DET
brj-25043	288	8	high	high	ADJ
brj-25043	288	9	cost	cost	NOUN
brj-25043	288	10	of	of	ADP
brj-25043	288	11	sensors	sensor	NOUN
brj-25043	288	12	,	,	PUNCT
brj-25043	288	13	limited	limited	ADJ
brj-25043	288	14	data	data	NOUN
brj-25043	288	15	availability	availability	NOUN
brj-25043	288	16	,	,	PUNCT
brj-25043	288	17	and	and	CCONJ
brj-25043	288	18	the	the	DET
brj-25043	288	19	complexity	complexity	NOUN
brj-25043	288	20	of	of	ADP
brj-25043	288	21	integrating	integrate	VERB
brj-25043	288	22	ml	ml	NOUN
brj-25043	288	23	models	model	NOUN
brj-25043	288	24	into	into	ADP
brj-25043	288	25	real	real	ADJ
brj-25043	288	26	-	-	PUNCT
brj-25043	288	27	time	time	NOUN
brj-25043	288	28	control	control	NOUN
brj-25043	288	29	systems	system	NOUN
brj-25043	288	30	.	.	PUNCT
brj-25043	289	1	comparative	comparative	ADJ
brj-25043	289	2	performance	performance	NOUN
brj-25043	289	3	of	of	ADP
brj-25043	289	4	models	model	NOUN
brj-25043	289	5	to	to	PART
brj-25043	289	6	evaluate	evaluate	VERB
brj-25043	289	7	the	the	DET
brj-25043	289	8	relative	relative	ADJ
brj-25043	289	9	strengths	strength	NOUN
brj-25043	289	10	of	of	ADP
brj-25043	289	11	different	different	ADJ
brj-25043	289	12	modelling	modelling	NOUN
brj-25043	289	13	approaches	approach	NOUN
brj-25043	289	14	,	,	PUNCT
brj-25043	289	15	a	a	DET
brj-25043	289	16	comparative	comparative	ADJ
brj-25043	289	17	analysis	analysis	NOUN
brj-25043	289	18	was	be	AUX
brj-25043	289	19	conducted	conduct	VERB
brj-25043	289	20	between	between	ADP
brj-25043	289	21	mathematical	mathematical	ADJ
brj-25043	289	22	models	model	NOUN
brj-25043	289	23	and	and	CCONJ
brj-25043	289	24	ml	ml	VERB
brj-25043	289	25	by	by	ADP
brj-25043	289	26	using	use	VERB
brj-25043	289	27	ann	ann	PROPN
brj-25043	289	28	techniques	technique	NOUN
brj-25043	289	29	applied	apply	VERB
brj-25043	289	30	to	to	ADP
brj-25043	289	31	biogas	biogas	NOUN
brj-25043	289	32	production	production	NOUN
brj-25043	289	33	from	from	ADP
brj-25043	289	34	co	co	ADJ
brj-25043	289	35	-	-	NOUN
brj-25043	289	36	digestion	digestion	NOUN
brj-25043	289	37	systems	system	NOUN
brj-25043	289	38	.	.	PUNCT
brj-25043	290	1	this	this	DET
brj-25043	290	2	comparison	comparison	NOUN
brj-25043	290	3	assessed	assess	VERB
brj-25043	290	4	predictive	predictive	ADJ
brj-25043	290	5	accuracy	accuracy	NOUN
brj-25043	290	6	using	use	VERB
brj-25043	290	7	statistical	statistical	ADJ
brj-25043	290	8	indicators	indicator	NOUN
brj-25043	290	9	such	such	ADJ
brj-25043	290	10	as	as	ADP
brj-25043	290	11	r²	r²	NOUN
brj-25043	290	12	and	and	CCONJ
brj-25043	290	13	rmse	rmse	NOUN
brj-25043	290	14	.	.	PUNCT
brj-25043	291	1	the	the	DET
brj-25043	291	2	results	result	NOUN
brj-25043	291	3	provide	provide	VERB
brj-25043	291	4	insights	insight	NOUN
brj-25043	291	5	into	into	ADP
brj-25043	291	6	the	the	DET
brj-25043	291	7	trade	trade	NOUN
brj-25043	291	8	-	-	PUNCT
brj-25043	291	9	offs	off	NOUN
brj-25043	291	10	between	between	ADP
brj-25043	291	11	classical	classical	ADJ
brj-25043	291	12	kinetic	kinetic	NOUN
brj-25043	291	13	formulations	formulation	NOUN
brj-25043	291	14	and	and	CCONJ
brj-25043	291	15	advanced	advanced	ADJ
brj-25043	291	16	data	data	NOUN
brj-25043	291	17	-	-	PUNCT
brj-25043	291	18	driven	drive	VERB
brj-25043	291	19	methods	method	NOUN
brj-25043	291	20	.	.	PUNCT
brj-25043	292	1	table	table	NOUN
brj-25043	292	2	5	5	NUM
brj-25043	292	3	presents	present	VERB
brj-25043	292	4	a	a	DET
brj-25043	292	5	comparative	comparative	ADJ
brj-25043	292	6	analysis	analysis	NOUN
brj-25043	292	7	between	between	ADP
brj-25043	292	8	classical	classical	ADJ
brj-25043	292	9	and	and	CCONJ
brj-25043	292	10	ml	ml	NOUN
brj-25043	292	11	models	model	NOUN
brj-25043	292	12	’	'	PUNCT
brj-25043	292	13	performance	performance	NOUN
brj-25043	292	14	metrics	metric	NOUN
brj-25043	292	15	for	for	ADP
brj-25043	292	16	predicting	predict	VERB
brj-25043	292	17	biogas	biogas	NOUN
brj-25043	292	18	production	production	NOUN
brj-25043	292	19	from	from	ADP
brj-25043	292	20	co	co	ADJ
brj-25043	292	21	-	-	NOUN
brj-25043	292	22	digestion	digestion	NOUN
brj-25043	292	23	systems	system	NOUN
brj-25043	292	24	for	for	ADP
brj-25043	292	25	the	the	DET
brj-25043	292	26	same	same	ADJ
brj-25043	292	27	dataset	dataset	NOUN
brj-25043	292	28	(	(	PUNCT
brj-25043	292	29	abdel	abdel	PROPN
brj-25043	292	30	daiem	daiem	PROPN
brj-25043	292	31	et	et	PROPN
brj-25043	292	32	al	al	PROPN
brj-25043	292	33	.	.	PROPN
brj-25043	292	34	2021	2021	NUM
brj-25043	292	35	)	)	PUNCT
brj-25043	292	36	.	.	PUNCT
brj-25043	293	1	the	the	DET
brj-25043	293	2	comparative	comparative	ADJ
brj-25043	293	3	analysis	analysis	NOUN
brj-25043	293	4	highlights	highlight	NOUN
brj-25043	293	5	the	the	DET
brj-25043	293	6	performance	performance	NOUN
brj-25043	293	7	of	of	ADP
brj-25043	293	8	both	both	PRON
brj-25043	293	9	traditional	traditional	ADJ
brj-25043	293	10	tdmms	tdmms	NOUN
brj-25043	293	11	and	and	CCONJ
brj-25043	293	12	ann	ann	PROPN
brj-25043	293	13	approaches	approach	NOUN
brj-25043	293	14	in	in	ADP
brj-25043	293	15	predicting	predict	VERB
brj-25043	293	16	biogas	biogas	NOUN
brj-25043	293	17	production	production	NOUN
brj-25043	293	18	from	from	ADP
brj-25043	293	19	co	co	ADJ
brj-25043	293	20	-	-	NOUN
brj-25043	293	21	digestion	digestion	NOUN
brj-25043	293	22	systems	system	NOUN
brj-25043	293	23	.	.	PUNCT
brj-25043	294	1	among	among	ADP
brj-25043	294	2	the	the	DET
brj-25043	294	3	mathematical	mathematical	ADJ
brj-25043	294	4	models	model	NOUN
brj-25043	294	5	,	,	PUNCT
brj-25043	294	6	the	the	DET
brj-25043	294	7	logistic	logistic	ADJ
brj-25043	294	8	kinetic	kinetic	ADJ
brj-25043	294	9	formulation	formulation	NOUN
brj-25043	294	10	emerged	emerge	VERB
brj-25043	294	11	as	as	ADP
brj-25043	294	12	the	the	DET
brj-25043	294	13	most	most	ADV
brj-25043	294	14	accurate	accurate	ADJ
brj-25043	294	15	,	,	PUNCT
brj-25043	294	16	with	with	ADP
brj-25043	294	17	an	an	DET
brj-25043	294	18	r²	r²	NOUN
brj-25043	294	19	value	value	NOUN
brj-25043	294	20	of	of	ADP
brj-25043	294	21	0.9879	0.9879	NUM
brj-25043	294	22	,	,	PUNCT
brj-25043	294	23	although	although	SCONJ
brj-25043	294	24	all	all	DET
brj-25043	294	25	mathematical	mathematical	ADJ
brj-25043	294	26	models	model	NOUN
brj-25043	294	27	achieved	achieve	VERB
brj-25043	294	28	strong	strong	ADJ
brj-25043	294	29	correlations	correlation	NOUN
brj-25043	294	30	(	(	PUNCT
brj-25043	294	31	r²	r²	VERB
brj-25043	294	32	>	>	X
brj-25043	294	33	0.97	0.97	NUM
brj-25043	294	34	)	)	PUNCT
brj-25043	294	35	.	.	PUNCT
brj-25043	295	1	nevertheless	nevertheless	ADV
brj-25043	295	2	,	,	PUNCT
brj-25043	295	3	their	their	PRON
brj-25043	295	4	relatively	relatively	ADV
brj-25043	295	5	large	large	ADJ
brj-25043	295	6	rmse	rmse	NOUN
brj-25043	295	7	>	>	X
brj-25043	295	8	1000	1000	NUM
brj-25043	295	9	indicates	indicate	VERB
brj-25043	295	10	limited	limited	ADJ
brj-25043	295	11	predictive	predictive	ADJ
brj-25043	295	12	precision	precision	NOUN
brj-25043	295	13	when	when	SCONJ
brj-25043	295	14	applied	apply	VERB
brj-25043	295	15	to	to	ADP
brj-25043	295	16	dynamic	dynamic	ADJ
brj-25043	295	17	and	and	CCONJ
brj-25043	295	18	nonlinear	nonlinear	ADJ
brj-25043	295	19	digestion	digestion	NOUN
brj-25043	295	20	processes	process	NOUN
brj-25043	295	21	,	,	PUNCT
brj-25043	295	22	underscoring	underscore	VERB
brj-25043	295	23	their	their	PRON
brj-25043	295	24	inability	inability	NOUN
brj-25043	295	25	to	to	PART
brj-25043	295	26	capture	capture	VERB
brj-25043	295	27	the	the	DET
brj-25043	295	28	complexity	complexity	NOUN
brj-25043	295	29	of	of	ADP
brj-25043	295	30	anaerobic	anaerobic	ADJ
brj-25043	295	31	digestion	digestion	NOUN
brj-25043	295	32	fully	fully	ADV
brj-25043	295	33	.	.	PUNCT
brj-25043	296	1	in	in	ADP
brj-25043	296	2	contrast	contrast	NOUN
brj-25043	296	3	,	,	PUNCT
brj-25043	296	4	ann	ann	PROPN
brj-25043	296	5	-	-	PUNCT
brj-25043	296	6	based	base	VERB
brj-25043	296	7	approaches	approach	NOUN
brj-25043	296	8	demonstrated	demonstrate	VERB
brj-25043	296	9	considerably	considerably	ADV
brj-25043	296	10	lower	low	ADJ
brj-25043	296	11	error	error	NOUN
brj-25043	296	12	margins	margin	NOUN
brj-25043	296	13	(	(	PUNCT
brj-25043	296	14	rmse	rmse	NOUN
brj-25043	296	15	<	<	X
brj-25043	296	16	10	10	NUM
brj-25043	296	17	)	)	PUNCT
brj-25043	296	18	,	,	PUNCT
brj-25043	296	19	highlighting	highlight	VERB
brj-25043	296	20	their	their	PRON
brj-25043	296	21	superior	superior	ADJ
brj-25043	296	22	capacity	capacity	NOUN
brj-25043	296	23	to	to	PART
brj-25043	296	24	model	model	NOUN
brj-25043	296	25	process	process	NOUN
brj-25043	296	26	variability	variability	NOUN
brj-25043	296	27	and	and	CCONJ
brj-25043	296	28	nonlinear	nonlinear	ADJ
brj-25043	296	29	relationships	relationship	NOUN
brj-25043	296	30	.	.	PUNCT
brj-25043	297	1	conventional	conventional	ADJ
brj-25043	297	2	ann	ann	PROPN
brj-25043	297	3	training	training	NOUN
brj-25043	297	4	methods	method	NOUN
brj-25043	297	5	such	such	ADJ
brj-25043	297	6	as	as	ADP
brj-25043	297	7	back	back	ADJ
brj-25043	297	8	-	-	PUNCT
brj-25043	297	9	propagation	propagation	NOUN
brj-25043	297	10	,	,	PUNCT
brj-25043	297	11	marquardt	marquardt	PROPN
brj-25043	297	12	–	–	PUNCT
brj-25043	297	13	levenberg	levenberg	PROPN
brj-25043	297	14	,	,	PUNCT
brj-25043	297	15	and	and	CCONJ
brj-25043	297	16	ant	ant	ADJ
brj-25043	297	17	colony	colony	NOUN
brj-25043	297	18	optimization	optimization	NOUN
brj-25043	297	19	yielded	yield	VERB
brj-25043	297	20	moderate	moderate	ADJ
brj-25043	297	21	-	-	PUNCT
brj-25043	297	22	to	to	ADP
brj-25043	297	23	-	-	PUNCT
brj-25043	297	24	high	high	ADJ
brj-25043	297	25	predictive	predictive	ADJ
brj-25043	297	26	accuracy	accuracy	NOUN
brj-25043	297	27	(	(	PUNCT
brj-25043	297	28	r²	r²	VERB
brj-25043	297	29	between	between	ADP
brj-25043	297	30	0.89	0.89	NUM
brj-25043	297	31	and	and	CCONJ
brj-25043	297	32	0.92	0.92	NUM
brj-25043	297	33	)	)	PUNCT
brj-25043	297	34	;	;	PUNCT
brj-25043	297	35	however	however	ADV
brj-25043	297	36	,	,	PUNCT
brj-25043	297	37	the	the	DET
brj-25043	297	38	integration	integration	NOUN
brj-25043	297	39	of	of	ADP
brj-25043	297	40	metaheuristic	metaheuristic	ADJ
brj-25043	297	41	optimization	optimization	NOUN
brj-25043	297	42	techniques	technique	NOUN
brj-25043	297	43	substantially	substantially	ADV
brj-25043	297	44	improved	improve	VERB
brj-25043	297	45	performance	performance	NOUN
brj-25043	297	46	.	.	PUNCT
brj-25043	298	1	specifically	specifically	ADV
brj-25043	298	2	,	,	PUNCT
brj-25043	298	3	the	the	DET
brj-25043	298	4	mffnn	mffnn	NOUN
brj-25043	298	5	-	-	PUNCT
brj-25043	298	6	mfo	mfo	NOUN
brj-25043	298	7	model	model	NOUN
brj-25043	298	8	achieved	achieve	VERB
brj-25043	298	9	nearperfect	nearperfect	NOUN
brj-25043	298	10	predictive	predictive	ADJ
brj-25043	298	11	accuracy	accuracy	NOUN
brj-25043	298	12	(	(	PUNCT
brj-25043	298	13	r²	r²	NOUN
brj-25043	298	14	=	=	SYM
brj-25043	298	15	0.9994	0.9994	NUM
brj-25043	298	16	;	;	PUNCT
brj-25043	298	17	rmse	rmse	NOUN
brj-25043	298	18	=	=	PROPN
brj-25043	298	19	3.86	3.86	NUM
brj-25043	298	20	)	)	PUNCT
brj-25043	298	21	,	,	PUNCT
brj-25043	298	22	clearly	clearly	ADV
brj-25043	298	23	outperforming	outperform	VERB
brj-25043	298	24	both	both	CCONJ
brj-25043	298	25	conventional	conventional	ADJ
brj-25043	298	26	ann	ann	PROPN
brj-25043	298	27	structures	structure	NOUN
brj-25043	298	28	and	and	CCONJ
brj-25043	298	29	mathematical	mathematical	ADJ
brj-25043	298	30	models	model	NOUN
brj-25043	298	31	.	.	PUNCT
brj-25043	299	1	these	these	DET
brj-25043	299	2	findings	finding	NOUN
brj-25043	299	3	illustrate	illustrate	VERB
brj-25043	299	4	the	the	DET
brj-25043	299	5	value	value	NOUN
brj-25043	299	6	of	of	ADP
brj-25043	299	7	ann	ann	PROPN
brj-25043	299	8	models	model	NOUN
brj-25043	299	9	,	,	PUNCT
brj-25043	299	10	particularly	particularly	ADV
brj-25043	299	11	when	when	SCONJ
brj-25043	299	12	coupled	couple	VERB
brj-25043	299	13	with	with	ADP
brj-25043	299	14	advanced	advanced	ADJ
brj-25043	299	15	optimization	optimization	NOUN
brj-25043	299	16	algorithms	algorithm	NOUN
brj-25043	299	17	,	,	PUNCT
brj-25043	299	18	in	in	ADP
brj-25043	299	19	addressing	address	VERB
brj-25043	299	20	the	the	DET
brj-25043	299	21	complexity	complexity	NOUN
brj-25043	299	22	of	of	ADP
brj-25043	299	23	anaerobic	anaerobic	ADJ
brj-25043	299	24	digestion	digestion	NOUN
brj-25043	299	25	systems	system	NOUN
brj-25043	299	26	and	and	CCONJ
brj-25043	299	27	emphasize	emphasize	VERB
brj-25043	299	28	the	the	DET
brj-25043	299	29	potential	potential	NOUN
brj-25043	299	30	of	of	ADP
brj-25043	299	31	hybrid	hybrid	ADJ
brj-25043	299	32	ann	ann	PROPN
brj-25043	299	33	–	–	PUNCT
brj-25043	299	34	optimization	optimization	NOUN
brj-25043	299	35	frameworks	framework	NOUN
brj-25043	299	36	as	as	ADP
brj-25043	299	37	robust	robust	ADJ
brj-25043	299	38	and	and	CCONJ
brj-25043	299	39	reliable	reliable	ADJ
brj-25043	299	40	predictive	predictive	ADJ
brj-25043	299	41	tools	tool	NOUN
brj-25043	299	42	for	for	ADP
brj-25043	299	43	biogas	biogas	NOUN
brj-25043	299	44	production	production	NOUN
brj-25043	299	45	modelling	modelling	NOUN
brj-25043	299	46	.	.	PUNCT
brj-25043	300	1	peer	peer	NOUN
brj-25043	300	2	-	-	PUNCT
brj-25043	300	3	reviewed	review	VERB
brj-25043	300	4	review	review	NOUN
brj-25043	300	5	article	article	NOUN
brj-25043	300	6	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	300	7	galal	galal	PROPN
brj-25043	300	8	et	et	PROPN
brj-25043	300	9	al	al	PROPN
brj-25043	300	10	.	.	PROPN
brj-25043	301	1	(	(	PUNCT
brj-25043	301	2	2025	2025	NUM
brj-25043	301	3	)	)	PUNCT
brj-25043	301	4	.	.	PUNCT
brj-25043	302	1	“	"	PUNCT
brj-25043	302	2	math	math	NOUN
brj-25043	302	3	modeling	modeling	NOUN
brj-25043	302	4	biogas	biogas	NOUN
brj-25043	302	5	production	production	NOUN
brj-25043	302	6	,	,	PUNCT
brj-25043	302	7	”	"	PUNCT
brj-25043	302	8	bioresources	bioresource	NOUN
brj-25043	302	9	20(4	20(4	NOUN
brj-25043	302	10	)	)	PUNCT
brj-25043	302	11	,	,	PUNCT
brj-25043	302	12	11237	11237	NUM
brj-25043	302	13	-	-	SYM
brj-25043	302	14	11266	11266	NUM
brj-25043	302	15	.	.	PUNCT
brj-25043	303	1	11255	11255	NUM
brj-25043	303	2	table	table	NOUN
brj-25043	303	3	5	5	NUM
brj-25043	303	4	.	.	PUNCT
brj-25043	303	5	comparative	comparative	ADJ
brj-25043	303	6	analysis	analysis	NOUN
brj-25043	303	7	between	between	ADP
brj-25043	303	8	classical	classical	ADJ
brj-25043	303	9	and	and	CCONJ
brj-25043	303	10	ml	ml	NOUN
brj-25043	303	11	models	model	NOUN
brj-25043	303	12	’	'	PUNCT
brj-25043	303	13	performance	performance	NOUN
brj-25043	303	14	metrics	metric	NOUN
brj-25043	303	15	for	for	ADP
brj-25043	303	16	predicting	predict	VERB
brj-25043	303	17	biogas	biogas	NOUN
brj-25043	303	18	production	production	NOUN
brj-25043	303	19	from	from	ADP
brj-25043	303	20	co	co	ADJ
brj-25043	303	21	-	-	NOUN
brj-25043	303	22	digestion	digestion	NOUN
brj-25043	303	23	systems	system	NOUN
brj-25043	303	24	(	(	PUNCT
brj-25043	303	25	abdel	abdel	PROPN
brj-25043	303	26	daiem	daiem	PROPN
brj-25043	303	27	et	et	PROPN
brj-25043	303	28	al	al	PROPN
brj-25043	303	29	.	.	PROPN
brj-25043	303	30	2021	2021	NUM
brj-25043	303	31	)	)	PUNCT
brj-25043	303	32	model	model	NOUN
brj-25043	303	33	r²	r²	NOUN
brj-25043	303	34	(	(	PUNCT
brj-25043	303	35	correlation	correlation	NOUN
brj-25043	303	36	coefficient	coefficient	NOUN
brj-25043	303	37	)	)	PUNCT
brj-25043	303	38	rmse	rmse	NOUN
brj-25043	303	39	(	(	PUNCT
brj-25043	303	40	root	root	NOUN
brj-25043	303	41	mean	mean	VERB
brj-25043	303	42	square	square	NOUN
brj-25043	303	43	error	error	NOUN
brj-25043	303	44	)	)	PUNCT
brj-25043	303	45	notes	note	VERB
brj-25043	303	46	logistic	logistic	ADJ
brj-25043	303	47	kinetic	kinetic	ADJ
brj-25043	303	48	model	model	NOUN
brj-25043	303	49	0.9879	0.9879	NUM
brj-25043	303	50	1079.00	1079.00	NUM
brj-25043	303	51	best	well	ADV
brj-25043	303	52	-	-	PUNCT
brj-25043	303	53	performing	perform	VERB
brj-25043	303	54	mathematical	mathematical	ADJ
brj-25043	303	55	model	model	NOUN
brj-25043	303	56	exponential	exponential	ADJ
brj-25043	303	57	rise	rise	NOUN
brj-25043	303	58	-	-	PUNCT
brj-25043	303	59	tomaximum	tomaximum	NOUN
brj-25043	303	60	0.9753	0.9753	NUM
brj-25043	303	61	1540.00	1540.00	NUM
brj-25043	303	62	lower	low	ADJ
brj-25043	303	63	accuracy	accuracy	NOUN
brj-25043	303	64	than	than	ADP
brj-25043	303	65	logistic	logistic	ADJ
brj-25043	303	66	modified	modify	VERB
brj-25043	303	67	gompertz	gompertz	NOUN
brj-25043	303	68	0.9815	0.9815	NUM
brj-25043	303	69	1334.20	1334.20	NUM
brj-25043	303	70	good	good	ADJ
brj-25043	303	71	fit	fit	ADJ
brj-25043	303	72	but	but	CCONJ
brj-25043	303	73	less	less	ADV
brj-25043	303	74	robust	robust	ADJ
brj-25043	303	75	modified	modify	VERB
brj-25043	303	76	logistic	logistic	ADJ
brj-25043	303	77	0.9845	0.9845	PROPN
brj-25043	303	78	1221.00	1221.00	NUM
brj-25043	303	79	reliable	reliable	ADJ
brj-25043	303	80	,	,	PUNCT
brj-25043	303	81	close	close	ADJ
brj-25043	303	82	to	to	ADP
brj-25043	303	83	a	a	DET
brj-25043	303	84	logistic	logistic	ADJ
brj-25043	303	85	model	model	NOUN
brj-25043	303	86	ann	ann	PROPN
brj-25043	303	87	-	-	PUNCT
brj-25043	303	88	bp	bp	PROPN
brj-25043	303	89	(	(	PUNCT
brj-25043	303	90	back	back	NOUN
brj-25043	303	91	propagation	propagation	NOUN
brj-25043	303	92	)	)	PUNCT
brj-25043	304	1	0.8990	0.8990	NUM
brj-25043	304	2	7.20	7.20	NUM
brj-25043	304	3	acceptable	acceptable	ADJ
brj-25043	304	4	,	,	PUNCT
brj-25043	304	5	but	but	CCONJ
brj-25043	304	6	weaker	weak	ADJ
brj-25043	304	7	ann	ann	PROPN
brj-25043	304	8	-	-	PUNCT
brj-25043	304	9	ml	ml	PROPN
brj-25043	304	10	(	(	PUNCT
brj-25043	304	11	marquardtlevenberg	marquardtlevenberg	PROPN
brj-25043	304	12	)	)	PUNCT
brj-25043	304	13	0.9200	0.9200	NUM
brj-25043	304	14	3.94	3.94	NUM
brj-25043	304	15	improved	improve	VERB
brj-25043	304	16	ann	ann	PROPN
brj-25043	304	17	performance	performance	NOUN
brj-25043	304	18	ann	ann	PROPN
brj-25043	304	19	-	-	PUNCT
brj-25043	304	20	aco	aco	PROPN
brj-25043	304	21	(	(	PUNCT
brj-25043	304	22	ant	ant	ADJ
brj-25043	304	23	colony	colony	NOUN
brj-25043	304	24	optimization	optimization	NOUN
brj-25043	304	25	)	)	PUNCT
brj-25043	304	26	0.900	0.900	NUM
brj-25043	304	27	7.50	7.50	NUM
brj-25043	304	28	like	like	ADP
brj-25043	304	29	bp	bp	PROPN
brj-25043	304	30	mffnn	mffnn	PROPN
brj-25043	304	31	-	-	PUNCT
brj-25043	304	32	mfo	mfo	PROPN
brj-25043	304	33	(	(	PUNCT
brj-25043	304	34	proposed	propose	VERB
brj-25043	304	35	ann	ann	PROPN
brj-25043	304	36	with	with	ADP
brj-25043	304	37	moth	moth	NOUN
brj-25043	304	38	flame	flame	NOUN
brj-25043	304	39	optimization	optimization	NOUN
brj-25043	304	40	)	)	PUNCT
brj-25043	304	41	0.9994	0.9994	NUM
brj-25043	304	42	3.86	3.86	NUM
brj-25043	304	43	highest	high	ADJ
brj-25043	304	44	predictive	predictive	ADJ
brj-25043	304	45	accuracy	accuracy	NOUN
brj-25043	304	46	research	research	NOUN
brj-25043	304	47	gaps	gap	NOUN
brj-25043	304	48	and	and	CCONJ
brj-25043	304	49	available	available	ADJ
brj-25043	304	50	future	future	ADJ
brj-25043	304	51	extensions	extension	NOUN
brj-25043	304	52	following	follow	VERB
brj-25043	304	53	the	the	DET
brj-25043	304	54	previous	previous	ADJ
brj-25043	304	55	review	review	NOUN
brj-25043	304	56	of	of	ADP
brj-25043	304	57	the	the	DET
brj-25043	304	58	mathematical	mathematical	ADJ
brj-25043	304	59	modelling	modelling	NOUN
brj-25043	304	60	of	of	ADP
brj-25043	304	61	the	the	DET
brj-25043	304	62	ad	ad	NOUN
brj-25043	304	63	process	process	NOUN
brj-25043	304	64	,	,	PUNCT
brj-25043	304	65	some	some	DET
brj-25043	304	66	research	research	NOUN
brj-25043	304	67	gaps	gap	NOUN
brj-25043	304	68	have	have	AUX
brj-25043	304	69	arisen	arise	VERB
brj-25043	304	70	,	,	PUNCT
brj-25043	304	71	which	which	PRON
brj-25043	304	72	can	can	AUX
brj-25043	304	73	be	be	AUX
brj-25043	304	74	considered	consider	VERB
brj-25043	304	75	promising	promising	ADJ
brj-25043	304	76	candidates	candidate	NOUN
brj-25043	304	77	for	for	ADP
brj-25043	304	78	future	future	ADJ
brj-25043	304	79	extensions	extension	NOUN
brj-25043	304	80	.	.	PUNCT
brj-25043	305	1	these	these	DET
brj-25043	305	2	gaps	gap	NOUN
brj-25043	305	3	may	may	AUX
brj-25043	305	4	be	be	AUX
brj-25043	305	5	concluded	conclude	VERB
brj-25043	305	6	as	as	SCONJ
brj-25043	305	7	follows	follow	NOUN
brj-25043	305	8	.	.	PUNCT
brj-25043	306	1	future	future	ADJ
brj-25043	306	2	extensions	extension	NOUN
brj-25043	306	3	:	:	PUNCT
brj-25043	306	4	actionable	actionable	ADJ
brj-25043	306	5	directions	direction	NOUN
brj-25043	306	6	ad	ad	NOUN
brj-25043	306	7	recent	recent	ADJ
brj-25043	306	8	practice	practice	NOUN
brj-25043	306	9	in	in	ADP
brj-25043	306	10	ad	ad	NOUN
brj-25043	306	11	has	have	AUX
brj-25043	306	12	introduced	introduce	VERB
brj-25043	306	13	dosing	dosing	NOUN
brj-25043	306	14	of	of	ADP
brj-25043	306	15	conductive	conductive	ADJ
brj-25043	306	16	materials	material	NOUN
brj-25043	306	17	(	(	PUNCT
brj-25043	306	18	e.g.	e.g.	ADV
brj-25043	306	19	,	,	PUNCT
brj-25043	306	20	biochar	biochar	NOUN
brj-25043	306	21	,	,	PUNCT
brj-25043	306	22	fe₃o₄	fe₃o₄	PROPN
brj-25043	306	23	)	)	PUNCT
brj-25043	306	24	to	to	PART
brj-25043	306	25	stimulate	stimulate	VERB
brj-25043	306	26	direct	direct	ADJ
brj-25043	306	27	interspecies	interspecie	NOUN
brj-25043	306	28	electron	electron	NOUN
brj-25043	306	29	transfer	transfer	NOUN
brj-25043	306	30	(	(	PUNCT
brj-25043	306	31	diet	diet	NOUN
brj-25043	306	32	)	)	PUNCT
brj-25043	306	33	(	(	PUNCT
brj-25043	306	34	lo	lo	INTJ
brj-25043	306	35	et	et	PROPN
brj-25043	306	36	al	al	PROPN
brj-25043	306	37	.	.	PROPN
brj-25043	306	38	2010	2010	NUM
brj-25043	306	39	)	)	PUNCT
brj-25043	306	40	.	.	PUNCT
brj-25043	307	1	a	a	DET
brj-25043	307	2	natural	natural	ADJ
brj-25043	307	3	extension	extension	NOUN
brj-25043	307	4	is	be	AUX
brj-25043	307	5	to	to	PART
brj-25043	307	6	augment	augment	VERB
brj-25043	307	7	cumulative	cumulative	ADJ
brj-25043	307	8	kinetic	kinetic	NOUN
brj-25043	307	9	models	model	NOUN
brj-25043	307	10	(	(	PUNCT
brj-25043	307	11	e.g.	e.g.	ADV
brj-25043	307	12	,	,	PUNCT
brj-25043	307	13	chen	chen	PROPN
brj-25043	307	14	–	–	PUNCT
brj-25043	307	15	hashimoto	hashimoto	NOUN
brj-25043	307	16	,	,	PUNCT
brj-25043	307	17	modified	modify	VERB
brj-25043	307	18	gompertz	gompertz	NOUN
brj-25043	307	19	)	)	PUNCT
brj-25043	307	20	with	with	ADP
brj-25043	307	21	a	a	DET
brj-25043	307	22	conductivity	conductivity	NOUN
brj-25043	307	23	/	/	SYM
brj-25043	307	24	diet	diet	NOUN
brj-25043	307	25	factor	factor	NOUN
brj-25043	307	26	,	,	PUNCT
brj-25043	307	27	keff	keff	NOUN
brj-25043	307	28	=	=	SYM
brj-25043	307	29	k₀	k₀	PROPN
brj-25043	308	1	[	[	X
brj-25043	308	2	1	1	NUM
brj-25043	308	3	+	+	NUM
brj-25043	308	4	α	α	NOUN
brj-25043	308	5	φβ	φβ	NOUN
brj-25043	308	6	/	/	PUNCT
brj-25043	308	7	(	(	PUNCT
brj-25043	308	8	1	1	NUM
brj-25043	308	9	+	+	CCONJ
brj-25043	308	10	γ	γ	X
brj-25043	308	11	d	d	PROPN
brj-25043	308	12	)	)	PUNCT
brj-25043	308	13	]	]	PUNCT
brj-25043	308	14	(	(	PUNCT
brj-25043	308	15	15	15	NUM
brj-25043	308	16	)	)	PUNCT
brj-25043	308	17	where	where	SCONJ
brj-25043	308	18	ϕ	ϕ	PROPN
brj-25043	308	19	denotes	denote	VERB
brj-25043	308	20	the	the	DET
brj-25043	308	21	mass	mass	ADJ
brj-25043	308	22	fraction	fraction	NOUN
brj-25043	308	23	of	of	ADP
brj-25043	308	24	conductive	conductive	ADJ
brj-25043	308	25	additive	additive	NOUN
brj-25043	308	26	and	and	CCONJ
brj-25043	308	27	d	d	ADP
brj-25043	308	28	a	a	DET
brj-25043	308	29	representative	representative	ADJ
brj-25043	308	30	particle	particle	NOUN
brj-25043	308	31	size	size	NOUN
brj-25043	308	32	,	,	PUNCT
brj-25043	308	33	this	this	DET
brj-25043	308	34	formulation	formulation	NOUN
brj-25043	308	35	preserves	preserve	VERB
brj-25043	308	36	parameter	parameter	NOUN
brj-25043	308	37	interpretability	interpretability	NOUN
brj-25043	308	38	while	while	SCONJ
brj-25043	308	39	explicitly	explicitly	ADV
brj-25043	308	40	linking	link	VERB
brj-25043	308	41	additive	additive	NOUN
brj-25043	308	42	dosing	dose	VERB
brj-25043	308	43	to	to	ADP
brj-25043	308	44	performance	performance	NOUN
brj-25043	308	45	.	.	PUNCT
brj-25043	309	1	calibration	calibration	NOUN
brj-25043	309	2	requires	require	VERB
brj-25043	309	3	only	only	ADV
brj-25043	309	4	routine	routine	ADJ
brj-25043	309	5	operational	operational	ADJ
brj-25043	309	6	data	datum	NOUN
brj-25043	309	7	(	(	PUNCT
brj-25043	309	8	biogas	biogas	NOUN
brj-25043	309	9	rate	rate	NOUN
brj-25043	309	10	,	,	PUNCT
brj-25043	309	11	temperature	temperature	NOUN
brj-25043	309	12	)	)	PUNCT
brj-25043	309	13	supplemented	supplement	VERB
brj-25043	309	14	with	with	ADP
brj-25043	309	15	two	two	NUM
brj-25043	309	16	readily	readily	ADV
brj-25043	309	17	available	available	ADJ
brj-25043	309	18	proxies	proxy	NOUN
brj-25043	309	19	:	:	PUNCT
brj-25043	309	20	oxidation	oxidation	NOUN
brj-25043	309	21	,	,	PUNCT
brj-25043	309	22	reduction	reduction	NOUN
brj-25043	309	23	potential	potential	NOUN
brj-25043	309	24	,	,	PUNCT
brj-25043	309	25	and	and	CCONJ
brj-25043	309	26	slurry	slurry	NOUN
brj-25043	309	27	conductivity	conductivity	NOUN
brj-25043	309	28	.	.	PUNCT
brj-25043	310	1	toxic	toxic	ADJ
brj-25043	310	2	inhibition	inhibition	NOUN
brj-25043	310	3	(	(	PUNCT
brj-25043	310	4	e.g.	e.g.	ADV
brj-25043	310	5	,	,	PUNCT
brj-25043	310	6	free	free	ADJ
brj-25043	310	7	nh₃	nh₃	PROPN
brj-25043	310	8	,	,	PUNCT
brj-25043	310	9	sulfide	sulfide	NOUN
brj-25043	310	10	,	,	PUNCT
brj-25043	310	11	lcfa	lcfa	NOUN
brj-25043	310	12	)	)	PUNCT
brj-25043	310	13	can	can	AUX
brj-25043	310	14	be	be	AUX
brj-25043	310	15	included	include	VERB
brj-25043	310	16	multiplicatively	multiplicatively	ADV
brj-25043	310	17	via	via	ADP
brj-25043	310	18	haldane	haldane	NOUN
brj-25043	310	19	-	-	PUNCT
brj-25043	310	20	type	type	NOUN
brj-25043	310	21	terms	term	NOUN
brj-25043	310	22	,	,	PUNCT
brj-25043	310	23	allowing	allow	VERB
brj-25043	310	24	operators	operator	NOUN
brj-25043	310	25	to	to	PART
brj-25043	310	26	evaluate	evaluate	VERB
brj-25043	310	27	when	when	SCONJ
brj-25043	310	28	inhibitory	inhibitory	ADJ
brj-25043	310	29	effects	effect	NOUN
brj-25043	310	30	offset	offset	VERB
brj-25043	310	31	diet	diet	NOUN
brj-25043	310	32	benefits	benefit	NOUN
brj-25043	310	33	and	and	CCONJ
brj-25043	310	34	to	to	PART
brj-25043	310	35	adjust	adjust	VERB
brj-25043	310	36	set	set	ADJ
brj-25043	310	37	-	-	PUNCT
brj-25043	310	38	points	point	NOUN
brj-25043	310	39	accordingly	accordingly	ADV
brj-25043	310	40	(	(	PUNCT
brj-25043	310	41	lo	lo	INTJ
brj-25043	310	42	et	et	PROPN
brj-25043	310	43	al	al	PROPN
brj-25043	310	44	.	.	PROPN
brj-25043	310	45	2010	2010	NUM
brj-25043	310	46	)	)	PUNCT
brj-25043	310	47	.	.	PUNCT
brj-25043	311	1	for	for	ADP
brj-25043	311	2	control	control	NOUN
brj-25043	311	3	-	-	PUNCT
brj-25043	311	4	oriented	orient	VERB
brj-25043	311	5	applications	application	NOUN
brj-25043	311	6	,	,	PUNCT
brj-25043	311	7	the	the	DET
brj-25043	311	8	process	process	NOUN
brj-25043	311	9	can	can	AUX
brj-25043	311	10	be	be	AUX
brj-25043	311	11	represented	represent	VERB
brj-25043	311	12	by	by	ADP
brj-25043	311	13	two	two	NUM
brj-25043	311	14	coupled	couple	VERB
brj-25043	311	15	states	state	NOUN
brj-25043	311	16	,	,	PUNCT
brj-25043	311	17	hydrolysis	hydrolysis	NOUN
brj-25043	311	18	/	/	SYM
brj-25043	311	19	acidogenesis	acidogenesi	NOUN
brj-25043	311	20	and	and	CCONJ
brj-25043	311	21	methanogenesis	methanogenesis	NOUN
brj-25043	311	22	,	,	PUNCT
brj-25043	311	23	driven	drive	VERB
brj-25043	311	24	by	by	ADP
brj-25043	311	25	measurable	measurable	ADJ
brj-25043	311	26	or	or	CCONJ
brj-25043	311	27	soft	soft	ADJ
brj-25043	311	28	-	-	PUNCT
brj-25043	311	29	sensed	sense	VERB
brj-25043	311	30	variables	variable	NOUN
brj-25043	311	31	.	.	PUNCT
brj-25043	312	1	the	the	DET
brj-25043	312	2	following	follow	VERB
brj-25043	312	3	equations	equation	NOUN
brj-25043	312	4	define	define	VERB
brj-25043	312	5	a	a	DET
brj-25043	312	6	minimal	minimal	ADJ
brj-25043	312	7	state	state	NOUN
brj-25043	312	8	-	-	PUNCT
brj-25043	312	9	space	space	NOUN
brj-25043	312	10	model	model	NOUN
brj-25043	312	11	,	,	PUNCT
brj-25043	312	12	x	x	X
brj-25043	313	1	=	=	PUNCT
brj-25043	314	1	[	[	X
brj-25043	314	2	s_vfa	s_vfa	PROPN
brj-25043	314	3	,	,	PUNCT
brj-25043	314	4	x_meth	x_meth	PROPN
brj-25043	314	5	]	]	X
brj-25043	314	6	(	(	PUNCT
brj-25043	314	7	16	16	NUM
brj-25043	314	8	)	)	PUNCT
brj-25043	314	9	ẋ	ẋ	PUNCT
brj-25043	315	1	=	=	SYM
brj-25043	315	2	f(x	f(x	PROPN
brj-25043	315	3	,	,	PUNCT
brj-25043	315	4	olr	olr	PROPN
brj-25043	315	5	,	,	PUNCT
brj-25043	315	6	t	t	PROPN
brj-25043	315	7	,	,	PUNCT
brj-25043	315	8	ph	ph	PROPN
brj-25043	315	9	)	)	PUNCT
brj-25043	315	10	,	,	PUNCT
brj-25043	315	11	(	(	PUNCT
brj-25043	315	12	17	17	X
brj-25043	315	13	)	)	PUNCT
brj-25043	315	14	peer	peer	NOUN
brj-25043	315	15	-	-	PUNCT
brj-25043	315	16	reviewed	review	VERB
brj-25043	315	17	review	review	NOUN
brj-25043	315	18	article	article	NOUN
brj-25043	315	19	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	315	20	galal	galal	PROPN
brj-25043	315	21	et	et	PROPN
brj-25043	315	22	al	al	PROPN
brj-25043	315	23	.	.	PROPN
brj-25043	315	24	(	(	PUNCT
brj-25043	315	25	2025	2025	NUM
brj-25043	315	26	)	)	PUNCT
brj-25043	315	27	.	.	PUNCT
brj-25043	316	1	“	"	PUNCT
brj-25043	316	2	math	math	NOUN
brj-25043	316	3	modeling	modeling	NOUN
brj-25043	316	4	biogas	biogas	NOUN
brj-25043	316	5	production	production	NOUN
brj-25043	316	6	,	,	PUNCT
brj-25043	316	7	”	"	PUNCT
brj-25043	316	8	bioresources	bioresource	NOUN
brj-25043	316	9	20(4	20(4	NOUN
brj-25043	316	10	)	)	PUNCT
brj-25043	316	11	,	,	PUNCT
brj-25043	316	12	11237	11237	NUM
brj-25043	316	13	-	-	SYM
brj-25043	316	14	11266	11266	NUM
brj-25043	316	15	.	.	PUNCT
brj-25043	317	1	11256	11256	NUM
brj-25043	317	2	with	with	ADP
brj-25043	317	3	outputs	output	NOUN
brj-25043	317	4	including	include	VERB
brj-25043	317	5	biogas	biogas	NOUN
brj-25043	317	6	flow	flow	NOUN
brj-25043	317	7	and	and	CCONJ
brj-25043	317	8	a	a	DET
brj-25043	317	9	soft	soft	ADJ
brj-25043	317	10	vfa	vfa	PROPN
brj-25043	317	11	/	/	SYM
brj-25043	317	12	alk	alk	PROPN
brj-25043	317	13	indicator	indicator	NOUN
brj-25043	317	14	derived	derive	VERB
brj-25043	317	15	from	from	ADP
brj-25043	317	16	ph	ph	VERB
brj-25043	317	17	,	,	PUNCT
brj-25043	317	18	alkalinity	alkalinity	NOUN
brj-25043	317	19	,	,	PUNCT
brj-25043	317	20	and	and	CCONJ
brj-25043	317	21	gas	gas	NOUN
brj-25043	317	22	rate	rate	NOUN
brj-25043	317	23	.	.	PUNCT
brj-25043	318	1	an	an	DET
brj-25043	318	2	extended	extended	ADJ
brj-25043	318	3	kalman	kalman	NOUN
brj-25043	318	4	filter	filter	NOUN
brj-25043	318	5	or	or	CCONJ
brj-25043	318	6	moving	move	VERB
brj-25043	318	7	-	-	PUNCT
brj-25043	318	8	horizon	horizon	NOUN
brj-25043	318	9	estimator	estimator	NOUN
brj-25043	318	10	can	can	AUX
brj-25043	318	11	integrate	integrate	VERB
brj-25043	318	12	scada	scada	PROPN
brj-25043	318	13	data	data	PROPN
brj-25043	318	14	with	with	ADP
brj-25043	318	15	the	the	DET
brj-25043	318	16	soft	soft	ADJ
brj-25043	318	17	sensor	sensor	NOUN
brj-25043	318	18	to	to	PART
brj-25043	318	19	reconstruct	reconstruct	VERB
brj-25043	318	20	unmeasured	unmeasured	ADJ
brj-25043	318	21	states	state	NOUN
brj-25043	318	22	and	and	CCONJ
brj-25043	318	23	provide	provide	VERB
brj-25043	318	24	(	(	PUNCT
brj-25043	318	25	1	1	NUM
brj-25043	318	26	to	to	PART
brj-25043	318	27	3	3	NUM
brj-25043	318	28	)	)	PUNCT
brj-25043	318	29	day	day	NOUN
brj-25043	318	30	acidification	acidification	NOUN
brj-25043	318	31	risk	risk	NOUN
brj-25043	318	32	bands	band	NOUN
brj-25043	318	33	,	,	PUNCT
brj-25043	318	34	enabling	enable	VERB
brj-25043	318	35	operators	operator	NOUN
brj-25043	318	36	to	to	PART
brj-25043	318	37	connect	connect	VERB
brj-25043	318	38	forecasts	forecast	NOUN
brj-25043	318	39	to	to	ADP
brj-25043	318	40	actionable	actionable	ADJ
brj-25043	318	41	levers	lever	NOUN
brj-25043	318	42	(	(	PUNCT
brj-25043	318	43	e.g.	e.g.	ADV
brj-25043	318	44	,	,	PUNCT
brj-25043	318	45	olr	olr	NOUN
brj-25043	318	46	ramping	ramp	VERB
brj-25043	318	47	,	,	PUNCT
brj-25043	318	48	temporary	temporary	ADJ
brj-25043	318	49	set	set	NOUN
brj-25043	318	50	-	-	PUNCT
brj-25043	318	51	point	point	NOUN
brj-25043	318	52	changes	change	NOUN
brj-25043	318	53	,	,	PUNCT
brj-25043	318	54	co	co	ADJ
brj-25043	318	55	-	-	NOUN
brj-25043	318	56	substrate	substrate	ADJ
brj-25043	318	57	throttling	throttling	NOUN
brj-25043	318	58	)	)	PUNCT
brj-25043	318	59	(	(	PUNCT
brj-25043	318	60	schroer	schroer	NOUN
brj-25043	318	61	and	and	CCONJ
brj-25043	318	62	just	just	ADV
brj-25043	318	63	2023	2023	NUM
brj-25043	318	64	)	)	PUNCT
brj-25043	318	65	.	.	PUNCT
brj-25043	319	1	given	give	VERB
brj-25043	319	2	the	the	DET
brj-25043	319	3	prevalence	prevalence	NOUN
brj-25043	319	4	of	of	ADP
brj-25043	319	5	small	small	ADJ
brj-25043	319	6	,	,	PUNCT
brj-25043	319	7	noisy	noisy	ADJ
brj-25043	319	8	datasets	dataset	NOUN
brj-25043	319	9	,	,	PUNCT
brj-25043	319	10	plant	plant	NOUN
brj-25043	319	11	-	-	PUNCT
brj-25043	319	12	level	level	NOUN
brj-25043	319	13	kinetic	kinetic	NOUN
brj-25043	319	14	parameters	parameter	NOUN
brj-25043	319	15	should	should	AUX
brj-25043	319	16	be	be	AUX
brj-25043	319	17	treated	treat	VERB
brj-25043	319	18	as	as	ADP
brj-25043	319	19	random	random	ADJ
brj-25043	319	20	effects	effect	NOUN
brj-25043	319	21	,	,	PUNCT
brj-25043	319	22	e.g.	e.g.	ADV
brj-25043	319	23	,	,	PUNCT
brj-25043	319	24	(	(	PUNCT
brj-25043	319	25	a	a	PRON
brj-25043	319	26	,	,	PUNCT
brj-25043	319	27	λ	λ	NOUN
brj-25043	319	28	,	,	PUNCT
brj-25043	319	29	dm)_j	dm)_j	PUNCT
brj-25043	319	30	~	~	PUNCT
brj-25043	319	31	n(μ	n(μ	NUM
brj-25043	319	32	,	,	PUNCT
brj-25043	319	33	σ	σ	PROPN
brj-25043	319	34	)	)	PUNCT
brj-25043	319	35	for	for	ADP
brj-25043	319	36	plant	plant	NOUN
brj-25043	319	37	j.	j.	PROPN
brj-25043	319	38	partial	partial	ADJ
brj-25043	319	39	pooling	pooling	NOUN
brj-25043	319	40	stabilizes	stabilize	VERB
brj-25043	319	41	estimates	estimate	NOUN
brj-25043	319	42	in	in	ADP
brj-25043	319	43	data	data	NOUN
brj-25043	319	44	-	-	PUNCT
brj-25043	319	45	scarce	scarce	NOUN
brj-25043	319	46	settings	setting	NOUN
brj-25043	319	47	while	while	SCONJ
brj-25043	319	48	retaining	retain	VERB
brj-25043	319	49	site	site	NOUN
brj-25043	319	50	-	-	PUNCT
brj-25043	319	51	specific	specific	ADJ
brj-25043	319	52	behaviour	behaviour	NOUN
brj-25043	319	53	.	.	PUNCT
brj-25043	320	1	multi	multi	ADJ
brj-25043	320	2	-	-	NOUN
brj-25043	320	3	facility	facility	NOUN
brj-25043	320	4	fitting	fitting	ADJ
brj-25043	320	5	with	with	ADP
brj-25043	320	6	leave	leave	VERB
brj-25043	320	7	-	-	PUNCT
brj-25043	320	8	one	one	NUM
brj-25043	320	9	-	-	PUNCT
brj-25043	320	10	plant	plant	NOUN
brj-25043	320	11	-	-	PUNCT
brj-25043	320	12	out	out	ADP
brj-25043	320	13	validation	validation	NOUN
brj-25043	320	14	quantifies	quantifie	NOUN
brj-25043	320	15	transferability	transferability	NOUN
brj-25043	320	16	,	,	PUNCT
brj-25043	320	17	producing	produce	VERB
brj-25043	320	18	plantspecific	plantspecific	ADJ
brj-25043	320	19	posterior	posterior	ADJ
brj-25043	320	20	distributions	distribution	NOUN
brj-25043	320	21	with	with	ADP
brj-25043	320	22	credible	credible	ADJ
brj-25043	320	23	intervals	interval	NOUN
brj-25043	320	24	.	.	PUNCT
brj-25043	321	1	these	these	PRON
brj-25043	321	2	can	can	AUX
brj-25043	321	3	be	be	AUX
brj-25043	321	4	propagated	propagate	VERB
brj-25043	321	5	into	into	ADP
brj-25043	321	6	riskaware	riskaware	NOUN
brj-25043	321	7	dashboards	dashboard	NOUN
brj-25043	321	8	and	and	CCONJ
brj-25043	321	9	sustainability	sustainability	NOUN
brj-25043	321	10	kpis	kpis	PROPN
brj-25043	321	11	(	(	PUNCT
brj-25043	321	12	e.g.	e.g.	ADV
brj-25043	321	13	,	,	PUNCT
brj-25043	321	14	gwp	gwp	PROPN
brj-25043	321	15	per	per	ADP
brj-25043	321	16	kwh	kwh	PROPN
brj-25043	321	17	,	,	PUNCT
brj-25043	321	18	lcoe	lcoe	ADJ
brj-25043	321	19	)	)	PUNCT
brj-25043	321	20	,	,	PUNCT
brj-25043	321	21	ensuring	ensure	VERB
brj-25043	321	22	that	that	SCONJ
brj-25043	321	23	uncertainty	uncertainty	NOUN
brj-25043	321	24	is	be	AUX
brj-25043	321	25	explicitly	explicitly	ADV
brj-25043	321	26	visible	visible	ADJ
brj-25043	321	27	in	in	ADP
brj-25043	321	28	decision	decision	NOUN
brj-25043	321	29	-	-	PUNCT
brj-25043	321	30	making	making	NOUN
brj-25043	321	31	(	(	PUNCT
brj-25043	321	32	gala	gala	NOUN
brj-25043	321	33	2021	2021	NUM
brj-25043	321	34	)	)	PUNCT
brj-25043	321	35	.	.	PUNCT
brj-25043	322	1	for	for	ADP
brj-25043	322	2	forecasting	forecast	VERB
brj-25043	322	3	with	with	ADP
brj-25043	322	4	treeor	treeor	NOUN
brj-25043	322	5	sequence	sequence	NOUN
brj-25043	322	6	-	-	PUNCT
brj-25043	322	7	based	base	VERB
brj-25043	322	8	ml	ml	NOUN
brj-25043	322	9	models	model	NOUN
brj-25043	322	10	,	,	PUNCT
brj-25043	322	11	embedding	embed	VERB
brj-25043	322	12	domain	domain	NOUN
brj-25043	322	13	constraints	constraint	NOUN
brj-25043	322	14	is	be	AUX
brj-25043	322	15	essential	essential	ADJ
brj-25043	322	16	:	:	PUNCT
brj-25043	322	17	monotonicity	monotonicity	NOUN
brj-25043	322	18	of	of	ADP
brj-25043	322	19	biogas	biogas	NOUN
brj-25043	322	20	rate	rate	NOUN
brj-25043	322	21	with	with	ADP
brj-25043	322	22	olr	olr	NOUN
brj-25043	322	23	(	(	PUNCT
brj-25043	322	24	within	within	ADP
brj-25043	322	25	safe	safe	ADJ
brj-25043	322	26	ranges	range	NOUN
brj-25043	322	27	)	)	PUNCT
brj-25043	322	28	,	,	PUNCT
brj-25043	322	29	positive	positive	ADJ
brj-25043	322	30	correlation	correlation	NOUN
brj-25043	322	31	of	of	ADP
brj-25043	322	32	vfa	vfa	PROPN
brj-25043	322	33	with	with	ADP
brj-25043	322	34	olr	olr	NOUN
brj-25043	322	35	,	,	PUNCT
brj-25043	322	36	and	and	CCONJ
brj-25043	322	37	soft	soft	ADJ
brj-25043	322	38	penalties	penalty	NOUN
brj-25043	322	39	for	for	ADP
brj-25043	322	40	mass	mass	ADJ
brj-25043	322	41	-	-	PUNCT
brj-25043	322	42	balance	balance	NOUN
brj-25043	322	43	violations	violation	NOUN
brj-25043	322	44	.	.	PUNCT
brj-25043	323	1	residualbased	residualbase	VERB
brj-25043	323	2	change	change	NOUN
brj-25043	323	3	-	-	PUNCT
brj-25043	323	4	point	point	NOUN
brj-25043	323	5	detection	detection	NOUN
brj-25043	323	6	(	(	PUNCT
brj-25043	323	7	e.g.	e.g.	ADV
brj-25043	323	8	,	,	PUNCT
brj-25043	323	9	cusum	cusum	NOUN
brj-25043	323	10	,	,	PUNCT
brj-25043	323	11	bayesian	bayesian	NOUN
brj-25043	323	12	online	online	ADJ
brj-25043	323	13	methods	method	NOUN
brj-25043	323	14	)	)	PUNCT
brj-25043	323	15	can	can	AUX
brj-25043	323	16	flag	flag	VERB
brj-25043	323	17	operational	operational	ADJ
brj-25043	323	18	regime	regime	NOUN
brj-25043	323	19	shifts	shift	NOUN
brj-25043	323	20	(	(	PUNCT
brj-25043	323	21	feedstock	feedstock	NOUN
brj-25043	323	22	change	change	NOUN
brj-25043	323	23	,	,	PUNCT
brj-25043	323	24	mixer	mixer	NOUN
brj-25043	323	25	outage	outage	NOUN
brj-25043	323	26	)	)	PUNCT
brj-25043	323	27	.	.	PUNCT
brj-25043	324	1	these	these	DET
brj-25043	324	2	triggers	trigger	NOUN
brj-25043	324	3	initiate	initiate	VERB
brj-25043	324	4	lightweight	lightweight	ADJ
brj-25043	324	5	re	re	NOUN
brj-25043	324	6	-	-	NOUN
brj-25043	324	7	tuning	tune	VERB
brj-25043	324	8	and	and	CCONJ
brj-25043	324	9	widen	widen	VERB
brj-25043	324	10	predictive	predictive	ADJ
brj-25043	324	11	intervals	interval	NOUN
brj-25043	324	12	,	,	PUNCT
brj-25043	324	13	transforming	transform	VERB
brj-25043	324	14	ml	ml	ADP
brj-25043	324	15	from	from	ADP
brj-25043	324	16	a	a	DET
brj-25043	324	17	static	static	ADJ
brj-25043	324	18	predictor	predictor	NOUN
brj-25043	324	19	into	into	ADP
brj-25043	324	20	an	an	DET
brj-25043	324	21	operator	operator	NOUN
brj-25043	324	22	-	-	PUNCT
brj-25043	324	23	safe	safe	ADJ
brj-25043	324	24	assistant	assistant	NOUN
brj-25043	324	25	(	(	PUNCT
brj-25043	324	26	ling	ling	NOUN
brj-25043	324	27	et	et	PROPN
brj-25043	324	28	al	al	PROPN
brj-25043	324	29	.	.	PROPN
brj-25043	324	30	2024	2024	NUM
brj-25043	324	31	)	)	PUNCT
brj-25043	324	32	.	.	PUNCT
brj-25043	325	1	finally	finally	ADV
brj-25043	325	2	,	,	PUNCT
brj-25043	325	3	the	the	DET
brj-25043	325	4	experimental	experimental	ADJ
brj-25043	325	5	design	design	NOUN
brj-25043	325	6	can	can	AUX
brj-25043	325	7	be	be	AUX
brj-25043	325	8	optimized	optimize	VERB
brj-25043	325	9	to	to	PART
brj-25043	325	10	reduce	reduce	VERB
brj-25043	325	11	the	the	DET
brj-25043	325	12	cost	cost	NOUN
brj-25043	325	13	of	of	ADP
brj-25043	325	14	bmp	bmp	NOUN
brj-25043	325	15	and	and	CCONJ
brj-25043	325	16	pilot	pilot	NOUN
brj-25043	325	17	trials	trial	NOUN
brj-25043	325	18	.	.	PUNCT
brj-25043	326	1	starting	start	VERB
brj-25043	326	2	from	from	ADP
brj-25043	326	3	a	a	DET
brj-25043	326	4	latin	latin	ADJ
brj-25043	326	5	-	-	PUNCT
brj-25043	326	6	hypercube	hypercube	NOUN
brj-25043	326	7	of	of	ADP
brj-25043	326	8	feed	feed	NOUN
brj-25043	326	9	ratios	ratio	NOUN
brj-25043	326	10	and	and	CCONJ
brj-25043	326	11	pre	pre	NOUN
brj-25043	326	12	-	-	NOUN
brj-25043	326	13	treatments	treatment	NOUN
brj-25043	326	14	,	,	PUNCT
brj-25043	326	15	cumulative	cumulative	ADJ
brj-25043	326	16	or	or	CCONJ
brj-25043	326	17	hybrid	hybrid	NOUN
brj-25043	326	18	models	model	NOUN
brj-25043	326	19	are	be	AUX
brj-25043	326	20	fitted	fit	VERB
brj-25043	326	21	,	,	PUNCT
brj-25043	326	22	and	and	CCONJ
brj-25043	326	23	the	the	DET
brj-25043	326	24	next	next	ADJ
brj-25043	326	25	experimental	experimental	ADJ
brj-25043	326	26	point	point	NOUN
brj-25043	326	27	is	be	AUX
brj-25043	326	28	selected	select	VERB
brj-25043	326	29	by	by	ADP
brj-25043	326	30	maximizing	maximize	VERB
brj-25043	326	31	expected	expect	VERB
brj-25043	326	32	reduction	reduction	NOUN
brj-25043	326	33	in	in	ADP
brj-25043	326	34	parameter	parameter	NOUN
brj-25043	326	35	uncertainty	uncertainty	NOUN
brj-25043	326	36	under	under	ADP
brj-25043	326	37	safety	safety	NOUN
brj-25043	326	38	constraints	constraint	NOUN
brj-25043	326	39	(	(	PUNCT
brj-25043	326	40	e.g.	e.g.	ADV
brj-25043	326	41	,	,	PUNCT
brj-25043	326	42	vfa	vfa	PROPN
brj-25043	326	43	/	/	SYM
brj-25043	326	44	alk	alk	VERB
brj-25043	326	45	≤	≤	NUM
brj-25043	326	46	threshold	threshold	NOUN
brj-25043	326	47	)	)	PUNCT
brj-25043	326	48	.	.	PUNCT
brj-25043	327	1	this	this	DET
brj-25043	327	2	adaptive	adaptive	ADJ
brj-25043	327	3	loop	loop	NOUN
brj-25043	327	4	accelerates	accelerate	VERB
brj-25043	327	5	the	the	DET
brj-25043	327	6	development	development	NOUN
brj-25043	327	7	of	of	ADP
brj-25043	327	8	decision	decision	NOUN
brj-25043	327	9	-	-	PUNCT
brj-25043	327	10	quality	quality	NOUN
brj-25043	327	11	models	model	NOUN
brj-25043	327	12	for	for	ADP
brj-25043	327	13	novel	novel	ADJ
brj-25043	327	14	feedstock	feedstock	NOUN
brj-25043	327	15	mixtures	mixture	NOUN
brj-25043	327	16	while	while	SCONJ
brj-25043	327	17	minimizing	minimize	VERB
brj-25043	327	18	resource	resource	NOUN
brj-25043	327	19	requirements	requirement	NOUN
brj-25043	327	20	(	(	PUNCT
brj-25043	327	21	tiwari	tiwari	X
brj-25043	327	22	et	et	PROPN
brj-25043	327	23	al	al	PROPN
brj-25043	327	24	.	.	PROPN
brj-25043	327	25	2025	2025	NUM
brj-25043	327	26	)	)	PUNCT
brj-25043	327	27	.	.	PUNCT
brj-25043	328	1	incorporating	incorporate	VERB
brj-25043	328	2	parameter	parameter	NOUN
brj-25043	328	3	uncertainty	uncertainty	NOUN
brj-25043	328	4	estimating	estimate	VERB
brj-25043	328	5	the	the	DET
brj-25043	328	6	model	model	NOUN
brj-25043	328	7	parameters	parameter	NOUN
brj-25043	328	8	is	be	AUX
brj-25043	328	9	one	one	NUM
brj-25043	328	10	of	of	ADP
brj-25043	328	11	the	the	DET
brj-25043	328	12	main	main	ADJ
brj-25043	328	13	objectives	objective	NOUN
brj-25043	328	14	when	when	SCONJ
brj-25043	328	15	simulating	simulate	VERB
brj-25043	328	16	biogas	biogas	NOUN
brj-25043	328	17	production	production	NOUN
brj-25043	328	18	over	over	ADP
brj-25043	328	19	the	the	DET
brj-25043	328	20	ad	ad	NOUN
brj-25043	328	21	process	process	NOUN
brj-25043	328	22	using	use	VERB
brj-25043	328	23	mathematical	mathematical	ADJ
brj-25043	328	24	modelling	modelling	NOUN
brj-25043	328	25	.	.	PUNCT
brj-25043	329	1	however	however	ADV
brj-25043	329	2	,	,	PUNCT
brj-25043	329	3	if	if	SCONJ
brj-25043	329	4	the	the	DET
brj-25043	329	5	same	same	ADJ
brj-25043	329	6	ad	ad	NOUN
brj-25043	329	7	process	process	NOUN
brj-25043	329	8	has	have	AUX
brj-25043	329	9	been	be	AUX
brj-25043	329	10	repeated	repeat	VERB
brj-25043	329	11	enough	enough	ADJ
brj-25043	329	12	times	time	NOUN
brj-25043	329	13	,	,	PUNCT
brj-25043	329	14	these	these	DET
brj-25043	329	15	parameters	parameter	NOUN
brj-25043	329	16	are	be	AUX
brj-25043	329	17	expected	expect	VERB
brj-25043	329	18	to	to	PART
brj-25043	329	19	vary	vary	VERB
brj-25043	329	20	slightly	slightly	ADV
brj-25043	329	21	from	from	ADP
brj-25043	329	22	time	time	NOUN
brj-25043	329	23	to	to	ADP
brj-25043	329	24	time	time	NOUN
brj-25043	329	25	.	.	PUNCT
brj-25043	330	1	few	few	ADJ
brj-25043	330	2	studies	study	NOUN
brj-25043	330	3	estimated	estimate	VERB
brj-25043	330	4	the	the	DET
brj-25043	330	5	ranges	range	NOUN
brj-25043	330	6	of	of	ADP
brj-25043	330	7	some	some	DET
brj-25043	330	8	model	model	NOUN
brj-25043	330	9	parameters	parameter	NOUN
brj-25043	330	10	to	to	PART
brj-25043	330	11	investigate	investigate	VERB
brj-25043	330	12	their	their	PRON
brj-25043	330	13	variations	variation	NOUN
brj-25043	330	14	.	.	PUNCT
brj-25043	331	1	for	for	ADP
brj-25043	331	2	example	example	NOUN
brj-25043	331	3	,	,	PUNCT
brj-25043	331	4	kumar	kumar	PROPN
brj-25043	331	5	et	et	PROPN
brj-25043	331	6	al	al	PROPN
brj-25043	331	7	.	.	PROPN
brj-25043	332	1	(	(	PUNCT
brj-25043	332	2	2004	2004	NUM
brj-25043	332	3	)	)	PUNCT
brj-25043	332	4	achieved	achieve	VERB
brj-25043	332	5	a	a	DET
brj-25043	332	6	qualitative	qualitative	ADJ
brj-25043	332	7	assessment	assessment	NOUN
brj-25043	332	8	study	study	NOUN
brj-25043	332	9	of	of	ADP
brj-25043	332	10	different	different	ADJ
brj-25043	332	11	methane	methane	NOUN
brj-25043	332	12	emission	emission	NOUN
brj-25043	332	13	data	datum	NOUN
brj-25043	332	14	using	use	VERB
brj-25043	332	15	municipal	municipal	ADJ
brj-25043	332	16	solid	solid	ADJ
brj-25043	332	17	waste	waste	NOUN
brj-25043	332	18	disposal	disposal	NOUN
brj-25043	332	19	sites	site	NOUN
brj-25043	332	20	;	;	PUNCT
brj-25043	332	21	danner	danner	NOUN
brj-25043	332	22	(	(	PUNCT
brj-25043	332	23	2006	2006	NUM
brj-25043	332	24	)	)	PUNCT
brj-25043	332	25	considered	consider	VERB
brj-25043	332	26	the	the	DET
brj-25043	332	27	parameter	parameter	NOUN
brj-25043	332	28	uncertainty	uncertainty	NOUN
brj-25043	332	29	for	for	ADP
brj-25043	332	30	some	some	PRON
brj-25043	332	31	of	of	ADP
brj-25043	332	32	the	the	DET
brj-25043	332	33	growth	growth	NOUN
brj-25043	332	34	models	model	NOUN
brj-25043	332	35	;	;	PUNCT
brj-25043	332	36	budiyono	budiyono	NOUN
brj-25043	332	37	et	et	PROPN
brj-25043	332	38	al	al	PROPN
brj-25043	332	39	.	.	PROPN
brj-25043	333	1	(	(	PUNCT
brj-25043	333	2	2010	2010	NUM
brj-25043	333	3	)	)	PUNCT
brj-25043	333	4	estimated	estimate	VERB
brj-25043	333	5	the	the	DET
brj-25043	333	6	parameters	parameter	NOUN
brj-25043	333	7	'	'	PART
brj-25043	333	8	ranges	range	NOUN
brj-25043	333	9	in	in	ADP
brj-25043	333	10	the	the	DET
brj-25043	333	11	modified	modify	VERB
brj-25043	333	12	gompertz	gompertz	NOUN
brj-25043	333	13	equation	equation	NOUN
brj-25043	333	14	that	that	PRON
brj-25043	333	15	was	be	AUX
brj-25043	333	16	used	use	VERB
brj-25043	333	17	to	to	PART
brj-25043	333	18	simulate	simulate	VERB
brj-25043	333	19	the	the	DET
brj-25043	333	20	biogas	biogas	NOUN
brj-25043	333	21	production	production	NOUN
brj-25043	333	22	resulting	result	VERB
brj-25043	333	23	from	from	ADP
brj-25043	333	24	cattle	cattle	NOUN
brj-25043	333	25	manure	manure	NOUN
brj-25043	333	26	.	.	PUNCT
brj-25043	334	1	mathematically	mathematically	ADV
brj-25043	334	2	,	,	PUNCT
brj-25043	334	3	to	to	PART
brj-25043	334	4	express	express	VERB
brj-25043	334	5	these	these	DET
brj-25043	334	6	parameters	parameter	NOUN
brj-25043	334	7	more	more	ADV
brj-25043	334	8	accurately	accurately	ADV
brj-25043	334	9	,	,	PUNCT
brj-25043	334	10	they	they	PRON
brj-25043	334	11	may	may	AUX
brj-25043	334	12	be	be	AUX
brj-25043	334	13	described	describe	VERB
brj-25043	334	14	as	as	ADP
brj-25043	334	15	random	random	ADJ
brj-25043	334	16	variables	variable	NOUN
brj-25043	334	17	rather	rather	ADV
brj-25043	334	18	than	than	ADP
brj-25043	334	19	deterministic	deterministic	ADJ
brj-25043	334	20	ones	one	NOUN
brj-25043	334	21	.	.	PUNCT
brj-25043	335	1	in	in	ADP
brj-25043	335	2	such	such	DET
brj-25043	335	3	a	a	DET
brj-25043	335	4	case	case	NOUN
brj-25043	335	5	,	,	PUNCT
brj-25043	335	6	a	a	DET
brj-25043	335	7	general	general	ADJ
brj-25043	335	8	parameter	parameter	NOUN
brj-25043	335	9	,	,	PUNCT
brj-25043	335	10	𝛾	𝛾	PROPN
brj-25043	335	11	,	,	PUNCT
brj-25043	335	12	can	can	AUX
brj-25043	335	13	be	be	AUX
brj-25043	335	14	expressed	express	VERB
brj-25043	335	15	by	by	ADP
brj-25043	335	16	the	the	DET
brj-25043	335	17	following	follow	VERB
brj-25043	335	18	equation	equation	NOUN
brj-25043	335	19	(	(	PUNCT
brj-25043	335	20	ghanem	ghanem	PROPN
brj-25043	335	21	and	and	CCONJ
brj-25043	335	22	spanos	spano	NOUN
brj-25043	335	23	2003	2003	NUM
brj-25043	335	24	)	)	PUNCT
brj-25043	335	25	,	,	PUNCT
brj-25043	335	26	𝛾(𝜃	𝛾(𝜃	PROPN
brj-25043	335	27	)	)	PUNCT
brj-25043	335	28	=	=	SYM
brj-25043	335	29	𝛾(1	𝛾(1	NOUN
brj-25043	335	30	+	+	CCONJ
brj-25043	335	31	𝜀𝛾	𝜀𝛾	X
brj-25043	335	32	𝜉(𝜃	𝜉(𝜃	NOUN
brj-25043	335	33	)	)	PUNCT
brj-25043	335	34	)	)	PUNCT
brj-25043	335	35	(	(	PUNCT
brj-25043	335	36	18	18	NUM
brj-25043	335	37	)	)	PUNCT
brj-25043	335	38	where	where	SCONJ
brj-25043	335	39	𝜀𝛾	𝜀𝛾	NOUN
brj-25043	335	40	is	be	AUX
brj-25043	335	41	a	a	DET
brj-25043	335	42	controlling	control	VERB
brj-25043	335	43	factor	factor	NOUN
brj-25043	335	44	for	for	ADP
brj-25043	335	45	the	the	DET
brj-25043	335	46	random	random	ADJ
brj-25043	335	47	part	part	NOUN
brj-25043	335	48	and	and	CCONJ
brj-25043	335	49	𝜉(𝜃	𝜉(𝜃	NOUN
brj-25043	335	50	)	)	PUNCT
brj-25043	335	51	is	be	AUX
brj-25043	335	52	a	a	DET
brj-25043	335	53	random	random	ADJ
brj-25043	335	54	variable	variable	NOUN
brj-25043	335	55	that	that	PRON
brj-25043	335	56	describes	describe	VERB
brj-25043	335	57	the	the	DET
brj-25043	335	58	expected	expect	VERB
brj-25043	335	59	uncertainty	uncertainty	NOUN
brj-25043	335	60	in	in	ADP
brj-25043	335	61	the	the	DET
brj-25043	335	62	deterministic	deterministic	ADJ
brj-25043	335	63	value	value	NOUN
brj-25043	335	64	of	of	ADP
brj-25043	335	65	𝛾.	𝛾.	NOUN
brj-25043	335	66	the	the	DET
brj-25043	335	67	random	random	ADJ
brj-25043	335	68	variable	variable	NOUN
brj-25043	335	69	𝜉(𝜃	𝜉(𝜃	NOUN
brj-25043	335	70	)	)	PUNCT
brj-25043	335	71	is	be	AUX
brj-25043	335	72	a	a	DET
brj-25043	335	73	real	real	ADV
brj-25043	335	74	-	-	PUNCT
brj-25043	335	75	valued	value	VERB
brj-25043	335	76	measurable	measurable	ADJ
brj-25043	335	77	function	function	NOUN
brj-25043	335	78	defined	define	VERB
brj-25043	335	79	on	on	ADP
brj-25043	335	80	a	a	DET
brj-25043	335	81	probability	probability	NOUN
brj-25043	335	82	space	space	NOUN
brj-25043	335	83	as	as	ADP
brj-25043	335	84	𝜉(𝜃	𝜉(𝜃	NOUN
brj-25043	335	85	):	):	PUNCT
brj-25043	335	86	ω	ω	PROPN
brj-25043	335	87	→	→	SYM
brj-25043	335	88	𝑅	𝑅	PROPN
brj-25043	335	89	,	,	PUNCT
brj-25043	335	90	defined	define	VERB
brj-25043	335	91	on	on	ADP
brj-25043	335	92	the	the	DET
brj-25043	335	93	triple	triple	ADJ
brj-25043	335	94	probability	probability	NOUN
brj-25043	335	95	space	space	NOUN
brj-25043	335	96	(	(	PUNCT
brj-25043	335	97	ω	ω	NOUN
brj-25043	335	98	,	,	PUNCT
brj-25043	335	99	ℱ	ℱ	PROPN
brj-25043	335	100	,	,	PUNCT
brj-25043	335	101	𝑃	𝑃	PROPN
brj-25043	335	102	)	)	PUNCT
brj-25043	335	103	.	.	PUNCT
brj-25043	336	1	this	this	DET
brj-25043	336	2	random	random	ADJ
brj-25043	336	3	variable	variable	NOUN
brj-25043	336	4	can	can	AUX
brj-25043	336	5	be	be	AUX
brj-25043	336	6	assigned	assign	VERB
brj-25043	336	7	entirely	entirely	ADV
brj-25043	336	8	by	by	ADP
brj-25043	336	9	repeating	repeat	VERB
brj-25043	336	10	the	the	DET
brj-25043	336	11	ad	ad	NOUN
brj-25043	336	12	process	process	NOUN
brj-25043	336	13	a	a	DET
brj-25043	336	14	relatively	relatively	ADV
brj-25043	336	15	large	large	ADJ
brj-25043	336	16	number	number	NOUN
brj-25043	336	17	of	of	ADP
brj-25043	336	18	times	time	NOUN
brj-25043	336	19	,	,	PUNCT
brj-25043	336	20	then	then	ADV
brj-25043	336	21	estimating	estimate	VERB
brj-25043	336	22	the	the	DET
brj-25043	336	23	model	model	NOUN
brj-25043	336	24	parameters	parameter	NOUN
brj-25043	336	25	in	in	ADP
brj-25043	336	26	each	each	DET
brj-25043	336	27	time	time	NOUN
brj-25043	336	28	.	.	PUNCT
brj-25043	337	1	for	for	ADP
brj-25043	337	2	each	each	DET
brj-25043	337	3	parameter	parameter	NOUN
brj-25043	337	4	,	,	PUNCT
brj-25043	337	5	the	the	DET
brj-25043	337	6	obtained	obtain	VERB
brj-25043	337	7	values	value	NOUN
brj-25043	337	8	can	can	AUX
brj-25043	337	9	peer	peer	NOUN
brj-25043	337	10	-	-	PUNCT
brj-25043	337	11	reviewed	review	VERB
brj-25043	337	12	review	review	NOUN
brj-25043	337	13	article	article	NOUN
brj-25043	337	14	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	337	15	galal	galal	PROPN
brj-25043	337	16	et	et	PROPN
brj-25043	337	17	al	al	PROPN
brj-25043	337	18	.	.	PROPN
brj-25043	338	1	(	(	PUNCT
brj-25043	338	2	2025	2025	NUM
brj-25043	338	3	)	)	PUNCT
brj-25043	338	4	.	.	PUNCT
brj-25043	339	1	“	"	PUNCT
brj-25043	339	2	math	math	NOUN
brj-25043	339	3	modeling	modeling	NOUN
brj-25043	339	4	biogas	biogas	NOUN
brj-25043	339	5	production	production	NOUN
brj-25043	339	6	,	,	PUNCT
brj-25043	339	7	”	"	PUNCT
brj-25043	339	8	bioresources	bioresource	NOUN
brj-25043	339	9	20(4	20(4	NOUN
brj-25043	339	10	)	)	PUNCT
brj-25043	339	11	,	,	PUNCT
brj-25043	339	12	11237	11237	NUM
brj-25043	339	13	-	-	SYM
brj-25043	339	14	11266	11266	NUM
brj-25043	339	15	.	.	PUNCT
brj-25043	340	1	11257	11257	NUM
brj-25043	340	2	then	then	ADV
brj-25043	340	3	be	be	AUX
brj-25043	340	4	plotted	plot	VERB
brj-25043	340	5	to	to	PART
brj-25043	340	6	determine	determine	VERB
brj-25043	340	7	its	its	PRON
brj-25043	340	8	probability	probability	NOUN
brj-25043	340	9	distribution	distribution	NOUN
brj-25043	340	10	and	and	CCONJ
brj-25043	340	11	its	its	PRON
brj-25043	340	12	statistical	statistical	ADJ
brj-25043	340	13	moments	moment	NOUN
brj-25043	340	14	such	such	ADJ
brj-25043	340	15	as	as	ADP
brj-25043	340	16	mean	mean	ADJ
brj-25043	340	17	,	,	PUNCT
brj-25043	340	18	variance	variance	NOUN
brj-25043	340	19	,	,	PUNCT
brj-25043	340	20	skewness	skewness	NOUN
brj-25043	340	21	,	,	PUNCT
brj-25043	340	22	and	and	CCONJ
brj-25043	340	23	kurtosis	kurtosis	NOUN
brj-25043	340	24	,	,	PUNCT
brj-25043	340	25	so	so	SCONJ
brj-25043	340	26	that	that	SCONJ
brj-25043	340	27	a	a	DET
brj-25043	340	28	complete	complete	ADJ
brj-25043	340	29	definition	definition	NOUN
brj-25043	340	30	for	for	ADP
brj-25043	340	31	this	this	DET
brj-25043	340	32	uncertain	uncertain	ADJ
brj-25043	340	33	parameter	parameter	NOUN
brj-25043	340	34	will	will	AUX
brj-25043	340	35	be	be	AUX
brj-25043	340	36	available	available	ADJ
brj-25043	340	37	.	.	PUNCT
brj-25043	341	1	the	the	DET
brj-25043	341	2	repetition	repetition	NOUN
brj-25043	341	3	of	of	ADP
brj-25043	341	4	the	the	DET
brj-25043	341	5	ad	ad	NOUN
brj-25043	341	6	process	process	NOUN
brj-25043	341	7	several	several	ADJ
brj-25043	341	8	times	time	NOUN
brj-25043	341	9	to	to	PART
brj-25043	341	10	determine	determine	VERB
brj-25043	341	11	the	the	DET
brj-25043	341	12	parameter	parameter	NOUN
brj-25043	341	13	uncertainty	uncertainty	NOUN
brj-25043	341	14	requires	require	VERB
brj-25043	341	15	short	short	ADJ
brj-25043	341	16	-	-	PUNCT
brj-25043	341	17	time	time	NOUN
brj-25043	341	18	processes	process	NOUN
brj-25043	341	19	and	and	CCONJ
brj-25043	341	20	many	many	ADJ
brj-25043	341	21	reactors	reactor	NOUN
brj-25043	341	22	working	work	VERB
brj-25043	341	23	simultaneously	simultaneously	ADV
brj-25043	341	24	.	.	PUNCT
brj-25043	342	1	moreover	moreover	ADV
brj-25043	342	2	,	,	PUNCT
brj-25043	342	3	when	when	SCONJ
brj-25043	342	4	the	the	DET
brj-25043	342	5	parameter	parameter	NOUN
brj-25043	342	6	uncertainty	uncertainty	NOUN
brj-25043	342	7	is	be	AUX
brj-25043	342	8	more	more	ADV
brj-25043	342	9	complicated	complicated	ADJ
brj-25043	342	10	and	and	CCONJ
brj-25043	342	11	expected	expect	VERB
brj-25043	342	12	to	to	PART
brj-25043	342	13	have	have	VERB
brj-25043	342	14	higher	high	ADJ
brj-25043	342	15	fluctuations	fluctuation	NOUN
brj-25043	342	16	with	with	ADP
brj-25043	342	17	time	time	NOUN
brj-25043	342	18	,	,	PUNCT
brj-25043	342	19	the	the	DET
brj-25043	342	20	random	random	ADJ
brj-25043	342	21	part	part	NOUN
brj-25043	342	22	can	can	AUX
brj-25043	342	23	be	be	AUX
brj-25043	342	24	expressed	express	VERB
brj-25043	342	25	as	as	ADP
brj-25043	342	26	a	a	DET
brj-25043	342	27	random	random	ADJ
brj-25043	342	28	process	process	NOUN
brj-25043	342	29	as	as	ADP
brj-25043	342	30	eq	eq	NOUN
brj-25043	342	31	.	.	PROPN
brj-25043	342	32	16	16	NUM
brj-25043	342	33	,	,	PUNCT
brj-25043	342	34	𝛾(𝑡	𝛾(𝑡	PROPN
brj-25043	342	35	,	,	PUNCT
brj-25043	342	36	𝜃	𝜃	NOUN
brj-25043	342	37	)	)	PUNCT
brj-25043	342	38	=	=	SYM
brj-25043	342	39	𝛾(1	𝛾(1	PROPN
brj-25043	342	40	+	+	CCONJ
brj-25043	342	41	𝜀	𝜀	X
brj-25043	342	42	ф(𝑡	ф(𝑡	PROPN
brj-25043	342	43	;	;	PUNCT
brj-25043	342	44	𝜃	𝜃	X
brj-25043	342	45	)	)	PUNCT
brj-25043	342	46	)	)	PUNCT
brj-25043	343	1	(	(	PUNCT
brj-25043	343	2	19	19	NUM
brj-25043	343	3	)	)	PUNCT
brj-25043	343	4	where	where	SCONJ
brj-25043	343	5	ф(𝑡	ф(𝑡	NOUN
brj-25043	343	6	;	;	PUNCT
brj-25043	343	7	𝜃	𝜃	X
brj-25043	343	8	)	)	PUNCT
brj-25043	343	9	is	be	AUX
brj-25043	343	10	a	a	DET
brj-25043	343	11	second	second	ADJ
brj-25043	343	12	-	-	PUNCT
brj-25043	343	13	order	order	NOUN
brj-25043	343	14	random	random	ADJ
brj-25043	343	15	process	process	NOUN
brj-25043	343	16	with	with	ADP
brj-25043	343	17	a	a	DET
brj-25043	343	18	finite	finite	ADJ
brj-25043	343	19	variance	variance	NOUN
brj-25043	343	20	.	.	PUNCT
brj-25043	344	1	this	this	DET
brj-25043	344	2	random	random	ADJ
brj-25043	344	3	process	process	NOUN
brj-25043	344	4	can	can	AUX
brj-25043	344	5	be	be	AUX
brj-25043	344	6	expanded	expand	VERB
brj-25043	344	7	into	into	ADP
brj-25043	344	8	random	random	ADJ
brj-25043	344	9	variables	variable	NOUN
brj-25043	344	10	multiplied	multiply	VERB
brj-25043	344	11	by	by	ADP
brj-25043	344	12	deterministic	deterministic	ADJ
brj-25043	344	13	constants	constant	NOUN
brj-25043	344	14	using	use	VERB
brj-25043	344	15	k	k	ADJ
brj-25043	344	16	-	-	ADJ
brj-25043	344	17	l	l	NOUN
brj-25043	344	18	expansion	expansion	NOUN
brj-25043	344	19	,	,	PUNCT
brj-25043	344	20	as	as	ADP
brj-25043	344	21	eq	eq	ADP
brj-25043	344	22	.	.	PROPN
brj-25043	344	23	17	17	NUM
brj-25043	344	24	(	(	PUNCT
brj-25043	344	25	ghanem	ghanem	PROPN
brj-25043	344	26	and	and	CCONJ
brj-25043	344	27	spanos	spano	NOUN
brj-25043	344	28	2003	2003	NUM
brj-25043	344	29	)	)	PUNCT
brj-25043	344	30	,	,	PUNCT
brj-25043	344	31	𝛾(𝑡	𝛾(𝑡	PROPN
brj-25043	344	32	;	;	PUNCT
brj-25043	344	33	𝜃	𝜃	X
brj-25043	344	34	)	)	PUNCT
brj-25043	344	35	=	=	SYM
brj-25043	344	36	�	�	PROPN
brj-25043	344	37	̅	̅	NOUN
brj-25043	344	38	�	�	NOUN
brj-25043	344	39	(𝑡	(𝑡	NOUN
brj-25043	344	40	)	)	PUNCT
brj-25043	345	1	+	+	CCONJ
brj-25043	345	2	∑	∑	PROPN
brj-25043	345	3	√𝜆𝑖	√𝜆𝑖	PROPN
brj-25043	345	4	∞	∞	PROPN
brj-25043	345	5	𝑖=1	𝑖=1	PROPN
brj-25043	345	6	𝑓𝑖(𝑡	𝑓𝑖(𝑡	NUM
brj-25043	345	7	)	)	PUNCT
brj-25043	345	8	𝜉𝑖(𝜃	𝜉𝑖(𝜃	PROPN
brj-25043	345	9	)	)	PUNCT
brj-25043	345	10	(	(	PUNCT
brj-25043	345	11	20	20	NUM
brj-25043	345	12	)	)	PUNCT
brj-25043	345	13	where	where	SCONJ
brj-25043	345	14	𝛾(𝑡	𝛾(𝑡	PROPN
brj-25043	345	15	)	)	PUNCT
brj-25043	345	16	is	be	AUX
brj-25043	345	17	the	the	DET
brj-25043	345	18	mean	mean	ADJ
brj-25043	345	19	value	value	NOUN
brj-25043	345	20	of	of	ADP
brj-25043	345	21	𝛾𝑡;𝜃	𝛾𝑡;𝜃	X
brj-25043	345	22	,	,	PUNCT
brj-25043	345	23	𝜉𝑖𝜃𝑖=1∞	𝜉𝑖𝜃𝑖=1∞	NOUN
brj-25043	345	24	is	be	AUX
brj-25043	345	25	a	a	DET
brj-25043	345	26	set	set	NOUN
brj-25043	345	27	of	of	ADP
brj-25043	345	28	uncorrelated	uncorrelated	ADJ
brj-25043	345	29	random	random	ADJ
brj-25043	345	30	variables	variable	NOUN
brj-25043	345	31	,	,	PUNCT
brj-25043	345	32	𝜆𝑖,𝑓𝑖𝑡	𝜆𝑖,𝑓𝑖𝑡	X
brj-25043	345	33	are	be	AUX
brj-25043	345	34	the	the	DET
brj-25043	345	35	eigenvalues	eigenvalues	PROPN
brj-25043	345	36	and	and	CCONJ
brj-25043	345	37	eigen	eigen	PROPN
brj-25043	345	38	functions	function	NOUN
brj-25043	345	39	,	,	PUNCT
brj-25043	345	40	respectively	respectively	ADV
brj-25043	345	41	.	.	PUNCT
brj-25043	346	1	both	both	DET
brj-25043	346	2	𝜆𝑖	𝜆𝑖	PROPN
brj-25043	346	3	,	,	PUNCT
brj-25043	346	4	𝑓𝑖(𝑡	𝑓𝑖(𝑡	NUM
brj-25043	346	5	)	)	PUNCT
brj-25043	346	6	can	can	AUX
brj-25043	346	7	be	be	AUX
brj-25043	346	8	evaluated	evaluate	VERB
brj-25043	346	9	by	by	ADP
brj-25043	346	10	solving	solve	VERB
brj-25043	346	11	the	the	DET
brj-25043	346	12	integral	integral	ADJ
brj-25043	346	13	eq	eq	NOUN
brj-25043	346	14	.	.	PROPN
brj-25043	346	15	18	18	NUM
brj-25043	346	16	,	,	PUNCT
brj-25043	346	17	∫	∫	PROPN
brj-25043	346	18	𝐶	𝐶	PROPN
brj-25043	346	19	𝛾𝛾(𝑡1	𝛾𝛾(𝑡1	PROPN
brj-25043	346	20	,	,	PUNCT
brj-25043	346	21	𝑡2	𝑡2	PROPN
brj-25043	346	22	)	)	PUNCT
brj-25043	346	23	𝑓𝑖(𝑡1	𝑓𝑖(𝑡1	PROPN
brj-25043	346	24	)	)	PUNCT
brj-25043	346	25	𝑑𝑡1	𝑑𝑡1	PROPN
brj-25043	346	26	𝐷	𝐷	PROPN
brj-25043	346	27	=	=	SYM
brj-25043	346	28	𝜆𝑖𝑓𝑖(𝑡2	𝜆𝑖𝑓𝑖(𝑡2	PROPN
brj-25043	346	29	)	)	PUNCT
brj-25043	346	30	(	(	PUNCT
brj-25043	346	31	21	21	NUM
brj-25043	346	32	)	)	PUNCT
brj-25043	346	33	where	where	SCONJ
brj-25043	346	34	d	d	NOUN
brj-25043	346	35	is	be	AUX
brj-25043	346	36	the	the	DET
brj-25043	346	37	time	time	NOUN
brj-25043	346	38	domain	domain	NOUN
brj-25043	346	39	over	over	ADP
brj-25043	346	40	which	which	PRON
brj-25043	346	41	𝛾(𝑡	𝛾(𝑡	PROPN
brj-25043	346	42	;	;	PUNCT
brj-25043	346	43	𝜃	𝜃	X
brj-25043	346	44	)	)	PUNCT
brj-25043	346	45	is	be	AUX
brj-25043	346	46	defined	define	VERB
brj-25043	346	47	and	and	CCONJ
brj-25043	346	48	𝑡1	𝑡1	NOUN
brj-25043	346	49	,	,	PUNCT
brj-25043	346	50	𝑡2	𝑡2	PROPN
brj-25043	346	51	∈	∈	PROPN
brj-25043	346	52	𝐷.	𝐷.	PROPN
brj-25043	346	53	including	include	VERB
brj-25043	346	54	these	these	DET
brj-25043	346	55	parameters	parameter	NOUN
brj-25043	346	56	,	,	PUNCT
brj-25043	346	57	uncertainty	uncertainty	NOUN
brj-25043	346	58	in	in	ADP
brj-25043	346	59	the	the	DET
brj-25043	346	60	model	model	NOUN
brj-25043	346	61	equation	equation	NOUN
brj-25043	346	62	yields	yield	VERB
brj-25043	346	63	a	a	DET
brj-25043	346	64	probability	probability	NOUN
brj-25043	346	65	distribution	distribution	NOUN
brj-25043	346	66	curve	curve	NOUN
brj-25043	346	67	for	for	ADP
brj-25043	346	68	the	the	DET
brj-25043	346	69	biogas	biogas	NOUN
brj-25043	346	70	production	production	NOUN
brj-25043	346	71	every	every	DET
brj-25043	346	72	time	time	NOUN
brj-25043	346	73	.	.	PUNCT
brj-25043	347	1	this	this	PRON
brj-25043	347	2	provides	provide	VERB
brj-25043	347	3	the	the	DET
brj-25043	347	4	expected	expect	VERB
brj-25043	347	5	value	value	NOUN
brj-25043	347	6	(	(	PUNCT
brj-25043	347	7	mean	mean	NOUN
brj-25043	347	8	)	)	PUNCT
brj-25043	347	9	,	,	PUNCT
brj-25043	347	10	variance	variance	NOUN
brj-25043	347	11	,	,	PUNCT
brj-25043	347	12	different	different	ADJ
brj-25043	347	13	quartiles	quartile	NOUN
brj-25043	347	14	,	,	PUNCT
brj-25043	347	15	required	require	VERB
brj-25043	347	16	threshold	threshold	NOUN
brj-25043	347	17	values	value	NOUN
brj-25043	347	18	,	,	PUNCT
brj-25043	347	19	and	and	CCONJ
brj-25043	347	20	statistical	statistical	ADJ
brj-25043	347	21	moments	moment	NOUN
brj-25043	347	22	for	for	ADP
brj-25043	347	23	the	the	DET
brj-25043	347	24	biogas	biogas	NOUN
brj-25043	347	25	production	production	NOUN
brj-25043	347	26	.	.	PUNCT
brj-25043	348	1	this	this	PRON
brj-25043	348	2	probably	probably	ADV
brj-25043	348	3	gives	give	VERB
brj-25043	348	4	a	a	DET
brj-25043	348	5	clear	clear	ADJ
brj-25043	348	6	vision	vision	NOUN
brj-25043	348	7	of	of	ADP
brj-25043	348	8	the	the	DET
brj-25043	348	9	ad	ad	NOUN
brj-25043	348	10	process	process	NOUN
brj-25043	348	11	.	.	PUNCT
brj-25043	349	1	such	such	ADJ
brj-25043	349	2	stochastic	stochastic	ADJ
brj-25043	349	3	approaches	approach	NOUN
brj-25043	349	4	could	could	AUX
brj-25043	349	5	also	also	ADV
brj-25043	349	6	incorporate	incorporate	VERB
brj-25043	349	7	sensitivity	sensitivity	NOUN
brj-25043	349	8	analysis	analysis	NOUN
brj-25043	349	9	to	to	PART
brj-25043	349	10	identify	identify	VERB
brj-25043	349	11	dominant	dominant	ADJ
brj-25043	349	12	parameters	parameter	NOUN
brj-25043	349	13	influencing	influence	VERB
brj-25043	349	14	biogas	biogas	NOUN
brj-25043	349	15	yield	yield	NOUN
brj-25043	349	16	variability	variability	NOUN
brj-25043	349	17	.	.	PUNCT
brj-25043	350	1	this	this	DET
brj-25043	350	2	concept	concept	NOUN
brj-25043	350	3	has	have	AUX
brj-25043	350	4	been	be	AUX
brj-25043	350	5	applied	apply	VERB
brj-25043	350	6	successfully	successfully	ADV
brj-25043	350	7	in	in	ADP
brj-25043	350	8	many	many	ADJ
brj-25043	350	9	fields	field	NOUN
brj-25043	350	10	(	(	PUNCT
brj-25043	350	11	galal	galal	PROPN
brj-25043	350	12	2013	2013	NUM
brj-25043	350	13	,	,	PUNCT
brj-25043	350	14	2021	2021	NUM
brj-25043	350	15	)	)	PUNCT
brj-25043	350	16	and	and	CCONJ
brj-25043	350	17	could	could	AUX
brj-25043	350	18	provide	provide	VERB
brj-25043	350	19	the	the	DET
brj-25043	350	20	designers	designer	NOUN
brj-25043	350	21	with	with	ADP
brj-25043	350	22	the	the	DET
brj-25043	350	23	system	system	NOUN
brj-25043	350	24	’s	’s	PART
brj-25043	350	25	random	random	ADJ
brj-25043	350	26	response	response	NOUN
brj-25043	350	27	due	due	ADP
brj-25043	350	28	to	to	ADP
brj-25043	350	29	these	these	DET
brj-25043	350	30	uncertain	uncertain	ADJ
brj-25043	350	31	parameters	parameter	NOUN
brj-25043	350	32	.	.	PUNCT
brj-25043	351	1	multidimensional	multidimensional	ADJ
brj-25043	351	2	mathematical	mathematical	ADJ
brj-25043	351	3	models	model	NOUN
brj-25043	351	4	the	the	DET
brj-25043	351	5	existing	exist	VERB
brj-25043	351	6	models	model	NOUN
brj-25043	351	7	usually	usually	ADV
brj-25043	351	8	plot	plot	VERB
brj-25043	351	9	the	the	DET
brj-25043	351	10	biogas	biogas	NOUN
brj-25043	351	11	production	production	NOUN
brj-25043	351	12	with	with	ADP
brj-25043	351	13	time	time	NOUN
brj-25043	351	14	under	under	ADP
brj-25043	351	15	certain	certain	ADJ
brj-25043	351	16	conditions	condition	NOUN
brj-25043	351	17	,	,	PUNCT
brj-25043	351	18	such	such	ADJ
brj-25043	351	19	as	as	ADP
brj-25043	351	20	the	the	DET
brj-25043	351	21	operating	operating	NOUN
brj-25043	351	22	temperature	temperature	NOUN
brj-25043	351	23	,	,	PUNCT
brj-25043	351	24	mixing	mix	VERB
brj-25043	351	25	ratio	ratio	NOUN
brj-25043	351	26	,	,	PUNCT
brj-25043	351	27	heavy	heavy	ADJ
brj-25043	351	28	metal	metal	NOUN
brj-25043	351	29	concentration	concentration	NOUN
brj-25043	351	30	,	,	PUNCT
brj-25043	351	31	etc	etc	X
brj-25043	351	32	.	.	X
brj-25043	352	1	this	this	PRON
brj-25043	352	2	yields	yield	VERB
brj-25043	352	3	a	a	DET
brj-25043	352	4	single	single	ADJ
brj-25043	352	5	plot	plot	NOUN
brj-25043	352	6	for	for	ADP
brj-25043	352	7	the	the	DET
brj-25043	352	8	biogas	biogas	NOUN
brj-25043	352	9	production	production	NOUN
brj-25043	352	10	versus	versus	ADP
brj-25043	352	11	time	time	NOUN
brj-25043	352	12	for	for	ADP
brj-25043	352	13	each	each	DET
brj-25043	352	14	realization	realization	NOUN
brj-25043	352	15	of	of	ADP
brj-25043	352	16	these	these	DET
brj-25043	352	17	conditions	condition	NOUN
brj-25043	352	18	.	.	PUNCT
brj-25043	353	1	however	however	ADV
brj-25043	353	2	,	,	PUNCT
brj-25043	353	3	these	these	DET
brj-25043	353	4	models	model	NOUN
brj-25043	353	5	can	can	AUX
brj-25043	353	6	be	be	AUX
brj-25043	353	7	extended	extend	VERB
brj-25043	353	8	to	to	ADP
brj-25043	353	9	cases	case	NOUN
brj-25043	353	10	with	with	ADP
brj-25043	353	11	two	two	NUM
brj-25043	353	12	or	or	CCONJ
brj-25043	353	13	more	more	ADJ
brj-25043	353	14	dimensions	dimension	NOUN
brj-25043	353	15	.	.	PUNCT
brj-25043	354	1	this	this	DET
brj-25043	354	2	extension	extension	NOUN
brj-25043	354	3	to	to	ADP
brj-25043	354	4	multidimensional	multidimensional	ADJ
brj-25043	354	5	modelling	modelling	NOUN
brj-25043	354	6	can	can	AUX
brj-25043	354	7	be	be	AUX
brj-25043	354	8	conducted	conduct	VERB
brj-25043	354	9	through	through	ADP
brj-25043	354	10	an	an	DET
brj-25043	354	11	equal	equal	ADJ
brj-25043	354	12	number	number	NOUN
brj-25043	354	13	of	of	ADP
brj-25043	354	14	curve	curve	NOUN
brj-25043	354	15	-	-	PUNCT
brj-25043	354	16	fitting	fit	VERB
brj-25043	354	17	steps	step	NOUN
brj-25043	354	18	.	.	PUNCT
brj-25043	355	1	to	to	PART
brj-25043	355	2	implement	implement	VERB
brj-25043	355	3	this	this	DET
brj-25043	355	4	extension	extension	NOUN
brj-25043	355	5	to	to	ADP
brj-25043	355	6	a	a	DET
brj-25043	355	7	multi	multi	ADJ
brj-25043	355	8	-	-	ADJ
brj-25043	355	9	dimensional	dimensional	ADJ
brj-25043	355	10	case	case	NOUN
brj-25043	355	11	,	,	PUNCT
brj-25043	355	12	consider	consider	VERB
brj-25043	355	13	a	a	DET
brj-25043	355	14	mathematical	mathematical	ADJ
brj-25043	355	15	model	model	NOUN
brj-25043	355	16	with	with	ADP
brj-25043	355	17	three	three	NUM
brj-25043	355	18	parameters	parameter	NOUN
brj-25043	355	19	a	a	DET
brj-25043	355	20	,	,	PUNCT
brj-25043	355	21	b	b	NOUN
brj-25043	355	22	,	,	PUNCT
brj-25043	355	23	and	and	CCONJ
brj-25043	355	24	k	k	PROPN
brj-25043	355	25	,	,	PUNCT
brj-25043	355	26	then	then	ADV
brj-25043	355	27	consider	consider	VERB
brj-25043	355	28	several	several	ADJ
brj-25043	355	29	variables	variable	NOUN
brj-25043	355	30	such	such	ADJ
brj-25043	355	31	as	as	ADP
brj-25043	355	32	the	the	DET
brj-25043	355	33	time	time	NOUN
brj-25043	355	34	,	,	PUNCT
brj-25043	355	35	which	which	PRON
brj-25043	355	36	is	be	AUX
brj-25043	355	37	defined	define	VERB
brj-25043	355	38	as	as	ADP
brj-25043	355	39	t	t	PROPN
brj-25043	355	40	∈	∈	PROPN
brj-25043	355	41	{	{	PUNCT
brj-25043	355	42	𝑡1	𝑡1	NOUN
brj-25043	355	43	,	,	PUNCT
brj-25043	355	44	𝑡2	𝑡2	PROPN
brj-25043	355	45	,	,	PUNCT
brj-25043	355	46	…	…	PUNCT
brj-25043	355	47	…	…	PUNCT
brj-25043	355	48	.,𝑡𝑙	.,𝑡𝑙	PUNCT
brj-25043	355	49	}	}	PUNCT
brj-25043	355	50	,	,	PUNCT
brj-25043	355	51	the	the	DET
brj-25043	355	52	mixing	mix	VERB
brj-25043	355	53	ratio	ratio	NOUN
brj-25043	355	54	defined	define	VERB
brj-25043	355	55	as	as	ADP
brj-25043	355	56	r	r	PROPN
brj-25043	355	57	∈	∈	PROPN
brj-25043	355	58	{	{	PUNCT
brj-25043	355	59	𝑟1	𝑟1	NOUN
brj-25043	355	60	,	,	PUNCT
brj-25043	355	61	𝑟2	𝑟2	NOUN
brj-25043	355	62	,	,	PUNCT
brj-25043	355	63	…	…	PUNCT
brj-25043	355	64	…	…	PUNCT
brj-25043	355	65	.,𝑟𝑚	.,𝑟𝑚	NOUN
brj-25043	355	66	}	}	PUNCT
brj-25043	355	67	,	,	PUNCT
brj-25043	355	68	the	the	DET
brj-25043	355	69	operating	operate	VERB
brj-25043	355	70	temperature	temperature	NOUN
brj-25043	355	71	defined	define	VERB
brj-25043	355	72	as	as	ADP
brj-25043	355	73	t∈	t∈	PROPN
brj-25043	355	74	{	{	PUNCT
brj-25043	355	75	𝑇1	𝑇1	PROPN
brj-25043	355	76	,	,	PUNCT
brj-25043	355	77	𝑇2	𝑇2	NOUN
brj-25043	355	78	,	,	PUNCT
brj-25043	355	79	…	…	PUNCT
brj-25043	355	80	…	…	PUNCT
brj-25043	355	81	.,𝑇𝑛	.,𝑇𝑛	NOUN
brj-25043	355	82	}	}	PUNCT
brj-25043	355	83	,	,	PUNCT
brj-25043	355	84	and	and	CCONJ
brj-25043	355	85	so	so	ADV
brj-25043	355	86	on	on	ADV
brj-25043	355	87	.	.	PUNCT
brj-25043	356	1	first	first	ADV
brj-25043	356	2	,	,	PUNCT
brj-25043	356	3	the	the	DET
brj-25043	356	4	biogas	biogas	NOUN
brj-25043	356	5	production	production	NOUN
brj-25043	356	6	is	be	AUX
brj-25043	356	7	plotted	plot	VERB
brj-25043	356	8	versus	versus	ADP
brj-25043	356	9	all	all	DET
brj-25043	356	10	time	time	NOUN
brj-25043	356	11	values	value	NOUN
brj-25043	356	12	,	,	PUNCT
brj-25043	356	13	t	t	PROPN
brj-25043	356	14	∈	∈	PROPN
brj-25043	356	15	{	{	PUNCT
brj-25043	356	16	𝑡1	𝑡1	PROPN
brj-25043	356	17	,	,	PUNCT
brj-25043	356	18	𝑡2	𝑡2	PROPN
brj-25043	356	19	,	,	PUNCT
brj-25043	356	20	…	…	PUNCT
brj-25043	356	21	…	…	PUNCT
brj-25043	356	22	.,𝑡𝑙	.,𝑡𝑙	PUNCT
brj-25043	356	23	}	}	PUNCT
brj-25043	356	24	at	at	ADP
brj-25043	356	25	𝑟1	𝑟1	PROPN
brj-25043	356	26	and	and	CCONJ
brj-25043	356	27	𝑇1	𝑇1	NOUN
brj-25043	356	28	.	.	PUNCT
brj-25043	357	1	then	then	ADV
brj-25043	357	2	,	,	PUNCT
brj-25043	357	3	the	the	DET
brj-25043	357	4	a	a	PRON
brj-25043	357	5	,	,	PUNCT
brj-25043	357	6	b	b	NOUN
brj-25043	357	7	,	,	PUNCT
brj-25043	357	8	and	and	CCONJ
brj-25043	357	9	k	k	PROPN
brj-25043	357	10	values	value	NOUN
brj-25043	357	11	are	be	AUX
brj-25043	357	12	estimated	estimate	VERB
brj-25043	357	13	for	for	ADP
brj-25043	357	14	the	the	DET
brj-25043	357	15	best	good	ADJ
brj-25043	357	16	correlation	correlation	NOUN
brj-25043	357	17	with	with	ADP
brj-25043	357	18	the	the	DET
brj-25043	357	19	experimental	experimental	ADJ
brj-25043	357	20	data	datum	NOUN
brj-25043	357	21	.	.	PUNCT
brj-25043	358	1	this	this	PRON
brj-25043	358	2	will	will	AUX
brj-25043	358	3	be	be	AUX
brj-25043	358	4	repeated	repeat	VERB
brj-25043	358	5	for	for	ADP
brj-25043	358	6	(	(	PUNCT
brj-25043	358	7	𝑟2	𝑟2	NOUN
brj-25043	358	8	,	,	PUNCT
brj-25043	358	9	𝑇1	𝑇1	NOUN
brj-25043	358	10	)	)	PUNCT
brj-25043	358	11	,	,	PUNCT
brj-25043	358	12	…	…	PUNCT
brj-25043	358	13	…	…	PUNCT
brj-25043	358	14	.	.	NUM
brj-25043	358	15	,	,	PUNCT
brj-25043	358	16	(	(	PUNCT
brj-25043	358	17	𝑟𝑚	𝑟𝑚	ADP
brj-25043	358	18	,	,	PUNCT
brj-25043	358	19	𝑇1	𝑇1	NOUN
brj-25043	358	20	)	)	PUNCT
brj-25043	358	21	.	.	PUNCT
brj-25043	359	1	this	this	PRON
brj-25043	359	2	yields	yield	VERB
brj-25043	359	3	a	a	DET
brj-25043	359	4	set	set	NOUN
brj-25043	359	5	of	of	ADP
brj-25043	359	6	m	m	PROPN
brj-25043	359	7	values	value	NOUN
brj-25043	359	8	for	for	ADP
brj-25043	359	9	each	each	DET
brj-25043	359	10	parameter	parameter	NOUN
brj-25043	359	11	varying	vary	VERB
brj-25043	359	12	with	with	ADP
brj-25043	359	13	r.	r.	PROPN
brj-25043	359	14	a	a	DET
brj-25043	359	15	second	second	ADJ
brj-25043	359	16	step	step	NOUN
brj-25043	359	17	of	of	ADP
brj-25043	359	18	curve	curve	NOUN
brj-25043	359	19	fitting	fitting	ADJ
brj-25043	359	20	is	be	AUX
brj-25043	359	21	then	then	ADV
brj-25043	359	22	performed	perform	VERB
brj-25043	359	23	to	to	PART
brj-25043	359	24	determine	determine	VERB
brj-25043	359	25	the	the	DET
brj-25043	359	26	best	good	ADJ
brj-25043	359	27	function	function	NOUN
brj-25043	359	28	with	with	ADP
brj-25043	359	29	the	the	DET
brj-25043	359	30	highest	high	ADJ
brj-25043	359	31	correlation	correlation	NOUN
brj-25043	359	32	for	for	ADP
brj-25043	359	33	each	each	DET
brj-25043	359	34	parameter	parameter	NOUN
brj-25043	359	35	in	in	ADP
brj-25043	359	36	r.	r.	NOUN
brj-25043	359	37	using	use	VERB
brj-25043	359	38	the	the	DET
brj-25043	359	39	matlab	matlab	PROPN
brj-25043	359	40	program	program	NOUN
brj-25043	359	41	(	(	PUNCT
brj-25043	359	42	2022	2022	NUM
brj-25043	359	43	)	)	PUNCT
brj-25043	359	44	,	,	PUNCT
brj-25043	359	45	many	many	ADJ
brj-25043	359	46	functions	function	NOUN
brj-25043	359	47	are	be	AUX
brj-25043	359	48	available	available	ADJ
brj-25043	359	49	to	to	PART
brj-25043	359	50	plot	plot	VERB
brj-25043	359	51	the	the	DET
brj-25043	359	52	model	model	NOUN
brj-25043	359	53	parameters	parameter	NOUN
brj-25043	359	54	versus	versus	ADP
brj-25043	359	55	r	r	NOUN
brj-25043	359	56	,	,	PUNCT
brj-25043	359	57	such	such	ADJ
brj-25043	359	58	as	as	ADP
brj-25043	359	59	the	the	DET
brj-25043	359	60	exponential	exponential	ADJ
brj-25043	359	61	,	,	PUNCT
brj-25043	359	62	rational	rational	ADJ
brj-25043	359	63	,	,	PUNCT
brj-25043	359	64	power	power	NOUN
brj-25043	359	65	,	,	PUNCT
brj-25043	359	66	spline	spline	NOUN
brj-25043	359	67	,	,	PUNCT
brj-25043	359	68	gaussian	gaussian	NOUN
brj-25043	359	69	,	,	PUNCT
brj-25043	359	70	weibull	weibull	PROPN
brj-25043	359	71	,	,	PUNCT
brj-25043	359	72	fourier	fourier	NOUN
brj-25043	359	73	,	,	PUNCT
brj-25043	359	74	and	and	CCONJ
brj-25043	359	75	peer	peer	NOUN
brj-25043	359	76	-	-	PUNCT
brj-25043	359	77	reviewed	review	VERB
brj-25043	359	78	review	review	NOUN
brj-25043	359	79	article	article	NOUN
brj-25043	359	80	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	359	81	galal	galal	PROPN
brj-25043	359	82	et	et	PROPN
brj-25043	359	83	al	al	PROPN
brj-25043	359	84	.	.	PROPN
brj-25043	360	1	(	(	PUNCT
brj-25043	360	2	2025	2025	NUM
brj-25043	360	3	)	)	PUNCT
brj-25043	360	4	.	.	PUNCT
brj-25043	361	1	“	"	PUNCT
brj-25043	361	2	math	math	NOUN
brj-25043	361	3	modeling	modeling	NOUN
brj-25043	361	4	biogas	biogas	NOUN
brj-25043	361	5	production	production	NOUN
brj-25043	361	6	,	,	PUNCT
brj-25043	361	7	”	"	PUNCT
brj-25043	361	8	bioresources	bioresource	NOUN
brj-25043	361	9	20(4	20(4	NOUN
brj-25043	361	10	)	)	PUNCT
brj-25043	361	11	,	,	PUNCT
brj-25043	361	12	11237	11237	NUM
brj-25043	361	13	-	-	SYM
brj-25043	361	14	11266	11266	NUM
brj-25043	361	15	.	.	PUNCT
brj-25043	362	1	11258	11258	NUM
brj-25043	362	2	sum	sum	NOUN
brj-25043	362	3	of	of	ADP
brj-25043	362	4	sine	sine	NOUN
brj-25043	362	5	,	,	PUNCT
brj-25043	362	6	and	and	CCONJ
brj-25043	362	7	polynomial	polynomial	ADJ
brj-25043	362	8	functions	function	NOUN
brj-25043	362	9	with	with	ADP
brj-25043	362	10	different	different	ADJ
brj-25043	362	11	degrees	degree	NOUN
brj-25043	362	12	.	.	PUNCT
brj-25043	363	1	the	the	DET
brj-25043	363	2	function	function	NOUN
brj-25043	363	3	selection	selection	NOUN
brj-25043	363	4	is	be	AUX
brj-25043	363	5	based	base	VERB
brj-25043	363	6	on	on	ADP
brj-25043	363	7	the	the	DET
brj-25043	363	8	best	good	ADJ
brj-25043	363	9	curve	curve	NOUN
brj-25043	363	10	fitting	fitting	ADJ
brj-25043	363	11	results	result	NOUN
brj-25043	363	12	determined	determine	VERB
brj-25043	363	13	by	by	ADP
brj-25043	363	14	r²	r²	NOUN
brj-25043	363	15	and	and	CCONJ
brj-25043	363	16	rmse	rmse	NOUN
brj-25043	363	17	.	.	PUNCT
brj-25043	364	1	in	in	ADP
brj-25043	364	2	some	some	DET
brj-25043	364	3	cases	case	NOUN
brj-25043	364	4	,	,	PUNCT
brj-25043	364	5	a	a	DET
brj-25043	364	6	function	function	NOUN
brj-25043	364	7	shows	show	VERB
brj-25043	364	8	a	a	DET
brj-25043	364	9	higher	high	ADJ
brj-25043	364	10	r2	r2	NOUN
brj-25043	364	11	value	value	NOUN
brj-25043	364	12	,	,	PUNCT
brj-25043	364	13	but	but	CCONJ
brj-25043	364	14	it	it	PRON
brj-25043	364	15	is	be	AUX
brj-25043	364	16	excluded	exclude	VERB
brj-25043	364	17	if	if	SCONJ
brj-25043	364	18	its	its	PRON
brj-25043	364	19	curve	curve	NOUN
brj-25043	364	20	does	do	AUX
brj-25043	364	21	not	not	PART
brj-25043	364	22	match	match	VERB
brj-25043	364	23	the	the	DET
brj-25043	364	24	expected	expect	VERB
brj-25043	364	25	behaviour	behaviour	NOUN
brj-25043	364	26	of	of	ADP
brj-25043	364	27	the	the	DET
brj-25043	364	28	experimental	experimental	ADJ
brj-25043	364	29	data	datum	NOUN
brj-25043	364	30	in	in	ADP
brj-25043	364	31	particular	particular	ADJ
brj-25043	364	32	intervals	interval	NOUN
brj-25043	364	33	.	.	PUNCT
brj-25043	365	1	the	the	DET
brj-25043	365	2	previous	previous	ADJ
brj-25043	365	3	curve	curve	NOUN
brj-25043	365	4	fitting	fitting	ADJ
brj-25043	365	5	step	step	NOUN
brj-25043	365	6	will	will	AUX
brj-25043	365	7	be	be	AUX
brj-25043	365	8	repeated	repeat	VERB
brj-25043	365	9	for	for	ADP
brj-25043	365	10	𝑇2	𝑇2	NOUN
brj-25043	365	11	,	,	PUNCT
brj-25043	365	12	𝑇3	𝑇3	PROPN
brj-25043	365	13	,	,	PUNCT
brj-25043	365	14	…	…	PUNCT
brj-25043	365	15	…	…	PUNCT
brj-25043	365	16	.	.	PUNCT
brj-25043	365	17	.	.	PUNCT
brj-25043	366	1	,	,	PUNCT
brj-25043	366	2	𝑇𝑛.	𝑇𝑛.	VERB
brj-25043	366	3	this	this	DET
brj-25043	366	4	yields	yield	VERB
brj-25043	366	5	another	another	PRON
brj-25043	366	6	n	n	ADV
brj-25043	366	7	set	set	NOUN
brj-25043	366	8	of	of	ADP
brj-25043	366	9	parameter	parameter	NOUN
brj-25043	366	10	values	value	NOUN
brj-25043	366	11	varying	vary	VERB
brj-25043	366	12	with	with	ADP
brj-25043	366	13	t	t	PROPN
brj-25043	366	14	,	,	PUNCT
brj-25043	366	15	which	which	PRON
brj-25043	366	16	will	will	AUX
brj-25043	366	17	be	be	AUX
brj-25043	366	18	plotted	plot	VERB
brj-25043	366	19	,	,	PUNCT
brj-25043	366	20	through	through	ADP
brj-25043	366	21	a	a	DET
brj-25043	366	22	third	third	ADJ
brj-25043	366	23	step	step	NOUN
brj-25043	366	24	of	of	ADP
brj-25043	366	25	curve	curve	NOUN
brj-25043	366	26	fitting	fitting	ADJ
brj-25043	366	27	for	for	ADP
brj-25043	366	28	the	the	DET
brj-25043	366	29	best	good	ADJ
brj-25043	366	30	correlation	correlation	NOUN
brj-25043	366	31	,	,	PUNCT
brj-25043	366	32	obtaining	obtain	VERB
brj-25043	366	33	another	another	DET
brj-25043	366	34	function	function	NOUN
brj-25043	366	35	for	for	ADP
brj-25043	366	36	these	these	DET
brj-25043	366	37	parameters	parameter	NOUN
brj-25043	366	38	in	in	ADP
brj-25043	366	39	both	both	DET
brj-25043	366	40	r	r	NOUN
brj-25043	366	41	and	and	CCONJ
brj-25043	366	42	t.	t.	NOUN
brj-25043	366	43	finally	finally	ADV
brj-25043	366	44	,	,	PUNCT
brj-25043	366	45	the	the	DET
brj-25043	366	46	model	model	NOUN
brj-25043	366	47	parameters	parameter	NOUN
brj-25043	366	48	are	be	AUX
brj-25043	366	49	obtained	obtain	VERB
brj-25043	366	50	as	as	ADP
brj-25043	366	51	functions	function	NOUN
brj-25043	366	52	;	;	PUNCT
brj-25043	366	53	i	i	PROPN
brj-25043	366	54	-	-	PUNCT
brj-25043	366	55	e	e	NOUN
brj-25043	366	56	:	:	PUNCT
brj-25043	366	57	=	=	SYM
brj-25043	366	58	𝑓(𝑟	𝑓(𝑟	NOUN
brj-25043	366	59	,	,	PUNCT
brj-25043	366	60	𝑇	𝑇	PROPN
brj-25043	366	61	)	)	PUNCT
brj-25043	366	62	,	,	PUNCT
brj-25043	366	63	=	=	SYM
brj-25043	366	64	𝑔(𝑟	𝑔(𝑟	PROPN
brj-25043	366	65	,	,	PUNCT
brj-25043	366	66	𝑇	𝑇	PROPN
brj-25043	366	67	)	)	PUNCT
brj-25043	366	68	,	,	PUNCT
brj-25043	366	69	and	and	CCONJ
brj-25043	366	70	𝑘	𝑘	X
brj-25043	366	71	=	=	PUNCT
brj-25043	366	72	ℎ(𝑟	ℎ(𝑟	PROPN
brj-25043	366	73	,	,	PUNCT
brj-25043	366	74	𝑇	𝑇	PROPN
brj-25043	366	75	)	)	PUNCT
brj-25043	366	76	.	.	PUNCT
brj-25043	367	1	substituting	substitute	VERB
brj-25043	367	2	these	these	DET
brj-25043	367	3	obtained	obtain	VERB
brj-25043	367	4	functions	function	NOUN
brj-25043	367	5	in	in	ADP
brj-25043	367	6	the	the	DET
brj-25043	367	7	model	model	NOUN
brj-25043	367	8	equation	equation	NOUN
brj-25043	367	9	provides	provide	VERB
brj-25043	367	10	a	a	DET
brj-25043	367	11	multidimensional	multidimensional	ADJ
brj-25043	367	12	version	version	NOUN
brj-25043	367	13	of	of	ADP
brj-25043	367	14	this	this	DET
brj-25043	367	15	model	model	NOUN
brj-25043	367	16	.	.	PUNCT
brj-25043	368	1	this	this	DET
brj-25043	368	2	technique	technique	NOUN
brj-25043	368	3	was	be	AUX
brj-25043	368	4	applied	apply	VERB
brj-25043	368	5	successfully	successfully	ADV
brj-25043	368	6	in	in	ADP
brj-25043	368	7	the	the	DET
brj-25043	368	8	case	case	NOUN
brj-25043	368	9	of	of	ADP
brj-25043	368	10	anaerobic	anaerobic	ADJ
brj-25043	368	11	co	co	ADJ
brj-25043	368	12	-	-	NOUN
brj-25043	368	13	digestion	digestion	NOUN
brj-25043	368	14	process	process	NOUN
brj-25043	368	15	of	of	ADP
brj-25043	368	16	waste	waste	NOUN
brj-25043	368	17	activated	activate	VERB
brj-25043	368	18	sludge	sludge	NOUN
brj-25043	368	19	with	with	ADP
brj-25043	368	20	wheat	wheat	NOUN
brj-25043	368	21	straw	straw	NOUN
brj-25043	368	22	by	by	ADP
brj-25043	368	23	abdel	abdel	PROPN
brj-25043	368	24	daiem	daiem	PROPN
brj-25043	368	25	et	et	PROPN
brj-25043	368	26	al	al	PROPN
brj-25043	368	27	.	.	PROPN
brj-25043	369	1	(	(	PUNCT
brj-25043	369	2	2021	2021	NUM
brj-25043	369	3	)	)	PUNCT
brj-25043	369	4	.	.	PUNCT
brj-25043	370	1	they	they	PRON
brj-25043	370	2	considered	consider	VERB
brj-25043	370	3	time	time	NOUN
brj-25043	370	4	as	as	ADP
brj-25043	370	5	the	the	DET
brj-25043	370	6	first	first	ADJ
brj-25043	370	7	variable	variable	NOUN
brj-25043	370	8	and	and	CCONJ
brj-25043	370	9	mixing	mix	VERB
brj-25043	370	10	ratio	ratio	NOUN
brj-25043	370	11	as	as	ADP
brj-25043	370	12	the	the	DET
brj-25043	370	13	second	second	ADJ
brj-25043	370	14	one	one	NUM
brj-25043	370	15	,	,	PUNCT
brj-25043	370	16	and	and	CCONJ
brj-25043	370	17	then	then	ADV
brj-25043	370	18	biogas	biogas	NOUN
brj-25043	370	19	production	production	NOUN
brj-25043	370	20	was	be	AUX
brj-25043	370	21	expressed	express	VERB
brj-25043	370	22	as	as	ADP
brj-25043	370	23	a	a	DET
brj-25043	370	24	function	function	NOUN
brj-25043	370	25	of	of	ADP
brj-25043	370	26	both	both	DET
brj-25043	370	27	variables	variable	NOUN
brj-25043	370	28	.	.	PUNCT
brj-25043	371	1	this	this	PRON
brj-25043	371	2	was	be	AUX
brj-25043	371	3	applied	apply	VERB
brj-25043	371	4	to	to	ADP
brj-25043	371	5	a	a	DET
brj-25043	371	6	group	group	NOUN
brj-25043	371	7	of	of	ADP
brj-25043	371	8	models	model	NOUN
brj-25043	371	9	that	that	PRON
brj-25043	371	10	contains	contain	VERB
brj-25043	371	11	a	a	DET
brj-25043	371	12	logistic	logistic	ADJ
brj-25043	371	13	kinetic	kinetic	ADJ
brj-25043	371	14	model	model	NOUN
brj-25043	371	15	,	,	PUNCT
brj-25043	371	16	a	a	DET
brj-25043	371	17	modified	modify	VERB
brj-25043	371	18	logistic	logistic	ADJ
brj-25043	371	19	model	model	NOUN
brj-25043	371	20	,	,	PUNCT
brj-25043	371	21	an	an	DET
brj-25043	371	22	exponential	exponential	ADJ
brj-25043	371	23	rise	rise	NOUN
brj-25043	371	24	-	-	PUNCT
brj-25043	371	25	to	to	ADP
brj-25043	371	26	-	-	PUNCT
brj-25043	371	27	maximum	maximum	NOUN
brj-25043	371	28	model	model	NOUN
brj-25043	371	29	,	,	PUNCT
brj-25043	371	30	and	and	CCONJ
brj-25043	371	31	a	a	DET
brj-25043	371	32	modified	modified	ADJ
brj-25043	371	33	gompertz	gompertz	NOUN
brj-25043	371	34	model	model	NOUN
brj-25043	371	35	.	.	PUNCT
brj-25043	372	1	the	the	DET
brj-25043	372	2	introduced	introduce	VERB
brj-25043	372	3	twodimensional	twodimensional	ADJ
brj-25043	372	4	models	model	NOUN
brj-25043	372	5	were	be	AUX
brj-25043	372	6	highly	highly	ADV
brj-25043	372	7	correlated	correlate	VERB
brj-25043	372	8	to	to	ADP
brj-25043	372	9	the	the	DET
brj-25043	372	10	experimental	experimental	ADJ
brj-25043	372	11	data	datum	NOUN
brj-25043	372	12	,	,	PUNCT
brj-25043	372	13	as	as	SCONJ
brj-25043	372	14	the	the	DET
brj-25043	372	15	r2	r2	NOUN
brj-25043	372	16	ranged	range	VERB
brj-25043	372	17	from	from	ADP
brj-25043	372	18	0.9753	0.9753	NUM
brj-25043	372	19	to	to	ADP
brj-25043	372	20	0.9879	0.9879	NUM
brj-25043	372	21	.	.	PUNCT
brj-25043	373	1	extending	extend	VERB
brj-25043	373	2	this	this	DET
brj-25043	373	3	strategy	strategy	NOUN
brj-25043	373	4	to	to	ADP
brj-25043	373	5	hybrid	hybrid	ADJ
brj-25043	373	6	mechanistic‑machine‑learning	mechanistic‑machine‑learne	VERB
brj-25043	373	7	surrogates	surrogate	NOUN
brj-25043	373	8	could	could	AUX
brj-25043	373	9	reduce	reduce	VERB
brj-25043	373	10	data	data	NOUN
brj-25043	373	11	requirements	requirement	NOUN
brj-25043	373	12	while	while	SCONJ
brj-25043	373	13	maintaining	maintain	VERB
brj-25043	373	14	physical	physical	ADJ
brj-25043	373	15	interpretability	interpretability	NOUN
brj-25043	373	16	.	.	PUNCT
brj-25043	374	1	however	however	ADV
brj-25043	374	2	,	,	PUNCT
brj-25043	374	3	the	the	DET
brj-25043	374	4	same	same	ADJ
brj-25043	374	5	concept	concept	NOUN
brj-25043	374	6	explained	explain	VERB
brj-25043	374	7	above	above	ADV
brj-25043	374	8	can	can	AUX
brj-25043	374	9	be	be	AUX
brj-25043	374	10	applied	apply	VERB
brj-25043	374	11	to	to	PART
brj-25043	374	12	include	include	VERB
brj-25043	374	13	more	more	ADJ
brj-25043	374	14	variables	variable	NOUN
brj-25043	374	15	as	as	ADP
brj-25043	374	16	inputs	input	NOUN
brj-25043	374	17	and	and	CCONJ
brj-25043	374	18	be	be	AUX
brj-25043	374	19	extended	extend	VERB
brj-25043	374	20	to	to	ADP
brj-25043	374	21	all	all	DET
brj-25043	374	22	the	the	DET
brj-25043	374	23	known	know	VERB
brj-25043	374	24	models	model	NOUN
brj-25043	374	25	.	.	PUNCT
brj-25043	375	1	machine	machine	NOUN
brj-25043	375	2	learning	learn	VERB
brj-25043	375	3	despite	despite	SCONJ
brj-25043	375	4	the	the	DET
brj-25043	375	5	growing	grow	VERB
brj-25043	375	6	use	use	NOUN
brj-25043	375	7	of	of	ADP
brj-25043	375	8	anns	anns	NOUN
brj-25043	375	9	in	in	ADP
brj-25043	375	10	modelling	model	VERB
brj-25043	375	11	biogas	biogas	NOUN
brj-25043	375	12	production	production	NOUN
brj-25043	375	13	,	,	PUNCT
brj-25043	375	14	several	several	ADJ
brj-25043	375	15	research	research	NOUN
brj-25043	375	16	gaps	gap	NOUN
brj-25043	375	17	remain	remain	VERB
brj-25043	375	18	.	.	PUNCT
brj-25043	376	1	most	most	ADJ
brj-25043	376	2	existing	exist	VERB
brj-25043	376	3	studies	study	NOUN
brj-25043	376	4	are	be	AUX
brj-25043	376	5	based	base	VERB
brj-25043	376	6	on	on	ADP
brj-25043	376	7	small	small	ADJ
brj-25043	376	8	-	-	PUNCT
brj-25043	376	9	scale	scale	NOUN
brj-25043	376	10	,	,	PUNCT
brj-25043	376	11	laboratory	laboratory	NOUN
brj-25043	376	12	,	,	PUNCT
brj-25043	376	13	or	or	CCONJ
brj-25043	376	14	pilot	pilot	NOUN
brj-25043	376	15	datasets	dataset	NOUN
brj-25043	376	16	,	,	PUNCT
brj-25043	376	17	which	which	PRON
brj-25043	376	18	may	may	AUX
brj-25043	376	19	not	not	PART
brj-25043	376	20	accurately	accurately	ADV
brj-25043	376	21	reflect	reflect	VERB
brj-25043	376	22	the	the	DET
brj-25043	376	23	variability	variability	NOUN
brj-25043	376	24	and	and	CCONJ
brj-25043	376	25	complexity	complexity	NOUN
brj-25043	376	26	of	of	ADP
brj-25043	376	27	full	full	ADJ
brj-25043	376	28	-	-	PUNCT
brj-25043	376	29	scale	scale	NOUN
brj-25043	376	30	ad	ad	NOUN
brj-25043	376	31	systems	system	NOUN
brj-25043	376	32	.	.	PUNCT
brj-25043	377	1	moreover	moreover	ADV
brj-25043	377	2	,	,	PUNCT
brj-25043	377	3	many	many	ADJ
brj-25043	377	4	models	model	NOUN
brj-25043	377	5	lack	lack	VERB
brj-25043	377	6	external	external	ADJ
brj-25043	377	7	validation	validation	NOUN
brj-25043	377	8	,	,	PUNCT
brj-25043	377	9	limiting	limit	VERB
brj-25043	377	10	their	their	PRON
brj-25043	377	11	generalizability	generalizability	NOUN
brj-25043	377	12	across	across	ADP
brj-25043	377	13	different	different	ADJ
brj-25043	377	14	feedstocks	feedstock	NOUN
brj-25043	377	15	,	,	PUNCT
brj-25043	377	16	climates	climate	NOUN
brj-25043	377	17	,	,	PUNCT
brj-25043	377	18	and	and	CCONJ
brj-25043	377	19	reactor	reactor	NOUN
brj-25043	377	20	types	type	NOUN
brj-25043	377	21	.	.	PUNCT
brj-25043	378	1	few	few	ADJ
brj-25043	378	2	studies	study	NOUN
brj-25043	378	3	have	have	AUX
brj-25043	378	4	addressed	address	VERB
brj-25043	378	5	temporal	temporal	ADJ
brj-25043	378	6	dynamics	dynamic	NOUN
brj-25043	378	7	in	in	ADP
brj-25043	378	8	biogas	biogas	NOUN
brj-25043	378	9	production	production	NOUN
brj-25043	378	10	,	,	PUNCT
brj-25043	378	11	such	such	ADJ
brj-25043	378	12	as	as	ADP
brj-25043	378	13	seasonality	seasonality	NOUN
brj-25043	378	14	or	or	CCONJ
brj-25043	378	15	real	real	ADJ
brj-25043	378	16	-	-	PUNCT
brj-25043	378	17	time	time	NOUN
brj-25043	378	18	operational	operational	ADJ
brj-25043	378	19	fluctuations	fluctuation	NOUN
brj-25043	378	20	.	.	PUNCT
brj-25043	379	1	additionally	additionally	ADV
brj-25043	379	2	,	,	PUNCT
brj-25043	379	3	the	the	DET
brj-25043	379	4	integration	integration	NOUN
brj-25043	379	5	of	of	ADP
brj-25043	379	6	ann	ann	PROPN
brj-25043	379	7	with	with	ADP
brj-25043	379	8	other	other	ADJ
brj-25043	379	9	advanced	advanced	ADJ
brj-25043	379	10	methods	method	NOUN
brj-25043	379	11	—	—	PUNCT
brj-25043	379	12	such	such	ADJ
brj-25043	379	13	as	as	ADP
brj-25043	379	14	hybrid	hybrid	ADJ
brj-25043	379	15	ml	ml	NOUN
brj-25043	379	16	models	model	NOUN
brj-25043	379	17	(	(	PUNCT
brj-25043	379	18	e.g.	e.g.	ADV
brj-25043	379	19	,	,	PUNCT
brj-25043	379	20	ann	ann	PROPN
brj-25043	379	21	-	-	PUNCT
brj-25043	379	22	ga	ga	PROPN
brj-25043	379	23	,	,	PUNCT
brj-25043	379	24	ann	ann	PROPN
brj-25043	379	25	-	-	PUNCT
brj-25043	379	26	pso	pso	NOUN
brj-25043	379	27	)	)	PUNCT
brj-25043	379	28	,	,	PUNCT
brj-25043	379	29	deep	deep	ADJ
brj-25043	379	30	learning	learning	NOUN
brj-25043	379	31	frameworks	framework	NOUN
brj-25043	379	32	(	(	PUNCT
brj-25043	379	33	e.g.	e.g.	ADV
brj-25043	379	34	,	,	PUNCT
brj-25043	379	35	lstm	lstm	PROPN
brj-25043	379	36	,	,	PUNCT
brj-25043	379	37	cnn	cnn	PROPN
brj-25043	379	38	)	)	PUNCT
brj-25043	379	39	,	,	PUNCT
brj-25043	379	40	and	and	CCONJ
brj-25043	379	41	internet	internet	NOUN
brj-25043	379	42	of	of	ADP
brj-25043	379	43	things	thing	NOUN
brj-25043	379	44	(	(	PUNCT
brj-25043	379	45	iot)-based	iot)-based	ADJ
brj-25043	379	46	sensor	sensor	NOUN
brj-25043	379	47	networks	network	NOUN
brj-25043	379	48	—	—	PUNCT
brj-25043	379	49	is	be	AUX
brj-25043	379	50	still	still	ADV
brj-25043	379	51	in	in	ADP
brj-25043	379	52	its	its	PRON
brj-25043	379	53	early	early	ADJ
brj-25043	379	54	stages	stage	NOUN
brj-25043	379	55	.	.	PUNCT
brj-25043	380	1	there	there	PRON
brj-25043	380	2	is	be	VERB
brj-25043	380	3	also	also	ADV
brj-25043	380	4	a	a	DET
brj-25043	380	5	need	need	NOUN
brj-25043	380	6	for	for	ADP
brj-25043	380	7	explainable	explainable	ADJ
brj-25043	380	8	ai	ai	NOUN
brj-25043	380	9	techniques	technique	NOUN
brj-25043	380	10	to	to	PART
brj-25043	380	11	enhance	enhance	VERB
brj-25043	380	12	the	the	DET
brj-25043	380	13	interpretability	interpretability	NOUN
brj-25043	380	14	of	of	ADP
brj-25043	380	15	ann	ann	PROPN
brj-25043	380	16	predictions	prediction	NOUN
brj-25043	380	17	for	for	ADP
brj-25043	380	18	plant	plant	NOUN
brj-25043	380	19	operators	operator	NOUN
brj-25043	380	20	and	and	CCONJ
brj-25043	380	21	decision	decision	NOUN
brj-25043	380	22	-	-	PUNCT
brj-25043	380	23	makers	maker	NOUN
brj-25043	380	24	.	.	PUNCT
brj-25043	381	1	future	future	ADJ
brj-25043	381	2	extensions	extension	NOUN
brj-25043	381	3	should	should	AUX
brj-25043	381	4	focus	focus	VERB
brj-25043	381	5	on	on	ADP
brj-25043	381	6	developing	develop	VERB
brj-25043	381	7	adaptive	adaptive	ADJ
brj-25043	381	8	,	,	PUNCT
brj-25043	381	9	self	self	NOUN
brj-25043	381	10	-	-	PUNCT
brj-25043	381	11	learning	learn	VERB
brj-25043	381	12	ann	ann	PROPN
brj-25043	381	13	models	model	NOUN
brj-25043	381	14	capable	capable	ADJ
brj-25043	381	15	of	of	ADP
brj-25043	381	16	real	real	ADJ
brj-25043	381	17	-	-	PUNCT
brj-25043	381	18	time	time	NOUN
brj-25043	381	19	prediction	prediction	NOUN
brj-25043	381	20	and	and	CCONJ
brj-25043	381	21	control	control	NOUN
brj-25043	381	22	and	and	CCONJ
brj-25043	381	23	trained	train	VERB
brj-25043	381	24	on	on	ADP
brj-25043	381	25	diverse	diverse	ADJ
brj-25043	381	26	and	and	CCONJ
brj-25043	381	27	large	large	ADJ
brj-25043	381	28	-	-	PUNCT
brj-25043	381	29	scale	scale	NOUN
brj-25043	381	30	datasets	dataset	NOUN
brj-25043	381	31	.	.	PUNCT
brj-25043	382	1	furthermore	furthermore	ADV
brj-25043	382	2	,	,	PUNCT
brj-25043	382	3	coupling	couple	VERB
brj-25043	382	4	ann	ann	PROPN
brj-25043	382	5	models	model	NOUN
brj-25043	382	6	with	with	ADP
brj-25043	382	7	life	life	NOUN
brj-25043	382	8	cycle	cycle	NOUN
brj-25043	382	9	assessment	assessment	NOUN
brj-25043	382	10	(	(	PUNCT
brj-25043	382	11	lca	lca	PROPN
brj-25043	382	12	)	)	PUNCT
brj-25043	382	13	and	and	CCONJ
brj-25043	382	14	techno	techno	NOUN
brj-25043	382	15	-	-	PUNCT
brj-25043	382	16	economic	economic	ADJ
brj-25043	382	17	analysis	analysis	NOUN
brj-25043	382	18	(	(	PUNCT
brj-25043	382	19	tea	tea	NOUN
brj-25043	382	20	)	)	PUNCT
brj-25043	382	21	tools	tool	NOUN
brj-25043	382	22	can	can	AUX
brj-25043	382	23	provide	provide	VERB
brj-25043	382	24	a	a	DET
brj-25043	382	25	more	more	ADV
brj-25043	382	26	holistic	holistic	ADJ
brj-25043	382	27	understanding	understanding	NOUN
brj-25043	382	28	of	of	ADP
brj-25043	382	29	sustainability	sustainability	NOUN
brj-25043	382	30	and	and	CCONJ
brj-25043	382	31	system	system	NOUN
brj-25043	382	32	performance	performance	NOUN
brj-25043	382	33	.	.	PUNCT
brj-25043	383	1	these	these	DET
brj-25043	383	2	improvements	improvement	NOUN
brj-25043	383	3	would	would	AUX
brj-25043	383	4	significantly	significantly	ADV
brj-25043	383	5	enhance	enhance	VERB
brj-25043	383	6	the	the	DET
brj-25043	383	7	operational	operational	ADJ
brj-25043	383	8	reliability	reliability	NOUN
brj-25043	383	9	,	,	PUNCT
brj-25043	383	10	economic	economic	ADJ
brj-25043	383	11	viability	viability	NOUN
brj-25043	383	12	,	,	PUNCT
brj-25043	383	13	and	and	CCONJ
brj-25043	383	14	environmental	environmental	ADJ
brj-25043	383	15	benefits	benefit	NOUN
brj-25043	383	16	of	of	ADP
brj-25043	383	17	biogas	biogas	NOUN
brj-25043	383	18	systems	system	NOUN
brj-25043	383	19	,	,	PUNCT
brj-25043	383	20	especially	especially	ADV
brj-25043	383	21	in	in	ADP
brj-25043	383	22	decentralized	decentralized	ADJ
brj-25043	383	23	rural	rural	ADJ
brj-25043	383	24	and	and	CCONJ
brj-25043	383	25	urban	urban	ADJ
brj-25043	383	26	applications	application	NOUN
brj-25043	383	27	.	.	PUNCT
brj-25043	384	1	future	future	ADJ
brj-25043	384	2	research	research	NOUN
brj-25043	384	3	should	should	AUX
brj-25043	384	4	focus	focus	VERB
brj-25043	384	5	on	on	ADP
brj-25043	384	6	developing	develop	VERB
brj-25043	384	7	hybrid	hybrid	ADJ
brj-25043	384	8	models	model	NOUN
brj-25043	384	9	that	that	PRON
brj-25043	384	10	combine	combine	VERB
brj-25043	384	11	the	the	DET
brj-25043	384	12	strengths	strength	NOUN
brj-25043	384	13	of	of	ADP
brj-25043	384	14	multiple	multiple	ADJ
brj-25043	384	15	ml	ml	NOUN
brj-25043	384	16	techniques	technique	NOUN
brj-25043	384	17	(	(	PUNCT
brj-25043	384	18	e.g.	e.g.	ADV
brj-25043	384	19	,	,	PUNCT
brj-25043	384	20	ann	ann	PROPN
brj-25043	384	21	-	-	PUNCT
brj-25043	384	22	ga	ga	PROPN
brj-25043	384	23	,	,	PUNCT
brj-25043	384	24	rf	rf	NOUN
brj-25043	384	25	-	-	NOUN
brj-25043	384	26	pso	pso	NOUN
brj-25043	384	27	,	,	PUNCT
brj-25043	384	28	or	or	CCONJ
brj-25043	384	29	lstm	lstm	NOUN
brj-25043	384	30	-	-	PUNCT
brj-25043	384	31	cnn	cnn	PROPN
brj-25043	384	32	)	)	PUNCT
brj-25043	384	33	to	to	PART
brj-25043	384	34	enhance	enhance	VERB
brj-25043	384	35	robustness	robustness	NOUN
brj-25043	384	36	and	and	CCONJ
brj-25043	384	37	generalizability	generalizability	NOUN
brj-25043	384	38	.	.	PUNCT
brj-25043	385	1	there	there	PRON
brj-25043	385	2	is	be	VERB
brj-25043	385	3	also	also	ADV
brj-25043	385	4	significant	significant	ADJ
brj-25043	385	5	potential	potential	NOUN
brj-25043	385	6	in	in	ADP
brj-25043	385	7	integrating	integrate	VERB
brj-25043	385	8	ml	ml	NOUN
brj-25043	385	9	with	with	ADP
brj-25043	385	10	iot	iot	ADJ
brj-25043	385	11	sensors	sensor	NOUN
brj-25043	385	12	for	for	ADP
brj-25043	385	13	real	real	ADJ
brj-25043	385	14	-	-	PUNCT
brj-25043	385	15	time	time	NOUN
brj-25043	385	16	monitoring	monitoring	NOUN
brj-25043	385	17	,	,	PUNCT
brj-25043	385	18	as	as	ADV
brj-25043	385	19	well	well	ADV
brj-25043	385	20	as	as	ADP
brj-25043	385	21	with	with	ADP
brj-25043	385	22	lca	lca	PROPN
brj-25043	385	23	or	or	CCONJ
brj-25043	385	24	tea	tea	NOUN
brj-25043	385	25	to	to	PART
brj-25043	385	26	evaluate	evaluate	VERB
brj-25043	385	27	sustainability	sustainability	NOUN
brj-25043	385	28	and	and	CCONJ
brj-25043	385	29	economic	economic	ADJ
brj-25043	385	30	performance	performance	NOUN
brj-25043	385	31	.	.	PUNCT
brj-25043	386	1	additionally	additionally	ADV
brj-25043	386	2	,	,	PUNCT
brj-25043	386	3	explainable	explainable	ADJ
brj-25043	386	4	ai	ai	NOUN
brj-25043	386	5	(	(	PUNCT
brj-25043	386	6	xai	xai	PROPN
brj-25043	386	7	)	)	PUNCT
brj-25043	386	8	can	can	AUX
brj-25043	386	9	improve	improve	VERB
brj-25043	386	10	model	model	NOUN
brj-25043	386	11	transparency	transparency	NOUN
brj-25043	386	12	and	and	CCONJ
brj-25043	386	13	stakeholder	stakeholder	NOUN
brj-25043	386	14	confidence	confidence	NOUN
brj-25043	386	15	.	.	PUNCT
brj-25043	387	1	through	through	ADP
brj-25043	387	2	addressing	address	VERB
brj-25043	387	3	these	these	DET
brj-25043	387	4	gaps	gap	NOUN
brj-25043	387	5	,	,	PUNCT
brj-25043	387	6	ml	ml	VERB
brj-25043	387	7	can	can	AUX
brj-25043	387	8	play	play	VERB
brj-25043	387	9	a	a	DET
brj-25043	387	10	transformative	transformative	ADJ
brj-25043	387	11	role	role	NOUN
brj-25043	387	12	in	in	ADP
brj-25043	387	13	optimizing	optimize	VERB
brj-25043	387	14	biogas	biogas	NOUN
brj-25043	387	15	systems	system	NOUN
brj-25043	387	16	,	,	PUNCT
brj-25043	387	17	improving	improve	VERB
brj-25043	387	18	resource	resource	NOUN
brj-25043	387	19	efficiency	efficiency	NOUN
brj-25043	387	20	,	,	PUNCT
brj-25043	387	21	and	and	CCONJ
brj-25043	387	22	peer	peer	NOUN
brj-25043	387	23	-	-	PUNCT
brj-25043	387	24	reviewed	review	VERB
brj-25043	387	25	review	review	NOUN
brj-25043	387	26	article	article	NOUN
brj-25043	387	27	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	387	28	galal	galal	PROPN
brj-25043	387	29	et	et	PROPN
brj-25043	387	30	al	al	PROPN
brj-25043	387	31	.	.	PROPN
brj-25043	388	1	(	(	PUNCT
brj-25043	388	2	2025	2025	NUM
brj-25043	388	3	)	)	PUNCT
brj-25043	388	4	.	.	PUNCT
brj-25043	389	1	“	"	PUNCT
brj-25043	389	2	math	math	NOUN
brj-25043	389	3	modeling	modeling	NOUN
brj-25043	389	4	biogas	biogas	NOUN
brj-25043	389	5	production	production	NOUN
brj-25043	389	6	,	,	PUNCT
brj-25043	389	7	”	"	PUNCT
brj-25043	389	8	bioresources	bioresource	NOUN
brj-25043	389	9	20(4	20(4	NOUN
brj-25043	389	10	)	)	PUNCT
brj-25043	389	11	,	,	PUNCT
brj-25043	389	12	11237	11237	NUM
brj-25043	389	13	-	-	SYM
brj-25043	389	14	11266	11266	NUM
brj-25043	389	15	.	.	PUNCT
brj-25043	390	1	11259	11259	NUM
brj-25043	390	2	supporting	support	VERB
brj-25043	390	3	climate	climate	NOUN
brj-25043	390	4	-	-	PUNCT
brj-25043	390	5	resilient	resilient	ADJ
brj-25043	390	6	waste	waste	NOUN
brj-25043	390	7	management	management	NOUN
brj-25043	390	8	strategies	strategy	NOUN
brj-25043	390	9	,	,	PUNCT
brj-25043	390	10	particularly	particularly	ADV
brj-25043	390	11	in	in	ADP
brj-25043	390	12	countries	country	NOUN
brj-25043	390	13	with	with	ADP
brj-25043	390	14	abundant	abundant	ADJ
brj-25043	390	15	biomass	biomass	NOUN
brj-25043	390	16	resources	resource	NOUN
brj-25043	390	17	.	.	PUNCT
brj-25043	391	1	beyond	beyond	ADP
brj-25043	391	2	laboratory	laboratory	NOUN
brj-25043	391	3	datasets	dataset	NOUN
brj-25043	391	4	,	,	PUNCT
brj-25043	391	5	several	several	ADJ
brj-25043	391	6	full	full	ADJ
brj-25043	391	7	-	-	PUNCT
brj-25043	391	8	scale	scale	NOUN
brj-25043	391	9	and	and	CCONJ
brj-25043	391	10	pilot	pilot	NOUN
brj-25043	391	11	studies	study	NOUN
brj-25043	391	12	demonstrate	demonstrate	VERB
brj-25043	391	13	operational	operational	ADJ
brj-25043	391	14	value	value	NOUN
brj-25043	391	15	from	from	ADP
brj-25043	391	16	ml	ml	NOUN
brj-25043	391	17	in	in	ADP
brj-25043	391	18	live	live	ADJ
brj-25043	391	19	operating	operating	NOUN
brj-25043	391	20	biogas	biogas	NOUN
brj-25043	391	21	plants	plant	NOUN
brj-25043	391	22	.	.	PUNCT
brj-25043	392	1	in	in	ADP
brj-25043	392	2	an	an	DET
brj-25043	392	3	industrial	industrial	ADJ
brj-25043	392	4	-	-	PUNCT
brj-25043	392	5	scale	scale	NOUN
brj-25043	392	6	ad	ad	NOUN
brj-25043	392	7	facility	facility	NOUN
brj-25043	392	8	,	,	PUNCT
brj-25043	392	9	tree	tree	NOUN
brj-25043	392	10	-	-	PUNCT
brj-25043	392	11	based	base	VERB
brj-25043	392	12	models	model	NOUN
brj-25043	392	13	achieved	achieve	VERB
brj-25043	392	14	high	high	ADJ
brj-25043	392	15	forecasting	forecasting	NOUN
brj-25043	392	16	accuracy	accuracy	NOUN
brj-25043	392	17	(	(	PUNCT
brj-25043	392	18	rf	rf	ADJ
brj-25043	392	19	,	,	PUNCT
brj-25043	392	20	r²	r²	VERB
brj-25043	392	21	≈	≈	PROPN
brj-25043	392	22	0.924	0.924	NUM
brj-25043	392	23	)	)	PUNCT
brj-25043	392	24	,	,	PUNCT
brj-25043	392	25	supporting	support	VERB
brj-25043	392	26	routine	routine	ADJ
brj-25043	392	27	set	set	NOUN
brj-25043	392	28	-	-	PUNCT
brj-25043	392	29	point	point	NOUN
brj-25043	392	30	decisions	decision	NOUN
brj-25043	392	31	(	(	PUNCT
brj-25043	392	32	yildirim	yildirim	NOUN
brj-25043	392	33	and	and	CCONJ
brj-25043	392	34	ozkaya	ozkaya	NOUN
brj-25043	392	35	2023	2023	NUM
brj-25043	392	36	)	)	PUNCT
brj-25043	392	37	.	.	PUNCT
brj-25043	393	1	in	in	ADP
brj-25043	393	2	a	a	DET
brj-25043	393	3	full	full	ADJ
brj-25043	393	4	-	-	PUNCT
brj-25043	393	5	scale	scale	NOUN
brj-25043	393	6	wwtp	wwtp	NOUN
brj-25043	393	7	digester	digester	NOUN
brj-25043	393	8	,	,	PUNCT
brj-25043	393	9	an	an	DET
brj-25043	393	10	ensemble	ensemble	ADJ
brj-25043	393	11	approach	approach	NOUN
brj-25043	393	12	delivered	deliver	VERB
brj-25043	393	13	usable	usable	ADJ
brj-25043	393	14	accuracy	accuracy	NOUN
brj-25043	393	15	(	(	PUNCT
brj-25043	393	16	r²	r²	NOUN
brj-25043	393	17	=	=	SYM
brj-25043	393	18	0.778	0.778	NUM
brj-25043	393	19	;	;	PUNCT
brj-25043	393	20	rmse	rmse	NOUN
brj-25043	393	21	=	=	PROPN
brj-25043	393	22	0.306	0.306	NOUN
brj-25043	393	23	)	)	PUNCT
brj-25043	393	24	,	,	PUNCT
brj-25043	393	25	with	with	ADP
brj-25043	393	26	temperature	temperature	NOUN
brj-25043	393	27	and	and	CCONJ
brj-25043	393	28	return	return	NOUN
brj-25043	393	29	sludge	sludge	NOUN
brj-25043	393	30	emerging	emerge	VERB
brj-25043	393	31	as	as	ADP
brj-25043	393	32	key	key	ADJ
brj-25043	393	33	levers	lever	NOUN
brj-25043	393	34	(	(	PUNCT
brj-25043	393	35	sun	sun	PROPN
brj-25043	393	36	et	et	PROPN
brj-25043	393	37	al	al	PROPN
brj-25043	393	38	.	.	PROPN
brj-25043	393	39	2023	2023	NUM
brj-25043	393	40	)	)	PUNCT
brj-25043	393	41	.	.	PUNCT
brj-25043	394	1	across	across	ADP
brj-25043	394	2	four	four	NUM
brj-25043	394	3	dryad	dryad	NOUN
brj-25043	394	4	plants	plant	NOUN
brj-25043	394	5	processing	processing	NOUN
brj-25043	394	6	kitchen	kitchen	NOUN
brj-25043	394	7	waste	waste	NOUN
brj-25043	394	8	,	,	PUNCT
brj-25043	394	9	catboost	catboost	NOUN
brj-25043	394	10	models	model	NOUN
brj-25043	394	11	reached	reach	VERB
brj-25043	394	12	r²	r²	NOUN
brj-25043	394	13	=	=	SYM
brj-25043	394	14	0.604–0.915	0.604–0.915	NUM
brj-25043	394	15	for	for	ADP
brj-25043	394	16	biogas	biogas	NOUN
brj-25043	394	17	and	and	CCONJ
brj-25043	394	18	enabled	enable	VERB
brj-25043	394	19	a	a	DET
brj-25043	394	20	vfa	vfa	PROPN
brj-25043	394	21	/	/	SYM
brj-25043	394	22	alk	alk	VERB
brj-25043	394	23	soft	soft	ADJ
brj-25043	394	24	sensor	sensor	NOUN
brj-25043	394	25	to	to	PART
brj-25043	394	26	anticipate	anticipate	VERB
brj-25043	394	27	instability	instability	NOUN
brj-25043	394	28	(	(	PUNCT
brj-25043	394	29	zou	zou	PROPN
brj-25043	394	30	et	et	PROPN
brj-25043	394	31	al	al	PROPN
brj-25043	394	32	.	.	PROPN
brj-25043	394	33	2024	2024	NUM
brj-25043	394	34	)	)	PUNCT
brj-25043	394	35	.	.	PUNCT
brj-25043	395	1	a	a	DET
brj-25043	395	2	largescale	largescale	NOUN
brj-25043	395	3	study	study	NOUN
brj-25043	395	4	coupling	couple	VERB
brj-25043	395	5	lstm	lstm	NOUN
brj-25043	395	6	with	with	ADP
brj-25043	395	7	genetic	genetic	ADJ
brj-25043	395	8	algorithms	algorithm	NOUN
brj-25043	395	9	improved	improve	VERB
brj-25043	395	10	short	short	ADJ
brj-25043	395	11	-	-	PUNCT
brj-25043	395	12	term	term	NOUN
brj-25043	395	13	prediction	prediction	NOUN
brj-25043	395	14	(	(	PUNCT
brj-25043	395	15	r²	r²	VERB
brj-25043	395	16	≈	≈	PROPN
brj-25043	395	17	0.84–0.90	0.84–0.90	NOUN
brj-25043	395	18	)	)	PUNCT
brj-25043	395	19	and	and	CCONJ
brj-25043	395	20	highlighted	highlight	VERB
brj-25043	395	21	hrt	hrt	PROPN
brj-25043	395	22	sensitivity	sensitivity	NOUN
brj-25043	395	23	(	(	PUNCT
brj-25043	395	24	salamattalab	salamattalab	NOUN
brj-25043	395	25	et	et	PROPN
brj-25043	395	26	al	al	PROPN
brj-25043	395	27	.	.	PROPN
brj-25043	395	28	2024	2024	NUM
brj-25043	395	29	)	)	PUNCT
brj-25043	395	30	.	.	PUNCT
brj-25043	396	1	for	for	ADP
brj-25043	396	2	municipal	municipal	ADJ
brj-25043	396	3	codigestion	codigestion	NOUN
brj-25043	396	4	,	,	PUNCT
brj-25043	396	5	deep	deep	ADJ
brj-25043	396	6	models	model	NOUN
brj-25043	396	7	with	with	ADP
brj-25043	396	8	data	data	NOUN
brj-25043	396	9	-	-	PUNCT
brj-25043	396	10	augmentation	augmentation	NOUN
brj-25043	396	11	and	and	CCONJ
brj-25043	396	12	variable	variable	ADJ
brj-25043	396	13	-	-	PUNCT
brj-25043	396	14	selection	selection	NOUN
brj-25043	396	15	networks	network	NOUN
brj-25043	396	16	increased	increase	VERB
brj-25043	396	17	robustness	robustness	NOUN
brj-25043	396	18	under	under	ADP
brj-25043	396	19	missing	miss	VERB
brj-25043	396	20	data	datum	NOUN
brj-25043	396	21	(	(	PUNCT
brj-25043	396	22	e.g.	e.g.	ADV
brj-25043	396	23	,	,	PUNCT
brj-25043	396	24	lstm	lstm	NOUN
brj-25043	396	25	→	→	SYM
brj-25043	396	26	da	da	ADJ
brj-25043	396	27	-	-	PUNCT
brj-25043	396	28	lstm	lstm	PROPN
brj-25043	396	29	-	-	PUNCT
brj-25043	396	30	vsn	vsn	NOUN
brj-25043	396	31	,	,	PUNCT
brj-25043	396	32	r²	r²	VERB
brj-25043	396	33	from	from	ADP
brj-25043	396	34	0.38	0.38	NUM
brj-25043	396	35	to	to	ADP
brj-25043	396	36	0.76	0.76	NUM
brj-25043	396	37	)	)	PUNCT
brj-25043	396	38	,	,	PUNCT
brj-25043	396	39	clarifying	clarify	VERB
brj-25043	396	40	driver	driver	NOUN
brj-25043	396	41	importance	importance	NOUN
brj-25043	396	42	for	for	ADP
brj-25043	396	43	operators	operator	NOUN
brj-25043	396	44	(	(	PUNCT
brj-25043	396	45	jeong	jeong	PROPN
brj-25043	396	46	et	et	PROPN
brj-25043	396	47	al	al	PROPN
brj-25043	396	48	.	.	PROPN
brj-25043	396	49	2021	2021	NUM
brj-25043	396	50	)	)	PUNCT
brj-25043	396	51	.	.	PUNCT
brj-25043	397	1	similarly	similarly	ADV
brj-25043	397	2	,	,	PUNCT
brj-25043	397	3	feature	feature	NOUN
brj-25043	397	4	-	-	PUNCT
brj-25043	397	5	engineered	engineer	VERB
brj-25043	397	6	mlps	mlp	NOUN
brj-25043	397	7	using	use	VERB
brj-25043	397	8	minute	minute	NOUN
brj-25043	397	9	-	-	PUNCT
brj-25043	397	10	rate	rate	NOUN
brj-25043	397	11	scada	scada	PROPN
brj-25043	397	12	achieved	achieve	VERB
brj-25043	397	13	an	an	DET
brj-25043	397	14	adjusted	adjust	VERB
brj-25043	397	15	r²	r²	NOUN
brj-25043	397	16	≈	≈	PROPN
brj-25043	397	17	of	of	ADP
brj-25043	397	18	0.78	0.78	NUM
brj-25043	397	19	(	(	PUNCT
brj-25043	397	20	mape	mape	NOUN
brj-25043	397	21	≈	≈	PROPN
brj-25043	397	22	13.4	13.4	NUM
brj-25043	397	23	%	%	NOUN
brj-25043	397	24	)	)	PUNCT
brj-25043	397	25	,	,	PUNCT
brj-25043	397	26	showing	show	VERB
brj-25043	397	27	that	that	SCONJ
brj-25043	397	28	soft	soft	ADJ
brj-25043	397	29	-	-	PUNCT
brj-25043	397	30	sensor	sensor	NOUN
brj-25043	397	31	surrogates	surrogate	NOUN
brj-25043	397	32	can	can	AUX
brj-25043	397	33	approach	approach	VERB
brj-25043	397	34	lab	lab	NOUN
brj-25043	397	35	-	-	PUNCT
brj-25043	397	36	assisted	assist	VERB
brj-25043	397	37	baselines	baseline	NOUN
brj-25043	397	38	(	(	PUNCT
brj-25043	397	39	schroer	schroer	NOUN
brj-25043	397	40	and	and	CCONJ
brj-25043	397	41	just	just	ADV
brj-25043	397	42	2023	2023	NUM
brj-25043	397	43	)	)	PUNCT
brj-25043	397	44	.	.	PUNCT
brj-25043	398	1	from	from	ADP
brj-25043	398	2	prediction	prediction	NOUN
brj-25043	398	3	to	to	ADP
brj-25043	398	4	sustainability	sustainability	NOUN
brj-25043	398	5	metrics	metric	NOUN
brj-25043	398	6	(	(	PUNCT
brj-25043	398	7	lca	lca	PROPN
brj-25043	398	8	/	/	SYM
brj-25043	398	9	tea	tea	NOUN
brj-25043	398	10	)	)	PUNCT
brj-25043	398	11	linking	link	VERB
brj-25043	398	12	ml	ml	ADP
brj-25043	398	13	outputs	output	NOUN
brj-25043	398	14	to	to	ADP
brj-25043	398	15	sustainability	sustainability	NOUN
brj-25043	398	16	assessment	assessment	NOUN
brj-25043	398	17	enhances	enhance	VERB
brj-25043	398	18	the	the	DET
brj-25043	398	19	relevance	relevance	NOUN
brj-25043	398	20	of	of	ADP
brj-25043	398	21	predictive	predictive	ADJ
brj-25043	398	22	modelling	modelling	NOUN
brj-25043	398	23	in	in	ADP
brj-25043	398	24	decision	decision	NOUN
brj-25043	398	25	-	-	PUNCT
brj-25043	398	26	making	making	NOUN
brj-25043	398	27	by	by	ADP
brj-25043	398	28	translating	translate	VERB
brj-25043	398	29	results	result	NOUN
brj-25043	398	30	into	into	ADP
brj-25043	398	31	policy	policy	NOUN
brj-25043	398	32	and	and	CCONJ
brj-25043	398	33	financial	financial	ADJ
brj-25043	398	34	metrics	metric	NOUN
brj-25043	398	35	.	.	PUNCT
brj-25043	399	1	in	in	ADP
brj-25043	399	2	practice	practice	NOUN
brj-25043	399	3	,	,	PUNCT
brj-25043	399	4	probabilistic	probabilistic	ADJ
brj-25043	399	5	forecasts	forecast	NOUN
brj-25043	399	6	of	of	ADP
brj-25043	399	7	methane	methane	NOUN
brj-25043	399	8	production	production	NOUN
brj-25043	399	9	rates	rate	NOUN
brj-25043	399	10	,	,	PUNCT
brj-25043	399	11	𝑟ch4	𝑟ch4	PROPN
brj-25043	399	12	(	(	PUNCT
brj-25043	399	13	t	t	PROPN
brj-25043	399	14	)	)	PUNCT
brj-25043	399	15	,	,	PUNCT
brj-25043	399	16	and	and	CCONJ
brj-25043	399	17	biogas	biogas	NOUN
brj-25043	399	18	composition	composition	NOUN
brj-25043	399	19	can	can	AUX
brj-25043	399	20	be	be	AUX
brj-25043	399	21	transformed	transform	VERB
brj-25043	399	22	into	into	ADP
brj-25043	399	23	environmental	environmental	ADJ
brj-25043	399	24	and	and	CCONJ
brj-25043	399	25	economic	economic	ADJ
brj-25043	399	26	key	key	ADJ
brj-25043	399	27	performance	performance	NOUN
brj-25043	399	28	indicators	indicator	NOUN
brj-25043	399	29	(	(	PUNCT
brj-25043	399	30	kpis	kpis	PROPN
brj-25043	399	31	)	)	PUNCT
brj-25043	399	32	,	,	PUNCT
brj-25043	399	33	such	such	ADJ
brj-25043	399	34	as	as	ADP
brj-25043	399	35	global	global	ADJ
brj-25043	399	36	warming	warming	NOUN
brj-25043	399	37	potential	potential	NOUN
brj-25043	399	38	(	(	PUNCT
brj-25043	399	39	gwp	gwp	PROPN
brj-25043	399	40	,	,	PUNCT
brj-25043	399	41	expressed	express	VERB
brj-25043	399	42	as	as	ADP
brj-25043	399	43	kg	kg	PROPN
brj-25043	399	44	co₂-eq	co₂-eq	PUNCT
brj-25043	399	45	per	per	ADP
brj-25043	399	46	kwh	kwh	PROPN
brj-25043	399	47	delivered	deliver	VERB
brj-25043	399	48	)	)	PUNCT
brj-25043	399	49	and	and	CCONJ
brj-25043	399	50	the	the	DET
brj-25043	399	51	levelized	levelize	VERB
brj-25043	399	52	cost	cost	NOUN
brj-25043	399	53	of	of	ADP
brj-25043	399	54	energy	energy	NOUN
brj-25043	399	55	/	/	SYM
brj-25043	399	56	biogas	biogas	NOUN
brj-25043	399	57	(	(	PUNCT
brj-25043	399	58	lcoe	lcoe	ADJ
brj-25043	399	59	/	/	SYM
brj-25043	399	60	lcbg	lcbg	NOUN
brj-25043	399	61	)	)	PUNCT
brj-25043	399	62	(	(	PUNCT
brj-25043	399	63	said	say	VERB
brj-25043	399	64	et	et	PROPN
brj-25043	399	65	al	al	PROPN
brj-25043	399	66	.	.	PROPN
brj-25043	399	67	2020	2020	NUM
brj-25043	399	68	)	)	PUNCT
brj-25043	399	69	.	.	PUNCT
brj-25043	400	1	by	by	ADP
brj-25043	400	2	defining	define	VERB
brj-25043	400	3	a	a	DET
brj-25043	400	4	clear	clear	ADJ
brj-25043	400	5	functional	functional	ADJ
brj-25043	400	6	unit	unit	NOUN
brj-25043	400	7	(	(	PUNCT
brj-25043	400	8	e.g.	e.g.	ADV
brj-25043	400	9	,	,	PUNCT
brj-25043	400	10	“	"	PUNCT
brj-25043	400	11	per	per	ADP
brj-25043	400	12	kwh	kwh	NOUN
brj-25043	400	13	of	of	ADP
brj-25043	400	14	electricity	electricity	NOUN
brj-25043	400	15	exported	export	VERB
brj-25043	400	16	”	"	PUNCT
brj-25043	400	17	or	or	CCONJ
brj-25043	400	18	“	"	PUNCT
brj-25043	400	19	per	per	ADP
brj-25043	400	20	tonne	tonne	NOUN
brj-25043	400	21	vs	vs	ADP
brj-25043	400	22	fed	fed	PROPN
brj-25043	400	23	”	"	PUNCT
brj-25043	400	24	)	)	PUNCT
brj-25043	400	25	and	and	CCONJ
brj-25043	400	26	system	system	NOUN
brj-25043	400	27	boundary	boundary	NOUN
brj-25043	400	28	,	,	PUNCT
brj-25043	400	29	ml	ml	ADP
brj-25043	400	30	predictions	prediction	NOUN
brj-25043	400	31	can	can	AUX
brj-25043	400	32	be	be	AUX
brj-25043	400	33	mapped	map	VERB
brj-25043	400	34	to	to	ADP
brj-25043	400	35	life	life	NOUN
brj-25043	400	36	-	-	PUNCT
brj-25043	400	37	cycle	cycle	NOUN
brj-25043	400	38	inventory	inventory	NOUN
brj-25043	400	39	flows	flow	NOUN
brj-25043	400	40	(	(	PUNCT
brj-25043	400	41	electricity	electricity	NOUN
brj-25043	400	42	and	and	CCONJ
brj-25043	400	43	heat	heat	NOUN
brj-25043	400	44	generated	generate	VERB
brj-25043	400	45	through	through	ADP
brj-25043	400	46	chp	chp	NOUN
brj-25043	400	47	efficiency	efficiency	NOUN
brj-25043	400	48	,	,	PUNCT
brj-25043	400	49	auxiliary	auxiliary	ADJ
brj-25043	400	50	energy	energy	NOUN
brj-25043	400	51	for	for	ADP
brj-25043	400	52	heating	heating	NOUN
brj-25043	400	53	and	and	CCONJ
brj-25043	400	54	mixing	mixing	NOUN
brj-25043	400	55	,	,	PUNCT
brj-25043	400	56	flaring	flare	VERB
brj-25043	400	57	episodes	episode	NOUN
brj-25043	400	58	or	or	CCONJ
brj-25043	400	59	ch₄	ch₄	PROPN
brj-25043	400	60	slip	slip	NOUN
brj-25043	400	61	,	,	PUNCT
brj-25043	400	62	digestate	digestate	VERB
brj-25043	400	63	mass	mass	NOUN
brj-25043	400	64	and	and	CCONJ
brj-25043	400	65	nutrient	nutrient	ADJ
brj-25043	400	66	proxies	proxy	NOUN
brj-25043	400	67	)	)	PUNCT
brj-25043	400	68	as	as	ADV
brj-25043	400	69	well	well	ADV
brj-25043	400	70	as	as	ADP
brj-25043	400	71	to	to	ADP
brj-25043	400	72	financial	financial	ADJ
brj-25043	400	73	cash	cash	NOUN
brj-25043	400	74	flows	flow	NOUN
brj-25043	400	75	(	(	PUNCT
brj-25043	400	76	capex	capex	NOUN
brj-25043	400	77	annualization	annualization	NOUN
brj-25043	400	78	;	;	PUNCT
brj-25043	400	79	opex	opex	NOUN
brj-25043	400	80	for	for	ADP
brj-25043	400	81	energy	energy	NOUN
brj-25043	400	82	,	,	PUNCT
brj-25043	400	83	chemicals	chemical	NOUN
brj-25043	400	84	,	,	PUNCT
brj-25043	400	85	and	and	CCONJ
brj-25043	400	86	labour	labour	NOUN
brj-25043	400	87	;	;	PUNCT
brj-25043	400	88	tipping	tip	VERB
brj-25043	400	89	fees	fee	NOUN
brj-25043	400	90	;	;	PUNCT
brj-25043	400	91	and	and	CCONJ
brj-25043	400	92	revenues	revenue	NOUN
brj-25043	400	93	from	from	ADP
brj-25043	400	94	energy	energy	NOUN
brj-25043	400	95	and	and	CCONJ
brj-25043	400	96	fertilizer	fertilizer	NOUN
brj-25043	400	97	products	product	NOUN
brj-25043	400	98	)	)	PUNCT
brj-25043	400	99	.	.	PUNCT
brj-25043	401	1	the	the	DET
brj-25043	401	2	resulting	result	VERB
brj-25043	401	3	kpis	kpis	PROPN
brj-25043	401	4	are	be	AUX
brj-25043	401	5	computed	compute	VERB
brj-25043	401	6	through	through	ADP
brj-25043	401	7	straightforward	straightforward	ADJ
brj-25043	401	8	transformations	transformation	NOUN
brj-25043	401	9	of	of	ADP
brj-25043	401	10	predicted	predict	VERB
brj-25043	401	11	flows	flow	NOUN
brj-25043	401	12	.	.	PUNCT
brj-25043	402	1	this	this	DET
brj-25043	402	2	coupling	coupling	NOUN
brj-25043	402	3	enables	enable	VERB
brj-25043	402	4	direct	direct	ADJ
brj-25043	402	5	scenario	scenario	NOUN
brj-25043	402	6	testing	testing	NOUN
brj-25043	402	7	on	on	ADP
brj-25043	402	8	operational	operational	ADJ
brj-25043	402	9	levers	lever	NOUN
brj-25043	402	10	identified	identify	VERB
brj-25043	402	11	by	by	ADP
brj-25043	402	12	explainable	explainable	ADJ
brj-25043	402	13	ml	ml	NOUN
brj-25043	402	14	(	(	PUNCT
brj-25043	402	15	e.g.	e.g.	ADV
brj-25043	402	16	,	,	PUNCT
brj-25043	402	17	organic	organic	ADJ
brj-25043	402	18	loading	loading	NOUN
brj-25043	402	19	rate	rate	NOUN
brj-25043	402	20	,	,	PUNCT
brj-25043	402	21	hydraulic	hydraulic	ADJ
brj-25043	402	22	retention	retention	NOUN
brj-25043	402	23	time	time	NOUN
brj-25043	402	24	,	,	PUNCT
brj-25043	402	25	temperature	temperature	NOUN
brj-25043	402	26	set	set	NOUN
brj-25043	402	27	-	-	PUNCT
brj-25043	402	28	point	point	NOUN
brj-25043	402	29	,	,	PUNCT
brj-25043	402	30	or	or	CCONJ
brj-25043	402	31	co	co	NOUN
brj-25043	402	32	-	-	NOUN
brj-25043	402	33	substrate	substrate	NOUN
brj-25043	402	34	ratio	ratio	NOUN
brj-25043	402	35	)	)	PUNCT
brj-25043	402	36	.	.	PUNCT
brj-25043	403	1	operators	operator	NOUN
brj-25043	403	2	can	can	AUX
brj-25043	403	3	explore	explore	VERB
brj-25043	403	4	feasible	feasible	ADJ
brj-25043	403	5	parameter	parameter	NOUN
brj-25043	403	6	sets	set	NOUN
brj-25043	403	7	,	,	PUNCT
brj-25043	403	8	propagate	propagate	ADJ
brj-25043	403	9	forecast	forecast	NOUN
brj-25043	403	10	uncertainty	uncertainty	NOUN
brj-25043	403	11	through	through	ADP
brj-25043	403	12	quantile	quantile	ADJ
brj-25043	403	13	or	or	CCONJ
brj-25043	403	14	bootstrap	bootstrap	NOUN
brj-25043	403	15	ensembles	ensemble	NOUN
brj-25043	403	16	to	to	PART
brj-25043	403	17	generate	generate	VERB
brj-25043	403	18	5	5	NUM
brj-25043	403	19	to	to	PART
brj-25043	403	20	95	95	NUM
brj-25043	403	21	%	%	NOUN
brj-25043	403	22	confidence	confidence	NOUN
brj-25043	403	23	bands	band	NOUN
brj-25043	403	24	for	for	ADP
brj-25043	403	25	gwp	gwp	PROPN
brj-25043	403	26	and	and	CCONJ
brj-25043	403	27	lcoe	lcoe	ADJ
brj-25043	403	28	,	,	PUNCT
brj-25043	403	29	and	and	CCONJ
brj-25043	403	30	then	then	ADV
brj-25043	403	31	identify	identify	VERB
brj-25043	403	32	pareto	pareto	VERB
brj-25043	403	33	-	-	PUNCT
brj-25043	403	34	efficient	efficient	ADJ
brj-25043	403	35	operating	operating	NOUN
brj-25043	403	36	points	point	NOUN
brj-25043	403	37	(	(	PUNCT
brj-25043	403	38	e.g.	e.g.	ADV
brj-25043	403	39	,	,	PUNCT
brj-25043	403	40	minimizing	minimize	VERB
brj-25043	403	41	gwp	gwp	PROPN
brj-25043	403	42	while	while	SCONJ
brj-25043	403	43	keeping	keep	VERB
brj-25043	403	44	lcoe	lcoe	PROPN
brj-25043	403	45	below	below	ADP
brj-25043	403	46	a	a	DET
brj-25043	403	47	defined	define	VERB
brj-25043	403	48	threshold	threshold	NOUN
brj-25043	403	49	)	)	PUNCT
brj-25043	403	50	.	.	PUNCT
brj-25043	404	1	additional	additional	ADJ
brj-25043	404	2	credits	credit	NOUN
brj-25043	404	3	and	and	CCONJ
brj-25043	404	4	burdens	burden	NOUN
brj-25043	404	5	,	,	PUNCT
brj-25043	404	6	such	such	ADJ
brj-25043	404	7	as	as	ADP
brj-25043	404	8	displacement	displacement	NOUN
brj-25043	404	9	of	of	ADP
brj-25043	404	10	grid	grid	NOUN
brj-25043	404	11	electricity	electricity	NOUN
brj-25043	404	12	,	,	PUNCT
brj-25043	404	13	heat	heat	NOUN
brj-25043	404	14	recovery	recovery	NOUN
brj-25043	404	15	,	,	PUNCT
brj-25043	404	16	avoided	avoid	VERB
brj-25043	404	17	landfill	landfill	NOUN
brj-25043	404	18	emissions	emission	NOUN
brj-25043	404	19	,	,	PUNCT
brj-25043	404	20	or	or	CCONJ
brj-25043	404	21	nutrient	nutrient	NOUN
brj-25043	404	22	substitution	substitution	NOUN
brj-25043	404	23	from	from	ADP
brj-25043	404	24	digestate	digestate	NOUN
brj-25043	404	25	,	,	PUNCT
brj-25043	404	26	can	can	AUX
brj-25043	404	27	be	be	AUX
brj-25043	404	28	incorporated	incorporate	VERB
brj-25043	404	29	modularly	modularly	ADV
brj-25043	404	30	,	,	PUNCT
brj-25043	404	31	provided	provide	VERB
brj-25043	404	32	assumptions	assumption	NOUN
brj-25043	404	33	and	and	CCONJ
brj-25043	404	34	units	unit	NOUN
brj-25043	404	35	are	be	AUX
brj-25043	404	36	transparently	transparently	ADV
brj-25043	404	37	reported	report	VERB
brj-25043	404	38	for	for	ADP
brj-25043	404	39	transferability	transferability	NOUN
brj-25043	404	40	.	.	PUNCT
brj-25043	405	1	field	field	NOUN
brj-25043	405	2	-	-	PUNCT
brj-25043	405	3	scale	scale	NOUN
brj-25043	405	4	evidence	evidence	NOUN
brj-25043	405	5	and	and	CCONJ
brj-25043	405	6	engineering	engineering	NOUN
brj-25043	405	7	implications	implication	NOUN
brj-25043	405	8	from	from	ADP
brj-25043	405	9	a	a	DET
brj-25043	405	10	model	model	ADJ
brj-25043	405	11	-	-	PUNCT
brj-25043	405	12	selection	selection	NOUN
brj-25043	405	13	perspective	perspective	NOUN
brj-25043	405	14	,	,	PUNCT
brj-25043	405	15	cumulative	cumulative	ADJ
brj-25043	405	16	-	-	PUNCT
brj-25043	405	17	yield	yield	NOUN
brj-25043	405	18	kinetics	kinetic	NOUN
brj-25043	405	19	remain	remain	VERB
brj-25043	405	20	the	the	DET
brj-25043	405	21	most	most	ADV
brj-25043	405	22	practical	practical	ADJ
brj-25043	405	23	option	option	NOUN
brj-25043	405	24	when	when	SCONJ
brj-25043	405	25	only	only	ADV
brj-25043	405	26	batch	batch	NOUN
brj-25043	405	27	/	/	SYM
brj-25043	405	28	bmp	bmp	NOUN
brj-25043	405	29	tests	test	NOUN
brj-25043	405	30	or	or	CCONJ
brj-25043	405	31	limited	limited	ADJ
brj-25043	405	32	monitoring	monitoring	NOUN
brj-25043	405	33	data	datum	NOUN
brj-25043	405	34	are	be	AUX
brj-25043	405	35	available	available	ADJ
brj-25043	405	36	.	.	PUNCT
brj-25043	406	1	the	the	DET
brj-25043	406	2	modified	modify	VERB
brj-25043	406	3	gompertz	gompertz	NOUN
brj-25043	406	4	typically	typically	ADV
brj-25043	406	5	provides	provide	VERB
brj-25043	406	6	the	the	DET
brj-25043	406	7	most	most	ADV
brj-25043	406	8	accurate	accurate	ADJ
brj-25043	406	9	fit	fit	NOUN
brj-25043	406	10	across	across	ADP
brj-25043	406	11	substrates	substrate	NOUN
brj-25043	406	12	,	,	PUNCT
brj-25043	406	13	with	with	ADP
brj-25043	406	14	parameters	parameter	NOUN
brj-25043	406	15	a	a	DET
brj-25043	406	16	(	(	PUNCT
brj-25043	406	17	ultimate	ultimate	ADJ
brj-25043	406	18	potential	potential	NOUN
brj-25043	406	19	)	)	PUNCT
brj-25043	406	20	and	and	CCONJ
brj-25043	406	21	λ	λ	PROPN
brj-25043	406	22	(	(	PUNCT
brj-25043	406	23	lag	lag	PROPN
brj-25043	406	24	)	)	PUNCT
brj-25043	406	25	being	be	AUX
brj-25043	406	26	highly	highly	ADV
brj-25043	406	27	sensitive	sensitive	ADJ
brj-25043	406	28	and	and	CCONJ
brj-25043	406	29	directly	directly	ADV
brj-25043	406	30	guiding	guide	VERB
brj-25043	406	31	peer	peer	NOUN
brj-25043	406	32	-	-	PUNCT
brj-25043	406	33	reviewed	review	VERB
brj-25043	406	34	review	review	NOUN
brj-25043	406	35	article	article	NOUN
brj-25043	406	36	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	406	37	galal	galal	PROPN
brj-25043	406	38	et	et	PROPN
brj-25043	406	39	al	al	PROPN
brj-25043	406	40	.	.	PROPN
brj-25043	407	1	(	(	PUNCT
brj-25043	407	2	2025	2025	NUM
brj-25043	407	3	)	)	PUNCT
brj-25043	407	4	.	.	PUNCT
brj-25043	408	1	“	"	PUNCT
brj-25043	408	2	math	math	NOUN
brj-25043	408	3	modeling	modeling	NOUN
brj-25043	408	4	biogas	biogas	NOUN
brj-25043	408	5	production	production	NOUN
brj-25043	408	6	,	,	PUNCT
brj-25043	408	7	”	"	PUNCT
brj-25043	408	8	bioresources	bioresource	NOUN
brj-25043	408	9	20(4	20(4	NOUN
brj-25043	408	10	)	)	PUNCT
brj-25043	408	11	,	,	PUNCT
brj-25043	408	12	11237	11237	NUM
brj-25043	408	13	-	-	SYM
brj-25043	408	14	11266	11266	NUM
brj-25043	408	15	.	.	PUNCT
brj-25043	409	1	11260	11260	NUM
brj-25043	409	2	gasholder	gasholder	NOUN
brj-25043	409	3	sizing	sizing	NOUN
brj-25043	409	4	and	and	CCONJ
brj-25043	409	5	start	start	NOUN
brj-25043	409	6	-	-	PUNCT
brj-25043	409	7	up	up	ADP
brj-25043	409	8	expectations	expectation	NOUN
brj-25043	409	9	;	;	PUNCT
brj-25043	409	10	the	the	DET
brj-25043	409	11	exponential	exponential	ADJ
brj-25043	409	12	rise	rise	NOUN
brj-25043	409	13	-	-	PUNCT
brj-25043	409	14	to	to	ADP
brj-25043	409	15	-	-	PUNCT
brj-25043	409	16	maximum	maximum	NOUN
brj-25043	409	17	is	be	AUX
brj-25043	409	18	particularly	particularly	ADV
brj-25043	409	19	effective	effective	ADJ
brj-25043	409	20	in	in	ADP
brj-25043	409	21	landfill	landfill	NOUN
brj-25043	409	22	/	/	SYM
brj-25043	409	23	bmp	bmp	NOUN
brj-25043	409	24	contexts	contexts	NOUN
brj-25043	409	25	(	(	PUNCT
brj-25043	409	26	bilgili	bilgili	NOUN
brj-25043	409	27	et	et	PROPN
brj-25043	409	28	al	al	PROPN
brj-25043	409	29	.	.	PROPN
brj-25043	409	30	2009	2009	NUM
brj-25043	409	31	;	;	PUNCT
brj-25043	409	32	lo	lo	PROPN
brj-25043	409	33	et	et	PROPN
brj-25043	409	34	al	al	PROPN
brj-25043	409	35	.	.	PROPN
brj-25043	409	36	2010	2010	NUM
brj-25043	409	37	;	;	PUNCT
brj-25043	409	38	latinwo	latinwo	NOUN
brj-25043	409	39	and	and	CCONJ
brj-25043	409	40	agarry	agarry	PROPN
brj-25043	409	41	2015	2015	NUM
brj-25043	409	42	;	;	PUNCT
brj-25043	409	43	nielfa	nielfa	NOUN
brj-25043	409	44	et	et	PROPN
brj-25043	409	45	al	al	PROPN
brj-25043	409	46	.	.	PROPN
brj-25043	409	47	2015	2015	NUM
brj-25043	409	48	)	)	PUNCT
brj-25043	409	49	.	.	PUNCT
brj-25043	410	1	when	when	SCONJ
brj-25043	410	2	digester	digester	NOUN
brj-25043	410	3	operation	operation	NOUN
brj-25043	410	4	is	be	AUX
brj-25043	410	5	affected	affect	VERB
brj-25043	410	6	by	by	ADP
brj-25043	410	7	syntrophic	syntrophic	ADJ
brj-25043	410	8	interactions	interaction	NOUN
brj-25043	410	9	or	or	CCONJ
brj-25043	410	10	direct	direct	ADJ
brj-25043	410	11	interspecies	interspecie	NOUN
brj-25043	410	12	electron	electron	NOUN
brj-25043	410	13	transfer	transfer	NOUN
brj-25043	410	14	,	,	PUNCT
brj-25043	410	15	chen	chen	NOUN
brj-25043	410	16	-	-	PUNCT
brj-25043	410	17	hashimoto	hashimoto	NOUN
brj-25043	410	18	-	-	PUNCT
brj-25043	410	19	type	type	NOUN
brj-25043	410	20	models	model	NOUN
brj-25043	410	21	can	can	AUX
brj-25043	410	22	outperform	outperform	VERB
brj-25043	410	23	simpler	simple	ADJ
brj-25043	410	24	kinetics	kinetic	NOUN
brj-25043	410	25	and	and	CCONJ
brj-25043	410	26	should	should	AUX
brj-25043	410	27	be	be	AUX
brj-25043	410	28	considered	consider	VERB
brj-25043	410	29	during	during	ADP
brj-25043	410	30	scenario	scenario	NOUN
brj-25043	410	31	screening	screening	NOUN
brj-25043	410	32	(	(	PUNCT
brj-25043	410	33	li	li	PROPN
brj-25043	410	34	et	et	PROPN
brj-25043	410	35	al	al	PROPN
brj-25043	410	36	.	.	PROPN
brj-25043	410	37	2018	2018	NUM
brj-25043	410	38	)	)	PUNCT
brj-25043	410	39	.	.	PUNCT
brj-25043	411	1	in	in	ADP
brj-25043	411	2	continuously	continuously	ADV
brj-25043	411	3	fed	feed	VERB
brj-25043	411	4	plants	plant	NOUN
brj-25043	411	5	with	with	ADP
brj-25043	411	6	scada	scada	PROPN
brj-25043	411	7	data	data	PROPN
brj-25043	411	8	,	,	PUNCT
brj-25043	411	9	forecasting	forecasting	NOUN
brj-25043	411	10	and	and	CCONJ
brj-25043	411	11	stability	stability	NOUN
brj-25043	411	12	control	control	NOUN
brj-25043	411	13	benefit	benefit	VERB
brj-25043	411	14	from	from	ADP
brj-25043	411	15	ml	ml	ADP
brj-25043	411	16	pipelines	pipeline	NOUN
brj-25043	411	17	that	that	PRON
brj-25043	411	18	use	use	VERB
brj-25043	411	19	5	5	NUM
brj-25043	411	20	to	to	PART
brj-25043	411	21	15	15	NUM
brj-25043	411	22	-	-	PUNCT
brj-25043	411	23	minute	minute	NOUN
brj-25043	411	24	aggregates	aggregate	NOUN
brj-25043	411	25	of	of	ADP
brj-25043	411	26	standard	standard	ADJ
brj-25043	411	27	sensors	sensor	NOUN
brj-25043	411	28	(	(	PUNCT
brj-25043	411	29	biogas	biogas	NOUN
brj-25043	411	30	flow	flow	NOUN
brj-25043	411	31	,	,	PUNCT
brj-25043	411	32	temperature	temperature	NOUN
brj-25043	411	33	,	,	PUNCT
brj-25043	411	34	ph	ph	ADJ
brj-25043	411	35	,	,	PUNCT
brj-25043	411	36	influent	influent	NOUN
brj-25043	411	37	characteristics	characteristic	NOUN
brj-25043	411	38	)	)	PUNCT
brj-25043	411	39	,	,	PUNCT
brj-25043	411	40	supplemented	supplement	VERB
brj-25043	411	41	by	by	ADP
brj-25043	411	42	soft	soft	ADJ
brj-25043	411	43	sensors	sensor	NOUN
brj-25043	411	44	such	such	ADJ
brj-25043	411	45	as	as	ADP
brj-25043	411	46	vfa	vfa	PROPN
brj-25043	411	47	/	/	SYM
brj-25043	411	48	alk	alk	NOUN
brj-25043	411	49	estimators	estimator	NOUN
brj-25043	411	50	(	(	PUNCT
brj-25043	411	51	zou	zou	X
brj-25043	411	52	et	et	PROPN
brj-25043	411	53	al	al	PROPN
brj-25043	411	54	.	.	PROPN
brj-25043	411	55	2024	2024	NUM
brj-25043	411	56	)	)	PUNCT
brj-25043	411	57	.	.	PUNCT
brj-25043	412	1	practical	practical	ADJ
brj-25043	412	2	deployment	deployment	NOUN
brj-25043	412	3	involves	involve	VERB
brj-25043	412	4	routine	routine	ADJ
brj-25043	412	5	outlier	outlier	NOUN
brj-25043	412	6	handling	handling	NOUN
brj-25043	412	7	,	,	PUNCT
brj-25043	412	8	rolling	roll	VERB
brj-25043	412	9	cross	cross	NOUN
brj-25043	412	10	-	-	NOUN
brj-25043	412	11	validation	validation	NOUN
brj-25043	412	12	to	to	PART
brj-25043	412	13	account	account	VERB
brj-25043	412	14	for	for	ADP
brj-25043	412	15	seasonal	seasonal	ADJ
brj-25043	412	16	shifts	shift	NOUN
brj-25043	412	17	,	,	PUNCT
brj-25043	412	18	and	and	CCONJ
brj-25043	412	19	external	external	ADJ
brj-25043	412	20	validation	validation	NOUN
brj-25043	412	21	on	on	ADP
brj-25043	412	22	unseen	unseen	ADJ
brj-25043	412	23	weeks	week	NOUN
brj-25043	412	24	.	.	PUNCT
brj-25043	413	1	probabilistic	probabilistic	ADJ
brj-25043	413	2	time	time	NOUN
brj-25043	413	3	-	-	PUNCT
brj-25043	413	4	series	series	NOUN
brj-25043	413	5	models	model	NOUN
brj-25043	413	6	(	(	PUNCT
brj-25043	413	7	e.g.	e.g.	ADV
brj-25043	413	8	,	,	PUNCT
brj-25043	413	9	lstm	lstm	ADJ
brj-25043	413	10	/	/	SYM
brj-25043	413	11	tft	tft	ADJ
brj-25043	413	12	with	with	ADP
brj-25043	413	13	quantiles	quantile	NOUN
brj-25043	413	14	)	)	PUNCT
brj-25043	413	15	transform	transform	VERB
brj-25043	413	16	predictions	prediction	NOUN
brj-25043	413	17	into	into	ADP
brj-25043	413	18	risk	risk	NOUN
brj-25043	413	19	bands	band	NOUN
brj-25043	413	20	that	that	PRON
brj-25043	413	21	operators	operator	NOUN
brj-25043	413	22	can	can	AUX
brj-25043	413	23	map	map	VERB
brj-25043	413	24	to	to	ADP
brj-25043	413	25	actions	action	NOUN
brj-25043	413	26	such	such	ADJ
brj-25043	413	27	as	as	ADP
brj-25043	413	28	moderating	moderate	VERB
brj-25043	413	29	olr	olr	NOUN
brj-25043	413	30	ramps	ramp	NOUN
brj-25043	413	31	,	,	PUNCT
brj-25043	413	32	adjusting	adjust	VERB
brj-25043	413	33	hrt	hrt	PROPN
brj-25043	413	34	,	,	PUNCT
brj-25043	413	35	or	or	CCONJ
brj-25043	413	36	temporarily	temporarily	ADV
brj-25043	413	37	reducing	reduce	VERB
brj-25043	413	38	recalcitrant	recalcitrant	ADJ
brj-25043	413	39	co	co	NOUN
brj-25043	413	40	-	-	NOUN
brj-25043	413	41	substrates	substrate	NOUN
brj-25043	413	42	before	before	ADP
brj-25043	413	43	acidification	acidification	NOUN
brj-25043	413	44	escalates	escalate	NOUN
brj-25043	413	45	(	(	PUNCT
brj-25043	413	46	sappl	sappl	NOUN
brj-25043	413	47	et	et	PROPN
brj-25043	413	48	al	al	PROPN
brj-25043	413	49	.	.	PROPN
brj-25043	413	50	2023	2023	NUM
brj-25043	413	51	;	;	PUNCT
brj-25043	413	52	jeong	jeong	PROPN
brj-25043	413	53	et	et	PROPN
brj-25043	413	54	al	al	PROPN
brj-25043	413	55	.	.	PROPN
brj-25043	413	56	2021	2021	NUM
brj-25043	413	57	;	;	PUNCT
brj-25043	413	58	salamattalab	salamattalab	NOUN
brj-25043	413	59	et	et	PROPN
brj-25043	413	60	al	al	PROPN
brj-25043	413	61	.	.	PROPN
brj-25043	413	62	2024	2024	NUM
brj-25043	413	63	)	)	PUNCT
brj-25043	413	64	.	.	PUNCT
brj-25043	414	1	hybrid	hybrid	ADJ
brj-25043	414	2	mechanistic	mechanistic	ADJ
brj-25043	414	3	-	-	PUNCT
brj-25043	414	4	ml	ml	NOUN
brj-25043	414	5	approaches	approach	NOUN
brj-25043	414	6	provide	provide	VERB
brj-25043	414	7	a	a	DET
brj-25043	414	8	balanced	balanced	ADJ
brj-25043	414	9	solution	solution	NOUN
brj-25043	414	10	when	when	SCONJ
brj-25043	414	11	both	both	DET
brj-25043	414	12	interpretability	interpretability	NOUN
brj-25043	414	13	and	and	CCONJ
brj-25043	414	14	accuracy	accuracy	NOUN
brj-25043	414	15	are	be	AUX
brj-25043	414	16	needed	need	VERB
brj-25043	414	17	:	:	PUNCT
brj-25043	414	18	a	a	DET
brj-25043	414	19	kinetic	kinetic	ADJ
brj-25043	414	20	core	core	NOUN
brj-25043	414	21	captures	capture	VERB
brj-25043	414	22	the	the	DET
brj-25043	414	23	mass	mass	ADJ
brj-25043	414	24	-	-	PUNCT
brj-25043	414	25	balance	balance	NOUN
brj-25043	414	26	structure	structure	NOUN
brj-25043	414	27	,	,	PUNCT
brj-25043	414	28	while	while	SCONJ
brj-25043	414	29	ml	ml	PART
brj-25043	414	30	learns	learn	VERB
brj-25043	414	31	residuals	residual	NOUN
brj-25043	414	32	and	and	CCONJ
brj-25043	414	33	context	context	NOUN
brj-25043	414	34	-	-	PUNCT
brj-25043	414	35	specific	specific	ADJ
brj-25043	414	36	effects	effect	NOUN
brj-25043	414	37	(	(	PUNCT
brj-25043	414	38	gupta	gupta	PROPN
brj-25043	414	39	et	et	PROPN
brj-25043	414	40	al	al	PROPN
brj-25043	414	41	.	.	PROPN
brj-25043	414	42	2023	2023	NUM
brj-25043	414	43	;	;	PUNCT
brj-25043	414	44	ling	le	VERB
brj-25043	414	45	et	et	PROPN
brj-25043	414	46	al	al	PROPN
brj-25043	414	47	.	.	PROPN
brj-25043	414	48	2024	2024	NUM
brj-25043	414	49	;	;	PUNCT
brj-25043	414	50	geng	geng	PROPN
brj-25043	414	51	et	et	PROPN
brj-25043	414	52	al	al	PROPN
brj-25043	414	53	.	.	PROPN
brj-25043	414	54	2024	2024	NUM
brj-25043	414	55	)	)	PUNCT
brj-25043	414	56	.	.	PUNCT
brj-25043	415	1	this	this	DET
brj-25043	415	2	framework	framework	NOUN
brj-25043	415	3	naturally	naturally	ADV
brj-25043	415	4	fits	fit	VERB
brj-25043	415	5	with	with	ADP
brj-25043	415	6	iot	iot	NOUN
brj-25043	415	7	-	-	PUNCT
brj-25043	415	8	enabled	enable	VERB
brj-25043	415	9	“	"	PUNCT
brj-25043	415	10	smart	smart	ADJ
brj-25043	415	11	digesters	digester	NOUN
brj-25043	415	12	,	,	PUNCT
brj-25043	415	13	”	"	PUNCT
brj-25043	415	14	where	where	SCONJ
brj-25043	415	15	uncertainty	uncertainty	NOUN
brj-25043	415	16	-	-	PUNCT
brj-25043	415	17	aware	aware	ADJ
brj-25043	415	18	forecasts	forecast	NOUN
brj-25043	415	19	,	,	PUNCT
brj-25043	415	20	explainable	explainable	ADJ
brj-25043	415	21	features	feature	NOUN
brj-25043	415	22	,	,	PUNCT
brj-25043	415	23	and	and	CCONJ
brj-25043	415	24	control	control	NOUN
brj-25043	415	25	heuristics	heuristic	NOUN
brj-25043	415	26	are	be	AUX
brj-25043	415	27	integrated	integrate	VERB
brj-25043	415	28	into	into	ADP
brj-25043	415	29	operator	operator	NOUN
brj-25043	415	30	dashboards	dashboard	NOUN
brj-25043	415	31	to	to	PART
brj-25043	415	32	increase	increase	VERB
brj-25043	415	33	energy	energy	NOUN
brj-25043	415	34	yield	yield	NOUN
brj-25043	415	35	,	,	PUNCT
brj-25043	415	36	reduce	reduce	VERB
brj-25043	415	37	downtime	downtime	NOUN
brj-25043	415	38	,	,	PUNCT
brj-25043	415	39	and	and	CCONJ
brj-25043	415	40	support	support	VERB
brj-25043	415	41	tea	tea	NOUN
brj-25043	415	42	/	/	SYM
brj-25043	415	43	lca	lca	PROPN
brj-25043	415	44	decision	decision	NOUN
brj-25043	415	45	-	-	PUNCT
brj-25043	415	46	making	making	NOUN
brj-25043	415	47	for	for	ADP
brj-25043	415	48	co	co	NOUN
brj-25043	415	49	-	-	NOUN
brj-25043	415	50	digestion	digestion	NOUN
brj-25043	415	51	and	and	CCONJ
brj-25043	415	52	pre	pre	ADJ
brj-25043	415	53	-	-	ADJ
brj-25043	415	54	treatment	treatment	NOUN
brj-25043	415	55	options	option	NOUN
brj-25043	415	56	.	.	PUNCT
brj-25043	416	1	in	in	ADP
brj-25043	416	2	full	full	ADJ
brj-25043	416	3	-	-	PUNCT
brj-25043	416	4	scale	scale	NOUN
brj-25043	416	5	digesters	digester	NOUN
brj-25043	416	6	,	,	PUNCT
brj-25043	416	7	non	non	ADJ
brj-25043	416	8	-	-	ADJ
brj-25043	416	9	ideal	ideal	ADJ
brj-25043	416	10	hydraulics	hydraulic	NOUN
brj-25043	416	11	(	(	PUNCT
brj-25043	416	12	dead	dead	ADJ
brj-25043	416	13	zones	zone	NOUN
brj-25043	416	14	,	,	PUNCT
brj-25043	416	15	short	short	NOUN
brj-25043	416	16	-	-	PUNCT
brj-25043	416	17	circuiting	circuiting	NOUN
brj-25043	416	18	)	)	PUNCT
brj-25043	416	19	,	,	PUNCT
brj-25043	416	20	variable	variable	ADJ
brj-25043	416	21	rtd	rtd	PROPN
brj-25043	416	22	,	,	PUNCT
brj-25043	416	23	and	and	CCONJ
brj-25043	416	24	intermittent	intermittent	ADJ
brj-25043	416	25	sensors	sensor	NOUN
brj-25043	416	26	violate	violate	VERB
brj-25043	416	27	the	the	DET
brj-25043	416	28	homogeneity	homogeneity	NOUN
brj-25043	416	29	and	and	CCONJ
brj-25043	416	30	stationarity	stationarity	NOUN
brj-25043	416	31	assumed	assume	VERB
brj-25043	416	32	by	by	ADP
brj-25043	416	33	both	both	CCONJ
brj-25043	416	34	kinetic	kinetic	ADJ
brj-25043	416	35	and	and	CCONJ
brj-25043	416	36	ml	ml	NOUN
brj-25043	416	37	models	model	NOUN
brj-25043	416	38	.	.	PUNCT
brj-25043	417	1	scada	scada	PROPN
brj-25043	417	2	streams	streams	PROPN
brj-25043	417	3	are	be	AUX
brj-25043	417	4	irregularly	irregularly	ADV
brj-25043	417	5	sampled	sample	VERB
brj-25043	417	6	,	,	PUNCT
brj-25043	417	7	exhibit	exhibit	NOUN
brj-25043	417	8	drift	drift	NOUN
brj-25043	417	9	,	,	PUNCT
brj-25043	417	10	and	and	CCONJ
brj-25043	417	11	are	be	AUX
brj-25043	417	12	frequently	frequently	ADV
brj-25043	417	13	unsynchronized	unsynchronized	ADJ
brj-25043	417	14	with	with	ADP
brj-25043	417	15	gas	gas	NOUN
brj-25043	417	16	-	-	PUNCT
brj-25043	417	17	quality	quality	NOUN
brj-25043	417	18	measurements	measurement	NOUN
brj-25043	417	19	;	;	PUNCT
brj-25043	417	20	without	without	ADP
brj-25043	417	21	resampling	resample	VERB
brj-25043	417	22	,	,	PUNCT
brj-25043	417	23	calibration	calibration	NOUN
brj-25043	417	24	,	,	PUNCT
brj-25043	417	25	and	and	CCONJ
brj-25043	417	26	basic	basic	ADJ
brj-25043	417	27	qc	qc	PROPN
brj-25043	417	28	,	,	PUNCT
brj-25043	417	29	models	model	NOUN
brj-25043	417	30	learn	learn	VERB
brj-25043	417	31	artefacts	artefact	NOUN
brj-25043	417	32	(	(	PUNCT
brj-25043	417	33	sun	sun	NOUN
brj-25043	417	34	et	et	PROPN
brj-25043	417	35	al	al	PROPN
brj-25043	417	36	.	.	PROPN
brj-25043	417	37	2023	2023	NUM
brj-25043	417	38	;	;	PUNCT
brj-25043	417	39	zou	zou	PROPN
brj-25043	417	40	et	et	PROPN
brj-25043	417	41	al	al	PROPN
brj-25043	417	42	.	.	PROPN
brj-25043	417	43	2024	2024	NUM
brj-25043	417	44	)	)	PUNCT
brj-25043	417	45	.	.	PUNCT
brj-25043	418	1	seasonal	seasonal	ADJ
brj-25043	418	2	substrate	substrate	NOUN
brj-25043	418	3	shifts	shift	NOUN
brj-25043	418	4	and	and	CCONJ
brj-25043	418	5	co	co	ADJ
brj-25043	418	6	-	-	NOUN
brj-25043	418	7	substrate	substrate	ADJ
brj-25043	418	8	swings	swing	NOUN
brj-25043	418	9	cause	cause	VERB
brj-25043	418	10	distribution	distribution	NOUN
brj-25043	418	11	shift	shift	NOUN
brj-25043	418	12	that	that	PRON
brj-25043	418	13	degrades	degrade	VERB
brj-25043	418	14	accuracy	accuracy	NOUN
brj-25043	418	15	unless	unless	SCONJ
brj-25043	418	16	rolling	roll	VERB
brj-25043	418	17	validation	validation	NOUN
brj-25043	418	18	and	and	CCONJ
brj-25043	418	19	periodic	periodic	ADJ
brj-25043	418	20	recalibration	recalibration	NOUN
brj-25043	418	21	are	be	AUX
brj-25043	418	22	used	use	VERB
brj-25043	418	23	(	(	PUNCT
brj-25043	418	24	yildirim	yildirim	NOUN
brj-25043	418	25	and	and	CCONJ
brj-25043	418	26	ozkaya	ozkaya	NOUN
brj-25043	418	27	2023	2023	NUM
brj-25043	418	28	;	;	PUNCT
brj-25043	418	29	ling	le	VERB
brj-25043	418	30	et	et	PROPN
brj-25043	418	31	al	al	PROPN
brj-25043	418	32	.	.	PROPN
brj-25043	418	33	2024	2024	NUM
brj-25043	418	34	)	)	PUNCT
brj-25043	418	35	.	.	PUNCT
brj-25043	419	1	standardizing	standardize	VERB
brj-25043	419	2	units	unit	NOUN
brj-25043	419	3	(	(	PUNCT
brj-25043	419	4	e.g.	e.g.	ADV
brj-25043	419	5	,	,	PUNCT
brj-25043	419	6	ml	ml	PROPN
brj-25043	419	7	ch₄	ch₄	PROPN
brj-25043	419	8	gvs⁻¹	gvs⁻¹	PROPN
brj-25043	419	9	at	at	ADP
brj-25043	419	10	stp	stp	PROPN
brj-25043	419	11	,	,	PUNCT
brj-25043	419	12	dry	dry	ADJ
brj-25043	419	13	gas	gas	NOUN
brj-25043	419	14	)	)	PUNCT
brj-25043	419	15	and	and	CCONJ
brj-25043	419	16	documenting	document	VERB
brj-25043	419	17	feed	feed	NOUN
brj-25043	419	18	configuration	configuration	NOUN
brj-25043	419	19	are	be	AUX
brj-25043	419	20	prerequisites	prerequisite	NOUN
brj-25043	419	21	for	for	ADP
brj-25043	419	22	model	model	NOUN
brj-25043	419	23	transfer	transfer	NOUN
brj-25043	419	24	across	across	ADP
brj-25043	419	25	sites	site	NOUN
brj-25043	419	26	.	.	PUNCT
brj-25043	420	1	full	full	ADJ
brj-25043	420	2	-	-	PUNCT
brj-25043	420	3	scale	scale	NOUN
brj-25043	420	4	and	and	CCONJ
brj-25043	420	5	pilot	pilot	NOUN
brj-25043	420	6	experiences	experience	NOUN
brj-25043	420	7	increasingly	increasingly	ADV
brj-25043	420	8	show	show	VERB
brj-25043	420	9	that	that	SCONJ
brj-25043	420	10	data	data	NOUN
brj-25043	420	11	-	-	PUNCT
brj-25043	420	12	driven	drive	VERB
brj-25043	420	13	models	model	NOUN
brj-25043	420	14	can	can	AUX
brj-25043	420	15	directly	directly	ADV
brj-25043	420	16	improve	improve	VERB
brj-25043	420	17	operations	operation	NOUN
brj-25043	420	18	when	when	SCONJ
brj-25043	420	19	used	use	VERB
brj-25043	420	20	with	with	ADP
brj-25043	420	21	routine	routine	ADJ
brj-25043	420	22	plant	plant	NOUN
brj-25043	420	23	instrumentation	instrumentation	NOUN
brj-25043	420	24	.	.	PUNCT
brj-25043	421	1	in	in	ADP
brj-25043	421	2	industrial	industrial	ADJ
brj-25043	421	3	and	and	CCONJ
brj-25043	421	4	municipal	municipal	ADJ
brj-25043	421	5	environments	environment	NOUN
brj-25043	421	6	,	,	PUNCT
brj-25043	421	7	tree	tree	NOUN
brj-25043	421	8	-	-	PUNCT
brj-25043	421	9	based	base	VERB
brj-25043	421	10	ensembles	ensemble	NOUN
brj-25043	421	11	and	and	CCONJ
brj-25043	421	12	sequence	sequence	NOUN
brj-25043	421	13	models	model	NOUN
brj-25043	421	14	have	have	AUX
brj-25043	421	15	provided	provide	VERB
brj-25043	421	16	reliable	reliable	ADJ
brj-25043	421	17	short	short	ADJ
brj-25043	421	18	-	-	PUNCT
brj-25043	421	19	term	term	NOUN
brj-25043	421	20	forecasts	forecast	NOUN
brj-25043	421	21	and	and	CCONJ
brj-25043	421	22	soft	soft	ADJ
brj-25043	421	23	-	-	PUNCT
brj-25043	421	24	sensor	sensor	NOUN
brj-25043	421	25	surrogates	surrogate	NOUN
brj-25043	421	26	,	,	PUNCT
brj-25043	421	27	with	with	ADP
brj-25043	421	28	performance	performance	NOUN
brj-25043	421	29	generally	generally	ADV
brj-25043	421	30	ranging	range	VERB
brj-25043	421	31	from	from	ADP
brj-25043	421	32	r²	r²	NOUN
brj-25043	421	33	≈	≈	PROPN
brj-25043	421	34	0.60	0.60	NUM
brj-25043	421	35	to	to	ADP
brj-25043	421	36	0.99	0.99	NUM
brj-25043	421	37	depending	depend	VERB
brj-25043	421	38	on	on	ADP
brj-25043	421	39	horizon	horizon	NOUN
brj-25043	421	40	,	,	PUNCT
brj-25043	421	41	inputs	input	NOUN
brj-25043	421	42	,	,	PUNCT
brj-25043	421	43	and	and	CCONJ
brj-25043	421	44	plant	plant	NOUN
brj-25043	421	45	variability	variability	NOUN
brj-25043	421	46	(	(	PUNCT
brj-25043	421	47	schroer	schroer	NOUN
brj-25043	421	48	et	et	PROPN
brj-25043	421	49	al	al	PROPN
brj-25043	421	50	.	.	PROPN
brj-25043	421	51	2023	2023	NUM
brj-25043	421	52	;	;	PUNCT
brj-25043	421	53	yildirim	yildirim	PROPN
brj-25043	421	54	and	and	CCONJ
brj-25043	421	55	ozkaya	ozkaya	PROPN
brj-25043	421	56	2023	2023	NUM
brj-25043	421	57	;	;	PUNCT
brj-25043	421	58	zou	zou	PROPN
brj-25043	421	59	et	et	PROPN
brj-25043	421	60	al	al	PROPN
brj-25043	421	61	.	.	PROPN
brj-25043	421	62	2024	2024	NUM
brj-25043	421	63	;	;	PUNCT
brj-25043	421	64	sun	sun	PROPN
brj-25043	421	65	et	et	PROPN
brj-25043	421	66	al	al	PROPN
brj-25043	421	67	.	.	PROPN
brj-25043	421	68	2023	2023	NUM
brj-25043	421	69	;	;	PUNCT
brj-25043	421	70	salamattalab	salamattalab	NOUN
brj-25043	421	71	et	et	PROPN
brj-25043	421	72	al	al	PROPN
brj-25043	421	73	.	.	PROPN
brj-25043	421	74	2024	2024	NUM
brj-25043	421	75	;	;	PUNCT
brj-25043	421	76	jeong	jeong	PROPN
brj-25043	421	77	et	et	PROPN
brj-25043	421	78	al	al	PROPN
brj-25043	421	79	.	.	PROPN
brj-25043	421	80	2021	2021	NUM
brj-25043	421	81	)	)	PUNCT
brj-25043	421	82	.	.	PUNCT
brj-25043	422	1	feature	feature	NOUN
brj-25043	422	2	attribution	attribution	NOUN
brj-25043	422	3	methods	method	NOUN
brj-25043	422	4	(	(	PUNCT
brj-25043	422	5	e.g.	e.g.	ADV
brj-25043	422	6	,	,	PUNCT
brj-25043	422	7	shap	shap	NOUN
brj-25043	422	8	,	,	PUNCT
brj-25043	422	9	attention	attention	NOUN
brj-25043	422	10	)	)	PUNCT
brj-25043	422	11	consistently	consistently	ADV
brj-25043	422	12	identify	identify	VERB
brj-25043	422	13	olr	olr	NOUN
brj-25043	422	14	,	,	PUNCT
brj-25043	422	15	ph	ph	ADJ
brj-25043	422	16	,	,	PUNCT
brj-25043	422	17	temperature	temperature	NOUN
brj-25043	422	18	,	,	PUNCT
brj-25043	422	19	and	and	CCONJ
brj-25043	422	20	feed	feed	NOUN
brj-25043	422	21	configuration	configuration	NOUN
brj-25043	422	22	as	as	ADP
brj-25043	422	23	the	the	DET
brj-25043	422	24	main	main	ADJ
brj-25043	422	25	factors	factor	NOUN
brj-25043	422	26	,	,	PUNCT
brj-25043	422	27	supporting	support	VERB
brj-25043	422	28	targeted	target	VERB
brj-25043	422	29	set	set	NOUN
brj-25043	422	30	-	-	PUNCT
brj-25043	422	31	point	point	NOUN
brj-25043	422	32	tuning	tuning	NOUN
brj-25043	422	33	and	and	CCONJ
brj-25043	422	34	early	early	ADJ
brj-25043	422	35	-	-	PUNCT
brj-25043	422	36	warning	warning	NOUN
brj-25043	422	37	dashboards	dashboard	NOUN
brj-25043	422	38	(	(	PUNCT
brj-25043	422	39	ling	ling	NOUN
brj-25043	422	40	et	et	PROPN
brj-25043	422	41	al	al	PROPN
brj-25043	422	42	.	.	PROPN
brj-25043	422	43	2024	2024	NUM
brj-25043	422	44	;	;	PUNCT
brj-25043	422	45	zou	zou	PROPN
brj-25043	422	46	et	et	PROPN
brj-25043	422	47	al	al	PROPN
brj-25043	422	48	.	.	PROPN
brj-25043	422	49	2024	2024	NUM
brj-25043	422	50	;	;	PUNCT
brj-25043	422	51	gupta	gupta	PROPN
brj-25043	422	52	et	et	PROPN
brj-25043	422	53	al	al	PROPN
brj-25043	422	54	.	.	PROPN
brj-25043	422	55	2023	2023	NUM
brj-25043	422	56	)	)	PUNCT
brj-25043	422	57	.	.	PUNCT
brj-25043	423	1	from	from	ADP
brj-25043	423	2	an	an	DET
brj-25043	423	3	economic	economic	ADJ
brj-25043	423	4	perspective	perspective	NOUN
brj-25043	423	5	,	,	PUNCT
brj-25043	423	6	the	the	DET
brj-25043	423	7	adoption	adoption	NOUN
brj-25043	423	8	of	of	ADP
brj-25043	423	9	advanced	advanced	ADJ
brj-25043	423	10	ml	ml	NOUN
brj-25043	423	11	models	model	NOUN
brj-25043	423	12	requires	require	VERB
brj-25043	423	13	substantial	substantial	ADJ
brj-25043	423	14	investment	investment	NOUN
brj-25043	423	15	in	in	ADP
brj-25043	423	16	sensors	sensor	NOUN
brj-25043	423	17	,	,	PUNCT
brj-25043	423	18	automated	automate	VERB
brj-25043	423	19	data	data	NOUN
brj-25043	423	20	acquisition	acquisition	NOUN
brj-25043	423	21	systems	system	NOUN
brj-25043	423	22	,	,	PUNCT
brj-25043	423	23	and	and	CCONJ
brj-25043	423	24	skilled	skilled	ADJ
brj-25043	423	25	personnel	personnel	NOUN
brj-25043	423	26	for	for	ADP
brj-25043	423	27	calibration	calibration	NOUN
brj-25043	423	28	and	and	CCONJ
brj-25043	423	29	maintenance	maintenance	NOUN
brj-25043	423	30	.	.	PUNCT
brj-25043	424	1	operational	operational	ADJ
brj-25043	424	2	costs	cost	NOUN
brj-25043	424	3	for	for	ADP
brj-25043	424	4	energy	energy	NOUN
brj-25043	424	5	,	,	PUNCT
brj-25043	424	6	data	datum	NOUN
brj-25043	424	7	storage	storage	NOUN
brj-25043	424	8	,	,	PUNCT
brj-25043	424	9	and	and	CCONJ
brj-25043	424	10	software	software	NOUN
brj-25043	424	11	infrastructure	infrastructure	NOUN
brj-25043	424	12	may	may	AUX
brj-25043	424	13	limit	limit	VERB
brj-25043	424	14	uptake	uptake	ADJ
brj-25043	424	15	,	,	PUNCT
brj-25043	424	16	particularly	particularly	ADV
brj-25043	424	17	in	in	ADP
brj-25043	424	18	resource	resource	NOUN
brj-25043	424	19	-	-	PUNCT
brj-25043	424	20	constrained	constrain	VERB
brj-25043	424	21	contexts	contexts	NOUN
brj-25043	424	22	.	.	PUNCT
brj-25043	425	1	from	from	ADP
brj-25043	425	2	an	an	DET
brj-25043	425	3	engineering	engineering	NOUN
brj-25043	425	4	standpoint	standpoint	NOUN
brj-25043	425	5	,	,	PUNCT
brj-25043	425	6	integrating	integrate	VERB
brj-25043	425	7	predictive	predictive	ADJ
brj-25043	425	8	models	model	NOUN
brj-25043	425	9	into	into	ADP
brj-25043	425	10	real	real	ADJ
brj-25043	425	11	-	-	PUNCT
brj-25043	425	12	time	time	NOUN
brj-25043	425	13	plant	plant	NOUN
brj-25043	425	14	control	control	NOUN
brj-25043	425	15	is	be	AUX
brj-25043	425	16	complex	complex	ADJ
brj-25043	425	17	,	,	PUNCT
brj-25043	425	18	as	as	SCONJ
brj-25043	425	19	biogas	biogas	NOUN
brj-25043	425	20	systems	system	NOUN
brj-25043	425	21	are	be	AUX
brj-25043	425	22	subject	subject	ADJ
brj-25043	425	23	to	to	ADP
brj-25043	425	24	fluctuations	fluctuation	NOUN
brj-25043	425	25	in	in	ADP
brj-25043	425	26	feedstock	feedstock	NOUN
brj-25043	425	27	supply	supply	NOUN
brj-25043	425	28	,	,	PUNCT
brj-25043	425	29	microbial	microbial	ADJ
brj-25043	425	30	community	community	NOUN
brj-25043	425	31	dynamics	dynamic	NOUN
brj-25043	425	32	,	,	PUNCT
brj-25043	425	33	and	and	CCONJ
brj-25043	425	34	environmental	environmental	ADJ
brj-25043	425	35	conditions	condition	NOUN
brj-25043	425	36	.	.	PUNCT
brj-25043	426	1	the	the	DET
brj-25043	426	2	operational	operational	ADJ
brj-25043	426	3	reliability	reliability	NOUN
brj-25043	426	4	of	of	ADP
brj-25043	426	5	iotenabled	iotenable	VERB
brj-25043	426	6	monitoring	monitoring	NOUN
brj-25043	426	7	,	,	PUNCT
brj-25043	426	8	communication	communication	NOUN
brj-25043	426	9	latency	latency	NOUN
brj-25043	426	10	,	,	PUNCT
brj-25043	426	11	and	and	CCONJ
brj-25043	426	12	data	datum	NOUN
brj-25043	426	13	quality	quality	NOUN
brj-25043	426	14	further	far	ADV
brj-25043	426	15	constrain	constrain	VERB
brj-25043	426	16	peer	peer	NOUN
brj-25043	426	17	-	-	PUNCT
brj-25043	426	18	reviewed	review	VERB
brj-25043	426	19	review	review	NOUN
brj-25043	426	20	article	article	NOUN
brj-25043	426	21	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	426	22	galal	galal	PROPN
brj-25043	426	23	et	et	PROPN
brj-25043	426	24	al	al	PROPN
brj-25043	426	25	.	.	PROPN
brj-25043	427	1	(	(	PUNCT
brj-25043	427	2	2025	2025	NUM
brj-25043	427	3	)	)	PUNCT
brj-25043	427	4	.	.	PUNCT
brj-25043	428	1	“	"	PUNCT
brj-25043	428	2	math	math	NOUN
brj-25043	428	3	modeling	modeling	NOUN
brj-25043	428	4	biogas	biogas	NOUN
brj-25043	428	5	production	production	NOUN
brj-25043	428	6	,	,	PUNCT
brj-25043	428	7	”	"	PUNCT
brj-25043	428	8	bioresources	bioresource	NOUN
brj-25043	428	9	20(4	20(4	NOUN
brj-25043	428	10	)	)	PUNCT
brj-25043	428	11	,	,	PUNCT
brj-25043	428	12	11237	11237	NUM
brj-25043	428	13	-	-	SYM
brj-25043	428	14	11266	11266	NUM
brj-25043	428	15	.	.	PUNCT
brj-25043	429	1	11261	11261	NUM
brj-25043	429	2	implementation	implementation	NOUN
brj-25043	429	3	.	.	PUNCT
brj-25043	430	1	these	these	DET
brj-25043	430	2	challenges	challenge	NOUN
brj-25043	430	3	highlight	highlight	VERB
brj-25043	430	4	the	the	DET
brj-25043	430	5	importance	importance	NOUN
brj-25043	430	6	of	of	ADP
brj-25043	430	7	coupling	couple	VERB
brj-25043	430	8	modelling	model	VERB
brj-25043	430	9	studies	study	NOUN
brj-25043	430	10	with	with	ADP
brj-25043	430	11	tea	tea	NOUN
brj-25043	430	12	and	and	CCONJ
brj-25043	430	13	lca	lca	PROPN
brj-25043	430	14	to	to	PART
brj-25043	430	15	ensure	ensure	VERB
brj-25043	430	16	decision	decision	NOUN
brj-25043	430	17	relevance	relevance	NOUN
brj-25043	430	18	.	.	PUNCT
brj-25043	431	1	beyond	beyond	ADP
brj-25043	431	2	established	establish	VERB
brj-25043	431	3	frameworks	framework	NOUN
brj-25043	431	4	,	,	PUNCT
brj-25043	431	5	future	future	ADJ
brj-25043	431	6	research	research	NOUN
brj-25043	431	7	should	should	AUX
brj-25043	431	8	prioritize	prioritize	VERB
brj-25043	431	9	the	the	DET
brj-25043	431	10	development	development	NOUN
brj-25043	431	11	of	of	ADP
brj-25043	431	12	hybrid	hybrid	ADJ
brj-25043	431	13	mechanistic	mechanistic	ADJ
brj-25043	431	14	–	–	PUNCT
brj-25043	431	15	machine	machine	NOUN
brj-25043	431	16	learning	learning	NOUN
brj-25043	431	17	models	model	NOUN
brj-25043	431	18	tailored	tailor	VERB
brj-25043	431	19	specifically	specifically	ADV
brj-25043	431	20	for	for	ADP
brj-25043	431	21	anaerobic	anaerobic	ADJ
brj-25043	431	22	digestion	digestion	NOUN
brj-25043	431	23	.	.	PUNCT
brj-25043	432	1	for	for	ADP
brj-25043	432	2	example	example	NOUN
brj-25043	432	3	,	,	PUNCT
brj-25043	432	4	coupling	couple	VERB
brj-25043	432	5	ann	ann	PROPN
brj-25043	432	6	architectures	architecture	NOUN
brj-25043	432	7	with	with	ADP
brj-25043	432	8	ad	ad	NOUN
brj-25043	432	9	-	-	PUNCT
brj-25043	432	10	specific	specific	ADJ
brj-25043	432	11	kinetic	kinetic	ADJ
brj-25043	432	12	equations	equation	NOUN
brj-25043	432	13	(	(	PUNCT
brj-25043	432	14	e.g.	e.g.	ADV
brj-25043	432	15	,	,	PUNCT
brj-25043	432	16	hydrolysis	hydrolysis	NOUN
brj-25043	432	17	–	–	PUNCT
brj-25043	432	18	acidogenesis	acidogenesis	NOUN
brj-25043	432	19	–	–	PUNCT
brj-25043	432	20	methanogenesis	methanogenesis	NOUN
brj-25043	432	21	dynamics	dynamic	NOUN
brj-25043	432	22	)	)	PUNCT
brj-25043	432	23	could	could	AUX
brj-25043	432	24	combine	combine	VERB
brj-25043	432	25	predictive	predictive	ADJ
brj-25043	432	26	accuracy	accuracy	NOUN
brj-25043	432	27	with	with	ADP
brj-25043	432	28	mechanistic	mechanistic	ADJ
brj-25043	432	29	interpretability	interpretability	NOUN
brj-25043	432	30	.	.	PUNCT
brj-25043	433	1	such	such	ADJ
brj-25043	433	2	models	model	NOUN
brj-25043	433	3	,	,	PUNCT
brj-25043	433	4	trained	train	VERB
brj-25043	433	5	on	on	ADP
brj-25043	433	6	large	large	ADJ
brj-25043	433	7	-	-	PUNCT
brj-25043	433	8	scale	scale	NOUN
brj-25043	433	9	,	,	PUNCT
brj-25043	433	10	multi	multi	ADJ
brj-25043	433	11	-	-	ADJ
brj-25043	433	12	site	site	ADJ
brj-25043	433	13	datasets	dataset	NOUN
brj-25043	433	14	,	,	PUNCT
brj-25043	433	15	would	would	AUX
brj-25043	433	16	enable	enable	VERB
brj-25043	433	17	adaptive	adaptive	ADJ
brj-25043	433	18	real	real	ADJ
brj-25043	433	19	-	-	PUNCT
brj-25043	433	20	time	time	NOUN
brj-25043	433	21	control	control	NOUN
brj-25043	433	22	strategies	strategy	NOUN
brj-25043	433	23	unique	unique	ADJ
brj-25043	433	24	to	to	ADP
brj-25043	433	25	ad	ad	NOUN
brj-25043	433	26	.	.	PUNCT
brj-25043	434	1	this	this	DET
brj-25043	434	2	approach	approach	NOUN
brj-25043	434	3	moves	move	VERB
brj-25043	434	4	beyond	beyond	ADP
brj-25043	434	5	general	general	ADJ
brj-25043	434	6	ml	ml	NOUN
brj-25043	434	7	challenges	challenge	NOUN
brj-25043	434	8	,	,	PUNCT
brj-25043	434	9	offering	offer	VERB
brj-25043	434	10	concrete	concrete	NOUN
brj-25043	434	11	,	,	PUNCT
brj-25043	434	12	novel	novel	ADJ
brj-25043	434	13	pathways	pathway	NOUN
brj-25043	434	14	for	for	ADP
brj-25043	434	15	advancing	advance	VERB
brj-25043	434	16	ad	ad	NOUN
brj-25043	434	17	modelling	modelling	NOUN
brj-25043	434	18	.	.	PUNCT
brj-25043	435	1	conclusions	conclusion	NOUN
brj-25043	435	2	this	this	DET
brj-25043	435	3	review	review	NOUN
brj-25043	435	4	has	have	AUX
brj-25043	435	5	presented	present	VERB
brj-25043	435	6	a	a	DET
brj-25043	435	7	comprehensive	comprehensive	ADJ
brj-25043	435	8	analysis	analysis	NOUN
brj-25043	435	9	of	of	ADP
brj-25043	435	10	the	the	DET
brj-25043	435	11	recent	recent	ADJ
brj-25043	435	12	developments	development	NOUN
brj-25043	435	13	in	in	ADP
brj-25043	435	14	mathematical	mathematical	ADJ
brj-25043	435	15	modeling	modeling	NOUN
brj-25043	435	16	and	and	CCONJ
brj-25043	435	17	ml	ml	ADP
brj-25043	435	18	applications	application	NOUN
brj-25043	435	19	for	for	ADP
brj-25043	435	20	biogas	biogas	NOUN
brj-25043	435	21	production	production	NOUN
brj-25043	435	22	through	through	ADP
brj-25043	435	23	anaerobic	anaerobic	ADJ
brj-25043	435	24	digestion	digestion	NOUN
brj-25043	435	25	.	.	PUNCT
brj-25043	436	1	the	the	DET
brj-25043	436	2	findings	finding	NOUN
brj-25043	436	3	indicate	indicate	VERB
brj-25043	436	4	that	that	SCONJ
brj-25043	436	5	while	while	SCONJ
brj-25043	436	6	classical	classical	ADJ
brj-25043	436	7	kinetic	kinetic	NOUN
brj-25043	436	8	models	model	NOUN
brj-25043	436	9	like	like	ADP
brj-25043	436	10	the	the	DET
brj-25043	436	11	first	first	ADJ
brj-25043	436	12	order	order	NOUN
brj-25043	436	13	and	and	CCONJ
brj-25043	436	14	gompertz	gompertz	NOUN
brj-25043	436	15	provide	provide	VERB
brj-25043	436	16	proper	proper	ADJ
brj-25043	436	17	baseline	baseline	NOUN
brj-25043	436	18	estimations	estimation	NOUN
brj-25043	436	19	,	,	PUNCT
brj-25043	436	20	their	their	PRON
brj-25043	436	21	assumptions	assumption	NOUN
brj-25043	436	22	such	such	ADJ
brj-25043	436	23	as	as	ADP
brj-25043	436	24	limit	limit	NOUN
brj-25043	436	25	performance	performance	NOUN
brj-25043	436	26	under	under	ADP
brj-25043	436	27	complex	complex	ADJ
brj-25043	436	28	and	and	CCONJ
brj-25043	436	29	dynamic	dynamic	ADJ
brj-25043	436	30	ad	ad	NOUN
brj-25043	436	31	conditions	condition	NOUN
brj-25043	436	32	.	.	PUNCT
brj-25043	437	1	in	in	ADP
brj-25043	437	2	contrast	contrast	NOUN
brj-25043	437	3	,	,	PUNCT
brj-25043	437	4	ann	ann	PROPN
brj-25043	437	5	and	and	CCONJ
brj-25043	437	6	ml	ml	PROPN
brj-25043	437	7	techniques	technique	NOUN
brj-25043	437	8	demonstrate	demonstrate	VERB
brj-25043	437	9	superior	superior	ADJ
brj-25043	437	10	predictive	predictive	ADJ
brj-25043	437	11	accuracy	accuracy	NOUN
brj-25043	437	12	,	,	PUNCT
brj-25043	437	13	adaptability	adaptability	NOUN
brj-25043	437	14	,	,	PUNCT
brj-25043	437	15	and	and	CCONJ
brj-25043	437	16	capability	capability	NOUN
brj-25043	437	17	in	in	ADP
brj-25043	437	18	managing	manage	VERB
brj-25043	437	19	nonlinear	nonlinear	ADJ
brj-25043	437	20	and	and	CCONJ
brj-25043	437	21	multivariate	multivariate	NOUN
brj-25043	437	22	systems	system	NOUN
brj-25043	437	23	.	.	PUNCT
brj-25043	438	1	nonetheless	nonetheless	ADV
brj-25043	438	2	,	,	PUNCT
brj-25043	438	3	the	the	DET
brj-25043	438	4	absence	absence	NOUN
brj-25043	438	5	of	of	ADP
brj-25043	438	6	standardized	standardized	ADJ
brj-25043	438	7	datasets	dataset	NOUN
brj-25043	438	8	,	,	PUNCT
brj-25043	438	9	model	model	NOUN
brj-25043	438	10	interpretability	interpretability	NOUN
brj-25043	438	11	issues	issue	NOUN
brj-25043	438	12	,	,	PUNCT
brj-25043	438	13	and	and	CCONJ
brj-25043	438	14	lack	lack	NOUN
brj-25043	438	15	of	of	ADP
brj-25043	438	16	integration	integration	NOUN
brj-25043	438	17	with	with	ADP
brj-25043	438	18	real	real	ADJ
brj-25043	438	19	-	-	PUNCT
brj-25043	438	20	time	time	NOUN
brj-25043	438	21	control	control	NOUN
brj-25043	438	22	systems	system	NOUN
brj-25043	438	23	remain	remain	VERB
brj-25043	438	24	challenges	challenge	NOUN
brj-25043	438	25	.	.	PUNCT
brj-25043	439	1	future	future	ADJ
brj-25043	439	2	research	research	NOUN
brj-25043	439	3	should	should	AUX
brj-25043	439	4	focus	focus	VERB
brj-25043	439	5	on	on	ADP
brj-25043	439	6	hybrid	hybrid	ADJ
brj-25043	439	7	modeling	modeling	NOUN
brj-25043	439	8	approaches	approach	NOUN
brj-25043	439	9	that	that	PRON
brj-25043	439	10	leverage	leverage	VERB
brj-25043	439	11	the	the	DET
brj-25043	439	12	strengths	strength	NOUN
brj-25043	439	13	of	of	ADP
brj-25043	439	14	both	both	CCONJ
brj-25043	439	15	deterministic	deterministic	ADJ
brj-25043	439	16	and	and	CCONJ
brj-25043	439	17	data	data	NOUN
brj-25043	439	18	-	-	PUNCT
brj-25043	439	19	driven	drive	VERB
brj-25043	439	20	methods	method	NOUN
brj-25043	439	21	,	,	PUNCT
brj-25043	439	22	supported	support	VERB
brj-25043	439	23	by	by	ADP
brj-25043	439	24	advanced	advanced	ADJ
brj-25043	439	25	sensing	sense	VERB
brj-25043	439	26	technologies	technology	NOUN
brj-25043	439	27	and	and	CCONJ
brj-25043	439	28	cross	cross	ADJ
brj-25043	439	29	-	-	ADJ
brj-25043	439	30	disciplinary	disciplinary	ADJ
brj-25043	439	31	collaboration	collaboration	NOUN
brj-25043	439	32	.	.	PUNCT
brj-25043	440	1	by	by	ADP
brj-25043	440	2	addressing	address	VERB
brj-25043	440	3	these	these	DET
brj-25043	440	4	gaps	gap	NOUN
brj-25043	440	5	,	,	PUNCT
brj-25043	440	6	the	the	DET
brj-25043	440	7	ad	ad	NOUN
brj-25043	440	8	process	process	NOUN
brj-25043	440	9	can	can	AUX
brj-25043	440	10	be	be	AUX
brj-25043	440	11	optimized	optimize	VERB
brj-25043	440	12	for	for	ADP
brj-25043	440	13	enhanced	enhanced	ADJ
brj-25043	440	14	energy	energy	NOUN
brj-25043	440	15	recovery	recovery	NOUN
brj-25043	440	16	,	,	PUNCT
brj-25043	440	17	system	system	NOUN
brj-25043	440	18	stability	stability	NOUN
brj-25043	440	19	,	,	PUNCT
brj-25043	440	20	and	and	CCONJ
brj-25043	440	21	environmental	environmental	ADJ
brj-25043	440	22	sustainability	sustainability	NOUN
brj-25043	440	23	,	,	PUNCT
brj-25043	440	24	which	which	PRON
brj-25043	440	25	will	will	AUX
brj-25043	440	26	contribute	contribute	VERB
brj-25043	440	27	significantly	significantly	ADV
brj-25043	440	28	to	to	ADP
brj-25043	440	29	circular	circular	ADJ
brj-25043	440	30	economy	economy	NOUN
brj-25043	440	31	strategies	strategy	NOUN
brj-25043	440	32	and	and	CCONJ
brj-25043	440	33	global	global	ADJ
brj-25043	440	34	clean	clean	ADJ
brj-25043	440	35	energy	energy	NOUN
brj-25043	440	36	goals	goal	NOUN
brj-25043	440	37	.	.	PUNCT
brj-25043	441	1	this	this	DET
brj-25043	441	2	review	review	NOUN
brj-25043	441	3	has	have	AUX
brj-25043	441	4	integrated	integrate	VERB
brj-25043	441	5	deterministic	deterministic	ADJ
brj-25043	441	6	kinetics	kinetic	NOUN
brj-25043	441	7	with	with	ADP
brj-25043	441	8	modern	modern	ADJ
brj-25043	441	9	ml	ml	NOUN
brj-25043	441	10	for	for	ADP
brj-25043	441	11	ad	ad	NOUN
brj-25043	441	12	,	,	PUNCT
brj-25043	441	13	providing	provide	VERB
brj-25043	441	14	a	a	DET
brj-25043	441	15	side	side	NOUN
brj-25043	441	16	-	-	PUNCT
brj-25043	441	17	by	by	ADP
brj-25043	441	18	-	-	PUNCT
brj-25043	441	19	side	side	NOUN
brj-25043	441	20	appraisal	appraisal	NOUN
brj-25043	441	21	of	of	ADP
brj-25043	441	22	daily	daily	ADJ
brj-25043	441	23	-	-	PUNCT
brj-25043	441	24	rate	rate	NOUN
brj-25043	441	25	vs.	vs.	ADP
brj-25043	441	26	cumulative	cumulative	ADJ
brj-25043	441	27	-	-	PUNCT
brj-25043	441	28	yield	yield	NOUN
brj-25043	441	29	families	family	NOUN
brj-25043	441	30	and	and	CCONJ
brj-25043	441	31	clarifying	clarify	VERB
brj-25043	441	32	when	when	SCONJ
brj-25043	441	33	first	first	ADJ
brj-25043	441	34	-	-	PUNCT
brj-25043	441	35	order	order	NOUN
brj-25043	441	36	,	,	PUNCT
brj-25043	441	37	modified	modified	ADJ
brj-25043	441	38	gompertz	gompertz	NOUN
brj-25043	441	39	,	,	PUNCT
brj-25043	441	40	or	or	CCONJ
brj-25043	441	41	chen	chen	PROPN
brj-25043	441	42	–	–	PUNCT
brj-25043	441	43	hashimoto	hashimoto	NOUN
brj-25043	441	44	formulations	formulation	NOUN
brj-25043	441	45	are	be	AUX
brj-25043	441	46	most	most	ADV
brj-25043	441	47	defensible	defensible	ADJ
brj-25043	441	48	.	.	PUNCT
brj-25043	442	1	it	it	PRON
brj-25043	442	2	advances	advance	VERB
brj-25043	442	3	a	a	DET
brj-25043	442	4	multidimensional	multidimensional	ADJ
brj-25043	442	5	parameterization	parameterization	NOUN
brj-25043	442	6	that	that	PRON
brj-25043	442	7	elevates	elevate	VERB
brj-25043	442	8	kinetic	kinetic	ADJ
brj-25043	442	9	parameters	parameter	NOUN
brj-25043	442	10	to	to	ADP
brj-25043	442	11	functions	function	NOUN
brj-25043	442	12	of	of	ADP
brj-25043	442	13	operating	operating	NOUN
brj-25043	442	14	variables	variable	NOUN
brj-25043	442	15	,	,	PUNCT
brj-25043	442	16	and	and	CCONJ
brj-25043	442	17	it	it	PRON
brj-25043	442	18	frames	frame	VERB
brj-25043	442	19	parameter	parameter	VERB
brj-25043	442	20	uncertainty	uncertainty	NOUN
brj-25043	442	21	using	use	VERB
brj-25043	442	22	stochastic	stochastic	NOUN
brj-25043	442	23	(	(	PUNCT
brj-25043	442	24	random	random	ADJ
brj-25043	442	25	-	-	PUNCT
brj-25043	442	26	variable	variable	NOUN
brj-25043	442	27	/	/	SYM
brj-25043	442	28	process	process	NOUN
brj-25043	442	29	)	)	PUNCT
brj-25043	442	30	treatments	treatment	NOUN
brj-25043	442	31	to	to	PART
brj-25043	442	32	yield	yield	VERB
brj-25043	442	33	probabilistic	probabilistic	ADJ
brj-25043	442	34	production	production	NOUN
brj-25043	442	35	envelopes	envelope	NOUN
brj-25043	442	36	.	.	PUNCT
brj-25043	443	1	by	by	ADP
brj-25043	443	2	consolidating	consolidate	VERB
brj-25043	443	3	study	study	NOUN
brj-25043	443	4	-	-	PUNCT
brj-25043	443	5	level	level	NOUN
brj-25043	443	6	metrics	metric	NOUN
brj-25043	443	7	and	and	CCONJ
brj-25043	443	8	sensitivity	sensitivity	NOUN
brj-25043	443	9	emphases	emphasis	NOUN
brj-25043	443	10	(	(	PUNCT
brj-25043	443	11	notably	notably	ADV
brj-25043	443	12	a	a	PRON
brj-25043	443	13	and	and	CCONJ
brj-25043	443	14	λ	λ	NOUN
brj-25043	443	15	,	,	PUNCT
brj-25043	443	16	the	the	DET
brj-25043	443	17	work	work	NOUN
brj-25043	443	18	offers	offer	VERB
brj-25043	443	19	a	a	DET
brj-25043	443	20	reproducible	reproducible	ADJ
brj-25043	443	21	basis	basis	NOUN
brj-25043	443	22	for	for	ADP
brj-25043	443	23	model	model	NOUN
brj-25043	443	24	selection	selection	NOUN
brj-25043	443	25	,	,	PUNCT
brj-25043	443	26	benchmarking	benchmarking	NOUN
brj-25043	443	27	,	,	PUNCT
brj-25043	443	28	and	and	CCONJ
brj-25043	443	29	future	future	ADJ
brj-25043	443	30	hybrid	hybrid	ADJ
brj-25043	443	31	mechanistic	mechanistic	ADJ
brj-25043	443	32	–	–	PUNCT
brj-25043	443	33	ml	ml	NOUN
brj-25043	443	34	development	development	NOUN
brj-25043	443	35	.	.	PUNCT
brj-25043	444	1	for	for	ADP
brj-25043	444	2	practitioners	practitioner	NOUN
brj-25043	444	3	,	,	PUNCT
brj-25043	444	4	the	the	DET
brj-25043	444	5	review	review	NOUN
brj-25043	444	6	distills	distill	VERB
brj-25043	444	7	field	field	NOUN
brj-25043	444	8	-	-	PUNCT
brj-25043	444	9	scale	scale	NOUN
brj-25043	444	10	evidence	evidence	NOUN
brj-25043	444	11	that	that	SCONJ
brj-25043	444	12	ml	ml	INTJ
brj-25043	444	13	(	(	PUNCT
brj-25043	444	14	ensembles	ensemble	NOUN
brj-25043	444	15	and	and	CCONJ
brj-25043	444	16	sequence	sequence	NOUN
brj-25043	444	17	models	model	NOUN
brj-25043	444	18	)	)	PUNCT
brj-25043	444	19	can	can	AUX
brj-25043	444	20	provide	provide	VERB
brj-25043	444	21	short	short	ADJ
brj-25043	444	22	-	-	PUNCT
brj-25043	444	23	horizon	horizon	NOUN
brj-25043	444	24	forecasts	forecast	NOUN
brj-25043	444	25	and	and	CCONJ
brj-25043	444	26	soft	soft	ADJ
brj-25043	444	27	-	-	PUNCT
brj-25043	444	28	sensor	sensor	NOUN
brj-25043	444	29	proxies	proxy	NOUN
brj-25043	444	30	at	at	ADP
brj-25043	444	31	accuracy	accuracy	NOUN
brj-25043	444	32	suitable	suitable	ADJ
brj-25043	444	33	for	for	ADP
brj-25043	444	34	day	day	NOUN
brj-25043	444	35	-	-	PUNCT
brj-25043	444	36	to	to	ADP
brj-25043	444	37	-	-	PUNCT
brj-25043	444	38	day	day	NOUN
brj-25043	444	39	control	control	NOUN
brj-25043	444	40	,	,	PUNCT
brj-25043	444	41	while	while	SCONJ
brj-25043	444	42	retaining	retain	VERB
brj-25043	444	43	modified	modify	VERB
brj-25043	444	44	-	-	PUNCT
brj-25043	444	45	gompertz	gompertz	NOUN
brj-25043	444	46	-	-	PUNCT
brj-25043	444	47	type	type	NOUN
brj-25043	444	48	kinetics	kinetic	NOUN
brj-25043	444	49	for	for	ADP
brj-25043	444	50	design	design	NOUN
brj-25043	444	51	and	and	CCONJ
brj-25043	444	52	batch	batch	NOUN
brj-25043	444	53	/	/	SYM
brj-25043	444	54	bmp	bmp	NOUN
brj-25043	444	55	contexts	contexts	NOUN
brj-25043	444	56	.	.	PUNCT
brj-25043	445	1	it	it	PRON
brj-25043	445	2	maps	map	VERB
brj-25043	445	3	explainable	explainable	ADJ
brj-25043	445	4	features	feature	NOUN
brj-25043	445	5	(	(	PUNCT
brj-25043	445	6	olr	olr	NOUN
brj-25043	445	7	,	,	PUNCT
brj-25043	445	8	ph	ph	ADJ
brj-25043	445	9	,	,	PUNCT
brj-25043	445	10	temperature	temperature	NOUN
brj-25043	445	11	,	,	PUNCT
brj-25043	445	12	feed	feed	NOUN
brj-25043	445	13	configuration	configuration	NOUN
brj-25043	445	14	)	)	PUNCT
brj-25043	445	15	to	to	ADP
brj-25043	445	16	actionable	actionable	ADJ
brj-25043	445	17	levers	lever	NOUN
brj-25043	445	18	,	,	PUNCT
brj-25043	445	19	outlines	outline	VERB
brj-25043	445	20	a	a	DET
brj-25043	445	21	pragmatic	pragmatic	ADJ
brj-25043	445	22	deployment	deployment	NOUN
brj-25043	445	23	recipe	recipe	NOUN
brj-25043	445	24	(	(	PUNCT
brj-25043	445	25	clean	clean	ADJ
brj-25043	445	26	scada	scada	PROPN
brj-25043	445	27	ingestion	ingestion	PROPN
brj-25043	445	28	,	,	PUNCT
brj-25043	445	29	rolling	rolling	ADJ
brj-25043	445	30	/	/	SYM
brj-25043	445	31	external	external	ADJ
brj-25043	445	32	validation	validation	NOUN
brj-25043	445	33	,	,	PUNCT
brj-25043	445	34	probabilistic	probabilistic	ADJ
brj-25043	445	35	outputs	output	NOUN
brj-25043	445	36	)	)	PUNCT
brj-25043	445	37	,	,	PUNCT
brj-25043	445	38	and	and	CCONJ
brj-25043	445	39	proposes	propose	VERB
brj-25043	445	40	a	a	DET
brj-25043	445	41	hybrid	hybrid	ADJ
brj-25043	445	42	mechanistic	mechanistic	ADJ
brj-25043	445	43	–	–	PUNCT
brj-25043	445	44	ml	ml	ADV
brj-25043	445	45	blueprint	blueprint	NOUN
brj-25043	445	46	compatible	compatible	ADJ
brj-25043	445	47	with	with	ADP
brj-25043	445	48	iot	iot	ADJ
brj-25043	445	49	“	"	PUNCT
brj-25043	445	50	smart	smart	ADJ
brj-25043	445	51	digester	digester	NOUN
brj-25043	445	52	”	"	PUNCT
brj-25043	445	53	dashboards	dashboard	NOUN
brj-25043	445	54	.	.	PUNCT
brj-25043	446	1	these	these	DET
brj-25043	446	2	guidance	guidance	NOUN
brj-25043	446	3	points	point	NOUN
brj-25043	446	4	translate	translate	ADJ
brj-25043	446	5	model	model	NOUN
brj-25043	446	6	choice	choice	NOUN
brj-25043	446	7	into	into	ADP
brj-25043	446	8	concrete	concrete	ADJ
brj-25043	446	9	decisions	decision	NOUN
brj-25043	446	10	on	on	ADP
brj-25043	446	11	olr	olr	NOUN
brj-25043	446	12	ramps	ramp	NOUN
brj-25043	446	13	,	,	PUNCT
brj-25043	446	14	hrt	hrt	PROPN
brj-25043	446	15	adjustments	adjustment	NOUN
brj-25043	446	16	,	,	PUNCT
brj-25043	446	17	co	co	ADJ
brj-25043	446	18	-	-	NOUN
brj-25043	446	19	substrate	substrate	ADJ
brj-25043	446	20	scheduling	scheduling	NOUN
brj-25043	446	21	,	,	PUNCT
brj-25043	446	22	and	and	CCONJ
brj-25043	446	23	risk	risk	NOUN
brj-25043	446	24	-	-	PUNCT
brj-25043	446	25	aware	aware	ADJ
brj-25043	446	26	operations	operation	NOUN
brj-25043	446	27	.	.	PUNCT
brj-25043	447	1	finally	finally	ADV
brj-25043	447	2	,	,	PUNCT
brj-25043	447	3	we	we	PRON
brj-25043	447	4	recommend	recommend	VERB
brj-25043	447	5	reporting	report	VERB
brj-25043	447	6	sustainability	sustainability	NOUN
brj-25043	447	7	kpis	kpis	PROPN
brj-25043	447	8	(	(	PUNCT
brj-25043	447	9	e.g.	e.g.	ADV
brj-25043	447	10	,	,	PUNCT
brj-25043	447	11	gwp	gwp	PROPN
brj-25043	447	12	per	per	ADP
brj-25043	447	13	kwh	kwh	PROPN
brj-25043	447	14	,	,	PUNCT
brj-25043	447	15	lcoe	lcoe	ADJ
brj-25043	447	16	/	/	SYM
brj-25043	447	17	lcbg	lcbg	NOUN
brj-25043	447	18	)	)	PUNCT
brj-25043	447	19	alongside	alongside	ADP
brj-25043	447	20	predictive	predictive	ADJ
brj-25043	447	21	accuracy	accuracy	NOUN
brj-25043	447	22	and	and	CCONJ
brj-25043	447	23	using	use	VERB
brj-25043	447	24	probabilistic	probabilistic	ADJ
brj-25043	447	25	ml	ml	PROPN
brj-25043	447	26	outputs	output	NOUN
brj-25043	447	27	to	to	ADP
brj-25043	447	28	peer	peer	NOUN
brj-25043	447	29	-	-	PUNCT
brj-25043	447	30	reviewed	review	VERB
brj-25043	447	31	review	review	NOUN
brj-25043	447	32	article	article	NOUN
brj-25043	447	33	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	447	34	galal	galal	PROPN
brj-25043	447	35	et	et	PROPN
brj-25043	447	36	al	al	PROPN
brj-25043	447	37	.	.	PROPN
brj-25043	448	1	(	(	PUNCT
brj-25043	448	2	2025	2025	NUM
brj-25043	448	3	)	)	PUNCT
brj-25043	448	4	.	.	PUNCT
brj-25043	449	1	“	"	PUNCT
brj-25043	449	2	math	math	NOUN
brj-25043	449	3	modeling	modeling	NOUN
brj-25043	449	4	biogas	biogas	NOUN
brj-25043	449	5	production	production	NOUN
brj-25043	449	6	,	,	PUNCT
brj-25043	449	7	”	"	PUNCT
brj-25043	449	8	bioresources	bioresource	NOUN
brj-25043	449	9	20(4	20(4	NOUN
brj-25043	449	10	)	)	PUNCT
brj-25043	449	11	,	,	PUNCT
brj-25043	449	12	11237	11237	NUM
brj-25043	449	13	-	-	SYM
brj-25043	449	14	11266	11266	NUM
brj-25043	449	15	.	.	PUNCT
brj-25043	450	1	11262	11262	NUM
brj-25043	450	2	propagate	propagate	VERB
brj-25043	450	3	uncertainty	uncertainty	NOUN
brj-25043	450	4	into	into	ADP
brj-25043	450	5	lca	lca	PROPN
brj-25043	450	6	/	/	SYM
brj-25043	450	7	tea	tea	NOUN
brj-25043	450	8	,	,	PUNCT
brj-25043	450	9	enabling	enable	VERB
brj-25043	450	10	pareto	pareto	NOUN
brj-25043	450	11	-	-	PUNCT
brj-25043	450	12	based	base	VERB
brj-25043	450	13	selection	selection	NOUN
brj-25043	450	14	of	of	ADP
brj-25043	450	15	operating	operating	NOUN
brj-25043	450	16	setpoints	setpoint	NOUN
brj-25043	450	17	and	and	CCONJ
brj-25043	450	18	co	co	NOUN
brj-25043	450	19	-	-	NOUN
brj-25043	450	20	digestion	digestion	NOUN
brj-25043	450	21	strategies	strategy	NOUN
brj-25043	450	22	.	.	PUNCT
brj-25043	451	1	acknowledgments	acknowledgment	NOUN
brj-25043	451	2	the	the	DET
brj-25043	451	3	author	author	NOUN
brj-25043	451	4	would	would	AUX
brj-25043	451	5	like	like	VERB
brj-25043	451	6	to	to	PART
brj-25043	451	7	thank	thank	VERB
brj-25043	451	8	the	the	DET
brj-25043	451	9	deanship	deanship	NOUN
brj-25043	451	10	of	of	ADP
brj-25043	451	11	scientific	scientific	ADJ
brj-25043	451	12	research	research	NOUN
brj-25043	451	13	at	at	ADP
brj-25043	451	14	shaqra	shaqra	PROPN
brj-25043	451	15	university	university	PROPN
brj-25043	451	16	for	for	ADP
brj-25043	451	17	supporting	support	VERB
brj-25043	451	18	this	this	DET
brj-25043	451	19	work	work	NOUN
brj-25043	451	20	.	.	PUNCT
brj-25043	452	1	references	reference	NOUN
brj-25043	452	2	cited	cite	VERB
brj-25043	452	3	abdel	abdel	PROPN
brj-25043	452	4	daiem	daiem	PROPN
brj-25043	452	5	,	,	PUNCT
brj-25043	452	6	m.	m.	NOUN
brj-25043	452	7	m.	m.	NOUN
brj-25043	452	8	,	,	PUNCT
brj-25043	452	9	hatata	hatata	PROPN
brj-25043	452	10	,	,	PUNCT
brj-25043	452	11	a.	a.	NOUN
brj-25043	452	12	,	,	PUNCT
brj-25043	452	13	galal	galal	PROPN
brj-25043	452	14	,	,	PUNCT
brj-25043	452	15	o.	o.	PROPN
brj-25043	452	16	h.	h.	PROPN
brj-25043	452	17	,	,	PUNCT
brj-25043	452	18	said	say	VERB
brj-25043	452	19	,	,	PUNCT
brj-25043	452	20	n.	n.	NOUN
brj-25043	452	21	,	,	PUNCT
brj-25043	452	22	and	and	CCONJ
brj-25043	452	23	ahmed	ahmed	PROPN
brj-25043	452	24	,	,	PUNCT
brj-25043	452	25	d.	d.	PROPN
brj-25043	452	26	(	(	PUNCT
brj-25043	452	27	2021	2021	NUM
brj-25043	452	28	)	)	PUNCT
brj-25043	452	29	.	.	PUNCT
brj-25043	453	1	“	"	PUNCT
brj-25043	453	2	prediction	prediction	NOUN
brj-25043	453	3	of	of	ADP
brj-25043	453	4	biogas	biogas	NOUN
brj-25043	453	5	production	production	NOUN
brj-25043	453	6	from	from	ADP
brj-25043	453	7	anaerobic	anaerobic	ADJ
brj-25043	453	8	co	co	NOUN
brj-25043	453	9	-	-	NOUN
brj-25043	453	10	digestion	digestion	NOUN
brj-25043	453	11	of	of	ADP
brj-25043	453	12	waste	waste	NOUN
brj-25043	453	13	activated	activate	VERB
brj-25043	453	14	sludge	sludge	NOUN
brj-25043	453	15	and	and	CCONJ
brj-25043	453	16	wheat	wheat	NOUN
brj-25043	453	17	straw	straw	NOUN
brj-25043	453	18	using	use	VERB
brj-25043	453	19	two	two	NUM
brj-25043	453	20	-	-	PUNCT
brj-25043	453	21	dimensional	dimensional	ADJ
brj-25043	453	22	mathematical	mathematical	ADJ
brj-25043	453	23	models	model	NOUN
brj-25043	453	24	and	and	CCONJ
brj-25043	453	25	an	an	DET
brj-25043	453	26	artificial	artificial	ADJ
brj-25043	453	27	neural	neural	ADJ
brj-25043	453	28	network	network	NOUN
brj-25043	453	29	,	,	PUNCT
brj-25043	453	30	”	"	PUNCT
brj-25043	453	31	renewable	renewable	ADJ
brj-25043	453	32	energy	energy	NOUN
brj-25043	453	33	178	178	NUM
brj-25043	453	34	,	,	PUNCT
brj-25043	453	35	226	226	NUM
brj-25043	453	36	-	-	SYM
brj-25043	453	37	240	240	NUM
brj-25043	453	38	.	.	PUNCT
brj-25043	454	1	doi	doi	NOUN
brj-25043	454	2	:	:	PUNCT
brj-25043	455	1	10.1016	10.1016	NUM
brj-25043	455	2	/	/	SYM
brj-25043	455	3	j.renene.2021.06.050	j.renene.2021.06.050	PROPN
brj-25043	455	4	adeleke	adeleke	ADJ
brj-25043	455	5	,	,	PUNCT
brj-25043	455	6	o.	o.	INTJ
brj-25043	455	7	,	,	PUNCT
brj-25043	455	8	olatunji	olatunji	PROPN
brj-25043	455	9	,	,	PUNCT
brj-25043	455	10	k.	k.	PROPN
brj-25043	455	11	o.	o.	PROPN
brj-25043	455	12	,	,	PUNCT
brj-25043	455	13	madyira	madyira	PROPN
brj-25043	455	14	,	,	PUNCT
brj-25043	455	15	d.	d.	PROPN
brj-25043	455	16	m.	m.	PROPN
brj-25043	455	17	,	,	PUNCT
brj-25043	455	18	and	and	CCONJ
brj-25043	455	19	jen	jen	PROPN
brj-25043	455	20	,	,	PUNCT
brj-25043	455	21	t.-c	t.-c	PROPN
brj-25043	455	22	.	.	PUNCT
brj-25043	456	1	(	(	PUNCT
brj-25043	456	2	2025	2025	NUM
brj-25043	456	3	)	)	PUNCT
brj-25043	456	4	.	.	PUNCT
brj-25043	457	1	“	"	PUNCT
brj-25043	457	2	application	application	NOUN
brj-25043	457	3	of	of	ADP
brj-25043	457	4	multimodal	multimodal	NOUN
brj-25043	457	5	machine	machine	NOUN
brj-25043	457	6	learning	learning	NOUN
brj-25043	457	7	-	-	PUNCT
brj-25043	457	8	based	base	VERB
brj-25043	457	9	analysis	analysis	NOUN
brj-25043	457	10	for	for	ADP
brj-25043	457	11	the	the	DET
brj-25043	457	12	biomethane	biomethane	NOUN
brj-25043	457	13	yields	yield	NOUN
brj-25043	457	14	of	of	ADP
brj-25043	457	15	naohpretreated	naohpretreate	VERB
brj-25043	457	16	biomass	biomass	NOUN
brj-25043	457	17	,	,	PUNCT
brj-25043	457	18	”	"	PUNCT
brj-25043	457	19	scientific	scientific	ADJ
brj-25043	457	20	reports	report	NOUN
brj-25043	457	21	15(1	15(1	NUM
brj-25043	457	22	)	)	PUNCT
brj-25043	457	23	,	,	PUNCT
brj-25043	457	24	article	article	NOUN
brj-25043	457	25	24372	24372	NUM
brj-25043	457	26	.	.	PUNCT
brj-25043	458	1	doi	doi	NOUN
brj-25043	458	2	:	:	PUNCT
brj-25043	458	3	10.1038	10.1038	NUM
brj-25043	458	4	/	/	SYM
brj-25043	458	5	s41598025	s41598025	NOUN
brj-25043	458	6	-	-	PUNCT
brj-25043	458	7	09527	09527	NUM
brj-25043	458	8	-	-	SYM
brj-25043	458	9	5	5	NUM
brj-25043	458	10	adnane	adnane	NOUN
brj-25043	458	11	,	,	PUNCT
brj-25043	458	12	i.	i.	NOUN
brj-25043	458	13	,	,	PUNCT
brj-25043	458	14	taoumi	taoumi	PROPN
brj-25043	458	15	,	,	PUNCT
brj-25043	458	16	h.	h.	PROPN
brj-25043	458	17	,	,	PUNCT
brj-25043	458	18	elouahabi	elouahabi	NOUN
brj-25043	458	19	,	,	PUNCT
brj-25043	458	20	k.	k.	PROPN
brj-25043	458	21	,	,	PUNCT
brj-25043	458	22	lahrech	lahrech	PROPN
brj-25043	458	23	,	,	PUNCT
brj-25043	458	24	k.	k.	PROPN
brj-25043	458	25	,	,	PUNCT
brj-25043	458	26	and	and	CCONJ
brj-25043	458	27	oulmekki	oulmekki	ADJ
brj-25043	458	28	,	,	PUNCT
brj-25043	458	29	a.	a.	NOUN
brj-25043	458	30	(	(	PUNCT
brj-25043	458	31	2024	2024	NUM
brj-25043	458	32	)	)	PUNCT
brj-25043	458	33	.	.	PUNCT
brj-25043	459	1	“	"	PUNCT
brj-25043	459	2	valorization	valorization	NOUN
brj-25043	459	3	of	of	ADP
brj-25043	459	4	crop	crop	NOUN
brj-25043	459	5	residues	residue	NOUN
brj-25043	459	6	and	and	CCONJ
brj-25043	459	7	animal	animal	NOUN
brj-25043	459	8	wastes	waste	NOUN
brj-25043	459	9	:	:	PUNCT
brj-25043	459	10	anaerobic	anaerobic	NOUN
brj-25043	459	11	co	co	NOUN
brj-25043	459	12	-	-	NOUN
brj-25043	459	13	digestion	digestion	NOUN
brj-25043	459	14	technology	technology	NOUN
brj-25043	459	15	,	,	PUNCT
brj-25043	459	16	”	"	PUNCT
brj-25043	459	17	heliyon	heliyon	NOUN
brj-25043	459	18	10(5	10(5	NUM
brj-25043	459	19	)	)	PUNCT
brj-25043	459	20	,	,	PUNCT
brj-25043	459	21	article	article	NOUN
brj-25043	459	22	e26440	e26440	PROPN
brj-25043	459	23	.	.	PUNCT
brj-25043	459	24	doi	doi	PROPN
brj-25043	459	25	:	:	PUNCT
brj-25043	459	26	10.1016	10.1016	NUM
brj-25043	459	27	/	/	SYM
brj-25043	459	28	j.heliyon.2024.e26440	j.heliyon.2024.e26440	PROPN
brj-25043	459	29	alengebawy	alengebawy	PROPN
brj-25043	459	30	,	,	PUNCT
brj-25043	459	31	a.	a.	NOUN
brj-25043	459	32	,	,	PUNCT
brj-25043	459	33	ran	run	VERB
brj-25043	459	34	,	,	PUNCT
brj-25043	459	35	y.	y.	PROPN
brj-25043	459	36	,	,	PUNCT
brj-25043	459	37	osman	osman	PROPN
brj-25043	459	38	,	,	PUNCT
brj-25043	459	39	a.	a.	NOUN
brj-25043	459	40	i.	i.	PROPN
brj-25043	459	41	,	,	PUNCT
brj-25043	459	42	jin	jin	PROPN
brj-25043	459	43	,	,	PUNCT
brj-25043	459	44	k.	k.	PROPN
brj-25043	459	45	,	,	PUNCT
brj-25043	459	46	samer	samer	PROPN
brj-25043	459	47	,	,	PUNCT
brj-25043	459	48	m.	m.	NOUN
brj-25043	459	49	,	,	PUNCT
brj-25043	459	50	and	and	CCONJ
brj-25043	459	51	ai	ai	VERB
brj-25043	459	52	,	,	PUNCT
brj-25043	459	53	p.	p.	NOUN
brj-25043	459	54	(	(	PUNCT
brj-25043	459	55	2024	2024	NUM
brj-25043	459	56	)	)	PUNCT
brj-25043	459	57	.	.	PUNCT
brj-25043	460	1	“	"	PUNCT
brj-25043	460	2	anaerobic	anaerobic	ADJ
brj-25043	460	3	digestion	digestion	NOUN
brj-25043	460	4	of	of	ADP
brj-25043	460	5	agricultural	agricultural	ADJ
brj-25043	460	6	waste	waste	NOUN
brj-25043	460	7	for	for	ADP
brj-25043	460	8	biogas	biogas	NOUN
brj-25043	460	9	production	production	NOUN
brj-25043	460	10	and	and	CCONJ
brj-25043	460	11	sustainable	sustainable	ADJ
brj-25043	460	12	bioenergy	bioenergy	NOUN
brj-25043	460	13	recovery	recovery	NOUN
brj-25043	460	14	:	:	PUNCT
brj-25043	460	15	a	a	DET
brj-25043	460	16	review	review	NOUN
brj-25043	460	17	,	,	PUNCT
brj-25043	460	18	”	"	PUNCT
brj-25043	460	19	environmental	environmental	ADJ
brj-25043	460	20	chemistry	chemistry	NOUN
brj-25043	460	21	letters	letter	NOUN
brj-25043	460	22	22	22	NUM
brj-25043	460	23	,	,	PUNCT
brj-25043	460	24	2641	2641	NUM
brj-25043	460	25	-	-	SYM
brj-25043	460	26	2668	2668	NUM
brj-25043	460	27	.	.	PUNCT
brj-25043	461	1	doi	doi	NOUN
brj-25043	461	2	:	:	PUNCT
brj-25043	461	3	10.1007	10.1007	NUM
brj-25043	461	4	/	/	SYM
brj-25043	461	5	s10311	s10311	NOUN
brj-25043	461	6	-	-	PUNCT
brj-25043	461	7	024	024	NUM
brj-25043	461	8	-	-	PUNCT
brj-25043	461	9	01789	01789	NUM
brj-25043	461	10	-	-	SYM
brj-25043	461	11	1	1	NUM
brj-25043	461	12	altaş	altaş	NOUN
brj-25043	461	13	,	,	PUNCT
brj-25043	461	14	l.	l.	PROPN
brj-25043	461	15	(	(	PUNCT
brj-25043	461	16	2009	2009	NUM
brj-25043	461	17	)	)	PUNCT
brj-25043	461	18	.	.	PUNCT
brj-25043	462	1	“	"	PUNCT
brj-25043	462	2	inhibitory	inhibitory	ADJ
brj-25043	462	3	effect	effect	NOUN
brj-25043	462	4	of	of	ADP
brj-25043	462	5	heavy	heavy	ADJ
brj-25043	462	6	metals	metal	NOUN
brj-25043	462	7	on	on	ADP
brj-25043	462	8	methane	methane	NOUN
brj-25043	462	9	-	-	PUNCT
brj-25043	462	10	producing	produce	VERB
brj-25043	462	11	anaerobic	anaerobic	NOUN
brj-25043	462	12	granular	granular	ADJ
brj-25043	462	13	sludge	sludge	NOUN
brj-25043	462	14	,	,	PUNCT
brj-25043	462	15	”	"	PUNCT
brj-25043	462	16	journal	journal	NOUN
brj-25043	462	17	of	of	ADP
brj-25043	462	18	hazardous	hazardous	ADJ
brj-25043	462	19	materials	material	NOUN
brj-25043	462	20	162(2–3	162(2–3	NUM
brj-25043	462	21	)	)	PUNCT
brj-25043	462	22	,	,	PUNCT
brj-25043	462	23	1551	1551	NUM
brj-25043	462	24	-	-	SYM
brj-25043	462	25	1556	1556	NUM
brj-25043	462	26	.	.	PUNCT
brj-25043	463	1	doi	doi	NOUN
brj-25043	463	2	:	:	PUNCT
brj-25043	463	3	10.1016	10.1016	NUM
brj-25043	463	4	/	/	SYM
brj-25043	463	5	j.jhazmat.2008.06.048	j.jhazmat.2008.06.048	PROPN
brj-25043	463	6	amleh	amleh	PROPN
brj-25043	463	7	,	,	PUNCT
brj-25043	463	8	m.	m.	NOUN
brj-25043	463	9	a.	a.	NOUN
brj-25043	463	10	,	,	PUNCT
brj-25043	463	11	and	and	CCONJ
brj-25043	463	12	al	al	PROPN
brj-25043	463	13	-	-	PUNCT
brj-25043	463	14	freihat	freihat	PROPN
brj-25043	463	15	,	,	PUNCT
brj-25043	463	16	i.	i.	PROPN
brj-25043	463	17	f.	f.	PROPN
brj-25043	463	18	(	(	PUNCT
brj-25043	463	19	2025	2025	NUM
brj-25043	463	20	)	)	PUNCT
brj-25043	463	21	.	.	PUNCT
brj-25043	464	1	“	"	PUNCT
brj-25043	464	2	prediction	prediction	NOUN
brj-25043	464	3	of	of	ADP
brj-25043	464	4	new	new	ADJ
brj-25043	464	5	lifetimes	lifetime	NOUN
brj-25043	464	6	of	of	ADP
brj-25043	464	7	a	a	DET
brj-25043	464	8	step	step	NOUN
brj-25043	464	9	-	-	PUNCT
brj-25043	464	10	stress	stress	NOUN
brj-25043	464	11	test	test	NOUN
brj-25043	464	12	using	use	VERB
brj-25043	464	13	cumulative	cumulative	ADJ
brj-25043	464	14	exposure	exposure	NOUN
brj-25043	464	15	model	model	NOUN
brj-25043	464	16	with	with	ADP
brj-25043	464	17	censored	censored	ADJ
brj-25043	464	18	gompertz	gompertz	NOUN
brj-25043	464	19	data	datum	NOUN
brj-25043	464	20	,	,	PUNCT
brj-25043	464	21	”	"	PUNCT
brj-25043	464	22	statistics	statistic	NOUN
brj-25043	464	23	,	,	PUNCT
brj-25043	464	24	optimization	optimization	NOUN
brj-25043	464	25	&	&	CCONJ
brj-25043	464	26	information	information	NOUN
brj-25043	464	27	computing	compute	VERB
brj-25043	464	28	13(4	13(4	NUM
brj-25043	464	29	)	)	PUNCT
brj-25043	464	30	,	,	PUNCT
brj-25043	464	31	1368	1368	NUM
brj-25043	464	32	-	-	SYM
brj-25043	464	33	1387	1387	NUM
brj-25043	464	34	.	.	PUNCT
brj-25043	465	1	doi	doi	NOUN
brj-25043	465	2	:	:	PUNCT
brj-25043	465	3	10.19139	10.19139	NUM
brj-25043	465	4	/	/	SYM
brj-25043	465	5	soic-23105070	soic-23105070	ADJ
brj-25043	465	6	-	-	PUNCT
brj-25043	465	7	1852	1852	NUM
brj-25043	465	8	asadi	asadi	NOUN
brj-25043	465	9	,	,	PUNCT
brj-25043	465	10	m.	m.	NOUN
brj-25043	465	11	,	,	PUNCT
brj-25043	465	12	and	and	CCONJ
brj-25043	465	13	mcphedran	mcphedran	NOUN
brj-25043	465	14	,	,	PUNCT
brj-25043	465	15	k.	k.	PROPN
brj-25043	465	16	(	(	PUNCT
brj-25043	465	17	2021	2021	NUM
brj-25043	465	18	)	)	PUNCT
brj-25043	465	19	.	.	PUNCT
brj-25043	466	1	“	"	PUNCT
brj-25043	466	2	biogas	biogas	NOUN
brj-25043	466	3	maximization	maximization	NOUN
brj-25043	466	4	using	use	VERB
brj-25043	466	5	data	data	NOUN
brj-25043	466	6	-	-	PUNCT
brj-25043	466	7	driven	drive	VERB
brj-25043	466	8	modelling	modelling	NOUN
brj-25043	466	9	with	with	ADP
brj-25043	466	10	uncertainty	uncertainty	NOUN
brj-25043	466	11	analysis	analysis	NOUN
brj-25043	466	12	and	and	CCONJ
brj-25043	466	13	genetic	genetic	ADJ
brj-25043	466	14	algorithm	algorithm	NOUN
brj-25043	466	15	for	for	ADP
brj-25043	466	16	municipal	municipal	ADJ
brj-25043	466	17	wastewater	wastewater	NOUN
brj-25043	466	18	anaerobic	anaerobic	NOUN
brj-25043	466	19	digestion	digestion	NOUN
brj-25043	466	20	,	,	PUNCT
brj-25043	466	21	”	"	PUNCT
brj-25043	466	22	journal	journal	NOUN
brj-25043	466	23	of	of	ADP
brj-25043	466	24	environmental	environmental	ADJ
brj-25043	466	25	management	management	NOUN
brj-25043	466	26	293	293	NUM
brj-25043	466	27	,	,	PUNCT
brj-25043	466	28	article	article	NOUN
brj-25043	466	29	112875	112875	NUM
brj-25043	466	30	.	.	PUNCT
brj-25043	467	1	doi	doi	NOUN
brj-25043	467	2	:	:	PUNCT
brj-25043	467	3	10.1016	10.1016	NUM
brj-25043	467	4	/	/	SYM
brj-25043	467	5	j.jenvman.2021.112875	j.jenvman.2021.112875	PROPN
brj-25043	467	6	beltramo	beltramo	PROPN
brj-25043	467	7	,	,	PUNCT
brj-25043	467	8	t.	t.	PROPN
brj-25043	467	9	,	,	PUNCT
brj-25043	467	10	klocke	klocke	PROPN
brj-25043	467	11	,	,	PUNCT
brj-25043	467	12	m.	m.	NOUN
brj-25043	467	13	,	,	PUNCT
brj-25043	467	14	and	and	CCONJ
brj-25043	467	15	hitzmann	hitzmann	PROPN
brj-25043	467	16	,	,	PUNCT
brj-25043	467	17	b.	b.	PROPN
brj-25043	467	18	(	(	PUNCT
brj-25043	467	19	2019	2019	NUM
brj-25043	467	20	)	)	PUNCT
brj-25043	467	21	.	.	PUNCT
brj-25043	468	1	“	"	PUNCT
brj-25043	468	2	prediction	prediction	NOUN
brj-25043	468	3	of	of	ADP
brj-25043	468	4	the	the	DET
brj-25043	468	5	biogas	biogas	NOUN
brj-25043	468	6	production	production	NOUN
brj-25043	468	7	using	use	VERB
brj-25043	468	8	ga	ga	PROPN
brj-25043	468	9	and	and	CCONJ
brj-25043	468	10	aco	aco	PROPN
brj-25043	468	11	input	input	PROPN
brj-25043	468	12	features	feature	VERB
brj-25043	468	13	selection	selection	NOUN
brj-25043	468	14	method	method	NOUN
brj-25043	468	15	for	for	ADP
brj-25043	468	16	ann	ann	PROPN
brj-25043	468	17	model	model	NOUN
brj-25043	468	18	,	,	PUNCT
brj-25043	468	19	”	"	PUNCT
brj-25043	468	20	information	information	NOUN
brj-25043	468	21	processing	processing	NOUN
brj-25043	468	22	in	in	ADP
brj-25043	468	23	agriculture	agriculture	NOUN
brj-25043	468	24	6(3	6(3	PROPN
brj-25043	468	25	)	)	PUNCT
brj-25043	468	26	,	,	PUNCT
brj-25043	468	27	349	349	NUM
brj-25043	468	28	-	-	SYM
brj-25043	468	29	356	356	NUM
brj-25043	468	30	.	.	PUNCT
brj-25043	469	1	doi	doi	NOUN
brj-25043	469	2	:	:	PUNCT
brj-25043	469	3	10.1016	10.1016	NUM
brj-25043	469	4	/	/	SYM
brj-25043	469	5	j.inpa.2019.01.002	j.inpa.2019.01.002	NOUN
brj-25043	469	6	bilgili	bilgili	NOUN
brj-25043	469	7	,	,	PUNCT
brj-25043	469	8	m.	m.	NOUN
brj-25043	469	9	s.	s.	PROPN
brj-25043	469	10	,	,	PUNCT
brj-25043	469	11	demir	demir	PROPN
brj-25043	469	12	,	,	PUNCT
brj-25043	469	13	a.	a.	PROPN
brj-25043	469	14	,	,	PUNCT
brj-25043	469	15	and	and	CCONJ
brj-25043	469	16	varank	varank	NOUN
brj-25043	469	17	,	,	PUNCT
brj-25043	469	18	g.	g.	PROPN
brj-25043	469	19	(	(	PUNCT
brj-25043	469	20	2009	2009	NUM
brj-25043	469	21	)	)	PUNCT
brj-25043	469	22	.	.	PUNCT
brj-25043	470	1	“	"	PUNCT
brj-25043	470	2	evaluation	evaluation	NOUN
brj-25043	470	3	and	and	CCONJ
brj-25043	470	4	modeling	modeling	NOUN
brj-25043	470	5	of	of	ADP
brj-25043	470	6	biochemical	biochemical	ADJ
brj-25043	470	7	methane	methane	NOUN
brj-25043	470	8	potential	potential	NOUN
brj-25043	470	9	(	(	PUNCT
brj-25043	470	10	bmp	bmp	NOUN
brj-25043	470	11	)	)	PUNCT
brj-25043	470	12	of	of	ADP
brj-25043	470	13	landfilled	landfille	VERB
brj-25043	470	14	solid	solid	ADJ
brj-25043	470	15	waste	waste	NOUN
brj-25043	470	16	:	:	PUNCT
brj-25043	470	17	a	a	DET
brj-25043	470	18	pilot	pilot	NOUN
brj-25043	470	19	scale	scale	NOUN
brj-25043	470	20	study	study	NOUN
brj-25043	470	21	,	,	PUNCT
brj-25043	470	22	”	"	PUNCT
brj-25043	470	23	bioresource	bioresource	ADJ
brj-25043	470	24	technology	technology	NOUN
brj-25043	470	25	100(21	100(21	NUM
brj-25043	470	26	)	)	PUNCT
brj-25043	470	27	,	,	PUNCT
brj-25043	470	28	4976	4976	NUM
brj-25043	470	29	-	-	SYM
brj-25043	470	30	4980	4980	NUM
brj-25043	470	31	.	.	PUNCT
brj-25043	471	1	doi	doi	NOUN
brj-25043	471	2	:	:	PUNCT
brj-25043	471	3	10.1016	10.1016	NUM
brj-25043	471	4	/	/	SYM
brj-25043	471	5	j.biortech.2009.05.012	j.biortech.2009.05.012	PROPN
brj-25043	471	6	budiyono	budiyono	NOUN
brj-25043	471	7	,	,	PUNCT
brj-25043	471	8	b.	b.	PROPN
brj-25043	471	9	,	,	PUNCT
brj-25043	471	10	widiasa	widiasa	PROPN
brj-25043	471	11	,	,	PUNCT
brj-25043	471	12	i.	i.	PROPN
brj-25043	471	13	,	,	PUNCT
brj-25043	471	14	sunarso	sunarso	PROPN
brj-25043	471	15	,	,	PUNCT
brj-25043	471	16	s.	s.	PROPN
brj-25043	471	17	,	,	PUNCT
brj-25043	471	18	and	and	CCONJ
brj-25043	471	19	johari	johari	PROPN
brj-25043	471	20	,	,	PUNCT
brj-25043	471	21	s.	s.	PROPN
brj-25043	471	22	(	(	PUNCT
brj-25043	471	23	2010	2010	NUM
brj-25043	471	24	)	)	PUNCT
brj-25043	471	25	.	.	PUNCT
brj-25043	472	1	“	"	PUNCT
brj-25043	472	2	the	the	DET
brj-25043	472	3	kinetic	kinetic	NOUN
brj-25043	472	4	of	of	ADP
brj-25043	472	5	biogas	biogas	NOUN
brj-25043	472	6	production	production	NOUN
brj-25043	472	7	rate	rate	NOUN
brj-25043	472	8	from	from	ADP
brj-25043	472	9	cattle	cattle	NOUN
brj-25043	472	10	manure	manure	NOUN
brj-25043	472	11	in	in	ADP
brj-25043	472	12	batch	batch	NOUN
brj-25043	472	13	mode	mode	NOUN
brj-25043	472	14	,	,	PUNCT
brj-25043	472	15	”	"	PUNCT
brj-25043	472	16	international	international	ADJ
brj-25043	472	17	journal	journal	NOUN
brj-25043	472	18	of	of	ADP
brj-25043	472	19	chemical	chemical	PROPN
brj-25043	472	20	and	and	CCONJ
brj-25043	472	21	molecular	molecular	ADJ
brj-25043	472	22	engineering	engineering	NOUN
brj-25043	472	23	3(1	3(1	NUM
brj-25043	472	24	)	)	PUNCT
brj-25043	472	25	,	,	PUNCT
brj-25043	472	26	39	39	NUM
brj-25043	472	27	-	-	SYM
brj-25043	472	28	44	44	NUM
brj-25043	472	29	.	.	PUNCT
brj-25043	472	30	peer	peer	NOUN
brj-25043	472	31	-	-	PUNCT
brj-25043	472	32	reviewed	review	VERB
brj-25043	472	33	review	review	NOUN
brj-25043	472	34	article	article	NOUN
brj-25043	472	35	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	472	36	galal	galal	PROPN
brj-25043	472	37	et	et	PROPN
brj-25043	472	38	al	al	PROPN
brj-25043	472	39	.	.	PROPN
brj-25043	473	1	(	(	PUNCT
brj-25043	473	2	2025	2025	NUM
brj-25043	473	3	)	)	PUNCT
brj-25043	473	4	.	.	PUNCT
brj-25043	474	1	“	"	PUNCT
brj-25043	474	2	math	math	NOUN
brj-25043	474	3	modeling	modeling	NOUN
brj-25043	474	4	biogas	biogas	NOUN
brj-25043	474	5	production	production	NOUN
brj-25043	474	6	,	,	PUNCT
brj-25043	474	7	”	"	PUNCT
brj-25043	474	8	bioresources	bioresource	NOUN
brj-25043	474	9	20(4	20(4	NOUN
brj-25043	474	10	)	)	PUNCT
brj-25043	474	11	,	,	PUNCT
brj-25043	474	12	11237	11237	NUM
brj-25043	474	13	-	-	SYM
brj-25043	474	14	11266	11266	NUM
brj-25043	474	15	.	.	PUNCT
brj-25043	475	1	11263	11263	NUM
brj-25043	475	2	cruz	cruz	PROPN
brj-25043	475	3	,	,	PUNCT
brj-25043	475	4	i.	i.	PROPN
brj-25043	475	5	a.	a.	PROPN
brj-25043	475	6	,	,	PUNCT
brj-25043	475	7	nascimento	nascimento	PROPN
brj-25043	475	8	,	,	PUNCT
brj-25043	475	9	v.	v.	PROPN
brj-25043	475	10	r.	r.	PROPN
brj-25043	475	11	s.	s.	PROPN
brj-25043	475	12	,	,	PUNCT
brj-25043	475	13	felisardo	felisardo	PROPN
brj-25043	475	14	,	,	PUNCT
brj-25043	475	15	r.	r.	PROPN
brj-25043	475	16	j.	j.	PROPN
brj-25043	475	17	a.	a.	PROPN
brj-25043	475	18	,	,	PUNCT
brj-25043	475	19	dos	do	VERB
brj-25043	475	20	santos	santo	NOUN
brj-25043	475	21	,	,	PUNCT
brj-25043	475	22	a.	a.	NOUN
brj-25043	475	23	m.	m.	PROPN
brj-25043	475	24	g.	g.	PROPN
brj-25043	475	25	,	,	PUNCT
brj-25043	475	26	de	de	PROPN
brj-25043	475	27	jesus	jesus	PROPN
brj-25043	475	28	,	,	PUNCT
brj-25043	475	29	a.	a.	NOUN
brj-25043	475	30	a.	a.	PROPN
brj-25043	475	31	,	,	PUNCT
brj-25043	475	32	de	de	PROPN
brj-25043	475	33	vasconcelos	vasconcelos	PROPN
brj-25043	475	34	,	,	PUNCT
brj-25043	475	35	b.	b.	PROPN
brj-25043	475	36	r.	r.	PROPN
brj-25043	475	37	,	,	PUNCT
brj-25043	475	38	kumar	kumar	PROPN
brj-25043	475	39	,	,	PUNCT
brj-25043	475	40	v.	v.	PROPN
brj-25043	475	41	,	,	PUNCT
brj-25043	475	42	cavalcanti	cavalcanti	PROPN
brj-25043	475	43	,	,	PUNCT
brj-25043	475	44	e.	e.	PROPN
brj-25043	475	45	b.	b.	PROPN
brj-25043	475	46	,	,	PUNCT
brj-25043	475	47	de	de	PROPN
brj-25043	475	48	souza	souza	PROPN
brj-25043	475	49	,	,	PUNCT
brj-25043	475	50	r.	r.	PROPN
brj-25043	475	51	l.	l.	PROPN
brj-25043	475	52	,	,	PUNCT
brj-25043	475	53	and	and	CCONJ
brj-25043	475	54	ferreira	ferreira	PROPN
brj-25043	475	55	,	,	PUNCT
brj-25043	475	56	l.	l.	PROPN
brj-25043	475	57	f.	f.	PROPN
brj-25043	475	58	r.	r.	PROPN
brj-25043	475	59	(	(	PUNCT
brj-25043	475	60	2023	2023	NUM
brj-25043	475	61	)	)	PUNCT
brj-25043	475	62	.	.	PUNCT
brj-25043	476	1	“	"	PUNCT
brj-25043	476	2	evaluation	evaluation	NOUN
brj-25043	476	3	of	of	ADP
brj-25043	476	4	artificial	artificial	ADJ
brj-25043	476	5	neural	neural	ADJ
brj-25043	476	6	network	network	NOUN
brj-25043	476	7	models	model	NOUN
brj-25043	476	8	for	for	ADP
brj-25043	476	9	predictive	predictive	ADJ
brj-25043	476	10	monitoring	monitoring	NOUN
brj-25043	476	11	of	of	ADP
brj-25043	476	12	biogas	biogas	NOUN
brj-25043	476	13	production	production	NOUN
brj-25043	476	14	from	from	ADP
brj-25043	476	15	cassava	cassava	NOUN
brj-25043	476	16	wastewater	wastewater	NOUN
brj-25043	476	17	:	:	PUNCT
brj-25043	476	18	a	a	DET
brj-25043	476	19	training	training	NOUN
brj-25043	476	20	algorithms	algorithms	NOUN
brj-25043	476	21	approach	approach	NOUN
brj-25043	476	22	,	,	PUNCT
brj-25043	476	23	”	"	PUNCT
brj-25043	476	24	biomass	biomass	NOUN
brj-25043	476	25	and	and	CCONJ
brj-25043	476	26	bioenergy	bioenergy	NOUN
brj-25043	476	27	175	175	NUM
brj-25043	476	28	,	,	PUNCT
brj-25043	476	29	article	article	NOUN
brj-25043	476	30	106869	106869	NUM
brj-25043	476	31	.	.	PUNCT
brj-25043	477	1	doi	doi	NOUN
brj-25043	477	2	:	:	PUNCT
brj-25043	477	3	10.1016	10.1016	NUM
brj-25043	477	4	/	/	SYM
brj-25043	477	5	j.biombioe.2023.106869	j.biombioe.2023.106869	ADJ
brj-25043	477	6	danner	danner	NOUN
brj-25043	477	7	,	,	PUNCT
brj-25043	477	8	t.	t.	PROPN
brj-25043	477	9	w.	w.	PROPN
brj-25043	477	10	(	(	PUNCT
brj-25043	477	11	2006	2006	NUM
brj-25043	477	12	)	)	PUNCT
brj-25043	477	13	.	.	PUNCT
brj-25043	478	1	a	a	DET
brj-25043	478	2	formulation	formulation	NOUN
brj-25043	478	3	of	of	ADP
brj-25043	478	4	multidimensional	multidimensional	ADJ
brj-25043	478	5	growth	growth	NOUN
brj-25043	478	6	models	model	NOUN
brj-25043	478	7	for	for	ADP
brj-25043	478	8	the	the	DET
brj-25043	478	9	assessment	assessment	NOUN
brj-25043	478	10	and	and	CCONJ
brj-25043	478	11	forecast	forecast	NOUN
brj-25043	478	12	of	of	ADP
brj-25043	478	13	technology	technology	NOUN
brj-25043	478	14	attributes	attribute	VERB
brj-25043	478	15	,	,	PUNCT
brj-25043	478	16	ph.d	ph.d	PROPN
brj-25043	478	17	.	.	PUNCT
brj-25043	479	1	thesis	thesis	PROPN
brj-25043	479	2	,	,	PUNCT
brj-25043	479	3	georgia	georgia	PROPN
brj-25043	479	4	institute	institute	PROPN
brj-25043	479	5	of	of	ADP
brj-25043	479	6	technology	technology	PROPN
brj-25043	479	7	,	,	PUNCT
brj-25043	479	8	atlanta	atlanta	PROPN
brj-25043	479	9	,	,	PUNCT
brj-25043	479	10	ga	ga	PROPN
brj-25043	479	11	,	,	PUNCT
brj-25043	479	12	usa	usa	PROPN
brj-25043	479	13	.	.	PROPN
brj-25043	479	14	deepanraj	deepanraj	PROPN
brj-25043	479	15	,	,	PUNCT
brj-25043	479	16	b.	b.	PROPN
brj-25043	479	17	,	,	PUNCT
brj-25043	479	18	sivasubramanian	sivasubramanian	ADJ
brj-25043	479	19	,	,	PUNCT
brj-25043	479	20	v.	v.	ADV
brj-25043	479	21	,	,	PUNCT
brj-25043	479	22	and	and	CCONJ
brj-25043	479	23	jayaraj	jayaraj	PROPN
brj-25043	479	24	,	,	PUNCT
brj-25043	479	25	s.	s.	PROPN
brj-25043	479	26	(	(	PUNCT
brj-25043	479	27	2017	2017	NUM
brj-25043	479	28	)	)	PUNCT
brj-25043	479	29	.	.	PUNCT
brj-25043	480	1	“	"	PUNCT
brj-25043	480	2	effect	effect	NOUN
brj-25043	480	3	of	of	ADP
brj-25043	480	4	substrate	substrate	NOUN
brj-25043	480	5	pretreatment	pretreatment	NOUN
brj-25043	480	6	on	on	ADP
brj-25043	480	7	biogas	biogas	NOUN
brj-25043	480	8	production	production	NOUN
brj-25043	480	9	through	through	ADP
brj-25043	480	10	anaerobic	anaerobic	ADJ
brj-25043	480	11	digestion	digestion	NOUN
brj-25043	480	12	of	of	ADP
brj-25043	480	13	food	food	NOUN
brj-25043	480	14	waste	waste	NOUN
brj-25043	480	15	,	,	PUNCT
brj-25043	480	16	”	"	PUNCT
brj-25043	480	17	international	international	ADJ
brj-25043	480	18	journal	journal	NOUN
brj-25043	480	19	of	of	ADP
brj-25043	480	20	hydrogen	hydrogen	NOUN
brj-25043	480	21	energy	energy	NOUN
brj-25043	480	22	42(42	42(42	NOUN
brj-25043	480	23	)	)	PUNCT
brj-25043	480	24	,	,	PUNCT
brj-25043	480	25	26522	26522	NUM
brj-25043	480	26	-	-	SYM
brj-25043	480	27	26528	26528	NUM
brj-25043	480	28	.	.	PUNCT
brj-25043	481	1	doi	doi	NOUN
brj-25043	481	2	:	:	PUNCT
brj-25043	481	3	10.1016	10.1016	NUM
brj-25043	481	4	/	/	SYM
brj-25043	481	5	j.ijhydene.2017.06.178	j.ijhydene.2017.06.178	PROPN
brj-25043	481	6	fan	fan	PROPN
brj-25043	481	7	,	,	PUNCT
brj-25043	481	8	y.	y.	PROPN
brj-25043	481	9	,	,	PUNCT
brj-25043	481	10	wang	wang	PROPN
brj-25043	481	11	,	,	PUNCT
brj-25043	481	12	y.	y.	PROPN
brj-25043	481	13	,	,	PUNCT
brj-25043	481	14	qian	qian	PROPN
brj-25043	481	15	,	,	PUNCT
brj-25043	481	16	p.-y	p.-y	PROPN
brj-25043	481	17	.	.	PUNCT
brj-25043	481	18	,	,	PUNCT
brj-25043	481	19	and	and	CCONJ
brj-25043	481	20	gu	gu	NOUN
brj-25043	481	21	,	,	PUNCT
brj-25043	481	22	j.-d	j.-d	PROPN
brj-25043	481	23	.	.	PUNCT
brj-25043	482	1	(	(	PUNCT
brj-25043	482	2	2004	2004	NUM
brj-25043	482	3	)	)	PUNCT
brj-25043	482	4	.	.	PUNCT
brj-25043	483	1	“	"	PUNCT
brj-25043	483	2	optimization	optimization	NOUN
brj-25043	483	3	of	of	ADP
brj-25043	483	4	phthalic	phthalic	ADJ
brj-25043	483	5	acid	acid	NOUN
brj-25043	483	6	batch	batch	NOUN
brj-25043	483	7	biodegradation	biodegradation	NOUN
brj-25043	483	8	and	and	CCONJ
brj-25043	483	9	the	the	DET
brj-25043	483	10	use	use	NOUN
brj-25043	483	11	of	of	ADP
brj-25043	483	12	modified	modify	VERB
brj-25043	483	13	richards	richard	NOUN
brj-25043	483	14	model	model	NOUN
brj-25043	483	15	for	for	ADP
brj-25043	483	16	modelling	model	VERB
brj-25043	483	17	degradation	degradation	NOUN
brj-25043	483	18	,	,	PUNCT
brj-25043	483	19	”	"	PUNCT
brj-25043	483	20	international	international	ADJ
brj-25043	483	21	biodeterioration	biodeterioration	NOUN
brj-25043	483	22	&	&	CCONJ
brj-25043	483	23	biodegradation	biodegradation	PROPN
brj-25043	483	24	53(1	53(1	PROPN
brj-25043	483	25	)	)	PUNCT
brj-25043	483	26	,	,	PUNCT
brj-25043	483	27	57	57	NUM
brj-25043	483	28	-	-	SYM
brj-25043	483	29	63	63	NUM
brj-25043	483	30	.	.	PUNCT
brj-25043	484	1	doi	doi	NOUN
brj-25043	484	2	:	:	PUNCT
brj-25043	484	3	10.1016	10.1016	NUM
brj-25043	484	4	/	/	SYM
brj-25043	484	5	j.ibiod.2003.10.001	j.ibiod.2003.10.001	PROPN
brj-25043	484	6	galal	galal	PROPN
brj-25043	484	7	,	,	PUNCT
brj-25043	484	8	o.	o.	PROPN
brj-25043	484	9	h.	h.	PROPN
brj-25043	485	1	(	(	PUNCT
brj-25043	485	2	2013	2013	NUM
brj-25043	485	3	)	)	PUNCT
brj-25043	485	4	.	.	PUNCT
brj-25043	486	1	“	"	PUNCT
brj-25043	486	2	a	a	DET
brj-25043	486	3	proposed	propose	VERB
brj-25043	486	4	stochastic	stochastic	ADJ
brj-25043	486	5	finite	finite	ADJ
brj-25043	486	6	difference	difference	NOUN
brj-25043	486	7	approach	approach	NOUN
brj-25043	486	8	based	base	VERB
brj-25043	486	9	on	on	ADP
brj-25043	486	10	homogenous	homogenous	ADJ
brj-25043	486	11	chaos	chaos	NOUN
brj-25043	486	12	expansion	expansion	NOUN
brj-25043	486	13	,	,	PUNCT
brj-25043	486	14	”	"	PUNCT
brj-25043	486	15	journal	journal	NOUN
brj-25043	486	16	of	of	ADP
brj-25043	486	17	applied	apply	VERB
brj-25043	486	18	mathematics	mathematic	NOUN
brj-25043	486	19	2013	2013	NUM
brj-25043	486	20	,	,	PUNCT
brj-25043	486	21	article	article	NOUN
brj-25043	486	22	950469	950469	NUM
brj-25043	486	23	.	.	PUNCT
brj-25043	487	1	doi	doi	NOUN
brj-25043	487	2	:	:	PUNCT
brj-25043	487	3	10.1155/2013/950469	10.1155/2013/950469	NUM
brj-25043	487	4	galal	galal	NOUN
brj-25043	487	5	,	,	PUNCT
brj-25043	487	6	o.	o.	PROPN
brj-25043	487	7	h.	h.	PROPN
brj-25043	487	8	(	(	PUNCT
brj-25043	487	9	2021	2021	NUM
brj-25043	487	10	)	)	PUNCT
brj-25043	487	11	.	.	PUNCT
brj-25043	488	1	“	"	PUNCT
brj-25043	488	2	stochastic	stochastic	ADJ
brj-25043	488	3	velocity	velocity	NOUN
brj-25043	488	4	modeling	modeling	NOUN
brj-25043	488	5	of	of	ADP
brj-25043	488	6	magneto	magneto	NOUN
brj-25043	488	7	-	-	PUNCT
brj-25043	488	8	hydrodynamics	hydrodynamic	NOUN
brj-25043	488	9	nondarcy	nondarcy	NOUN
brj-25043	488	10	flow	flow	NOUN
brj-25043	488	11	between	between	ADP
brj-25043	488	12	two	two	NUM
brj-25043	488	13	stationary	stationary	ADJ
brj-25043	488	14	parallel	parallel	ADJ
brj-25043	488	15	plates	plate	NOUN
brj-25043	488	16	,	,	PUNCT
brj-25043	488	17	”	"	PUNCT
brj-25043	488	18	alexandria	alexandria	PROPN
brj-25043	488	19	engineering	engineering	PROPN
brj-25043	488	20	journal	journal	PROPN
brj-25043	488	21	60(4	60(4	PROPN
brj-25043	488	22	)	)	PUNCT
brj-25043	488	23	,	,	PUNCT
brj-25043	488	24	4191	4191	NUM
brj-25043	488	25	-	-	SYM
brj-25043	488	26	4201	4201	NUM
brj-25043	488	27	.	.	PUNCT
brj-25043	489	1	doi	doi	NOUN
brj-25043	489	2	:	:	PUNCT
brj-25043	489	3	10.1016	10.1016	NUM
brj-25043	489	4	/	/	SYM
brj-25043	489	5	j.aej.2021.03.010	j.aej.2021.03.010	PROPN
brj-25043	489	6	geng	geng	PROPN
brj-25043	489	7	,	,	PUNCT
brj-25043	489	8	z.	z.	PROPN
brj-25043	489	9	,	,	PUNCT
brj-25043	489	10	shi	shi	PROPN
brj-25043	489	11	,	,	PUNCT
brj-25043	489	12	x.	x.	PROPN
brj-25043	489	13	,	,	PUNCT
brj-25043	489	14	ma	ma	PROPN
brj-25043	489	15	,	,	PUNCT
brj-25043	489	16	b.	b.	PROPN
brj-25043	489	17	,	,	PUNCT
brj-25043	489	18	chu	chu	PROPN
brj-25043	489	19	,	,	PUNCT
brj-25043	489	20	c.	c.	PROPN
brj-25043	489	21	,	,	PUNCT
brj-25043	489	22	and	and	CCONJ
brj-25043	489	23	han	han	PROPN
brj-25043	489	24	,	,	PUNCT
brj-25043	489	25	y.	y.	PROPN
brj-25043	489	26	(	(	PUNCT
brj-25043	489	27	2024	2024	NUM
brj-25043	489	28	)	)	PUNCT
brj-25043	489	29	.	.	PUNCT
brj-25043	490	1	“	"	PUNCT
brj-25043	490	2	biogas	biogas	NOUN
brj-25043	490	3	production	production	NOUN
brj-25043	490	4	prediction	prediction	NOUN
brj-25043	490	5	model	model	NOUN
brj-25043	490	6	of	of	ADP
brj-25043	490	7	food	food	NOUN
brj-25043	490	8	waste	waste	NOUN
brj-25043	490	9	anaerobic	anaerobic	NOUN
brj-25043	490	10	digestion	digestion	NOUN
brj-25043	490	11	for	for	ADP
brj-25043	490	12	energy	energy	NOUN
brj-25043	490	13	optimization	optimization	NOUN
brj-25043	490	14	using	use	VERB
brj-25043	490	15	mixup	mixup	NOUN
brj-25043	490	16	data	datum	NOUN
brj-25043	490	17	augmentation	augmentation	NOUN
brj-25043	490	18	-	-	PUNCT
brj-25043	490	19	based	base	VERB
brj-25043	490	20	global	global	ADJ
brj-25043	490	21	attention	attention	NOUN
brj-25043	490	22	mechanism	mechanism	NOUN
brj-25043	490	23	,	,	PUNCT
brj-25043	490	24	”	"	PUNCT
brj-25043	490	25	environmental	environmental	ADJ
brj-25043	490	26	science	science	NOUN
brj-25043	490	27	and	and	CCONJ
brj-25043	490	28	pollution	pollution	NOUN
brj-25043	490	29	research	research	NOUN
brj-25043	490	30	31(6	31(6	NUM
brj-25043	490	31	)	)	PUNCT
brj-25043	490	32	,	,	PUNCT
brj-25043	490	33	9121	9121	NUM
brj-25043	490	34	-	-	SYM
brj-25043	490	35	9134	9134	NUM
brj-25043	490	36	.	.	PUNCT
brj-25043	491	1	doi	doi	NOUN
brj-25043	491	2	:	:	PUNCT
brj-25043	491	3	10.1007	10.1007	NUM
brj-25043	491	4	/	/	SYM
brj-25043	491	5	s11356	s11356	NOUN
brj-25043	491	6	-	-	PUNCT
brj-25043	491	7	023	023	NUM
brj-25043	491	8	-	-	PUNCT
brj-25043	491	9	31653	31653	NUM
brj-25043	491	10	-	-	SYM
brj-25043	491	11	8	8	NUM
brj-25043	491	12	ghanem	ghanem	PROPN
brj-25043	491	13	,	,	PUNCT
brj-25043	491	14	r.	r.	PROPN
brj-25043	491	15	g.	g.	PROPN
brj-25043	491	16	,	,	PUNCT
brj-25043	491	17	and	and	CCONJ
brj-25043	491	18	spanos	spanos	PROPN
brj-25043	491	19	,	,	PUNCT
brj-25043	491	20	p.	p.	PROPN
brj-25043	491	21	d.	d.	PROPN
brj-25043	491	22	(	(	PUNCT
brj-25043	491	23	2003	2003	NUM
brj-25043	491	24	)	)	PUNCT
brj-25043	491	25	.	.	PUNCT
brj-25043	492	1	stochastic	stochastic	ADJ
brj-25043	492	2	finite	finite	ADJ
brj-25043	492	3	elements	element	NOUN
brj-25043	492	4	:	:	PUNCT
brj-25043	492	5	a	a	DET
brj-25043	492	6	spectral	spectral	ADJ
brj-25043	492	7	approach	approach	NOUN
brj-25043	492	8	,	,	PUNCT
brj-25043	492	9	springer	springer	NOUN
brj-25043	492	10	new	new	PROPN
brj-25043	492	11	york	york	PROPN
brj-25043	492	12	,	,	PUNCT
brj-25043	492	13	ny	ny	PROPN
brj-25043	492	14	,	,	PUNCT
brj-25043	492	15	usa	usa	PROPN
brj-25043	492	16	.	.	PROPN
brj-25043	492	17	de	de	X
brj-25043	492	18	gioannis	gioannis	PROPN
brj-25043	492	19	,	,	PUNCT
brj-25043	492	20	g.	g.	PROPN
brj-25043	492	21	,	,	PUNCT
brj-25043	492	22	muntoni	muntoni	PROPN
brj-25043	492	23	,	,	PUNCT
brj-25043	492	24	a.	a.	PROPN
brj-25043	492	25	,	,	PUNCT
brj-25043	492	26	cappai	cappai	PROPN
brj-25043	492	27	,	,	PUNCT
brj-25043	492	28	g.	g.	PROPN
brj-25043	492	29	,	,	PUNCT
brj-25043	492	30	and	and	CCONJ
brj-25043	492	31	milia	milia	PROPN
brj-25043	492	32	,	,	PUNCT
brj-25043	492	33	s.	s.	PROPN
brj-25043	492	34	(	(	PUNCT
brj-25043	492	35	2009	2009	NUM
brj-25043	492	36	)	)	PUNCT
brj-25043	492	37	.	.	PUNCT
brj-25043	493	1	“	"	PUNCT
brj-25043	493	2	landfill	landfill	NOUN
brj-25043	493	3	gas	gas	NOUN
brj-25043	493	4	generation	generation	NOUN
brj-25043	493	5	after	after	ADP
brj-25043	493	6	mechanical	mechanical	ADJ
brj-25043	493	7	biological	biological	ADJ
brj-25043	493	8	treatment	treatment	NOUN
brj-25043	493	9	of	of	ADP
brj-25043	493	10	municipal	municipal	ADJ
brj-25043	493	11	solid	solid	ADJ
brj-25043	493	12	waste	waste	NOUN
brj-25043	493	13	.	.	PUNCT
brj-25043	494	1	estimation	estimation	NOUN
brj-25043	494	2	of	of	ADP
brj-25043	494	3	gas	gas	NOUN
brj-25043	494	4	generation	generation	NOUN
brj-25043	494	5	rate	rate	NOUN
brj-25043	494	6	constants	constant	NOUN
brj-25043	494	7	,	,	PUNCT
brj-25043	494	8	”	"	PUNCT
brj-25043	494	9	waste	waste	NOUN
brj-25043	494	10	management	management	NOUN
brj-25043	494	11	29(3	29(3	NUM
brj-25043	494	12	)	)	PUNCT
brj-25043	494	13	,	,	PUNCT
brj-25043	494	14	1026	1026	NUM
brj-25043	494	15	-	-	SYM
brj-25043	494	16	1034	1034	NUM
brj-25043	494	17	.	.	PUNCT
brj-25043	495	1	doi	doi	NOUN
brj-25043	495	2	:	:	PUNCT
brj-25043	495	3	10.1016	10.1016	NUM
brj-25043	495	4	/	/	SYM
brj-25043	495	5	j.wasman.2008.08.016	j.wasman.2008.08.016	PROPN
brj-25043	495	6	gupta	gupta	PROPN
brj-25043	495	7	,	,	PUNCT
brj-25043	495	8	r.	r.	PROPN
brj-25043	495	9	,	,	PUNCT
brj-25043	495	10	zhang	zhang	PROPN
brj-25043	495	11	,	,	PUNCT
brj-25043	495	12	l.	l.	PROPN
brj-25043	495	13	,	,	PUNCT
brj-25043	495	14	hou	hou	PROPN
brj-25043	495	15	,	,	PUNCT
brj-25043	495	16	j.	j.	PROPN
brj-25043	495	17	,	,	PUNCT
brj-25043	495	18	zhang	zhang	PROPN
brj-25043	495	19	,	,	PUNCT
brj-25043	495	20	z.	z.	PROPN
brj-25043	495	21	,	,	PUNCT
brj-25043	495	22	liu	liu	PROPN
brj-25043	495	23	,	,	PUNCT
brj-25043	495	24	h.	h.	PROPN
brj-25043	495	25	,	,	PUNCT
brj-25043	495	26	you	you	PRON
brj-25043	495	27	,	,	PUNCT
brj-25043	495	28	s.	s.	PROPN
brj-25043	495	29	,	,	PUNCT
brj-25043	495	30	ok	ok	INTJ
brj-25043	495	31	,	,	PUNCT
brj-25043	495	32	y.	y.	PROPN
brj-25043	495	33	s.	s.	PROPN
brj-25043	495	34	,	,	PUNCT
brj-25043	495	35	and	and	CCONJ
brj-25043	495	36	li	li	PROPN
brj-25043	495	37	,	,	PUNCT
brj-25043	495	38	w.	w.	PROPN
brj-25043	495	39	(	(	PUNCT
brj-25043	495	40	2023	2023	NUM
brj-25043	495	41	)	)	PUNCT
brj-25043	495	42	.	.	PUNCT
brj-25043	496	1	“	"	PUNCT
brj-25043	496	2	review	review	NOUN
brj-25043	496	3	of	of	ADP
brj-25043	496	4	explainable	explainable	ADJ
brj-25043	496	5	machine	machine	NOUN
brj-25043	496	6	learning	learn	VERB
brj-25043	496	7	for	for	ADP
brj-25043	496	8	anaerobic	anaerobic	ADJ
brj-25043	496	9	digestion	digestion	NOUN
brj-25043	496	10	,	,	PUNCT
brj-25043	496	11	”	"	PUNCT
brj-25043	496	12	bioresource	bioresource	ADP
brj-25043	496	13	technology	technology	NOUN
brj-25043	496	14	369	369	NUM
brj-25043	496	15	,	,	PUNCT
brj-25043	496	16	article	article	NOUN
brj-25043	496	17	128468	128468	NUM
brj-25043	496	18	.	.	PUNCT
brj-25043	497	1	doi	doi	NOUN
brj-25043	497	2	:	:	PUNCT
brj-25043	497	3	10.1016	10.1016	NUM
brj-25043	497	4	/	/	SYM
brj-25043	497	5	j.biortech.2022.128468	j.biortech.2022.128468	PROPN
brj-25043	497	6	hsieh	hsieh	PROPN
brj-25043	497	7	,	,	PUNCT
brj-25043	497	8	y.-h	y.-h	PROPN
brj-25043	497	9	.	.	PUNCT
brj-25043	498	1	(	(	PUNCT
brj-25043	498	2	2009	2009	NUM
brj-25043	498	3	)	)	PUNCT
brj-25043	498	4	.	.	PUNCT
brj-25043	499	1	“	"	PUNCT
brj-25043	499	2	richards	richard	NOUN
brj-25043	499	3	model	model	NOUN
brj-25043	499	4	:	:	PUNCT
brj-25043	499	5	a	a	DET
brj-25043	499	6	simple	simple	ADJ
brj-25043	499	7	procedure	procedure	NOUN
brj-25043	499	8	for	for	ADP
brj-25043	499	9	real	real	ADJ
brj-25043	499	10	-	-	PUNCT
brj-25043	499	11	time	time	NOUN
brj-25043	499	12	prediction	prediction	NOUN
brj-25043	499	13	of	of	ADP
brj-25043	499	14	outbreak	outbreak	NOUN
brj-25043	499	15	severity	severity	NOUN
brj-25043	499	16	,	,	PUNCT
brj-25043	499	17	”	"	PUNCT
brj-25043	499	18	modeling	modeling	NOUN
brj-25043	499	19	and	and	CCONJ
brj-25043	499	20	dynamics	dynamic	NOUN
brj-25043	499	21	of	of	ADP
brj-25043	499	22	infectious	infectious	ADJ
brj-25043	499	23	diseases	disease	NOUN
brj-25043	499	24	1	1	NUM
brj-25043	499	25	,	,	PUNCT
brj-25043	499	26	216	216	NUM
brj-25043	499	27	-	-	SYM
brj-25043	499	28	236	236	NUM
brj-25043	499	29	.	.	PUNCT
brj-25043	500	1	doi	doi	NOUN
brj-25043	500	2	:	:	PUNCT
brj-25043	500	3	10.1142/97898142612650009	10.1142/97898142612650009	NUM
brj-25043	500	4	jafari	jafari	NOUN
brj-25043	500	5	-	-	NOUN
brj-25043	500	6	sejahrood	sejahrood	ADJ
brj-25043	500	7	,	,	PUNCT
brj-25043	500	8	a.	a.	NOUN
brj-25043	500	9	,	,	PUNCT
brj-25043	500	10	najafi	najafi	PROPN
brj-25043	500	11	,	,	PUNCT
brj-25043	500	12	b.	b.	PROPN
brj-25043	500	13	,	,	PUNCT
brj-25043	500	14	faizollahzadeh	faizollahzadeh	PROPN
brj-25043	500	15	ardabili	ardabili	PROPN
brj-25043	500	16	,	,	PUNCT
brj-25043	500	17	s.	s.	PROPN
brj-25043	500	18	,	,	PUNCT
brj-25043	500	19	shamshirband	shamshirband	PROPN
brj-25043	500	20	,	,	PUNCT
brj-25043	500	21	s.	s.	PROPN
brj-25043	500	22	,	,	PUNCT
brj-25043	500	23	mosavi	mosavi	VERB
brj-25043	500	24	,	,	PUNCT
brj-25043	500	25	a.	a.	NOUN
brj-25043	500	26	,	,	PUNCT
brj-25043	500	27	and	and	CCONJ
brj-25043	500	28	chau	chau	NOUN
brj-25043	500	29	,	,	PUNCT
brj-25043	500	30	k.	k.	PROPN
brj-25043	500	31	(	(	PUNCT
brj-25043	500	32	2019	2019	NUM
brj-25043	500	33	)	)	PUNCT
brj-25043	500	34	.	.	PUNCT
brj-25043	501	1	“	"	PUNCT
brj-25043	501	2	limiting	limit	VERB
brj-25043	501	3	factors	factor	NOUN
brj-25043	501	4	for	for	ADP
brj-25043	501	5	biogas	biogas	NOUN
brj-25043	501	6	production	production	NOUN
brj-25043	501	7	from	from	ADP
brj-25043	501	8	cow	cow	NOUN
brj-25043	501	9	manure	manure	NOUN
brj-25043	501	10	:	:	PUNCT
brj-25043	501	11	energo	energo	NOUN
brj-25043	501	12	-	-	PUNCT
brj-25043	501	13	environmental	environmental	ADJ
brj-25043	501	14	approach	approach	NOUN
brj-25043	501	15	,	,	PUNCT
brj-25043	501	16	”	"	PUNCT
brj-25043	501	17	engineering	engineering	NOUN
brj-25043	501	18	applications	application	NOUN
brj-25043	501	19	of	of	ADP
brj-25043	501	20	computational	computational	ADJ
brj-25043	501	21	fluid	fluid	ADJ
brj-25043	501	22	mechanics	mechanic	NOUN
brj-25043	501	23	13(1	13(1	NUM
brj-25043	501	24	)	)	PUNCT
brj-25043	501	25	,	,	PUNCT
brj-25043	501	26	954	954	NUM
brj-25043	501	27	-	-	SYM
brj-25043	501	28	966	966	NUM
brj-25043	501	29	.	.	PUNCT
brj-25043	502	1	doi	doi	NOUN
brj-25043	502	2	:	:	PUNCT
brj-25043	502	3	10.1080/19942060.2019.1654411	10.1080/19942060.2019.1654411	NUM
brj-25043	502	4	jameel	jameel	X
brj-25043	502	5	,	,	PUNCT
brj-25043	502	6	m.	m.	PROPN
brj-25043	502	7	k.	k.	PROPN
brj-25043	502	8	,	,	PUNCT
brj-25043	502	9	mustafa	mustafa	PROPN
brj-25043	502	10	,	,	PUNCT
brj-25043	502	11	m.	m.	NOUN
brj-25043	502	12	a.	a.	PROPN
brj-25043	502	13	,	,	PUNCT
brj-25043	502	14	ahmed	ahmed	PROPN
brj-25043	502	15	,	,	PUNCT
brj-25043	502	16	h.	h.	PROPN
brj-25043	502	17	s.	s.	PROPN
brj-25043	502	18	,	,	PUNCT
brj-25043	502	19	jassim	jassim	PROPN
brj-25043	502	20	mohammed	mohammed	PROPN
brj-25043	502	21	,	,	PUNCT
brj-25043	502	22	a.	a.	NOUN
brj-25043	502	23	,	,	PUNCT
brj-25043	502	24	ghazy	ghazy	PROPN
brj-25043	502	25	,	,	PUNCT
brj-25043	502	26	h.	h.	PROPN
brj-25043	502	27	,	,	PUNCT
brj-25043	502	28	shakir	shakir	PROPN
brj-25043	502	29	,	,	PUNCT
brj-25043	502	30	m.	m.	NOUN
brj-25043	502	31	n.	n.	PROPN
brj-25043	502	32	,	,	PUNCT
brj-25043	502	33	lawas	lawas	PROPN
brj-25043	502	34	,	,	PUNCT
brj-25043	502	35	a.	a.	NOUN
brj-25043	502	36	m.	m.	NOUN
brj-25043	502	37	,	,	PUNCT
brj-25043	502	38	khudhur	khudhur	PROPN
brj-25043	502	39	mohammed	mohammed	PROPN
brj-25043	502	40	,	,	PUNCT
brj-25043	502	41	s.	s.	PROPN
brj-25043	502	42	,	,	PUNCT
brj-25043	502	43	idan	idan	PROPN
brj-25043	502	44	,	,	PUNCT
brj-25043	502	45	a.	a.	PROPN
brj-25043	502	46	h.	h.	PROPN
brj-25043	502	47	,	,	PUNCT
brj-25043	502	48	and	and	CCONJ
brj-25043	502	49	mahmoud	mahmoud	PROPN
brj-25043	502	50	,	,	PUNCT
brj-25043	502	51	z.	z.	PROPN
brj-25043	502	52	h.	h.	PROPN
brj-25043	502	53	(	(	PUNCT
brj-25043	502	54	2024	2024	NUM
brj-25043	502	55	)	)	PUNCT
brj-25043	502	56	.	.	PUNCT
brj-25043	503	1	“	"	PUNCT
brj-25043	503	2	biogas	biogas	NOUN
brj-25043	503	3	:	:	PUNCT
brj-25043	503	4	production	production	NOUN
brj-25043	503	5	,	,	PUNCT
brj-25043	503	6	properties	property	NOUN
brj-25043	503	7	,	,	PUNCT
brj-25043	503	8	applications	application	NOUN
brj-25043	503	9	,	,	PUNCT
brj-25043	503	10	economic	economic	ADJ
brj-25043	503	11	and	and	CCONJ
brj-25043	503	12	challenges	challenge	NOUN
brj-25043	503	13	:	:	PUNCT
brj-25043	503	14	a	a	DET
brj-25043	503	15	review	review	NOUN
brj-25043	503	16	,	,	PUNCT
brj-25043	503	17	”	"	PUNCT
brj-25043	503	18	results	result	NOUN
brj-25043	503	19	in	in	ADP
brj-25043	503	20	chemistry	chemistry	NOUN
brj-25043	503	21	7	7	NUM
brj-25043	503	22	,	,	PUNCT
brj-25043	503	23	article	article	NOUN
brj-25043	503	24	101549	101549	NUM
brj-25043	503	25	.	.	PUNCT
brj-25043	504	1	doi	doi	NOUN
brj-25043	504	2	:	:	PUNCT
brj-25043	504	3	10.1016	10.1016	NUM
brj-25043	504	4	/	/	SYM
brj-25043	504	5	j.rechem.2024.101549	j.rechem.2024.101549	PROPN
brj-25043	504	6	jeong	jeong	PROPN
brj-25043	504	7	,	,	PUNCT
brj-25043	504	8	k.	k.	PROPN
brj-25043	504	9	,	,	PUNCT
brj-25043	504	10	abbas	abbas	PROPN
brj-25043	504	11	,	,	PUNCT
brj-25043	504	12	a.	a.	NOUN
brj-25043	504	13	,	,	PUNCT
brj-25043	504	14	shin	shin	PROPN
brj-25043	504	15	,	,	PUNCT
brj-25043	504	16	j.	j.	PROPN
brj-25043	504	17	,	,	PUNCT
brj-25043	504	18	son	son	NOUN
brj-25043	504	19	,	,	PUNCT
brj-25043	504	20	m.	m.	NOUN
brj-25043	504	21	,	,	PUNCT
brj-25043	504	22	kim	kim	PROPN
brj-25043	504	23	,	,	PUNCT
brj-25043	504	24	y.	y.	PROPN
brj-25043	504	25	m.	m.	PROPN
brj-25043	504	26	,	,	PUNCT
brj-25043	504	27	and	and	CCONJ
brj-25043	504	28	cho	cho	PROPN
brj-25043	504	29	,	,	PUNCT
brj-25043	504	30	k.	k.	PROPN
brj-25043	504	31	h.	h.	PROPN
brj-25043	504	32	(	(	PUNCT
brj-25043	504	33	2021	2021	NUM
brj-25043	504	34	)	)	PUNCT
brj-25043	504	35	.	.	PUNCT
brj-25043	505	1	“	"	PUNCT
brj-25043	505	2	prediction	prediction	NOUN
brj-25043	505	3	peer	peer	NOUN
brj-25043	505	4	-	-	PUNCT
brj-25043	505	5	reviewed	review	VERB
brj-25043	505	6	review	review	NOUN
brj-25043	505	7	article	article	NOUN
brj-25043	505	8	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	505	9	galal	galal	PROPN
brj-25043	505	10	et	et	PROPN
brj-25043	505	11	al	al	PROPN
brj-25043	505	12	.	.	PROPN
brj-25043	505	13	(	(	PUNCT
brj-25043	505	14	2025	2025	NUM
brj-25043	505	15	)	)	PUNCT
brj-25043	505	16	.	.	PUNCT
brj-25043	506	1	“	"	PUNCT
brj-25043	506	2	math	math	NOUN
brj-25043	506	3	modeling	modeling	NOUN
brj-25043	506	4	biogas	biogas	NOUN
brj-25043	506	5	production	production	NOUN
brj-25043	506	6	,	,	PUNCT
brj-25043	506	7	”	"	PUNCT
brj-25043	506	8	bioresources	bioresource	NOUN
brj-25043	506	9	20(4	20(4	NOUN
brj-25043	506	10	)	)	PUNCT
brj-25043	506	11	,	,	PUNCT
brj-25043	506	12	11237	11237	NUM
brj-25043	506	13	-	-	SYM
brj-25043	506	14	11266	11266	NUM
brj-25043	506	15	.	.	PUNCT
brj-25043	507	1	11264	11264	NUM
brj-25043	507	2	of	of	ADP
brj-25043	507	3	biogas	biogas	NOUN
brj-25043	507	4	production	production	NOUN
brj-25043	507	5	in	in	ADP
brj-25043	507	6	anaerobic	anaerobic	NOUN
brj-25043	507	7	co	co	NOUN
brj-25043	507	8	-	-	NOUN
brj-25043	507	9	digestion	digestion	NOUN
brj-25043	507	10	of	of	ADP
brj-25043	507	11	organic	organic	ADJ
brj-25043	507	12	wastes	waste	NOUN
brj-25043	507	13	using	use	VERB
brj-25043	507	14	deep	deep	ADJ
brj-25043	507	15	learning	learning	NOUN
brj-25043	507	16	models	model	NOUN
brj-25043	507	17	,	,	PUNCT
brj-25043	507	18	”	"	PUNCT
brj-25043	507	19	water	water	NOUN
brj-25043	507	20	research	research	NOUN
brj-25043	507	21	205	205	NUM
brj-25043	507	22	,	,	PUNCT
brj-25043	507	23	article	article	NOUN
brj-25043	507	24	117697	117697	NUM
brj-25043	507	25	.	.	PUNCT
brj-25043	508	1	doi	doi	NOUN
brj-25043	508	2	:	:	PUNCT
brj-25043	508	3	10.1016	10.1016	NUM
brj-25043	508	4	/	/	SYM
brj-25043	508	5	j.watres.2021.117697	j.watres.2021.117697	PROPN
brj-25043	508	6	komarysta	komarysta	PROPN
brj-25043	508	7	,	,	PUNCT
brj-25043	508	8	b.	b.	PROPN
brj-25043	508	9	,	,	PUNCT
brj-25043	508	10	dzhygyrey	dzhygyrey	PROPN
brj-25043	508	11	,	,	PUNCT
brj-25043	508	12	i.	i.	PROPN
brj-25043	508	13	,	,	PUNCT
brj-25043	508	14	bendiuh	bendiuh	NOUN
brj-25043	508	15	,	,	PUNCT
brj-25043	508	16	v.	v.	ADV
brj-25043	508	17	,	,	PUNCT
brj-25043	508	18	yavorovska	yavorovska	ADJ
brj-25043	508	19	,	,	PUNCT
brj-25043	508	20	o.	o.	PROPN
brj-25043	508	21	,	,	PUNCT
brj-25043	508	22	andreeva	andreeva	VERB
brj-25043	508	23	,	,	PUNCT
brj-25043	508	24	a.	a.	NOUN
brj-25043	508	25	,	,	PUNCT
brj-25043	508	26	berezenko	berezenko	PROPN
brj-25043	508	27	,	,	PUNCT
brj-25043	508	28	k.	k.	PROPN
brj-25043	508	29	,	,	PUNCT
brj-25043	508	30	meshcheriakova	meshcheriakova	PROPN
brj-25043	508	31	,	,	PUNCT
brj-25043	508	32	i.	i.	PROPN
brj-25043	508	33	,	,	PUNCT
brj-25043	508	34	vovk	vovk	ADJ
brj-25043	508	35	,	,	PUNCT
brj-25043	508	36	o.	o.	ADJ
brj-25043	508	37	,	,	PUNCT
brj-25043	508	38	dokshyna	dokshyna	NOUN
brj-25043	508	39	,	,	PUNCT
brj-25043	508	40	s.	s.	PROPN
brj-25043	508	41	,	,	PUNCT
brj-25043	508	42	and	and	CCONJ
brj-25043	508	43	maidanskyi	maidanskyi	ADJ
brj-25043	508	44	,	,	PUNCT
brj-25043	508	45	i.	i.	NOUN
brj-25043	508	46	(	(	PUNCT
brj-25043	508	47	2023	2023	NUM
brj-25043	508	48	)	)	PUNCT
brj-25043	508	49	.	.	PUNCT
brj-25043	509	1	“	"	PUNCT
brj-25043	509	2	optimizing	optimize	VERB
brj-25043	509	3	biogas	biogas	NOUN
brj-25043	509	4	production	production	NOUN
brj-25043	509	5	using	use	VERB
brj-25043	509	6	artificial	artificial	ADJ
brj-25043	509	7	neural	neural	ADJ
brj-25043	509	8	network	network	NOUN
brj-25043	509	9	,	,	PUNCT
brj-25043	509	10	”	"	PUNCT
brj-25043	509	11	eastern	eastern	ADJ
brj-25043	509	12	-	-	PUNCT
brj-25043	509	13	european	european	ADJ
brj-25043	509	14	journal	journal	NOUN
brj-25043	509	15	of	of	ADP
brj-25043	509	16	enterprise	enterprise	NOUN
brj-25043	509	17	technologies	technology	NOUN
brj-25043	509	18	2(8(122	2(8(122	NUM
brj-25043	509	19	)	)	PUNCT
brj-25043	509	20	,	,	PUNCT
brj-25043	509	21	53	53	NUM
brj-25043	509	22	-	-	SYM
brj-25043	509	23	64	64	NUM
brj-25043	509	24	.	.	PUNCT
brj-25043	510	1	doi	doi	NOUN
brj-25043	510	2	:	:	PUNCT
brj-25043	510	3	10.15587/17294061.2023.276431	10.15587/17294061.2023.276431	NUM
brj-25043	510	4	kumar	kumar	PROPN
brj-25043	510	5	,	,	PUNCT
brj-25043	510	6	s.	s.	PROPN
brj-25043	510	7	,	,	PUNCT
brj-25043	510	8	mondal	mondal	PROPN
brj-25043	510	9	,	,	PUNCT
brj-25043	510	10	a.	a.	NOUN
brj-25043	510	11	n.	n.	PROPN
brj-25043	510	12	,	,	PUNCT
brj-25043	510	13	gaikwad	gaikwad	NOUN
brj-25043	510	14	,	,	PUNCT
brj-25043	510	15	s.	s.	PROPN
brj-25043	510	16	a.	a.	PROPN
brj-25043	510	17	,	,	PUNCT
brj-25043	510	18	devotta	devotta	PROPN
brj-25043	510	19	,	,	PUNCT
brj-25043	510	20	s.	s.	PROPN
brj-25043	510	21	,	,	PUNCT
brj-25043	510	22	and	and	CCONJ
brj-25043	510	23	singh	singh	PROPN
brj-25043	510	24	,	,	PUNCT
brj-25043	510	25	r.	r.	PROPN
brj-25043	510	26	n.	n.	PROPN
brj-25043	510	27	(	(	PUNCT
brj-25043	510	28	2004	2004	NUM
brj-25043	510	29	)	)	PUNCT
brj-25043	510	30	.	.	PUNCT
brj-25043	511	1	“	"	PUNCT
brj-25043	511	2	qualitative	qualitative	ADJ
brj-25043	511	3	assessment	assessment	NOUN
brj-25043	511	4	of	of	ADP
brj-25043	511	5	methane	methane	NOUN
brj-25043	511	6	emission	emission	NOUN
brj-25043	511	7	inventory	inventory	NOUN
brj-25043	511	8	from	from	ADP
brj-25043	511	9	municipal	municipal	ADJ
brj-25043	511	10	solid	solid	ADJ
brj-25043	511	11	waste	waste	NOUN
brj-25043	511	12	disposal	disposal	NOUN
brj-25043	511	13	sites	site	NOUN
brj-25043	511	14	:	:	PUNCT
brj-25043	511	15	a	a	DET
brj-25043	511	16	case	case	NOUN
brj-25043	511	17	study	study	NOUN
brj-25043	511	18	,	,	PUNCT
brj-25043	511	19	”	"	PUNCT
brj-25043	511	20	atmospheric	atmospheric	ADJ
brj-25043	511	21	environment	environment	NOUN
brj-25043	511	22	38(29	38(29	NUM
brj-25043	511	23	)	)	PUNCT
brj-25043	511	24	,	,	PUNCT
brj-25043	511	25	4921	4921	NUM
brj-25043	511	26	-	-	SYM
brj-25043	511	27	4929	4929	NUM
brj-25043	511	28	.	.	PUNCT
brj-25043	512	1	doi	doi	NOUN
brj-25043	512	2	:	:	PUNCT
brj-25043	512	3	10.1016	10.1016	NUM
brj-25043	512	4	/	/	SYM
brj-25043	512	5	j.atmosenv.2004.05.052	j.atmosenv.2004.05.052	PROPN
brj-25043	512	6	latinwo	latinwo	PROPN
brj-25043	512	7	,	,	PUNCT
brj-25043	512	8	g.	g.	PROPN
brj-25043	512	9	k.	k.	PROPN
brj-25043	512	10	,	,	PUNCT
brj-25043	512	11	and	and	CCONJ
brj-25043	512	12	agarry	agarry	PROPN
brj-25043	512	13	,	,	PUNCT
brj-25043	512	14	s.	s.	PROPN
brj-25043	512	15	e.	e.	PROPN
brj-25043	512	16	(	(	PUNCT
brj-25043	512	17	2015	2015	NUM
brj-25043	512	18	)	)	PUNCT
brj-25043	512	19	.	.	PUNCT
brj-25043	513	1	“	"	PUNCT
brj-25043	513	2	modelling	model	VERB
brj-25043	513	3	the	the	DET
brj-25043	513	4	kinetics	kinetic	NOUN
brj-25043	513	5	of	of	ADP
brj-25043	513	6	biogas	biogas	NOUN
brj-25043	513	7	production	production	NOUN
brj-25043	513	8	from	from	ADP
brj-25043	513	9	mesophilic	mesophilic	ADJ
brj-25043	513	10	anaerobic	anaerobic	NOUN
brj-25043	513	11	co	co	NOUN
brj-25043	513	12	-	-	NOUN
brj-25043	513	13	digestion	digestion	NOUN
brj-25043	513	14	of	of	ADP
brj-25043	513	15	cow	cow	NOUN
brj-25043	513	16	dung	dung	NOUN
brj-25043	513	17	with	with	ADP
brj-25043	513	18	plantain	plantain	NOUN
brj-25043	513	19	peels	peel	NOUN
brj-25043	513	20	,	,	PUNCT
brj-25043	513	21	”	"	PUNCT
brj-25043	513	22	international	international	ADJ
brj-25043	513	23	journal	journal	NOUN
brj-25043	513	24	of	of	ADP
brj-25043	513	25	renewable	renewable	ADJ
brj-25043	513	26	energy	energy	NOUN
brj-25043	513	27	development	development	NOUN
brj-25043	513	28	4(1	4(1	NOUN
brj-25043	513	29	)	)	PUNCT
brj-25043	513	30	,	,	PUNCT
brj-25043	513	31	55	55	NUM
brj-25043	513	32	-	-	SYM
brj-25043	513	33	63	63	NUM
brj-25043	513	34	.	.	PUNCT
brj-25043	514	1	doi	doi	NOUN
brj-25043	514	2	:	:	PUNCT
brj-25043	514	3	10.14710	10.14710	NUM
brj-25043	514	4	/	/	SYM
brj-25043	514	5	ijred.4.1.55	ijred.4.1.55	NOUN
brj-25043	514	6	-	-	PUNCT
brj-25043	514	7	63	63	NUM
brj-25043	514	8	li	li	PROPN
brj-25043	514	9	,	,	PUNCT
brj-25043	514	10	c.	c.	PROPN
brj-25043	514	11	,	,	PUNCT
brj-25043	514	12	and	and	CCONJ
brj-25043	514	13	fang	fang	X
brj-25043	514	14	,	,	PUNCT
brj-25043	515	1	h.	h.	PROPN
brj-25043	515	2	h.	h.	PROPN
brj-25043	515	3	p.	p.	PROPN
brj-25043	515	4	(	(	PUNCT
brj-25043	515	5	2007	2007	NUM
brj-25043	515	6	)	)	PUNCT
brj-25043	515	7	.	.	PUNCT
brj-25043	516	1	“	"	PUNCT
brj-25043	516	2	inhibition	inhibition	NOUN
brj-25043	516	3	of	of	ADP
brj-25043	516	4	heavy	heavy	ADJ
brj-25043	516	5	metals	metal	NOUN
brj-25043	516	6	on	on	ADP
brj-25043	516	7	fermentative	fermentative	ADJ
brj-25043	516	8	hydrogen	hydrogen	NOUN
brj-25043	516	9	production	production	NOUN
brj-25043	516	10	by	by	ADP
brj-25043	516	11	granular	granular	ADJ
brj-25043	516	12	sludge	sludge	NOUN
brj-25043	516	13	,	,	PUNCT
brj-25043	516	14	”	"	PUNCT
brj-25043	516	15	chemosphere	chemosphere	ADJ
brj-25043	516	16	67(4	67(4	NUM
brj-25043	516	17	)	)	PUNCT
brj-25043	516	18	,	,	PUNCT
brj-25043	516	19	668	668	NUM
brj-25043	516	20	-	-	SYM
brj-25043	516	21	673	673	NUM
brj-25043	516	22	.	.	PUNCT
brj-25043	517	1	doi	doi	NOUN
brj-25043	517	2	:	:	PUNCT
brj-25043	517	3	10.1016	10.1016	NUM
brj-25043	517	4	/	/	SYM
brj-25043	517	5	j.chemosphere.2006.11.005	j.chemosphere.2006.11.005	PROPN
brj-25043	517	6	li	li	PROPN
brj-25043	517	7	,	,	PUNCT
brj-25043	517	8	m.	m.	NOUN
brj-25043	517	9	,	,	PUNCT
brj-25043	517	10	zhao	zhao	PROPN
brj-25043	517	11	,	,	PUNCT
brj-25043	517	12	y.	y.	PROPN
brj-25043	517	13	,	,	PUNCT
brj-25043	517	14	guo	guo	PROPN
brj-25043	517	15	,	,	PUNCT
brj-25043	517	16	q.	q.	PROPN
brj-25043	517	17	,	,	PUNCT
brj-25043	517	18	qian	qian	PROPN
brj-25043	517	19	,	,	PUNCT
brj-25043	517	20	x.	x.	NOUN
brj-25043	517	21	,	,	PUNCT
brj-25043	517	22	and	and	CCONJ
brj-25043	517	23	niu	niu	PROPN
brj-25043	517	24	,	,	PUNCT
brj-25043	517	25	d.	d.	PROPN
brj-25043	517	26	(	(	PUNCT
brj-25043	517	27	2008	2008	NUM
brj-25043	517	28	)	)	PUNCT
brj-25043	517	29	.	.	PUNCT
brj-25043	518	1	“	"	PUNCT
brj-25043	518	2	bio	bio	ADJ
brj-25043	518	3	-	-	ADJ
brj-25043	518	4	hydrogen	hydrogen	NOUN
brj-25043	518	5	production	production	NOUN
brj-25043	518	6	from	from	ADP
brj-25043	518	7	food	food	NOUN
brj-25043	518	8	waste	waste	NOUN
brj-25043	518	9	and	and	CCONJ
brj-25043	518	10	sewage	sewage	NOUN
brj-25043	518	11	sludge	sludge	NOUN
brj-25043	518	12	in	in	ADP
brj-25043	518	13	the	the	DET
brj-25043	518	14	presence	presence	NOUN
brj-25043	518	15	of	of	ADP
brj-25043	518	16	aged	aged	ADJ
brj-25043	518	17	refuse	refuse	NOUN
brj-25043	518	18	excavated	excavate	VERB
brj-25043	518	19	from	from	ADP
brj-25043	518	20	refuse	refuse	ADJ
brj-25043	518	21	landfill	landfill	NOUN
brj-25043	518	22	,	,	PUNCT
brj-25043	518	23	”	"	PUNCT
brj-25043	518	24	renewable	renewable	ADJ
brj-25043	518	25	energy	energy	NOUN
brj-25043	518	26	33(12	33(12	NUM
brj-25043	518	27	)	)	PUNCT
brj-25043	518	28	,	,	PUNCT
brj-25043	518	29	2573	2573	NUM
brj-25043	518	30	-	-	SYM
brj-25043	518	31	2579	2579	NUM
brj-25043	518	32	.	.	PUNCT
brj-25043	519	1	doi	doi	NOUN
brj-25043	519	2	:	:	PUNCT
brj-25043	519	3	10.1016	10.1016	NUM
brj-25043	519	4	/	/	SYM
brj-25043	519	5	j.renene.2008.02.018	j.renene.2008.02.018	PROPN
brj-25043	519	6	lin	lin	PROPN
brj-25043	519	7	,	,	PUNCT
brj-25043	519	8	c.y	c.y	PROPN
brj-25043	519	9	.	.	PROPN
brj-25043	519	10	,	,	PUNCT
brj-25043	519	11	and	and	CCONJ
brj-25043	519	12	shei	shei	PROPN
brj-25043	519	13	,	,	PUNCT
brj-25043	519	14	s.h	s.h	PROPN
brj-25043	519	15	.	.	PROPN
brj-25043	519	16	(	(	PUNCT
brj-25043	519	17	2008	2008	NUM
brj-25043	519	18	)	)	PUNCT
brj-25043	519	19	.	.	PUNCT
brj-25043	520	1	“	"	PUNCT
brj-25043	520	2	heavy	heavy	ADJ
brj-25043	520	3	metal	metal	NOUN
brj-25043	520	4	effects	effect	NOUN
brj-25043	520	5	on	on	ADP
brj-25043	520	6	fermentative	fermentative	ADJ
brj-25043	520	7	hydrogen	hydrogen	NOUN
brj-25043	520	8	production	production	NOUN
brj-25043	520	9	using	use	VERB
brj-25043	520	10	natural	natural	ADJ
brj-25043	520	11	mixed	mixed	ADJ
brj-25043	520	12	microflora	microflora	NOUN
brj-25043	520	13	,	,	PUNCT
brj-25043	520	14	”	"	PUNCT
brj-25043	520	15	international	international	ADJ
brj-25043	520	16	journal	journal	NOUN
brj-25043	520	17	of	of	ADP
brj-25043	520	18	hydrogen	hydrogen	NOUN
brj-25043	520	19	energy	energy	NOUN
brj-25043	520	20	33(2	33(2	NOUN
brj-25043	520	21	)	)	PUNCT
brj-25043	520	22	,	,	PUNCT
brj-25043	520	23	587	587	NUM
brj-25043	520	24	-	-	SYM
brj-25043	520	25	593	593	NUM
brj-25043	520	26	.	.	PUNCT
brj-25043	521	1	doi	doi	NOUN
brj-25043	521	2	:	:	PUNCT
brj-25043	521	3	10.1016	10.1016	NUM
brj-25043	521	4	/	/	SYM
brj-25043	521	5	j.ijhydene.2007.09.030	j.ijhydene.2007.09.030	PROPN
brj-25043	521	6	ling	ling	PROPN
brj-25043	521	7	,	,	PUNCT
brj-25043	521	8	j.	j.	PROPN
brj-25043	521	9	y.	y.	PROPN
brj-25043	521	10	x.	x.	PROPN
brj-25043	521	11	,	,	PUNCT
brj-25043	521	12	chan	chan	PROPN
brj-25043	521	13	,	,	PUNCT
brj-25043	521	14	y.	y.	PROPN
brj-25043	521	15	j.	j.	PROPN
brj-25043	521	16	,	,	PUNCT
brj-25043	521	17	chen	chen	PROPN
brj-25043	521	18	,	,	PUNCT
brj-25043	521	19	j.	j.	PROPN
brj-25043	521	20	w.	w.	PROPN
brj-25043	521	21	,	,	PUNCT
brj-25043	521	22	chong	chong	PROPN
brj-25043	521	23	,	,	PUNCT
brj-25043	521	24	d.	d.	PROPN
brj-25043	521	25	j.	j.	PROPN
brj-25043	521	26	s.	s.	PROPN
brj-25043	521	27	,	,	PUNCT
brj-25043	521	28	tan	tan	PROPN
brj-25043	521	29	,	,	PUNCT
brj-25043	521	30	a.	a.	PROPN
brj-25043	521	31	l.	l.	PROPN
brj-25043	521	32	l.	l.	PROPN
brj-25043	521	33	,	,	PUNCT
brj-25043	521	34	arumugasamy	arumugasamy	PROPN
brj-25043	521	35	,	,	PUNCT
brj-25043	521	36	s.	s.	PROPN
brj-25043	521	37	k.	k.	PROPN
brj-25043	521	38	,	,	PUNCT
brj-25043	521	39	and	and	CCONJ
brj-25043	521	40	lau	lau	PROPN
brj-25043	521	41	,	,	PUNCT
brj-25043	521	42	p.	p.	PROPN
brj-25043	521	43	l.	l.	PROPN
brj-25043	521	44	(	(	PUNCT
brj-25043	521	45	2024	2024	NUM
brj-25043	521	46	)	)	PUNCT
brj-25043	521	47	.	.	PUNCT
brj-25043	522	1	“	"	PUNCT
brj-25043	522	2	machine	machine	NOUN
brj-25043	522	3	learning	learning	NOUN
brj-25043	522	4	methods	method	NOUN
brj-25043	522	5	for	for	ADP
brj-25043	522	6	the	the	DET
brj-25043	522	7	modelling	modelling	NOUN
brj-25043	522	8	and	and	CCONJ
brj-25043	522	9	optimisation	optimisation	NOUN
brj-25043	522	10	of	of	ADP
brj-25043	522	11	biogas	biogas	NOUN
brj-25043	522	12	production	production	NOUN
brj-25043	522	13	from	from	ADP
brj-25043	522	14	anaerobic	anaerobic	ADJ
brj-25043	522	15	digestion	digestion	NOUN
brj-25043	522	16	:	:	PUNCT
brj-25043	522	17	a	a	DET
brj-25043	522	18	review	review	NOUN
brj-25043	522	19	,	,	PUNCT
brj-25043	522	20	”	"	PUNCT
brj-25043	522	21	environmental	environmental	ADJ
brj-25043	522	22	science	science	NOUN
brj-25043	522	23	and	and	CCONJ
brj-25043	522	24	pollution	pollution	NOUN
brj-25043	522	25	research	research	NOUN
brj-25043	522	26	31(13	31(13	NUM
brj-25043	522	27	)	)	PUNCT
brj-25043	522	28	,	,	PUNCT
brj-25043	522	29	19085	19085	NUM
brj-25043	522	30	-	-	SYM
brj-25043	522	31	19104	19104	NUM
brj-25043	522	32	.	.	PUNCT
brj-25043	523	1	doi	doi	NOUN
brj-25043	523	2	:	:	PUNCT
brj-25043	523	3	10.1007	10.1007	NUM
brj-25043	523	4	/	/	SYM
brj-25043	523	5	s11356	s11356	NOUN
brj-25043	523	6	-	-	PUNCT
brj-25043	523	7	024	024	NUM
brj-25043	523	8	-	-	PUNCT
brj-25043	523	9	32435	32435	NUM
brj-25043	523	10	-	-	SYM
brj-25043	523	11	6	6	NUM
brj-25043	523	12	liu	liu	PROPN
brj-25043	523	13	,	,	PUNCT
brj-25043	523	14	y.	y.	PROPN
brj-25043	523	15	,	,	PUNCT
brj-25043	523	16	watanabe	watanabe	PROPN
brj-25043	523	17	,	,	PUNCT
brj-25043	523	18	r.	r.	PROPN
brj-25043	523	19	,	,	PUNCT
brj-25043	523	20	li	li	PROPN
brj-25043	523	21	,	,	PUNCT
brj-25043	523	22	q.	q.	PROPN
brj-25043	523	23	,	,	PUNCT
brj-25043	523	24	luo	luo	PROPN
brj-25043	523	25	,	,	PUNCT
brj-25043	523	26	y.	y.	PROPN
brj-25043	523	27	,	,	PUNCT
brj-25043	523	28	tsuzuki	tsuzuki	PROPN
brj-25043	523	29	,	,	PUNCT
brj-25043	523	30	n.	n.	NOUN
brj-25043	523	31	,	,	PUNCT
brj-25043	523	32	ren	ren	PROPN
brj-25043	523	33	,	,	PUNCT
brj-25043	523	34	y.	y.	PROPN
brj-25043	523	35	,	,	PUNCT
brj-25043	523	36	qin	qin	PROPN
brj-25043	523	37	,	,	PUNCT
brj-25043	523	38	y.	y.	PROPN
brj-25043	523	39	,	,	PUNCT
brj-25043	523	40	and	and	CCONJ
brj-25043	523	41	li	li	PROPN
brj-25043	523	42	,	,	PUNCT
brj-25043	523	43	y.-y	y.-y	PROPN
brj-25043	523	44	.	.	PUNCT
brj-25043	524	1	(	(	PUNCT
brj-25043	524	2	2025	2025	NUM
brj-25043	524	3	)	)	PUNCT
brj-25043	524	4	.	.	PUNCT
brj-25043	525	1	“	"	PUNCT
brj-25043	525	2	enhanced	enhance	VERB
brj-25043	525	3	biomethane	biomethane	NOUN
brj-25043	525	4	production	production	NOUN
brj-25043	525	5	by	by	ADP
brj-25043	525	6	thermophilic	thermophilic	ADJ
brj-25043	525	7	high	high	ADJ
brj-25043	525	8	-	-	PUNCT
brj-25043	525	9	solid	solid	ADJ
brj-25043	525	10	anaerobic	anaerobic	NOUN
brj-25043	525	11	codigestion	codigestion	NOUN
brj-25043	525	12	of	of	ADP
brj-25043	525	13	rice	rice	NOUN
brj-25043	525	14	straw	straw	NOUN
brj-25043	525	15	and	and	CCONJ
brj-25043	525	16	food	food	NOUN
brj-25043	525	17	waste	waste	NOUN
brj-25043	525	18	:	:	PUNCT
brj-25043	525	19	cellulose	cellulose	NOUN
brj-25043	525	20	degradation	degradation	NOUN
brj-25043	525	21	and	and	CCONJ
brj-25043	525	22	microbial	microbial	ADJ
brj-25043	525	23	structure	structure	NOUN
brj-25043	525	24	,	,	PUNCT
brj-25043	525	25	”	"	PUNCT
brj-25043	525	26	chemical	chemical	NOUN
brj-25043	525	27	engineering	engineering	PROPN
brj-25043	525	28	journal	journal	PROPN
brj-25043	525	29	503	503	NUM
brj-25043	525	30	,	,	PUNCT
brj-25043	525	31	article	article	NOUN
brj-25043	525	32	158088	158088	NUM
brj-25043	525	33	.	.	PUNCT
brj-25043	526	1	doi	doi	NOUN
brj-25043	526	2	:	:	PUNCT
brj-25043	526	3	10.1016	10.1016	NUM
brj-25043	526	4	/	/	SYM
brj-25043	526	5	j.cej.2024.158088	j.cej.2024.158088	PROPN
brj-25043	526	6	lo	lo	PROPN
brj-25043	526	7	,	,	PUNCT
brj-25043	526	8	h.	h.	PROPN
brj-25043	526	9	m.	m.	PROPN
brj-25043	526	10	,	,	PUNCT
brj-25043	526	11	kurniawan	kurniawan	PROPN
brj-25043	526	12	,	,	PUNCT
brj-25043	526	13	t.	t.	PROPN
brj-25043	526	14	a.	a.	NOUN
brj-25043	526	15	,	,	PUNCT
brj-25043	526	16	sillanpää	sillanpää	ADV
brj-25043	526	17	,	,	PUNCT
brj-25043	526	18	m.	m.	NOUN
brj-25043	526	19	e.	e.	PROPN
brj-25043	526	20	t.	t.	PROPN
brj-25043	526	21	,	,	PUNCT
brj-25043	526	22	pai	pai	PROPN
brj-25043	526	23	,	,	PUNCT
brj-25043	526	24	t.	t.	PROPN
brj-25043	526	25	y.	y.	PROPN
brj-25043	526	26	,	,	PUNCT
brj-25043	526	27	chiang	chiang	PROPN
brj-25043	526	28	,	,	PUNCT
brj-25043	526	29	c.	c.	PROPN
brj-25043	526	30	f.	f.	PROPN
brj-25043	526	31	,	,	PUNCT
brj-25043	526	32	chao	chao	PROPN
brj-25043	526	33	,	,	PUNCT
brj-25043	527	1	k.	k.	PROPN
brj-25043	527	2	p.	p.	PROPN
brj-25043	527	3	,	,	PUNCT
brj-25043	527	4	liu	liu	PROPN
brj-25043	527	5	,	,	PUNCT
brj-25043	527	6	m.	m.	PROPN
brj-25043	527	7	h.	h.	PROPN
brj-25043	527	8	,	,	PUNCT
brj-25043	527	9	chuang	chuang	PROPN
brj-25043	527	10	,	,	PUNCT
brj-25043	527	11	s.	s.	PROPN
brj-25043	527	12	h.	h.	PROPN
brj-25043	527	13	,	,	PUNCT
brj-25043	527	14	banks	bank	NOUN
brj-25043	527	15	,	,	PUNCT
brj-25043	527	16	c.	c.	PROPN
brj-25043	527	17	j.	j.	PROPN
brj-25043	527	18	,	,	PUNCT
brj-25043	527	19	and	and	CCONJ
brj-25043	527	20	wang	wang	PROPN
brj-25043	527	21	,	,	PUNCT
brj-25043	527	22	s.	s.	PROPN
brj-25043	527	23	c.	c.	PROPN
brj-25043	527	24	(	(	PUNCT
brj-25043	527	25	2010	2010	NUM
brj-25043	527	26	)	)	PUNCT
brj-25043	527	27	.	.	PUNCT
brj-25043	528	1	“	"	PUNCT
brj-25043	528	2	modeling	model	VERB
brj-25043	528	3	biogas	biogas	NOUN
brj-25043	528	4	production	production	NOUN
brj-25043	528	5	from	from	ADP
brj-25043	528	6	organic	organic	ADJ
brj-25043	528	7	fraction	fraction	NOUN
brj-25043	528	8	of	of	ADP
brj-25043	528	9	msw	msw	NOUN
brj-25043	528	10	co	co	VERB
brj-25043	528	11	-	-	VERB
brj-25043	528	12	digested	digested	ADJ
brj-25043	528	13	with	with	ADP
brj-25043	528	14	mswi	mswi	NOUN
brj-25043	528	15	ashes	ashe	NOUN
brj-25043	528	16	in	in	ADP
brj-25043	528	17	anaerobic	anaerobic	ADJ
brj-25043	528	18	bioreactors	bioreactor	NOUN
brj-25043	528	19	,	,	PUNCT
brj-25043	528	20	”	"	PUNCT
brj-25043	528	21	bioresource	bioresource	ADP
brj-25043	528	22	technology	technology	NOUN
brj-25043	528	23	101(16	101(16	NOUN
brj-25043	528	24	)	)	PUNCT
brj-25043	528	25	,	,	PUNCT
brj-25043	528	26	6329	6329	NUM
brj-25043	528	27	-	-	SYM
brj-25043	528	28	6335	6335	NUM
brj-25043	528	29	.	.	PUNCT
brj-25043	529	1	doi	doi	NOUN
brj-25043	529	2	:	:	PUNCT
brj-25043	529	3	10.1016	10.1016	NUM
brj-25043	529	4	/	/	SYM
brj-25043	529	5	j.biortech.2010.03.048	j.biortech.2010.03.048	PROPN
brj-25043	529	6	lohani	lohani	PROPN
brj-25043	529	7	,	,	PUNCT
brj-25043	529	8	s.	s.	PROPN
brj-25043	529	9	p.	p.	PROPN
brj-25043	529	10	,	,	PUNCT
brj-25043	529	11	shakya	shakya	PROPN
brj-25043	529	12	,	,	PUNCT
brj-25043	529	13	s.	s.	PROPN
brj-25043	529	14	,	,	PUNCT
brj-25043	529	15	gurung	gurung	PROPN
brj-25043	529	16	,	,	PUNCT
brj-25043	529	17	p.	p.	PROPN
brj-25043	529	18	,	,	PUNCT
brj-25043	529	19	dhungana	dhungana	PROPN
brj-25043	529	20	,	,	PUNCT
brj-25043	529	21	b.	b.	PROPN
brj-25043	529	22	,	,	PUNCT
brj-25043	529	23	paudel	paudel	PROPN
brj-25043	529	24	,	,	PUNCT
brj-25043	529	25	d.	d.	PROPN
brj-25043	529	26	,	,	PUNCT
brj-25043	529	27	and	and	CCONJ
brj-25043	529	28	mainali	mainali	VERB
brj-25043	529	29	,	,	PUNCT
brj-25043	529	30	b.	b.	PROPN
brj-25043	529	31	(	(	PUNCT
brj-25043	529	32	2025	2025	NUM
brj-25043	529	33	)	)	PUNCT
brj-25043	529	34	.	.	PUNCT
brj-25043	530	1	“	"	PUNCT
brj-25043	530	2	anaerobic	anaerobic	ADJ
brj-25043	530	3	co	co	NOUN
brj-25043	530	4	-	-	NOUN
brj-25043	530	5	digestion	digestion	NOUN
brj-25043	530	6	of	of	ADP
brj-25043	530	7	food	food	NOUN
brj-25043	530	8	waste	waste	NOUN
brj-25043	530	9	,	,	PUNCT
brj-25043	530	10	poultry	poultry	NOUN
brj-25043	530	11	litter	litter	NOUN
brj-25043	530	12	and	and	CCONJ
brj-25043	530	13	sewage	sewage	NOUN
brj-25043	530	14	sludge	sludge	NOUN
brj-25043	530	15	:	:	PUNCT
brj-25043	530	16	seasonal	seasonal	ADJ
brj-25043	530	17	performance	performance	NOUN
brj-25043	530	18	under	under	ADP
brj-25043	530	19	ambient	ambient	ADJ
brj-25043	530	20	condition	condition	NOUN
brj-25043	530	21	and	and	CCONJ
brj-25043	530	22	model	model	NOUN
brj-25043	530	23	evaluation	evaluation	NOUN
brj-25043	530	24	,	,	PUNCT
brj-25043	530	25	”	"	PUNCT
brj-25043	530	26	energy	energy	NOUN
brj-25043	530	27	sources	source	NOUN
brj-25043	530	28	,	,	PUNCT
brj-25043	530	29	part	part	NOUN
brj-25043	530	30	a	a	DET
brj-25043	530	31	:	:	PUNCT
brj-25043	530	32	recovery	recovery	NOUN
brj-25043	530	33	,	,	PUNCT
brj-25043	530	34	utilization	utilization	NOUN
brj-25043	530	35	,	,	PUNCT
brj-25043	530	36	and	and	CCONJ
brj-25043	530	37	environmental	environmental	ADJ
brj-25043	530	38	effects	effect	NOUN
brj-25043	530	39	47(2	47(2	NUM
brj-25043	530	40	)	)	PUNCT
brj-25043	530	41	,	,	PUNCT
brj-25043	530	42	article	article	NOUN
brj-25043	530	43	1887976	1887976	NUM
brj-25043	530	44	.	.	PUNCT
brj-25043	531	1	doi	doi	NOUN
brj-25043	531	2	:	:	PUNCT
brj-25043	531	3	10.1080/15567036.2021.1887976	10.1080/15567036.2021.1887976	NUM
brj-25043	531	4	mu	mu	NOUN
brj-25043	531	5	,	,	PUNCT
brj-25043	531	6	y.	y.	PROPN
brj-25043	531	7	,	,	PUNCT
brj-25043	531	8	yu	yu	PROPN
brj-25043	531	9	,	,	PUNCT
brj-25043	531	10	h.-q	h.-q	PROPN
brj-25043	531	11	.	.	PUNCT
brj-25043	531	12	,	,	PUNCT
brj-25043	531	13	and	and	CCONJ
brj-25043	531	14	wang	wang	PROPN
brj-25043	531	15	,	,	PUNCT
brj-25043	531	16	g.	g.	PROPN
brj-25043	531	17	(	(	PUNCT
brj-25043	531	18	2007	2007	NUM
brj-25043	531	19	)	)	PUNCT
brj-25043	531	20	.	.	PUNCT
brj-25043	532	1	“	"	PUNCT
brj-25043	532	2	a	a	DET
brj-25043	532	3	kinetic	kinetic	ADJ
brj-25043	532	4	approach	approach	NOUN
brj-25043	532	5	to	to	ADP
brj-25043	532	6	anaerobic	anaerobic	ADJ
brj-25043	532	7	hydrogenproducing	hydrogenproducing	NOUN
brj-25043	532	8	process	process	NOUN
brj-25043	532	9	,	,	PUNCT
brj-25043	532	10	”	"	PUNCT
brj-25043	532	11	water	water	NOUN
brj-25043	532	12	research	research	NOUN
brj-25043	532	13	41(5	41(5	NUM
brj-25043	532	14	)	)	PUNCT
brj-25043	532	15	,	,	PUNCT
brj-25043	532	16	1152	1152	NUM
brj-25043	532	17	-	-	SYM
brj-25043	532	18	1160	1160	NUM
brj-25043	532	19	.	.	PUNCT
brj-25043	533	1	doi	doi	NOUN
brj-25043	533	2	:	:	PUNCT
brj-25043	533	3	10.1016	10.1016	NUM
brj-25043	533	4	/	/	SYM
brj-25043	533	5	j.watres.2006.11.047	j.watres.2006.11.047	PROPN
brj-25043	533	6	mueller	mueller	PROPN
brj-25043	533	7	,	,	PUNCT
brj-25043	533	8	l.	l.	PROPN
brj-25043	533	9	d.	d.	PROPN
brj-25043	533	10	,	,	PUNCT
brj-25043	533	11	nusbaum	nusbaum	PROPN
brj-25043	533	12	,	,	PUNCT
brj-25043	533	13	t.	t.	PROPN
brj-25043	533	14	j.	j.	PROPN
brj-25043	533	15	,	,	PUNCT
brj-25043	533	16	and	and	CCONJ
brj-25043	533	17	rose	rise	VERB
brj-25043	533	18	,	,	PUNCT
brj-25043	533	19	m.	m.	PROPN
brj-25043	533	20	r.	r.	PROPN
brj-25043	533	21	(	(	PUNCT
brj-25043	533	22	1995	1995	NUM
brj-25043	533	23	)	)	PUNCT
brj-25043	533	24	.	.	PUNCT
brj-25043	534	1	“	"	PUNCT
brj-25043	534	2	the	the	DET
brj-25043	534	3	gompertz	gompertz	NOUN
brj-25043	534	4	equation	equation	NOUN
brj-25043	534	5	as	as	ADP
brj-25043	534	6	a	a	DET
brj-25043	534	7	peer	peer	NOUN
brj-25043	534	8	-	-	PUNCT
brj-25043	534	9	reviewed	review	VERB
brj-25043	534	10	review	review	NOUN
brj-25043	534	11	article	article	NOUN
brj-25043	534	12	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	534	13	galal	galal	PROPN
brj-25043	534	14	et	et	PROPN
brj-25043	534	15	al	al	PROPN
brj-25043	534	16	.	.	PROPN
brj-25043	535	1	(	(	PUNCT
brj-25043	535	2	2025	2025	NUM
brj-25043	535	3	)	)	PUNCT
brj-25043	535	4	.	.	PUNCT
brj-25043	536	1	“	"	PUNCT
brj-25043	536	2	math	math	NOUN
brj-25043	536	3	modeling	modeling	NOUN
brj-25043	536	4	biogas	biogas	NOUN
brj-25043	536	5	production	production	NOUN
brj-25043	536	6	,	,	PUNCT
brj-25043	536	7	”	"	PUNCT
brj-25043	536	8	bioresources	bioresource	NOUN
brj-25043	536	9	20(4	20(4	NOUN
brj-25043	536	10	)	)	PUNCT
brj-25043	536	11	,	,	PUNCT
brj-25043	536	12	11237	11237	NUM
brj-25043	536	13	-	-	SYM
brj-25043	536	14	11266	11266	NUM
brj-25043	536	15	.	.	PUNCT
brj-25043	537	1	11265	11265	NUM
brj-25043	537	2	predictive	predictive	ADJ
brj-25043	537	3	tool	tool	NOUN
brj-25043	537	4	in	in	ADP
brj-25043	537	5	demography	demography	NOUN
brj-25043	537	6	,	,	PUNCT
brj-25043	537	7	”	"	PUNCT
brj-25043	537	8	experimental	experimental	ADJ
brj-25043	537	9	gerontology	gerontology	NOUN
brj-25043	537	10	30(6	30(6	NUM
brj-25043	537	11	)	)	PUNCT
brj-25043	537	12	,	,	PUNCT
brj-25043	537	13	553	553	NUM
brj-25043	537	14	-	-	SYM
brj-25043	537	15	569	569	NUM
brj-25043	537	16	.	.	PUNCT
brj-25043	538	1	doi	doi	NOUN
brj-25043	538	2	:	:	PUNCT
brj-25043	538	3	10.1016/0531	10.1016/0531	NUM
brj-25043	538	4	-	-	SYM
brj-25043	538	5	5565(95)00029	5565(95)00029	NUM
brj-25043	538	6	-	-	PUNCT
brj-25043	538	7	1	1	NUM
brj-25043	538	8	najafi	najafi	PROPN
brj-25043	538	9	,	,	PUNCT
brj-25043	538	10	b.	b.	PROPN
brj-25043	538	11	,	,	PUNCT
brj-25043	538	12	and	and	CCONJ
brj-25043	538	13	ardabili	ardabili	PROPN
brj-25043	538	14	,	,	PUNCT
brj-25043	538	15	s.	s.	PROPN
brj-25043	538	16	f.	f.	PROPN
brj-25043	538	17	(	(	PUNCT
brj-25043	538	18	2018	2018	NUM
brj-25043	538	19	)	)	PUNCT
brj-25043	538	20	.	.	PUNCT
brj-25043	539	1	“	"	PUNCT
brj-25043	539	2	application	application	NOUN
brj-25043	539	3	of	of	ADP
brj-25043	539	4	anfis	anfis	PROPN
brj-25043	539	5	,	,	PUNCT
brj-25043	539	6	ann	ann	PROPN
brj-25043	539	7	,	,	PUNCT
brj-25043	539	8	and	and	CCONJ
brj-25043	539	9	logistic	logistic	ADJ
brj-25043	539	10	methods	method	NOUN
brj-25043	539	11	in	in	ADP
brj-25043	539	12	estimating	estimate	VERB
brj-25043	539	13	biogas	biogas	NOUN
brj-25043	539	14	production	production	NOUN
brj-25043	539	15	from	from	ADP
brj-25043	539	16	spent	spend	VERB
brj-25043	539	17	mushroom	mushroom	NOUN
brj-25043	539	18	compost	compost	NOUN
brj-25043	539	19	(	(	PUNCT
brj-25043	539	20	smc	smc	PROPN
brj-25043	539	21	)	)	PUNCT
brj-25043	539	22	,	,	PUNCT
brj-25043	539	23	”	"	PUNCT
brj-25043	539	24	resources	resource	NOUN
brj-25043	539	25	,	,	PUNCT
brj-25043	539	26	conservation	conservation	NOUN
brj-25043	539	27	and	and	CCONJ
brj-25043	539	28	recycling	recycling	NOUN
brj-25043	539	29	133	133	NUM
brj-25043	539	30	,	,	PUNCT
brj-25043	539	31	169	169	NUM
brj-25043	539	32	-	-	SYM
brj-25043	539	33	178	178	NUM
brj-25043	539	34	.	.	PUNCT
brj-25043	540	1	doi	doi	NOUN
brj-25043	540	2	:	:	PUNCT
brj-25043	540	3	10.1016	10.1016	NUM
brj-25043	540	4	/	/	SYM
brj-25043	540	5	j.resconrec.2018.02.025	j.resconrec.2018.02.025	PROPN
brj-25043	540	6	nielfa	nielfa	NOUN
brj-25043	540	7	,	,	PUNCT
brj-25043	540	8	a.	a.	PROPN
brj-25043	540	9	,	,	PUNCT
brj-25043	540	10	cano	cano	PROPN
brj-25043	540	11	,	,	PUNCT
brj-25043	540	12	r.	r.	PROPN
brj-25043	540	13	,	,	PUNCT
brj-25043	540	14	vinot	vinot	ADV
brj-25043	540	15	,	,	PUNCT
brj-25043	540	16	m.	m.	NOUN
brj-25043	540	17	,	,	PUNCT
brj-25043	540	18	fernández	fernández	PROPN
brj-25043	540	19	,	,	PUNCT
brj-25043	540	20	e.	e.	PROPN
brj-25043	540	21	,	,	PUNCT
brj-25043	540	22	and	and	CCONJ
brj-25043	540	23	fdz	fdz	PROPN
brj-25043	540	24	-	-	PUNCT
brj-25043	540	25	polanco	polanco	PROPN
brj-25043	540	26	,	,	PUNCT
brj-25043	540	27	m.	m.	NOUN
brj-25043	540	28	(	(	PUNCT
brj-25043	540	29	2015	2015	NUM
brj-25043	540	30	)	)	PUNCT
brj-25043	540	31	.	.	PUNCT
brj-25043	541	1	“	"	PUNCT
brj-25043	541	2	anaerobic	anaerobic	VERB
brj-25043	541	3	digestion	digestion	NOUN
brj-25043	541	4	modeling	modeling	NOUN
brj-25043	541	5	of	of	ADP
brj-25043	541	6	the	the	DET
brj-25043	541	7	main	main	ADJ
brj-25043	541	8	components	component	NOUN
brj-25043	541	9	of	of	ADP
brj-25043	541	10	organic	organic	ADJ
brj-25043	541	11	fraction	fraction	NOUN
brj-25043	541	12	of	of	ADP
brj-25043	541	13	municipal	municipal	ADJ
brj-25043	541	14	solid	solid	ADJ
brj-25043	541	15	waste	waste	NOUN
brj-25043	541	16	,	,	PUNCT
brj-25043	541	17	”	"	PUNCT
brj-25043	541	18	process	process	NOUN
brj-25043	541	19	safety	safety	NOUN
brj-25043	541	20	and	and	CCONJ
brj-25043	541	21	environmental	environmental	ADJ
brj-25043	541	22	protection	protection	NOUN
brj-25043	541	23	94	94	NUM
brj-25043	541	24	,	,	PUNCT
brj-25043	541	25	180	180	NUM
brj-25043	541	26	-	-	SYM
brj-25043	541	27	187	187	NUM
brj-25043	541	28	.	.	PUNCT
brj-25043	542	1	doi	doi	NOUN
brj-25043	542	2	:	:	PUNCT
brj-25043	542	3	10.1016	10.1016	NUM
brj-25043	542	4	/	/	SYM
brj-25043	542	5	j.psep.2015.02.002	j.psep.2015.02.002	NOUN
brj-25043	542	6	olatunji	olatunji	NOUN
brj-25043	542	7	,	,	PUNCT
brj-25043	542	8	k.	k.	PROPN
brj-25043	542	9	o.	o.	PROPN
brj-25043	542	10	,	,	PUNCT
brj-25043	542	11	mootswi	mootswi	PROPN
brj-25043	542	12	,	,	PUNCT
brj-25043	542	13	k.	k.	PROPN
brj-25043	542	14	d.	d.	PROPN
brj-25043	542	15	,	,	PUNCT
brj-25043	542	16	olatunji	olatunji	PROPN
brj-25043	542	17	,	,	PUNCT
brj-25043	542	18	o.	o.	NOUN
brj-25043	542	19	o.	o.	PROPN
brj-25043	542	20	,	,	PUNCT
brj-25043	542	21	zwane	zwane	NOUN
brj-25043	542	22	,	,	PUNCT
brj-25043	542	23	m.	m.	NOUN
brj-25043	542	24	i.	i.	PROPN
brj-25043	542	25	,	,	PUNCT
brj-25043	542	26	van	van	PROPN
brj-25043	542	27	rensburg	rensburg	PROPN
brj-25043	542	28	,	,	PUNCT
brj-25043	542	29	n.	n.	PROPN
brj-25043	542	30	j.	j.	PROPN
brj-25043	542	31	,	,	PUNCT
brj-25043	542	32	and	and	CCONJ
brj-25043	542	33	madyira	madyira	PROPN
brj-25043	542	34	,	,	PUNCT
brj-25043	542	35	d.	d.	PROPN
brj-25043	542	36	m.	m.	PROPN
brj-25043	542	37	(	(	PUNCT
brj-25043	542	38	2025	2025	NUM
brj-25043	542	39	)	)	PUNCT
brj-25043	542	40	.	.	PUNCT
brj-25043	543	1	“	"	PUNCT
brj-25043	543	2	anaerobic	anaerobic	ADJ
brj-25043	543	3	co	co	NOUN
brj-25043	543	4	-	-	NOUN
brj-25043	543	5	digestion	digestion	NOUN
brj-25043	543	6	of	of	ADP
brj-25043	543	7	food	food	NOUN
brj-25043	543	8	waste	waste	NOUN
brj-25043	543	9	and	and	CCONJ
brj-25043	543	10	groundnut	groundnut	NOUN
brj-25043	543	11	shells	shell	NOUN
brj-25043	543	12	:	:	PUNCT
brj-25043	543	13	synergistic	synergistic	ADJ
brj-25043	543	14	impact	impact	NOUN
brj-25043	543	15	assessment	assessment	NOUN
brj-25043	543	16	and	and	CCONJ
brj-25043	543	17	kinetic	kinetic	ADJ
brj-25043	543	18	modeling	modeling	NOUN
brj-25043	543	19	,	,	PUNCT
brj-25043	543	20	”	"	PUNCT
brj-25043	543	21	waste	waste	NOUN
brj-25043	543	22	and	and	CCONJ
brj-25043	543	23	biomass	biomass	NOUN
brj-25043	543	24	valorization	valorization	NOUN
brj-25043	543	25	16	16	NUM
brj-25043	543	26	,	,	PUNCT
brj-25043	543	27	3745	3745	NUM
brj-25043	543	28	-	-	SYM
brj-25043	543	29	3760	3760	NUM
brj-25043	543	30	.	.	PUNCT
brj-25043	544	1	doi	doi	NOUN
brj-25043	544	2	:	:	PUNCT
brj-25043	544	3	10.1007	10.1007	NUM
brj-25043	544	4	/	/	SYM
brj-25043	544	5	s12649	s12649	NOUN
brj-25043	544	6	-	-	PUNCT
brj-25043	544	7	025	025	NUM
brj-25043	544	8	-	-	PUNCT
brj-25043	544	9	02904	02904	NUM
brj-25043	544	10	-	-	SYM
brj-25043	544	11	1	1	NUM
brj-25043	544	12	peleg	peleg	NOUN
brj-25043	544	13	,	,	PUNCT
brj-25043	544	14	m.	m.	NOUN
brj-25043	544	15	,	,	PUNCT
brj-25043	544	16	and	and	CCONJ
brj-25043	544	17	corradini	corradini	PROPN
brj-25043	544	18	,	,	PUNCT
brj-25043	544	19	m.	m.	NOUN
brj-25043	544	20	g.	g.	PROPN
brj-25043	544	21	(	(	PUNCT
brj-25043	544	22	2011	2011	NUM
brj-25043	544	23	)	)	PUNCT
brj-25043	544	24	.	.	PUNCT
brj-25043	545	1	“	"	PUNCT
brj-25043	545	2	microbial	microbial	ADJ
brj-25043	545	3	growth	growth	NOUN
brj-25043	545	4	curves	curve	NOUN
brj-25043	545	5	:	:	PUNCT
brj-25043	545	6	what	what	PRON
brj-25043	545	7	the	the	DET
brj-25043	545	8	models	model	NOUN
brj-25043	545	9	tell	tell	VERB
brj-25043	545	10	us	we	PRON
brj-25043	545	11	and	and	CCONJ
brj-25043	545	12	what	what	PRON
brj-25043	545	13	they	they	PRON
brj-25043	545	14	can	can	AUX
brj-25043	545	15	not	not	PART
brj-25043	545	16	,	,	PUNCT
brj-25043	545	17	”	"	PUNCT
brj-25043	545	18	critical	critical	ADJ
brj-25043	545	19	reviews	review	NOUN
brj-25043	545	20	in	in	ADP
brj-25043	545	21	food	food	NOUN
brj-25043	545	22	science	science	NOUN
brj-25043	545	23	and	and	CCONJ
brj-25043	545	24	nutrition	nutrition	NOUN
brj-25043	545	25	51(10	51(10	NUM
brj-25043	545	26	)	)	PUNCT
brj-25043	545	27	,	,	PUNCT
brj-25043	545	28	917	917	NUM
brj-25043	545	29	-	-	SYM
brj-25043	545	30	945	945	NUM
brj-25043	545	31	.	.	PUNCT
brj-25043	546	1	doi	doi	NOUN
brj-25043	546	2	:	:	PUNCT
brj-25043	546	3	10.1080/10408398.2011.570463	10.1080/10408398.2011.570463	NUM
brj-25043	546	4	pulgarín	pulgarín	NOUN
brj-25043	546	5	-	-	PUNCT
brj-25043	546	6	muñoz	muñoz	PROPN
brj-25043	546	7	,	,	PUNCT
brj-25043	546	8	c.	c.	PROPN
brj-25043	546	9	e.	e.	PROPN
brj-25043	546	10	,	,	PUNCT
brj-25043	546	11	saldarriaga	saldarriaga	PROPN
brj-25043	546	12	-	-	PUNCT
brj-25043	546	13	molina	molina	PROPN
brj-25043	546	14	,	,	PUNCT
brj-25043	546	15	j.	j.	PROPN
brj-25043	546	16	c.	c.	PROPN
brj-25043	546	17	,	,	PUNCT
brj-25043	546	18	correa	correa	PROPN
brj-25043	546	19	-	-	PUNCT
brj-25043	546	20	ochoa	ochoa	PROPN
brj-25043	546	21	,	,	PUNCT
brj-25043	546	22	m.	m.	NOUN
brj-25043	546	23	a.	a.	PROPN
brj-25043	546	24	,	,	PUNCT
brj-25043	546	25	and	and	CCONJ
brj-25043	546	26	castrovalencia	castrovalencia	NOUN
brj-25043	546	27	,	,	PUNCT
brj-25043	546	28	j.	j.	PROPN
brj-25043	546	29	c.	c.	PROPN
brj-25043	546	30	(	(	PUNCT
brj-25043	546	31	2025	2025	NUM
brj-25043	546	32	)	)	PUNCT
brj-25043	546	33	.	.	PUNCT
brj-25043	547	1	“	"	PUNCT
brj-25043	547	2	effect	effect	NOUN
brj-25043	547	3	of	of	ADP
brj-25043	547	4	cosubstrate	cosubstrate	ADJ
brj-25043	547	5	ratio	ratio	NOUN
brj-25043	547	6	and	and	CCONJ
brj-25043	547	7	temperature	temperature	NOUN
brj-25043	547	8	on	on	ADP
brj-25043	547	9	sewage	sewage	NOUN
brj-25043	547	10	sludge	sludge	NOUN
brj-25043	547	11	and	and	CCONJ
brj-25043	547	12	agro	agro	ADJ
brj-25043	547	13	-	-	PUNCT
brj-25043	547	14	industrial	industrial	ADJ
brj-25043	547	15	fruit	fruit	NOUN
brj-25043	547	16	and	and	CCONJ
brj-25043	547	17	vegetable	vegetable	NOUN
brj-25043	547	18	waste	waste	NOUN
brj-25043	547	19	anaerobic	anaerobic	NOUN
brj-25043	547	20	co	co	NOUN
brj-25043	547	21	-	-	NOUN
brj-25043	547	22	digestion	digestion	NOUN
brj-25043	547	23	,	,	PUNCT
brj-25043	547	24	”	"	PUNCT
brj-25043	547	25	waste	waste	NOUN
brj-25043	547	26	and	and	CCONJ
brj-25043	547	27	biomass	biomass	NOUN
brj-25043	547	28	valorization	valorization	NOUN
brj-25043	547	29	2025	2025	NUM
brj-25043	547	30	,	,	PUNCT
brj-25043	547	31	available	available	ADJ
brj-25043	547	32	online	online	NOUN
brj-25043	547	33	.	.	PUNCT
brj-25043	548	1	doi	doi	NOUN
brj-25043	548	2	:	:	PUNCT
brj-25043	548	3	10.1007	10.1007	NUM
brj-25043	548	4	/	/	SYM
brj-25043	548	5	s12649	s12649	NOUN
brj-25043	548	6	-	-	PUNCT
brj-25043	548	7	025	025	NUM
brj-25043	548	8	-	-	PUNCT
brj-25043	548	9	03129	03129	NUM
brj-25043	548	10	-	-	PUNCT
brj-25043	548	11	y	y	PROPN
brj-25043	548	12	roberts	roberts	PROPN
brj-25043	548	13	,	,	PUNCT
brj-25043	548	14	s.	s.	PROPN
brj-25043	548	15	,	,	PUNCT
brj-25043	548	16	mathaka	mathaka	ADV
brj-25043	548	17	,	,	PUNCT
brj-25043	548	18	n.	n.	NOUN
brj-25043	548	19	,	,	PUNCT
brj-25043	548	20	zeleke	zeleke	NOUN
brj-25043	548	21	,	,	PUNCT
brj-25043	548	22	m.	m.	NOUN
brj-25043	548	23	a.	a.	NOUN
brj-25043	548	24	,	,	PUNCT
brj-25043	548	25	and	and	CCONJ
brj-25043	548	26	nwaigwe	nwaigwe	PROPN
brj-25043	548	27	,	,	PUNCT
brj-25043	548	28	k.	k.	PROPN
brj-25043	548	29	n.	n.	PROPN
brj-25043	548	30	(	(	PUNCT
brj-25043	548	31	2023	2023	NUM
brj-25043	548	32	)	)	PUNCT
brj-25043	548	33	.	.	PUNCT
brj-25043	549	1	“	"	PUNCT
brj-25043	549	2	comparative	comparative	ADJ
brj-25043	549	3	analysis	analysis	NOUN
brj-25043	549	4	of	of	ADP
brj-25043	549	5	five	five	NUM
brj-25043	549	6	kinetic	kinetic	ADJ
brj-25043	549	7	models	model	NOUN
brj-25043	549	8	for	for	ADP
brj-25043	549	9	prediction	prediction	NOUN
brj-25043	549	10	of	of	ADP
brj-25043	549	11	methane	methane	NOUN
brj-25043	549	12	yield	yield	NOUN
brj-25043	549	13	,	,	PUNCT
brj-25043	549	14	”	"	PUNCT
brj-25043	549	15	journal	journal	NOUN
brj-25043	549	16	of	of	ADP
brj-25043	549	17	the	the	DET
brj-25043	549	18	institution	institution	NOUN
brj-25043	549	19	of	of	ADP
brj-25043	549	20	engineers	engineer	NOUN
brj-25043	549	21	(	(	PUNCT
brj-25043	549	22	india)series	india)serie	NOUN
brj-25043	549	23	a	a	DET
brj-25043	549	24	104	104	NUM
brj-25043	549	25	,	,	PUNCT
brj-25043	549	26	335	335	NUM
brj-25043	549	27	-	-	SYM
brj-25043	549	28	342	342	NUM
brj-25043	549	29	.	.	PUNCT
brj-25043	550	1	doi	doi	NOUN
brj-25043	550	2	:	:	PUNCT
brj-25043	550	3	10.1007	10.1007	NUM
brj-25043	550	4	/	/	SYM
brj-25043	550	5	s40030	s40030	NOUN
brj-25043	550	6	-	-	NOUN
brj-25043	550	7	02300715	02300715	NUM
brj-25043	550	8	-	-	PUNCT
brj-25043	550	9	y	y	PROPN
brj-25043	550	10	rossi	rossi	PROPN
brj-25043	550	11	,	,	PUNCT
brj-25043	550	12	e.	e.	PROPN
brj-25043	550	13	,	,	PUNCT
brj-25043	550	14	pecorini	pecorini	PROPN
brj-25043	550	15	,	,	PUNCT
brj-25043	550	16	i.	i.	NOUN
brj-25043	550	17	,	,	PUNCT
brj-25043	550	18	and	and	CCONJ
brj-25043	550	19	iannelli	iannelli	ADV
brj-25043	550	20	,	,	PUNCT
brj-25043	550	21	r.	r.	PROPN
brj-25043	550	22	(	(	PUNCT
brj-25043	550	23	2022	2022	NUM
brj-25043	550	24	)	)	PUNCT
brj-25043	550	25	.	.	PUNCT
brj-25043	551	1	“	"	PUNCT
brj-25043	551	2	multilinear	multilinear	VERB
brj-25043	551	3	regression	regression	NOUN
brj-25043	551	4	model	model	NOUN
brj-25043	551	5	for	for	ADP
brj-25043	551	6	biogas	biogas	NOUN
brj-25043	551	7	production	production	NOUN
brj-25043	551	8	prediction	prediction	NOUN
brj-25043	551	9	from	from	ADP
brj-25043	551	10	dry	dry	ADJ
brj-25043	551	11	anaerobic	anaerobic	NOUN
brj-25043	551	12	digestion	digestion	NOUN
brj-25043	551	13	of	of	ADP
brj-25043	551	14	ofmsw	ofmsw	NOUN
brj-25043	551	15	,	,	PUNCT
brj-25043	551	16	”	"	PUNCT
brj-25043	551	17	sustainability	sustainability	NOUN
brj-25043	551	18	14(8	14(8	NUM
brj-25043	551	19	)	)	PUNCT
brj-25043	551	20	,	,	PUNCT
brj-25043	551	21	article	article	NOUN
brj-25043	551	22	4393	4393	NUM
brj-25043	551	23	.	.	PUNCT
brj-25043	552	1	doi	doi	NOUN
brj-25043	552	2	:	:	PUNCT
brj-25043	552	3	10.3390	10.3390	NUM
brj-25043	552	4	/	/	SYM
brj-25043	552	5	su14084393	su14084393	PROPN
brj-25043	552	6	said	say	VERB
brj-25043	552	7	,	,	PUNCT
brj-25043	552	8	n.	n.	NOUN
brj-25043	552	9	,	,	PUNCT
brj-25043	552	10	alblawi	alblawi	PROPN
brj-25043	552	11	,	,	PUNCT
brj-25043	552	12	a.	a.	NOUN
brj-25043	552	13	,	,	PUNCT
brj-25043	552	14	hendy	hendy	PROPN
brj-25043	552	15	,	,	PUNCT
brj-25043	552	16	i.	i.	PROPN
brj-25043	552	17	a.	a.	PROPN
brj-25043	552	18	,	,	PUNCT
brj-25043	552	19	and	and	CCONJ
brj-25043	552	20	abdel	abdel	PROPN
brj-25043	552	21	daiem	daiem	PROPN
brj-25043	552	22	,	,	PUNCT
brj-25043	552	23	m.	m.	NOUN
brj-25043	552	24	m.	m.	NOUN
brj-25043	552	25	(	(	PUNCT
brj-25043	552	26	2020	2020	NUM
brj-25043	552	27	)	)	PUNCT
brj-25043	552	28	.	.	PUNCT
brj-25043	553	1	“	"	PUNCT
brj-25043	553	2	analysis	analysis	NOUN
brj-25043	553	3	of	of	ADP
brj-25043	553	4	energy	energy	NOUN
brj-25043	553	5	and	and	CCONJ
brj-25043	553	6	greenhouse	greenhouse	NOUN
brj-25043	553	7	gas	gas	NOUN
brj-25043	553	8	emissions	emission	NOUN
brj-25043	553	9	of	of	ADP
brj-25043	553	10	rice	rice	NOUN
brj-25043	553	11	straw	straw	NOUN
brj-25043	553	12	to	to	ADP
brj-25043	553	13	energy	energy	NOUN
brj-25043	553	14	chain	chain	NOUN
brj-25043	553	15	in	in	ADP
brj-25043	553	16	egypt	egypt	PROPN
brj-25043	553	17	,	,	PUNCT
brj-25043	553	18	”	"	PUNCT
brj-25043	553	19	bioresources	bioresource	NOUN
brj-25043	553	20	15(1	15(1	NUM
brj-25043	553	21	)	)	PUNCT
brj-25043	553	22	,	,	PUNCT
brj-25043	553	23	1510	1510	NUM
brj-25043	553	24	-	-	SYM
brj-25043	553	25	1520	1520	NUM
brj-25043	553	26	.	.	PUNCT
brj-25043	554	1	doi	doi	NOUN
brj-25043	554	2	:	:	PUNCT
brj-25043	554	3	10.15376	10.15376	NUM
brj-25043	554	4	/	/	SYM
brj-25043	554	5	biores.15.1.1510	biores.15.1.1510	PROPN
brj-25043	554	6	-	-	SYM
brj-25043	554	7	1520	1520	NUM
brj-25043	554	8	salamattalab	salamattalab	NOUN
brj-25043	554	9	,	,	PUNCT
brj-25043	554	10	m.	m.	NOUN
brj-25043	554	11	m.	m.	NOUN
brj-25043	554	12	,	,	PUNCT
brj-25043	554	13	zonoozi	zonoozi	NOUN
brj-25043	554	14	,	,	PUNCT
brj-25043	554	15	m.	m.	PROPN
brj-25043	554	16	h.	h.	PROPN
brj-25043	554	17	,	,	PUNCT
brj-25043	554	18	and	and	CCONJ
brj-25043	554	19	molavi	molavi	NOUN
brj-25043	554	20	-	-	PUNCT
brj-25043	554	21	arabshahi	arabshahi	NOUN
brj-25043	554	22	,	,	PUNCT
brj-25043	554	23	m.	m.	NOUN
brj-25043	554	24	(	(	PUNCT
brj-25043	554	25	2024	2024	NUM
brj-25043	554	26	)	)	PUNCT
brj-25043	554	27	.	.	PUNCT
brj-25043	555	1	“	"	PUNCT
brj-25043	555	2	innovative	innovative	ADJ
brj-25043	555	3	approach	approach	NOUN
brj-25043	555	4	for	for	ADP
brj-25043	555	5	predicting	predict	VERB
brj-25043	555	6	biogas	biogas	NOUN
brj-25043	555	7	production	production	NOUN
brj-25043	555	8	from	from	ADP
brj-25043	555	9	large	large	ADJ
brj-25043	555	10	-	-	PUNCT
brj-25043	555	11	scale	scale	NOUN
brj-25043	555	12	anaerobic	anaerobic	NOUN
brj-25043	555	13	digester	digester	NOUN
brj-25043	555	14	using	use	VERB
brj-25043	555	15	long	long	ADJ
brj-25043	555	16	-	-	PUNCT
brj-25043	555	17	short	short	ADJ
brj-25043	555	18	term	term	NOUN
brj-25043	555	19	memory	memory	NOUN
brj-25043	555	20	(	(	PUNCT
brj-25043	555	21	lstm	lstm	NOUN
brj-25043	555	22	)	)	PUNCT
brj-25043	555	23	coupled	couple	VERB
brj-25043	555	24	with	with	ADP
brj-25043	555	25	genetic	genetic	ADJ
brj-25043	555	26	algorithm	algorithm	NOUN
brj-25043	555	27	(	(	PUNCT
brj-25043	555	28	ga	ga	NOUN
brj-25043	555	29	)	)	PUNCT
brj-25043	555	30	,	,	PUNCT
brj-25043	555	31	”	"	PUNCT
brj-25043	555	32	waste	waste	NOUN
brj-25043	555	33	management	management	NOUN
brj-25043	555	34	175	175	NUM
brj-25043	555	35	,	,	PUNCT
brj-25043	555	36	30	30	NUM
brj-25043	555	37	-	-	SYM
brj-25043	555	38	41	41	NUM
brj-25043	555	39	.	.	PUNCT
brj-25043	556	1	doi	doi	NOUN
brj-25043	556	2	:	:	PUNCT
brj-25043	556	3	10.1016	10.1016	NUM
brj-25043	556	4	/	/	SYM
brj-25043	556	5	j.wasman.2023.12.046	j.wasman.2023.12.046	NOUN
brj-25043	556	6	sappl	sappl	NOUN
brj-25043	556	7	,	,	PUNCT
brj-25043	556	8	j.	j.	PROPN
brj-25043	556	9	,	,	PUNCT
brj-25043	556	10	harders	harder	NOUN
brj-25043	556	11	,	,	PUNCT
brj-25043	556	12	m.	m.	NOUN
brj-25043	556	13	,	,	PUNCT
brj-25043	556	14	and	and	CCONJ
brj-25043	556	15	rauch	rauch	PROPN
brj-25043	556	16	,	,	PUNCT
brj-25043	556	17	w.	w.	PROPN
brj-25043	556	18	(	(	PUNCT
brj-25043	556	19	2023	2023	NUM
brj-25043	556	20	)	)	PUNCT
brj-25043	556	21	.	.	PUNCT
brj-25043	557	1	“	"	PUNCT
brj-25043	557	2	machine	machine	NOUN
brj-25043	557	3	learning	learn	VERB
brj-25043	557	4	for	for	ADP
brj-25043	557	5	quantile	quantile	ADJ
brj-25043	557	6	regression	regression	NOUN
brj-25043	557	7	of	of	ADP
brj-25043	557	8	biogas	biogas	NOUN
brj-25043	557	9	production	production	NOUN
brj-25043	557	10	rates	rate	NOUN
brj-25043	557	11	in	in	ADP
brj-25043	557	12	anaerobic	anaerobic	ADJ
brj-25043	557	13	digesters	digester	NOUN
brj-25043	557	14	,	,	PUNCT
brj-25043	557	15	”	"	PUNCT
brj-25043	557	16	science	science	NOUN
brj-25043	557	17	of	of	ADP
brj-25043	557	18	the	the	DET
brj-25043	557	19	total	total	ADJ
brj-25043	557	20	environment	environment	NOUN
brj-25043	557	21	872	872	NUM
brj-25043	557	22	,	,	PUNCT
brj-25043	557	23	article	article	NOUN
brj-25043	557	24	161923	161923	NUM
brj-25043	557	25	.	.	PUNCT
brj-25043	558	1	doi	doi	NOUN
brj-25043	558	2	:	:	PUNCT
brj-25043	558	3	10.1016	10.1016	NUM
brj-25043	558	4	/	/	SYM
brj-25043	558	5	j.scitotenv.2023.161923	j.scitotenv.2023.161923	PROPN
brj-25043	558	6	schroer	schroer	PROPN
brj-25043	558	7	,	,	PUNCT
brj-25043	558	8	h.	h.	PROPN
brj-25043	558	9	w.	w.	PROPN
brj-25043	558	10	,	,	PUNCT
brj-25043	558	11	and	and	CCONJ
brj-25043	558	12	just	just	ADV
brj-25043	558	13	,	,	PUNCT
brj-25043	558	14	c.	c.	PROPN
brj-25043	558	15	l.	l.	PROPN
brj-25043	558	16	(	(	PUNCT
brj-25043	558	17	2023	2023	NUM
brj-25043	558	18	)	)	PUNCT
brj-25043	558	19	.	.	PUNCT
brj-25043	559	1	“	"	PUNCT
brj-25043	559	2	feature	feature	NOUN
brj-25043	559	3	engineering	engineering	NOUN
brj-25043	559	4	and	and	CCONJ
brj-25043	559	5	supervised	supervised	ADJ
brj-25043	559	6	machine	machine	NOUN
brj-25043	559	7	learning	learning	NOUN
brj-25043	559	8	to	to	PART
brj-25043	559	9	forecast	forecast	VERB
brj-25043	559	10	biogas	biogas	NOUN
brj-25043	559	11	production	production	NOUN
brj-25043	559	12	during	during	ADP
brj-25043	559	13	municipal	municipal	ADJ
brj-25043	559	14	anaerobic	anaerobic	NOUN
brj-25043	559	15	co	co	NOUN
brj-25043	559	16	-	-	NOUN
brj-25043	559	17	digestion	digestion	NOUN
brj-25043	559	18	,	,	PUNCT
brj-25043	559	19	”	"	PUNCT
brj-25043	559	20	acs	acs	PROPN
brj-25043	559	21	es&t	es&t	PROPN
brj-25043	559	22	engineering	engineer	VERB
brj-25043	559	23	4(3	4(3	NUM
brj-25043	559	24	)	)	PUNCT
brj-25043	559	25	,	,	PUNCT
brj-25043	559	26	660	660	NUM
brj-25043	559	27	-	-	SYM
brj-25043	559	28	672	672	NUM
brj-25043	559	29	.	.	PUNCT
brj-25043	560	1	doi	doi	NOUN
brj-25043	560	2	:	:	PUNCT
brj-25043	560	3	10.1021	10.1021	NUM
brj-25043	560	4	/	/	SYM
brj-25043	560	5	acsestengg.3c00435	acsestengg.3c00435	PROPN
brj-25043	560	6	shindell	shindell	PROPN
brj-25043	560	7	,	,	PUNCT
brj-25043	560	8	d.	d.	PROPN
brj-25043	560	9	,	,	PUNCT
brj-25043	560	10	sadavarte	sadavarte	NOUN
brj-25043	560	11	,	,	PUNCT
brj-25043	560	12	p.	p.	PROPN
brj-25043	560	13	,	,	PUNCT
brj-25043	560	14	aben	aben	PROPN
brj-25043	560	15	,	,	PUNCT
brj-25043	560	16	i.	i.	PROPN
brj-25043	560	17	,	,	PUNCT
brj-25043	560	18	bredariol	bredariol	NOUN
brj-25043	560	19	,	,	PUNCT
brj-25043	560	20	t.	t.	PROPN
brj-25043	560	21	de	de	PROPN
brj-25043	560	22	o.	o.	PROPN
brj-25043	560	23	,	,	PUNCT
brj-25043	560	24	dreyfus	dreyfus	PROPN
brj-25043	560	25	,	,	PUNCT
brj-25043	560	26	g.	g.	PROPN
brj-25043	560	27	,	,	PUNCT
brj-25043	560	28	höglund	höglund	NOUN
brj-25043	560	29	-	-	PUNCT
brj-25043	560	30	isaksson	isaksson	NOUN
brj-25043	560	31	,	,	PUNCT
brj-25043	560	32	l.	l.	PROPN
brj-25043	560	33	,	,	PUNCT
brj-25043	560	34	poulter	poulter	PROPN
brj-25043	560	35	,	,	PUNCT
brj-25043	560	36	b.	b.	PROPN
brj-25043	560	37	,	,	PUNCT
brj-25043	560	38	saunois	saunois	NOUN
brj-25043	560	39	,	,	PUNCT
brj-25043	560	40	m.	m.	NOUN
brj-25043	560	41	,	,	PUNCT
brj-25043	560	42	schmidt	schmidt	PROPN
brj-25043	560	43	,	,	PUNCT
brj-25043	560	44	g.	g.	PROPN
brj-25043	560	45	a.	a.	PROPN
brj-25043	560	46	,	,	PUNCT
brj-25043	560	47	and	and	CCONJ
brj-25043	560	48	szopa	szopa	PROPN
brj-25043	560	49	,	,	PUNCT
brj-25043	560	50	s.	s.	PROPN
brj-25043	560	51	(	(	PUNCT
brj-25043	560	52	2024	2024	NUM
brj-25043	560	53	)	)	PUNCT
brj-25043	560	54	.	.	PUNCT
brj-25043	561	1	“	"	PUNCT
brj-25043	561	2	the	the	DET
brj-25043	561	3	methane	methane	NOUN
brj-25043	561	4	imperative	imperative	NOUN
brj-25043	561	5	,	,	PUNCT
brj-25043	561	6	”	"	PUNCT
brj-25043	561	7	frontiers	frontier	NOUN
brj-25043	561	8	in	in	ADP
brj-25043	561	9	science	science	NOUN
brj-25043	561	10	2	2	NUM
brj-25043	561	11	,	,	PUNCT
brj-25043	561	12	article	article	NOUN
brj-25043	561	13	1349770	1349770	NUM
brj-25043	561	14	.	.	PUNCT
brj-25043	562	1	doi	doi	NOUN
brj-25043	562	2	:	:	PUNCT
brj-25043	562	3	10.3389	10.3389	NUM
brj-25043	562	4	/	/	SYM
brj-25043	562	5	fsci.2024.1349770	fsci.2024.1349770	NOUN
brj-25043	562	6	simon	simon	NOUN
brj-25043	562	7	,	,	PUNCT
brj-25043	562	8	m.	m.	PROPN
brj-25043	562	9	k.	k.	PROPN
brj-25043	562	10	(	(	PUNCT
brj-25043	562	11	2002	2002	NUM
brj-25043	562	12	)	)	PUNCT
brj-25043	562	13	.	.	PUNCT
brj-25043	563	1	probability	probability	NOUN
brj-25043	563	2	distributions	distribution	NOUN
brj-25043	563	3	involving	involve	VERB
brj-25043	563	4	gaussian	gaussian	ADJ
brj-25043	563	5	random	random	ADJ
brj-25043	563	6	variables	variable	NOUN
brj-25043	563	7	,	,	PUNCT
brj-25043	563	8	springer	springer	NOUN
brj-25043	563	9	,	,	PUNCT
brj-25043	563	10	new	new	PROPN
brj-25043	563	11	york	york	PROPN
brj-25043	563	12	,	,	PUNCT
brj-25043	563	13	ny	ny	PROPN
brj-25043	563	14	,	,	PUNCT
brj-25043	563	15	usa	usa	PROPN
brj-25043	563	16	.	.	PROPN
brj-25043	563	17	sun	sun	PROPN
brj-25043	563	18	,	,	PUNCT
brj-25043	563	19	j.	j.	PROPN
brj-25043	563	20	,	,	PUNCT
brj-25043	563	21	xu	xu	PROPN
brj-25043	563	22	,	,	PUNCT
brj-25043	563	23	y.	y.	PROPN
brj-25043	563	24	,	,	PUNCT
brj-25043	563	25	nairat	nairat	PROPN
brj-25043	563	26	,	,	PUNCT
brj-25043	563	27	s.	s.	PROPN
brj-25043	563	28	,	,	PUNCT
brj-25043	563	29	zhou	zhou	PROPN
brj-25043	563	30	,	,	PUNCT
brj-25043	563	31	j.	j.	PROPN
brj-25043	563	32	,	,	PUNCT
brj-25043	563	33	and	and	CCONJ
brj-25043	563	34	he	he	PRON
brj-25043	563	35	,	,	PUNCT
brj-25043	563	36	z.	z.	PROPN
brj-25043	563	37	(	(	PUNCT
brj-25043	563	38	2023	2023	NUM
brj-25043	563	39	)	)	PUNCT
brj-25043	563	40	.	.	PUNCT
brj-25043	564	1	“	"	PUNCT
brj-25043	564	2	prediction	prediction	NOUN
brj-25043	564	3	of	of	ADP
brj-25043	564	4	biogas	biogas	NOUN
brj-25043	564	5	production	production	NOUN
brj-25043	564	6	peer	peer	NOUN
brj-25043	564	7	-	-	PUNCT
brj-25043	564	8	reviewed	review	VERB
brj-25043	564	9	review	review	NOUN
brj-25043	564	10	article	article	NOUN
brj-25043	564	11	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	ADP
brj-25043	564	12	galal	galal	PROPN
brj-25043	564	13	et	et	PROPN
brj-25043	564	14	al	al	PROPN
brj-25043	564	15	.	.	PROPN
brj-25043	564	16	(	(	PUNCT
brj-25043	564	17	2025	2025	NUM
brj-25043	564	18	)	)	PUNCT
brj-25043	564	19	.	.	PUNCT
brj-25043	565	1	“	"	PUNCT
brj-25043	565	2	math	math	NOUN
brj-25043	565	3	modeling	modeling	NOUN
brj-25043	565	4	biogas	biogas	NOUN
brj-25043	565	5	production	production	NOUN
brj-25043	565	6	,	,	PUNCT
brj-25043	565	7	”	"	PUNCT
brj-25043	565	8	bioresources	bioresource	NOUN
brj-25043	565	9	20(4	20(4	NOUN
brj-25043	565	10	)	)	PUNCT
brj-25043	565	11	,	,	PUNCT
brj-25043	565	12	11237	11237	NUM
brj-25043	565	13	-	-	SYM
brj-25043	565	14	11266	11266	NUM
brj-25043	565	15	.	.	PUNCT
brj-25043	566	1	11266	11266	NUM
brj-25043	566	2	in	in	ADP
brj-25043	566	3	anaerobic	anaerobic	ADJ
brj-25043	566	4	digestion	digestion	NOUN
brj-25043	566	5	of	of	ADP
brj-25043	566	6	a	a	DET
brj-25043	566	7	full‐scale	full‐scale	NOUN
brj-25043	566	8	wastewater	wastewater	NOUN
brj-25043	566	9	treatment	treatment	NOUN
brj-25043	566	10	plant	plant	NOUN
brj-25043	566	11	using	use	VERB
brj-25043	566	12	ensembled	ensembled	ADJ
brj-25043	566	13	machine	machine	NOUN
brj-25043	566	14	learning	learning	NOUN
brj-25043	566	15	models	model	NOUN
brj-25043	566	16	,	,	PUNCT
brj-25043	566	17	”	"	PUNCT
brj-25043	566	18	water	water	NOUN
brj-25043	566	19	environment	environment	NOUN
brj-25043	566	20	research	research	PROPN
brj-25043	566	21	95(6	95(6	NUM
brj-25043	566	22	)	)	PUNCT
brj-25043	566	23	,	,	PUNCT
brj-25043	566	24	article	article	NOUN
brj-25043	566	25	e10893	e10893	VERB
brj-25043	566	26	.	.	PUNCT
brj-25043	567	1	doi	doi	NOUN
brj-25043	567	2	:	:	PUNCT
brj-25043	567	3	10.1002	10.1002	NUM
brj-25043	567	4	/	/	SYM
brj-25043	567	5	wer.10893	wer.10893	NUM
brj-25043	567	6	tian	tian	PROPN
brj-25043	567	7	,	,	PUNCT
brj-25043	567	8	y.	y.	PROPN
brj-25043	567	9	,	,	PUNCT
brj-25043	567	10	yang	yang	PROPN
brj-25043	567	11	,	,	PUNCT
brj-25043	567	12	k.	k.	PROPN
brj-25043	567	13	,	,	PUNCT
brj-25043	567	14	zheng	zheng	PROPN
brj-25043	567	15	,	,	PUNCT
brj-25043	567	16	l.	l.	PROPN
brj-25043	567	17	,	,	PUNCT
brj-25043	567	18	han	han	PROPN
brj-25043	567	19	,	,	PUNCT
brj-25043	567	20	x.	x.	PROPN
brj-25043	567	21	,	,	PUNCT
brj-25043	567	22	xu	xu	PROPN
brj-25043	567	23	,	,	PUNCT
brj-25043	567	24	y.	y.	PROPN
brj-25043	567	25	,	,	PUNCT
brj-25043	567	26	li	li	PROPN
brj-25043	567	27	,	,	PUNCT
brj-25043	567	28	y.	y.	PROPN
brj-25043	567	29	,	,	PUNCT
brj-25043	567	30	li	li	PROPN
brj-25043	567	31	,	,	PUNCT
brj-25043	567	32	s.	s.	PROPN
brj-25043	567	33	,	,	PUNCT
brj-25043	567	34	xu	xu	PROPN
brj-25043	567	35	,	,	PUNCT
brj-25043	567	36	x.	x.	PROPN
brj-25043	567	37	,	,	PUNCT
brj-25043	567	38	zhang	zhang	PROPN
brj-25043	567	39	,	,	PUNCT
brj-25043	567	40	h.	h.	PROPN
brj-25043	567	41	,	,	PUNCT
brj-25043	567	42	and	and	CCONJ
brj-25043	567	43	zhao	zhao	PROPN
brj-25043	567	44	,	,	PUNCT
brj-25043	567	45	l.	l.	PROPN
brj-25043	567	46	(	(	PUNCT
brj-25043	567	47	2020	2020	NUM
brj-25043	567	48	)	)	PUNCT
brj-25043	567	49	.	.	PUNCT
brj-25043	568	1	“	"	PUNCT
brj-25043	568	2	modelling	model	VERB
brj-25043	568	3	biogas	biogas	NOUN
brj-25043	568	4	production	production	NOUN
brj-25043	568	5	kinetics	kinetic	NOUN
brj-25043	568	6	of	of	ADP
brj-25043	568	7	various	various	ADJ
brj-25043	568	8	heavy	heavy	ADJ
brj-25043	568	9	metals	metal	NOUN
brj-25043	568	10	exposed	expose	VERB
brj-25043	568	11	anaerobic	anaerobic	NOUN
brj-25043	568	12	fermentation	fermentation	NOUN
brj-25043	568	13	process	process	NOUN
brj-25043	568	14	using	use	VERB
brj-25043	568	15	sigmoidal	sigmoidal	ADJ
brj-25043	568	16	growth	growth	NOUN
brj-25043	568	17	functions	function	NOUN
brj-25043	568	18	,	,	PUNCT
brj-25043	568	19	”	"	PUNCT
brj-25043	568	20	waste	waste	NOUN
brj-25043	568	21	and	and	CCONJ
brj-25043	568	22	biomass	biomass	NOUN
brj-25043	568	23	valorization	valorization	NOUN
brj-25043	568	24	11(9	11(9	PROPN
brj-25043	568	25	)	)	PUNCT
brj-25043	568	26	,	,	PUNCT
brj-25043	568	27	4837	4837	NUM
brj-25043	568	28	-	-	SYM
brj-25043	568	29	4848	4848	NUM
brj-25043	568	30	.	.	PUNCT
brj-25043	569	1	doi	doi	NOUN
brj-25043	569	2	:	:	PUNCT
brj-25043	569	3	10.1007	10.1007	NUM
brj-25043	569	4	/	/	SYM
brj-25043	569	5	s12649	s12649	NOUN
brj-25043	569	6	-	-	PUNCT
brj-25043	569	7	019	019	NUM
brj-25043	569	8	-	-	PUNCT
brj-25043	569	9	00810	00810	NUM
brj-25043	569	10	-	-	PUNCT
brj-25043	569	11	x	x	SYM
brj-25043	569	12	tiwari	tiwari	PROPN
brj-25043	569	13	,	,	PUNCT
brj-25043	569	14	s.	s.	PROPN
brj-25043	569	15	b.	b.	PROPN
brj-25043	569	16	,	,	PUNCT
brj-25043	569	17	dixit	dixit	PROPN
brj-25043	569	18	,	,	PUNCT
brj-25043	569	19	s.	s.	PROPN
brj-25043	569	20	,	,	PUNCT
brj-25043	569	21	tyagi	tyagi	PROPN
brj-25043	569	22	,	,	PUNCT
brj-25043	569	23	v.	v.	PROPN
brj-25043	569	24	k.	k.	PROPN
brj-25043	569	25	,	,	PUNCT
brj-25043	569	26	veksha	veksha	PROPN
brj-25043	569	27	,	,	PUNCT
brj-25043	569	28	a.	a.	PROPN
brj-25043	569	29	,	,	PUNCT
brj-25043	569	30	lim	lim	PROPN
brj-25043	569	31	,	,	PUNCT
brj-25043	569	32	t.-t	t.-t	PROPN
brj-25043	569	33	.	.	PUNCT
brj-25043	569	34	,	,	PUNCT
brj-25043	569	35	and	and	CCONJ
brj-25043	569	36	kazmi	kazmi	PROPN
brj-25043	569	37	,	,	PUNCT
brj-25043	569	38	a.	a.	NOUN
brj-25043	569	39	a.	a.	NOUN
brj-25043	569	40	(	(	PUNCT
brj-25043	569	41	2025	2025	NUM
brj-25043	569	42	)	)	PUNCT
brj-25043	569	43	.	.	PUNCT
brj-25043	570	1	“	"	PUNCT
brj-25043	570	2	comparative	comparative	ADJ
brj-25043	570	3	evaluation	evaluation	NOUN
brj-25043	570	4	of	of	ADP
brj-25043	570	5	mechanistic	mechanistic	ADJ
brj-25043	570	6	models	model	NOUN
brj-25043	570	7	for	for	ADP
brj-25043	570	8	biogas	biogas	NOUN
brj-25043	570	9	production	production	NOUN
brj-25043	570	10	in	in	ADP
brj-25043	570	11	dietenhanced	dietenhanced	ADJ
brj-25043	570	12	anaerobic	anaerobic	NOUN
brj-25043	570	13	digestion	digestion	NOUN
brj-25043	570	14	,	,	PUNCT
brj-25043	570	15	”	"	PUNCT
brj-25043	570	16	journal	journal	NOUN
brj-25043	570	17	of	of	ADP
brj-25043	570	18	environmental	environmental	ADJ
brj-25043	570	19	management	management	NOUN
brj-25043	570	20	391	391	NUM
brj-25043	570	21	,	,	PUNCT
brj-25043	570	22	article	article	NOUN
brj-25043	570	23	i	i	PROPN
brj-25043	570	24	d	d	PROPN
brj-25043	570	25	126614	126614	NUM
brj-25043	570	26	.	.	PUNCT
brj-25043	571	1	doi	doi	NOUN
brj-25043	571	2	:	:	PUNCT
brj-25043	571	3	10.1016	10.1016	NUM
brj-25043	571	4	/	/	SYM
brj-25043	571	5	j.jenvman.2025.126614	j.jenvman.2025.126614	PROPN
brj-25043	571	6	tonner	tonner	PROPN
brj-25043	571	7	,	,	PUNCT
brj-25043	571	8	p.	p.	PROPN
brj-25043	571	9	d.	d.	PROPN
brj-25043	571	10	,	,	PUNCT
brj-25043	571	11	darnell	darnell	PROPN
brj-25043	571	12	,	,	PUNCT
brj-25043	571	13	c.	c.	PROPN
brj-25043	571	14	l.	l.	PROPN
brj-25043	571	15	,	,	PUNCT
brj-25043	571	16	engelhardt	engelhardt	PROPN
brj-25043	571	17	,	,	PUNCT
brj-25043	571	18	b.	b.	PROPN
brj-25043	571	19	e.	e.	PROPN
brj-25043	571	20	,	,	PUNCT
brj-25043	571	21	and	and	CCONJ
brj-25043	571	22	schmid	schmid	PROPN
brj-25043	571	23	,	,	PUNCT
brj-25043	571	24	a.	a.	PROPN
brj-25043	571	25	k.	k.	PROPN
brj-25043	571	26	(	(	PUNCT
brj-25043	571	27	2017	2017	NUM
brj-25043	571	28	)	)	PUNCT
brj-25043	571	29	.	.	PUNCT
brj-25043	572	1	“	"	PUNCT
brj-25043	572	2	detecting	detect	VERB
brj-25043	572	3	differential	differential	ADJ
brj-25043	572	4	growth	growth	NOUN
brj-25043	572	5	of	of	ADP
brj-25043	572	6	microbial	microbial	ADJ
brj-25043	572	7	populations	population	NOUN
brj-25043	572	8	with	with	ADP
brj-25043	572	9	gaussian	gaussian	ADJ
brj-25043	572	10	process	process	NOUN
brj-25043	572	11	regression	regression	NOUN
brj-25043	572	12	,	,	PUNCT
brj-25043	572	13	”	"	PUNCT
brj-25043	572	14	genome	genome	NOUN
brj-25043	572	15	research	research	NOUN
brj-25043	572	16	27(2	27(2	NOUN
brj-25043	572	17	)	)	PUNCT
brj-25043	572	18	,	,	PUNCT
brj-25043	572	19	320	320	NUM
brj-25043	572	20	-	-	SYM
brj-25043	572	21	333	333	NUM
brj-25043	572	22	.	.	PUNCT
brj-25043	573	1	doi	doi	NOUN
brj-25043	573	2	:	:	PUNCT
brj-25043	573	3	10.1101	10.1101	NUM
brj-25043	573	4	/	/	SYM
brj-25043	573	5	gr.210286.116	gr.210286.116	NOUN
brj-25043	573	6	tufaner	tufaner	NOUN
brj-25043	573	7	,	,	PUNCT
brj-25043	573	8	f.	f.	PROPN
brj-25043	573	9	,	,	PUNCT
brj-25043	573	10	dalkılıç	dalkılıç	PROPN
brj-25043	573	11	,	,	PUNCT
brj-25043	573	12	k.	k.	PROPN
brj-25043	573	13	,	,	PUNCT
brj-25043	573	14	and	and	CCONJ
brj-25043	573	15	uğurlu	uğurlu	NOUN
brj-25043	573	16	,	,	PUNCT
brj-25043	573	17	a.	a.	NOUN
brj-25043	573	18	(	(	PUNCT
brj-25043	573	19	2025	2025	NUM
brj-25043	573	20	)	)	PUNCT
brj-25043	573	21	.	.	PUNCT
brj-25043	574	1	“	"	PUNCT
brj-25043	574	2	artificial	artificial	ADJ
brj-25043	574	3	intelligence	intelligence	NOUN
brj-25043	574	4	-	-	PUNCT
brj-25043	574	5	based	base	VERB
brj-25043	574	6	modeling	modeling	NOUN
brj-25043	574	7	of	of	ADP
brj-25043	574	8	biogas	biogas	NOUN
brj-25043	574	9	production	production	NOUN
brj-25043	574	10	in	in	ADP
brj-25043	574	11	a	a	DET
brj-25043	574	12	combined	combine	VERB
brj-25043	574	13	microbial	microbial	ADJ
brj-25043	574	14	electrolysis	electrolysis	NOUN
brj-25043	574	15	cell	cell	NOUN
brj-25043	574	16	-	-	PUNCT
brj-25043	574	17	anaerobic	anaerobic	NOUN
brj-25043	574	18	digestion	digestion	NOUN
brj-25043	574	19	system	system	NOUN
brj-25043	574	20	using	use	VERB
brj-25043	574	21	artificial	artificial	ADJ
brj-25043	574	22	neural	neural	ADJ
brj-25043	574	23	networks	network	NOUN
brj-25043	574	24	and	and	CCONJ
brj-25043	574	25	adaptive	adaptive	ADJ
brj-25043	574	26	neuro	neuro	NOUN
brj-25043	574	27	-	-	PUNCT
brj-25043	574	28	fuzzy	fuzzy	ADJ
brj-25043	574	29	inference	inference	NOUN
brj-25043	574	30	system	system	NOUN
brj-25043	574	31	,	,	PUNCT
brj-25043	574	32	”	"	PUNCT
brj-25043	574	33	environmental	environmental	ADJ
brj-25043	574	34	science	science	NOUN
brj-25043	574	35	and	and	CCONJ
brj-25043	574	36	pollution	pollution	NOUN
brj-25043	574	37	research	research	NOUN
brj-25043	574	38	32	32	NUM
brj-25043	574	39	,	,	PUNCT
brj-25043	574	40	12524	12524	NUM
brj-25043	574	41	-	-	SYM
brj-25043	574	42	12546	12546	NUM
brj-25043	574	43	.	.	PUNCT
brj-25043	575	1	doi	doi	NOUN
brj-25043	575	2	:	:	PUNCT
brj-25043	575	3	10.1007	10.1007	NUM
brj-25043	575	4	/	/	SYM
brj-25043	575	5	s11356	s11356	NOUN
brj-25043	575	6	-	-	PUNCT
brj-25043	575	7	025	025	NUM
brj-25043	575	8	-	-	PUNCT
brj-25043	575	9	36467	36467	NUM
brj-25043	575	10	-	-	SYM
brj-25043	575	11	4	4	NUM
brj-25043	575	12	yildirim	yildirim	NOUN
brj-25043	575	13	,	,	PUNCT
brj-25043	575	14	o.	o.	PROPN
brj-25043	575	15	,	,	PUNCT
brj-25043	575	16	and	and	CCONJ
brj-25043	575	17	ozkaya	ozkaya	PROPN
brj-25043	575	18	,	,	PUNCT
brj-25043	575	19	b.	b.	PROPN
brj-25043	575	20	(	(	PUNCT
brj-25043	575	21	2023	2023	NUM
brj-25043	575	22	)	)	PUNCT
brj-25043	575	23	.	.	PUNCT
brj-25043	576	1	“	"	PUNCT
brj-25043	576	2	prediction	prediction	NOUN
brj-25043	576	3	of	of	ADP
brj-25043	576	4	biogas	biogas	NOUN
brj-25043	576	5	production	production	NOUN
brj-25043	576	6	of	of	ADP
brj-25043	576	7	industrial	industrial	ADJ
brj-25043	576	8	scale	scale	NOUN
brj-25043	576	9	anaerobic	anaerobic	NOUN
brj-25043	576	10	digestion	digestion	NOUN
brj-25043	576	11	plant	plant	NOUN
brj-25043	576	12	by	by	ADP
brj-25043	576	13	machine	machine	NOUN
brj-25043	576	14	learning	learning	NOUN
brj-25043	576	15	algorithms	algorithm	NOUN
brj-25043	576	16	,	,	PUNCT
brj-25043	576	17	”	"	PUNCT
brj-25043	576	18	chemosphere	chemosphere	PROPN
brj-25043	576	19	335	335	NUM
brj-25043	576	20	,	,	PUNCT
brj-25043	576	21	article	article	NOUN
brj-25043	576	22	138976	138976	NUM
brj-25043	576	23	.	.	PUNCT
brj-25043	577	1	doi	doi	NOUN
brj-25043	577	2	:	:	PUNCT
brj-25043	577	3	10.1016	10.1016	NUM
brj-25043	577	4	/	/	SYM
brj-25043	577	5	j.chemosphere.2023.138976	j.chemosphere.2023.138976	PROPN
brj-25043	577	6	yusuf	yusuf	PROPN
brj-25043	577	7	,	,	PUNCT
brj-25043	577	8	m.	m.	NOUN
brj-25043	577	9	o.	o.	PROPN
brj-25043	577	10	l.	l.	PROPN
brj-25043	577	11	,	,	PUNCT
brj-25043	577	12	debora	debora	PROPN
brj-25043	577	13	,	,	PUNCT
brj-25043	577	14	a.	a.	NOUN
brj-25043	577	15	,	,	PUNCT
brj-25043	577	16	and	and	CCONJ
brj-25043	577	17	ogheneruona	ogheneruona	PROPN
brj-25043	577	18	,	,	PUNCT
brj-25043	577	19	d.	d.	PROPN
brj-25043	577	20	e.	e.	PROPN
brj-25043	577	21	(	(	PUNCT
brj-25043	577	22	2011	2011	NUM
brj-25043	577	23	)	)	PUNCT
brj-25043	577	24	.	.	PUNCT
brj-25043	578	1	“	"	PUNCT
brj-25043	578	2	ambient	ambient	ADJ
brj-25043	578	3	temperature	temperature	NOUN
brj-25043	578	4	kinetic	kinetic	ADJ
brj-25043	578	5	assessment	assessment	NOUN
brj-25043	578	6	of	of	ADP
brj-25043	578	7	biogas	biogas	NOUN
brj-25043	578	8	production	production	NOUN
brj-25043	578	9	from	from	ADP
brj-25043	578	10	co	co	NOUN
brj-25043	578	11	-	-	NOUN
brj-25043	578	12	digestion	digestion	NOUN
brj-25043	578	13	of	of	ADP
brj-25043	578	14	horse	horse	NOUN
brj-25043	578	15	and	and	CCONJ
brj-25043	578	16	cow	cow	NOUN
brj-25043	578	17	dung	dung	NOUN
brj-25043	578	18	,	,	PUNCT
brj-25043	578	19	”	"	PUNCT
brj-25043	578	20	research	research	NOUN
brj-25043	578	21	in	in	ADP
brj-25043	578	22	agricultural	agricultural	ADJ
brj-25043	578	23	engineering	engineering	NOUN
brj-25043	578	24	57(3	57(3	NUM
brj-25043	578	25	)	)	PUNCT
brj-25043	578	26	,	,	PUNCT
brj-25043	578	27	97	97	NUM
brj-25043	578	28	-	-	SYM
brj-25043	578	29	104	104	NUM
brj-25043	578	30	.	.	PUNCT
brj-25043	579	1	doi	doi	NOUN
brj-25043	579	2	:	:	PUNCT
brj-25043	579	3	10.17221/25/2010	10.17221/25/2010	NUM
brj-25043	579	4	-	-	PUNCT
brj-25043	579	5	rae	rae	PROPN
brj-25043	579	6	zhu	zhu	PROPN
brj-25043	579	7	,	,	PUNCT
brj-25043	579	8	t.	t.	PROPN
brj-25043	579	9	,	,	PUNCT
brj-25043	579	10	zhou	zhou	PROPN
brj-25043	579	11	,	,	PUNCT
brj-25043	579	12	y.	y.	PROPN
brj-25043	579	13	,	,	PUNCT
brj-25043	579	14	chen	chen	PROPN
brj-25043	579	15	,	,	PUNCT
brj-25043	579	16	j.	j.	PROPN
brj-25043	579	17	m.	m.	PROPN
brj-25043	579	18	,	,	PUNCT
brj-25043	579	19	ju	ju	PROPN
brj-25043	579	20	,	,	PUNCT
brj-25043	579	21	w.	w.	PROPN
brj-25043	579	22	,	,	PUNCT
brj-25043	579	23	yan	yan	PROPN
brj-25043	579	24	,	,	PUNCT
brj-25043	579	25	r.	r.	PROPN
brj-25043	579	26	,	,	PUNCT
brj-25043	579	27	xie	xie	PROPN
brj-25043	579	28	,	,	PUNCT
brj-25043	579	29	r.	r.	PROPN
brj-25043	579	30	,	,	PUNCT
brj-25043	579	31	and	and	CCONJ
brj-25043	579	32	mao	mao	PROPN
brj-25043	579	33	,	,	PUNCT
brj-25043	579	34	y.	y.	PROPN
brj-25043	579	35	(	(	PUNCT
brj-25043	579	36	2025	2025	NUM
brj-25043	579	37	)	)	PUNCT
brj-25043	579	38	.	.	PUNCT
brj-25043	580	1	“	"	PUNCT
brj-25043	580	2	divergent	divergent	ADJ
brj-25043	580	3	responses	response	NOUN
brj-25043	580	4	of	of	ADP
brj-25043	580	5	ch4	ch4	NOUN
brj-25043	580	6	emissions	emission	NOUN
brj-25043	580	7	and	and	CCONJ
brj-25043	580	8	uptake	uptake	ADJ
brj-25043	580	9	to	to	ADP
brj-25043	580	10	global	global	ADJ
brj-25043	580	11	change	change	NOUN
brj-25043	580	12	drivers	driver	NOUN
brj-25043	580	13	,	,	PUNCT
brj-25043	580	14	”	"	PUNCT
brj-25043	580	15	global	global	ADJ
brj-25043	580	16	biogeochemical	biogeochemical	ADJ
brj-25043	580	17	cycles	cycle	NOUN
brj-25043	580	18	39(3	39(3	NUM
brj-25043	580	19	)	)	PUNCT
brj-25043	580	20	,	,	PUNCT
brj-25043	580	21	article	article	NOUN
brj-25043	580	22	e2024gb008183	e2024gb008183	PROPN
brj-25043	580	23	.	.	PUNCT
brj-25043	581	1	doi	doi	PROPN
brj-25043	581	2	:	:	PUNCT
brj-25043	581	3	10.1029/2024gb008183	10.1029/2024gb008183	NUM
brj-25043	581	4	zou	zou	PROPN
brj-25043	581	5	,	,	PUNCT
brj-25043	581	6	j.	j.	PROPN
brj-25043	581	7	,	,	PUNCT
brj-25043	581	8	lü	lü	PROPN
brj-25043	581	9	,	,	PUNCT
brj-25043	581	10	f.	f.	PROPN
brj-25043	581	11	,	,	PUNCT
brj-25043	581	12	chen	chen	PROPN
brj-25043	581	13	,	,	PUNCT
brj-25043	581	14	l.	l.	PROPN
brj-25043	581	15	,	,	PUNCT
brj-25043	581	16	zhang	zhang	PROPN
brj-25043	581	17	,	,	PUNCT
brj-25043	581	18	h.	h.	PROPN
brj-25043	581	19	,	,	PUNCT
brj-25043	581	20	and	and	CCONJ
brj-25043	581	21	he	he	PRON
brj-25043	581	22	,	,	PUNCT
brj-25043	581	23	p.	p.	NOUN
brj-25043	581	24	(	(	PUNCT
brj-25043	581	25	2024	2024	NUM
brj-25043	581	26	)	)	PUNCT
brj-25043	581	27	.	.	PUNCT
brj-25043	582	1	“	"	PUNCT
brj-25043	582	2	machine	machine	NOUN
brj-25043	582	3	learning	learning	NOUN
brj-25043	582	4	for	for	ADP
brj-25043	582	5	enhancing	enhance	VERB
brj-25043	582	6	prediction	prediction	NOUN
brj-25043	582	7	of	of	ADP
brj-25043	582	8	biogas	biogas	NOUN
brj-25043	582	9	production	production	NOUN
brj-25043	582	10	and	and	CCONJ
brj-25043	582	11	building	build	VERB
brj-25043	582	12	a	a	DET
brj-25043	582	13	vfa	vfa	PROPN
brj-25043	582	14	/	/	SYM
brj-25043	582	15	alk	alk	VERB
brj-25043	582	16	soft	soft	ADJ
brj-25043	582	17	sensor	sensor	NOUN
brj-25043	582	18	in	in	ADP
brj-25043	582	19	full	full	ADJ
brj-25043	582	20	-	-	PUNCT
brj-25043	582	21	scale	scale	NOUN
brj-25043	582	22	dry	dry	ADJ
brj-25043	582	23	anaerobic	anaerobic	NOUN
brj-25043	582	24	digestion	digestion	NOUN
brj-25043	582	25	of	of	ADP
brj-25043	582	26	kitchen	kitchen	NOUN
brj-25043	582	27	food	food	PROPN
brj-25043	582	28	waste	waste	NOUN
brj-25043	582	29	,	,	PUNCT
brj-25043	582	30	”	"	PUNCT
brj-25043	582	31	journal	journal	NOUN
brj-25043	582	32	of	of	ADP
brj-25043	582	33	environmental	environmental	ADJ
brj-25043	582	34	management	management	NOUN
brj-25043	582	35	371	371	NUM
brj-25043	582	36	,	,	PUNCT
brj-25043	582	37	article	article	NOUN
brj-25043	582	38	123190	123190	NUM
brj-25043	582	39	.	.	PUNCT
brj-25043	583	1	doi	doi	NOUN
brj-25043	583	2	:	:	PUNCT
brj-25043	583	3	10.1016	10.1016	NUM
brj-25043	583	4	/	/	SYM
brj-25043	583	5	j.jenvman.2024.123190	j.jenvman.2024.123190	PROPN
brj-25043	583	6	zwietering	zwietering	NOUN
brj-25043	583	7	,	,	PUNCT
brj-25043	583	8	m.	m.	PROPN
brj-25043	583	9	h.	h.	PROPN
brj-25043	583	10	,	,	PUNCT
brj-25043	583	11	jongenburger	jongenburger	PROPN
brj-25043	583	12	,	,	PUNCT
brj-25043	583	13	i.	i.	PROPN
brj-25043	583	14	,	,	PUNCT
brj-25043	583	15	rombouts	rombout	NOUN
brj-25043	583	16	,	,	PUNCT
brj-25043	583	17	f.	f.	PROPN
brj-25043	583	18	m.	m.	PROPN
brj-25043	583	19	,	,	PUNCT
brj-25043	583	20	and	and	CCONJ
brj-25043	583	21	van’t	van’t	NUM
brj-25043	583	22	riet	riet	NOUN
brj-25043	583	23	,	,	PUNCT
brj-25043	583	24	k.	k.	PROPN
brj-25043	583	25	(	(	PUNCT
brj-25043	583	26	1990	1990	NUM
brj-25043	583	27	)	)	PUNCT
brj-25043	583	28	.	.	PUNCT
brj-25043	584	1	“	"	PUNCT
brj-25043	584	2	modeling	modeling	NOUN
brj-25043	584	3	of	of	ADP
brj-25043	584	4	the	the	DET
brj-25043	584	5	bacterial	bacterial	ADJ
brj-25043	584	6	growth	growth	NOUN
brj-25043	584	7	curve	curve	NOUN
brj-25043	584	8	,	,	PUNCT
brj-25043	584	9	”	"	PUNCT
brj-25043	584	10	applied	apply	VERB
brj-25043	584	11	and	and	CCONJ
brj-25043	584	12	environmental	environmental	ADJ
brj-25043	584	13	microbiology	microbiology	NOUN
brj-25043	584	14	56(6	56(6	PROPN
brj-25043	584	15	)	)	PUNCT
brj-25043	584	16	,	,	PUNCT
brj-25043	584	17	1875	1875	NUM
brj-25043	584	18	-	-	SYM
brj-25043	584	19	1881	1881	NUM
brj-25043	584	20	.	.	PUNCT
brj-25043	585	1	doi	doi	NOUN
brj-25043	585	2	:	:	PUNCT
brj-25043	585	3	10.1128	10.1128	NUM
brj-25043	585	4	/	/	SYM
brj-25043	585	5	aem.56.6.1875	aem.56.6.1875	PROPN
brj-25043	585	6	-	-	PUNCT
brj-25043	585	7	1881.1990	1881.1990	NUM
brj-25043	585	8	article	article	NOUN
brj-25043	585	9	submitted	submit	VERB
brj-25043	585	10	:	:	PUNCT
brj-25043	585	11	august	august	PROPN
brj-25043	585	12	5	5	NUM
brj-25043	585	13	,	,	PUNCT
brj-25043	585	14	2025	2025	NUM
brj-25043	585	15	;	;	PUNCT
brj-25043	585	16	peer	peer	NOUN
brj-25043	585	17	review	review	NOUN
brj-25043	585	18	completed	complete	VERB
brj-25043	585	19	:	:	PUNCT
brj-25043	585	20	september	september	PROPN
brj-25043	585	21	5	5	NUM
brj-25043	585	22	,	,	PUNCT
brj-25043	585	23	2025	2025	NUM
brj-25043	585	24	;	;	PUNCT
brj-25043	585	25	revised	revise	VERB
brj-25043	585	26	version	version	NOUN
brj-25043	585	27	received	receive	VERB
brj-25043	585	28	:	:	PUNCT
brj-25043	585	29	september	september	PROPN
brj-25043	585	30	14	14	NUM
brj-25043	585	31	,	,	PUNCT
brj-25043	585	32	2025	2025	NUM
brj-25043	585	33	;	;	PUNCT
brj-25043	585	34	accepted	accept	VERB
brj-25043	585	35	:	:	PUNCT
brj-25043	585	36	september	september	PROPN
brj-25043	585	37	15	15	NUM
brj-25043	585	38	,	,	PUNCT
brj-25043	585	39	2025	2025	NUM
brj-25043	585	40	;	;	PUNCT
brj-25043	585	41	published	publish	VERB
brj-25043	585	42	:	:	PUNCT
brj-25043	585	43	september	september	PROPN
brj-25043	585	44	17	17	NUM
brj-25043	585	45	,	,	PUNCT
brj-25043	585	46	2025	2025	NUM
brj-25043	585	47	.	.	PUNCT
brj-25043	586	1	doi	doi	NOUN
brj-25043	586	2	:	:	PUNCT
brj-25043	586	3	10.15376	10.15376	NUM
brj-25043	586	4	/	/	SYM
brj-25043	586	5	biores.20.4.galal	biores.20.4.galal	PROPN