id	sid	tid	token	lemma	pos
brj-23786	1	1	peer	peer	NOUN
brj-23786	1	2	-	-	PUNCT
brj-23786	1	3	review	review	NOUN
brj-23786	1	4	article	article	NOUN
brj-23786	1	5	peer	peer	NOUN
brj-23786	1	6	-	-	PUNCT
brj-23786	1	7	reviewed	review	VERB
brj-23786	1	8	article	article	NOUN
brj-23786	1	9	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	1	10	xu	xu	PROPN
brj-23786	1	11	et	et	PROPN
brj-23786	1	12	al	al	PROPN
brj-23786	1	13	.	.	PROPN
brj-23786	2	1	(	(	PUNCT
brj-23786	2	2	2024	2024	NUM
brj-23786	2	3	)	)	PUNCT
brj-23786	2	4	.	.	PUNCT
brj-23786	3	1	“	"	PUNCT
brj-23786	3	2	pyrolysis	pyrolysis	NOUN
brj-23786	3	3	kinetics	kinetic	NOUN
brj-23786	3	4	with	with	ADP
brj-23786	3	5	ann	ann	PROPN
brj-23786	3	6	,	,	PUNCT
brj-23786	3	7	”	"	PUNCT
brj-23786	3	8	bioresources	bioresource	NOUN
brj-23786	3	9	19(4	19(4	NUM
brj-23786	3	10	)	)	PUNCT
brj-23786	3	11	,	,	PUNCT
brj-23786	3	12	7513	7513	NUM
brj-23786	3	13	-	-	SYM
brj-23786	3	14	7529	7529	NUM
brj-23786	3	15	.	.	PUNCT
brj-23786	4	1	7513	7513	NUM
brj-23786	4	2	coupling	couple	VERB
brj-23786	4	3	kinetic	kinetic	ADJ
brj-23786	4	4	modeling	modeling	NOUN
brj-23786	4	5	with	with	ADP
brj-23786	4	6	artificial	artificial	ADJ
brj-23786	4	7	neural	neural	ADJ
brj-23786	4	8	networks	network	NOUN
brj-23786	4	9	to	to	PART
brj-23786	4	10	predict	predict	VERB
brj-23786	4	11	the	the	DET
brj-23786	4	12	kinetic	kinetic	ADJ
brj-23786	4	13	parameters	parameter	NOUN
brj-23786	4	14	of	of	ADP
brj-23786	4	15	pine	pine	NOUN
brj-23786	4	16	needle	needle	NOUN
brj-23786	4	17	pyrolysis	pyrolysis	NOUN
brj-23786	4	18	langui	langui	NOUN
brj-23786	4	19	xu	xu	PROPN
brj-23786	4	20	,	,	PUNCT
brj-23786	4	21	a	a	DET
brj-23786	4	22	lin	lin	PROPN
brj-23786	4	23	zhang	zhang	PROPN
brj-23786	4	24	,	,	PUNCT
brj-23786	4	25	a	a	DET
brj-23786	4	26	xiangjun	xiangjun	X
brj-23786	4	27	he	he	PRON
brj-23786	4	28	,	,	PUNCT
brj-23786	4	29	a	a	DET
brj-23786	4	30	wenbin	wenbin	NOUN
brj-23786	4	31	he	he	PRON
brj-23786	4	32	,	,	PUNCT
brj-23786	4	33	b	b	PROPN
brj-23786	4	34	ziyong	ziyong	PROPN
brj-23786	4	35	wang	wang	PROPN
brj-23786	4	36	,	,	PUNCT
brj-23786	4	37	c	c	PROPN
brj-23786	4	38	weihua	weihua	PROPN
brj-23786	4	39	niu	niu	PROPN
brj-23786	4	40	,	,	PUNCT
brj-23786	4	41	d	d	PROPN
brj-23786	4	42	dong	dong	PROPN
brj-23786	4	43	wei	wei	PROPN
brj-23786	4	44	,	,	PUNCT
brj-23786	4	45	d	d	PROPN
brj-23786	4	46	yi	yi	PROPN
brj-23786	4	47	ran	run	VERB
brj-23786	4	48	,	,	PUNCT
brj-23786	4	49	e	e	PROPN
brj-23786	4	50	wendan	wendan	PROPN
brj-23786	4	51	wu	wu	PROPN
brj-23786	4	52	,	,	PUNCT
brj-23786	4	53	f	f	PROPN
brj-23786	4	54	mingjun	mingjun	PROPN
brj-23786	4	55	cheng	cheng	PROPN
brj-23786	4	56	,	,	PUNCT
brj-23786	4	57	f	f	PROPN
brj-23786	4	58	jundou	jundou	PROPN
brj-23786	4	59	liu	liu	PROPN
brj-23786	4	60	,	,	PUNCT
brj-23786	4	61	g	g	PROPN
brj-23786	4	62	and	and	CCONJ
brj-23786	4	63	ruyi	ruyi	PROPN
brj-23786	5	1	huang	huang	PROPN
brj-23786	5	2	a	a	PROPN
brj-23786	5	3	,	,	PUNCT
brj-23786	5	4	e	e	NOUN
brj-23786	5	5	,	,	PUNCT
brj-23786	5	6	*	*	PUNCT
brj-23786	5	7	the	the	DET
brj-23786	5	8	pyrolysis	pyrolysis	NOUN
brj-23786	5	9	behavior	behavior	NOUN
brj-23786	5	10	of	of	ADP
brj-23786	5	11	biomass	biomass	NOUN
brj-23786	5	12	is	be	AUX
brj-23786	5	13	critical	critical	ADJ
brj-23786	5	14	for	for	ADP
brj-23786	5	15	industrial	industrial	ADJ
brj-23786	5	16	process	process	NOUN
brj-23786	5	17	design	design	NOUN
brj-23786	5	18	,	,	PUNCT
brj-23786	5	19	yet	yet	CCONJ
brj-23786	5	20	the	the	DET
brj-23786	5	21	complexity	complexity	NOUN
brj-23786	5	22	of	of	ADP
brj-23786	5	23	pyrolysis	pyrolysis	NOUN
brj-23786	5	24	models	model	NOUN
brj-23786	5	25	makes	make	VERB
brj-23786	5	26	this	this	DET
brj-23786	5	27	task	task	NOUN
brj-23786	5	28	challenging	challenging	ADJ
brj-23786	5	29	.	.	PUNCT
brj-23786	6	1	this	this	DET
brj-23786	6	2	paper	paper	NOUN
brj-23786	6	3	introduces	introduce	VERB
brj-23786	6	4	an	an	DET
brj-23786	6	5	innovative	innovative	ADJ
brj-23786	6	6	hybrid	hybrid	NOUN
brj-23786	6	7	model	model	NOUN
brj-23786	6	8	to	to	PART
brj-23786	6	9	quantify	quantify	VERB
brj-23786	6	10	the	the	DET
brj-23786	6	11	pyrolysis	pyrolysis	NOUN
brj-23786	6	12	potential	potential	NOUN
brj-23786	6	13	of	of	ADP
brj-23786	6	14	pine	pine	ADJ
brj-23786	6	15	needles	needle	NOUN
brj-23786	6	16	,	,	PUNCT
brj-23786	6	17	predicting	predict	VERB
brj-23786	6	18	the	the	DET
brj-23786	6	19	entire	entire	ADJ
brj-23786	6	20	process	process	NOUN
brj-23786	6	21	of	of	ADP
brj-23786	6	22	their	their	PRON
brj-23786	6	23	pyrolysis	pyrolysis	NOUN
brj-23786	6	24	behavior	behavior	NOUN
brj-23786	6	25	.	.	PUNCT
brj-23786	7	1	through	through	ADP
brj-23786	7	2	experimental	experimental	ADJ
brj-23786	7	3	analyses	analysis	NOUN
brj-23786	7	4	and	and	CCONJ
brj-23786	7	5	kinetic	kinetic	ADJ
brj-23786	7	6	parameter	parameter	NOUN
brj-23786	7	7	calculations	calculation	NOUN
brj-23786	7	8	of	of	ADP
brj-23786	7	9	pine	pine	ADJ
brj-23786	7	10	needle	needle	NOUN
brj-23786	7	11	pyrolysis	pyrolysis	NOUN
brj-23786	7	12	,	,	PUNCT
brj-23786	7	13	the	the	DET
brj-23786	7	14	study	study	NOUN
brj-23786	7	15	employs	employ	VERB
brj-23786	7	16	a	a	DET
brj-23786	7	17	kinetic	kinetic	ADJ
brj-23786	7	18	model	model	NOUN
brj-23786	7	19	with	with	ADP
brj-23786	7	20	a	a	DET
brj-23786	7	21	chemical	chemical	NOUN
brj-23786	7	22	reaction	reaction	NOUN
brj-23786	7	23	mechanism	mechanism	NOUN
brj-23786	7	24	.	.	PUNCT
brj-23786	8	1	additionally	additionally	ADV
brj-23786	8	2	,	,	PUNCT
brj-23786	8	3	it	it	PRON
brj-23786	8	4	introduces	introduce	VERB
brj-23786	8	5	an	an	DET
brj-23786	8	6	improved	improved	ADJ
brj-23786	8	7	dung	dung	NOUN
brj-23786	8	8	beetle	beetle	NOUN
brj-23786	8	9	optimization	optimization	NOUN
brj-23786	8	10	algorithm	algorithm	NOUN
brj-23786	8	11	to	to	PART
brj-23786	8	12	accurately	accurately	ADV
brj-23786	8	13	capture	capture	VERB
brj-23786	8	14	the	the	DET
brj-23786	8	15	primary	primary	ADJ
brj-23786	8	16	trends	trend	NOUN
brj-23786	8	17	in	in	ADP
brj-23786	8	18	pine	pine	ADJ
brj-23786	8	19	needle	needle	NOUN
brj-23786	8	20	pyrolysis	pyrolysis	NOUN
brj-23786	8	21	.	.	PUNCT
brj-23786	9	1	the	the	DET
brj-23786	9	2	developed	develop	VERB
brj-23786	9	3	artificial	artificial	ADJ
brj-23786	9	4	neural	neural	ADJ
brj-23786	9	5	network	network	NOUN
brj-23786	9	6	model	model	NOUN
brj-23786	9	7	incorporates	incorporate	VERB
brj-23786	9	8	meta	meta	ADJ
brj-23786	9	9	-	-	PUNCT
brj-23786	9	10	heuristic	heuristic	ADJ
brj-23786	9	11	algorithms	algorithm	NOUN
brj-23786	9	12	to	to	PART
brj-23786	9	13	address	address	VERB
brj-23786	9	14	process	process	NOUN
brj-23786	9	15	error	error	NOUN
brj-23786	9	16	factors	factor	NOUN
brj-23786	9	17	.	.	PUNCT
brj-23786	10	1	validation	validation	NOUN
brj-23786	10	2	is	be	AUX
brj-23786	10	3	based	base	VERB
brj-23786	10	4	on	on	ADP
brj-23786	10	5	experimental	experimental	ADJ
brj-23786	10	6	data	datum	NOUN
brj-23786	10	7	from	from	ADP
brj-23786	10	8	tg	tg	PROPN
brj-23786	10	9	at	at	ADP
brj-23786	10	10	three	three	NUM
brj-23786	10	11	different	different	ADJ
brj-23786	10	12	heating	heating	NOUN
brj-23786	10	13	rates	rate	NOUN
brj-23786	10	14	.	.	PUNCT
brj-23786	11	1	the	the	DET
brj-23786	11	2	results	result	NOUN
brj-23786	11	3	demonstrate	demonstrate	VERB
brj-23786	11	4	that	that	SCONJ
brj-23786	11	5	the	the	DET
brj-23786	11	6	hybrid	hybrid	NOUN
brj-23786	11	7	model	model	NOUN
brj-23786	11	8	exhibits	exhibit	VERB
brj-23786	11	9	strong	strong	ADJ
brj-23786	11	10	predictive	predictive	ADJ
brj-23786	11	11	performance	performance	NOUN
brj-23786	11	12	compared	compare	VERB
brj-23786	11	13	to	to	ADP
brj-23786	11	14	the	the	DET
brj-23786	11	15	standalone	standalone	ADJ
brj-23786	11	16	model	model	NOUN
brj-23786	11	17	,	,	PUNCT
brj-23786	11	18	with	with	ADP
brj-23786	11	19	coefficients	coefficient	NOUN
brj-23786	11	20	of	of	ADP
brj-23786	11	21	determination	determination	NOUN
brj-23786	11	22	(	(	PUNCT
brj-23786	11	23	r²	r²	NOUN
brj-23786	11	24	)	)	PUNCT
brj-23786	11	25	of	of	ADP
brj-23786	11	26	0.9999	0.9999	NUM
brj-23786	11	27	and	and	CCONJ
brj-23786	11	28	0.999	0.999	NUM
brj-23786	11	29	for	for	ADP
brj-23786	11	30	predicting	predict	VERB
brj-23786	11	31	the	the	DET
brj-23786	11	32	conversion	conversion	NOUN
brj-23786	11	33	degree	degree	NOUN
brj-23786	11	34	and	and	CCONJ
brj-23786	11	35	conversion	conversion	NOUN
brj-23786	11	36	rate	rate	NOUN
brj-23786	11	37	of	of	ADP
brj-23786	11	38	untrained	untrained	ADJ
brj-23786	11	39	data	datum	NOUN
brj-23786	11	40	,	,	PUNCT
brj-23786	11	41	respectively	respectively	ADV
brj-23786	11	42	.	.	PUNCT
brj-23786	12	1	additionally	additionally	ADV
brj-23786	12	2	,	,	PUNCT
brj-23786	12	3	the	the	DET
brj-23786	12	4	standard	standard	ADJ
brj-23786	12	5	errors	error	NOUN
brj-23786	12	6	of	of	ADP
brj-23786	12	7	prediction	prediction	NOUN
brj-23786	12	8	(	(	PUNCT
brj-23786	12	9	sep	sep	PROPN
brj-23786	12	10	)	)	PUNCT
brj-23786	12	11	are	be	AUX
brj-23786	12	12	0.249	0.249	NUM
brj-23786	12	13	%	%	NOUN
brj-23786	12	14	and	and	CCONJ
brj-23786	12	15	0.449	0.449	NUM
brj-23786	12	16	%	%	NOUN
brj-23786	12	17	for	for	ADP
brj-23786	12	18	predicting	predict	VERB
brj-23786	12	19	the	the	DET
brj-23786	12	20	conversion	conversion	NOUN
brj-23786	12	21	degree	degree	NOUN
brj-23786	12	22	and	and	CCONJ
brj-23786	12	23	conversion	conversion	NOUN
brj-23786	12	24	rate	rate	NOUN
brj-23786	12	25	of	of	ADP
brj-23786	12	26	untrained	untrained	ADJ
brj-23786	12	27	data	datum	NOUN
brj-23786	12	28	,	,	PUNCT
brj-23786	12	29	respectively	respectively	ADV
brj-23786	12	30	.	.	PUNCT
brj-23786	13	1	doi	doi	NOUN
brj-23786	13	2	:	:	PUNCT
brj-23786	13	3	10.15376	10.15376	NUM
brj-23786	13	4	/	/	SYM
brj-23786	13	5	biores.19.4.7513	biores.19.4.7513	NOUN
brj-23786	13	6	-	-	PUNCT
brj-23786	13	7	7529	7529	NUM
brj-23786	13	8	keywords	keyword	NOUN
brj-23786	13	9	:	:	PUNCT
brj-23786	13	10	pine	pine	ADJ
brj-23786	13	11	needle	needle	NOUN
brj-23786	13	12	pyrolysis	pyrolysis	NOUN
brj-23786	13	13	;	;	PUNCT
brj-23786	13	14	kinetic	kinetic	ADJ
brj-23786	13	15	model	model	NOUN
brj-23786	13	16	;	;	PUNCT
brj-23786	13	17	artificial	artificial	ADJ
brj-23786	13	18	neural	neural	ADJ
brj-23786	13	19	networks	network	NOUN
brj-23786	13	20	;	;	PUNCT
brj-23786	13	21	prediction	prediction	NOUN
brj-23786	13	22	contact	contact	NOUN
brj-23786	13	23	information	information	NOUN
brj-23786	13	24	:	:	PUNCT
brj-23786	13	25	a	a	X
brj-23786	13	26	:	:	PUNCT
brj-23786	13	27	school	school	NOUN
brj-23786	13	28	of	of	ADP
brj-23786	13	29	mechanical	mechanical	ADJ
brj-23786	13	30	engineering	engineering	NOUN
brj-23786	13	31	,	,	PUNCT
brj-23786	13	32	north	north	PROPN
brj-23786	13	33	china	china	PROPN
brj-23786	13	34	university	university	PROPN
brj-23786	13	35	of	of	ADP
brj-23786	13	36	water	water	NOUN
brj-23786	13	37	resources	resource	NOUN
brj-23786	13	38	and	and	CCONJ
brj-23786	13	39	electric	electric	ADJ
brj-23786	13	40	power	power	NOUN
brj-23786	13	41	,	,	PUNCT
brj-23786	13	42	zhengzhou	zhengzhou	PROPN
brj-23786	13	43	450011	450011	NUM
brj-23786	13	44	,	,	PUNCT
brj-23786	13	45	china	china	PROPN
brj-23786	13	46	;	;	PUNCT
brj-23786	13	47	b	b	X
brj-23786	13	48	:	:	PUNCT
brj-23786	13	49	school	school	NOUN
brj-23786	13	50	of	of	ADP
brj-23786	13	51	mechanical	mechanical	ADJ
brj-23786	13	52	engineering	engineering	NOUN
brj-23786	13	53	,	,	PUNCT
brj-23786	13	54	zhengzhou	zhengzhou	PROPN
brj-23786	13	55	university	university	PROPN
brj-23786	13	56	of	of	ADP
brj-23786	13	57	light	light	PROPN
brj-23786	13	58	industry	industry	NOUN
brj-23786	13	59	,	,	PUNCT
brj-23786	13	60	zhengzhou	zhengzhou	PROPN
brj-23786	13	61	,	,	PUNCT
brj-23786	13	62	china	china	PROPN
brj-23786	13	63	;	;	PUNCT
brj-23786	13	64	c	c	X
brj-23786	13	65	:	:	PUNCT
brj-23786	13	66	henan	henan	PROPN
brj-23786	13	67	alst	alst	PROPN
brj-23786	13	68	new	new	ADJ
brj-23786	13	69	energy	energy	PROPN
brj-23786	13	70	technology	technology	PROPN
brj-23786	13	71	co.	co.	PROPN
brj-23786	13	72	ltd	ltd	PROPN
brj-23786	13	73	,	,	PUNCT
brj-23786	13	74	zhengzhou	zhengzhou	PROPN
brj-23786	13	75	450001	450001	NUM
brj-23786	13	76	,	,	PUNCT
brj-23786	13	77	china	china	PROPN
brj-23786	13	78	;	;	PUNCT
brj-23786	14	1	d	d	X
brj-23786	14	2	:	:	PUNCT
brj-23786	14	3	zhengzhou	zhengzhou	PROPN
brj-23786	14	4	yuzhong	yuzhong	PROPN
brj-23786	14	5	energy	energy	PROPN
brj-23786	14	6	co.	co.	PROPN
brj-23786	14	7	,	,	PUNCT
brj-23786	14	8	ltd	ltd	PROPN
brj-23786	14	9	,	,	PUNCT
brj-23786	14	10	zhengzhou	zhengzhou	PROPN
brj-23786	14	11	,	,	PUNCT
brj-23786	14	12	china	china	PROPN
brj-23786	14	13	;	;	PUNCT
brj-23786	14	14	e	e	X
brj-23786	14	15	:	:	PUNCT
brj-23786	14	16	biogas	biogas	NOUN
brj-23786	14	17	institute	institute	PROPN
brj-23786	14	18	of	of	ADP
brj-23786	14	19	ministry	ministry	PROPN
brj-23786	14	20	of	of	ADP
brj-23786	14	21	agriculture	agriculture	PROPN
brj-23786	14	22	and	and	CCONJ
brj-23786	14	23	rural	rural	ADJ
brj-23786	14	24	affairs	affair	NOUN
brj-23786	14	25	,	,	PUNCT
brj-23786	14	26	key	key	ADJ
brj-23786	14	27	laboratory	laboratory	NOUN
brj-23786	14	28	of	of	ADP
brj-23786	14	29	development	development	NOUN
brj-23786	14	30	and	and	CCONJ
brj-23786	14	31	application	application	NOUN
brj-23786	14	32	of	of	ADP
brj-23786	14	33	rural	rural	ADJ
brj-23786	14	34	renewable	renewable	ADJ
brj-23786	14	35	energy	energy	NOUN
brj-23786	14	36	,	,	PUNCT
brj-23786	14	37	ministry	ministry	NOUN
brj-23786	14	38	of	of	ADP
brj-23786	14	39	agriculture	agriculture	PROPN
brj-23786	14	40	and	and	CCONJ
brj-23786	14	41	rural	rural	ADJ
brj-23786	14	42	affairs	affair	NOUN
brj-23786	14	43	,	,	PUNCT
brj-23786	14	44	chengdu	chengdu	PROPN
brj-23786	14	45	610041	610041	NUM
brj-23786	14	46	,	,	PUNCT
brj-23786	14	47	china	china	PROPN
brj-23786	14	48	;	;	PUNCT
brj-23786	14	49	f	f	X
brj-23786	14	50	:	:	PUNCT
brj-23786	14	51	sichuan	sichuan	PROPN
brj-23786	14	52	pratacultural	pratacultural	PROPN
brj-23786	14	53	technology	technology	PROPN
brj-23786	14	54	research	research	NOUN
brj-23786	14	55	and	and	CCONJ
brj-23786	14	56	extension	extension	NOUN
brj-23786	14	57	center	center	NOUN
brj-23786	14	58	chengdu	chengdu	PROPN
brj-23786	14	59	610041	610041	NUM
brj-23786	14	60	,	,	PUNCT
brj-23786	14	61	china	china	PROPN
brj-23786	14	62	;	;	PUNCT
brj-23786	14	63	g	g	PROPN
brj-23786	14	64	:	:	PUNCT
brj-23786	14	65	sichuan	sichuan	PROPN
brj-23786	14	66	agricultural	agricultural	ADJ
brj-23786	14	67	planning	planning	NOUN
brj-23786	14	68	and	and	CCONJ
brj-23786	14	69	construction	construction	NOUN
brj-23786	14	70	service	service	NOUN
brj-23786	14	71	center	center	NOUN
brj-23786	14	72	,	,	PUNCT
brj-23786	14	73	chengdu	chengdu	PROPN
brj-23786	14	74	610041	610041	NUM
brj-23786	14	75	,	,	PUNCT
brj-23786	14	76	china	china	PROPN
brj-23786	14	77	;	;	PUNCT
brj-23786	14	78	*	*	PUNCT
brj-23786	14	79	corresponding	correspond	VERB
brj-23786	14	80	author	author	NOUN
brj-23786	14	81	:	:	PUNCT
brj-23786	14	82	huangruyi1983@qq.com	huangruyi1983@qq.com	X
brj-23786	14	83	introduction	introduction	NOUN
brj-23786	14	84	biomass	biomass	NOUN
brj-23786	14	85	is	be	AUX
brj-23786	14	86	globally	globally	ADV
brj-23786	14	87	acknowledged	acknowledge	VERB
brj-23786	14	88	as	as	ADP
brj-23786	14	89	a	a	DET
brj-23786	14	90	“	"	PUNCT
brj-23786	14	91	zero	zero	NUM
brj-23786	14	92	carbon	carbon	NOUN
brj-23786	14	93	”	"	PUNCT
brj-23786	14	94	renewable	renewable	ADJ
brj-23786	14	95	energy	energy	NOUN
brj-23786	14	96	source	source	NOUN
brj-23786	14	97	(	(	PUNCT
brj-23786	14	98	huang	huang	PROPN
brj-23786	14	99	et	et	PROPN
brj-23786	14	100	al	al	PROPN
brj-23786	14	101	.	.	PROPN
brj-23786	14	102	2021	2021	NUM
brj-23786	14	103	)	)	PUNCT
brj-23786	14	104	,	,	PUNCT
brj-23786	14	105	and	and	CCONJ
brj-23786	14	106	its	its	PRON
brj-23786	14	107	pyrolysis	pyrolysis	NOUN
brj-23786	14	108	products	product	NOUN
brj-23786	14	109	hold	hold	VERB
brj-23786	14	110	vast	vast	ADJ
brj-23786	14	111	potential	potential	NOUN
brj-23786	14	112	for	for	ADP
brj-23786	14	113	green	green	ADJ
brj-23786	14	114	economy	economy	NOUN
brj-23786	14	115	applications	application	NOUN
brj-23786	14	116	,	,	PUNCT
brj-23786	14	117	including	include	VERB
brj-23786	14	118	biofuels	biofuel	NOUN
brj-23786	14	119	and	and	CCONJ
brj-23786	14	120	chemicals	chemical	NOUN
brj-23786	14	121	.	.	PUNCT
brj-23786	15	1	pyrolysis	pyrolysis	NOUN
brj-23786	15	2	plays	play	VERB
brj-23786	15	3	a	a	DET
brj-23786	15	4	crucial	crucial	ADJ
brj-23786	15	5	role	role	NOUN
brj-23786	15	6	in	in	ADP
brj-23786	15	7	the	the	DET
brj-23786	15	8	formation	formation	NOUN
brj-23786	15	9	and	and	CCONJ
brj-23786	15	10	evolution	evolution	NOUN
brj-23786	15	11	of	of	ADP
brj-23786	15	12	biomass	biomass	NOUN
brj-23786	15	13	fuels	fuel	NOUN
brj-23786	15	14	during	during	ADP
brj-23786	15	15	the	the	DET
brj-23786	15	16	combustion	combustion	NOUN
brj-23786	15	17	process	process	NOUN
brj-23786	15	18	,	,	PUNCT
brj-23786	15	19	exerting	exert	VERB
brj-23786	15	20	a	a	DET
brj-23786	15	21	direct	direct	ADJ
brj-23786	15	22	impact	impact	NOUN
brj-23786	15	23	on	on	ADP
brj-23786	15	24	subsequent	subsequent	ADJ
brj-23786	15	25	processes	process	NOUN
brj-23786	15	26	.	.	PUNCT
brj-23786	16	1	therefore	therefore	ADV
brj-23786	16	2	,	,	PUNCT
brj-23786	16	3	studying	study	VERB
brj-23786	16	4	the	the	DET
brj-23786	16	5	pyrolytic	pyrolytic	ADJ
brj-23786	16	6	properties	property	NOUN
brj-23786	16	7	of	of	ADP
brj-23786	16	8	biomass	biomass	NOUN
brj-23786	16	9	is	be	AUX
brj-23786	16	10	crucial	crucial	ADJ
brj-23786	16	11	for	for	ADP
brj-23786	16	12	enhancing	enhance	VERB
brj-23786	16	13	energy	energy	NOUN
brj-23786	16	14	use	use	NOUN
brj-23786	16	15	efficiency	efficiency	NOUN
brj-23786	16	16	(	(	PUNCT
brj-23786	16	17	gbolahan	gbolahan	VERB
brj-23786	16	18	et	et	PROPN
brj-23786	16	19	al	al	PROPN
brj-23786	16	20	.	.	PROPN
brj-23786	16	21	2022	2022	NUM
brj-23786	16	22	;	;	PUNCT
brj-23786	16	23	ke	ke	PROPN
brj-23786	16	24	et	et	PROPN
brj-23786	16	25	al	al	PROPN
brj-23786	16	26	.	.	PROPN
brj-23786	16	27	2022	2022	NUM
brj-23786	16	28	;	;	PUNCT
brj-23786	16	29	zhong	zhong	PROPN
brj-23786	16	30	et	et	PROPN
brj-23786	16	31	al	al	PROPN
brj-23786	16	32	.	.	PROPN
brj-23786	16	33	2023	2023	NUM
brj-23786	16	34	)	)	PUNCT
brj-23786	16	35	.	.	PUNCT
brj-23786	17	1	due	due	ADP
brj-23786	17	2	to	to	ADP
brj-23786	17	3	the	the	DET
brj-23786	17	4	increasing	increase	VERB
brj-23786	17	5	demand	demand	NOUN
brj-23786	17	6	for	for	ADP
brj-23786	17	7	biomass	biomass	NOUN
brj-23786	17	8	fuels	fuel	NOUN
brj-23786	17	9	in	in	ADP
brj-23786	17	10	science	science	NOUN
brj-23786	17	11	and	and	CCONJ
brj-23786	17	12	industry	industry	NOUN
brj-23786	17	13	,	,	PUNCT
brj-23786	17	14	the	the	DET
brj-23786	17	15	study	study	NOUN
brj-23786	17	16	of	of	ADP
brj-23786	17	17	the	the	DET
brj-23786	17	18	laws	law	NOUN
brj-23786	17	19	governing	govern	VERB
brj-23786	17	20	the	the	DET
brj-23786	17	21	pyrolysis	pyrolysis	NOUN
brj-23786	17	22	and	and	CCONJ
brj-23786	17	23	combustion	combustion	NOUN
brj-23786	17	24	behaviour	behaviour	NOUN
brj-23786	17	25	of	of	ADP
brj-23786	17	26	biomass	biomass	NOUN
brj-23786	17	27	is	be	AUX
brj-23786	17	28	key	key	ADJ
brj-23786	17	29	to	to	ADP
brj-23786	17	30	peer	peer	NOUN
brj-23786	17	31	-	-	PUNCT
brj-23786	17	32	reviewed	review	VERB
brj-23786	17	33	article	article	NOUN
brj-23786	17	34	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	18	1	xu	xu	PROPN
brj-23786	18	2	et	et	PROPN
brj-23786	18	3	al	al	PROPN
brj-23786	18	4	.	.	PROPN
brj-23786	18	5	(	(	PUNCT
brj-23786	18	6	2024	2024	NUM
brj-23786	18	7	)	)	PUNCT
brj-23786	18	8	.	.	PUNCT
brj-23786	19	1	“	"	PUNCT
brj-23786	19	2	pyrolysis	pyrolysis	NOUN
brj-23786	19	3	kinetics	kinetic	NOUN
brj-23786	19	4	with	with	ADP
brj-23786	19	5	ann	ann	PROPN
brj-23786	19	6	,	,	PUNCT
brj-23786	19	7	”	"	PUNCT
brj-23786	19	8	bioresources	bioresource	NOUN
brj-23786	19	9	19(4	19(4	NUM
brj-23786	19	10	)	)	PUNCT
brj-23786	19	11	,	,	PUNCT
brj-23786	19	12	7513	7513	NUM
brj-23786	19	13	-	-	SYM
brj-23786	19	14	7529	7529	NUM
brj-23786	19	15	.	.	PUNCT
brj-23786	20	1	7514	7514	NUM
brj-23786	20	2	the	the	DET
brj-23786	20	3	effective	effective	ADJ
brj-23786	20	4	use	use	NOUN
brj-23786	20	5	of	of	ADP
brj-23786	20	6	biomass	biomass	NOUN
brj-23786	20	7	fuels	fuel	NOUN
brj-23786	20	8	(	(	PUNCT
brj-23786	20	9	ragauskas	ragauskas	PROPN
brj-23786	20	10	et	et	PROPN
brj-23786	20	11	al	al	PROPN
brj-23786	20	12	.	.	PROPN
brj-23786	20	13	2006	2006	NUM
brj-23786	20	14	;	;	PUNCT
brj-23786	20	15	zhu	zhu	PROPN
brj-23786	20	16	et	et	PROPN
brj-23786	20	17	al	al	PROPN
brj-23786	20	18	.	.	PROPN
brj-23786	20	19	2021	2021	NUM
brj-23786	20	20	;	;	PUNCT
brj-23786	20	21	vo	vo	X
brj-23786	20	22	et	et	PROPN
brj-23786	20	23	al	al	PROPN
brj-23786	20	24	.	.	PROPN
brj-23786	20	25	2022	2022	NUM
brj-23786	20	26	)	)	PUNCT
brj-23786	20	27	.	.	PUNCT
brj-23786	21	1	the	the	DET
brj-23786	21	2	main	main	ADJ
brj-23786	21	3	components	component	NOUN
brj-23786	21	4	of	of	ADP
brj-23786	21	5	biomass	biomass	NOUN
brj-23786	21	6	are	be	AUX
brj-23786	21	7	hemicellulose	hemicellulose	NOUN
brj-23786	21	8	,	,	PUNCT
brj-23786	21	9	cellulose	cellulose	NOUN
brj-23786	21	10	,	,	PUNCT
brj-23786	21	11	and	and	CCONJ
brj-23786	21	12	lignin	lignin	PROPN
brj-23786	21	13	;	;	PUNCT
brj-23786	21	14	based	base	VERB
brj-23786	21	15	on	on	ADP
brj-23786	21	16	such	such	DET
brj-23786	21	17	a	a	DET
brj-23786	21	18	composition	composition	NOUN
brj-23786	21	19	,	,	PUNCT
brj-23786	21	20	chemical	chemical	NOUN
brj-23786	21	21	kinetics	kinetic	NOUN
brj-23786	21	22	provides	provide	VERB
brj-23786	21	23	a	a	DET
brj-23786	21	24	theoretical	theoretical	ADJ
brj-23786	21	25	basis	basis	NOUN
brj-23786	21	26	for	for	ADP
brj-23786	21	27	the	the	DET
brj-23786	21	28	quantitative	quantitative	ADJ
brj-23786	21	29	description	description	NOUN
brj-23786	21	30	of	of	ADP
brj-23786	21	31	pyrolysis	pyrolysis	NOUN
brj-23786	21	32	reaction	reaction	NOUN
brj-23786	21	33	processes	process	NOUN
brj-23786	21	34	(	(	PUNCT
brj-23786	21	35	kersten	kersten	VERB
brj-23786	21	36	et	et	PROPN
brj-23786	21	37	al	al	PROPN
brj-23786	21	38	.	.	PROPN
brj-23786	21	39	2005	2005	NUM
brj-23786	21	40	;	;	PUNCT
brj-23786	21	41	ka	ka	PROPN
brj-23786	21	42	et	et	PROPN
brj-23786	21	43	al	al	PROPN
brj-23786	21	44	.	.	PROPN
brj-23786	21	45	2012	2012	NUM
brj-23786	21	46	;	;	PUNCT
brj-23786	21	47	ding	de	VERB
brj-23786	21	48	et	et	PROPN
brj-23786	21	49	al	al	PROPN
brj-23786	21	50	.	.	PROPN
brj-23786	21	51	2020	2020	NUM
brj-23786	21	52	;	;	PUNCT
brj-23786	21	53	ding	de	VERB
brj-23786	21	54	et	et	PROPN
brj-23786	21	55	al	al	PROPN
brj-23786	21	56	.	.	PROPN
brj-23786	21	57	2023	2023	NUM
brj-23786	21	58	)	)	PUNCT
brj-23786	21	59	.	.	PUNCT
brj-23786	22	1	biomass	biomass	NOUN
brj-23786	22	2	pyrolysis	pyrolysis	NOUN
brj-23786	22	3	kinetics	kinetic	NOUN
brj-23786	22	4	are	be	AUX
brj-23786	22	5	used	use	VERB
brj-23786	22	6	to	to	PART
brj-23786	22	7	characterize	characterize	VERB
brj-23786	22	8	the	the	DET
brj-23786	22	9	effects	effect	NOUN
brj-23786	22	10	of	of	ADP
brj-23786	22	11	parameters	parameter	NOUN
brj-23786	22	12	such	such	ADJ
brj-23786	22	13	as	as	ADP
brj-23786	22	14	reaction	reaction	NOUN
brj-23786	22	15	temperature	temperature	NOUN
brj-23786	22	16	and	and	CCONJ
brj-23786	22	17	reaction	reaction	NOUN
brj-23786	22	18	time	time	NOUN
brj-23786	22	19	on	on	ADP
brj-23786	22	20	the	the	DET
brj-23786	22	21	conversion	conversion	NOUN
brj-23786	22	22	of	of	ADP
brj-23786	22	23	reaction	reaction	NOUN
brj-23786	22	24	products	product	NOUN
brj-23786	22	25	during	during	ADP
brj-23786	22	26	thermal	thermal	ADJ
brj-23786	22	27	decomposition	decomposition	NOUN
brj-23786	22	28	reactions	reaction	NOUN
brj-23786	22	29	of	of	ADP
brj-23786	22	30	biomass	biomass	NOUN
brj-23786	22	31	(	(	PUNCT
brj-23786	22	32	xu	xu	INTJ
brj-23786	22	33	et	et	PROPN
brj-23786	22	34	al	al	PROPN
brj-23786	22	35	.	.	PROPN
brj-23786	22	36	2020	2020	NUM
brj-23786	22	37	)	)	PUNCT
brj-23786	22	38	.	.	PUNCT
brj-23786	23	1	many	many	ADJ
brj-23786	23	2	scholars	scholar	NOUN
brj-23786	23	3	have	have	AUX
brj-23786	23	4	conducted	conduct	VERB
brj-23786	23	5	extensive	extensive	ADJ
brj-23786	23	6	research	research	NOUN
brj-23786	23	7	on	on	ADP
brj-23786	23	8	the	the	DET
brj-23786	23	9	kinetic	kinetic	ADJ
brj-23786	23	10	parameters	parameter	NOUN
brj-23786	23	11	of	of	ADP
brj-23786	23	12	biomass	biomass	NOUN
brj-23786	23	13	pyrolysis	pyrolysis	NOUN
brj-23786	23	14	processes	process	NOUN
brj-23786	23	15	(	(	PUNCT
brj-23786	23	16	white	white	PROPN
brj-23786	23	17	et	et	PROPN
brj-23786	23	18	al	al	PROPN
brj-23786	23	19	.	.	PROPN
brj-23786	23	20	2011	2011	NUM
brj-23786	23	21	)	)	PUNCT
brj-23786	23	22	,	,	PUNCT
brj-23786	23	23	providing	provide	VERB
brj-23786	23	24	important	important	ADJ
brj-23786	23	25	data	datum	NOUN
brj-23786	23	26	for	for	ADP
brj-23786	23	27	the	the	DET
brj-23786	23	28	design	design	NOUN
brj-23786	23	29	of	of	ADP
brj-23786	23	30	pyrolysis	pyrolysis	NOUN
brj-23786	23	31	reactors	reactor	NOUN
brj-23786	23	32	and	and	CCONJ
brj-23786	23	33	subsequent	subsequent	ADJ
brj-23786	23	34	combustion	combustion	NOUN
brj-23786	23	35	equipment	equipment	NOUN
brj-23786	23	36	.	.	PUNCT
brj-23786	24	1	while	while	SCONJ
brj-23786	24	2	the	the	DET
brj-23786	24	3	prediction	prediction	NOUN
brj-23786	24	4	results	result	NOUN
brj-23786	24	5	of	of	ADP
brj-23786	24	6	the	the	DET
brj-23786	24	7	kinetic	kinetic	ADJ
brj-23786	24	8	model	model	NOUN
brj-23786	24	9	agree	agree	VERB
brj-23786	24	10	to	to	ADP
brj-23786	24	11	some	some	DET
brj-23786	24	12	extent	extent	NOUN
brj-23786	24	13	with	with	ADP
brj-23786	24	14	the	the	DET
brj-23786	24	15	experimental	experimental	ADJ
brj-23786	24	16	data	datum	NOUN
brj-23786	24	17	,	,	PUNCT
brj-23786	24	18	there	there	PRON
brj-23786	24	19	are	be	VERB
brj-23786	24	20	still	still	ADV
brj-23786	24	21	significant	significant	ADJ
brj-23786	24	22	discrepancies	discrepancy	NOUN
brj-23786	24	23	between	between	ADP
brj-23786	24	24	them	they	PRON
brj-23786	24	25	(	(	PUNCT
brj-23786	24	26	ding	ding	NOUN
brj-23786	24	27	et	et	PROPN
brj-23786	24	28	al	al	PROPN
brj-23786	24	29	.	.	PROPN
brj-23786	24	30	2019	2019	NUM
brj-23786	24	31	;	;	PUNCT
brj-23786	24	32	liborio	liborio	PROPN
brj-23786	24	33	et	et	PROPN
brj-23786	24	34	al	al	PROPN
brj-23786	24	35	.	.	PROPN
brj-23786	24	36	2024	2024	NUM
brj-23786	24	37	)	)	PUNCT
brj-23786	24	38	.	.	PUNCT
brj-23786	25	1	machine	machine	NOUN
brj-23786	25	2	learning	learning	NOUN
brj-23786	25	3	models	model	NOUN
brj-23786	25	4	show	show	VERB
brj-23786	25	5	exceptional	exceptional	ADJ
brj-23786	25	6	accuracy	accuracy	NOUN
brj-23786	25	7	in	in	ADP
brj-23786	25	8	predicting	predict	VERB
brj-23786	25	9	highly	highly	ADV
brj-23786	25	10	non	non	ADJ
brj-23786	25	11	-	-	ADJ
brj-23786	25	12	linear	linear	ADJ
brj-23786	25	13	processes	process	NOUN
brj-23786	25	14	and	and	CCONJ
brj-23786	25	15	can	can	AUX
brj-23786	25	16	automatically	automatically	ADV
brj-23786	25	17	learn	learn	VERB
brj-23786	25	18	from	from	ADP
brj-23786	25	19	data	datum	NOUN
brj-23786	25	20	without	without	ADP
brj-23786	25	21	the	the	DET
brj-23786	25	22	need	need	NOUN
brj-23786	25	23	for	for	ADP
brj-23786	25	24	real	real	ADJ
brj-23786	25	25	operating	operating	NOUN
brj-23786	25	26	and	and	CCONJ
brj-23786	25	27	chemical	chemical	NOUN
brj-23786	25	28	conditions	condition	NOUN
brj-23786	25	29	,	,	PUNCT
brj-23786	25	30	greatly	greatly	ADV
brj-23786	25	31	reducing	reduce	VERB
brj-23786	25	32	the	the	DET
brj-23786	25	33	need	need	NOUN
brj-23786	25	34	for	for	ADP
brj-23786	25	35	human	human	ADJ
brj-23786	25	36	intervention	intervention	NOUN
brj-23786	25	37	(	(	PUNCT
brj-23786	25	38	breiman	breiman	NOUN
brj-23786	25	39	1996	1996	NUM
brj-23786	25	40	;	;	PUNCT
brj-23786	25	41	sunphorka	sunphorka	NOUN
brj-23786	25	42	et	et	PROPN
brj-23786	25	43	al	al	PROPN
brj-23786	25	44	.	.	PROPN
brj-23786	25	45	2017	2017	NUM
brj-23786	25	46	;	;	PUNCT
brj-23786	25	47	naqvi	naqvi	PROPN
brj-23786	25	48	et	et	PROPN
brj-23786	25	49	al	al	PROPN
brj-23786	25	50	.	.	PROPN
brj-23786	25	51	2018	2018	NUM
brj-23786	25	52	;	;	PUNCT
brj-23786	25	53	hu	hu	PROPN
brj-23786	25	54	et	et	PROPN
brj-23786	25	55	al	al	PROPN
brj-23786	25	56	.	.	PROPN
brj-23786	25	57	2022	2022	NUM
brj-23786	25	58	)	)	PUNCT
brj-23786	25	59	.	.	PUNCT
brj-23786	26	1	these	these	DET
brj-23786	26	2	models	model	NOUN
brj-23786	26	3	have	have	AUX
brj-23786	26	4	been	be	AUX
brj-23786	26	5	used	use	VERB
brj-23786	26	6	extensively	extensively	ADV
brj-23786	26	7	to	to	PART
brj-23786	26	8	simulate	simulate	VERB
brj-23786	26	9	thermal	thermal	ADJ
brj-23786	26	10	processes	process	NOUN
brj-23786	26	11	involving	involve	VERB
brj-23786	26	12	biomass	biomass	NOUN
brj-23786	26	13	pyrolysis	pyrolysis	NOUN
brj-23786	26	14	,	,	PUNCT
brj-23786	26	15	gasification	gasification	NOUN
brj-23786	26	16	,	,	PUNCT
brj-23786	26	17	and	and	CCONJ
brj-23786	26	18	combustion	combustion	NOUN
brj-23786	26	19	(	(	PUNCT
brj-23786	26	20	dubdub	dubdub	PROPN
brj-23786	26	21	and	and	CCONJ
brj-23786	26	22	al	al	PROPN
brj-23786	26	23	-	-	PUNCT
brj-23786	26	24	yaari	yaari	PROPN
brj-23786	26	25	2020	2020	NUM
brj-23786	26	26	;	;	PUNCT
brj-23786	26	27	bi	bi	PROPN
brj-23786	26	28	et	et	PROPN
brj-23786	26	29	al	al	PROPN
brj-23786	26	30	.	.	PROPN
brj-23786	26	31	2021	2021	NUM
brj-23786	26	32	;	;	PUNCT
brj-23786	26	33	yang	yang	PROPN
brj-23786	26	34	et	et	PROPN
brj-23786	26	35	al	al	PROPN
brj-23786	26	36	.	.	PROPN
brj-23786	26	37	2022	2022	NUM
brj-23786	26	38	)	)	PUNCT
brj-23786	26	39	.	.	PUNCT
brj-23786	27	1	however	however	ADV
brj-23786	27	2	,	,	PUNCT
brj-23786	27	3	machine	machine	NOUN
brj-23786	27	4	learning	learning	NOUN
brj-23786	27	5	models	model	NOUN
brj-23786	27	6	have	have	VERB
brj-23786	27	7	certain	certain	ADJ
brj-23786	27	8	drawbacks	drawback	NOUN
brj-23786	27	9	:	:	PUNCT
brj-23786	27	10	machine	machine	NOUN
brj-23786	27	11	learning	learning	NOUN
brj-23786	27	12	models	model	NOUN
brj-23786	27	13	typically	typically	ADV
brj-23786	27	14	depend	depend	VERB
brj-23786	27	15	on	on	ADP
brj-23786	27	16	significant	significant	ADJ
brj-23786	27	17	amounts	amount	NOUN
brj-23786	27	18	of	of	ADP
brj-23786	27	19	high	high	ADJ
brj-23786	27	20	-	-	PUNCT
brj-23786	27	21	quality	quality	NOUN
brj-23786	27	22	data	datum	NOUN
brj-23786	27	23	.	.	PUNCT
brj-23786	28	1	insufficient	insufficient	ADJ
brj-23786	28	2	data	datum	NOUN
brj-23786	28	3	or	or	CCONJ
brj-23786	28	4	poor	poor	ADJ
brj-23786	28	5	data	datum	NOUN
brj-23786	28	6	quality	quality	NOUN
brj-23786	28	7	can	can	AUX
brj-23786	28	8	negatively	negatively	ADV
brj-23786	28	9	affect	affect	VERB
brj-23786	28	10	model	model	NOUN
brj-23786	28	11	performance	performance	NOUN
brj-23786	28	12	.	.	PUNCT
brj-23786	29	1	many	many	ADJ
brj-23786	29	2	machine	machine	NOUN
brj-23786	29	3	learning	learn	VERB
brj-23786	29	4	algorithms	algorithm	NOUN
brj-23786	29	5	are	be	AUX
brj-23786	29	6	described	describe	VERB
brj-23786	29	7	as	as	ADP
brj-23786	29	8	black	black	ADJ
brj-23786	29	9	-	-	PUNCT
brj-23786	29	10	box	box	NOUN
brj-23786	29	11	models	model	NOUN
brj-23786	29	12	,	,	PUNCT
brj-23786	29	13	meaning	mean	VERB
brj-23786	29	14	that	that	SCONJ
brj-23786	29	15	their	their	PRON
brj-23786	29	16	inner	inner	ADJ
brj-23786	29	17	workings	working	NOUN
brj-23786	29	18	are	be	AUX
brj-23786	29	19	complicated	complicated	ADJ
brj-23786	29	20	and	and	CCONJ
brj-23786	29	21	difficult	difficult	ADJ
brj-23786	29	22	to	to	PART
brj-23786	29	23	elucidate	elucidate	VERB
brj-23786	29	24	,	,	PUNCT
brj-23786	29	25	making	make	VERB
brj-23786	29	26	it	it	PRON
brj-23786	29	27	challenging	challenging	ADJ
brj-23786	29	28	to	to	PART
brj-23786	29	29	understand	understand	VERB
brj-23786	29	30	and	and	CCONJ
brj-23786	29	31	characterize	characterize	VERB
brj-23786	29	32	the	the	DET
brj-23786	29	33	model	model	NOUN
brj-23786	29	34	’s	’s	PART
brj-23786	29	35	predictions	prediction	NOUN
brj-23786	29	36	(	(	PUNCT
brj-23786	29	37	dubdub	dubdub	PROPN
brj-23786	29	38	and	and	CCONJ
brj-23786	29	39	al	al	PROPN
brj-23786	29	40	-	-	PUNCT
brj-23786	29	41	yaari	yaari	PROPN
brj-23786	29	42	2020	2020	NUM
brj-23786	29	43	;	;	PUNCT
brj-23786	29	44	bi	bi	PROPN
brj-23786	29	45	et	et	PROPN
brj-23786	29	46	al	al	PROPN
brj-23786	29	47	.	.	PROPN
brj-23786	29	48	2021	2021	NUM
brj-23786	29	49	)	)	PUNCT
brj-23786	29	50	.	.	PUNCT
brj-23786	30	1	in	in	ADP
brj-23786	30	2	addition	addition	NOUN
brj-23786	30	3	,	,	PUNCT
brj-23786	30	4	machine	machine	NOUN
brj-23786	30	5	learning	learning	NOUN
brj-23786	30	6	models	model	NOUN
brj-23786	30	7	can	can	AUX
brj-23786	30	8	accurately	accurately	ADV
brj-23786	30	9	predict	predict	VERB
brj-23786	30	10	outcomes	outcome	NOUN
brj-23786	30	11	within	within	ADP
brj-23786	30	12	the	the	DET
brj-23786	30	13	training	training	NOUN
brj-23786	30	14	domain	domain	NOUN
brj-23786	30	15	,	,	PUNCT
brj-23786	30	16	but	but	CCONJ
brj-23786	30	17	they	they	PRON
brj-23786	30	18	often	often	ADV
brj-23786	30	19	perform	perform	VERB
brj-23786	30	20	poorly	poorly	ADV
brj-23786	30	21	in	in	ADP
brj-23786	30	22	domains	domain	NOUN
brj-23786	30	23	outside	outside	ADP
brj-23786	30	24	the	the	DET
brj-23786	30	25	training	training	NOUN
brj-23786	30	26	data	datum	NOUN
brj-23786	30	27	(	(	PUNCT
brj-23786	30	28	xing	xing	PROPN
brj-23786	30	29	et	et	PROPN
brj-23786	30	30	al	al	PROPN
brj-23786	30	31	.	.	PROPN
brj-23786	30	32	2019	2019	NUM
brj-23786	30	33	;	;	PUNCT
brj-23786	30	34	zhang	zhang	PROPN
brj-23786	30	35	et	et	PROPN
brj-23786	30	36	al	al	PROPN
brj-23786	30	37	.	.	PROPN
brj-23786	30	38	2022	2022	NUM
brj-23786	30	39	)	)	PUNCT
brj-23786	30	40	.	.	PUNCT
brj-23786	31	1	for	for	ADP
brj-23786	31	2	example	example	NOUN
brj-23786	31	3	,	,	PUNCT
brj-23786	31	4	forty	forty	NUM
brj-23786	31	5	-	-	PUNCT
brj-23786	31	6	nine	nine	NUM
brj-23786	31	7	tobacco	tobacco	NOUN
brj-23786	31	8	samples	sample	NOUN
brj-23786	31	9	were	be	AUX
brj-23786	31	10	used	use	VERB
brj-23786	31	11	to	to	PART
brj-23786	31	12	study	study	VERB
brj-23786	31	13	pyrolysis	pyrolysis	NOUN
brj-23786	31	14	kinetics	kinetic	NOUN
brj-23786	31	15	through	through	ADP
brj-23786	31	16	machine	machine	NOUN
brj-23786	31	17	learning	learning	NOUN
brj-23786	31	18	approaches	approach	NOUN
brj-23786	31	19	(	(	PUNCT
brj-23786	31	20	wei	wei	PROPN
brj-23786	31	21	et	et	PROPN
brj-23786	31	22	al	al	PROPN
brj-23786	31	23	.	.	PROPN
brj-23786	31	24	2023	2023	NUM
brj-23786	31	25	)	)	PUNCT
brj-23786	31	26	.	.	PUNCT
brj-23786	32	1	a	a	DET
brj-23786	32	2	comprehensive	comprehensive	ADJ
brj-23786	32	3	artificial	artificial	ADJ
brj-23786	32	4	intelligence	intelligence	NOUN
brj-23786	32	5	model	model	NOUN
brj-23786	32	6	without	without	ADP
brj-23786	32	7	considering	consider	VERB
brj-23786	32	8	the	the	DET
brj-23786	32	9	chemical	chemical	NOUN
brj-23786	32	10	reaction	reaction	NOUN
brj-23786	32	11	mechanism	mechanism	NOUN
brj-23786	32	12	was	be	AUX
brj-23786	32	13	presented	present	VERB
brj-23786	32	14	to	to	PART
brj-23786	32	15	predictive	predictive	VERB
brj-23786	32	16	the	the	DET
brj-23786	32	17	thermal	thermal	ADJ
brj-23786	32	18	decomposition	decomposition	NOUN
brj-23786	32	19	of	of	ADP
brj-23786	32	20	rice	rice	NOUN
brj-23786	32	21	husk	husk	NOUN
brj-23786	32	22	(	(	PUNCT
brj-23786	32	23	alaba	alaba	PROPN
brj-23786	32	24	et	et	PROPN
brj-23786	32	25	al	al	PROPN
brj-23786	32	26	.	.	PROPN
brj-23786	32	27	2019	2019	NUM
brj-23786	32	28	)	)	PUNCT
brj-23786	32	29	.	.	PUNCT
brj-23786	33	1	a	a	DET
brj-23786	33	2	large	large	ADJ
brj-23786	33	3	amount	amount	NOUN
brj-23786	33	4	of	of	ADP
brj-23786	33	5	laboratory	laboratory	NOUN
brj-23786	33	6	data	datum	NOUN
brj-23786	33	7	poses	pose	VERB
brj-23786	33	8	significant	significant	ADJ
brj-23786	33	9	challenges	challenge	NOUN
brj-23786	33	10	to	to	ADP
brj-23786	33	11	predictive	predictive	ADJ
brj-23786	33	12	work	work	NOUN
brj-23786	33	13	.	.	PUNCT
brj-23786	34	1	moreover	moreover	ADV
brj-23786	34	2	,	,	PUNCT
brj-23786	34	3	non	non	ADJ
brj-23786	34	4	-	-	ADJ
brj-23786	34	5	mechanistic	mechanistic	ADJ
brj-23786	34	6	models	model	NOUN
brj-23786	34	7	lack	lack	VERB
brj-23786	34	8	interpretability	interpretability	NOUN
brj-23786	34	9	and	and	CCONJ
brj-23786	34	10	are	be	AUX
brj-23786	34	11	highly	highly	ADV
brj-23786	34	12	dependent	dependent	ADJ
brj-23786	34	13	on	on	ADP
brj-23786	34	14	data	datum	NOUN
brj-23786	34	15	.	.	PUNCT
brj-23786	35	1	to	to	PART
brj-23786	35	2	enhance	enhance	VERB
brj-23786	35	3	predictive	predictive	ADJ
brj-23786	35	4	capability	capability	NOUN
brj-23786	35	5	,	,	PUNCT
brj-23786	35	6	an	an	DET
brj-23786	35	7	innovative	innovative	ADJ
brj-23786	35	8	framework	framework	NOUN
brj-23786	35	9	has	have	AUX
brj-23786	35	10	been	be	AUX
brj-23786	35	11	developed	develop	VERB
brj-23786	35	12	to	to	PART
brj-23786	35	13	improve	improve	VERB
brj-23786	35	14	the	the	DET
brj-23786	35	15	generalization	generalization	NOUN
brj-23786	35	16	of	of	ADP
brj-23786	35	17	predictive	predictive	ADJ
brj-23786	35	18	models	model	NOUN
brj-23786	35	19	.	.	PUNCT
brj-23786	36	1	in	in	ADP
brj-23786	36	2	the	the	DET
brj-23786	36	3	framework	framework	NOUN
brj-23786	36	4	,	,	PUNCT
brj-23786	36	5	kinetic	kinetic	NOUN
brj-23786	36	6	models	model	NOUN
brj-23786	36	7	based	base	VERB
brj-23786	36	8	on	on	ADP
brj-23786	36	9	chemical	chemical	ADJ
brj-23786	36	10	reaction	reaction	NOUN
brj-23786	36	11	mechanisms	mechanism	NOUN
brj-23786	36	12	were	be	AUX
brj-23786	36	13	integrated	integrate	VERB
brj-23786	36	14	with	with	ADP
brj-23786	36	15	data	data	NOUN
brj-23786	36	16	-	-	PUNCT
brj-23786	36	17	driven	drive	VERB
brj-23786	36	18	machine	machine	NOUN
brj-23786	36	19	learning	learning	NOUN
brj-23786	36	20	models	model	NOUN
brj-23786	36	21	.	.	PUNCT
brj-23786	37	1	kinetic	kinetic	ADJ
brj-23786	37	2	models	model	NOUN
brj-23786	37	3	based	base	VERB
brj-23786	37	4	on	on	ADP
brj-23786	37	5	chemical	chemical	ADJ
brj-23786	37	6	reaction	reaction	NOUN
brj-23786	37	7	mechanisms	mechanism	NOUN
brj-23786	37	8	were	be	AUX
brj-23786	37	9	used	use	VERB
brj-23786	37	10	to	to	PART
brj-23786	37	11	predict	predict	VERB
brj-23786	37	12	optimize	optimize	NOUN
brj-23786	37	13	initial	initial	ADJ
brj-23786	37	14	values	value	NOUN
brj-23786	37	15	of	of	ADP
brj-23786	37	16	the	the	DET
brj-23786	37	17	kinetic	kinetic	ADJ
brj-23786	37	18	parameters	parameter	NOUN
brj-23786	37	19	(	(	PUNCT
brj-23786	37	20	kaczor	kaczor	PROPN
brj-23786	37	21	et	et	PROPN
brj-23786	37	22	al	al	PROPN
brj-23786	37	23	.	.	PROPN
brj-23786	37	24	2020	2020	NUM
brj-23786	37	25	;	;	PUNCT
brj-23786	37	26	dubdub	dubdub	PROPN
brj-23786	37	27	and	and	CCONJ
brj-23786	37	28	alyaari	alyaari	PROPN
brj-23786	37	29	2021	2021	NUM
brj-23786	37	30	;	;	PUNCT
brj-23786	37	31	marchese	marchese	PROPN
brj-23786	37	32	et	et	PROPN
brj-23786	37	33	al	al	PROPN
brj-23786	37	34	.	.	PROPN
brj-23786	37	35	2024	2024	NUM
brj-23786	37	36	)	)	PUNCT
brj-23786	37	37	.	.	PUNCT
brj-23786	38	1	the	the	DET
brj-23786	38	2	bp	bp	PROPN
brj-23786	38	3	-	-	PUNCT
brj-23786	38	4	ann	ann	PROPN
brj-23786	38	5	model	model	NOUN
brj-23786	38	6	was	be	AUX
brj-23786	38	7	used	use	VERB
brj-23786	38	8	to	to	PART
brj-23786	38	9	predict	predict	VERB
brj-23786	38	10	the	the	DET
brj-23786	38	11	error	error	NOUN
brj-23786	38	12	distribution	distribution	NOUN
brj-23786	38	13	of	of	ADP
brj-23786	38	14	the	the	DET
brj-23786	38	15	kinetic	kinetic	ADJ
brj-23786	38	16	parameters	parameter	NOUN
brj-23786	38	17	.	.	PUNCT
brj-23786	39	1	a	a	DET
brj-23786	39	2	combination	combination	NOUN
brj-23786	39	3	of	of	ADP
brj-23786	39	4	kinetic	kinetic	ADJ
brj-23786	39	5	and	and	CCONJ
brj-23786	39	6	artificial	artificial	ADJ
brj-23786	39	7	neural	neural	ADJ
brj-23786	39	8	network	network	NOUN
brj-23786	39	9	models	model	NOUN
brj-23786	39	10	was	be	AUX
brj-23786	39	11	used	use	VERB
brj-23786	39	12	to	to	PART
brj-23786	39	13	provide	provide	VERB
brj-23786	39	14	a	a	DET
brj-23786	39	15	comprehensive	comprehensive	ADJ
brj-23786	39	16	prediction	prediction	NOUN
brj-23786	39	17	of	of	ADP
brj-23786	39	18	pyrolysis	pyrolysis	NOUN
brj-23786	39	19	in	in	ADP
brj-23786	39	20	the	the	DET
brj-23786	39	21	training	training	NOUN
brj-23786	39	22	and	and	CCONJ
brj-23786	39	23	nontraining	nontraining	NOUN
brj-23786	39	24	zones	zone	NOUN
brj-23786	39	25	.	.	PUNCT
brj-23786	40	1	pine	pine	ADJ
brj-23786	40	2	needles	needle	NOUN
brj-23786	40	3	are	be	AUX
brj-23786	40	4	abundant	abundant	ADJ
brj-23786	40	5	in	in	ADP
brj-23786	40	6	resins	resin	NOUN
brj-23786	40	7	and	and	CCONJ
brj-23786	40	8	oils	oil	NOUN
brj-23786	40	9	,	,	PUNCT
brj-23786	40	10	known	know	VERB
brj-23786	40	11	for	for	ADP
brj-23786	40	12	their	their	PRON
brj-23786	40	13	high	high	ADJ
brj-23786	40	14	calorific	calorific	NOUN
brj-23786	40	15	value	value	NOUN
brj-23786	40	16	,	,	PUNCT
brj-23786	40	17	flammability	flammability	NOUN
brj-23786	40	18	,	,	PUNCT
brj-23786	40	19	low	low	ADJ
brj-23786	40	20	ash	ash	NOUN
brj-23786	40	21	content	content	NOUN
brj-23786	40	22	,	,	PUNCT
brj-23786	40	23	and	and	CCONJ
brj-23786	40	24	minimal	minimal	ADJ
brj-23786	40	25	emissions	emission	NOUN
brj-23786	40	26	of	of	ADP
brj-23786	40	27	nitrogen	nitrogen	NOUN
brj-23786	40	28	and	and	CCONJ
brj-23786	40	29	sulfur	sulfur	NOUN
brj-23786	40	30	pollutants	pollutant	NOUN
brj-23786	40	31	,	,	PUNCT
brj-23786	40	32	making	make	VERB
brj-23786	40	33	them	they	PRON
brj-23786	40	34	an	an	DET
brj-23786	40	35	effective	effective	ADJ
brj-23786	40	36	biomass	biomass	NOUN
brj-23786	40	37	fuel	fuel	NOUN
brj-23786	40	38	source	source	NOUN
brj-23786	40	39	(	(	PUNCT
brj-23786	40	40	martín	martín	NOUN
brj-23786	40	41	-	-	PUNCT
brj-23786	40	42	lara	lara	PROPN
brj-23786	40	43	et	et	PROPN
brj-23786	40	44	al	al	PROPN
brj-23786	40	45	.	.	PROPN
brj-23786	40	46	2016	2016	NUM
brj-23786	40	47	)	)	PUNCT
brj-23786	40	48	.	.	PUNCT
brj-23786	41	1	in	in	ADP
brj-23786	41	2	this	this	DET
brj-23786	41	3	study	study	NOUN
brj-23786	41	4	,	,	PUNCT
brj-23786	41	5	pine	pine	ADJ
brj-23786	41	6	needles	needle	NOUN
brj-23786	41	7	were	be	AUX
brj-23786	41	8	chosen	choose	VERB
brj-23786	41	9	as	as	ADP
brj-23786	41	10	the	the	DET
brj-23786	41	11	research	research	NOUN
brj-23786	41	12	subject	subject	NOUN
brj-23786	41	13	to	to	PART
brj-23786	41	14	explore	explore	VERB
brj-23786	41	15	a	a	DET
brj-23786	41	16	method	method	NOUN
brj-23786	41	17	that	that	PRON
brj-23786	41	18	combines	combine	VERB
brj-23786	41	19	chemical	chemical	ADJ
brj-23786	41	20	kinetics	kinetic	NOUN
brj-23786	41	21	-	-	PUNCT
brj-23786	41	22	based	base	VERB
brj-23786	41	23	models	model	NOUN
brj-23786	41	24	with	with	ADP
brj-23786	41	25	data	data	NOUN
brj-23786	41	26	-	-	PUNCT
brj-23786	41	27	driven	drive	VERB
brj-23786	41	28	models	model	NOUN
brj-23786	41	29	for	for	ADP
brj-23786	41	30	predicting	predict	VERB
brj-23786	41	31	the	the	DET
brj-23786	41	32	pyrolysis	pyrolysis	NOUN
brj-23786	41	33	process	process	NOUN
brj-23786	41	34	.	.	PUNCT
brj-23786	42	1	the	the	DET
brj-23786	42	2	objectives	objective	NOUN
brj-23786	42	3	of	of	ADP
brj-23786	42	4	this	this	DET
brj-23786	42	5	study	study	NOUN
brj-23786	42	6	were	be	AUX
brj-23786	42	7	to	to	ADP
brj-23786	42	8	(	(	PUNCT
brj-23786	42	9	1	1	X
brj-23786	42	10	)	)	PUNCT
brj-23786	42	11	conduct	conduct	NOUN
brj-23786	42	12	pyrolysis	pyrolysis	NOUN
brj-23786	42	13	experiments	experiment	NOUN
brj-23786	42	14	to	to	PART
brj-23786	42	15	investigate	investigate	VERB
brj-23786	42	16	the	the	DET
brj-23786	42	17	relationship	relationship	NOUN
brj-23786	42	18	between	between	ADP
brj-23786	42	19	pine	pine	PROPN
brj-23786	42	20	needle	needle	NOUN
brj-23786	42	21	conversion	conversion	NOUN
brj-23786	42	22	degree	degree	NOUN
brj-23786	42	23	and	and	CCONJ
brj-23786	42	24	temperature	temperature	NOUN
brj-23786	42	25	at	at	ADP
brj-23786	42	26	various	various	ADJ
brj-23786	42	27	heating	heating	NOUN
brj-23786	42	28	rates	rate	NOUN
brj-23786	42	29	(	(	PUNCT
brj-23786	42	30	10	10	NUM
brj-23786	42	31	,	,	PUNCT
brj-23786	42	32	20	20	NUM
brj-23786	42	33	,	,	PUNCT
brj-23786	42	34	and	and	CCONJ
brj-23786	42	35	40	40	NUM
brj-23786	42	36	k	k	NOUN
brj-23786	42	37	/	/	SYM
brj-23786	42	38	min	min	NOUN
brj-23786	42	39	)	)	PUNCT
brj-23786	42	40	.	.	PUNCT
brj-23786	43	1	(	(	PUNCT
brj-23786	43	2	2	2	X
brj-23786	43	3	)	)	PUNCT
brj-23786	43	4	optimize	optimize	VERB
brj-23786	43	5	the	the	DET
brj-23786	43	6	kinetic	kinetic	ADJ
brj-23786	43	7	parameters	parameter	NOUN
brj-23786	43	8	of	of	ADP
brj-23786	43	9	three	three	NUM
brj-23786	43	10	components	component	NOUN
brj-23786	43	11	peer	peer	NOUN
brj-23786	43	12	-	-	PUNCT
brj-23786	43	13	reviewed	review	VERB
brj-23786	43	14	article	article	NOUN
brj-23786	43	15	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	44	1	xu	xu	PROPN
brj-23786	44	2	et	et	PROPN
brj-23786	44	3	al	al	PROPN
brj-23786	44	4	.	.	PROPN
brj-23786	44	5	(	(	PUNCT
brj-23786	44	6	2024	2024	NUM
brj-23786	44	7	)	)	PUNCT
brj-23786	44	8	.	.	PUNCT
brj-23786	45	1	“	"	PUNCT
brj-23786	45	2	pyrolysis	pyrolysis	NOUN
brj-23786	45	3	kinetics	kinetic	NOUN
brj-23786	45	4	with	with	ADP
brj-23786	45	5	ann	ann	PROPN
brj-23786	45	6	,	,	PUNCT
brj-23786	45	7	”	"	PUNCT
brj-23786	45	8	bioresources	bioresource	NOUN
brj-23786	45	9	19(4	19(4	NUM
brj-23786	45	10	)	)	PUNCT
brj-23786	45	11	,	,	PUNCT
brj-23786	45	12	7513	7513	NUM
brj-23786	45	13	-	-	SYM
brj-23786	45	14	7529	7529	NUM
brj-23786	45	15	.	.	PUNCT
brj-23786	45	16	7515	7515	NUM
brj-23786	45	17	using	use	VERB
brj-23786	45	18	a	a	DET
brj-23786	45	19	kinetic	kinetic	ADJ
brj-23786	45	20	model	model	NOUN
brj-23786	45	21	integrated	integrate	VERB
brj-23786	45	22	with	with	ADP
brj-23786	45	23	the	the	DET
brj-23786	45	24	mantis	mantis	ADJ
brj-23786	45	25	algorithm	algorithm	NOUN
brj-23786	45	26	,	,	PUNCT
brj-23786	45	27	and	and	CCONJ
brj-23786	45	28	analyze	analyze	VERB
brj-23786	45	29	the	the	DET
brj-23786	45	30	errors	error	NOUN
brj-23786	45	31	.	.	PUNCT
brj-23786	46	1	(	(	PUNCT
brj-23786	46	2	3	3	X
brj-23786	46	3	)	)	PUNCT
brj-23786	46	4	utilize	utilize	VERB
brj-23786	46	5	a	a	DET
brj-23786	46	6	bp	bp	PROPN
brj-23786	46	7	-	-	PUNCT
brj-23786	46	8	ann	ann	PROPN
brj-23786	46	9	model	model	NOUN
brj-23786	46	10	in	in	ADP
brj-23786	46	11	conjunction	conjunction	NOUN
brj-23786	46	12	with	with	ADP
brj-23786	46	13	a	a	DET
brj-23786	46	14	genetic	genetic	ADJ
brj-23786	46	15	algorithm	algorithm	NOUN
brj-23786	46	16	to	to	PART
brj-23786	46	17	predict	predict	VERB
brj-23786	46	18	errors	error	NOUN
brj-23786	46	19	in	in	ADP
brj-23786	46	20	kinetic	kinetic	ADJ
brj-23786	46	21	parameters	parameter	NOUN
brj-23786	46	22	and	and	CCONJ
brj-23786	46	23	compare	compare	VERB
brj-23786	46	24	them	they	PRON
brj-23786	46	25	with	with	ADP
brj-23786	46	26	parameters	parameter	NOUN
brj-23786	46	27	obtained	obtain	VERB
brj-23786	46	28	from	from	ADP
brj-23786	46	29	a	a	DET
brj-23786	46	30	standalone	standalone	ADJ
brj-23786	46	31	kinetic	kinetic	ADJ
brj-23786	46	32	model	model	NOUN
brj-23786	46	33	.	.	PUNCT
brj-23786	47	1	experimental	experimental	ADJ
brj-23786	47	2	thermal	thermal	ADJ
brj-23786	47	3	analysis	analysis	NOUN
brj-23786	47	4	experiments	experiment	NOUN
brj-23786	47	5	pine	pine	ADJ
brj-23786	47	6	needles	needle	NOUN
brj-23786	47	7	were	be	AUX
brj-23786	47	8	selected	select	VERB
brj-23786	47	9	as	as	ADP
brj-23786	47	10	samples	sample	NOUN
brj-23786	47	11	for	for	ADP
brj-23786	47	12	thermogravimetric	thermogravimetric	ADJ
brj-23786	47	13	(	(	PUNCT
brj-23786	47	14	tg	tg	NOUN
brj-23786	47	15	)	)	PUNCT
brj-23786	47	16	experiments	experiment	NOUN
brj-23786	47	17	.	.	PUNCT
brj-23786	48	1	the	the	DET
brj-23786	48	2	samples	sample	NOUN
brj-23786	48	3	were	be	AUX
brj-23786	48	4	initially	initially	ADV
brj-23786	48	5	ground	grind	VERB
brj-23786	48	6	in	in	ADP
brj-23786	48	7	a	a	DET
brj-23786	48	8	grinder	grinder	NOUN
brj-23786	48	9	,	,	PUNCT
brj-23786	48	10	and	and	CCONJ
brj-23786	48	11	the	the	DET
brj-23786	48	12	resulting	result	VERB
brj-23786	48	13	particles	particle	NOUN
brj-23786	48	14	were	be	AUX
brj-23786	48	15	then	then	ADV
brj-23786	48	16	sieved	sieve	VERB
brj-23786	48	17	through	through	ADP
brj-23786	48	18	an	an	DET
brj-23786	48	19	80	80	NUM
brj-23786	48	20	-	-	PUNCT
brj-23786	48	21	mesh	mesh	NOUN
brj-23786	48	22	sieve	sieve	NOUN
brj-23786	48	23	to	to	PART
brj-23786	48	24	achieve	achieve	VERB
brj-23786	48	25	uniform	uniform	ADJ
brj-23786	48	26	particle	particle	NOUN
brj-23786	48	27	size	size	NOUN
brj-23786	48	28	.	.	PUNCT
brj-23786	49	1	the	the	DET
brj-23786	49	2	samples	sample	NOUN
brj-23786	49	3	were	be	AUX
brj-23786	49	4	baked	bake	VERB
brj-23786	49	5	at	at	ADP
brj-23786	49	6	423	423	NUM
brj-23786	49	7	k	k	NOUN
brj-23786	49	8	to	to	PART
brj-23786	49	9	ensure	ensure	VERB
brj-23786	49	10	the	the	DET
brj-23786	49	11	evaporation	evaporation	NOUN
brj-23786	49	12	of	of	ADP
brj-23786	49	13	free	free	ADJ
brj-23786	49	14	and	and	CCONJ
brj-23786	49	15	bound	bound	ADJ
brj-23786	49	16	water	water	NOUN
brj-23786	49	17	(	(	PUNCT
brj-23786	49	18	zha	zha	NOUN
brj-23786	49	19	et	et	PROPN
brj-23786	49	20	al	al	PROPN
brj-23786	49	21	.	.	PROPN
brj-23786	49	22	2022	2022	NUM
brj-23786	49	23	)	)	PUNCT
brj-23786	49	24	.	.	PUNCT
brj-23786	50	1	the	the	DET
brj-23786	50	2	pyrolysis	pyrolysis	NOUN
brj-23786	50	3	process	process	NOUN
brj-23786	50	4	was	be	AUX
brj-23786	50	5	conducted	conduct	VERB
brj-23786	50	6	using	use	VERB
brj-23786	50	7	a	a	DET
brj-23786	50	8	ta	ta	PROPN
brj-23786	50	9	instruments	instrument	NOUN
brj-23786	50	10	(	(	PUNCT
brj-23786	50	11	sdt	sdt	PROPN
brj-23786	50	12	q600	q600	PROPN
brj-23786	50	13	thermal	thermal	ADJ
brj-23786	50	14	analyzer	analyzer	NOUN
brj-23786	50	15	)	)	PUNCT
brj-23786	50	16	.	.	PUNCT
brj-23786	51	1	samples	sample	NOUN
brj-23786	51	2	weighing	weigh	VERB
brj-23786	51	3	9.0	9.0	NUM
brj-23786	51	4	±	±	NUM
brj-23786	51	5	0.5	0.5	NUM
brj-23786	51	6	mg	mg	NOUN
brj-23786	51	7	were	be	AUX
brj-23786	51	8	placed	place	VERB
brj-23786	51	9	in	in	ADP
brj-23786	51	10	an	an	DET
brj-23786	51	11	aluminum	aluminum	NOUN
brj-23786	51	12	crucible	crucible	NOUN
brj-23786	51	13	and	and	CCONJ
brj-23786	51	14	heated	heat	VERB
brj-23786	51	15	from	from	ADP
brj-23786	51	16	298	298	NUM
brj-23786	51	17	to	to	ADP
brj-23786	51	18	1173	1173	NUM
brj-23786	51	19	k	k	NOUN
brj-23786	51	20	at	at	ADP
brj-23786	51	21	heating	heating	NOUN
brj-23786	51	22	rates	rate	NOUN
brj-23786	51	23	of	of	ADP
brj-23786	51	24	10	10	NUM
brj-23786	51	25	,	,	PUNCT
brj-23786	51	26	20	20	NUM
brj-23786	51	27	,	,	PUNCT
brj-23786	51	28	or	or	CCONJ
brj-23786	51	29	40	40	NUM
brj-23786	51	30	k	k	NOUN
brj-23786	51	31	/	/	SYM
brj-23786	51	32	min	min	PROPN
brj-23786	51	33	.	.	PROPN
brj-23786	51	34	nitrogen	nitrogen	PROPN
brj-23786	51	35	was	be	AUX
brj-23786	51	36	circulated	circulate	VERB
brj-23786	51	37	at	at	ADP
brj-23786	51	38	a	a	DET
brj-23786	51	39	rate	rate	NOUN
brj-23786	51	40	of	of	ADP
brj-23786	51	41	100	100	NUM
brj-23786	51	42	ml	ml	NOUN
brj-23786	51	43	/	/	SYM
brj-23786	51	44	min	min	NOUN
brj-23786	51	45	to	to	PART
brj-23786	51	46	maintain	maintain	VERB
brj-23786	51	47	an	an	DET
brj-23786	51	48	ambient	ambient	ADJ
brj-23786	51	49	gas	gas	NOUN
brj-23786	51	50	environment	environment	NOUN
brj-23786	51	51	during	during	ADP
brj-23786	51	52	pyrolysis	pyrolysis	NOUN
brj-23786	51	53	.	.	PUNCT
brj-23786	52	1	parallel	parallel	ADJ
brj-23786	52	2	reaction	reaction	NOUN
brj-23786	52	3	kinetic	kinetic	NOUN
brj-23786	52	4	modelling	model	VERB
brj-23786	52	5	predictions	prediction	NOUN
brj-23786	52	6	the	the	DET
brj-23786	52	7	concept	concept	NOUN
brj-23786	52	8	of	of	ADP
brj-23786	52	9	kinetic	kinetic	ADJ
brj-23786	52	10	parallel	parallel	ADJ
brj-23786	52	11	reaction	reaction	NOUN
brj-23786	52	12	prediction	prediction	NOUN
brj-23786	52	13	aims	aim	VERB
brj-23786	52	14	to	to	PART
brj-23786	52	15	optimize	optimize	VERB
brj-23786	52	16	kinetic	kinetic	ADJ
brj-23786	52	17	parameters	parameter	NOUN
brj-23786	52	18	using	use	VERB
brj-23786	52	19	a	a	DET
brj-23786	52	20	kinetic	kinetic	ADJ
brj-23786	52	21	model	model	NOUN
brj-23786	52	22	combined	combine	VERB
brj-23786	52	23	with	with	ADP
brj-23786	52	24	an	an	DET
brj-23786	52	25	improved	improved	ADJ
brj-23786	52	26	dung	dung	NOUN
brj-23786	52	27	beetle	beetle	NOUN
brj-23786	52	28	optimization	optimization	NOUN
brj-23786	52	29	algorithm	algorithm	NOUN
brj-23786	52	30	with	with	ADP
brj-23786	52	31	tg	tg	PROPN
brj-23786	52	32	experimental	experimental	ADJ
brj-23786	52	33	data	datum	NOUN
brj-23786	52	34	.	.	PUNCT
brj-23786	53	1	the	the	DET
brj-23786	53	2	method	method	NOUN
brj-23786	53	3	aims	aim	VERB
brj-23786	53	4	to	to	PART
brj-23786	53	5	predict	predict	VERB
brj-23786	53	6	the	the	DET
brj-23786	53	7	pyrolysis	pyrolysis	NOUN
brj-23786	53	8	process	process	NOUN
brj-23786	53	9	of	of	ADP
brj-23786	53	10	pine	pine	ADJ
brj-23786	53	11	needles	needle	NOUN
brj-23786	53	12	by	by	ADP
brj-23786	53	13	utilizing	utilize	VERB
brj-23786	53	14	optimized	optimize	VERB
brj-23786	53	15	parameters	parameter	NOUN
brj-23786	53	16	and	and	CCONJ
brj-23786	53	17	comparing	compare	VERB
brj-23786	53	18	experimental	experimental	ADJ
brj-23786	53	19	results	result	NOUN
brj-23786	53	20	with	with	ADP
brj-23786	53	21	predicted	predict	VERB
brj-23786	53	22	outcomes	outcome	NOUN
brj-23786	53	23	to	to	PART
brj-23786	53	24	derive	derive	VERB
brj-23786	53	25	prediction	prediction	NOUN
brj-23786	53	26	deviations	deviation	NOUN
brj-23786	53	27	.	.	PUNCT
brj-23786	54	1	kinetic	kinetic	ADJ
brj-23786	54	2	modelling	modelling	NOUN
brj-23786	54	3	of	of	ADP
brj-23786	54	4	parallel	parallel	ADJ
brj-23786	54	5	reactions	reaction	NOUN
brj-23786	54	6	the	the	DET
brj-23786	54	7	decomposition	decomposition	NOUN
brj-23786	54	8	of	of	ADP
brj-23786	54	9	pine	pine	ADJ
brj-23786	54	10	needles	needle	NOUN
brj-23786	54	11	is	be	AUX
brj-23786	54	12	considered	consider	VERB
brj-23786	54	13	as	as	ADP
brj-23786	54	14	the	the	DET
brj-23786	54	15	sum	sum	NOUN
brj-23786	54	16	of	of	ADP
brj-23786	54	17	parallel	parallel	ADJ
brj-23786	54	18	reactions	reaction	NOUN
brj-23786	54	19	of	of	ADP
brj-23786	54	20	three	three	NUM
brj-23786	54	21	components	component	NOUN
brj-23786	54	22	:	:	PUNCT
brj-23786	54	23	hemicellulose	hemicellulose	NOUN
brj-23786	54	24	,	,	PUNCT
brj-23786	54	25	cellulose	cellulose	NOUN
brj-23786	54	26	and	and	CCONJ
brj-23786	54	27	lignin	lignin	PROPN
brj-23786	54	28	(	(	PUNCT
brj-23786	54	29	machmudah	machmudah	PROPN
brj-23786	54	30	et	et	PROPN
brj-23786	54	31	al	al	PROPN
brj-23786	54	32	.	.	PROPN
brj-23786	54	33	2020	2020	NUM
brj-23786	54	34	)	)	PUNCT
brj-23786	54	35	.	.	PUNCT
brj-23786	55	1	the	the	DET
brj-23786	55	2	parallel	parallel	ADJ
brj-23786	55	3	kinetics	kinetic	NOUN
brj-23786	55	4	scheme	scheme	NOUN
brj-23786	55	5	for	for	ADP
brj-23786	55	6	the	the	DET
brj-23786	55	7	three	three	NUM
brj-23786	55	8	components	component	NOUN
brj-23786	55	9	is	be	AUX
brj-23786	55	10	given	give	VERB
brj-23786	55	11	as	as	ADP
brj-23786	55	12	eq	eq	NOUN
brj-23786	55	13	.	.	PROPN
brj-23786	55	14	1	1	NUM
brj-23786	55	15	,	,	PUNCT
brj-23786	55	16	𝑐𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡𝑖	𝑐𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡𝑖	NOUN
brj-23786	55	17	→	→	SYM
brj-23786	55	18	(	(	PUNCT
brj-23786	55	19	𝑣𝑖)𝑣𝑜𝑙𝑎𝑡𝑖𝑙𝑒𝑠	𝑣𝑖)𝑣𝑜𝑙𝑎𝑡𝑖𝑙𝑒𝑠	NOUN
brj-23786	55	20	+	+	CCONJ
brj-23786	55	21	(	(	PUNCT
brj-23786	55	22	1	1	NUM
brj-23786	55	23	−	−	NOUN
brj-23786	55	24	𝑣𝑖)𝑐ℎ𝑎𝑟	𝑣𝑖)𝑐ℎ𝑎𝑟	NOUN
brj-23786	55	25	(	(	PUNCT
brj-23786	55	26	1	1	NUM
brj-23786	55	27	)	)	PUNCT
brj-23786	55	28	where	where	SCONJ
brj-23786	55	29	vi	vi	PROPN
brj-23786	55	30	represents	represent	VERB
brj-23786	55	31	the	the	DET
brj-23786	55	32	volatile	volatile	ADJ
brj-23786	55	33	yield	yield	NOUN
brj-23786	55	34	of	of	ADP
brj-23786	55	35	each	each	DET
brj-23786	55	36	component	component	NOUN
brj-23786	55	37	reaction	reaction	NOUN
brj-23786	55	38	.	.	PUNCT
brj-23786	56	1	according	accord	VERB
brj-23786	56	2	to	to	ADP
brj-23786	56	3	the	the	DET
brj-23786	56	4	arrhenius	arrhenius	PROPN
brj-23786	56	5	equation	equation	NOUN
brj-23786	56	6	,	,	PUNCT
brj-23786	56	7	it	it	PRON
brj-23786	56	8	is	be	AUX
brj-23786	56	9	assumed	assume	VERB
brj-23786	56	10	that	that	SCONJ
brj-23786	56	11	the	the	DET
brj-23786	56	12	reaction	reaction	NOUN
brj-23786	56	13	mechanisms	mechanism	NOUN
brj-23786	56	14	of	of	ADP
brj-23786	56	15	each	each	DET
brj-23786	56	16	component	component	NOUN
brj-23786	56	17	are	be	AUX
brj-23786	56	18	all	all	PRON
brj-23786	56	19	of	of	ADP
brj-23786	56	20	one	one	NUM
brj-23786	56	21	order	order	NOUN
brj-23786	56	22	.	.	PUNCT
brj-23786	57	1	the	the	DET
brj-23786	57	2	reaction	reaction	NOUN
brj-23786	57	3	rates	rate	NOUN
brj-23786	57	4	of	of	ADP
brj-23786	57	5	these	these	DET
brj-23786	57	6	three	three	NUM
brj-23786	57	7	components	component	NOUN
brj-23786	57	8	can	can	AUX
brj-23786	57	9	be	be	AUX
brj-23786	57	10	expressed	express	VERB
brj-23786	57	11	as	as	ADP
brj-23786	57	12	eq	eq	NOUN
brj-23786	57	13	.	.	PROPN
brj-23786	57	14	2	2	NUM
brj-23786	57	15	,	,	PUNCT
brj-23786	57	16	d𝛼i	d𝛼i	VERB
brj-23786	57	17	d𝑇	d𝑇	NOUN
brj-23786	58	1	=	=	PUNCT
brj-23786	58	2	𝐴i	𝐴i	PROPN
brj-23786	58	3	𝛽	𝛽	PROPN
brj-23786	58	4	e−	e−	PROPN
brj-23786	58	5	𝐸i	𝐸i	PROPN
brj-23786	58	6	𝑅t(1	𝑅t(1	NOUN
brj-23786	59	1	−	−	PROPN
brj-23786	59	2	𝛼i	𝛼i	PROPN
brj-23786	59	3	)	)	PUNCT
brj-23786	60	1	i	i	PROPN
brj-23786	60	2	=	=	PUNCT
brj-23786	60	3	1~3	1~3	NUM
brj-23786	60	4	(	(	PUNCT
brj-23786	60	5	2	2	NUM
brj-23786	60	6	)	)	PUNCT
brj-23786	60	7	where	where	SCONJ
brj-23786	60	8	𝛼i	𝛼i	PROPN
brj-23786	60	9	=	=	PUNCT
brj-23786	60	10	𝑚i0−𝑚i	𝑚i0−𝑚i	VERB
brj-23786	60	11	𝑚i0−𝑚i∞	𝑚i0−𝑚i∞	ADJ
brj-23786	60	12	denotes	denote	NOUN
brj-23786	60	13	the	the	DET
brj-23786	60	14	degree	degree	NOUN
brj-23786	60	15	of	of	ADP
brj-23786	60	16	response	response	NOUN
brj-23786	60	17	of	of	ADP
brj-23786	60	18	the	the	DET
brj-23786	60	19	i	i	PROPN
brj-23786	60	20	-	-	PUNCT
brj-23786	60	21	th	th	VERB
brj-23786	60	22	component	component	NOUN
brj-23786	60	23	.	.	PUNCT
brj-23786	61	1	the	the	DET
brj-23786	61	2	conversion	conversion	NOUN
brj-23786	61	3	degree	degree	NOUN
brj-23786	61	4	(	(	PUNCT
brj-23786	61	5	a	a	X
brj-23786	61	6	)	)	PUNCT
brj-23786	61	7	can	can	AUX
brj-23786	61	8	be	be	AUX
brj-23786	61	9	defined	define	VERB
brj-23786	61	10	as	as	SCONJ
brj-23786	61	11	follows	follow	VERB
brj-23786	61	12	,	,	PUNCT
brj-23786	61	13	𝛼	𝛼	NOUN
brj-23786	61	14	=	=	SYM
brj-23786	61	15	𝑚0−𝑚	𝑚0−𝑚	PROPN
brj-23786	61	16	𝑚0−𝑚∞	𝑚0−𝑚∞	PUNCT
brj-23786	61	17	(	(	PUNCT
brj-23786	61	18	3	3	NUM
brj-23786	61	19	)	)	PUNCT
brj-23786	61	20	where	where	SCONJ
brj-23786	61	21	𝑚0	𝑚0	NOUN
brj-23786	61	22	and	and	CCONJ
brj-23786	61	23	𝑚∞	𝑚∞	PROPN
brj-23786	61	24	represent	represent	VERB
brj-23786	61	25	the	the	DET
brj-23786	61	26	initial	initial	ADJ
brj-23786	61	27	and	and	CCONJ
brj-23786	61	28	final	final	ADJ
brj-23786	61	29	sample	sample	NOUN
brj-23786	61	30	masses	masse	NOUN
brj-23786	61	31	,	,	PUNCT
brj-23786	61	32	respectively	respectively	ADV
brj-23786	61	33	.	.	PUNCT
brj-23786	62	1	the	the	DET
brj-23786	62	2	total	total	ADJ
brj-23786	62	3	conversion	conversion	NOUN
brj-23786	62	4	degree	degree	NOUN
brj-23786	62	5	is	be	AUX
brj-23786	62	6	defined	define	VERB
brj-23786	62	7	as	as	ADP
brj-23786	62	8	the	the	DET
brj-23786	62	9	sum	sum	NOUN
brj-23786	62	10	of	of	ADP
brj-23786	62	11	individual	individual	ADJ
brj-23786	62	12	component	component	NOUN
brj-23786	62	13	conversions	conversion	NOUN
brj-23786	62	14	and	and	CCONJ
brj-23786	62	15	was	be	AUX
brj-23786	62	16	calculated	calculate	VERB
brj-23786	62	17	as	as	SCONJ
brj-23786	62	18	follows	follow	VERB
brj-23786	62	19	,	,	PUNCT
brj-23786	62	20	𝛼	𝛼	X
brj-23786	62	21	=	=	PUNCT
brj-23786	62	22	∑	∑	PUNCT
brj-23786	63	1	𝑟i(𝑚i0−𝑚i)i	𝑟i(𝑚i0−𝑚i)i	X
brj-23786	63	2	𝑚i0−𝑚i∞	𝑚i0−𝑚i∞	NOUN
brj-23786	63	3	=	=	PUNCT
brj-23786	63	4	∑	∑	PUNCT
brj-23786	63	5	𝑟𝑖𝛼𝑖𝑖	𝑟𝑖𝛼𝑖𝑖	NOUN
brj-23786	63	6	(	(	PUNCT
brj-23786	63	7	4	4	NUM
brj-23786	63	8	)	)	PUNCT
brj-23786	63	9	where	where	SCONJ
brj-23786	63	10	𝑟𝑖	𝑟𝑖	PRON
brj-23786	63	11	represents	represent	VERB
brj-23786	63	12	the	the	DET
brj-23786	63	13	initial	initial	ADJ
brj-23786	63	14	mass	mass	ADJ
brj-23786	63	15	fraction	fraction	NOUN
brj-23786	63	16	of	of	ADP
brj-23786	63	17	component	component	NOUN
brj-23786	63	18	i	i	PROPN
brj-23786	63	19	,	,	PUNCT
brj-23786	63	20	and	and	CCONJ
brj-23786	63	21	∑	∑	ADV
brj-23786	63	22	𝑟𝑖	𝑟𝑖	PRON
brj-23786	63	23	=	=	SYM
brj-23786	63	24	1𝑖	1𝑖	PROPN
brj-23786	63	25	,	,	PUNCT
brj-23786	63	26	the	the	DET
brj-23786	63	27	overall	overall	ADJ
brj-23786	63	28	kinetic	kinetic	ADJ
brj-23786	63	29	equation	equation	NOUN
brj-23786	63	30	for	for	ADP
brj-23786	63	31	the	the	DET
brj-23786	63	32	three	three	NUM
brj-23786	63	33	-	-	PUNCT
brj-23786	63	34	component	component	NOUN
brj-23786	63	35	can	can	AUX
brj-23786	63	36	be	be	AUX
brj-23786	63	37	expressed	express	VERB
brj-23786	63	38	as	as	ADP
brj-23786	63	39	eq	eq	NOUN
brj-23786	63	40	.	.	PROPN
brj-23786	63	41	5	5	NUM
brj-23786	63	42	,	,	PUNCT
brj-23786	63	43	peer	peer	NOUN
brj-23786	63	44	-	-	PUNCT
brj-23786	63	45	reviewed	review	VERB
brj-23786	63	46	article	article	NOUN
brj-23786	63	47	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	64	1	xu	xu	PROPN
brj-23786	64	2	et	et	PROPN
brj-23786	64	3	al	al	PROPN
brj-23786	64	4	.	.	PROPN
brj-23786	64	5	(	(	PUNCT
brj-23786	64	6	2024	2024	NUM
brj-23786	64	7	)	)	PUNCT
brj-23786	64	8	.	.	PUNCT
brj-23786	65	1	“	"	PUNCT
brj-23786	65	2	pyrolysis	pyrolysis	NOUN
brj-23786	65	3	kinetics	kinetic	NOUN
brj-23786	65	4	with	with	ADP
brj-23786	65	5	ann	ann	PROPN
brj-23786	65	6	,	,	PUNCT
brj-23786	65	7	”	"	PUNCT
brj-23786	65	8	bioresources	bioresource	NOUN
brj-23786	65	9	19(4	19(4	NUM
brj-23786	65	10	)	)	PUNCT
brj-23786	65	11	,	,	PUNCT
brj-23786	65	12	7513	7513	NUM
brj-23786	65	13	-	-	SYM
brj-23786	65	14	7529	7529	NUM
brj-23786	65	15	.	.	PUNCT
brj-23786	66	1	7516	7516	NUM
brj-23786	66	2	d𝛼	d𝛼	NOUN
brj-23786	66	3	d𝑇	d𝑇	NOUN
brj-23786	66	4	=	=	PUNCT
brj-23786	66	5	∑	∑	PUNCT
brj-23786	66	6	𝑟ii	𝑟ii	NOUN
brj-23786	66	7	𝐴i	𝐴i	PROPN
brj-23786	66	8	𝛽	𝛽	PROPN
brj-23786	66	9	e−	e−	PROPN
brj-23786	66	10	𝐸i	𝐸i	PROPN
brj-23786	66	11	rt(1	rt(1	PROPN
brj-23786	66	12	−	−	PROPN
brj-23786	66	13	𝛼i	𝛼i	NOUN
brj-23786	66	14	)	)	PUNCT
brj-23786	66	15	i	i	PROPN
brj-23786	67	1	=	=	SYM
brj-23786	67	2	1~3	1~3	NUM
brj-23786	67	3	(	(	PUNCT
brj-23786	67	4	5	5	NUM
brj-23786	67	5	)	)	PUNCT
brj-23786	67	6	in	in	ADP
brj-23786	67	7	eq	eq	ADP
brj-23786	67	8	.	.	PROPN
brj-23786	67	9	5	5	NUM
brj-23786	67	10	,	,	PUNCT
brj-23786	67	11	eight	eight	NUM
brj-23786	67	12	unknown	unknown	ADJ
brj-23786	67	13	parameters	parameter	NOUN
brj-23786	67	14	must	must	AUX
brj-23786	67	15	be	be	AUX
brj-23786	67	16	determined	determine	VERB
brj-23786	67	17	to	to	PART
brj-23786	67	18	fit	fit	VERB
brj-23786	67	19	the	the	DET
brj-23786	67	20	experimental	experimental	ADJ
brj-23786	67	21	data	datum	NOUN
brj-23786	67	22	.	.	PUNCT
brj-23786	68	1	the	the	DET
brj-23786	68	2	objective	objective	NOUN
brj-23786	68	3	of	of	ADP
brj-23786	68	4	the	the	DET
brj-23786	68	5	optimization	optimization	NOUN
brj-23786	68	6	method	method	NOUN
brj-23786	68	7	is	be	AUX
brj-23786	68	8	to	to	PART
brj-23786	68	9	minimize	minimize	VERB
brj-23786	68	10	the	the	DET
brj-23786	68	11	difference	difference	NOUN
brj-23786	68	12	between	between	ADP
brj-23786	68	13	the	the	DET
brj-23786	68	14	experimental	experimental	ADJ
brj-23786	68	15	and	and	CCONJ
brj-23786	68	16	simulated	simulated	ADJ
brj-23786	68	17	values	value	NOUN
brj-23786	68	18	.	.	PUNCT
brj-23786	69	1	this	this	PRON
brj-23786	69	2	is	be	AUX
brj-23786	69	3	achieved	achieve	VERB
brj-23786	69	4	by	by	ADP
brj-23786	69	5	minimizing	minimize	VERB
brj-23786	69	6	the	the	DET
brj-23786	69	7	sum	sum	NOUN
brj-23786	69	8	of	of	ADP
brj-23786	69	9	the	the	DET
brj-23786	69	10	squared	square	VERB
brj-23786	69	11	differences	difference	NOUN
brj-23786	69	12	between	between	ADP
brj-23786	69	13	the	the	DET
brj-23786	69	14	experimental	experimental	ADJ
brj-23786	69	15	and	and	CCONJ
brj-23786	69	16	simulated	simulated	ADJ
brj-23786	69	17	mass	mass	NOUN
brj-23786	69	18	loss	loss	NOUN
brj-23786	69	19	values	value	NOUN
brj-23786	69	20	at	at	ADP
brj-23786	69	21	all	all	DET
brj-23786	69	22	heating	heating	NOUN
brj-23786	69	23	rates	rate	NOUN
brj-23786	69	24	,	,	PUNCT
brj-23786	69	25	as	as	SCONJ
brj-23786	69	26	shown	show	VERB
brj-23786	69	27	in	in	ADP
brj-23786	69	28	eq	eq	ADP
brj-23786	69	29	.	.	PROPN
brj-23786	69	30	6	6	NUM
brj-23786	69	31	,	,	PUNCT
brj-23786	69	32	𝑆𝐷𝑇𝐺	𝑆𝐷𝑇𝐺	PROPN
brj-23786	69	33	=	=	PUNCT
brj-23786	69	34	∑	∑	PUNCT
brj-23786	69	35	𝑆𝑗	𝑆𝑗	PROPN
brj-23786	69	36	=	=	PUNCT
brj-23786	69	37	∑	∑	PUNCT
brj-23786	69	38	∑	∑	PUNCT
brj-23786	69	39	[	[	X
brj-23786	69	40	(	(	PUNCT
brj-23786	69	41	𝑑𝛼	𝑑𝛼	ADP
brj-23786	69	42	𝑑𝑇	𝑑𝑇	PROPN
brj-23786	69	43	)	)	PUNCT
brj-23786	70	1	𝑗,𝑘	𝑗,𝑘	INTJ
brj-23786	70	2	𝑒𝑥𝑝	𝑒𝑥𝑝	INTJ
brj-23786	70	3	−	−	PROPN
brj-23786	70	4	(	(	PUNCT
brj-23786	70	5	𝑑𝛼	𝑑𝛼	ADP
brj-23786	70	6	𝑑𝑇	𝑑𝑇	PROPN
brj-23786	70	7	)	)	PUNCT
brj-23786	71	1	𝑗,𝑘	𝑗,𝑘	VERB
brj-23786	71	2	𝑠𝑖𝑚𝑢]2	𝑠𝑖𝑚𝑢]2	NOUN
brj-23786	71	3	+	+	CCONJ
brj-23786	71	4	∑	∑	PROPN
brj-23786	71	5	∑	∑	PUNCT
brj-23786	71	6	[	[	X
brj-23786	71	7	(	(	PUNCT
brj-23786	71	8	𝛼)𝑗,𝑘	𝛼)𝑗,𝑘	NOUN
brj-23786	71	9	𝑒𝑥𝑝	𝑒𝑥𝑝	INTJ
brj-23786	71	10	−	−	PROPN
brj-23786	72	1	(	(	PUNCT
brj-23786	72	2	𝛼)𝑗,𝑘	𝛼)𝑗,𝑘	NOUN
brj-23786	72	3	𝑠𝑖𝑚𝑢]2	𝑠𝑖𝑚𝑢]2	AUX
brj-23786	72	4	𝑘𝑗𝑘𝑗𝑗	𝑘𝑗𝑘𝑗𝑗	NOUN
brj-23786	72	5	(	(	PUNCT
brj-23786	72	6	6	6	NUM
brj-23786	72	7	)	)	PUNCT
brj-23786	72	8	here	here	ADV
brj-23786	72	9	the	the	DET
brj-23786	72	10	superscripts	superscript	NOUN
brj-23786	72	11	“	"	PUNCT
brj-23786	72	12	exp	exp	NOUN
brj-23786	72	13	”	"	PUNCT
brj-23786	72	14	and	and	CCONJ
brj-23786	72	15	“	"	PUNCT
brj-23786	72	16	simu	simu	NOUN
brj-23786	72	17	”	"	PUNCT
brj-23786	72	18	represent	represent	VERB
brj-23786	72	19	the	the	DET
brj-23786	72	20	experimental	experimental	ADJ
brj-23786	72	21	and	and	CCONJ
brj-23786	72	22	simulated	simulated	ADJ
brj-23786	72	23	values	value	NOUN
brj-23786	72	24	,	,	PUNCT
brj-23786	72	25	respectively	respectively	ADV
brj-23786	72	26	.	.	PUNCT
brj-23786	73	1	the	the	DET
brj-23786	73	2	index	index	NOUN
brj-23786	73	3	“	"	PUNCT
brj-23786	73	4	j	j	NOUN
brj-23786	73	5	”	"	PUNCT
brj-23786	73	6	represents	represent	VERB
brj-23786	73	7	the	the	DET
brj-23786	73	8	number	number	NOUN
brj-23786	73	9	of	of	ADP
brj-23786	73	10	heating	heating	NOUN
brj-23786	73	11	rates	rate	NOUN
brj-23786	73	12	,	,	PUNCT
brj-23786	73	13	and	and	CCONJ
brj-23786	73	14	“	"	PUNCT
brj-23786	73	15	k	k	X
brj-23786	73	16	”	"	PUNCT
brj-23786	73	17	represents	represent	VERB
brj-23786	73	18	the	the	DET
brj-23786	73	19	number	number	NOUN
brj-23786	73	20	of	of	ADP
brj-23786	73	21	data	datum	NOUN
brj-23786	73	22	points	point	NOUN
brj-23786	73	23	in	in	ADP
brj-23786	73	24	the	the	DET
brj-23786	73	25	experiment	experiment	NOUN
brj-23786	73	26	.	.	PUNCT
brj-23786	74	1	in	in	ADP
brj-23786	74	2	optimization	optimization	NOUN
brj-23786	74	3	computations	computation	NOUN
brj-23786	74	4	,	,	PUNCT
brj-23786	74	5	the	the	DET
brj-23786	74	6	parameters	parameter	NOUN
brj-23786	74	7	r²	r²	VERB
brj-23786	74	8	and	and	CCONJ
brj-23786	74	9	sep	sep	PROPN
brj-23786	74	10	were	be	AUX
brj-23786	74	11	used	use	VERB
brj-23786	74	12	to	to	PART
brj-23786	74	13	assess	assess	VERB
brj-23786	74	14	the	the	DET
brj-23786	74	15	discrepancy	discrepancy	NOUN
brj-23786	74	16	between	between	ADP
brj-23786	74	17	experimental	experimental	ADJ
brj-23786	74	18	and	and	CCONJ
brj-23786	74	19	simulated	simulated	ADJ
brj-23786	74	20	values	value	NOUN
brj-23786	74	21	.	.	PUNCT
brj-23786	75	1	improved	improve	VERB
brj-23786	75	2	dung	dung	NOUN
brj-23786	75	3	beetle	beetle	NOUN
brj-23786	75	4	optimization	optimization	NOUN
brj-23786	75	5	algorithm	algorithm	NOUN
brj-23786	75	6	the	the	DET
brj-23786	75	7	dung	dung	NOUN
brj-23786	75	8	beetle	beetle	NOUN
brj-23786	75	9	optimization	optimization	NOUN
brj-23786	75	10	algorithm	algorithm	NOUN
brj-23786	75	11	(	(	PUNCT
brj-23786	75	12	dbo	dbo	NOUN
brj-23786	75	13	)	)	PUNCT
brj-23786	75	14	is	be	AUX
brj-23786	75	15	a	a	DET
brj-23786	75	16	mathematical	mathematical	ADJ
brj-23786	75	17	model	model	NOUN
brj-23786	75	18	inspired	inspire	VERB
brj-23786	75	19	by	by	ADP
brj-23786	75	20	the	the	DET
brj-23786	75	21	behavior	behavior	NOUN
brj-23786	75	22	of	of	ADP
brj-23786	75	23	dung	dung	NOUN
brj-23786	75	24	beetles	beetle	NOUN
brj-23786	75	25	,	,	PUNCT
brj-23786	75	26	including	include	VERB
brj-23786	75	27	rolling	roll	VERB
brj-23786	75	28	balls	ball	NOUN
brj-23786	75	29	,	,	PUNCT
brj-23786	75	30	dancing	dancing	NOUN
brj-23786	75	31	,	,	PUNCT
brj-23786	75	32	foraging	foraging	NOUN
brj-23786	75	33	,	,	PUNCT
brj-23786	75	34	stealing	stealing	NOUN
brj-23786	75	35	,	,	PUNCT
brj-23786	75	36	and	and	CCONJ
brj-23786	75	37	breeding	breeding	NOUN
brj-23786	75	38	.	.	PUNCT
brj-23786	76	1	the	the	DET
brj-23786	76	2	algorithm	algorithm	NOUN
brj-23786	76	3	performs	perform	VERB
brj-23786	76	4	an	an	DET
brj-23786	76	5	iterative	iterative	NOUN
brj-23786	76	6	update	update	NOUN
brj-23786	76	7	through	through	ADP
brj-23786	76	8	the	the	DET
brj-23786	76	9	following	follow	VERB
brj-23786	76	10	steps	step	NOUN
brj-23786	76	11	:	:	PUNCT
brj-23786	76	12	initializing	initialize	VERB
brj-23786	76	13	the	the	DET
brj-23786	76	14	dung	dung	NOUN
brj-23786	76	15	beetle	beetle	NOUN
brj-23786	76	16	population	population	NOUN
brj-23786	76	17	,	,	PUNCT
brj-23786	76	18	evaluating	evaluate	VERB
brj-23786	76	19	the	the	DET
brj-23786	76	20	fitness	fitness	NOUN
brj-23786	76	21	of	of	ADP
brj-23786	76	22	individual	individual	ADJ
brj-23786	76	23	dung	dung	NOUN
brj-23786	76	24	beetles	beetle	NOUN
brj-23786	76	25	,	,	PUNCT
brj-23786	76	26	updating	update	VERB
brj-23786	76	27	the	the	DET
brj-23786	76	28	position	position	NOUN
brj-23786	76	29	and	and	CCONJ
brj-23786	76	30	orientation	orientation	NOUN
brj-23786	76	31	of	of	ADP
brj-23786	76	32	the	the	DET
brj-23786	76	33	dung	dung	NOUN
brj-23786	76	34	beetles	beetle	NOUN
brj-23786	76	35	,	,	PUNCT
brj-23786	76	36	and	and	CCONJ
brj-23786	76	37	finally	finally	ADV
brj-23786	76	38	outputting	output	VERB
brj-23786	76	39	the	the	DET
brj-23786	76	40	optimal	optimal	ADJ
brj-23786	76	41	solution	solution	NOUN
brj-23786	76	42	(	(	PUNCT
brj-23786	76	43	xue	xue	PROPN
brj-23786	76	44	and	and	CCONJ
brj-23786	76	45	shen	shen	PROPN
brj-23786	76	46	2022	2022	NUM
brj-23786	76	47	;	;	PUNCT
brj-23786	76	48	zhu	zhu	PROPN
brj-23786	76	49	et	et	PROPN
brj-23786	76	50	al	al	PROPN
brj-23786	76	51	.	.	PROPN
brj-23786	76	52	2024	2024	NUM
brj-23786	76	53	)	)	PUNCT
brj-23786	76	54	.	.	PUNCT
brj-23786	77	1	however	however	ADV
brj-23786	77	2	,	,	PUNCT
brj-23786	77	3	the	the	DET
brj-23786	77	4	dung	dung	NOUN
brj-23786	77	5	beetle	beetle	NOUN
brj-23786	77	6	optimization	optimization	NOUN
brj-23786	77	7	algorithm	algorithm	NOUN
brj-23786	77	8	has	have	VERB
brj-23786	77	9	limitations	limitation	NOUN
brj-23786	77	10	in	in	ADP
brj-23786	77	11	global	global	ADJ
brj-23786	77	12	search	search	NOUN
brj-23786	77	13	and	and	CCONJ
brj-23786	77	14	tends	tend	VERB
brj-23786	77	15	to	to	PART
brj-23786	77	16	converge	converge	VERB
brj-23786	77	17	slowly	slowly	ADV
brj-23786	77	18	when	when	SCONJ
brj-23786	77	19	dealing	deal	VERB
brj-23786	77	20	with	with	ADP
brj-23786	77	21	complex	complex	ADJ
brj-23786	77	22	optimization	optimization	NOUN
brj-23786	77	23	problems	problem	NOUN
brj-23786	77	24	.	.	PUNCT
brj-23786	78	1	therefore	therefore	ADV
brj-23786	78	2	,	,	PUNCT
brj-23786	78	3	this	this	DET
brj-23786	78	4	study	study	NOUN
brj-23786	78	5	proposes	propose	VERB
brj-23786	78	6	an	an	DET
brj-23786	78	7	improved	improved	ADJ
brj-23786	78	8	dung	dung	NOUN
brj-23786	78	9	beetle	beetle	NOUN
brj-23786	78	10	optimization	optimization	NOUN
brj-23786	78	11	algorithm	algorithm	NOUN
brj-23786	78	12	(	(	PUNCT
brj-23786	78	13	shen	shen	PROPN
brj-23786	78	14	et	et	PROPN
brj-23786	78	15	al	al	PROPN
brj-23786	78	16	.	.	PROPN
brj-23786	78	17	2023	2023	NUM
brj-23786	78	18	)	)	PUNCT
brj-23786	78	19	.	.	PUNCT
brj-23786	79	1	the	the	DET
brj-23786	79	2	improved	improve	VERB
brj-23786	79	3	dung	dung	NOUN
brj-23786	79	4	beetle	beetle	NOUN
brj-23786	79	5	optimization	optimization	NOUN
brj-23786	79	6	algorithm	algorithm	NOUN
brj-23786	79	7	enhanced	enhance	VERB
brj-23786	79	8	the	the	DET
brj-23786	79	9	convergence	convergence	NOUN
brj-23786	79	10	speed	speed	NOUN
brj-23786	79	11	and	and	CCONJ
brj-23786	79	12	accuracy	accuracy	NOUN
brj-23786	79	13	of	of	ADP
brj-23786	79	14	the	the	DET
brj-23786	79	15	search	search	NOUN
brj-23786	79	16	process	process	NOUN
brj-23786	79	17	by	by	ADP
brj-23786	79	18	introducing	introduce	VERB
brj-23786	79	19	an	an	DET
brj-23786	79	20	initialized	initialize	VERB
brj-23786	79	21	logistic	logistic	ADJ
brj-23786	79	22	chaos	chaos	NOUN
brj-23786	79	23	mapping	mapping	NOUN
brj-23786	79	24	population	population	NOUN
brj-23786	79	25	and	and	CCONJ
brj-23786	79	26	improving	improve	VERB
brj-23786	79	27	the	the	DET
brj-23786	79	28	position	position	NOUN
brj-23786	79	29	update	update	NOUN
brj-23786	79	30	mechanism	mechanism	NOUN
brj-23786	79	31	of	of	ADP
brj-23786	79	32	individuals	individual	NOUN
brj-23786	79	33	in	in	ADP
brj-23786	79	34	the	the	DET
brj-23786	79	35	population	population	NOUN
brj-23786	79	36	using	use	VERB
brj-23786	79	37	the	the	DET
brj-23786	79	38	sinusoidal	sinusoidal	ADJ
brj-23786	79	39	algorithm	algorithm	NOUN
brj-23786	79	40	(	(	PUNCT
brj-23786	79	41	msa	msa	PROPN
brj-23786	79	42	)	)	PUNCT
brj-23786	79	43	.	.	PUNCT
brj-23786	80	1	in	in	ADP
brj-23786	80	2	addition	addition	NOUN
brj-23786	80	3	,	,	PUNCT
brj-23786	80	4	an	an	DET
brj-23786	80	5	adaptive	adaptive	ADJ
brj-23786	80	6	gauss	gauss	ADJ
brj-23786	80	7	-	-	PUNCT
brj-23786	80	8	cauchy	cauchy	NOUN
brj-23786	80	9	perturbation	perturbation	NOUN
brj-23786	80	10	modification	modification	NOUN
brj-23786	80	11	strategy	strategy	NOUN
brj-23786	80	12	was	be	AUX
brj-23786	80	13	used	use	VERB
brj-23786	80	14	to	to	PART
brj-23786	80	15	enhance	enhance	VERB
brj-23786	80	16	the	the	DET
brj-23786	80	17	adaptability	adaptability	NOUN
brj-23786	80	18	and	and	CCONJ
brj-23786	80	19	robustness	robustness	NOUN
brj-23786	80	20	of	of	ADP
brj-23786	80	21	the	the	DET
brj-23786	80	22	model	model	NOUN
brj-23786	80	23	for	for	ADP
brj-23786	80	24	complex	complex	ADJ
brj-23786	80	25	problems	problem	NOUN
brj-23786	80	26	.	.	PUNCT
brj-23786	81	1	compared	compare	VERB
brj-23786	81	2	to	to	ADP
brj-23786	81	3	the	the	DET
brj-23786	81	4	traditional	traditional	ADJ
brj-23786	81	5	dung	dung	NOUN
brj-23786	81	6	beetle	beetle	NOUN
brj-23786	81	7	algorithm	algorithm	NOUN
brj-23786	81	8	,	,	PUNCT
brj-23786	81	9	the	the	DET
brj-23786	81	10	msadbo	msadbo	NOUN
brj-23786	81	11	algorithm	algorithm	PROPN
brj-23786	81	12	demonstrates	demonstrate	VERB
brj-23786	81	13	a	a	DET
brj-23786	81	14	significant	significant	ADJ
brj-23786	81	15	improvement	improvement	NOUN
brj-23786	81	16	in	in	ADP
brj-23786	81	17	search	search	NOUN
brj-23786	81	18	efficiency	efficiency	NOUN
brj-23786	81	19	and	and	CCONJ
brj-23786	81	20	solution	solution	NOUN
brj-23786	81	21	quality	quality	NOUN
brj-23786	81	22	(	(	PUNCT
brj-23786	81	23	guo	guo	PROPN
brj-23786	81	24	et	et	PROPN
brj-23786	81	25	al	al	PROPN
brj-23786	81	26	.	.	PROPN
brj-23786	81	27	2023	2023	NUM
brj-23786	81	28	)	)	PUNCT
brj-23786	81	29	.	.	PUNCT
brj-23786	82	1	artificial	artificial	ADJ
brj-23786	82	2	neural	neural	ADJ
brj-23786	82	3	network	network	NOUN
brj-23786	82	4	(	(	PUNCT
brj-23786	82	5	ann	ann	PROPN
brj-23786	82	6	)	)	PUNCT
brj-23786	82	7	model	model	NOUN
brj-23786	82	8	predictions	prediction	NOUN
brj-23786	82	9	the	the	DET
brj-23786	82	10	deviations	deviation	NOUN
brj-23786	82	11	predicted	predict	VERB
brj-23786	82	12	by	by	ADP
brj-23786	82	13	the	the	DET
brj-23786	82	14	kinetic	kinetic	ADJ
brj-23786	82	15	model	model	NOUN
brj-23786	82	16	based	base	VERB
brj-23786	82	17	on	on	ADP
brj-23786	82	18	chemical	chemical	ADJ
brj-23786	82	19	reactions	reaction	NOUN
brj-23786	82	20	were	be	AUX
brj-23786	82	21	used	use	VERB
brj-23786	82	22	as	as	ADP
brj-23786	82	23	training	training	NOUN
brj-23786	82	24	inputs	input	NOUN
brj-23786	82	25	for	for	ADP
brj-23786	82	26	the	the	DET
brj-23786	82	27	neural	neural	ADJ
brj-23786	82	28	network	network	NOUN
brj-23786	82	29	.	.	PUNCT
brj-23786	83	1	a	a	DET
brj-23786	83	2	genetic	genetic	ADJ
brj-23786	83	3	algorithm	algorithm	NOUN
brj-23786	83	4	was	be	AUX
brj-23786	83	5	then	then	ADV
brj-23786	83	6	introduced	introduce	VERB
brj-23786	83	7	to	to	PART
brj-23786	83	8	construct	construct	VERB
brj-23786	83	9	a	a	DET
brj-23786	83	10	data	data	NOUN
brj-23786	83	11	-	-	PUNCT
brj-23786	83	12	driven	drive	VERB
brj-23786	83	13	back	back	NOUN
brj-23786	83	14	-	-	PUNCT
brj-23786	83	15	propagation	propagation	NOUN
brj-23786	83	16	neural	neural	ADJ
brj-23786	83	17	network	network	NOUN
brj-23786	83	18	model	model	NOUN
brj-23786	83	19	to	to	PART
brj-23786	83	20	predict	predict	VERB
brj-23786	83	21	the	the	DET
brj-23786	83	22	errors	error	NOUN
brj-23786	83	23	calculated	calculate	VERB
brj-23786	83	24	by	by	ADP
brj-23786	83	25	the	the	DET
brj-23786	83	26	kinetic	kinetic	ADJ
brj-23786	83	27	model	model	NOUN
brj-23786	83	28	.	.	PUNCT
brj-23786	84	1	back	back	ADV
brj-23786	84	2	propagating	propagate	VERB
brj-23786	84	3	artificial	artificial	ADJ
brj-23786	84	4	neutral	neutral	ADJ
brj-23786	84	5	net	net	NOUN
brj-23786	84	6	(	(	PUNCT
brj-23786	84	7	bp	bp	PROPN
brj-23786	84	8	-	-	PUNCT
brj-23786	84	9	ann	ann	PROPN
brj-23786	84	10	)	)	PUNCT
brj-23786	84	11	model	model	NOUN
brj-23786	84	12	bp	bp	PROPN
brj-23786	84	13	-	-	PUNCT
brj-23786	84	14	ann	ann	PROPN
brj-23786	84	15	,	,	PUNCT
brj-23786	84	16	a	a	DET
brj-23786	84	17	multilayer	multilayer	ADJ
brj-23786	84	18	neural	neural	ADJ
brj-23786	84	19	network	network	NOUN
brj-23786	84	20	using	use	VERB
brj-23786	84	21	an	an	DET
brj-23786	84	22	error	error	NOUN
brj-23786	84	23	backpropagation	backpropagation	NOUN
brj-23786	84	24	algorithm	algorithm	NOUN
brj-23786	84	25	,	,	PUNCT
brj-23786	84	26	is	be	AUX
brj-23786	84	27	renowned	renowned	ADJ
brj-23786	84	28	for	for	ADP
brj-23786	84	29	its	its	PRON
brj-23786	84	30	powerful	powerful	ADJ
brj-23786	84	31	learning	learning	NOUN
brj-23786	84	32	and	and	CCONJ
brj-23786	84	33	nonlinear	nonlinear	ADJ
brj-23786	84	34	mapping	mapping	NOUN
brj-23786	84	35	capabilities	capability	NOUN
brj-23786	84	36	,	,	PUNCT
brj-23786	84	37	making	make	VERB
brj-23786	84	38	it	it	PRON
brj-23786	84	39	one	one	NUM
brj-23786	84	40	of	of	ADP
brj-23786	84	41	the	the	DET
brj-23786	84	42	bp	bp	PROPN
brj-23786	84	43	-	-	PUNCT
brj-23786	84	44	ann	ann	PROPN
brj-23786	84	45	consists	consist	VERB
brj-23786	84	46	of	of	ADP
brj-23786	84	47	an	an	DET
brj-23786	84	48	input	input	NOUN
brj-23786	84	49	layer	layer	NOUN
brj-23786	84	50	,	,	PUNCT
brj-23786	84	51	hidden	hidden	ADJ
brj-23786	84	52	layers	layer	NOUN
brj-23786	84	53	,	,	PUNCT
brj-23786	84	54	and	and	CCONJ
brj-23786	84	55	an	an	DET
brj-23786	84	56	output	output	NOUN
brj-23786	84	57	layer	layer	NOUN
brj-23786	84	58	,	,	PUNCT
brj-23786	84	59	where	where	SCONJ
brj-23786	84	60	information	information	NOUN
brj-23786	84	61	is	be	AUX
brj-23786	84	62	transferred	transfer	VERB
brj-23786	84	63	between	between	ADP
brj-23786	84	64	neurons	neuron	NOUN
brj-23786	84	65	across	across	ADP
brj-23786	84	66	different	different	ADJ
brj-23786	84	67	layers	layer	NOUN
brj-23786	84	68	.	.	PUNCT
brj-23786	85	1	the	the	DET
brj-23786	85	2	number	number	NOUN
brj-23786	85	3	of	of	ADP
brj-23786	85	4	neurons	neuron	NOUN
brj-23786	85	5	in	in	ADP
brj-23786	85	6	the	the	DET
brj-23786	85	7	input	input	NOUN
brj-23786	85	8	and	and	CCONJ
brj-23786	85	9	output	output	NOUN
brj-23786	85	10	layers	layer	NOUN
brj-23786	85	11	is	be	AUX
brj-23786	85	12	determined	determine	VERB
brj-23786	85	13	by	by	ADP
brj-23786	85	14	the	the	DET
brj-23786	85	15	input	input	NOUN
brj-23786	85	16	parameters	parameter	NOUN
brj-23786	85	17	and	and	CCONJ
brj-23786	85	18	output	output	NOUN
brj-23786	85	19	targets	target	NOUN
brj-23786	85	20	,	,	PUNCT
brj-23786	85	21	respectively	respectively	ADV
brj-23786	85	22	,	,	PUNCT
brj-23786	85	23	while	while	SCONJ
brj-23786	85	24	the	the	DET
brj-23786	85	25	number	number	NOUN
brj-23786	85	26	of	of	ADP
brj-23786	85	27	neurons	neuron	NOUN
brj-23786	85	28	in	in	ADP
brj-23786	85	29	the	the	DET
brj-23786	85	30	hidden	hide	VERB
brj-23786	85	31	layer	layer	NOUN
brj-23786	85	32	can	can	AUX
brj-23786	85	33	be	be	AUX
brj-23786	85	34	adjusted	adjust	VERB
brj-23786	85	35	as	as	ADP
brj-23786	85	36	needed	need	VERB
brj-23786	85	37	(	(	PUNCT
brj-23786	85	38	cheng	cheng	PROPN
brj-23786	85	39	et	et	PROPN
brj-23786	85	40	al	al	PROPN
brj-23786	85	41	.	.	PROPN
brj-23786	85	42	2022	2022	NUM
brj-23786	85	43	)	)	PUNCT
brj-23786	85	44	.	.	PUNCT
brj-23786	86	1	peer	peer	NOUN
brj-23786	86	2	-	-	PUNCT
brj-23786	86	3	reviewed	review	VERB
brj-23786	86	4	article	article	NOUN
brj-23786	86	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	86	6	xu	xu	PROPN
brj-23786	86	7	et	et	PROPN
brj-23786	86	8	al	al	PROPN
brj-23786	86	9	.	.	PROPN
brj-23786	86	10	(	(	PUNCT
brj-23786	86	11	2024	2024	NUM
brj-23786	86	12	)	)	PUNCT
brj-23786	86	13	.	.	PUNCT
brj-23786	87	1	“	"	PUNCT
brj-23786	87	2	pyrolysis	pyrolysis	NOUN
brj-23786	87	3	kinetics	kinetic	NOUN
brj-23786	87	4	with	with	ADP
brj-23786	87	5	ann	ann	PROPN
brj-23786	87	6	,	,	PUNCT
brj-23786	87	7	”	"	PUNCT
brj-23786	87	8	bioresources	bioresource	NOUN
brj-23786	87	9	19(4	19(4	NUM
brj-23786	87	10	)	)	PUNCT
brj-23786	87	11	,	,	PUNCT
brj-23786	87	12	7513	7513	NUM
brj-23786	87	13	-	-	SYM
brj-23786	87	14	7529	7529	NUM
brj-23786	87	15	.	.	PUNCT
brj-23786	88	1	7517	7517	NUM
brj-23786	88	2	ga	ga	PROPN
brj-23786	88	3	-	-	PUNCT
brj-23786	88	4	bp	bp	PROPN
brj-23786	88	5	-	-	PUNCT
brj-23786	88	6	ann	ann	PROPN
brj-23786	88	7	collaboration	collaboration	NOUN
brj-23786	88	8	model	model	NOUN
brj-23786	88	9	genetic	genetic	ADJ
brj-23786	88	10	algorithms	algorithm	NOUN
brj-23786	88	11	(	(	PUNCT
brj-23786	88	12	ga	ga	NOUN
brj-23786	88	13	)	)	PUNCT
brj-23786	88	14	are	be	AUX
brj-23786	88	15	widely	widely	ADV
brj-23786	88	16	used	use	VERB
brj-23786	88	17	in	in	ADP
brj-23786	88	18	artificial	artificial	ADJ
brj-23786	88	19	neural	neural	ADJ
brj-23786	88	20	networks	network	NOUN
brj-23786	88	21	due	due	ADP
brj-23786	88	22	to	to	ADP
brj-23786	88	23	their	their	PRON
brj-23786	88	24	robustness	robustness	NOUN
brj-23786	88	25	,	,	PUNCT
brj-23786	88	26	stochastic	stochastic	ADJ
brj-23786	88	27	nature	nature	NOUN
brj-23786	88	28	,	,	PUNCT
brj-23786	88	29	global	global	ADJ
brj-23786	88	30	perspective	perspective	NOUN
brj-23786	88	31	,	,	PUNCT
brj-23786	88	32	and	and	CCONJ
brj-23786	88	33	inherent	inherent	ADJ
brj-23786	88	34	parallel	parallel	ADJ
brj-23786	88	35	processing	processing	NOUN
brj-23786	88	36	capabilities	capability	NOUN
brj-23786	88	37	(	(	PUNCT
brj-23786	88	38	quan	quan	PROPN
brj-23786	88	39	et	et	PROPN
brj-23786	88	40	al	al	PROPN
brj-23786	88	41	.	.	PROPN
brj-23786	88	42	2016	2016	NUM
brj-23786	88	43	)	)	PUNCT
brj-23786	88	44	.	.	PUNCT
brj-23786	89	1	the	the	DET
brj-23786	89	2	main	main	ADJ
brj-23786	89	3	objective	objective	NOUN
brj-23786	89	4	of	of	ADP
brj-23786	89	5	integrating	integrate	VERB
brj-23786	89	6	genetic	genetic	ADJ
brj-23786	89	7	algorithms	algorithm	NOUN
brj-23786	89	8	with	with	ADP
brj-23786	89	9	artificial	artificial	ADJ
brj-23786	89	10	neural	neural	ADJ
brj-23786	89	11	networks	network	NOUN
brj-23786	89	12	is	be	AUX
brj-23786	89	13	to	to	PART
brj-23786	89	14	use	use	VERB
brj-23786	89	15	genetic	genetic	ADJ
brj-23786	89	16	algorithms	algorithm	NOUN
brj-23786	89	17	to	to	PART
brj-23786	89	18	optimize	optimize	VERB
brj-23786	89	19	the	the	DET
brj-23786	89	20	weighting	weighting	NOUN
brj-23786	89	21	parameters	parameter	NOUN
brj-23786	89	22	of	of	ADP
brj-23786	89	23	artificial	artificial	ADJ
brj-23786	89	24	neural	neural	ADJ
brj-23786	89	25	networks	network	NOUN
brj-23786	89	26	,	,	PUNCT
brj-23786	89	27	replacing	replace	VERB
brj-23786	89	28	traditional	traditional	ADJ
brj-23786	89	29	,	,	PUNCT
brj-23786	89	30	inefficient	inefficient	ADJ
brj-23786	89	31	,	,	PUNCT
brj-23786	89	32	and	and	CCONJ
brj-23786	89	33	less	less	ADV
brj-23786	89	34	intelligent	intelligent	ADJ
brj-23786	89	35	learning	learning	NOUN
brj-23786	89	36	algorithms	algorithm	NOUN
brj-23786	89	37	with	with	ADP
brj-23786	89	38	more	more	ADV
brj-23786	89	39	effective	effective	ADJ
brj-23786	89	40	advanced	advanced	ADJ
brj-23786	89	41	methods	method	NOUN
brj-23786	89	42	based	base	VERB
brj-23786	89	43	on	on	ADP
brj-23786	89	44	genetic	genetic	ADJ
brj-23786	89	45	algorithms	algorithm	NOUN
brj-23786	89	46	(	(	PUNCT
brj-23786	89	47	conn	conn	PROPN
brj-23786	89	48	et	et	PROPN
brj-23786	89	49	al	al	PROPN
brj-23786	89	50	.	.	PROPN
brj-23786	89	51	1991	1991	NUM
brj-23786	89	52	)	)	PUNCT
brj-23786	89	53	.	.	PUNCT
brj-23786	90	1	the	the	DET
brj-23786	90	2	backpropagation	backpropagation	NOUN
brj-23786	90	3	mechanism	mechanism	NOUN
brj-23786	90	4	in	in	ADP
brj-23786	90	5	bp	bp	PROPN
brj-23786	90	6	-	-	PUNCT
brj-23786	90	7	ann	ann	PROPN
brj-23786	90	8	searches	search	NOUN
brj-23786	90	9	for	for	ADP
brj-23786	90	10	the	the	DET
brj-23786	90	11	extrema	extrema	NOUN
brj-23786	90	12	of	of	ADP
brj-23786	90	13	a	a	DET
brj-23786	90	14	nonlinear	nonlinear	ADJ
brj-23786	90	15	function	function	NOUN
brj-23786	90	16	using	use	VERB
brj-23786	90	17	the	the	DET
brj-23786	90	18	gradient	gradient	ADJ
brj-23786	90	19	method	method	NOUN
brj-23786	90	20	,	,	PUNCT
brj-23786	90	21	which	which	PRON
brj-23786	90	22	can	can	AUX
brj-23786	90	23	lead	lead	VERB
brj-23786	90	24	to	to	ADP
brj-23786	90	25	the	the	DET
brj-23786	90	26	issue	issue	NOUN
brj-23786	90	27	of	of	ADP
brj-23786	90	28	getting	getting	AUX
brj-23786	90	29	trapped	trap	VERB
brj-23786	90	30	in	in	ADP
brj-23786	90	31	local	local	ADJ
brj-23786	90	32	minima	minima	NOUN
brj-23786	90	33	.	.	PUNCT
brj-23786	91	1	in	in	ADP
brj-23786	91	2	contrast	contrast	NOUN
brj-23786	91	3	,	,	PUNCT
brj-23786	91	4	ga	ga	PROPN
brj-23786	91	5	possesses	possess	VERB
brj-23786	91	6	a	a	DET
brj-23786	91	7	powerful	powerful	ADJ
brj-23786	91	8	macro	macro	ADJ
brj-23786	91	9	search	search	NOUN
brj-23786	91	10	capability	capability	NOUN
brj-23786	91	11	and	and	CCONJ
brj-23786	91	12	demonstrates	demonstrate	VERB
brj-23786	91	13	excellent	excellent	ADJ
brj-23786	91	14	global	global	ADJ
brj-23786	91	15	optimization	optimization	NOUN
brj-23786	91	16	performance	performance	NOUN
brj-23786	91	17	.	.	PUNCT
brj-23786	92	1	they	they	PRON
brj-23786	92	2	continuously	continuously	ADV
brj-23786	92	3	enhance	enhance	VERB
brj-23786	92	4	the	the	DET
brj-23786	92	5	quality	quality	NOUN
brj-23786	92	6	of	of	ADP
brj-23786	92	7	candidate	candidate	NOUN
brj-23786	92	8	solutions	solution	NOUN
brj-23786	92	9	by	by	ADP
brj-23786	92	10	simulating	simulate	VERB
brj-23786	92	11	natural	natural	ADJ
brj-23786	92	12	selection	selection	NOUN
brj-23786	92	13	and	and	CCONJ
brj-23786	92	14	genetic	genetic	ADJ
brj-23786	92	15	variation	variation	NOUN
brj-23786	92	16	processes	process	NOUN
brj-23786	92	17	,	,	PUNCT
brj-23786	92	18	thereby	thereby	ADV
brj-23786	92	19	approaching	approach	VERB
brj-23786	92	20	closer	close	ADV
brj-23786	92	21	to	to	ADP
brj-23786	92	22	the	the	DET
brj-23786	92	23	global	global	ADJ
brj-23786	92	24	optimal	optimal	ADJ
brj-23786	92	25	solution	solution	NOUN
brj-23786	92	26	.	.	PUNCT
brj-23786	93	1	therefore	therefore	ADV
brj-23786	93	2	,	,	PUNCT
brj-23786	93	3	this	this	DET
brj-23786	93	4	study	study	NOUN
brj-23786	93	5	combined	combine	VERB
brj-23786	93	6	ga	ga	PROPN
brj-23786	93	7	with	with	ADP
brj-23786	93	8	bp	bp	PROPN
brj-23786	93	9	-	-	PUNCT
brj-23786	93	10	ann	ann	PROPN
brj-23786	93	11	to	to	PART
brj-23786	93	12	leverage	leverage	VERB
brj-23786	93	13	their	their	PRON
brj-23786	93	14	complementary	complementary	ADJ
brj-23786	93	15	strengths	strength	NOUN
brj-23786	93	16	,	,	PUNCT
brj-23786	93	17	effectively	effectively	ADV
brj-23786	93	18	overcoming	overcome	VERB
brj-23786	93	19	the	the	DET
brj-23786	93	20	local	local	ADJ
brj-23786	93	21	extremum	extremum	ADJ
brj-23786	93	22	problem	problem	NOUN
brj-23786	93	23	inherent	inherent	ADJ
brj-23786	93	24	in	in	ADP
brj-23786	93	25	the	the	DET
brj-23786	93	26	backpropagation	backpropagation	NOUN
brj-23786	93	27	algorithm	algorithm	NOUN
brj-23786	93	28	.	.	PUNCT
brj-23786	94	1	this	this	DET
brj-23786	94	2	integration	integration	NOUN
brj-23786	94	3	improved	improve	VERB
brj-23786	94	4	the	the	DET
brj-23786	94	5	overall	overall	ADJ
brj-23786	94	6	performance	performance	NOUN
brj-23786	94	7	and	and	CCONJ
brj-23786	94	8	accuracy	accuracy	NOUN
brj-23786	94	9	of	of	ADP
brj-23786	94	10	the	the	DET
brj-23786	94	11	neural	neural	ADJ
brj-23786	94	12	network	network	NOUN
brj-23786	94	13	(	(	PUNCT
brj-23786	94	14	zhu	zhu	X
brj-23786	94	15	et	et	PROPN
brj-23786	94	16	al	al	PROPN
brj-23786	94	17	.	.	PROPN
brj-23786	94	18	2020	2020	NUM
brj-23786	94	19	)	)	PUNCT
brj-23786	94	20	.	.	PUNCT
brj-23786	95	1	coupled	couple	VERB
brj-23786	95	2	kinetic	kinetic	ADJ
brj-23786	95	3	model	model	NOUN
brj-23786	95	4	and	and	CCONJ
brj-23786	95	5	ga	ga	PROPN
brj-23786	95	6	-	-	PUNCT
brj-23786	95	7	bp	bp	PROPN
brj-23786	95	8	-	-	PUNCT
brj-23786	95	9	ann	ann	PROPN
brj-23786	95	10	model	model	NOUN
brj-23786	95	11	predictions	prediction	NOUN
brj-23786	95	12	the	the	DET
brj-23786	95	13	kinetic	kinetic	ADJ
brj-23786	95	14	model	model	NOUN
brj-23786	95	15	,	,	PUNCT
brj-23786	95	16	enhanced	enhance	VERB
brj-23786	95	17	by	by	ADP
brj-23786	95	18	the	the	DET
brj-23786	95	19	dung	dung	NOUN
brj-23786	95	20	beetle	beetle	NOUN
brj-23786	95	21	optimization	optimization	NOUN
brj-23786	95	22	algorithm	algorithm	NOUN
brj-23786	95	23	,	,	PUNCT
brj-23786	95	24	predicted	predict	VERB
brj-23786	95	25	the	the	DET
brj-23786	95	26	kinetic	kinetic	ADJ
brj-23786	95	27	parameters	parameter	NOUN
brj-23786	95	28	of	of	ADP
brj-23786	95	29	each	each	DET
brj-23786	95	30	component	component	NOUN
brj-23786	95	31	.	.	PUNCT
brj-23786	96	1	these	these	DET
brj-23786	96	2	optimal	optimal	ADJ
brj-23786	96	3	parameters	parameter	NOUN
brj-23786	96	4	were	be	AUX
brj-23786	96	5	then	then	ADV
brj-23786	96	6	utilized	utilize	VERB
brj-23786	96	7	to	to	PART
brj-23786	96	8	predict	predict	VERB
brj-23786	96	9	the	the	DET
brj-23786	96	10	pyrolysis	pyrolysis	NOUN
brj-23786	96	11	of	of	ADP
brj-23786	96	12	pine	pine	ADJ
brj-23786	96	13	needles	needle	NOUN
brj-23786	96	14	.	.	PUNCT
brj-23786	97	1	the	the	DET
brj-23786	97	2	model	model	NOUN
brj-23786	97	3	predictions	prediction	NOUN
brj-23786	97	4	were	be	AUX
brj-23786	97	5	compared	compare	VERB
brj-23786	97	6	with	with	ADP
brj-23786	97	7	experimental	experimental	ADJ
brj-23786	97	8	(	(	PUNCT
brj-23786	97	9	tg	tg	NOUN
brj-23786	97	10	)	)	PUNCT
brj-23786	97	11	data	datum	NOUN
brj-23786	97	12	to	to	PART
brj-23786	97	13	calculate	calculate	VERB
brj-23786	97	14	differences	difference	NOUN
brj-23786	97	15	.	.	PUNCT
brj-23786	98	1	these	these	DET
brj-23786	98	2	differences	difference	NOUN
brj-23786	98	3	served	serve	VERB
brj-23786	98	4	as	as	ADP
brj-23786	98	5	input	input	NOUN
brj-23786	98	6	data	datum	NOUN
brj-23786	98	7	for	for	ADP
brj-23786	98	8	training	train	VERB
brj-23786	98	9	the	the	DET
brj-23786	98	10	ga	ga	PROPN
brj-23786	98	11	-	-	PUNCT
brj-23786	98	12	bp	bp	PROPN
brj-23786	98	13	-	-	PUNCT
brj-23786	98	14	ann	ann	PROPN
brj-23786	98	15	model	model	NOUN
brj-23786	98	16	to	to	PART
brj-23786	98	17	predict	predict	VERB
brj-23786	98	18	the	the	DET
brj-23786	98	19	error	error	NOUN
brj-23786	98	20	values	value	NOUN
brj-23786	98	21	generated	generate	VERB
brj-23786	98	22	by	by	ADP
brj-23786	98	23	the	the	DET
brj-23786	98	24	kinetic	kinetic	ADJ
brj-23786	98	25	model	model	NOUN
brj-23786	98	26	.	.	PUNCT
brj-23786	99	1	the	the	DET
brj-23786	99	2	prediction	prediction	NOUN
brj-23786	99	3	results	result	VERB
brj-23786	99	4	from	from	ADP
brj-23786	99	5	the	the	DET
brj-23786	99	6	kinetic	kinetic	ADJ
brj-23786	99	7	model	model	NOUN
brj-23786	99	8	were	be	AUX
brj-23786	99	9	combined	combine	VERB
brj-23786	99	10	with	with	ADP
brj-23786	99	11	the	the	DET
brj-23786	99	12	error	error	NOUN
brj-23786	99	13	predictions	prediction	NOUN
brj-23786	99	14	from	from	ADP
brj-23786	99	15	the	the	DET
brj-23786	99	16	ga	ga	PROPN
brj-23786	99	17	-	-	PUNCT
brj-23786	99	18	bp	bp	PROPN
brj-23786	99	19	-	-	PUNCT
brj-23786	99	20	ann	ann	PROPN
brj-23786	99	21	model	model	NOUN
brj-23786	99	22	to	to	PART
brj-23786	99	23	generate	generate	VERB
brj-23786	99	24	the	the	DET
brj-23786	99	25	overall	overall	ADJ
brj-23786	99	26	prediction	prediction	NOUN
brj-23786	99	27	data	datum	NOUN
brj-23786	99	28	.	.	PUNCT
brj-23786	100	1	figure	figure	NOUN
brj-23786	100	2	1	1	NUM
brj-23786	100	3	illustrates	illustrate	VERB
brj-23786	100	4	the	the	DET
brj-23786	100	5	framework	framework	NOUN
brj-23786	100	6	of	of	ADP
brj-23786	100	7	this	this	DET
brj-23786	100	8	integrated	integrate	VERB
brj-23786	100	9	approach	approach	NOUN
brj-23786	100	10	.	.	PUNCT
brj-23786	101	1	fig	fig	NOUN
brj-23786	101	2	.	.	PUNCT
brj-23786	102	1	1	1	X
brj-23786	102	2	.	.	X
brj-23786	102	3	structure	structure	NOUN
brj-23786	102	4	of	of	ADP
brj-23786	102	5	coupled	couple	VERB
brj-23786	102	6	schematic	schematic	ADJ
brj-23786	102	7	diagram	diagram	NOUN
brj-23786	102	8	of	of	ADP
brj-23786	102	9	the	the	DET
brj-23786	102	10	ga	ga	PROPN
brj-23786	102	11	-	-	PUNCT
brj-23786	102	12	bp	bp	PROPN
brj-23786	102	13	-	-	PUNCT
brj-23786	102	14	ann	ann	PROPN
brj-23786	102	15	peer	peer	NOUN
brj-23786	102	16	-	-	PUNCT
brj-23786	102	17	reviewed	review	VERB
brj-23786	102	18	article	article	NOUN
brj-23786	102	19	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	102	20	xu	xu	PROPN
brj-23786	102	21	et	et	PROPN
brj-23786	102	22	al	al	PROPN
brj-23786	102	23	.	.	PROPN
brj-23786	102	24	(	(	PUNCT
brj-23786	102	25	2024	2024	NUM
brj-23786	102	26	)	)	PUNCT
brj-23786	102	27	.	.	PUNCT
brj-23786	103	1	“	"	PUNCT
brj-23786	103	2	pyrolysis	pyrolysis	NOUN
brj-23786	103	3	kinetics	kinetic	NOUN
brj-23786	103	4	with	with	ADP
brj-23786	103	5	ann	ann	PROPN
brj-23786	103	6	,	,	PUNCT
brj-23786	103	7	”	"	PUNCT
brj-23786	103	8	bioresources	bioresource	NOUN
brj-23786	103	9	19(4	19(4	NUM
brj-23786	103	10	)	)	PUNCT
brj-23786	103	11	,	,	PUNCT
brj-23786	103	12	7513	7513	NUM
brj-23786	103	13	-	-	SYM
brj-23786	103	14	7529	7529	NUM
brj-23786	103	15	.	.	PUNCT
brj-23786	104	1	7518	7518	NUM
brj-23786	104	2	results	result	NOUN
brj-23786	104	3	and	and	CCONJ
brj-23786	104	4	discussion	discussion	NOUN
brj-23786	104	5	thermogravimetric	thermogravimetric	ADJ
brj-23786	104	6	analysis	analysis	NOUN
brj-23786	104	7	figure	figure	NOUN
brj-23786	104	8	2	2	NUM
brj-23786	104	9	displays	display	VERB
brj-23786	104	10	the	the	DET
brj-23786	104	11	conversion	conversion	NOUN
brj-23786	104	12	degree	degree	NOUN
brj-23786	104	13	(	(	PUNCT
brj-23786	104	14	𝛼	𝛼	NOUN
brj-23786	104	15	)	)	PUNCT
brj-23786	104	16	and	and	CCONJ
brj-23786	104	17	conversion	conversion	NOUN
brj-23786	104	18	rate	rate	NOUN
brj-23786	104	19	(	(	PUNCT
brj-23786	104	20	d𝛼	d𝛼	NOUN
brj-23786	104	21	d𝑇⁄	d𝑇⁄	NOUN
brj-23786	104	22	)	)	PUNCT
brj-23786	104	23	curves	curve	NOUN
brj-23786	104	24	for	for	ADP
brj-23786	104	25	three	three	NUM
brj-23786	104	26	heating	heating	NOUN
brj-23786	104	27	rates	rate	NOUN
brj-23786	104	28	.	.	PUNCT
brj-23786	105	1	the	the	DET
brj-23786	105	2	pyrolysis	pyrolysis	NOUN
brj-23786	105	3	process	process	NOUN
brj-23786	105	4	of	of	ADP
brj-23786	105	5	pine	pine	ADJ
brj-23786	105	6	needles	needle	NOUN
brj-23786	105	7	occurred	occur	VERB
brj-23786	105	8	between	between	ADP
brj-23786	105	9	420	420	NUM
brj-23786	105	10	k	k	NOUN
brj-23786	105	11	and	and	CCONJ
brj-23786	105	12	800	800	NUM
brj-23786	105	13	k	k	NOUN
brj-23786	105	14	,	,	PUNCT
brj-23786	105	15	with	with	ADP
brj-23786	105	16	a	a	DET
brj-23786	105	17	peak	peak	NOUN
brj-23786	105	18	occurring	occur	VERB
brj-23786	105	19	between	between	ADP
brj-23786	105	20	600	600	NUM
brj-23786	105	21	k	k	NOUN
brj-23786	105	22	and	and	CCONJ
brj-23786	105	23	650	650	NUM
brj-23786	105	24	k.	k.	NOUN
brj-23786	105	25	additionally	additionally	ADV
brj-23786	105	26	,	,	PUNCT
brj-23786	105	27	distinct	distinct	ADJ
brj-23786	105	28	shoulder	shoulder	NOUN
brj-23786	105	29	regions	region	NOUN
brj-23786	105	30	appeared	appear	VERB
brj-23786	105	31	on	on	ADP
brj-23786	105	32	either	either	DET
brj-23786	105	33	side	side	NOUN
brj-23786	105	34	of	of	ADP
brj-23786	105	35	the	the	DET
brj-23786	105	36	peak	peak	NOUN
brj-23786	105	37	.	.	PUNCT
brj-23786	106	1	as	as	SCONJ
brj-23786	106	2	the	the	DET
brj-23786	106	3	heating	heating	NOUN
brj-23786	106	4	rate	rate	NOUN
brj-23786	106	5	increased	increase	VERB
brj-23786	106	6	,	,	PUNCT
brj-23786	106	7	both	both	CCONJ
brj-23786	106	8	the	the	DET
brj-23786	106	9	shoulder	shoulder	NOUN
brj-23786	106	10	and	and	CCONJ
brj-23786	106	11	the	the	DET
brj-23786	106	12	peak	peak	NOUN
brj-23786	106	13	shifted	shift	VERB
brj-23786	106	14	to	to	ADP
brj-23786	106	15	higher	high	ADJ
brj-23786	106	16	temperatures	temperature	NOUN
brj-23786	106	17	,	,	PUNCT
brj-23786	106	18	which	which	PRON
brj-23786	106	19	is	be	AUX
brj-23786	106	20	consistent	consistent	ADJ
brj-23786	106	21	with	with	ADP
brj-23786	106	22	chang	chang	PROPN
brj-23786	106	23	et	et	PROPN
brj-23786	106	24	al	al	PROPN
brj-23786	106	25	.	.	PROPN
brj-23786	107	1	(	(	PUNCT
brj-23786	107	2	2008	2008	NUM
brj-23786	107	3	)	)	PUNCT
brj-23786	107	4	.	.	PUNCT
brj-23786	108	1	the	the	DET
brj-23786	108	2	increasing	increase	VERB
brj-23786	108	3	prominence	prominence	NOUN
brj-23786	108	4	of	of	ADP
brj-23786	108	5	the	the	DET
brj-23786	108	6	shoulder	shoulder	NOUN
brj-23786	108	7	region	region	NOUN
brj-23786	108	8	indicates	indicate	VERB
brj-23786	108	9	an	an	DET
brj-23786	108	10	increase	increase	NOUN
brj-23786	108	11	in	in	ADP
brj-23786	108	12	the	the	DET
brj-23786	108	13	complexity	complexity	NOUN
brj-23786	108	14	of	of	ADP
brj-23786	108	15	the	the	DET
brj-23786	108	16	reaction	reaction	NOUN
brj-23786	108	17	,	,	PUNCT
brj-23786	108	18	implying	imply	VERB
brj-23786	108	19	the	the	DET
brj-23786	108	20	presence	presence	NOUN
brj-23786	108	21	of	of	ADP
brj-23786	108	22	multiple	multiple	ADJ
brj-23786	108	23	overlapping	overlap	VERB
brj-23786	108	24	reactions	reaction	NOUN
brj-23786	108	25	.	.	PUNCT
brj-23786	109	1	this	this	DET
brj-23786	109	2	complexity	complexity	NOUN
brj-23786	109	3	makes	make	VERB
brj-23786	109	4	it	it	PRON
brj-23786	109	5	challenging	challenging	ADJ
brj-23786	109	6	to	to	PART
brj-23786	109	7	construct	construct	VERB
brj-23786	109	8	an	an	DET
brj-23786	109	9	accurate	accurate	ADJ
brj-23786	109	10	kinetic	kinetic	ADJ
brj-23786	109	11	model	model	NOUN
brj-23786	109	12	to	to	PART
brj-23786	109	13	predict	predict	VERB
brj-23786	109	14	pyrolysis	pyrolysis	NOUN
brj-23786	109	15	behavior	behavior	NOUN
brj-23786	109	16	.	.	PUNCT
brj-23786	110	1	fig	fig	NOUN
brj-23786	110	2	.	.	PUNCT
brj-23786	111	1	2	2	X
brj-23786	111	2	.	.	X
brj-23786	111	3	curves	curve	NOUN
brj-23786	111	4	of	of	ADP
brj-23786	111	5	conversion	conversion	NOUN
brj-23786	111	6	degree	degree	NOUN
brj-23786	111	7	(	(	PUNCT
brj-23786	111	8	𝛂	𝛂	NOUN
brj-23786	111	9	)	)	PUNCT
brj-23786	111	10	and	and	CCONJ
brj-23786	111	11	conversion	conversion	NOUN
brj-23786	111	12	rate	rate	NOUN
brj-23786	111	13	(	(	PUNCT
brj-23786	111	14	𝐝𝜶	𝐝𝜶	NOUN
brj-23786	111	15	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	111	16	)	)	PUNCT
brj-23786	111	17	at	at	ADP
brj-23786	111	18	three	three	NUM
brj-23786	111	19	heating	heating	NOUN
brj-23786	111	20	rates	rate	NOUN
brj-23786	111	21	kinetic	kinetic	ADJ
brj-23786	111	22	modelling	modelling	NOUN
brj-23786	111	23	predictions	prediction	NOUN
brj-23786	111	24	in	in	ADP
brj-23786	111	25	this	this	DET
brj-23786	111	26	study	study	NOUN
brj-23786	111	27	,	,	PUNCT
brj-23786	111	28	a	a	DET
brj-23786	111	29	kinetic	kinetic	ADJ
brj-23786	111	30	model	model	NOUN
brj-23786	111	31	and	and	CCONJ
brj-23786	111	32	the	the	DET
brj-23786	111	33	msadbo	msadbo	NOUN
brj-23786	111	34	algorithm	algorithm	PROPN
brj-23786	111	35	were	be	AUX
brj-23786	111	36	introduced	introduce	VERB
brj-23786	111	37	to	to	PART
brj-23786	111	38	predict	predict	VERB
brj-23786	111	39	the	the	DET
brj-23786	111	40	kinetic	kinetic	ADJ
brj-23786	111	41	parameters	parameter	NOUN
brj-23786	111	42	of	of	ADP
brj-23786	111	43	hemicellulose	hemicellulose	NOUN
brj-23786	111	44	,	,	PUNCT
brj-23786	111	45	cellulose	cellulose	NOUN
brj-23786	111	46	and	and	CCONJ
brj-23786	111	47	lignin	lignin	NOUN
brj-23786	111	48	from	from	ADP
brj-23786	111	49	tg	tg	PROPN
brj-23786	111	50	data	datum	NOUN
brj-23786	111	51	.	.	PUNCT
brj-23786	112	1	the	the	DET
brj-23786	112	2	optimized	optimize	VERB
brj-23786	112	3	initial	initial	ADJ
brj-23786	112	4	values	value	NOUN
brj-23786	112	5	of	of	ADP
brj-23786	112	6	the	the	DET
brj-23786	112	7	kinetic	kinetic	ADJ
brj-23786	112	8	parameters	parameter	NOUN
brj-23786	112	9	(	(	PUNCT
brj-23786	112	10	a	a	PRON
brj-23786	112	11	and	and	CCONJ
brj-23786	112	12	ea	ea	NUM
brj-23786	112	13	)	)	PUNCT
brj-23786	112	14	for	for	ADP
brj-23786	112	15	hemicellulose	hemicellulose	NOUN
brj-23786	112	16	,	,	PUNCT
brj-23786	112	17	cellulose	cellulose	NOUN
brj-23786	112	18	,	,	PUNCT
brj-23786	112	19	and	and	CCONJ
brj-23786	112	20	lignin	lignin	NOUN
brj-23786	112	21	were	be	AUX
brj-23786	112	22	calculated	calculate	VERB
brj-23786	112	23	using	use	VERB
brj-23786	112	24	the	the	DET
brj-23786	112	25	iso	iso	NOUN
brj-23786	112	26	-	-	PUNCT
brj-23786	112	27	conversion	conversion	NOUN
brj-23786	112	28	method	method	NOUN
brj-23786	112	29	of	of	ADP
brj-23786	112	30	the	the	DET
brj-23786	112	31	kissinger	kissinger	PROPN
brj-23786	112	32	-	-	PUNCT
brj-23786	112	33	kai	kai	PROPN
brj-23786	112	34	method	method	NOUN
brj-23786	112	35	(	(	PUNCT
brj-23786	112	36	xu	xu	INTJ
brj-23786	112	37	et	et	PROPN
brj-23786	112	38	al	al	PROPN
brj-23786	112	39	.	.	PROPN
brj-23786	112	40	2023	2023	NUM
brj-23786	112	41	)	)	PUNCT
brj-23786	112	42	,	,	PUNCT
brj-23786	112	43	as	as	SCONJ
brj-23786	112	44	shown	show	VERB
brj-23786	112	45	in	in	ADP
brj-23786	112	46	table	table	NOUN
brj-23786	112	47	1	1	NUM
brj-23786	112	48	.	.	PUNCT
brj-23786	112	49	table	table	NOUN
brj-23786	112	50	1	1	NUM
brj-23786	112	51	.	.	X
brj-23786	112	52	optimal	optimal	ADJ
brj-23786	112	53	parameters	parameter	NOUN
brj-23786	112	54	by	by	ADP
brj-23786	112	55	msadbo	msadbo	NOUN
brj-23786	112	56	on	on	ADP
brj-23786	112	57	two	two	NUM
brj-23786	112	58	heating	heating	NOUN
brj-23786	112	59	rates	rate	NOUN
brj-23786	112	60	substances	substance	VERB
brj-23786	112	61	parameters	parameter	NOUN
brj-23786	112	62	initial	initial	ADJ
brj-23786	112	63	values	value	NOUN
brj-23786	112	64	search	search	NOUN
brj-23786	112	65	range	range	NOUN
brj-23786	112	66	msadbo	msadbo	NOUN
brj-23786	112	67	optimized	optimize	VERB
brj-23786	112	68	values	value	NOUN
brj-23786	112	69	difference	difference	NOUN
brj-23786	112	70	of	of	ADP
brj-23786	112	71	paramaters	paramater	NOUN
brj-23786	112	72	hemicellulose	hemicellulose	NOUN
brj-23786	112	73	e1	e1	PROPN
brj-23786	112	74	(	(	PUNCT
brj-23786	112	75	kj	kj	PROPN
brj-23786	112	76	/	/	SYM
brj-23786	112	77	mol	mol	PROPN
brj-23786	112	78	)	)	PUNCT
brj-23786	112	79	162.08	162.08	NUM
brj-23786	112	80	122	122	NUM
brj-23786	112	81	-	-	SYM
brj-23786	112	82	202	202	NUM
brj-23786	112	83	155.08	155.08	NUM
brj-23786	112	84	4.32	4.32	NUM
brj-23786	112	85	%	%	NOUN
brj-23786	112	86	lna1[ln(s-1	lna1[ln(s-1	NOUN
brj-23786	112	87	)	)	PUNCT
brj-23786	112	88	]	]	PUNCT
brj-23786	113	1	34.78	34.78	NUM
brj-23786	113	2	26	26	NUM
brj-23786	113	3	-	-	SYM
brj-23786	113	4	38	38	NUM
brj-23786	113	5	29.71	29.71	NUM
brj-23786	113	6	14.58	14.58	NUM
brj-23786	113	7	%	%	NOUN
brj-23786	113	8	r1	r1	NOUN
brj-23786	113	9	0.38	0.38	NUM
brj-23786	113	10	0.28	0.28	NUM
brj-23786	113	11	-	-	SYM
brj-23786	113	12	0.48	0.48	NUM
brj-23786	113	13	0.48	0.48	NUM
brj-23786	113	14	26.32	26.32	NUM
brj-23786	113	15	%	%	NOUN
brj-23786	113	16	cellulose	cellulose	NOUN
brj-23786	113	17	e2	e2	PROPN
brj-23786	113	18	(	(	PUNCT
brj-23786	113	19	kj	kj	PROPN
brj-23786	113	20	/	/	SYM
brj-23786	113	21	mol	mol	PROPN
brj-23786	113	22	)	)	PUNCT
brj-23786	113	23	165.46	165.46	NUM
brj-23786	113	24	125	125	NUM
brj-23786	113	25	-	-	SYM
brj-23786	113	26	205	205	NUM
brj-23786	113	27	107.46	107.46	NUM
brj-23786	113	28	35.05	35.05	NUM
brj-23786	113	29	%	%	NOUN
brj-23786	113	30	lna2[ln(s-1	lna2[ln(s-1	NOUN
brj-23786	113	31	)	)	PUNCT
brj-23786	113	32	]	]	PUNCT
brj-23786	114	1	31.46	31.46	NUM
brj-23786	114	2	24	24	NUM
brj-23786	114	3	-	-	SYM
brj-23786	114	4	36	36	NUM
brj-23786	114	5	32.93	32.93	NUM
brj-23786	114	6	4.67	4.67	NUM
brj-23786	114	7	%	%	NOUN
brj-23786	114	8	r2	r2	PROPN
brj-23786	114	9	0.26	0.26	NUM
brj-23786	114	10	0.16	0.16	NUM
brj-23786	114	11	-	-	PUNCT
brj-23786	114	12	0.36	0.36	NUM
brj-23786	114	13	0.36	0.36	NUM
brj-23786	114	14	38.46	38.46	NUM
brj-23786	114	15	%	%	NOUN
brj-23786	114	16	lignin	lignin	NOUN
brj-23786	114	17	e3(kj	e3(kj	PROPN
brj-23786	114	18	/	/	SYM
brj-23786	114	19	mol	mol	NOUN
brj-23786	114	20	)	)	PUNCT
brj-23786	114	21	184.33	184.33	NUM
brj-23786	114	22	144	144	NUM
brj-23786	114	23	-	-	SYM
brj-23786	114	24	224	224	NUM
brj-23786	114	25	177.33	177.33	NUM
brj-23786	114	26	3.80	3.80	NUM
brj-23786	114	27	%	%	NOUN
brj-23786	114	28	lna3[ln(s-1	lna3[ln(s-1	NOUN
brj-23786	114	29	)	)	PUNCT
brj-23786	114	30	]	]	PUNCT
brj-23786	114	31	31.67	31.67	NUM
brj-23786	114	32	24	24	NUM
brj-23786	114	33	-	-	SYM
brj-23786	114	34	36	36	NUM
brj-23786	114	35	30.01	30.01	NUM
brj-23786	114	36	5.24	5.24	NUM
brj-23786	114	37	%	%	NOUN
brj-23786	114	38	r3	r3	PROPN
brj-23786	114	39	0.36	0.36	NUM
brj-23786	114	40	0.16	0.16	NUM
brj-23786	114	41	-	-	SYM
brj-23786	114	42	0.56	0.56	NUM
brj-23786	114	43	0.16	0.16	NUM
brj-23786	114	44	4.32	4.32	NUM
brj-23786	114	45	%	%	NOUN
brj-23786	114	46	peer	peer	NOUN
brj-23786	114	47	-	-	PUNCT
brj-23786	114	48	reviewed	review	VERB
brj-23786	114	49	article	article	NOUN
brj-23786	114	50	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	114	51	xu	xu	PROPN
brj-23786	114	52	et	et	PROPN
brj-23786	114	53	al	al	PROPN
brj-23786	114	54	.	.	PROPN
brj-23786	114	55	(	(	PUNCT
brj-23786	114	56	2024	2024	NUM
brj-23786	114	57	)	)	PUNCT
brj-23786	114	58	.	.	PUNCT
brj-23786	115	1	“	"	PUNCT
brj-23786	115	2	pyrolysis	pyrolysis	NOUN
brj-23786	115	3	kinetics	kinetic	NOUN
brj-23786	115	4	with	with	ADP
brj-23786	115	5	ann	ann	PROPN
brj-23786	115	6	,	,	PUNCT
brj-23786	115	7	”	"	PUNCT
brj-23786	115	8	bioresources	bioresource	NOUN
brj-23786	115	9	19(4	19(4	NUM
brj-23786	115	10	)	)	PUNCT
brj-23786	115	11	,	,	PUNCT
brj-23786	115	12	7513	7513	NUM
brj-23786	115	13	-	-	SYM
brj-23786	115	14	7529	7529	NUM
brj-23786	115	15	.	.	PUNCT
brj-23786	116	1	7519	7519	NUM
brj-23786	116	2	the	the	DET
brj-23786	116	3	parameters	parameter	NOUN
brj-23786	116	4	of	of	ADP
brj-23786	116	5	the	the	DET
brj-23786	116	6	pine	pine	ADJ
brj-23786	116	7	needle	needle	NOUN
brj-23786	116	8	pyrolysis	pyrolysis	NOUN
brj-23786	116	9	model	model	NOUN
brj-23786	116	10	to	to	PART
brj-23786	116	11	be	be	AUX
brj-23786	116	12	optimized	optimize	VERB
brj-23786	116	13	consisted	consist	VERB
brj-23786	116	14	of	of	ADP
brj-23786	116	15	three	three	NUM
brj-23786	116	16	aspects	aspect	NOUN
brj-23786	116	17	(	(	PUNCT
brj-23786	116	18	9	9	NUM
brj-23786	116	19	parameters	parameter	NOUN
brj-23786	116	20	in	in	ADP
brj-23786	116	21	total	total	ADJ
brj-23786	116	22	):	):	PUNCT
brj-23786	116	23	the	the	DET
brj-23786	116	24	initial	initial	ADJ
brj-23786	116	25	mass	mass	NOUN
brj-23786	116	26	fraction	fraction	NOUN
brj-23786	116	27	(	(	PUNCT
brj-23786	116	28	ri	ri	NOUN
brj-23786	116	29	)	)	PUNCT
brj-23786	116	30	and	and	CCONJ
brj-23786	116	31	the	the	DET
brj-23786	116	32	chemical	chemical	ADJ
brj-23786	116	33	kinetic	kinetic	ADJ
brj-23786	116	34	parameters	parameter	NOUN
brj-23786	116	35	(	(	PUNCT
brj-23786	116	36	ai	ai	VERB
brj-23786	116	37	,	,	PUNCT
brj-23786	116	38	ei	ei	NOUN
brj-23786	116	39	)	)	PUNCT
brj-23786	116	40	for	for	ADP
brj-23786	116	41	hemicellulose	hemicellulose	NOUN
brj-23786	116	42	,	,	PUNCT
brj-23786	116	43	cellulose	cellulose	NOUN
brj-23786	116	44	,	,	PUNCT
brj-23786	116	45	and	and	CCONJ
brj-23786	116	46	lignin	lignin	NOUN
brj-23786	116	47	.	.	PUNCT
brj-23786	117	1	since	since	SCONJ
brj-23786	117	2	the	the	DET
brj-23786	117	3	sum	sum	NOUN
brj-23786	117	4	of	of	ADP
brj-23786	117	5	the	the	DET
brj-23786	117	6	mass	mass	ADJ
brj-23786	117	7	fractions	fraction	NOUN
brj-23786	117	8	of	of	ADP
brj-23786	117	9	the	the	DET
brj-23786	117	10	three	three	NUM
brj-23786	117	11	main	main	ADJ
brj-23786	117	12	components	component	NOUN
brj-23786	117	13	is	be	AUX
brj-23786	117	14	1	1	NUM
brj-23786	117	15	,	,	PUNCT
brj-23786	117	16	only	only	ADV
brj-23786	117	17	eight	eight	NUM
brj-23786	117	18	parameters	parameter	NOUN
brj-23786	117	19	need	need	VERB
brj-23786	117	20	to	to	PART
brj-23786	117	21	be	be	AUX
brj-23786	117	22	optimized	optimize	VERB
brj-23786	117	23	.	.	PUNCT
brj-23786	118	1	table	table	NOUN
brj-23786	118	2	1	1	NUM
brj-23786	118	3	shows	show	VERB
brj-23786	118	4	the	the	DET
brj-23786	118	5	initial	initial	ADJ
brj-23786	118	6	values	value	NOUN
brj-23786	118	7	and	and	CCONJ
brj-23786	118	8	search	search	NOUN
brj-23786	118	9	ranges	range	NOUN
brj-23786	118	10	for	for	ADP
brj-23786	118	11	these	these	DET
brj-23786	118	12	optimization	optimization	NOUN
brj-23786	118	13	parameters	parameter	NOUN
brj-23786	118	14	.	.	PUNCT
brj-23786	119	1	note	note	VERB
brj-23786	119	2	that	that	SCONJ
brj-23786	119	3	the	the	DET
brj-23786	119	4	optimization	optimization	NOUN
brj-23786	119	5	process	process	NOUN
brj-23786	119	6	did	do	AUX
brj-23786	119	7	not	not	PART
brj-23786	119	8	include	include	VERB
brj-23786	119	9	tg	tg	PROPN
brj-23786	119	10	data	datum	NOUN
brj-23786	119	11	at	at	ADP
brj-23786	119	12	a	a	DET
brj-23786	119	13	heating	heating	NOUN
brj-23786	119	14	rate	rate	NOUN
brj-23786	119	15	of	of	ADP
brj-23786	119	16	40	40	NUM
brj-23786	119	17	k	k	PROPN
brj-23786	119	18	/	/	SYM
brj-23786	119	19	min	min	PROPN
brj-23786	119	20	.	.	PUNCT
brj-23786	120	1	the	the	DET
brj-23786	120	2	optimal	optimal	ADJ
brj-23786	120	3	kinetic	kinetic	ADJ
brj-23786	120	4	parameters	parameter	NOUN
brj-23786	120	5	derived	derive	VERB
brj-23786	120	6	from	from	ADP
brj-23786	120	7	the	the	DET
brj-23786	120	8	optimization	optimization	NOUN
brj-23786	120	9	were	be	AUX
brj-23786	120	10	then	then	ADV
brj-23786	120	11	used	use	VERB
brj-23786	120	12	to	to	PART
brj-23786	120	13	predict	predict	VERB
brj-23786	120	14	the	the	DET
brj-23786	120	15	biomass	biomass	NOUN
brj-23786	120	16	conversion	conversion	NOUN
brj-23786	120	17	degree	degree	NOUN
brj-23786	120	18	(	(	PUNCT
brj-23786	120	19	𝛼	𝛼	NOUN
brj-23786	120	20	)	)	PUNCT
brj-23786	120	21	and	and	CCONJ
brj-23786	120	22	conversion	conversion	NOUN
brj-23786	120	23	rate	rate	NOUN
brj-23786	120	24	(	(	PUNCT
brj-23786	120	25	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	120	26	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	120	27	)	)	PUNCT
brj-23786	120	28	,	,	PUNCT
brj-23786	120	29	in	in	ADP
brj-23786	120	30	the	the	DET
brj-23786	120	31	trained	train	VERB
brj-23786	120	32	regions	region	NOUN
brj-23786	120	33	(	(	PUNCT
brj-23786	120	34	10	10	NUM
brj-23786	120	35	and	and	CCONJ
brj-23786	120	36	20	20	NUM
brj-23786	120	37	k	k	NOUN
brj-23786	120	38	/	/	SYM
brj-23786	120	39	min	min	NOUN
brj-23786	120	40	)	)	PUNCT
brj-23786	120	41	and	and	CCONJ
brj-23786	120	42	the	the	DET
brj-23786	120	43	untrained	untrained	ADJ
brj-23786	120	44	region	region	NOUN
brj-23786	120	45	(	(	PUNCT
brj-23786	120	46	40	40	NUM
brj-23786	120	47	k	k	NOUN
brj-23786	120	48	/	/	SYM
brj-23786	120	49	min	min	NOUN
brj-23786	120	50	)	)	PUNCT
brj-23786	120	51	,	,	PUNCT
brj-23786	120	52	as	as	SCONJ
brj-23786	120	53	shown	show	VERB
brj-23786	120	54	in	in	ADP
brj-23786	120	55	fig	fig	NOUN
brj-23786	120	56	.	.	PUNCT
brj-23786	121	1	3	3	X
brj-23786	121	2	.	.	X
brj-23786	121	3	in	in	ADP
brj-23786	121	4	fig	fig	NOUN
brj-23786	121	5	.	.	PUNCT
brj-23786	122	1	3	3	NUM
brj-23786	122	2	(	(	PUNCT
brj-23786	122	3	a	a	NOUN
brj-23786	122	4	-	-	PUNCT
brj-23786	122	5	c	c	NOUN
brj-23786	122	6	)	)	PUNCT
brj-23786	122	7	,	,	PUNCT
brj-23786	122	8	the	the	DET
brj-23786	122	9	model	model	NOUN
brj-23786	122	10	’s	’s	PART
brj-23786	122	11	trend	trend	NOUN
brj-23786	122	12	in	in	ADP
brj-23786	122	13	predicting	predict	VERB
brj-23786	122	14	the	the	DET
brj-23786	122	15	conversion	conversion	NOUN
brj-23786	122	16	degree	degree	NOUN
brj-23786	122	17	at	at	ADP
brj-23786	122	18	the	the	DET
brj-23786	122	19	three	three	NUM
brj-23786	122	20	heating	heating	NOUN
brj-23786	122	21	rates	rate	NOUN
brj-23786	122	22	was	be	AUX
brj-23786	122	23	generally	generally	ADV
brj-23786	122	24	accurate	accurate	ADJ
brj-23786	122	25	,	,	PUNCT
brj-23786	122	26	but	but	CCONJ
brj-23786	122	27	there	there	PRON
brj-23786	122	28	were	be	VERB
brj-23786	122	29	some	some	DET
brj-23786	122	30	notable	notable	ADJ
brj-23786	122	31	differences	difference	NOUN
brj-23786	122	32	,	,	PUNCT
brj-23786	122	33	mainly	mainly	ADV
brj-23786	122	34	from	from	ADP
brj-23786	122	35	400	400	NUM
brj-23786	122	36	to	to	ADP
brj-23786	122	37	600	600	NUM
brj-23786	122	38	k	k	NOUN
brj-23786	122	39	,	,	PUNCT
brj-23786	122	40	and	and	CCONJ
brj-23786	122	41	650	650	NUM
brj-23786	122	42	to	to	PART
brj-23786	122	43	900	900	NUM
brj-23786	122	44	k.	k.	NOUN
brj-23786	122	45	in	in	ADP
brj-23786	122	46	fig	fig	NOUN
brj-23786	122	47	.	.	PUNCT
brj-23786	123	1	3	3	NUM
brj-23786	123	2	(	(	PUNCT
brj-23786	123	3	d	d	NOUN
brj-23786	123	4	-	-	PUNCT
brj-23786	123	5	f	f	NOUN
brj-23786	123	6	)	)	PUNCT
brj-23786	123	7	,	,	PUNCT
brj-23786	123	8	the	the	DET
brj-23786	123	9	model	model	NOUN
brj-23786	123	10	predictions	prediction	NOUN
brj-23786	123	11	for	for	ADP
brj-23786	123	12	the	the	DET
brj-23786	123	13	conversion	conversion	NOUN
brj-23786	123	14	rate	rate	NOUN
brj-23786	123	15	showed	show	VERB
brj-23786	123	16	significant	significant	ADJ
brj-23786	123	17	errors	error	NOUN
brj-23786	123	18	in	in	ADP
brj-23786	123	19	the	the	DET
brj-23786	123	20	shoulder	shoulder	NOUN
brj-23786	123	21	regions	region	NOUN
brj-23786	123	22	on	on	ADP
brj-23786	123	23	both	both	DET
brj-23786	123	24	sides	side	NOUN
brj-23786	123	25	of	of	ADP
brj-23786	123	26	the	the	DET
brj-23786	123	27	peak	peak	NOUN
brj-23786	123	28	,	,	PUNCT
brj-23786	123	29	corresponding	correspond	VERB
brj-23786	123	30	to	to	ADP
brj-23786	123	31	the	the	DET
brj-23786	123	32	error	error	NOUN
brj-23786	123	33	regions	region	NOUN
brj-23786	123	34	in	in	ADP
brj-23786	123	35	the	the	DET
brj-23786	123	36	conversion	conversion	NOUN
brj-23786	123	37	degree	degree	NOUN
brj-23786	123	38	.	.	PUNCT
brj-23786	124	1	these	these	DET
brj-23786	124	2	results	result	NOUN
brj-23786	124	3	indicate	indicate	VERB
brj-23786	124	4	that	that	SCONJ
brj-23786	124	5	the	the	DET
brj-23786	124	6	prediction	prediction	NOUN
brj-23786	124	7	model	model	NOUN
brj-23786	124	8	needed	need	VERB
brj-23786	124	9	improvement	improvement	NOUN
brj-23786	124	10	and	and	CCONJ
brj-23786	124	11	should	should	AUX
brj-23786	124	12	be	be	AUX
brj-23786	124	13	the	the	DET
brj-23786	124	14	focus	focus	NOUN
brj-23786	124	15	of	of	ADP
brj-23786	124	16	future	future	ADJ
brj-23786	124	17	research	research	NOUN
brj-23786	124	18	.	.	PUNCT
brj-23786	125	1	table	table	NOUN
brj-23786	125	2	2	2	NUM
brj-23786	125	3	shows	show	VERB
brj-23786	125	4	that	that	SCONJ
brj-23786	125	5	the	the	DET
brj-23786	125	6	r²	r²	ADJ
brj-23786	125	7	values	value	NOUN
brj-23786	125	8	for	for	ADP
brj-23786	125	9	the	the	DET
brj-23786	125	10	kinetic	kinetic	ADJ
brj-23786	125	11	modeling	modeling	NOUN
brj-23786	125	12	of	of	ADP
brj-23786	125	13	conversion	conversion	NOUN
brj-23786	125	14	degree	degree	NOUN
brj-23786	125	15	were	be	AUX
brj-23786	125	16	all	all	PRON
brj-23786	125	17	above	above	ADP
brj-23786	125	18	0.98	0.98	NUM
brj-23786	125	19	,	,	PUNCT
brj-23786	125	20	while	while	SCONJ
brj-23786	125	21	the	the	DET
brj-23786	125	22	predicted	predict	VERB
brj-23786	125	23	r²	r²	NOUN
brj-23786	125	24	values	value	NOUN
brj-23786	125	25	for	for	ADP
brj-23786	125	26	conversion	conversion	NOUN
brj-23786	125	27	rate	rate	NOUN
brj-23786	125	28	were	be	AUX
brj-23786	125	29	all	all	ADV
brj-23786	125	30	below	below	ADP
brj-23786	125	31	0.75	0.75	NUM
brj-23786	125	32	.	.	PUNCT
brj-23786	126	1	additionally	additionally	ADV
brj-23786	126	2	,	,	PUNCT
brj-23786	126	3	the	the	DET
brj-23786	126	4	standard	standard	ADJ
brj-23786	126	5	error	error	NOUN
brj-23786	126	6	of	of	ADP
brj-23786	126	7	prediction	prediction	NOUN
brj-23786	126	8	(	(	PUNCT
brj-23786	126	9	sep	sep	PROPN
brj-23786	126	10	)	)	PUNCT
brj-23786	126	11	for	for	ADP
brj-23786	126	12	conversion	conversion	NOUN
brj-23786	126	13	degree	degree	NOUN
brj-23786	126	14	and	and	CCONJ
brj-23786	126	15	conversion	conversion	NOUN
brj-23786	126	16	rate	rate	NOUN
brj-23786	126	17	in	in	ADP
brj-23786	126	18	untrained	untrained	ADJ
brj-23786	126	19	zones	zone	NOUN
brj-23786	126	20	were	be	AUX
brj-23786	126	21	3.570	3.570	NUM
brj-23786	126	22	%	%	NOUN
brj-23786	126	23	and	and	CCONJ
brj-23786	126	24	9.409	9.409	NUM
brj-23786	126	25	%	%	NOUN
brj-23786	126	26	,	,	PUNCT
brj-23786	126	27	respectively	respectively	ADV
brj-23786	126	28	.	.	PUNCT
brj-23786	127	1	although	although	SCONJ
brj-23786	127	2	the	the	DET
brj-23786	127	3	model	model	NOUN
brj-23786	127	4	performed	perform	VERB
brj-23786	127	5	well	well	ADV
brj-23786	127	6	in	in	ADP
brj-23786	127	7	predicting	predict	VERB
brj-23786	127	8	conversion	conversion	NOUN
brj-23786	127	9	,	,	PUNCT
brj-23786	127	10	it	it	PRON
brj-23786	127	11	still	still	ADV
brj-23786	127	12	needs	need	VERB
brj-23786	127	13	to	to	PART
brj-23786	127	14	be	be	AUX
brj-23786	127	15	improved	improve	VERB
brj-23786	127	16	in	in	ADP
brj-23786	127	17	predicting	predict	VERB
brj-23786	127	18	the	the	DET
brj-23786	127	19	conversion	conversion	NOUN
brj-23786	127	20	rate	rate	NOUN
brj-23786	127	21	.	.	PUNCT
brj-23786	128	1	this	this	PRON
brj-23786	128	2	suggests	suggest	VERB
brj-23786	128	3	that	that	SCONJ
brj-23786	128	4	further	further	ADJ
brj-23786	128	5	optimization	optimization	NOUN
brj-23786	128	6	and	and	CCONJ
brj-23786	128	7	refinement	refinement	NOUN
brj-23786	128	8	are	be	AUX
brj-23786	128	9	needed	need	VERB
brj-23786	128	10	for	for	SCONJ
brj-23786	128	11	the	the	DET
brj-23786	128	12	prediction	prediction	NOUN
brj-23786	128	13	model	model	NOUN
brj-23786	128	14	to	to	PART
brj-23786	128	15	improve	improve	VERB
brj-23786	128	16	its	its	PRON
brj-23786	128	17	overall	overall	ADJ
brj-23786	128	18	predictive	predictive	ADJ
brj-23786	128	19	performance	performance	NOUN
brj-23786	128	20	.	.	PUNCT
brj-23786	129	1	table	table	NOUN
brj-23786	129	2	2	2	NUM
brj-23786	129	3	.	.	PUNCT
brj-23786	130	1	r2	r2	PROPN
brj-23786	130	2	and	and	CCONJ
brj-23786	130	3	sep	sep	PROPN
brj-23786	130	4	from	from	ADP
brj-23786	130	5	the	the	DET
brj-23786	130	6	kinetic	kinetic	ADJ
brj-23786	130	7	model	model	NOUN
brj-23786	130	8	heating	heating	NOUN
brj-23786	130	9	rate	rate	NOUN
brj-23786	130	10	(	(	PUNCT
brj-23786	130	11	k	k	NOUN
brj-23786	130	12	/	/	SYM
brj-23786	130	13	min	min	NOUN
brj-23786	130	14	)	)	PUNCT
brj-23786	130	15	conversion	conversion	NOUN
brj-23786	130	16	degree	degree	NOUN
brj-23786	130	17	(	(	PUNCT
brj-23786	130	18	𝛂	𝛂	NOUN
brj-23786	130	19	)	)	PUNCT
brj-23786	130	20	conversion	conversion	NOUN
brj-23786	130	21	rate	rate	NOUN
brj-23786	130	22	(	(	PUNCT
brj-23786	130	23	𝐝𝛂	𝐝𝛂	NOUN
brj-23786	130	24	𝐝𝐓	𝐝𝐓	NUM
brj-23786	130	25	)	)	PUNCT
brj-23786	130	26	r2	r2	PROPN
brj-23786	130	27	sep	sep	PROPN
brj-23786	130	28	(	(	PUNCT
brj-23786	130	29	%	%	INTJ
brj-23786	130	30	)	)	PUNCT
brj-23786	131	1	r2	r2	PROPN
brj-23786	131	2	sep	sep	PROPN
brj-23786	131	3	(	(	PUNCT
brj-23786	131	4	%	%	NOUN
brj-23786	131	5	)	)	PUNCT
brj-23786	131	6	10	10	NUM
brj-23786	131	7	0.9898	0.9898	NUM
brj-23786	131	8	4.049	4.049	NUM
brj-23786	131	9	0.7217	0.7217	NUM
brj-23786	131	10	9.543	9.543	NUM
brj-23786	131	11	20	20	NUM
brj-23786	131	12	0.9905	0.9905	NUM
brj-23786	131	13	3.569	3.569	NUM
brj-23786	131	14	0.7455	0.7455	NUM
brj-23786	131	15	9.405	9.405	NUM
brj-23786	131	16	40	40	NUM
brj-23786	131	17	0.9905	0.9905	NUM
brj-23786	131	18	3.570	3.570	NUM
brj-23786	131	19	0.7412	0.7412	NUM
brj-23786	131	20	9.409	9.409	NUM
brj-23786	131	21	ga	ga	PROPN
brj-23786	131	22	-	-	PUNCT
brj-23786	131	23	bp	bp	PROPN
brj-23786	131	24	-	-	PUNCT
brj-23786	131	25	ann	ann	PROPN
brj-23786	131	26	model	model	NOUN
brj-23786	131	27	predictions	prediction	NOUN
brj-23786	131	28	the	the	DET
brj-23786	131	29	ga	ga	PROPN
brj-23786	131	30	-	-	PUNCT
brj-23786	131	31	bp	bp	PROPN
brj-23786	131	32	-	-	PUNCT
brj-23786	131	33	ann	ann	PROPN
brj-23786	131	34	model	model	NOUN
brj-23786	131	35	was	be	AUX
brj-23786	131	36	trained	train	VERB
brj-23786	131	37	using	use	VERB
brj-23786	131	38	experimental	experimental	ADJ
brj-23786	131	39	data	datum	NOUN
brj-23786	131	40	collected	collect	VERB
brj-23786	131	41	at	at	ADP
brj-23786	131	42	heating	heating	NOUN
brj-23786	131	43	rates	rate	NOUN
brj-23786	131	44	of	of	ADP
brj-23786	131	45	10	10	NUM
brj-23786	131	46	and	and	CCONJ
brj-23786	131	47	20	20	NUM
brj-23786	131	48	k	k	NOUN
brj-23786	131	49	/	/	SYM
brj-23786	131	50	min	min	PROPN
brj-23786	131	51	.	.	PUNCT
brj-23786	132	1	the	the	DET
brj-23786	132	2	trained	train	VERB
brj-23786	132	3	model	model	NOUN
brj-23786	132	4	was	be	AUX
brj-23786	132	5	used	use	VERB
brj-23786	132	6	to	to	PART
brj-23786	132	7	predict	predict	VERB
brj-23786	132	8	the	the	DET
brj-23786	132	9	conversion	conversion	NOUN
brj-23786	132	10	degree	degree	NOUN
brj-23786	132	11	(	(	PUNCT
brj-23786	132	12	𝛼	𝛼	NOUN
brj-23786	132	13	)	)	PUNCT
brj-23786	132	14	and	and	CCONJ
brj-23786	132	15	the	the	DET
brj-23786	132	16	conversion	conversion	NOUN
brj-23786	132	17	rate	rate	NOUN
brj-23786	132	18	(	(	PUNCT
brj-23786	132	19	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	132	20	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	132	21	)	)	PUNCT
brj-23786	132	22	at	at	ADP
brj-23786	132	23	the	the	DET
brj-23786	132	24	trained	train	VERB
brj-23786	132	25	heating	heating	NOUN
brj-23786	132	26	rates	rate	NOUN
brj-23786	132	27	(	(	PUNCT
brj-23786	132	28	10	10	NUM
brj-23786	132	29	and	and	CCONJ
brj-23786	132	30	20	20	NUM
brj-23786	132	31	k	k	NOUN
brj-23786	132	32	/	/	SYM
brj-23786	132	33	min	min	NOUN
brj-23786	132	34	)	)	PUNCT
brj-23786	132	35	,	,	PUNCT
brj-23786	132	36	as	as	ADV
brj-23786	132	37	well	well	ADV
brj-23786	132	38	as	as	ADP
brj-23786	132	39	at	at	ADP
brj-23786	132	40	an	an	DET
brj-23786	132	41	untrained	untrained	ADJ
brj-23786	132	42	heating	heating	NOUN
brj-23786	132	43	rate	rate	NOUN
brj-23786	132	44	(	(	PUNCT
brj-23786	132	45	40	40	NUM
brj-23786	132	46	k	k	NOUN
brj-23786	132	47	/	/	SYM
brj-23786	132	48	min	min	NOUN
brj-23786	132	49	)	)	PUNCT
brj-23786	132	50	.	.	PUNCT
brj-23786	133	1	figure	figure	NOUN
brj-23786	133	2	4	4	NUM
brj-23786	133	3	compares	compare	VERB
brj-23786	133	4	the	the	DET
brj-23786	133	5	experimental	experimental	ADJ
brj-23786	133	6	values	value	NOUN
brj-23786	133	7	with	with	ADP
brj-23786	133	8	the	the	DET
brj-23786	133	9	predicted	predict	VERB
brj-23786	133	10	values	value	NOUN
brj-23786	133	11	at	at	ADP
brj-23786	133	12	three	three	NUM
brj-23786	133	13	heating	heating	NOUN
brj-23786	133	14	rates	rate	NOUN
brj-23786	133	15	.	.	PUNCT
brj-23786	134	1	in	in	ADP
brj-23786	134	2	fig	fig	NOUN
brj-23786	134	3	.	.	PUNCT
brj-23786	135	1	4	4	NUM
brj-23786	135	2	(	(	PUNCT
brj-23786	135	3	a	a	NOUN
brj-23786	135	4	-	-	PUNCT
brj-23786	135	5	f	f	NOUN
brj-23786	135	6	)	)	PUNCT
brj-23786	135	7	,	,	PUNCT
brj-23786	135	8	the	the	DET
brj-23786	135	9	predictions	prediction	NOUN
brj-23786	135	10	for	for	ADP
brj-23786	135	11	the	the	DET
brj-23786	135	12	conversion	conversion	NOUN
brj-23786	135	13	degree	degree	NOUN
brj-23786	135	14	(	(	PUNCT
brj-23786	135	15	𝛼	𝛼	NOUN
brj-23786	135	16	)	)	PUNCT
brj-23786	135	17	and	and	CCONJ
brj-23786	135	18	conversion	conversion	NOUN
brj-23786	135	19	rate	rate	NOUN
brj-23786	135	20	(	(	PUNCT
brj-23786	135	21	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	135	22	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	135	23	)	)	PUNCT
brj-23786	135	24	in	in	ADP
brj-23786	135	25	the	the	DET
brj-23786	135	26	training	training	NOUN
brj-23786	135	27	temperature	temperature	NOUN
brj-23786	135	28	ranges	range	NOUN
brj-23786	135	29	(	(	PUNCT
brj-23786	135	30	10	10	NUM
brj-23786	135	31	and	and	CCONJ
brj-23786	135	32	20	20	NUM
brj-23786	136	1	k	k	NOUN
brj-23786	136	2	/	/	SYM
brj-23786	136	3	min	min	NOUN
brj-23786	136	4	)	)	PUNCT
brj-23786	136	5	were	be	AUX
brj-23786	136	6	in	in	ADP
brj-23786	136	7	general	general	ADJ
brj-23786	136	8	agreement	agreement	NOUN
brj-23786	136	9	with	with	ADP
brj-23786	136	10	the	the	DET
brj-23786	136	11	experimental	experimental	ADJ
brj-23786	136	12	data	datum	NOUN
brj-23786	136	13	.	.	PUNCT
brj-23786	137	1	however	however	ADV
brj-23786	137	2	,	,	PUNCT
brj-23786	137	3	around	around	ADP
brj-23786	137	4	the	the	DET
brj-23786	137	5	peak	peak	NOUN
brj-23786	137	6	temperature	temperature	NOUN
brj-23786	137	7	(	(	PUNCT
brj-23786	137	8	about	about	ADV
brj-23786	137	9	630	630	NUM
brj-23786	137	10	k	k	NOUN
brj-23786	137	11	)	)	PUNCT
brj-23786	137	12	for	for	ADP
brj-23786	137	13	all	all	DET
brj-23786	137	14	three	three	NUM
brj-23786	137	15	heating	heating	NOUN
brj-23786	137	16	rates	rate	NOUN
brj-23786	137	17	,	,	PUNCT
brj-23786	137	18	there	there	PRON
brj-23786	137	19	was	be	VERB
brj-23786	137	20	a	a	DET
brj-23786	137	21	noticeable	noticeable	ADJ
brj-23786	137	22	underestimation	underestimation	NOUN
brj-23786	137	23	and	and	CCONJ
brj-23786	137	24	leftward	leftward	NOUN
brj-23786	137	25	shift	shift	NOUN
brj-23786	137	26	between	between	ADP
brj-23786	137	27	the	the	DET
brj-23786	137	28	predicted	predict	VERB
brj-23786	137	29	and	and	CCONJ
brj-23786	137	30	experimental	experimental	ADJ
brj-23786	137	31	values	value	NOUN
brj-23786	137	32	of	of	ADP
brj-23786	137	33	d𝛼	d𝛼	NOUN
brj-23786	137	34	d𝑇⁄	d𝑇⁄	NOUN
brj-23786	137	35	,	,	PUNCT
brj-23786	137	36	particularly	particularly	ADV
brj-23786	137	37	evident	evident	ADJ
brj-23786	137	38	in	in	ADP
brj-23786	137	39	the	the	DET
brj-23786	137	40	untrained	untrained	ADJ
brj-23786	137	41	range	range	NOUN
brj-23786	137	42	.	.	PUNCT
brj-23786	138	1	this	this	DET
brj-23786	138	2	observation	observation	NOUN
brj-23786	138	3	is	be	AUX
brj-23786	138	4	supported	support	VERB
brj-23786	138	5	by	by	ADP
brj-23786	138	6	the	the	DET
brj-23786	138	7	r2	r2	PROPN
brj-23786	138	8	and	and	CCONJ
brj-23786	138	9	sep	sep	NOUN
brj-23786	138	10	values	value	NOUN
brj-23786	138	11	in	in	ADP
brj-23786	138	12	table	table	NOUN
brj-23786	138	13	3	3	NUM
brj-23786	138	14	:	:	PUNCT
brj-23786	138	15	within	within	ADP
brj-23786	138	16	the	the	DET
brj-23786	138	17	trained	train	VERB
brj-23786	138	18	range	range	NOUN
brj-23786	138	19	,	,	PUNCT
brj-23786	138	20	the	the	DET
brj-23786	138	21	r2	r2	PROPN
brj-23786	138	22	values	value	NOUN
brj-23786	138	23	for	for	ADP
brj-23786	138	24	predicted	predict	VERB
brj-23786	138	25	conversion	conversion	NOUN
brj-23786	138	26	degree	degree	NOUN
brj-23786	138	27	(	(	PUNCT
brj-23786	138	28	𝛼	𝛼	X
brj-23786	138	29	)	)	PUNCT
brj-23786	138	30	were	be	AUX
brj-23786	138	31	all	all	PRON
brj-23786	138	32	above	above	ADP
brj-23786	138	33	0.995	0.995	NUM
brj-23786	138	34	and	and	CCONJ
brj-23786	138	35	for	for	ADP
brj-23786	138	36	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	138	37	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	138	38	they	they	PRON
brj-23786	138	39	were	be	AUX
brj-23786	138	40	all	all	ADV
brj-23786	138	41	above	above	ADP
brj-23786	138	42	0.97	0.97	NUM
brj-23786	138	43	.	.	PUNCT
brj-23786	139	1	conversely	conversely	ADV
brj-23786	139	2	,	,	PUNCT
brj-23786	139	3	in	in	ADP
brj-23786	139	4	the	the	DET
brj-23786	139	5	untrained	untrained	ADJ
brj-23786	139	6	range	range	NOUN
brj-23786	139	7	(	(	PUNCT
brj-23786	139	8	40	40	NUM
brj-23786	139	9	k	k	NOUN
brj-23786	139	10	/	/	SYM
brj-23786	139	11	min	min	NOUN
brj-23786	139	12	)	)	PUNCT
brj-23786	139	13	,	,	PUNCT
brj-23786	139	14	the	the	DET
brj-23786	139	15	r2	r2	PROPN
brj-23786	139	16	value	value	NOUN
brj-23786	139	17	dropped	drop	VERB
brj-23786	139	18	to	to	ADP
brj-23786	139	19	0.994	0.994	NUM
brj-23786	139	20	,	,	PUNCT
brj-23786	139	21	and	and	CCONJ
brj-23786	139	22	for	for	ADP
brj-23786	139	23	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	139	24	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	139	25	it	it	PRON
brj-23786	139	26	dropped	drop	VERB
brj-23786	139	27	to	to	ADP
brj-23786	139	28	approximately	approximately	ADV
brj-23786	139	29	0.95	0.95	NUM
brj-23786	139	30	.	.	PUNCT
brj-23786	140	1	peer	peer	NOUN
brj-23786	140	2	-	-	PUNCT
brj-23786	140	3	reviewed	review	VERB
brj-23786	140	4	article	article	NOUN
brj-23786	140	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	140	6	xu	xu	PROPN
brj-23786	140	7	et	et	PROPN
brj-23786	140	8	al	al	PROPN
brj-23786	140	9	.	.	PROPN
brj-23786	140	10	(	(	PUNCT
brj-23786	140	11	2024	2024	NUM
brj-23786	140	12	)	)	PUNCT
brj-23786	140	13	.	.	PUNCT
brj-23786	141	1	“	"	PUNCT
brj-23786	141	2	pyrolysis	pyrolysis	NOUN
brj-23786	141	3	kinetics	kinetic	NOUN
brj-23786	141	4	with	with	ADP
brj-23786	141	5	ann	ann	PROPN
brj-23786	141	6	,	,	PUNCT
brj-23786	141	7	”	"	PUNCT
brj-23786	141	8	bioresources	bioresource	NOUN
brj-23786	141	9	19(4	19(4	NUM
brj-23786	141	10	)	)	PUNCT
brj-23786	141	11	,	,	PUNCT
brj-23786	141	12	7513	7513	NUM
brj-23786	141	13	-	-	SYM
brj-23786	141	14	7529	7529	NUM
brj-23786	141	15	.	.	PUNCT
brj-23786	142	1	7520	7520	NUM
brj-23786	142	2	fig	fig	NOUN
brj-23786	142	3	.	.	PUNCT
brj-23786	143	1	3	3	NUM
brj-23786	143	2	(	(	PUNCT
brj-23786	143	3	a	a	NOUN
brj-23786	143	4	-	-	PUNCT
brj-23786	143	5	f	f	NOUN
brj-23786	143	6	)	)	PUNCT
brj-23786	143	7	.	.	PUNCT
brj-23786	144	1	𝜶	𝜶	NOUN
brj-23786	144	2	and	and	CCONJ
brj-23786	144	3	𝐝𝜶	𝐝𝜶	PRON
brj-23786	144	4	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	144	5	predictions	prediction	NOUN
brj-23786	144	6	from	from	ADP
brj-23786	144	7	the	the	DET
brj-23786	144	8	kinetic	kinetic	ADJ
brj-23786	144	9	model	model	NOUN
brj-23786	144	10	compared	compare	VERB
brj-23786	144	11	to	to	ADP
brj-23786	144	12	the	the	DET
brj-23786	144	13	traditional	traditional	ADJ
brj-23786	144	14	dynamics	dynamic	NOUN
brj-23786	144	15	prediction	prediction	NOUN
brj-23786	144	16	model	model	NOUN
brj-23786	144	17	,	,	PUNCT
brj-23786	144	18	the	the	DET
brj-23786	144	19	ga	ga	PROPN
brj-23786	144	20	-	-	PUNCT
brj-23786	144	21	bp	bp	PROPN
brj-23786	144	22	-	-	PUNCT
brj-23786	144	23	ann	ann	PROPN
brj-23786	144	24	model	model	NOUN
brj-23786	144	25	showed	show	VERB
brj-23786	144	26	significant	significant	ADJ
brj-23786	144	27	advantages	advantage	NOUN
brj-23786	144	28	with	with	ADP
brj-23786	144	29	significantly	significantly	ADV
brj-23786	144	30	lower	low	ADJ
brj-23786	144	31	sep	sep	NOUN
brj-23786	144	32	values	value	NOUN
brj-23786	144	33	and	and	CCONJ
brj-23786	144	34	higher	high	ADJ
brj-23786	144	35	prediction	prediction	NOUN
brj-23786	144	36	accuracy	accuracy	NOUN
brj-23786	144	37	.	.	PUNCT
brj-23786	145	1	specifically	specifically	ADV
brj-23786	145	2	,	,	PUNCT
brj-23786	145	3	the	the	DET
brj-23786	145	4	sep	sep	NOUN
brj-23786	145	5	value	value	NOUN
brj-23786	145	6	of	of	ADP
brj-23786	145	7	the	the	DET
brj-23786	145	8	conversion	conversion	NOUN
brj-23786	145	9	degree	degree	NOUN
brj-23786	145	10	in	in	ADP
brj-23786	145	11	the	the	DET
brj-23786	145	12	training	training	NOUN
brj-23786	145	13	region	region	NOUN
brj-23786	145	14	was	be	AUX
brj-23786	145	15	only	only	ADV
brj-23786	145	16	0.554	0.554	NUM
brj-23786	145	17	%	%	NOUN
brj-23786	145	18	and	and	CCONJ
brj-23786	145	19	0.508	0.508	NUM
brj-23786	145	20	%	%	NOUN
brj-23786	145	21	,	,	PUNCT
brj-23786	145	22	and	and	CCONJ
brj-23786	145	23	the	the	DET
brj-23786	145	24	sep	sep	NOUN
brj-23786	145	25	value	value	NOUN
brj-23786	145	26	of	of	ADP
brj-23786	145	27	the	the	DET
brj-23786	145	28	conversion	conversion	NOUN
brj-23786	145	29	rate	rate	NOUN
brj-23786	145	30	was	be	AUX
brj-23786	145	31	2.323	2.323	NUM
brj-23786	145	32	%	%	NOUN
brj-23786	145	33	and	and	CCONJ
brj-23786	145	34	2.171	2.171	NUM
brj-23786	145	35	%	%	NOUN
brj-23786	145	36	.	.	PUNCT
brj-23786	146	1	this	this	DET
brj-23786	146	2	result	result	NOUN
brj-23786	146	3	indicates	indicate	VERB
brj-23786	146	4	that	that	SCONJ
brj-23786	146	5	the	the	DET
brj-23786	146	6	ga	ga	PROPN
brj-23786	146	7	-	-	PUNCT
brj-23786	146	8	bp	bp	PROPN
brj-23786	146	9	-	-	PUNCT
brj-23786	146	10	ann	ann	PROPN
brj-23786	146	11	model	model	NOUN
brj-23786	146	12	was	be	AUX
brj-23786	146	13	able	able	ADJ
brj-23786	146	14	to	to	PART
brj-23786	146	15	fit	fit	VERB
brj-23786	146	16	the	the	DET
brj-23786	146	17	training	training	NOUN
brj-23786	146	18	data	datum	NOUN
brj-23786	146	19	well	well	ADV
brj-23786	146	20	and	and	CCONJ
brj-23786	146	21	provide	provide	VERB
brj-23786	146	22	relatively	relatively	ADV
brj-23786	146	23	accurate	accurate	ADJ
brj-23786	146	24	predictions	prediction	NOUN
brj-23786	146	25	.	.	PUNCT
brj-23786	147	1	however	however	ADV
brj-23786	147	2	,	,	PUNCT
brj-23786	147	3	when	when	SCONJ
brj-23786	147	4	the	the	DET
brj-23786	147	5	model	model	NOUN
brj-23786	147	6	was	be	AUX
brj-23786	147	7	applied	apply	VERB
brj-23786	147	8	to	to	ADP
brj-23786	147	9	untrained	untrained	ADJ
brj-23786	147	10	regions	region	NOUN
brj-23786	147	11	,	,	PUNCT
brj-23786	147	12	there	there	PRON
brj-23786	147	13	was	be	VERB
brj-23786	147	14	a	a	DET
brj-23786	147	15	significant	significant	ADJ
brj-23786	147	16	drop	drop	NOUN
brj-23786	147	17	in	in	ADP
brj-23786	147	18	prediction	prediction	NOUN
brj-23786	147	19	performance	performance	NOUN
brj-23786	147	20	.	.	PUNCT
brj-23786	148	1	in	in	ADP
brj-23786	148	2	these	these	DET
brj-23786	148	3	untrained	untrained	ADJ
brj-23786	148	4	regions	region	NOUN
brj-23786	148	5	,	,	PUNCT
brj-23786	148	6	the	the	DET
brj-23786	148	7	sep	sep	NOUN
brj-23786	148	8	value	value	NOUN
brj-23786	148	9	for	for	ADP
brj-23786	148	10	the	the	DET
brj-23786	148	11	degree	degree	NOUN
brj-23786	148	12	of	of	ADP
brj-23786	148	13	conversion	conversion	NOUN
brj-23786	148	14	increased	increase	VERB
brj-23786	148	15	to	to	ADP
brj-23786	148	16	0.774	0.774	NUM
brj-23786	148	17	%	%	NOUN
brj-23786	148	18	,	,	PUNCT
brj-23786	148	19	while	while	SCONJ
brj-23786	148	20	the	the	DET
brj-23786	148	21	sep	sep	NOUN
brj-23786	148	22	value	value	NOUN
brj-23786	148	23	for	for	ADP
brj-23786	148	24	the	the	DET
brj-23786	148	25	conversion	conversion	NOUN
brj-23786	148	26	rate	rate	NOUN
brj-23786	148	27	increased	increase	VERB
brj-23786	148	28	to	to	ADP
brj-23786	148	29	4.615	4.615	NUM
brj-23786	148	30	%	%	NOUN
brj-23786	148	31	.	.	PUNCT
brj-23786	149	1	this	this	DET
brj-23786	149	2	change	change	NOUN
brj-23786	149	3	indicates	indicate	VERB
brj-23786	149	4	that	that	SCONJ
brj-23786	149	5	although	although	SCONJ
brj-23786	149	6	the	the	DET
brj-23786	149	7	ga	ga	PROPN
brj-23786	149	8	-	-	PUNCT
brj-23786	149	9	bp	bp	PROPN
brj-23786	149	10	-	-	PUNCT
brj-23786	149	11	ann	ann	PROPN
brj-23786	149	12	model	model	NOUN
brj-23786	149	13	performed	perform	VERB
brj-23786	149	14	well	well	ADV
brj-23786	149	15	in	in	ADP
brj-23786	149	16	the	the	DET
brj-23786	149	17	trained	train	VERB
brj-23786	149	18	regions	region	NOUN
brj-23786	149	19	,	,	PUNCT
brj-23786	149	20	its	its	PRON
brj-23786	149	21	predictive	predictive	ADJ
brj-23786	149	22	peer	peer	NOUN
brj-23786	149	23	-	-	PUNCT
brj-23786	149	24	reviewed	review	VERB
brj-23786	149	25	article	article	NOUN
brj-23786	149	26	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	149	27	xu	xu	PROPN
brj-23786	149	28	et	et	PROPN
brj-23786	149	29	al	al	PROPN
brj-23786	149	30	.	.	PROPN
brj-23786	150	1	(	(	PUNCT
brj-23786	150	2	2024	2024	NUM
brj-23786	150	3	)	)	PUNCT
brj-23786	150	4	.	.	PUNCT
brj-23786	151	1	“	"	PUNCT
brj-23786	151	2	pyrolysis	pyrolysis	NOUN
brj-23786	151	3	kinetics	kinetic	NOUN
brj-23786	151	4	with	with	ADP
brj-23786	151	5	ann	ann	PROPN
brj-23786	151	6	,	,	PUNCT
brj-23786	151	7	”	"	PUNCT
brj-23786	151	8	bioresources	bioresource	NOUN
brj-23786	151	9	19(4	19(4	NUM
brj-23786	151	10	)	)	PUNCT
brj-23786	151	11	,	,	PUNCT
brj-23786	151	12	7513	7513	NUM
brj-23786	151	13	-	-	SYM
brj-23786	151	14	7529	7529	NUM
brj-23786	151	15	.	.	PUNCT
brj-23786	152	1	7521	7521	NUM
brj-23786	152	2	ability	ability	NOUN
brj-23786	152	3	was	be	AUX
brj-23786	152	4	relatively	relatively	ADV
brj-23786	152	5	weak	weak	ADJ
brj-23786	152	6	in	in	ADP
brj-23786	152	7	the	the	DET
brj-23786	152	8	untrained	untrained	ADJ
brj-23786	152	9	regions	region	NOUN
brj-23786	152	10	.	.	PUNCT
brj-23786	153	1	overall	overall	ADJ
brj-23786	153	2	,	,	PUNCT
brj-23786	153	3	as	as	ADP
brj-23786	153	4	a	a	DET
brj-23786	153	5	data	data	NOUN
brj-23786	153	6	-	-	PUNCT
brj-23786	153	7	driven	drive	VERB
brj-23786	153	8	approach	approach	NOUN
brj-23786	153	9	,	,	PUNCT
brj-23786	153	10	the	the	DET
brj-23786	153	11	ga	ga	PROPN
brj-23786	153	12	-	-	PUNCT
brj-23786	153	13	bp	bp	PROPN
brj-23786	153	14	-	-	PUNCT
brj-23786	153	15	ann	ann	PROPN
brj-23786	153	16	model	model	NOUN
brj-23786	153	17	demonstrated	demonstrate	VERB
brj-23786	153	18	excellent	excellent	ADJ
brj-23786	153	19	performance	performance	NOUN
brj-23786	153	20	within	within	ADP
brj-23786	153	21	the	the	DET
brj-23786	153	22	training	training	NOUN
brj-23786	153	23	domain	domain	NOUN
brj-23786	153	24	but	but	CCONJ
brj-23786	153	25	exhibited	exhibit	VERB
brj-23786	153	26	significant	significant	ADJ
brj-23786	153	27	deterioration	deterioration	NOUN
brj-23786	153	28	in	in	ADP
brj-23786	153	29	performance	performance	NOUN
brj-23786	153	30	outside	outside	ADP
brj-23786	153	31	the	the	DET
brj-23786	153	32	trained	train	VERB
brj-23786	153	33	conditions	condition	NOUN
brj-23786	153	34	,	,	PUNCT
brj-23786	153	35	highlighting	highlight	VERB
brj-23786	153	36	the	the	DET
brj-23786	153	37	model	model	NOUN
brj-23786	153	38	’s	’s	PART
brj-23786	153	39	limitations	limitation	NOUN
brj-23786	153	40	in	in	ADP
brj-23786	153	41	extrapolating	extrapolate	VERB
brj-23786	153	42	to	to	ADP
brj-23786	153	43	untrained	untrained	ADJ
brj-23786	153	44	scenarios	scenario	NOUN
brj-23786	153	45	.	.	PUNCT
brj-23786	154	1	table	table	NOUN
brj-23786	154	2	3	3	NUM
brj-23786	154	3	.	.	PUNCT
brj-23786	155	1	r2	r2	PROPN
brj-23786	155	2	and	and	CCONJ
brj-23786	155	3	sep	sep	PROPN
brj-23786	155	4	from	from	ADP
brj-23786	155	5	the	the	DET
brj-23786	155	6	ga	ga	PROPN
brj-23786	155	7	-	-	PUNCT
brj-23786	155	8	bp	bp	PROPN
brj-23786	155	9	-	-	PUNCT
brj-23786	155	10	ann	ann	PROPN
brj-23786	155	11	model	model	NOUN
brj-23786	155	12	heating	heating	NOUN
brj-23786	155	13	rate	rate	NOUN
brj-23786	155	14	(	(	PUNCT
brj-23786	155	15	k	k	NOUN
brj-23786	155	16	/	/	SYM
brj-23786	155	17	min	min	NOUN
brj-23786	155	18	)	)	PUNCT
brj-23786	155	19	conversion	conversion	NOUN
brj-23786	155	20	degree	degree	NOUN
brj-23786	155	21	(	(	PUNCT
brj-23786	155	22	𝛂	𝛂	NOUN
brj-23786	155	23	)	)	PUNCT
brj-23786	155	24	conversion	conversion	NOUN
brj-23786	155	25	rate	rate	NOUN
brj-23786	155	26	(	(	PUNCT
brj-23786	155	27	𝐝𝛂	𝐝𝛂	NOUN
brj-23786	155	28	𝐝𝐓	𝐝𝐓	NUM
brj-23786	155	29	)	)	PUNCT
brj-23786	155	30	r2	r2	PROPN
brj-23786	155	31	sep	sep	PROPN
brj-23786	155	32	(	(	PUNCT
brj-23786	155	33	%	%	INTJ
brj-23786	155	34	)	)	PUNCT
brj-23786	156	1	r2	r2	PROPN
brj-23786	156	2	sep	sep	PROPN
brj-23786	156	3	(	(	PUNCT
brj-23786	156	4	%	%	NOUN
brj-23786	156	5	)	)	PUNCT
brj-23786	156	6	10	10	NUM
brj-23786	156	7	0.9955	0.9955	NUM
brj-23786	156	8	0.554	0.554	NUM
brj-23786	156	9	0.9756	0.9756	NUM
brj-23786	156	10	2.323	2.323	NUM
brj-23786	156	11	20	20	NUM
brj-23786	156	12	0.9971	0.9971	NUM
brj-23786	156	13	0.508	0.508	NUM
brj-23786	156	14	0.9763	0.9763	NUM
brj-23786	156	15	2.171	2.171	NUM
brj-23786	156	16	40	40	NUM
brj-23786	156	17	0.9948	0.9948	NUM
brj-23786	156	18	0.774	0.774	NUM
brj-23786	156	19	0.9508	0.9508	NUM
brj-23786	156	20	4.615	4.615	NUM
brj-23786	156	21	fig	fig	NOUN
brj-23786	156	22	.	.	PUNCT
brj-23786	156	23	4	4	NUM
brj-23786	156	24	(	(	PUNCT
brj-23786	156	25	a	a	NOUN
brj-23786	156	26	-	-	PUNCT
brj-23786	156	27	f	f	NOUN
brj-23786	156	28	)	)	PUNCT
brj-23786	156	29	.	.	PUNCT
brj-23786	157	1	𝜶	𝜶	NOUN
brj-23786	157	2	and	and	CCONJ
brj-23786	157	3	𝐝𝜶	𝐝𝜶	PRON
brj-23786	157	4	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	157	5	predictions	prediction	NOUN
brj-23786	157	6	from	from	ADP
brj-23786	157	7	the	the	DET
brj-23786	157	8	ga	ga	PROPN
brj-23786	157	9	-	-	PUNCT
brj-23786	157	10	bp	bp	PROPN
brj-23786	157	11	-	-	PUNCT
brj-23786	157	12	ann	ann	PROPN
brj-23786	157	13	model	model	NOUN
brj-23786	157	14	peer	peer	NOUN
brj-23786	157	15	-	-	PUNCT
brj-23786	157	16	reviewed	review	VERB
brj-23786	157	17	article	article	NOUN
brj-23786	157	18	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	157	19	xu	xu	PROPN
brj-23786	157	20	et	et	PROPN
brj-23786	157	21	al	al	PROPN
brj-23786	157	22	.	.	PROPN
brj-23786	158	1	(	(	PUNCT
brj-23786	158	2	2024	2024	NUM
brj-23786	158	3	)	)	PUNCT
brj-23786	158	4	.	.	PUNCT
brj-23786	159	1	“	"	PUNCT
brj-23786	159	2	pyrolysis	pyrolysis	NOUN
brj-23786	159	3	kinetics	kinetic	NOUN
brj-23786	159	4	with	with	ADP
brj-23786	159	5	ann	ann	PROPN
brj-23786	159	6	,	,	PUNCT
brj-23786	159	7	”	"	PUNCT
brj-23786	159	8	bioresources	bioresource	NOUN
brj-23786	159	9	19(4	19(4	NUM
brj-23786	159	10	)	)	PUNCT
brj-23786	159	11	,	,	PUNCT
brj-23786	159	12	7513	7513	NUM
brj-23786	159	13	-	-	SYM
brj-23786	159	14	7529	7529	NUM
brj-23786	159	15	.	.	PUNCT
brj-23786	160	1	7522	7522	NUM
brj-23786	160	2	kinetic	kinetic	NOUN
brj-23786	160	3	-	-	PUNCT
brj-23786	160	4	ann	ann	NOUN
brj-23786	160	5	coupled	couple	VERB
brj-23786	160	6	model	model	NOUN
brj-23786	160	7	predictions	prediction	NOUN
brj-23786	160	8	a	a	DET
brj-23786	160	9	kinetic	kinetic	ADJ
brj-23786	160	10	model	model	NOUN
brj-23786	160	11	was	be	AUX
brj-23786	160	12	used	use	VERB
brj-23786	160	13	to	to	PART
brj-23786	160	14	predict	predict	VERB
brj-23786	160	15	the	the	DET
brj-23786	160	16	main	main	ADJ
brj-23786	160	17	trends	trend	NOUN
brj-23786	160	18	in	in	ADP
brj-23786	160	19	pyrolysis	pyrolysis	NOUN
brj-23786	160	20	,	,	PUNCT
brj-23786	160	21	and	and	CCONJ
brj-23786	160	22	a	a	DET
brj-23786	160	23	ga	ga	NOUN
brj-23786	160	24	-	-	PUNCT
brj-23786	160	25	bpann	bpann	ADJ
brj-23786	160	26	model	model	NOUN
brj-23786	160	27	was	be	AUX
brj-23786	160	28	used	use	VERB
brj-23786	160	29	to	to	PART
brj-23786	160	30	predict	predict	VERB
brj-23786	160	31	process	process	NOUN
brj-23786	160	32	deviations	deviation	NOUN
brj-23786	160	33	.	.	PUNCT
brj-23786	161	1	together	together	ADV
brj-23786	161	2	,	,	PUNCT
brj-23786	161	3	these	these	DET
brj-23786	161	4	two	two	NUM
brj-23786	161	5	parts	part	NOUN
brj-23786	161	6	made	make	VERB
brj-23786	161	7	the	the	DET
brj-23786	161	8	complete	complete	ADJ
brj-23786	161	9	prediction	prediction	NOUN
brj-23786	161	10	.	.	PUNCT
brj-23786	162	1	figure	figure	NOUN
brj-23786	162	2	5	5	NUM
brj-23786	162	3	parts	part	NOUN
brj-23786	162	4	(	(	PUNCT
brj-23786	162	5	a	a	DET
brj-23786	162	6	-	-	PUNCT
brj-23786	162	7	f	f	NOUN
brj-23786	162	8	)	)	PUNCT
brj-23786	162	9	depict	depict	VERB
brj-23786	162	10	the	the	DET
brj-23786	162	11	complete	complete	ADJ
brj-23786	162	12	predictions	prediction	NOUN
brj-23786	162	13	of	of	ADP
brj-23786	162	14	conversion	conversion	NOUN
brj-23786	162	15	degree	degree	NOUN
brj-23786	162	16	(	(	PUNCT
brj-23786	162	17	𝛼	𝛼	NOUN
brj-23786	162	18	)	)	PUNCT
brj-23786	162	19	and	and	CCONJ
brj-23786	162	20	conversion	conversion	NOUN
brj-23786	162	21	rate	rate	NOUN
brj-23786	162	22	(	(	PUNCT
brj-23786	162	23	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	162	24	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	162	25	)	)	PUNCT
brj-23786	162	26	by	by	ADP
brj-23786	162	27	the	the	DET
brj-23786	162	28	coupled	couple	VERB
brj-23786	162	29	model	model	NOUN
brj-23786	162	30	for	for	ADP
brj-23786	162	31	heating	heating	NOUN
brj-23786	162	32	rates	rate	NOUN
brj-23786	162	33	of	of	ADP
brj-23786	162	34	10	10	NUM
brj-23786	162	35	,	,	PUNCT
brj-23786	162	36	20	20	NUM
brj-23786	162	37	(	(	PUNCT
brj-23786	162	38	trained	train	VERB
brj-23786	162	39	region	region	NOUN
brj-23786	162	40	)	)	PUNCT
brj-23786	162	41	and	and	CCONJ
brj-23786	162	42	40	40	NUM
brj-23786	162	43	k	k	NOUN
brj-23786	162	44	/	/	SYM
brj-23786	162	45	min	min	NOUN
brj-23786	162	46	(	(	PUNCT
brj-23786	162	47	untrained	untrained	ADJ
brj-23786	162	48	region	region	NOUN
brj-23786	162	49	)	)	PUNCT
brj-23786	162	50	.	.	PUNCT
brj-23786	163	1	these	these	DET
brj-23786	163	2	figures	figure	NOUN
brj-23786	163	3	show	show	VERB
brj-23786	163	4	that	that	SCONJ
brj-23786	163	5	the	the	DET
brj-23786	163	6	predictions	prediction	NOUN
brj-23786	163	7	of	of	ADP
brj-23786	163	8	the	the	DET
brj-23786	163	9	coupled	couple	VERB
brj-23786	163	10	model	model	NOUN
brj-23786	163	11	closely	closely	ADV
brj-23786	163	12	matched	match	VERB
brj-23786	163	13	the	the	DET
brj-23786	163	14	experimental	experimental	ADJ
brj-23786	163	15	data	datum	NOUN
brj-23786	163	16	.	.	PUNCT
brj-23786	164	1	the	the	DET
brj-23786	164	2	coupled	couple	VERB
brj-23786	164	3	kinetic	kinetic	NOUN
brj-23786	164	4	-	-	PUNCT
brj-23786	164	5	ann	ann	PROPN
brj-23786	164	6	model	model	NOUN
brj-23786	164	7	exhibited	exhibit	VERB
brj-23786	164	8	significant	significant	ADJ
brj-23786	164	9	improvement	improvement	NOUN
brj-23786	164	10	over	over	ADP
brj-23786	164	11	separate	separate	ADJ
brj-23786	164	12	models	model	NOUN
brj-23786	164	13	,	,	PUNCT
brj-23786	164	14	particularly	particularly	ADV
brj-23786	164	15	in	in	ADP
brj-23786	164	16	regions	region	NOUN
brj-23786	164	17	not	not	PART
brj-23786	164	18	explicitly	explicitly	ADV
brj-23786	164	19	trained	train	VERB
brj-23786	164	20	.	.	PUNCT
brj-23786	165	1	this	this	PRON
brj-23786	165	2	indicates	indicate	VERB
brj-23786	165	3	that	that	SCONJ
brj-23786	165	4	coupled	couple	VERB
brj-23786	165	5	models	model	NOUN
brj-23786	165	6	were	be	AUX
brj-23786	165	7	more	more	ADV
brj-23786	165	8	effective	effective	ADJ
brj-23786	165	9	in	in	ADP
brj-23786	165	10	capturing	capture	VERB
brj-23786	165	11	and	and	CCONJ
brj-23786	165	12	predicting	predict	VERB
brj-23786	165	13	trends	trend	NOUN
brj-23786	165	14	in	in	ADP
brj-23786	165	15	experimental	experimental	ADJ
brj-23786	165	16	data	datum	NOUN
brj-23786	165	17	,	,	PUNCT
brj-23786	165	18	especially	especially	ADV
brj-23786	165	19	when	when	SCONJ
brj-23786	165	20	dealing	deal	VERB
brj-23786	165	21	with	with	ADP
brj-23786	165	22	complex	complex	ADJ
brj-23786	165	23	datasets	dataset	NOUN
brj-23786	165	24	.	.	PUNCT
brj-23786	166	1	fig	fig	NOUN
brj-23786	166	2	.	.	PUNCT
brj-23786	167	1	5	5	NUM
brj-23786	167	2	(	(	PUNCT
brj-23786	167	3	a	a	NOUN
brj-23786	167	4	-	-	PUNCT
brj-23786	167	5	f	f	NOUN
brj-23786	167	6	)	)	PUNCT
brj-23786	167	7	.	.	PUNCT
brj-23786	168	1	𝜶	𝜶	NOUN
brj-23786	168	2	and	and	CCONJ
brj-23786	168	3	𝐝𝜶	𝐝𝜶	PRON
brj-23786	168	4	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	168	5	predictions	prediction	NOUN
brj-23786	168	6	from	from	ADP
brj-23786	168	7	coupled	couple	VERB
brj-23786	168	8	kinetic	kinetic	NOUN
brj-23786	168	9	-	-	PUNCT
brj-23786	168	10	ann	ann	NOUN
brj-23786	168	11	model	model	NOUN
brj-23786	168	12	peer	peer	NOUN
brj-23786	168	13	-	-	PUNCT
brj-23786	168	14	reviewed	review	VERB
brj-23786	168	15	article	article	NOUN
brj-23786	168	16	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	168	17	xu	xu	PROPN
brj-23786	168	18	et	et	PROPN
brj-23786	168	19	al	al	PROPN
brj-23786	168	20	.	.	PROPN
brj-23786	169	1	(	(	PUNCT
brj-23786	169	2	2024	2024	NUM
brj-23786	169	3	)	)	PUNCT
brj-23786	169	4	.	.	PUNCT
brj-23786	170	1	“	"	PUNCT
brj-23786	170	2	pyrolysis	pyrolysis	NOUN
brj-23786	170	3	kinetics	kinetic	NOUN
brj-23786	170	4	with	with	ADP
brj-23786	170	5	ann	ann	PROPN
brj-23786	170	6	,	,	PUNCT
brj-23786	170	7	”	"	PUNCT
brj-23786	170	8	bioresources	bioresource	NOUN
brj-23786	170	9	19(4	19(4	NUM
brj-23786	170	10	)	)	PUNCT
brj-23786	170	11	,	,	PUNCT
brj-23786	170	12	7513	7513	NUM
brj-23786	170	13	-	-	SYM
brj-23786	170	14	7529	7529	NUM
brj-23786	170	15	.	.	PUNCT
brj-23786	171	1	7523	7523	NUM
brj-23786	171	2	table	table	NOUN
brj-23786	171	3	4	4	NUM
brj-23786	171	4	presents	present	VERB
brj-23786	171	5	the	the	DET
brj-23786	171	6	r2	r2	PROPN
brj-23786	171	7	and	and	CCONJ
brj-23786	171	8	sep	sep	PROPN
brj-23786	171	9	for	for	ADP
brj-23786	171	10	the	the	DET
brj-23786	171	11	conversion	conversion	NOUN
brj-23786	171	12	degree	degree	NOUN
brj-23786	171	13	(	(	PUNCT
brj-23786	171	14	α	α	NOUN
brj-23786	171	15	)	)	PUNCT
brj-23786	171	16	and	and	CCONJ
brj-23786	171	17	conversion	conversion	NOUN
brj-23786	171	18	rate	rate	NOUN
brj-23786	171	19	(	(	PUNCT
brj-23786	171	20	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	171	21	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	171	22	)	)	PUNCT
brj-23786	171	23	.	.	PUNCT
brj-23786	172	1	the	the	DET
brj-23786	172	2	r2	r2	PROPN
brj-23786	172	3	values	value	NOUN
brj-23786	172	4	for	for	ADP
brj-23786	172	5	the	the	DET
brj-23786	172	6	conversion	conversion	NOUN
brj-23786	172	7	degree	degree	NOUN
brj-23786	172	8	(	(	PUNCT
brj-23786	172	9	α	α	NOUN
brj-23786	172	10	)	)	PUNCT
brj-23786	172	11	were	be	AUX
brj-23786	172	12	all	all	ADV
brj-23786	172	13	above	above	ADP
brj-23786	172	14	0.9999	0.9999	NUM
brj-23786	172	15	,	,	PUNCT
brj-23786	172	16	while	while	SCONJ
brj-23786	172	17	those	those	PRON
brj-23786	172	18	for	for	ADP
brj-23786	172	19	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	172	20	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	172	21	were	be	AUX
brj-23786	172	22	above	above	ADP
brj-23786	172	23	0.999	0.999	NUM
brj-23786	172	24	.	.	PUNCT
brj-23786	173	1	the	the	DET
brj-23786	173	2	sep	sep	NOUN
brj-23786	173	3	for	for	ADP
brj-23786	173	4	the	the	DET
brj-23786	173	5	conversion	conversion	NOUN
brj-23786	173	6	degree	degree	NOUN
brj-23786	173	7	(	(	PUNCT
brj-23786	173	8	𝛼	𝛼	X
brj-23786	173	9	)	)	PUNCT
brj-23786	173	10	was	be	AUX
brj-23786	173	11	below	below	ADP
brj-23786	173	12	0.25	0.25	NUM
brj-23786	173	13	%	%	NOUN
brj-23786	173	14	,	,	PUNCT
brj-23786	173	15	and	and	CCONJ
brj-23786	173	16	for	for	ADP
brj-23786	173	17	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	173	18	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	173	19	,	,	PUNCT
brj-23786	173	20	it	it	PRON
brj-23786	173	21	was	be	AUX
brj-23786	173	22	below	below	ADP
brj-23786	173	23	0.45	0.45	NUM
brj-23786	173	24	%	%	NOUN
brj-23786	173	25	,	,	PUNCT
brj-23786	173	26	particularly	particularly	ADV
brj-23786	173	27	in	in	ADP
brj-23786	173	28	the	the	DET
brj-23786	173	29	untrained	untrained	ADJ
brj-23786	173	30	range	range	NOUN
brj-23786	173	31	(	(	PUNCT
brj-23786	173	32	40	40	NUM
brj-23786	173	33	k	k	NOUN
brj-23786	173	34	/	/	SYM
brj-23786	173	35	min	min	NOUN
brj-23786	173	36	)	)	PUNCT
brj-23786	173	37	,	,	PUNCT
brj-23786	173	38	where	where	SCONJ
brj-23786	173	39	the	the	DET
brj-23786	173	40	performance	performance	NOUN
brj-23786	173	41	significantly	significantly	ADV
brj-23786	173	42	exceeded	exceed	VERB
brj-23786	173	43	that	that	PRON
brj-23786	173	44	of	of	ADP
brj-23786	173	45	a	a	DET
brj-23786	173	46	single	single	ADJ
brj-23786	173	47	model	model	NOUN
brj-23786	173	48	.	.	PUNCT
brj-23786	174	1	this	this	PRON
brj-23786	174	2	indicates	indicate	VERB
brj-23786	174	3	that	that	SCONJ
brj-23786	174	4	the	the	DET
brj-23786	174	5	coupled	couple	VERB
brj-23786	174	6	model	model	NOUN
brj-23786	174	7	performed	perform	VERB
brj-23786	174	8	well	well	ADV
brj-23786	174	9	across	across	ADP
brj-23786	174	10	the	the	DET
brj-23786	174	11	temperature	temperature	NOUN
brj-23786	174	12	range	range	NOUN
brj-23786	174	13	,	,	PUNCT
brj-23786	174	14	offering	offer	VERB
brj-23786	174	15	substantial	substantial	ADJ
brj-23786	174	16	predictive	predictive	ADJ
brj-23786	174	17	advantages	advantage	NOUN
brj-23786	174	18	.	.	PUNCT
brj-23786	175	1	however	however	ADV
brj-23786	175	2	,	,	PUNCT
brj-23786	175	3	at	at	ADP
brj-23786	175	4	40	40	NUM
brj-23786	175	5	k	k	NOUN
brj-23786	175	6	/	/	SYM
brj-23786	175	7	min	min	NOUN
brj-23786	175	8	,	,	PUNCT
brj-23786	175	9	there	there	PRON
brj-23786	175	10	was	be	VERB
brj-23786	175	11	a	a	DET
brj-23786	175	12	slight	slight	ADJ
brj-23786	175	13	increase	increase	NOUN
brj-23786	175	14	in	in	ADP
brj-23786	175	15	the	the	DET
brj-23786	175	16	sep	sep	PROPN
brj-23786	175	17	,	,	PUNCT
brj-23786	175	18	but	but	CCONJ
brj-23786	175	19	it	it	PRON
brj-23786	175	20	remained	remain	VERB
brj-23786	175	21	within	within	ADP
brj-23786	175	22	acceptable	acceptable	ADJ
brj-23786	175	23	limits	limit	NOUN
brj-23786	175	24	.	.	PUNCT
brj-23786	176	1	this	this	PRON
brj-23786	176	2	could	could	AUX
brj-23786	176	3	be	be	AUX
brj-23786	176	4	attributed	attribute	VERB
brj-23786	176	5	to	to	ADP
brj-23786	176	6	unknown	unknown	ADJ
brj-23786	176	7	factors	factor	NOUN
brj-23786	176	8	affecting	affect	VERB
brj-23786	176	9	the	the	DET
brj-23786	176	10	predictions	prediction	NOUN
brj-23786	176	11	of	of	ADP
brj-23786	176	12	the	the	DET
brj-23786	176	13	coupled	couple	VERB
brj-23786	176	14	model	model	NOUN
brj-23786	176	15	in	in	ADP
brj-23786	176	16	this	this	DET
brj-23786	176	17	range	range	NOUN
brj-23786	176	18	or	or	CCONJ
brj-23786	176	19	insufficient	insufficient	ADJ
brj-23786	176	20	training	training	NOUN
brj-23786	176	21	data	datum	NOUN
brj-23786	176	22	.	.	PUNCT
brj-23786	177	1	nonetheless	nonetheless	ADV
brj-23786	177	2	,	,	PUNCT
brj-23786	177	3	the	the	DET
brj-23786	177	4	coupled	couple	VERB
brj-23786	177	5	model	model	NOUN
brj-23786	177	6	demonstrated	demonstrate	VERB
brj-23786	177	7	high	high	ADJ
brj-23786	177	8	accuracy	accuracy	NOUN
brj-23786	177	9	and	and	CCONJ
brj-23786	177	10	robustness	robustness	NOUN
brj-23786	177	11	,	,	PUNCT
brj-23786	177	12	significantly	significantly	ADV
brj-23786	177	13	outperforming	outperform	VERB
brj-23786	177	14	a	a	DET
brj-23786	177	15	single	single	ADJ
brj-23786	177	16	model	model	NOUN
brj-23786	177	17	in	in	ADP
brj-23786	177	18	prediction	prediction	NOUN
brj-23786	177	19	.	.	PUNCT
brj-23786	178	1	table	table	NOUN
brj-23786	178	2	4	4	NUM
brj-23786	178	3	.	.	PUNCT
brj-23786	179	1	r2	r2	PROPN
brj-23786	179	2	and	and	CCONJ
brj-23786	179	3	sep	sep	PROPN
brj-23786	179	4	from	from	ADP
brj-23786	179	5	the	the	DET
brj-23786	179	6	coupled	couple	VERB
brj-23786	179	7	kinetic	kinetic	NOUN
brj-23786	179	8	-	-	PUNCT
brj-23786	179	9	ann	ann	NOUN
brj-23786	179	10	model	model	NOUN
brj-23786	179	11	heating	heating	NOUN
brj-23786	179	12	rate	rate	NOUN
brj-23786	179	13	(	(	PUNCT
brj-23786	179	14	k	k	NOUN
brj-23786	179	15	/	/	SYM
brj-23786	179	16	min	min	NOUN
brj-23786	179	17	)	)	PUNCT
brj-23786	179	18	conversion	conversion	NOUN
brj-23786	179	19	degree	degree	NOUN
brj-23786	179	20	(	(	PUNCT
brj-23786	179	21	𝜶	𝜶	NOUN
brj-23786	179	22	)	)	PUNCT
brj-23786	179	23	conversion	conversion	NOUN
brj-23786	179	24	rate	rate	NOUN
brj-23786	179	25	(	(	PUNCT
brj-23786	179	26	𝐝𝜶	𝐝𝜶	NOUN
brj-23786	179	27	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	179	28	)	)	PUNCT
brj-23786	180	1	r2	r2	PROPN
brj-23786	180	2	sep	sep	PROPN
brj-23786	180	3	(	(	PUNCT
brj-23786	180	4	%	%	INTJ
brj-23786	180	5	)	)	PUNCT
brj-23786	180	6	r2	r2	PROPN
brj-23786	180	7	sep	sep	PROPN
brj-23786	180	8	(	(	PUNCT
brj-23786	180	9	%	%	NOUN
brj-23786	180	10	)	)	PUNCT
brj-23786	180	11	10	10	NUM
brj-23786	181	1	0.99997	0.99997	NUM
brj-23786	181	2	0.205	0.205	NUM
brj-23786	181	3	0.99961	0.99961	NUM
brj-23786	181	4	0.402	0.402	NUM
brj-23786	181	5	20	20	NUM
brj-23786	181	6	0.99993	0.99993	NUM
brj-23786	181	7	0.227	0.227	NUM
brj-23786	181	8	0.99959	0.99959	NUM
brj-23786	181	9	0.407	0.407	NUM
brj-23786	181	10	40	40	NUM
brj-23786	181	11	0.99993	0.99993	NUM
brj-23786	181	12	0.249	0.249	NUM
brj-23786	181	13	0.99944	0.99944	NUM
brj-23786	181	14	0.447	0.447	NUM
brj-23786	181	15	accuracy	accuracy	NOUN
brj-23786	181	16	of	of	ADP
brj-23786	181	17	kinetic	kinetic	NOUN
brj-23786	181	18	,	,	PUNCT
brj-23786	181	19	ga	ga	PROPN
brj-23786	181	20	-	-	PUNCT
brj-23786	181	21	bp	bp	PROPN
brj-23786	181	22	-	-	PUNCT
brj-23786	181	23	ann	ann	PROPN
brj-23786	181	24	and	and	CCONJ
brj-23786	181	25	coupled	couple	VERB
brj-23786	181	26	kinetic	kinetic	NOUN
brj-23786	181	27	-	-	PUNCT
brj-23786	181	28	ann	ann	NOUN
brj-23786	181	29	models	model	NOUN
brj-23786	181	30	this	this	DET
brj-23786	181	31	section	section	NOUN
brj-23786	181	32	compares	compare	VERB
brj-23786	181	33	the	the	DET
brj-23786	181	34	predictive	predictive	ADJ
brj-23786	181	35	effectiveness	effectiveness	NOUN
brj-23786	181	36	of	of	ADP
brj-23786	181	37	the	the	DET
brj-23786	181	38	kinetic	kinetic	ADJ
brj-23786	181	39	model	model	NOUN
brj-23786	181	40	,	,	PUNCT
brj-23786	181	41	the	the	DET
brj-23786	181	42	gabp	gabp	NOUN
brj-23786	181	43	-	-	PUNCT
brj-23786	181	44	ann	ann	PROPN
brj-23786	181	45	model	model	NOUN
brj-23786	181	46	,	,	PUNCT
brj-23786	181	47	and	and	CCONJ
brj-23786	181	48	the	the	DET
brj-23786	181	49	coupled	couple	VERB
brj-23786	181	50	model	model	NOUN
brj-23786	181	51	(	(	PUNCT
brj-23786	181	52	fig	fig	NOUN
brj-23786	181	53	.	.	PUNCT
brj-23786	181	54	6	6	NUM
brj-23786	181	55	)	)	PUNCT
brj-23786	181	56	.	.	PUNCT
brj-23786	182	1	figure	figure	NOUN
brj-23786	182	2	6	6	NUM
brj-23786	182	3	(	(	PUNCT
brj-23786	182	4	a	a	DET
brj-23786	182	5	-	-	PUNCT
brj-23786	182	6	c	c	NOUN
brj-23786	182	7	)	)	PUNCT
brj-23786	182	8	compares	compare	VERB
brj-23786	182	9	the	the	DET
brj-23786	182	10	prediction	prediction	NOUN
brj-23786	182	11	results	result	NOUN
brj-23786	182	12	of	of	ADP
brj-23786	182	13	the	the	DET
brj-23786	182	14	conversion	conversion	NOUN
brj-23786	182	15	degree	degree	NOUN
brj-23786	182	16	for	for	ADP
brj-23786	182	17	three	three	NUM
brj-23786	182	18	different	different	ADJ
brj-23786	182	19	heating	heating	NOUN
brj-23786	182	20	rates	rate	NOUN
brj-23786	182	21	among	among	ADP
brj-23786	182	22	the	the	DET
brj-23786	182	23	three	three	NUM
brj-23786	182	24	models	model	NOUN
brj-23786	182	25	with	with	ADP
brj-23786	182	26	the	the	DET
brj-23786	182	27	experimental	experimental	ADJ
brj-23786	182	28	results	result	NOUN
brj-23786	182	29	.	.	PUNCT
brj-23786	183	1	figure	figure	VERB
brj-23786	183	2	6	6	NUM
brj-23786	183	3	(	(	PUNCT
brj-23786	183	4	d	d	NOUN
brj-23786	183	5	-	-	PUNCT
brj-23786	183	6	f	f	NOUN
brj-23786	183	7	)	)	PUNCT
brj-23786	183	8	compares	compare	VERB
brj-23786	183	9	the	the	DET
brj-23786	183	10	prediction	prediction	NOUN
brj-23786	183	11	results	result	NOUN
brj-23786	183	12	of	of	ADP
brj-23786	183	13	the	the	DET
brj-23786	183	14	conversion	conversion	NOUN
brj-23786	183	15	rate	rate	NOUN
brj-23786	183	16	for	for	ADP
brj-23786	183	17	three	three	NUM
brj-23786	183	18	different	different	ADJ
brj-23786	183	19	heating	heating	NOUN
brj-23786	183	20	rates	rate	NOUN
brj-23786	183	21	among	among	ADP
brj-23786	183	22	the	the	DET
brj-23786	183	23	three	three	NUM
brj-23786	183	24	models	model	NOUN
brj-23786	183	25	with	with	ADP
brj-23786	183	26	the	the	DET
brj-23786	183	27	experimental	experimental	ADJ
brj-23786	183	28	results	result	NOUN
brj-23786	183	29	.	.	PUNCT
brj-23786	184	1	the	the	DET
brj-23786	184	2	prediction	prediction	NOUN
brj-23786	184	3	curves	curve	NOUN
brj-23786	184	4	of	of	ADP
brj-23786	184	5	the	the	DET
brj-23786	184	6	coupled	couple	VERB
brj-23786	184	7	model	model	NOUN
brj-23786	184	8	were	be	AUX
brj-23786	184	9	the	the	DET
brj-23786	184	10	most	most	ADV
brj-23786	184	11	consistent	consistent	ADJ
brj-23786	184	12	with	with	ADP
brj-23786	184	13	the	the	DET
brj-23786	184	14	experimental	experimental	ADJ
brj-23786	184	15	curves	curve	NOUN
brj-23786	184	16	,	,	PUNCT
brj-23786	184	17	followed	follow	VERB
brj-23786	184	18	by	by	ADP
brj-23786	184	19	ga	ga	PROPN
brj-23786	184	20	-	-	PUNCT
brj-23786	184	21	bp	bp	PROPN
brj-23786	184	22	-	-	PUNCT
brj-23786	184	23	ann	ann	PROPN
brj-23786	184	24	,	,	PUNCT
brj-23786	184	25	with	with	ADP
brj-23786	184	26	the	the	DET
brj-23786	184	27	kinetic	kinetic	ADJ
brj-23786	184	28	model	model	NOUN
brj-23786	184	29	performing	perform	VERB
brj-23786	184	30	the	the	DET
brj-23786	184	31	worst	bad	ADJ
brj-23786	184	32	.	.	PUNCT
brj-23786	185	1	figure	figure	NOUN
brj-23786	185	2	7(a	7(a	NUM
brj-23786	185	3	)	)	PUNCT
brj-23786	185	4	compares	compare	VERB
brj-23786	185	5	the	the	DET
brj-23786	185	6	predictive	predictive	ADJ
brj-23786	185	7	effectiveness	effectiveness	NOUN
brj-23786	185	8	of	of	ADP
brj-23786	185	9	the	the	DET
brj-23786	185	10	three	three	NUM
brj-23786	185	11	models	model	NOUN
brj-23786	185	12	for	for	ADP
brj-23786	185	13	conversion	conversion	NOUN
brj-23786	185	14	degree	degree	NOUN
brj-23786	185	15	based	base	VERB
brj-23786	185	16	on	on	ADP
brj-23786	185	17	r²	r²	NOUN
brj-23786	185	18	values	value	NOUN
brj-23786	185	19	.	.	PUNCT
brj-23786	186	1	although	although	SCONJ
brj-23786	186	2	the	the	DET
brj-23786	186	3	kinetic	kinetic	ADJ
brj-23786	186	4	model	model	NOUN
brj-23786	186	5	’s	’s	PART
brj-23786	186	6	predictions	prediction	NOUN
brj-23786	186	7	were	be	AUX
brj-23786	186	8	poor	poor	ADJ
brj-23786	186	9	,	,	PUNCT
brj-23786	186	10	its	its	PRON
brj-23786	186	11	results	result	NOUN
brj-23786	186	12	were	be	AUX
brj-23786	186	13	still	still	ADV
brj-23786	186	14	higher	high	ADJ
brj-23786	186	15	than	than	ADP
brj-23786	186	16	0.98	0.98	NUM
brj-23786	186	17	.	.	PUNCT
brj-23786	187	1	the	the	DET
brj-23786	187	2	other	other	ADJ
brj-23786	187	3	models	model	NOUN
brj-23786	187	4	performed	perform	VERB
brj-23786	187	5	well	well	ADV
brj-23786	187	6	in	in	ADP
brj-23786	187	7	predicting	predict	VERB
brj-23786	187	8	conversion	conversion	NOUN
brj-23786	187	9	degree	degree	NOUN
brj-23786	187	10	,	,	PUNCT
brj-23786	187	11	with	with	ADP
brj-23786	187	12	r²	r²	NOUN
brj-23786	187	13	values	value	NOUN
brj-23786	187	14	above	above	ADP
brj-23786	187	15	0.99	0.99	NUM
brj-23786	187	16	.	.	PUNCT
brj-23786	188	1	in	in	ADP
brj-23786	188	2	particular	particular	ADJ
brj-23786	188	3	,	,	PUNCT
brj-23786	188	4	the	the	DET
brj-23786	188	5	coupled	couple	VERB
brj-23786	188	6	kinetic	kinetic	NOUN
brj-23786	188	7	-	-	PUNCT
brj-23786	188	8	ann	ann	PROPN
brj-23786	188	9	model	model	NOUN
brj-23786	188	10	had	have	VERB
brj-23786	188	11	an	an	DET
brj-23786	188	12	r²	r²	ADJ
brj-23786	188	13	value	value	NOUN
brj-23786	188	14	of	of	ADP
brj-23786	188	15	more	more	ADJ
brj-23786	188	16	than	than	ADP
brj-23786	188	17	0.9999	0.9999	NUM
brj-23786	188	18	,	,	PUNCT
brj-23786	188	19	which	which	PRON
brj-23786	188	20	was	be	AUX
brj-23786	188	21	better	well	ADJ
brj-23786	188	22	than	than	ADP
brj-23786	188	23	both	both	CCONJ
brj-23786	188	24	the	the	DET
brj-23786	188	25	kinetic	kinetic	ADJ
brj-23786	188	26	model	model	NOUN
brj-23786	188	27	and	and	CCONJ
brj-23786	188	28	the	the	DET
brj-23786	188	29	ga	ga	PROPN
brj-23786	188	30	-	-	PUNCT
brj-23786	188	31	bp	bp	PROPN
brj-23786	188	32	-	-	PUNCT
brj-23786	188	33	ann	ann	PROPN
brj-23786	188	34	model	model	NOUN
brj-23786	188	35	.	.	PUNCT
brj-23786	189	1	however	however	ADV
brj-23786	189	2	,	,	PUNCT
brj-23786	189	3	fig	fig	NOUN
brj-23786	189	4	.	.	PUNCT
brj-23786	190	1	7(b	7(b	X
brj-23786	190	2	)	)	PUNCT
brj-23786	190	3	shows	show	VERB
brj-23786	190	4	that	that	SCONJ
brj-23786	190	5	the	the	DET
brj-23786	190	6	kinetic	kinetic	ADJ
brj-23786	190	7	model	model	NOUN
brj-23786	190	8	performed	perform	VERB
brj-23786	190	9	extremely	extremely	ADV
brj-23786	190	10	poorly	poorly	ADV
brj-23786	190	11	in	in	ADP
brj-23786	190	12	predicting	predict	VERB
brj-23786	190	13	conversion	conversion	NOUN
brj-23786	190	14	rate	rate	NOUN
brj-23786	190	15	(	(	PUNCT
brj-23786	190	16	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	190	17	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	190	18	)	)	PUNCT
brj-23786	190	19	at	at	ADP
brj-23786	190	20	the	the	DET
brj-23786	190	21	untrained	untrained	ADJ
brj-23786	190	22	heating	heating	NOUN
brj-23786	190	23	rate	rate	NOUN
brj-23786	190	24	of	of	ADP
brj-23786	190	25	40	40	NUM
brj-23786	190	26	k	k	NOUN
brj-23786	190	27	/	/	SYM
brj-23786	190	28	min	min	NOUN
brj-23786	190	29	(	(	PUNCT
brj-23786	190	30	r2	r2	PROPN
brj-23786	190	31	:	:	PUNCT
brj-23786	190	32	0.74119	0.74119	NUM
brj-23786	190	33	)	)	PUNCT
brj-23786	190	34	,	,	PUNCT
brj-23786	190	35	whereas	whereas	SCONJ
brj-23786	190	36	the	the	DET
brj-23786	190	37	coupled	couple	VERB
brj-23786	190	38	model	model	NOUN
brj-23786	190	39	maintained	maintain	VERB
brj-23786	190	40	a	a	DET
brj-23786	190	41	high	high	ADJ
brj-23786	190	42	level	level	NOUN
brj-23786	190	43	of	of	ADP
brj-23786	190	44	accuracy	accuracy	NOUN
brj-23786	190	45	with	with	ADP
brj-23786	190	46	an	an	DET
brj-23786	190	47	r2	r2	NOUN
brj-23786	190	48	value	value	NOUN
brj-23786	190	49	of	of	ADP
brj-23786	190	50	0.99944	0.99944	NUM
brj-23786	190	51	.	.	PUNCT
brj-23786	191	1	however	however	ADV
brj-23786	191	2	,	,	PUNCT
brj-23786	191	3	whether	whether	SCONJ
brj-23786	191	4	in	in	ADP
brj-23786	191	5	the	the	DET
brj-23786	191	6	trained	train	VERB
brj-23786	191	7	or	or	CCONJ
brj-23786	191	8	untrained	untrained	ADJ
brj-23786	191	9	regions	region	NOUN
brj-23786	191	10	,	,	PUNCT
brj-23786	191	11	it	it	PRON
brj-23786	191	12	was	be	AUX
brj-23786	191	13	found	find	VERB
brj-23786	191	14	that	that	SCONJ
brj-23786	191	15	the	the	DET
brj-23786	191	16	r²	r²	NOUN
brj-23786	191	17	value	value	NOUN
brj-23786	191	18	of	of	ADP
brj-23786	191	19	the	the	DET
brj-23786	191	20	conversion	conversion	NOUN
brj-23786	191	21	degree	degree	NOUN
brj-23786	191	22	was	be	AUX
brj-23786	191	23	consistently	consistently	ADV
brj-23786	191	24	higher	high	ADJ
brj-23786	191	25	than	than	ADP
brj-23786	191	26	that	that	PRON
brj-23786	191	27	of	of	ADP
brj-23786	191	28	the	the	DET
brj-23786	191	29	conversion	conversion	NOUN
brj-23786	191	30	rate	rate	NOUN
brj-23786	191	31	.	.	PUNCT
brj-23786	192	1	this	this	DET
brj-23786	192	2	difference	difference	NOUN
brj-23786	192	3	may	may	AUX
brj-23786	192	4	be	be	AUX
brj-23786	192	5	due	due	ADJ
brj-23786	192	6	to	to	ADP
brj-23786	192	7	the	the	DET
brj-23786	192	8	fact	fact	NOUN
brj-23786	192	9	that	that	SCONJ
brj-23786	192	10	the	the	DET
brj-23786	192	11	conversion	conversion	NOUN
brj-23786	192	12	rate	rate	NOUN
brj-23786	192	13	is	be	AUX
brj-23786	192	14	derived	derive	VERB
brj-23786	192	15	from	from	ADP
brj-23786	192	16	the	the	DET
brj-23786	192	17	derivative	derivative	NOUN
brj-23786	192	18	of	of	ADP
brj-23786	192	19	the	the	DET
brj-23786	192	20	conversion	conversion	NOUN
brj-23786	192	21	degree	degree	NOUN
brj-23786	192	22	,	,	PUNCT
brj-23786	192	23	making	make	VERB
brj-23786	192	24	it	it	PRON
brj-23786	192	25	more	more	ADV
brj-23786	192	26	susceptible	susceptible	ADJ
brj-23786	192	27	to	to	ADP
brj-23786	192	28	noise	noise	NOUN
brj-23786	192	29	.	.	PUNCT
brj-23786	193	1	figure	figure	NOUN
brj-23786	193	2	7	7	NUM
brj-23786	193	3	(	(	PUNCT
brj-23786	193	4	a	a	DET
brj-23786	193	5	,	,	PUNCT
brj-23786	193	6	c	c	NOUN
brj-23786	193	7	)	)	PUNCT
brj-23786	193	8	compares	compare	VERB
brj-23786	193	9	the	the	DET
brj-23786	193	10	predictive	predictive	ADJ
brj-23786	193	11	effectiveness	effectiveness	NOUN
brj-23786	193	12	of	of	ADP
brj-23786	193	13	three	three	NUM
brj-23786	193	14	models	model	NOUN
brj-23786	193	15	for	for	ADP
brj-23786	193	16	conversion	conversion	NOUN
brj-23786	193	17	degree	degree	NOUN
brj-23786	193	18	based	base	VERB
brj-23786	193	19	on	on	ADP
brj-23786	193	20	r²	r²	NOUN
brj-23786	193	21	and	and	CCONJ
brj-23786	193	22	sep	sep	PROPN
brj-23786	193	23	.	.	PUNCT
brj-23786	194	1	although	although	SCONJ
brj-23786	194	2	the	the	DET
brj-23786	194	3	kinetic	kinetic	ADJ
brj-23786	194	4	model	model	NOUN
brj-23786	194	5	’s	’s	PART
brj-23786	194	6	predictions	prediction	NOUN
brj-23786	194	7	were	be	AUX
brj-23786	194	8	poor	poor	ADJ
brj-23786	194	9	,	,	PUNCT
brj-23786	194	10	the	the	DET
brj-23786	194	11	r²	r²	NOUN
brj-23786	194	12	results	result	NOUN
brj-23786	194	13	were	be	AUX
brj-23786	194	14	still	still	ADV
brj-23786	194	15	higher	high	ADJ
brj-23786	194	16	than	than	ADP
brj-23786	194	17	0.98	0.98	NUM
brj-23786	194	18	.	.	PUNCT
brj-23786	195	1	the	the	DET
brj-23786	195	2	other	other	ADJ
brj-23786	195	3	models	model	NOUN
brj-23786	195	4	performed	perform	VERB
brj-23786	195	5	excellently	excellently	ADV
brj-23786	195	6	in	in	ADP
brj-23786	195	7	predicting	predict	VERB
brj-23786	195	8	the	the	DET
brj-23786	195	9	conversion	conversion	NOUN
brj-23786	195	10	degree	degree	NOUN
brj-23786	195	11	,	,	PUNCT
brj-23786	195	12	with	with	ADP
brj-23786	195	13	r²	r²	NOUN
brj-23786	195	14	values	value	NOUN
brj-23786	195	15	above	above	ADP
brj-23786	195	16	0.99	0.99	NUM
brj-23786	195	17	.	.	PUNCT
brj-23786	196	1	in	in	ADP
brj-23786	196	2	particular	particular	ADJ
brj-23786	196	3	,	,	PUNCT
brj-23786	196	4	the	the	DET
brj-23786	196	5	coupled	couple	VERB
brj-23786	196	6	kinetic	kinetic	NOUN
brj-23786	196	7	-	-	PUNCT
brj-23786	196	8	ann	ann	NOUN
brj-23786	196	9	model	model	NOUN
brj-23786	196	10	achieved	achieve	VERB
brj-23786	196	11	an	an	DET
brj-23786	196	12	r²	r²	NOUN
brj-23786	196	13	value	value	NOUN
brj-23786	196	14	of	of	ADP
brj-23786	196	15	more	more	ADJ
brj-23786	196	16	than	than	ADP
brj-23786	196	17	0.9999	0.9999	NUM
brj-23786	196	18	,	,	PUNCT
brj-23786	196	19	outperforming	outperform	VERB
brj-23786	196	20	both	both	CCONJ
brj-23786	196	21	the	the	DET
brj-23786	196	22	kinetic	kinetic	ADJ
brj-23786	196	23	model	model	NOUN
brj-23786	196	24	and	and	CCONJ
brj-23786	196	25	the	the	DET
brj-23786	196	26	ga	ga	PROPN
brj-23786	196	27	-	-	PUNCT
brj-23786	196	28	bp	bp	PROPN
brj-23786	196	29	-	-	PUNCT
brj-23786	196	30	ann	ann	PROPN
brj-23786	196	31	model	model	NOUN
brj-23786	196	32	.	.	PUNCT
brj-23786	197	1	this	this	PRON
brj-23786	197	2	is	be	AUX
brj-23786	197	3	consistent	consistent	ADJ
brj-23786	197	4	with	with	ADP
brj-23786	197	5	the	the	DET
brj-23786	197	6	sep	sep	NOUN
brj-23786	197	7	trend	trend	NOUN
brj-23786	197	8	,	,	PUNCT
brj-23786	197	9	which	which	PRON
brj-23786	197	10	was	be	AUX
brj-23786	197	11	below	below	ADP
brj-23786	197	12	0.25	0.25	NUM
brj-23786	197	13	%	%	NOUN
brj-23786	197	14	for	for	ADP
brj-23786	197	15	the	the	DET
brj-23786	197	16	coupled	couple	VERB
brj-23786	197	17	model	model	NOUN
brj-23786	197	18	,	,	PUNCT
brj-23786	197	19	compensating	compensate	VERB
brj-23786	197	20	for	for	ADP
brj-23786	197	21	the	the	DET
brj-23786	197	22	lack	lack	NOUN
brj-23786	197	23	of	of	ADP
brj-23786	197	24	predictive	predictive	ADJ
brj-23786	197	25	power	power	NOUN
brj-23786	197	26	of	of	ADP
brj-23786	197	27	a	a	DET
brj-23786	197	28	single	single	ADJ
brj-23786	197	29	model	model	NOUN
brj-23786	197	30	in	in	ADP
brj-23786	197	31	untrained	untrained	ADJ
brj-23786	197	32	regions	region	NOUN
brj-23786	197	33	.	.	PUNCT
brj-23786	198	1	peer	peer	NOUN
brj-23786	198	2	-	-	PUNCT
brj-23786	198	3	reviewed	review	VERB
brj-23786	198	4	article	article	NOUN
brj-23786	198	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	198	6	xu	xu	PROPN
brj-23786	198	7	et	et	PROPN
brj-23786	198	8	al	al	PROPN
brj-23786	198	9	.	.	PROPN
brj-23786	198	10	(	(	PUNCT
brj-23786	198	11	2024	2024	NUM
brj-23786	198	12	)	)	PUNCT
brj-23786	198	13	.	.	PUNCT
brj-23786	199	1	“	"	PUNCT
brj-23786	199	2	pyrolysis	pyrolysis	NOUN
brj-23786	199	3	kinetics	kinetic	NOUN
brj-23786	199	4	with	with	ADP
brj-23786	199	5	ann	ann	PROPN
brj-23786	199	6	,	,	PUNCT
brj-23786	199	7	”	"	PUNCT
brj-23786	199	8	bioresources	bioresource	NOUN
brj-23786	199	9	19(4	19(4	NUM
brj-23786	199	10	)	)	PUNCT
brj-23786	199	11	,	,	PUNCT
brj-23786	199	12	7513	7513	NUM
brj-23786	199	13	-	-	SYM
brj-23786	199	14	7529	7529	NUM
brj-23786	199	15	.	.	PUNCT
brj-23786	200	1	7524	7524	NUM
brj-23786	200	2	fig	fig	NOUN
brj-23786	200	3	.	.	PUNCT
brj-23786	201	1	6	6	NUM
brj-23786	201	2	(	(	PUNCT
brj-23786	201	3	a	a	NOUN
brj-23786	201	4	-	-	PUNCT
brj-23786	201	5	f	f	NOUN
brj-23786	201	6	)	)	PUNCT
brj-23786	201	7	.	.	PUNCT
brj-23786	202	1	comparison	comparison	NOUN
brj-23786	202	2	of	of	ADP
brj-23786	202	3	𝜶	𝜶	NOUN
brj-23786	202	4	and	and	CCONJ
brj-23786	202	5	𝐝𝜶	𝐝𝜶	PRON
brj-23786	202	6	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	202	7	predictions	prediction	NOUN
brj-23786	202	8	at	at	ADP
brj-23786	202	9	10	10	NUM
brj-23786	202	10	,	,	PUNCT
brj-23786	202	11	20	20	NUM
brj-23786	202	12	and	and	CCONJ
brj-23786	202	13	40	40	NUM
brj-23786	202	14	k	k	NOUN
brj-23786	202	15	/	/	SYM
brj-23786	202	16	min	min	NOUN
brj-23786	202	17	from	from	ADP
brj-23786	202	18	three	three	NUM
brj-23786	202	19	models	model	NOUN
brj-23786	202	20	however	however	ADV
brj-23786	202	21	,	,	PUNCT
brj-23786	202	22	fig	fig	NOUN
brj-23786	202	23	.	.	PUNCT
brj-23786	203	1	7(b	7(b	X
brj-23786	203	2	,	,	PUNCT
brj-23786	203	3	d	d	X
brj-23786	203	4	)	)	PUNCT
brj-23786	203	5	shows	show	VERB
brj-23786	203	6	that	that	SCONJ
brj-23786	203	7	the	the	DET
brj-23786	203	8	kinetic	kinetic	ADJ
brj-23786	203	9	model	model	NOUN
brj-23786	203	10	performed	perform	VERB
brj-23786	203	11	extremely	extremely	ADV
brj-23786	203	12	poorly	poorly	ADV
brj-23786	203	13	in	in	ADP
brj-23786	203	14	predicting	predict	VERB
brj-23786	203	15	conversion	conversion	NOUN
brj-23786	203	16	rate	rate	NOUN
brj-23786	203	17	(	(	PUNCT
brj-23786	203	18	𝑑𝛼	𝑑𝛼	NOUN
brj-23786	203	19	𝑑𝑇⁄	𝑑𝑇⁄	NOUN
brj-23786	203	20	)	)	PUNCT
brj-23786	203	21	at	at	ADP
brj-23786	203	22	the	the	DET
brj-23786	203	23	untrained	untrained	ADJ
brj-23786	203	24	heating	heating	NOUN
brj-23786	203	25	rate	rate	NOUN
brj-23786	203	26	of	of	ADP
brj-23786	203	27	40	40	NUM
brj-23786	203	28	k	k	NOUN
brj-23786	203	29	/	/	SYM
brj-23786	203	30	min	min	NOUN
brj-23786	203	31	(	(	PUNCT
brj-23786	203	32	r2	r2	PROPN
brj-23786	203	33	:	:	PUNCT
brj-23786	203	34	0.74119	0.74119	NUM
brj-23786	203	35	,	,	PUNCT
brj-23786	203	36	sep	sep	PROPN
brj-23786	203	37	:	:	PUNCT
brj-23786	203	38	9.409	9.409	NUM
brj-23786	203	39	%	%	NOUN
brj-23786	203	40	)	)	PUNCT
brj-23786	203	41	.	.	PUNCT
brj-23786	204	1	in	in	ADP
brj-23786	204	2	contrast	contrast	NOUN
brj-23786	204	3	,	,	PUNCT
brj-23786	204	4	the	the	DET
brj-23786	204	5	coupled	couple	VERB
brj-23786	204	6	model	model	NOUN
brj-23786	204	7	maintained	maintain	VERB
brj-23786	204	8	a	a	DET
brj-23786	204	9	high	high	ADJ
brj-23786	204	10	level	level	NOUN
brj-23786	204	11	of	of	ADP
brj-23786	204	12	accuracy	accuracy	NOUN
brj-23786	204	13	,	,	PUNCT
brj-23786	204	14	with	with	ADP
brj-23786	204	15	an	an	DET
brj-23786	204	16	r2	r2	NOUN
brj-23786	204	17	value	value	NOUN
brj-23786	204	18	of	of	ADP
brj-23786	204	19	0.99944	0.99944	NUM
brj-23786	204	20	and	and	CCONJ
brj-23786	204	21	an	an	DET
brj-23786	204	22	sep	sep	NOUN
brj-23786	204	23	value	value	NOUN
brj-23786	204	24	of	of	ADP
brj-23786	204	25	0.447	0.447	NUM
brj-23786	204	26	%	%	NOUN
brj-23786	204	27	.	.	PUNCT
brj-23786	205	1	it	it	PRON
brj-23786	205	2	was	be	AUX
brj-23786	205	3	found	find	VERB
brj-23786	205	4	that	that	SCONJ
brj-23786	205	5	the	the	DET
brj-23786	205	6	r2	r2	PROPN
brj-23786	205	7	value	value	NOUN
brj-23786	205	8	of	of	ADP
brj-23786	205	9	the	the	DET
brj-23786	205	10	conversion	conversion	NOUN
brj-23786	205	11	degree	degree	NOUN
brj-23786	205	12	was	be	AUX
brj-23786	205	13	consistently	consistently	ADV
brj-23786	205	14	higher	high	ADJ
brj-23786	205	15	than	than	ADP
brj-23786	205	16	that	that	PRON
brj-23786	205	17	of	of	ADP
brj-23786	205	18	the	the	DET
brj-23786	205	19	conversion	conversion	NOUN
brj-23786	205	20	rate	rate	NOUN
brj-23786	205	21	,	,	PUNCT
brj-23786	205	22	whether	whether	SCONJ
brj-23786	205	23	in	in	ADP
brj-23786	205	24	trained	train	VERB
brj-23786	205	25	or	or	CCONJ
brj-23786	205	26	untrained	untrained	ADJ
brj-23786	205	27	regions	region	NOUN
brj-23786	205	28	.	.	PUNCT
brj-23786	206	1	this	this	DET
brj-23786	206	2	difference	difference	NOUN
brj-23786	206	3	may	may	AUX
brj-23786	206	4	be	be	AUX
brj-23786	206	5	due	due	ADJ
brj-23786	206	6	to	to	ADP
brj-23786	206	7	the	the	DET
brj-23786	206	8	fact	fact	NOUN
brj-23786	206	9	that	that	SCONJ
brj-23786	206	10	the	the	DET
brj-23786	206	11	conversion	conversion	NOUN
brj-23786	206	12	rate	rate	NOUN
brj-23786	206	13	is	be	AUX
brj-23786	206	14	derived	derive	VERB
brj-23786	206	15	from	from	ADP
brj-23786	206	16	the	the	DET
brj-23786	206	17	derivative	derivative	NOUN
brj-23786	206	18	of	of	ADP
brj-23786	206	19	the	the	DET
brj-23786	206	20	conversion	conversion	NOUN
brj-23786	206	21	degree	degree	NOUN
brj-23786	206	22	,	,	PUNCT
brj-23786	206	23	making	make	VERB
brj-23786	206	24	it	it	PRON
brj-23786	206	25	more	more	ADV
brj-23786	206	26	susceptible	susceptible	ADJ
brj-23786	206	27	to	to	ADP
brj-23786	206	28	noise	noise	NOUN
brj-23786	206	29	.	.	PUNCT
brj-23786	207	1	peer	peer	NOUN
brj-23786	207	2	-	-	PUNCT
brj-23786	207	3	reviewed	review	VERB
brj-23786	207	4	article	article	NOUN
brj-23786	207	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	207	6	xu	xu	PROPN
brj-23786	207	7	et	et	PROPN
brj-23786	207	8	al	al	PROPN
brj-23786	207	9	.	.	PROPN
brj-23786	207	10	(	(	PUNCT
brj-23786	207	11	2024	2024	NUM
brj-23786	207	12	)	)	PUNCT
brj-23786	207	13	.	.	PUNCT
brj-23786	208	1	“	"	PUNCT
brj-23786	208	2	pyrolysis	pyrolysis	NOUN
brj-23786	208	3	kinetics	kinetic	NOUN
brj-23786	208	4	with	with	ADP
brj-23786	208	5	ann	ann	PROPN
brj-23786	208	6	,	,	PUNCT
brj-23786	208	7	”	"	PUNCT
brj-23786	208	8	bioresources	bioresource	NOUN
brj-23786	208	9	19(4	19(4	NUM
brj-23786	208	10	)	)	PUNCT
brj-23786	208	11	,	,	PUNCT
brj-23786	208	12	7513	7513	NUM
brj-23786	208	13	-	-	SYM
brj-23786	208	14	7529	7529	NUM
brj-23786	208	15	.	.	PUNCT
brj-23786	209	1	7525	7525	NUM
brj-23786	209	2	fig	fig	NOUN
brj-23786	209	3	.	.	PUNCT
brj-23786	210	1	7	7	NUM
brj-23786	210	2	(	(	PUNCT
brj-23786	210	3	a	a	NOUN
brj-23786	210	4	-	-	PUNCT
brj-23786	210	5	d	d	NOUN
brj-23786	210	6	)	)	PUNCT
brj-23786	210	7	.	.	PUNCT
brj-23786	211	1	r2	r2	PROPN
brj-23786	211	2	and	and	CCONJ
brj-23786	211	3	sep	sep	PROPN
brj-23786	211	4	comparison	comparison	NOUN
brj-23786	211	5	of	of	ADP
brj-23786	211	6	𝜶	𝜶	NOUN
brj-23786	211	7	and	and	CCONJ
brj-23786	211	8	𝐝𝜶	𝐝𝜶	PRON
brj-23786	211	9	𝐝𝑻	𝐝𝑻	NOUN
brj-23786	211	10	predictions	prediction	NOUN
brj-23786	211	11	at	at	ADP
brj-23786	211	12	10	10	NUM
brj-23786	211	13	,	,	PUNCT
brj-23786	211	14	20	20	NUM
brj-23786	211	15	and	and	CCONJ
brj-23786	211	16	40	40	NUM
brj-23786	211	17	k	k	NOUN
brj-23786	211	18	/	/	SYM
brj-23786	211	19	min	min	NOUN
brj-23786	211	20	from	from	ADP
brj-23786	211	21	three	three	NUM
brj-23786	211	22	models	model	NOUN
brj-23786	211	23	conclusions	conclusion	NOUN
brj-23786	211	24	1	1	X
brj-23786	211	25	.	.	PUNCT
brj-23786	212	1	this	this	DET
brj-23786	212	2	paper	paper	NOUN
brj-23786	212	3	successfully	successfully	ADV
brj-23786	212	4	proposed	propose	VERB
brj-23786	212	5	an	an	DET
brj-23786	212	6	innovative	innovative	ADJ
brj-23786	212	7	biomass	biomass	NOUN
brj-23786	212	8	pyrolysis	pyrolysis	NOUN
brj-23786	212	9	modeling	model	VERB
brj-23786	212	10	scheme	scheme	NOUN
brj-23786	212	11	that	that	PRON
brj-23786	212	12	integrates	integrate	VERB
brj-23786	212	13	a	a	DET
brj-23786	212	14	kinetic	kinetic	ADJ
brj-23786	212	15	model	model	NOUN
brj-23786	212	16	based	base	VERB
brj-23786	212	17	on	on	ADP
brj-23786	212	18	chemical	chemical	ADJ
brj-23786	212	19	reaction	reaction	NOUN
brj-23786	212	20	mechanisms	mechanism	NOUN
brj-23786	212	21	with	with	ADP
brj-23786	212	22	an	an	DET
brj-23786	212	23	empirically	empirically	ADV
brj-23786	212	24	-	-	PUNCT
brj-23786	212	25	based	base	VERB
brj-23786	212	26	machine	machine	NOUN
brj-23786	212	27	learning	learning	NOUN
brj-23786	212	28	model	model	NOUN
brj-23786	212	29	.	.	PUNCT
brj-23786	213	1	when	when	SCONJ
brj-23786	213	2	validated	validate	VERB
brj-23786	213	3	against	against	ADP
brj-23786	213	4	experimental	experimental	ADJ
brj-23786	213	5	data	datum	NOUN
brj-23786	213	6	,	,	PUNCT
brj-23786	213	7	the	the	DET
brj-23786	213	8	method	method	NOUN
brj-23786	213	9	demonstrated	demonstrate	VERB
brj-23786	213	10	extremely	extremely	ADV
brj-23786	213	11	high	high	ADJ
brj-23786	213	12	prediction	prediction	NOUN
brj-23786	213	13	accuracy	accuracy	NOUN
brj-23786	213	14	,	,	PUNCT
brj-23786	213	15	particularly	particularly	ADV
brj-23786	213	16	in	in	ADP
brj-23786	213	17	unfamiliar	unfamiliar	ADJ
brj-23786	213	18	scenarios	scenario	NOUN
brj-23786	213	19	,	,	PUNCT
brj-23786	213	20	showcasing	showcase	VERB
brj-23786	213	21	significant	significant	ADJ
brj-23786	213	22	advantages	advantage	NOUN
brj-23786	213	23	.	.	PUNCT
brj-23786	214	1	2	2	X
brj-23786	214	2	.	.	X
brj-23786	214	3	in	in	ADP
brj-23786	214	4	the	the	DET
brj-23786	214	5	study	study	NOUN
brj-23786	214	6	of	of	ADP
brj-23786	214	7	chemical	chemical	ADJ
brj-23786	214	8	reaction	reaction	NOUN
brj-23786	214	9	kinetic	kinetic	NOUN
brj-23786	214	10	modeling	modeling	NOUN
brj-23786	214	11	,	,	PUNCT
brj-23786	214	12	the	the	DET
brj-23786	214	13	introduction	introduction	NOUN
brj-23786	214	14	of	of	ADP
brj-23786	214	15	the	the	DET
brj-23786	214	16	improved	improved	ADJ
brj-23786	214	17	dung	dung	NOUN
brj-23786	214	18	beetle	beetle	NOUN
brj-23786	214	19	optimization	optimization	NOUN
brj-23786	214	20	algorithm	algorithm	NOUN
brj-23786	214	21	significantly	significantly	ADV
brj-23786	214	22	enhances	enhance	VERB
brj-23786	214	23	the	the	DET
brj-23786	214	24	capability	capability	NOUN
brj-23786	214	25	to	to	ADP
brj-23786	214	26	fine	fine	ADJ
brj-23786	214	27	-	-	PUNCT
brj-23786	214	28	tune	tune	NOUN
brj-23786	214	29	kinetic	kinetic	NOUN
brj-23786	214	30	parameters	parameter	NOUN
brj-23786	214	31	.	.	PUNCT
brj-23786	215	1	this	this	DET
brj-23786	215	2	enhancement	enhancement	NOUN
brj-23786	215	3	allows	allow	VERB
brj-23786	215	4	the	the	DET
brj-23786	215	5	model	model	NOUN
brj-23786	215	6	to	to	PART
brj-23786	215	7	more	more	ADV
brj-23786	215	8	accurately	accurately	ADV
brj-23786	215	9	describe	describe	VERB
brj-23786	215	10	complex	complex	ADJ
brj-23786	215	11	pyrolysis	pyrolysis	NOUN
brj-23786	215	12	processes	process	NOUN
brj-23786	215	13	and	and	CCONJ
brj-23786	215	14	improves	improve	VERB
brj-23786	215	15	prediction	prediction	NOUN
brj-23786	215	16	reliability	reliability	NOUN
brj-23786	215	17	.	.	PUNCT
brj-23786	216	1	3	3	X
brj-23786	216	2	.	.	X
brj-23786	216	3	through	through	ADP
brj-23786	216	4	comparison	comparison	NOUN
brj-23786	216	5	,	,	PUNCT
brj-23786	216	6	it	it	PRON
brj-23786	216	7	was	be	AUX
brj-23786	216	8	found	find	VERB
brj-23786	216	9	that	that	SCONJ
brj-23786	216	10	among	among	ADP
brj-23786	216	11	the	the	DET
brj-23786	216	12	three	three	NUM
brj-23786	216	13	prediction	prediction	NOUN
brj-23786	216	14	models	model	NOUN
brj-23786	216	15	,	,	PUNCT
brj-23786	216	16	predicting	predict	VERB
brj-23786	216	17	the	the	DET
brj-23786	216	18	degree	degree	NOUN
brj-23786	216	19	of	of	ADP
brj-23786	216	20	conversion	conversion	NOUN
brj-23786	216	21	performs	perform	VERB
brj-23786	216	22	better	well	ADV
brj-23786	216	23	than	than	ADP
brj-23786	216	24	predicting	predict	VERB
brj-23786	216	25	the	the	DET
brj-23786	216	26	conversion	conversion	NOUN
brj-23786	216	27	rate	rate	NOUN
brj-23786	216	28	.	.	PUNCT
brj-23786	217	1	this	this	PRON
brj-23786	217	2	may	may	AUX
brj-23786	217	3	be	be	AUX
brj-23786	217	4	due	due	ADJ
brj-23786	217	5	to	to	PART
brj-23786	217	6	noise	noise	VERB
brj-23786	217	7	errors	error	NOUN
brj-23786	217	8	in	in	ADP
brj-23786	217	9	the	the	DET
brj-23786	217	10	derivative	derivative	ADJ
brj-23786	217	11	calculation	calculation	NOUN
brj-23786	217	12	of	of	ADP
brj-23786	217	13	conversion	conversion	NOUN
brj-23786	217	14	rate	rate	NOUN
brj-23786	217	15	parameters	parameter	NOUN
brj-23786	217	16	.	.	PUNCT
brj-23786	218	1	acknowledgments	acknowledgment	NOUN
brj-23786	218	2	this	this	DET
brj-23786	218	3	study	study	NOUN
brj-23786	218	4	is	be	AUX
brj-23786	218	5	supported	support	VERB
brj-23786	218	6	by	by	ADP
brj-23786	218	7	international	international	ADJ
brj-23786	218	8	science	science	NOUN
brj-23786	218	9	and	and	CCONJ
brj-23786	218	10	technology	technology	NOUN
brj-23786	218	11	cooperation	cooperation	NOUN
brj-23786	218	12	project	project	NOUN
brj-23786	218	13	of	of	ADP
brj-23786	218	14	henan	henan	PROPN
brj-23786	218	15	province	province	PROPN
brj-23786	218	16	(	(	PUNCT
brj-23786	218	17	232102521011	232102521011	NUM
brj-23786	218	18	)	)	PUNCT
brj-23786	218	19	;	;	PUNCT
brj-23786	218	20	natural	natural	ADJ
brj-23786	218	21	science	science	NOUN
brj-23786	218	22	foundation	foundation	PROPN
brj-23786	218	23	of	of	ADP
brj-23786	218	24	sichuan	sichuan	PROPN
brj-23786	218	25	peer	peer	NOUN
brj-23786	218	26	-	-	PUNCT
brj-23786	218	27	reviewed	review	VERB
brj-23786	218	28	article	article	NOUN
brj-23786	218	29	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	218	30	xu	xu	PROPN
brj-23786	218	31	et	et	PROPN
brj-23786	218	32	al	al	PROPN
brj-23786	218	33	.	.	PROPN
brj-23786	219	1	(	(	PUNCT
brj-23786	219	2	2024	2024	NUM
brj-23786	219	3	)	)	PUNCT
brj-23786	219	4	.	.	PUNCT
brj-23786	220	1	“	"	PUNCT
brj-23786	220	2	pyrolysis	pyrolysis	NOUN
brj-23786	220	3	kinetics	kinetic	NOUN
brj-23786	220	4	with	with	ADP
brj-23786	220	5	ann	ann	PROPN
brj-23786	220	6	,	,	PUNCT
brj-23786	220	7	”	"	PUNCT
brj-23786	220	8	bioresources	bioresource	NOUN
brj-23786	220	9	19(4	19(4	NUM
brj-23786	220	10	)	)	PUNCT
brj-23786	220	11	,	,	PUNCT
brj-23786	220	12	7513	7513	NUM
brj-23786	220	13	-	-	SYM
brj-23786	220	14	7529	7529	NUM
brj-23786	220	15	.	.	PUNCT
brj-23786	221	1	7526	7526	NUM
brj-23786	221	2	province	province	NOUN
brj-23786	221	3	(	(	PUNCT
brj-23786	221	4	2023nsfsc1253	2023nsfsc1253	NUM
brj-23786	221	5	)	)	PUNCT
brj-23786	221	6	;	;	PUNCT
brj-23786	221	7	regional	regional	ADJ
brj-23786	221	8	innovation	innovation	NOUN
brj-23786	221	9	cooperation	cooperation	NOUN
brj-23786	221	10	project	project	NOUN
brj-23786	221	11	of	of	ADP
brj-23786	221	12	sichuan	sichuan	PROPN
brj-23786	221	13	province	province	PROPN
brj-23786	221	14	(	(	PUNCT
brj-23786	221	15	2024yfhz0148	2024yfhz0148	PROPN
brj-23786	221	16	)	)	PUNCT
brj-23786	221	17	;	;	PUNCT
brj-23786	221	18	agricultural	agricultural	ADJ
brj-23786	221	19	science	science	NOUN
brj-23786	221	20	and	and	CCONJ
brj-23786	221	21	technology	technology	NOUN
brj-23786	221	22	innovation	innovation	NOUN
brj-23786	221	23	project	project	NOUN
brj-23786	221	24	of	of	ADP
brj-23786	221	25	chinese	chinese	PROPN
brj-23786	221	26	academy	academy	PROPN
brj-23786	221	27	of	of	ADP
brj-23786	221	28	agricultural	agricultural	ADJ
brj-23786	221	29	sciences	science	NOUN
brj-23786	221	30	(	(	PUNCT
brj-23786	221	31	caas	caas	ADJ
brj-23786	221	32	-	-	PUNCT
brj-23786	221	33	astip-2016	astip-2016	NOUN
brj-23786	221	34	-	-	PUNCT
brj-23786	221	35	bioma	bioma	NOUN
brj-23786	221	36	)	)	PUNCT
brj-23786	221	37	.	.	PUNCT
brj-23786	222	1	references	reference	NOUN
brj-23786	222	2	cited	cite	VERB
brj-23786	222	3	alaba	alaba	PROPN
brj-23786	222	4	,	,	PUNCT
brj-23786	222	5	p.	p.	PROPN
brj-23786	222	6	,	,	PUNCT
brj-23786	222	7	popoola	popoola	PROPN
brj-23786	222	8	,	,	PUNCT
brj-23786	222	9	s.	s.	PROPN
brj-23786	222	10	,	,	PUNCT
brj-23786	222	11	abnisal	abnisal	NOUN
brj-23786	222	12	,	,	PUNCT
brj-23786	222	13	f.	f.	PROPN
brj-23786	222	14	,	,	PUNCT
brj-23786	222	15	lee	lee	PROPN
brj-23786	222	16	,	,	PUNCT
brj-23786	222	17	c.	c.	PROPN
brj-23786	222	18	,	,	PUNCT
brj-23786	222	19	ohunakin	ohunakin	NOUN
brj-23786	222	20	,	,	PUNCT
brj-23786	222	21	o.	o.	PROPN
brj-23786	222	22	,	,	PUNCT
brj-23786	222	23	adetiba	adetiba	PROPN
brj-23786	222	24	,	,	PUNCT
brj-23786	222	25	e.	e.	PROPN
brj-23786	222	26	,	,	PUNCT
brj-23786	222	27	akanle	akanle	PROPN
brj-23786	222	28	,	,	PUNCT
brj-23786	222	29	m.	m.	NOUN
brj-23786	222	30	,	,	PUNCT
brj-23786	222	31	patah	patah	NOUN
brj-23786	222	32	,	,	PUNCT
brj-23786	222	33	m.	m.	NOUN
brj-23786	222	34	,	,	PUNCT
brj-23786	222	35	atayero	atayero	PROPN
brj-23786	222	36	,	,	PUNCT
brj-23786	222	37	a.	a.	NOUN
brj-23786	222	38	,	,	PUNCT
brj-23786	222	39	and	and	CCONJ
brj-23786	222	40	daud	daud	PROPN
brj-23786	222	41	,	,	PUNCT
brj-23786	222	42	w.	w.	PROPN
brj-23786	222	43	(	(	PUNCT
brj-23786	222	44	2019	2019	NUM
brj-23786	222	45	)	)	PUNCT
brj-23786	222	46	.	.	PUNCT
brj-23786	223	1	“	"	PUNCT
brj-23786	223	2	thermal	thermal	ADJ
brj-23786	223	3	decomposition	decomposition	NOUN
brj-23786	223	4	of	of	ADP
brj-23786	223	5	rice	rice	NOUN
brj-23786	223	6	husk	husk	NOUN
brj-23786	223	7	:	:	PUNCT
brj-23786	223	8	a	a	DET
brj-23786	223	9	comprehensive	comprehensive	ADJ
brj-23786	223	10	artificial	artificial	ADJ
brj-23786	223	11	intelligence	intelligence	NOUN
brj-23786	223	12	predictive	predictive	ADJ
brj-23786	223	13	model	model	NOUN
brj-23786	223	14	,	,	PUNCT
brj-23786	223	15	”	"	PUNCT
brj-23786	223	16	journal	journal	NOUN
brj-23786	223	17	of	of	ADP
brj-23786	223	18	thermal	thermal	ADJ
brj-23786	223	19	analysis	analysis	NOUN
brj-23786	223	20	and	and	CCONJ
brj-23786	223	21	calorimetry	calorimetry	NOUN
brj-23786	223	22	140	140	NUM
brj-23786	223	23	,	,	PUNCT
brj-23786	223	24	1811	1811	NUM
brj-23786	223	25	-	-	SYM
brj-23786	223	26	1823	1823	NUM
brj-23786	223	27	.	.	PUNCT
brj-23786	224	1	doi	doi	NOUN
brj-23786	224	2	:	:	PUNCT
brj-23786	224	3	10.1007	10.1007	NUM
brj-23786	224	4	/	/	SYM
brj-23786	224	5	s10973	s10973	NOUN
brj-23786	224	6	-	-	PUNCT
brj-23786	224	7	019	019	NUM
brj-23786	224	8	-	-	PUNCT
brj-23786	224	9	08915	08915	NUM
brj-23786	224	10	-	-	SYM
brj-23786	224	11	0	0	NUM
brj-23786	224	12	breiman	breiman	NOUN
brj-23786	224	13	,	,	PUNCT
brj-23786	224	14	l.	l.	PROPN
brj-23786	224	15	(	(	PUNCT
brj-23786	224	16	1996	1996	NUM
brj-23786	224	17	)	)	PUNCT
brj-23786	224	18	.	.	PUNCT
brj-23786	225	1	“	"	PUNCT
brj-23786	225	2	mach	mach	NOUN
brj-23786	225	3	learn	learn	VERB
brj-23786	225	4	24	24	NUM
brj-23786	225	5	,	,	PUNCT
brj-23786	225	6	”	"	PUNCT
brj-23786	225	7	in	in	ADP
brj-23786	225	8	:	:	PUNCT
brj-23786	225	9	stacked	stack	VERB
brj-23786	225	10	regressions	regression	NOUN
brj-23786	225	11	,	,	PUNCT
brj-23786	225	12	49	49	NUM
brj-23786	225	13	-	-	SYM
brj-23786	225	14	64	64	NUM
brj-23786	225	15	.	.	PUNCT
brj-23786	226	1	doi	doi	NOUN
brj-23786	226	2	:	:	PUNCT
brj-23786	226	3	10	10	NUM
brj-23786	226	4	.	.	PUNCT
brj-23786	226	5	1007	1007	NUM
brj-23786	226	6	/	/	SYM
brj-23786	226	7	bf00117832	bf00117832	NOUN
brj-23786	226	8	bi	bi	NOUN
brj-23786	226	9	,	,	PUNCT
brj-23786	226	10	h.	h.	PROPN
brj-23786	226	11	,	,	PUNCT
brj-23786	226	12	wang	wang	PROPN
brj-23786	226	13	,	,	PUNCT
brj-23786	226	14	c.	c.	PROPN
brj-23786	226	15	,	,	PUNCT
brj-23786	226	16	jiang	jiang	PROPN
brj-23786	226	17	,	,	PUNCT
brj-23786	226	18	x.	x.	PROPN
brj-23786	226	19	,	,	PUNCT
brj-23786	226	20	jiang	jiang	PROPN
brj-23786	226	21	,	,	PUNCT
brj-23786	226	22	c.	c.	PROPN
brj-23786	226	23	,	,	PUNCT
brj-23786	226	24	bao	bao	PROPN
brj-23786	226	25	,	,	PUNCT
brj-23786	226	26	l.	l.	PROPN
brj-23786	226	27	,	,	PUNCT
brj-23786	226	28	and	and	CCONJ
brj-23786	226	29	lin	lin	PROPN
brj-23786	226	30	,	,	PUNCT
brj-23786	226	31	q.	q.	PROPN
brj-23786	226	32	(	(	PUNCT
brj-23786	226	33	2021	2021	NUM
brj-23786	226	34	)	)	PUNCT
brj-23786	226	35	.	.	PUNCT
brj-23786	227	1	“	"	PUNCT
brj-23786	227	2	thermodynamics	thermodynamic	NOUN
brj-23786	227	3	,	,	PUNCT
brj-23786	227	4	kinetics	kinetic	NOUN
brj-23786	227	5	,	,	PUNCT
brj-23786	227	6	gas	gas	NOUN
brj-23786	227	7	emissions	emission	NOUN
brj-23786	227	8	and	and	CCONJ
brj-23786	227	9	artificial	artificial	ADJ
brj-23786	227	10	neural	neural	ADJ
brj-23786	227	11	network	network	NOUN
brj-23786	227	12	modeling	modeling	NOUN
brj-23786	227	13	of	of	ADP
brj-23786	227	14	co	co	NOUN
brj-23786	227	15	-	-	NOUN
brj-23786	227	16	pyrolysis	pyrolysis	NOUN
brj-23786	227	17	of	of	ADP
brj-23786	227	18	sewage	sewage	NOUN
brj-23786	227	19	sludge	sludge	NOUN
brj-23786	227	20	and	and	CCONJ
brj-23786	227	21	peanut	peanut	NOUN
brj-23786	227	22	shell	shell	NOUN
brj-23786	227	23	,	,	PUNCT
brj-23786	227	24	”	"	PUNCT
brj-23786	227	25	fuel	fuel	NOUN
brj-23786	227	26	284	284	NUM
brj-23786	227	27	,	,	PUNCT
brj-23786	227	28	article	article	NOUN
brj-23786	227	29	118988	118988	NUM
brj-23786	227	30	.	.	PUNCT
brj-23786	228	1	doi	doi	NOUN
brj-23786	228	2	:	:	PUNCT
brj-23786	228	3	10.1016	10.1016	NUM
brj-23786	228	4	/	/	SYM
brj-23786	228	5	j.	j.	PROPN
brj-23786	228	6	fuel	fuel	PROPN
brj-23786	228	7	.	.	PUNCT
brj-23786	229	1	2020	2020	NUM
brj-23786	229	2	.	.	PUNCT
brj-23786	230	1	118988	118988	NUM
brj-23786	230	2	chang	chang	PROPN
brj-23786	230	3	,	,	PUNCT
brj-23786	230	4	d.	d.	PROPN
brj-23786	230	5	,	,	PUNCT
brj-23786	230	6	zhang	zhang	PROPN
brj-23786	230	7	,	,	PUNCT
brj-23786	230	8	x.	x.	PROPN
brj-23786	230	9	,	,	PUNCT
brj-23786	230	10	and	and	CCONJ
brj-23786	230	11	zheng	zheng	PROPN
brj-23786	230	12	,	,	PUNCT
brj-23786	230	13	c.	c.	PROPN
brj-23786	230	14	(	(	PUNCT
brj-23786	230	15	2008	2008	NUM
brj-23786	230	16	)	)	PUNCT
brj-23786	230	17	.	.	PUNCT
brj-23786	231	1	“	"	PUNCT
brj-23786	231	2	a	a	DET
brj-23786	231	3	genetic	genetic	ADJ
brj-23786	231	4	algorithm	algorithm	NOUN
brj-23786	231	5	with	with	ADP
brj-23786	231	6	gene	gene	NOUN
brj-23786	231	7	rearrangement	rearrangement	NOUN
brj-23786	231	8	for	for	ADP
brj-23786	231	9	k	k	NOUN
brj-23786	231	10	-	-	PUNCT
brj-23786	231	11	means	means	NOUN
brj-23786	231	12	clustering	clustering	NOUN
brj-23786	231	13	,	,	PUNCT
brj-23786	231	14	”	"	PUNCT
brj-23786	231	15	pattern	pattern	NOUN
brj-23786	231	16	recognition	recognition	NOUN
brj-23786	231	17	42(7	42(7	PROPN
brj-23786	231	18	)	)	PUNCT
brj-23786	231	19	,	,	PUNCT
brj-23786	231	20	1210	1210	NUM
brj-23786	231	21	-	-	SYM
brj-23786	231	22	1222	1222	NUM
brj-23786	231	23	.	.	PUNCT
brj-23786	232	1	doi	doi	NOUN
brj-23786	232	2	:	:	PUNCT
brj-23786	232	3	10	10	NUM
brj-23786	232	4	.	.	X
brj-23786	233	1	1016	1016	NUM
brj-23786	233	2	/	/	SYM
brj-23786	233	3	j.	j.	PROPN
brj-23786	233	4	patcog	patcog	PROPN
brj-23786	233	5	.	.	PUNCT
brj-23786	234	1	2008	2008	NUM
brj-23786	234	2	.	.	PUNCT
brj-23786	235	1	11	11	NUM
brj-23786	235	2	.	.	X
brj-23786	235	3	006	006	NUM
brj-23786	235	4	cheng	cheng	PROPN
brj-23786	235	5	,	,	PUNCT
brj-23786	235	6	p.	p.	PROPN
brj-23786	235	7	,	,	PUNCT
brj-23786	235	8	wang	wang	PROPN
brj-23786	235	9	,	,	PUNCT
brj-23786	235	10	d.	d.	PROPN
brj-23786	235	11	,	,	PUNCT
brj-23786	235	12	zhou	zhou	PROPN
brj-23786	235	13	,	,	PUNCT
brj-23786	235	14	j.	j.	PROPN
brj-23786	235	15	,	,	PUNCT
brj-23786	235	16	zuo	zuo	PROPN
brj-23786	235	17	,	,	PUNCT
brj-23786	235	18	s.	s.	PROPN
brj-23786	235	19	,	,	PUNCT
brj-23786	235	20	and	and	CCONJ
brj-23786	235	21	zhang	zhang	PROPN
brj-23786	235	22	,	,	PUNCT
brj-23786	235	23	p.	p.	NOUN
brj-23786	235	24	(	(	PUNCT
brj-23786	235	25	2022	2022	NUM
brj-23786	235	26	)	)	PUNCT
brj-23786	235	27	.	.	PUNCT
brj-23786	236	1	“	"	PUNCT
brj-23786	236	2	comparison	comparison	NOUN
brj-23786	236	3	of	of	ADP
brj-23786	236	4	the	the	DET
brj-23786	236	5	warm	warm	ADJ
brj-23786	236	6	deformation	deformation	NOUN
brj-23786	236	7	constitutive	constitutive	ADJ
brj-23786	236	8	model	model	NOUN
brj-23786	236	9	of	of	ADP
brj-23786	236	10	gh4169	gh4169	PROPN
brj-23786	236	11	alloy	alloy	NOUN
brj-23786	236	12	based	base	VERB
brj-23786	236	13	on	on	ADP
brj-23786	236	14	neural	neural	ADJ
brj-23786	236	15	network	network	NOUN
brj-23786	236	16	and	and	CCONJ
brj-23786	236	17	the	the	DET
brj-23786	236	18	arrhenius	arrhenius	PROPN
brj-23786	236	19	model	model	NOUN
brj-23786	236	20	,	,	PUNCT
brj-23786	236	21	”	"	PUNCT
brj-23786	236	22	metals	metal	NOUN
brj-23786	236	23	12(9	12(9	NUM
brj-23786	236	24	)	)	PUNCT
brj-23786	236	25	,	,	PUNCT
brj-23786	236	26	article	article	NOUN
brj-23786	236	27	1429	1429	NUM
brj-23786	236	28	.	.	PUNCT
brj-23786	237	1	doi	doi	NOUN
brj-23786	237	2	:	:	PUNCT
brj-23786	237	3	10.3390	10.3390	NUM
brj-23786	237	4	/	/	SYM
brj-23786	237	5	met12091429	met12091429	PROPN
brj-23786	237	6	conn	conn	PROPN
brj-23786	237	7	,	,	PUNCT
brj-23786	237	8	a.	a.	PROPN
brj-23786	237	9	,	,	PUNCT
brj-23786	237	10	gould	gould	PROPN
brj-23786	237	11	,	,	PUNCT
brj-23786	237	12	n.	n.	NOUN
brj-23786	237	13	,	,	PUNCT
brj-23786	237	14	and	and	CCONJ
brj-23786	237	15	toint	toint	NOUN
brj-23786	237	16	,	,	PUNCT
brj-23786	237	17	p.	p.	NOUN
brj-23786	237	18	(	(	PUNCT
brj-23786	237	19	1991	1991	NUM
brj-23786	237	20	)	)	PUNCT
brj-23786	237	21	.	.	PUNCT
brj-23786	238	1	“	"	PUNCT
brj-23786	238	2	a	a	DET
brj-23786	238	3	globally	globally	ADV
brj-23786	238	4	convergent	convergent	NOUN
brj-23786	238	5	augmented	augment	VERB
brj-23786	238	6	lagrangian	lagrangian	ADJ
brj-23786	238	7	algorithm	algorithm	NOUN
brj-23786	238	8	for	for	ADP
brj-23786	238	9	optimization	optimization	NOUN
brj-23786	238	10	with	with	ADP
brj-23786	238	11	general	general	ADJ
brj-23786	238	12	constraints	constraint	NOUN
brj-23786	238	13	and	and	CCONJ
brj-23786	238	14	simple	simple	ADJ
brj-23786	238	15	bounds	bound	NOUN
brj-23786	238	16	,	,	PUNCT
brj-23786	238	17	”	"	PUNCT
brj-23786	238	18	siam	siam	ADJ
brj-23786	238	19	journal	journal	PROPN
brj-23786	238	20	on	on	ADP
brj-23786	238	21	numerical	numerical	ADJ
brj-23786	238	22	analysis	analysis	NOUN
brj-23786	238	23	28	28	NUM
brj-23786	238	24	,	,	PUNCT
brj-23786	238	25	545	545	NUM
brj-23786	238	26	-	-	SYM
brj-23786	238	27	572	572	NUM
brj-23786	238	28	.	.	PUNCT
brj-23786	239	1	doi	doi	NOUN
brj-23786	239	2	:	:	PUNCT
brj-23786	239	3	10.1137/0728030	10.1137/0728030	NUM
brj-23786	239	4	ding	ding	NOUN
brj-23786	239	5	,	,	PUNCT
brj-23786	239	6	y.	y.	PROPN
brj-23786	239	7	,	,	PUNCT
brj-23786	239	8	zhang	zhang	PROPN
brj-23786	239	9	,	,	PUNCT
brj-23786	239	10	w.	w.	PROPN
brj-23786	239	11	,	,	PUNCT
brj-23786	239	12	yu	yu	PROPN
brj-23786	239	13	,	,	PUNCT
brj-23786	239	14	l.	l.	PROPN
brj-23786	239	15	,	,	PUNCT
brj-23786	239	16	and	and	CCONJ
brj-23786	239	17	lu	lu	PROPN
brj-23786	239	18	,	,	PUNCT
brj-23786	239	19	k.	k.	PROPN
brj-23786	239	20	(	(	PUNCT
brj-23786	239	21	2019	2019	NUM
brj-23786	239	22	)	)	PUNCT
brj-23786	239	23	.	.	PUNCT
brj-23786	240	1	“	"	PUNCT
brj-23786	240	2	the	the	DET
brj-23786	240	3	accuracy	accuracy	NOUN
brj-23786	240	4	and	and	CCONJ
brj-23786	240	5	efficiency	efficiency	NOUN
brj-23786	240	6	of	of	ADP
brj-23786	240	7	ga	ga	PROPN
brj-23786	240	8	and	and	CCONJ
brj-23786	240	9	pso	pso	NOUN
brj-23786	240	10	optimization	optimization	NOUN
brj-23786	240	11	schemes	scheme	NOUN
brj-23786	240	12	on	on	ADP
brj-23786	240	13	estimating	estimate	VERB
brj-23786	240	14	reaction	reaction	NOUN
brj-23786	240	15	kinetic	kinetic	ADJ
brj-23786	240	16	parameters	parameter	NOUN
brj-23786	240	17	of	of	ADP
brj-23786	240	18	biomass	biomass	NOUN
brj-23786	240	19	pyrolysis	pyrolysis	NOUN
brj-23786	240	20	,	,	PUNCT
brj-23786	240	21	”	"	PUNCT
brj-23786	240	22	energy	energy	NOUN
brj-23786	240	23	176	176	NUM
brj-23786	240	24	,	,	PUNCT
brj-23786	240	25	582	582	NUM
brj-23786	240	26	-	-	SYM
brj-23786	240	27	588	588	NUM
brj-23786	240	28	.	.	PUNCT
brj-23786	240	29	doi	doi	NOUN
brj-23786	240	30	:	:	PUNCT
brj-23786	240	31	10.1016	10.1016	NUM
brj-23786	240	32	/	/	SYM
brj-23786	240	33	j.energy.2019.04.030	j.energy.2019.04.030	PROPN
brj-23786	240	34	ding	ding	NOUN
brj-23786	240	35	,	,	PUNCT
brj-23786	240	36	y.	y.	PROPN
brj-23786	240	37	,	,	PUNCT
brj-23786	240	38	huang	huang	PROPN
brj-23786	240	39	,	,	PUNCT
brj-23786	240	40	b.	b.	PROPN
brj-23786	240	41	,	,	PUNCT
brj-23786	240	42	li	li	PROPN
brj-23786	240	43	,	,	PUNCT
brj-23786	240	44	k.	k.	PROPN
brj-23786	240	45	,	,	PUNCT
brj-23786	240	46	du	du	PROPN
brj-23786	240	47	,	,	PUNCT
brj-23786	240	48	w.	w.	PROPN
brj-23786	240	49	,	,	PUNCT
brj-23786	240	50	lu	lu	PROPN
brj-23786	240	51	,	,	PUNCT
brj-23786	240	52	k.	k.	PROPN
brj-23786	240	53	,	,	PUNCT
brj-23786	240	54	and	and	CCONJ
brj-23786	240	55	zhang	zhang	PROPN
brj-23786	240	56	,	,	PUNCT
brj-23786	240	57	y.	y.	PROPN
brj-23786	240	58	(	(	PUNCT
brj-23786	240	59	2020	2020	NUM
brj-23786	240	60	)	)	PUNCT
brj-23786	240	61	.	.	PUNCT
brj-23786	241	1	“	"	PUNCT
brj-23786	241	2	thermal	thermal	ADJ
brj-23786	241	3	interaction	interaction	NOUN
brj-23786	241	4	analysis	analysis	NOUN
brj-23786	241	5	of	of	ADP
brj-23786	241	6	isolated	isolated	ADJ
brj-23786	241	7	hemicellulose	hemicellulose	NOUN
brj-23786	241	8	and	and	CCONJ
brj-23786	241	9	cellulose	cellulose	NOUN
brj-23786	241	10	by	by	ADP
brj-23786	241	11	kinetic	kinetic	ADJ
brj-23786	241	12	parameters	parameter	NOUN
brj-23786	241	13	during	during	ADP
brj-23786	241	14	biomass	biomass	NOUN
brj-23786	241	15	pyrolysis	pyrolysis	NOUN
brj-23786	241	16	,	,	PUNCT
brj-23786	241	17	”	"	PUNCT
brj-23786	241	18	energy	energy	NOUN
brj-23786	241	19	195	195	NUM
brj-23786	241	20	,	,	PUNCT
brj-23786	241	21	article	article	NOUN
brj-23786	241	22	117010	117010	NUM
brj-23786	241	23	.	.	PUNCT
brj-23786	242	1	doi	doi	NOUN
brj-23786	242	2	:	:	PUNCT
brj-23786	242	3	10.1016	10.1016	NUM
brj-23786	242	4	/	/	SYM
brj-23786	242	5	j.energy.2020.117010	j.energy.2020.117010	NOUN
brj-23786	242	6	ding	ding	NOUN
brj-23786	242	7	,	,	PUNCT
brj-23786	242	8	y.	y.	PROPN
brj-23786	242	9	,	,	PUNCT
brj-23786	242	10	jiang	jiang	PROPN
brj-23786	242	11	,	,	PUNCT
brj-23786	242	12	g.	g.	PROPN
brj-23786	242	13	,	,	PUNCT
brj-23786	242	14	fukumoto	fukumoto	NOUN
brj-23786	242	15	,	,	PUNCT
brj-23786	242	16	k.	k.	PROPN
brj-23786	242	17	,	,	PUNCT
brj-23786	242	18	zhao	zhao	PROPN
brj-23786	242	19	,	,	PUNCT
brj-23786	242	20	m.	m.	NOUN
brj-23786	242	21	,	,	PUNCT
brj-23786	242	22	zhang	zhang	PROPN
brj-23786	242	23	,	,	PUNCT
brj-23786	242	24	x.	x.	PROPN
brj-23786	242	25	,	,	PUNCT
brj-23786	242	26	wang	wang	PROPN
brj-23786	242	27	,	,	PUNCT
brj-23786	242	28	c.	c.	PROPN
brj-23786	242	29	,	,	PUNCT
brj-23786	242	30	and	and	CCONJ
brj-23786	242	31	li	li	PROPN
brj-23786	242	32	,	,	PUNCT
brj-23786	242	33	c.	c.	PROPN
brj-23786	242	34	(	(	PUNCT
brj-23786	242	35	2023	2023	NUM
brj-23786	242	36	)	)	PUNCT
brj-23786	242	37	.	.	PUNCT
brj-23786	243	1	“	"	PUNCT
brj-23786	243	2	experimental	experimental	ADJ
brj-23786	243	3	and	and	CCONJ
brj-23786	243	4	numerical	numerical	PROPN
brj-23786	243	5	simulation	simulation	NOUN
brj-23786	243	6	of	of	ADP
brj-23786	243	7	multi	multi	ADJ
brj-23786	243	8	-	-	ADJ
brj-23786	243	9	component	component	ADJ
brj-23786	243	10	combustion	combustion	NOUN
brj-23786	243	11	of	of	ADP
brj-23786	243	12	typical	typical	ADJ
brj-23786	243	13	no	no	PRON
brj-23786	243	14	-	-	PUNCT
brj-23786	243	15	charring	char	VERB
brj-23786	243	16	material	material	NOUN
brj-23786	243	17	,	,	PUNCT
brj-23786	243	18	”	"	PUNCT
brj-23786	243	19	energy	energy	NOUN
brj-23786	243	20	262	262	NUM
brj-23786	243	21	(	(	PUNCT
brj-23786	243	22	pb	pb	PROPN
brj-23786	243	23	)	)	PUNCT
brj-23786	243	24	,	,	PUNCT
brj-23786	243	25	article	article	NOUN
brj-23786	243	26	125555	125555	NUM
brj-23786	243	27	.	.	PUNCT
brj-23786	244	1	doi	doi	NOUN
brj-23786	244	2	:	:	PUNCT
brj-23786	244	3	10.1016	10.1016	NUM
brj-23786	244	4	/	/	SYM
brj-23786	244	5	j.energy.2022.125555	j.energy.2022.125555	PROPN
brj-23786	244	6	dubdub	dubdub	PROPN
brj-23786	244	7	,	,	PUNCT
brj-23786	244	8	i.	i.	PROPN
brj-23786	244	9	,	,	PUNCT
brj-23786	244	10	and	and	CCONJ
brj-23786	244	11	al	al	PROPN
brj-23786	244	12	-	-	PUNCT
brj-23786	244	13	yaari	yaari	PROPN
brj-23786	244	14	,	,	PUNCT
brj-23786	244	15	m.	m.	NOUN
brj-23786	244	16	(	(	PUNCT
brj-23786	244	17	2020	2020	NUM
brj-23786	244	18	)	)	PUNCT
brj-23786	244	19	.	.	PUNCT
brj-23786	245	1	“	"	PUNCT
brj-23786	245	2	pyrolysis	pyrolysis	NOUN
brj-23786	245	3	of	of	ADP
brj-23786	245	4	low	low	ADJ
brj-23786	245	5	density	density	NOUN
brj-23786	245	6	polyethylene	polyethylene	NOUN
brj-23786	245	7	:	:	PUNCT
brj-23786	245	8	kinetic	kinetic	ADJ
brj-23786	245	9	study	study	NOUN
brj-23786	245	10	using	use	VERB
brj-23786	245	11	tga	tga	PROPN
brj-23786	245	12	data	datum	NOUN
brj-23786	245	13	and	and	CCONJ
brj-23786	245	14	ann	ann	PROPN
brj-23786	245	15	prediction	prediction	NOUN
brj-23786	245	16	,	,	PUNCT
brj-23786	245	17	”	"	PUNCT
brj-23786	245	18	polymers	polymer	NOUN
brj-23786	245	19	12(4	12(4	NUM
brj-23786	245	20	)	)	PUNCT
brj-23786	245	21	,	,	PUNCT
brj-23786	245	22	891	891	NUM
brj-23786	245	23	-	-	SYM
brj-23786	245	24	891	891	NUM
brj-23786	245	25	.	.	PUNCT
brj-23786	246	1	doi	doi	NOUN
brj-23786	246	2	:	:	PUNCT
brj-23786	246	3	10.3390	10.3390	NUM
brj-23786	246	4	/	/	SYM
brj-23786	246	5	polym12040891	polym12040891	ADJ
brj-23786	246	6	dubdub	dubdub	NOUN
brj-23786	246	7	,	,	PUNCT
brj-23786	246	8	i.	i.	NOUN
brj-23786	246	9	,	,	PUNCT
brj-23786	246	10	and	and	CCONJ
brj-23786	246	11	alyaari	alyaari	PROPN
brj-23786	246	12	,	,	PUNCT
brj-23786	246	13	m.	m.	NOUN
brj-23786	246	14	(	(	PUNCT
brj-23786	246	15	2021	2021	NUM
brj-23786	246	16	)	)	PUNCT
brj-23786	246	17	.	.	PUNCT
brj-23786	247	1	“	"	PUNCT
brj-23786	247	2	pyrolysis	pyrolysis	NOUN
brj-23786	247	3	of	of	ADP
brj-23786	247	4	mixed	mixed	ADJ
brj-23786	247	5	plastic	plastic	ADJ
brj-23786	247	6	waste	waste	NOUN
brj-23786	247	7	:	:	PUNCT
brj-23786	247	8	ii	ii	PROPN
brj-23786	247	9	.	.	PUNCT
brj-23786	247	10	artificial	artificial	ADJ
brj-23786	247	11	neural	neural	ADJ
brj-23786	247	12	networks	network	NOUN
brj-23786	247	13	prediction	prediction	NOUN
brj-23786	247	14	and	and	CCONJ
brj-23786	247	15	sensitivity	sensitivity	NOUN
brj-23786	247	16	analysis	analysis	NOUN
brj-23786	247	17	,	,	PUNCT
brj-23786	247	18	”	"	PUNCT
brj-23786	247	19	applied	apply	VERB
brj-23786	247	20	sciences	science	NOUN
brj-23786	247	21	11(18	11(18	NUM
brj-23786	247	22	)	)	PUNCT
brj-23786	247	23	,	,	PUNCT
brj-23786	247	24	8456	8456	NUM
brj-23786	247	25	.	.	PUNCT
brj-23786	248	1	doi	doi	NOUN
brj-23786	248	2	:	:	PUNCT
brj-23786	248	3	10.3390	10.3390	NUM
brj-23786	248	4	/	/	SYM
brj-23786	248	5	app11188456	app11188456	NOUN
brj-23786	248	6	gbolahan	gbolahan	NOUN
brj-23786	248	7	,	,	PUNCT
brj-23786	248	8	i.	i.	NOUN
brj-23786	248	9	,	,	PUNCT
brj-23786	248	10	pobitra	pobitra	PROPN
brj-23786	248	11	,	,	PUNCT
brj-23786	248	12	h.	h.	PROPN
brj-23786	248	13	,	,	PUNCT
brj-23786	248	14	chinyere	chinyere	INTJ
brj-23786	248	15	,	,	PUNCT
brj-23786	248	16	c.	c.	PROPN
brj-23786	248	17	,	,	PUNCT
brj-23786	248	18	ken	ken	PROPN
brj-23786	248	19	,	,	PUNCT
brj-23786	248	20	c.	c.	PROPN
brj-23786	248	21	,	,	PUNCT
brj-23786	248	22	abhishek	abhishek	PROPN
brj-23786	248	23	,	,	PUNCT
brj-23786	248	24	s.	s.	PROPN
brj-23786	248	25	,	,	PUNCT
brj-23786	248	26	jorge	jorge	VERB
brj-23786	248	27	,	,	PUNCT
brj-23786	248	28	p.	p.	NOUN
brj-23786	248	29	,	,	PUNCT
brj-23786	248	30	and	and	CCONJ
brj-23786	248	31	kalpit	kalpit	PROPN
brj-23786	248	32	,	,	PUNCT
brj-23786	248	33	s.	s.	PROPN
brj-23786	248	34	(	(	PUNCT
brj-23786	248	35	2022	2022	NUM
brj-23786	248	36	)	)	PUNCT
brj-23786	248	37	.	.	PUNCT
brj-23786	249	1	“	"	PUNCT
brj-23786	249	2	advances	advance	NOUN
brj-23786	249	3	in	in	ADP
brj-23786	249	4	biosolids	biosolid	NOUN
brj-23786	249	5	pyrolysis	pyrolysis	NOUN
brj-23786	249	6	:	:	PUNCT
brj-23786	249	7	roles	role	NOUN
brj-23786	249	8	of	of	ADP
brj-23786	249	9	pre	pre	NOUN
brj-23786	249	10	-	-	NOUN
brj-23786	249	11	treatments	treatment	NOUN
brj-23786	249	12	,	,	PUNCT
brj-23786	249	13	catalysts	catalyst	NOUN
brj-23786	249	14	,	,	PUNCT
brj-23786	249	15	and	and	CCONJ
brj-23786	249	16	cofeeding	cofeede	VERB
brj-23786	249	17	on	on	ADP
brj-23786	249	18	products	product	NOUN
brj-23786	249	19	distribution	distribution	NOUN
brj-23786	249	20	and	and	CCONJ
brj-23786	249	21	high	high	ADJ
brj-23786	249	22	-	-	PUNCT
brj-23786	249	23	value	value	NOUN
brj-23786	249	24	chemical	chemical	NOUN
brj-23786	249	25	production	production	NOUN
brj-23786	249	26	,	,	PUNCT
brj-23786	249	27	”	"	PUNCT
brj-23786	249	28	journal	journal	NOUN
brj-23786	249	29	of	of	ADP
brj-23786	249	30	analytical	analytical	ADJ
brj-23786	249	31	and	and	CCONJ
brj-23786	249	32	applied	applied	ADJ
brj-23786	249	33	pyrolysis	pyrolysis	NOUN
brj-23786	249	34	166	166	NUM
brj-23786	249	35	,	,	PUNCT
brj-23786	249	36	article	article	NOUN
brj-23786	249	37	105608	105608	NUM
brj-23786	249	38	.	.	PUNCT
brj-23786	250	1	doi	doi	NOUN
brj-23786	250	2	:	:	PUNCT
brj-23786	250	3	10.1016	10.1016	NUM
brj-23786	250	4	/	/	SYM
brj-23786	250	5	j.jaap.2022.105608	j.jaap.2022.105608	PROPN
brj-23786	250	6	guo	guo	PROPN
brj-23786	250	7	,	,	PUNCT
brj-23786	250	8	x.	x.	PROPN
brj-23786	250	9	,	,	PUNCT
brj-23786	250	10	qin	qin	PROPN
brj-23786	250	11	,	,	PUNCT
brj-23786	250	12	x.	x.	PROPN
brj-23786	250	13	,	,	PUNCT
brj-23786	250	14	zhang	zhang	PROPN
brj-23786	250	15	,	,	PUNCT
brj-23786	250	16	qing	qe	VERB
brj-23786	250	17	.	.	PROPN
brj-23786	250	18	,	,	PUNCT
brj-23786	250	19	zhang	zhang	PROPN
brj-23786	250	20	,	,	PUNCT
brj-23786	250	21	y.	y.	PROPN
brj-23786	250	22	,	,	PUNCT
brj-23786	250	23	wang	wang	PROPN
brj-23786	250	24	,	,	PUNCT
brj-23786	250	25	p.	p.	PROPN
brj-23786	250	26	,	,	PUNCT
brj-23786	250	27	and	and	CCONJ
brj-23786	250	28	fan	fan	PROPN
brj-23786	250	29	,	,	PUNCT
brj-23786	250	30	z.	z.	PROPN
brj-23786	250	31	(	(	PUNCT
brj-23786	250	32	2023	2023	NUM
brj-23786	250	33	)	)	PUNCT
brj-23786	250	34	.	.	PUNCT
brj-23786	251	1	“	"	PUNCT
brj-23786	251	2	speaker	speaker	NOUN
brj-23786	251	3	peer	peer	NOUN
brj-23786	251	4	-	-	PUNCT
brj-23786	251	5	reviewed	review	VERB
brj-23786	251	6	article	article	NOUN
brj-23786	251	7	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	251	8	xu	xu	PROPN
brj-23786	251	9	et	et	PROPN
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brj-23786	251	11	.	.	PROPN
brj-23786	252	1	(	(	PUNCT
brj-23786	252	2	2024	2024	NUM
brj-23786	252	3	)	)	PUNCT
brj-23786	252	4	.	.	PUNCT
brj-23786	253	1	“	"	PUNCT
brj-23786	253	2	pyrolysis	pyrolysis	NOUN
brj-23786	253	3	kinetics	kinetic	NOUN
brj-23786	253	4	with	with	ADP
brj-23786	253	5	ann	ann	PROPN
brj-23786	253	6	,	,	PUNCT
brj-23786	253	7	”	"	PUNCT
brj-23786	253	8	bioresources	bioresource	NOUN
brj-23786	253	9	19(4	19(4	NUM
brj-23786	253	10	)	)	PUNCT
brj-23786	253	11	,	,	PUNCT
brj-23786	253	12	7513	7513	NUM
brj-23786	253	13	-	-	SYM
brj-23786	253	14	7529	7529	NUM
brj-23786	253	15	.	.	PUNCT
brj-23786	254	1	7527	7527	NUM
brj-23786	254	2	recognition	recognition	NOUN
brj-23786	254	3	based	base	VERB
brj-23786	254	4	on	on	ADP
brj-23786	254	5	dung	dung	NOUN
brj-23786	254	6	beetle	beetle	NOUN
brj-23786	254	7	optimized	optimize	VERB
brj-23786	254	8	cnn	cnn	PROPN
brj-23786	254	9	,	,	PUNCT
brj-23786	254	10	”	"	PUNCT
brj-23786	254	11	applied	apply	VERB
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brj-23786	254	13	13(17	13(17	NUM
brj-23786	254	14	)	)	PUNCT
brj-23786	254	15	,	,	PUNCT
brj-23786	254	16	article	article	NOUN
brj-23786	254	17	9787	9787	NUM
brj-23786	254	18	.	.	PUNCT
brj-23786	255	1	doi	doi	NOUN
brj-23786	255	2	:	:	PUNCT
brj-23786	255	3	10.3390	10.3390	NUM
brj-23786	255	4	/	/	SYM
brj-23786	255	5	app13179787	app13179787	ADJ
brj-23786	255	6	huang	huang	PROPN
brj-23786	255	7	,	,	PUNCT
brj-23786	255	8	r.	r.	PROPN
brj-23786	255	9	,	,	PUNCT
brj-23786	255	10	huang	huang	PROPN
brj-23786	255	11	,	,	PUNCT
brj-23786	255	12	z.	z.	PROPN
brj-23786	255	13	,	,	PUNCT
brj-23786	255	14	ran	run	VERB
brj-23786	255	15	,	,	PUNCT
brj-23786	255	16	y.	y.	PROPN
brj-23786	255	17	,	,	PUNCT
brj-23786	255	18	xiong	xiong	PROPN
brj-23786	255	19	,	,	PUNCT
brj-23786	255	20	x.	x.	PROPN
brj-23786	255	21	,	,	PUNCT
brj-23786	255	22	luo	luo	PROPN
brj-23786	255	23	,	,	PUNCT
brj-23786	255	24	t.	t.	PROPN
brj-23786	255	25	,	,	PUNCT
brj-23786	255	26	long	long	ADV
brj-23786	255	27	,	,	PUNCT
brj-23786	255	28	e.	e.	PROPN
brj-23786	255	29	,	,	PUNCT
brj-23786	255	30	mei	mei	PROPN
brj-23786	255	31	,	,	PUNCT
brj-23786	255	32	z.	z.	PROPN
brj-23786	255	33	,	,	PUNCT
brj-23786	255	34	and	and	CCONJ
brj-23786	255	35	wang	wang	PROPN
brj-23786	255	36	,	,	PUNCT
brj-23786	255	37	j.	j.	PROPN
brj-23786	255	38	(	(	PUNCT
brj-23786	255	39	2021	2021	NUM
brj-23786	255	40	)	)	PUNCT
brj-23786	255	41	.	.	PUNCT
brj-23786	256	1	“	"	PUNCT
brj-23786	256	2	experimental	experimental	ADJ
brj-23786	256	3	and	and	CCONJ
brj-23786	256	4	simulation	simulation	NOUN
brj-23786	256	5	study	study	NOUN
brj-23786	256	6	on	on	ADP
brj-23786	256	7	the	the	DET
brj-23786	256	8	surface	surface	NOUN
brj-23786	256	9	contact	contact	NOUN
brj-23786	256	10	between	between	ADP
brj-23786	256	11	biogas	biogas	NOUN
brj-23786	256	12	fermentation	fermentation	NOUN
brj-23786	256	13	liquid	liquid	NOUN
brj-23786	256	14	and	and	CCONJ
brj-23786	256	15	straw	straw	NOUN
brj-23786	256	16	material	material	NOUN
brj-23786	256	17	based	base	VERB
brj-23786	256	18	on	on	ADP
brj-23786	256	19	hydraulic	hydraulic	ADJ
brj-23786	256	20	mixing	mixing	NOUN
brj-23786	256	21	,	,	PUNCT
brj-23786	256	22	”	"	PUNCT
brj-23786	256	23	energy	energy	NOUN
brj-23786	256	24	222	222	NUM
brj-23786	256	25	,	,	PUNCT
brj-23786	256	26	article	article	NOUN
brj-23786	256	27	111992	111992	NUM
brj-23786	256	28	.	.	PUNCT
brj-23786	257	1	doi	doi	NOUN
brj-23786	257	2	:	:	PUNCT
brj-23786	257	3	10.1016	10.1016	NUM
brj-23786	257	4	/	/	SYM
brj-23786	257	5	j.energy.2021.119992	j.energy.2021.119992	PROPN
brj-23786	257	6	hu	hu	PROPN
brj-23786	257	7	,	,	PUNCT
brj-23786	257	8	z.	z.	PROPN
brj-23786	257	9	,	,	PUNCT
brj-23786	257	10	yuan	yuan	PROPN
brj-23786	257	11	,	,	PUNCT
brj-23786	257	12	y.	y.	PROPN
brj-23786	257	13	,	,	PUNCT
brj-23786	257	14	li	li	PROPN
brj-23786	257	15	,	,	PUNCT
brj-23786	257	16	x.	x.	PROPN
brj-23786	257	17	,	,	PUNCT
brj-23786	257	18	tu	tu	PROPN
brj-23786	257	19	,	,	PUNCT
brj-23786	257	20	z.	z.	PROPN
brj-23786	257	21	,	,	PUNCT
brj-23786	257	22	dacres	dacre	VERB
brj-23786	257	23	,	,	PUNCT
brj-23786	257	24	o.	o.	PROPN
brj-23786	257	25	,	,	PUNCT
brj-23786	257	26	zhu	zhu	PROPN
brj-23786	257	27	,	,	PUNCT
brj-23786	257	28	y.	y.	PROPN
brj-23786	257	29	,	,	PUNCT
brj-23786	257	30	shi	shi	PROPN
brj-23786	257	31	,	,	PUNCT
brj-23786	257	32	l.	l.	PROPN
brj-23786	257	33	,	,	PUNCT
brj-23786	257	34	hu	hu	PROPN
brj-23786	257	35	,	,	PUNCT
brj-23786	257	36	h.	h.	PROPN
brj-23786	257	37	,	,	PUNCT
brj-23786	257	38	liu	liu	PROPN
brj-23786	257	39	,	,	PUNCT
brj-23786	257	40	h.	h.	PROPN
brj-23786	257	41	,	,	PUNCT
brj-23786	257	42	luo	luo	PROPN
brj-23786	257	43	,	,	PUNCT
brj-23786	257	44	g.	g.	PROPN
brj-23786	257	45	,	,	PUNCT
brj-23786	257	46	and	and	CCONJ
brj-23786	257	47	yao	yao	PROPN
brj-23786	257	48	,	,	PUNCT
brj-23786	257	49	h.	h.	PROPN
brj-23786	257	50	(	(	PUNCT
brj-23786	257	51	2022	2022	NUM
brj-23786	257	52	)	)	PUNCT
brj-23786	257	53	.	.	PUNCT
brj-23786	258	1	“	"	PUNCT
brj-23786	258	2	yield	yield	VERB
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brj-23786	258	4	of	of	ADP
brj-23786	258	5	‘	'	PUNCT
brj-23786	258	6	thermal	thermal	ADJ
brj-23786	258	7	-	-	PUNCT
brj-23786	258	8	dissolution	dissolution	NOUN
brj-23786	258	9	based	base	VERB
brj-23786	258	10	carbon	carbon	NOUN
brj-23786	258	11	enrichment	enrichment	NOUN
brj-23786	258	12	’	'	PUNCT
brj-23786	258	13	treatment	treatment	NOUN
brj-23786	258	14	on	on	ADP
brj-23786	258	15	biomass	biomass	NOUN
brj-23786	258	16	wastes	waste	NOUN
brj-23786	258	17	through	through	ADP
brj-23786	258	18	coupled	couple	VERB
brj-23786	258	19	model	model	NOUN
brj-23786	258	20	of	of	ADP
brj-23786	258	21	artificial	artificial	ADJ
brj-23786	258	22	neural	neural	ADJ
brj-23786	258	23	network	network	NOUN
brj-23786	258	24	and	and	CCONJ
brj-23786	258	25	adaboost	adaboost	ADV
brj-23786	258	26	,	,	PUNCT
brj-23786	258	27	”	"	PUNCT
brj-23786	258	28	bioresource	bioresource	ADJ
brj-23786	258	29	technology	technology	NOUN
brj-23786	258	30	343	343	NUM
brj-23786	258	31	,	,	PUNCT
brj-23786	258	32	article	article	NOUN
brj-23786	258	33	126083	126083	NUM
brj-23786	258	34	.	.	PUNCT
brj-23786	259	1	doi	doi	NOUN
brj-23786	259	2	:	:	PUNCT
brj-23786	259	3	10.1016	10.1016	NUM
brj-23786	259	4	/	/	SYM
brj-23786	259	5	j.biortech.2021.126083	j.biortech.2021.126083	PROPN
brj-23786	259	6	kersten	kersten	PROPN
brj-23786	259	7	,	,	PUNCT
brj-23786	259	8	s.	s.	PROPN
brj-23786	259	9	,	,	PUNCT
brj-23786	259	10	wang	wang	PROPN
brj-23786	259	11	,	,	PUNCT
brj-23786	259	12	x.	x.	PROPN
brj-23786	259	13	,	,	PUNCT
brj-23786	259	14	prins	prins	PROPN
brj-23786	259	15	,	,	PUNCT
brj-23786	259	16	w.	w.	NOUN
brj-23786	259	17	,	,	PUNCT
brj-23786	259	18	and	and	CCONJ
brj-23786	259	19	van	van	PROPN
brj-23786	259	20	,	,	PUNCT
brj-23786	259	21	swaaij	swaaij	NOUN
brj-23786	259	22	,	,	PUNCT
brj-23786	259	23	w.	w.	PROPN
brj-23786	259	24	p.	p.	PROPN
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brj-23786	259	26	(	(	PUNCT
brj-23786	259	27	2005	2005	NUM
brj-23786	259	28	)	)	PUNCT
brj-23786	259	29	.	.	PUNCT
brj-23786	260	1	“	"	PUNCT
brj-23786	260	2	biomass	biomass	NOUN
brj-23786	260	3	pyrolysis	pyrolysis	NOUN
brj-23786	260	4	in	in	ADP
brj-23786	260	5	a	a	DET
brj-23786	260	6	fluidized	fluidize	VERB
brj-23786	260	7	bed	bed	NOUN
brj-23786	260	8	reactor	reactor	NOUN
brj-23786	260	9	.	.	PUNCT
brj-23786	261	1	part	part	NOUN
brj-23786	261	2	1	1	NUM
brj-23786	261	3	:	:	PUNCT
brj-23786	261	4	  	  	SPACE
brj-23786	261	5	literature	literature	NOUN
brj-23786	261	6	review	review	NOUN
brj-23786	261	7	and	and	CCONJ
brj-23786	261	8	model	model	NOUN
brj-23786	261	9	simulations	simulation	NOUN
brj-23786	261	10	,	,	PUNCT
brj-23786	261	11	”	"	PUNCT
brj-23786	261	12	industrial	industrial	PROPN
brj-23786	261	13	&	&	CCONJ
brj-23786	261	14	engineering	engineering	NOUN
brj-23786	261	15	chemistry	chemistry	NOUN
brj-23786	261	16	research	research	NOUN
brj-23786	261	17	23	23	NUM
brj-23786	261	18	,	,	PUNCT
brj-23786	261	19	8773	8773	NUM
brj-23786	261	20	-	-	SYM
brj-23786	261	21	8785	8785	NUM
brj-23786	261	22	.	.	PUNCT
brj-23786	262	1	doi	doi	NOUN
brj-23786	262	2	:	:	PUNCT
brj-23786	262	3	10.1021	10.1021	NUM
brj-23786	262	4	/	/	SYM
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brj-23786	262	7	,	,	PUNCT
brj-23786	262	8	l.	l.	PROPN
brj-23786	262	9	,	,	PUNCT
brj-23786	262	10	adetoyese	adetoyese	NOUN
brj-23786	262	11	,	,	PUNCT
brj-23786	262	12	o.	o.	NOUN
brj-23786	262	13	,	,	PUNCT
brj-23786	262	14	and	and	CCONJ
brj-23786	262	15	chi	chi	PROPN
brj-23786	262	16	,	,	PUNCT
brj-23786	262	17	w.	w.	PROPN
brj-23786	262	18	(	(	PUNCT
brj-23786	262	19	2012	2012	NUM
brj-23786	262	20	)	)	PUNCT
brj-23786	262	21	.	.	PUNCT
brj-23786	263	1	“	"	PUNCT
brj-23786	263	2	experimental	experimental	ADJ
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brj-23786	263	6	of	of	ADP
brj-23786	263	7	biomass	biomass	NOUN
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brj-23786	263	9	,	,	PUNCT
brj-23786	263	10	”	"	PUNCT
brj-23786	263	11	chinese	chinese	ADJ
brj-23786	263	12	journal	journal	NOUN
brj-23786	263	13	of	of	ADP
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brj-23786	263	15	engineering	engineering	PROPN
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brj-23786	263	17	,	,	PUNCT
brj-23786	263	18	543	543	NUM
brj-23786	263	19	-	-	SYM
brj-23786	263	20	550	550	NUM
brj-23786	263	21	.	.	PUNCT
brj-23786	264	1	doi	doi	NOUN
brj-23786	264	2	:	:	PUNCT
brj-23786	264	3	10.1016	10.1016	NUM
brj-23786	264	4	/	/	SYM
brj-23786	264	5	s1004	s1004	PROPN
brj-23786	264	6	-	-	PUNCT
brj-23786	264	7	9541(11)60217	9541(11)60217	NUM
brj-23786	264	8	-	-	PUNCT
brj-23786	264	9	6	6	NUM
brj-23786	264	10	kaczor	kaczor	PROPN
brj-23786	264	11	,	,	PUNCT
brj-23786	264	12	z.	z.	PROPN
brj-23786	264	13	,	,	PUNCT
brj-23786	264	14	buliński	buliński	PROPN
brj-23786	264	15	,	,	PUNCT
brj-23786	264	16	z.	z.	PROPN
brj-23786	264	17	,	,	PUNCT
brj-23786	264	18	and	and	CCONJ
brj-23786	264	19	werle	werle	PROPN
brj-23786	264	20	,	,	PUNCT
brj-23786	264	21	s.	s.	PROPN
brj-23786	264	22	(	(	PUNCT
brj-23786	264	23	2020	2020	NUM
brj-23786	264	24	)	)	PUNCT
brj-23786	264	25	.	.	PUNCT
brj-23786	265	1	“	"	PUNCT
brj-23786	265	2	modelling	model	VERB
brj-23786	265	3	approaches	approach	NOUN
brj-23786	265	4	to	to	PART
brj-23786	265	5	waste	waste	VERB
brj-23786	265	6	biomass	biomass	NOUN
brj-23786	265	7	pyrolysis	pyrolysis	NOUN
brj-23786	265	8	:	:	PUNCT
brj-23786	265	9	a	a	DET
brj-23786	265	10	review	review	NOUN
brj-23786	265	11	,	,	PUNCT
brj-23786	265	12	”	"	PUNCT
brj-23786	265	13	renewable	renewable	ADJ
brj-23786	265	14	energy	energy	NOUN
brj-23786	265	15	159	159	NUM
brj-23786	265	16	,	,	PUNCT
brj-23786	265	17	427	427	NUM
brj-23786	265	18	-	-	SYM
brj-23786	265	19	443	443	NUM
brj-23786	265	20	.	.	PUNCT
brj-23786	266	1	doi	doi	NOUN
brj-23786	266	2	:	:	PUNCT
brj-23786	266	3	10.1016	10.1016	NUM
brj-23786	266	4	/	/	SYM
brj-23786	266	5	j.renene.2020.05.110	j.renene.2020.05.110	PROPN
brj-23786	266	6	ke	ke	PROPN
brj-23786	266	7	,	,	PUNCT
brj-23786	266	8	l.	l.	PROPN
brj-23786	266	9	,	,	PUNCT
brj-23786	266	10	wu	wu	PROPN
brj-23786	266	11	,	,	PUNCT
brj-23786	266	12	q.	q.	PROPN
brj-23786	266	13	,	,	PUNCT
brj-23786	266	14	zhou	zhou	PROPN
brj-23786	266	15	,	,	PUNCT
brj-23786	266	16	n.	n.	PROPN
brj-23786	266	17	,	,	PUNCT
brj-23786	266	18	xiong	xiong	PROPN
brj-23786	266	19	,	,	PUNCT
brj-23786	266	20	j.	j.	PROPN
brj-23786	266	21	,	,	PUNCT
brj-23786	266	22	yang	yang	PROPN
brj-23786	266	23	,	,	PUNCT
brj-23786	266	24	q.	q.	PROPN
brj-23786	266	25	,	,	PUNCT
brj-23786	266	26	zhang	zhang	PROPN
brj-23786	266	27	,	,	PUNCT
brj-23786	266	28	l.	l.	PROPN
brj-23786	266	29	,	,	PUNCT
brj-23786	266	30	wang	wang	PROPN
brj-23786	266	31	,	,	PUNCT
brj-23786	266	32	y.	y.	PROPN
brj-23786	266	33	,	,	PUNCT
brj-23786	266	34	dai	dai	PROPN
brj-23786	266	35	,	,	PUNCT
brj-23786	266	36	l.	l.	PROPN
brj-23786	266	37	,	,	PUNCT
brj-23786	266	38	zou	zou	PROPN
brj-23786	266	39	,	,	PUNCT
brj-23786	266	40	r.	r.	PROPN
brj-23786	266	41	,	,	PUNCT
brj-23786	266	42	liu	liu	PROPN
brj-23786	266	43	,	,	PUNCT
brj-23786	266	44	y.	y.	PROPN
brj-23786	266	45	,	,	PUNCT
brj-23786	266	46	ruan	ruan	PROPN
brj-23786	266	47	,	,	PUNCT
brj-23786	266	48	r.	r.	PROPN
brj-23786	266	49	,	,	PUNCT
brj-23786	266	50	and	and	CCONJ
brj-23786	266	51	wang	wang	PROPN
brj-23786	266	52	,	,	PUNCT
brj-23786	266	53	y.	y.	PROPN
brj-23786	266	54	(	(	PUNCT
brj-23786	266	55	2022	2022	NUM
brj-23786	266	56	)	)	PUNCT
brj-23786	266	57	.	.	PUNCT
brj-23786	267	1	“	"	PUNCT
brj-23786	267	2	lignocellulosic	lignocellulosic	ADJ
brj-23786	267	3	biomass	biomass	NOUN
brj-23786	267	4	pyrolysis	pyrolysis	NOUN
brj-23786	267	5	for	for	ADP
brj-23786	267	6	aromatic	aromatic	ADJ
brj-23786	267	7	hydrocarbons	hydrocarbon	NOUN
brj-23786	267	8	production	production	NOUN
brj-23786	267	9	:	:	PUNCT
brj-23786	267	10	pre	pre	ADJ
brj-23786	267	11	and	and	CCONJ
brj-23786	267	12	in	in	ADP
brj-23786	267	13	-	-	PUNCT
brj-23786	267	14	process	process	NOUN
brj-23786	267	15	enhancement	enhancement	NOUN
brj-23786	267	16	methods	method	NOUN
brj-23786	267	17	,	,	PUNCT
brj-23786	267	18	”	"	PUNCT
brj-23786	267	19	renewable	renewable	ADJ
brj-23786	267	20	and	and	CCONJ
brj-23786	267	21	sustainable	sustainable	ADJ
brj-23786	267	22	energy	energy	NOUN
brj-23786	267	23	reviews	review	NOUN
brj-23786	267	24	165	165	NUM
brj-23786	267	25	,	,	PUNCT
brj-23786	267	26	article	article	NOUN
brj-23786	267	27	112607	112607	NUM
brj-23786	267	28	.	.	PUNCT
brj-23786	268	1	doi	doi	NOUN
brj-23786	268	2	:	:	PUNCT
brj-23786	268	3	10.1016	10.1016	NUM
brj-23786	268	4	/	/	SYM
brj-23786	268	5	j.rser.2022.112607	j.rser.2022.112607	PROPN
brj-23786	268	6	liborio	liborio	PROPN
brj-23786	268	7	,	,	PUNCT
brj-23786	268	8	o.	o.	PROPN
brj-23786	268	9	,	,	PUNCT
brj-23786	268	10	arias	arias	PROPN
brj-23786	268	11	,	,	PUNCT
brj-23786	268	12	s.	s.	PROPN
brj-23786	268	13	,	,	PUNCT
brj-23786	268	14	mumbach	mumbach	INTJ
brj-23786	268	15	,	,	PUNCT
brj-23786	268	16	d.	d.	PROPN
brj-23786	268	17	,	,	PUNCT
brj-23786	268	18	alves	alves	PROPN
brj-23786	268	19	,	,	PUNCT
brj-23786	268	20	j.	j.	PROPN
brj-23786	268	21	,	,	PUNCT
brj-23786	268	22	silva	silva	PROPN
brj-23786	268	23	,	,	PUNCT
brj-23786	268	24	j.	j.	PROPN
brj-23786	268	25	,	,	PUNCT
brj-23786	268	26	and	and	CCONJ
brj-23786	268	27	pacheco	pacheco	PROPN
brj-23786	268	28	,	,	PUNCT
brj-23786	268	29	j.	j.	PROPN
brj-23786	268	30	(	(	PUNCT
brj-23786	268	31	2024	2024	NUM
brj-23786	268	32	)	)	PUNCT
brj-23786	268	33	.	.	PUNCT
brj-23786	269	1	“	"	PUNCT
brj-23786	269	2	evaluating	evaluate	VERB
brj-23786	269	3	black	black	ADJ
brj-23786	269	4	wattle	wattle	NOUN
brj-23786	269	5	bark	bark	NOUN
brj-23786	269	6	industrial	industrial	ADJ
brj-23786	269	7	residue	residue	NOUN
brj-23786	269	8	as	as	ADP
brj-23786	269	9	a	a	DET
brj-23786	269	10	new	new	ADJ
brj-23786	269	11	feedstock	feedstock	NOUN
brj-23786	269	12	for	for	ADP
brj-23786	269	13	bioenergy	bioenergy	NOUN
brj-23786	269	14	via	via	ADP
brj-23786	269	15	pyrolysis	pyrolysis	NOUN
brj-23786	269	16	and	and	CCONJ
brj-23786	269	17	multicomponent	multicomponent	NOUN
brj-23786	269	18	kinetic	kinetic	ADJ
brj-23786	269	19	modeling	modeling	NOUN
brj-23786	269	20	,	,	PUNCT
brj-23786	269	21	”	"	PUNCT
brj-23786	269	22	renewable	renewable	ADJ
brj-23786	269	23	energy	energy	NOUN
brj-23786	269	24	228	228	NUM
brj-23786	269	25	,	,	PUNCT
brj-23786	269	26	article	article	NOUN
brj-23786	269	27	120693	120693	NUM
brj-23786	269	28	.	.	PUNCT
brj-23786	270	1	doi	doi	NOUN
brj-23786	270	2	:	:	PUNCT
brj-23786	270	3	10.1016	10.1016	NUM
brj-23786	270	4	/	/	SYM
brj-23786	270	5	j.renene.2024.120693	j.renene.2024.120693	PROPN
brj-23786	270	6	machmudah	machmudah	PROPN
brj-23786	270	7	,	,	PUNCT
brj-23786	270	8	s.	s.	PROPN
brj-23786	270	9	,	,	PUNCT
brj-23786	270	10	wicaksono	wicaksono	PROPN
brj-23786	270	11	,	,	PUNCT
brj-23786	270	12	d.	d.	PROPN
brj-23786	270	13	,	,	PUNCT
brj-23786	270	14	happy	happy	ADJ
brj-23786	270	15	,	,	PUNCT
brj-23786	270	16	m.	m.	NOUN
brj-23786	270	17	,	,	PUNCT
brj-23786	270	18	winardi	winardi	NOUN
brj-23786	270	19	,	,	PUNCT
brj-23786	270	20	s.	s.	PROPN
brj-23786	270	21	wahyudiono	wahyudiono	PROPN
brj-23786	270	22	.	.	PROPN
brj-23786	270	23	,	,	PUNCT
brj-23786	270	24	kanda	kanda	PROPN
brj-23786	270	25	,	,	PUNCT
brj-23786	270	26	h.	h.	PROPN
brj-23786	270	27	,	,	PUNCT
brj-23786	270	28	and	and	CCONJ
brj-23786	270	29	goto	goto	NOUN
brj-23786	270	30	,	,	PUNCT
brj-23786	270	31	m.	m.	NOUN
brj-23786	270	32	(	(	PUNCT
brj-23786	270	33	2020	2020	NUM
brj-23786	270	34	)	)	PUNCT
brj-23786	270	35	.	.	PUNCT
brj-23786	271	1	“	"	PUNCT
brj-23786	271	2	water	water	NOUN
brj-23786	271	3	removal	removal	NOUN
brj-23786	271	4	from	from	ADP
brj-23786	271	5	wood	wood	NOUN
brj-23786	271	6	biomass	biomass	NOUN
brj-23786	271	7	by	by	ADP
brj-23786	271	8	liquefied	liquefy	VERB
brj-23786	271	9	dimethyl	dimethyl	NOUN
brj-23786	271	10	ether	ether	NOUN
brj-23786	271	11	for	for	ADP
brj-23786	271	12	enhancing	enhance	VERB
brj-23786	271	13	heating	heating	NOUN
brj-23786	271	14	value	value	NOUN
brj-23786	271	15	,	,	PUNCT
brj-23786	271	16	”	"	PUNCT
brj-23786	271	17	energy	energy	NOUN
brj-23786	271	18	reports	report	NOUN
brj-23786	271	19	6	6	NUM
brj-23786	271	20	,	,	PUNCT
brj-23786	271	21	824	824	NUM
brj-23786	271	22	-	-	SYM
brj-23786	271	23	831	831	NUM
brj-23786	271	24	.	.	PUNCT
brj-23786	272	1	doi	doi	NOUN
brj-23786	272	2	:	:	PUNCT
brj-23786	272	3	10.1016	10.1016	NUM
brj-23786	272	4	/	/	SYM
brj-23786	272	5	j.egyr.2020.04.006	j.egyr.2020.04.006	NOUN
brj-23786	272	6	marchese	marchese	PROPN
brj-23786	272	7	,	,	PUNCT
brj-23786	272	8	l.	l.	PROPN
brj-23786	272	9	,	,	PUNCT
brj-23786	272	10	kühl	kühl	PROPN
brj-23786	272	11	,	,	PUNCT
brj-23786	272	12	k.	k.	PROPN
brj-23786	272	13	,	,	PUNCT
brj-23786	272	14	silva	silva	PROPN
brj-23786	272	15	,	,	PUNCT
brj-23786	272	16	j.	j.	PROPN
brj-23786	272	17	,	,	PUNCT
brj-23786	272	18	mumbach	mumbach	INTJ
brj-23786	272	19	,	,	PUNCT
brj-23786	272	20	g.	g.	PROPN
brj-23786	272	21	,	,	PUNCT
brj-23786	272	22	alves	alves	PROPN
brj-23786	272	23	,	,	PUNCT
brj-23786	272	24	r.	r.	PROPN
brj-23786	272	25	,	,	PUNCT
brj-23786	272	26	alves	alves	PROPN
brj-23786	272	27	,	,	PUNCT
brj-23786	272	28	j.	j.	PROPN
brj-23786	272	29	,	,	PUNCT
brj-23786	272	30	and	and	CCONJ
brj-23786	272	31	domenico	domenico	PROPN
brj-23786	272	32	,	,	PUNCT
brj-23786	272	33	m.	m.	NOUN
brj-23786	272	34	(	(	PUNCT
brj-23786	272	35	2024	2024	NUM
brj-23786	272	36	)	)	PUNCT
brj-23786	272	37	.	.	PUNCT
brj-23786	273	1	“	"	PUNCT
brj-23786	273	2	exploring	explore	VERB
brj-23786	273	3	bioenergy	bioenergy	NOUN
brj-23786	273	4	prospects	prospect	NOUN
brj-23786	273	5	from	from	ADP
brj-23786	273	6	malt	malt	NOUN
brj-23786	273	7	bagasse	bagasse	NOUN
brj-23786	273	8	:	:	PUNCT
brj-23786	273	9	insights	insight	NOUN
brj-23786	273	10	through	through	ADP
brj-23786	273	11	pyrolysis	pyrolysis	NOUN
brj-23786	273	12	with	with	ADP
brj-23786	273	13	multi	multi	ADJ
brj-23786	273	14	-	-	ADJ
brj-23786	273	15	component	component	ADJ
brj-23786	273	16	kinetic	kinetic	ADJ
brj-23786	273	17	analysis	analysis	NOUN
brj-23786	273	18	and	and	CCONJ
brj-23786	273	19	thermodynamic	thermodynamic	ADJ
brj-23786	273	20	parameter	parameter	NOUN
brj-23786	273	21	estimation	estimation	NOUN
brj-23786	273	22	,	,	PUNCT
brj-23786	273	23	”	"	PUNCT
brj-23786	273	24	renewable	renewable	ADJ
brj-23786	273	25	energy	energy	NOUN
brj-23786	273	26	226	226	NUM
brj-23786	273	27	,	,	PUNCT
brj-23786	273	28	article	article	NOUN
brj-23786	273	29	120453	120453	NUM
brj-23786	273	30	.	.	PUNCT
brj-23786	274	1	doi	doi	NOUN
brj-23786	274	2	:	:	PUNCT
brj-23786	274	3	10.1016	10.1016	NUM
brj-23786	274	4	/	/	SYM
brj-23786	274	5	j.renene.2024.120453	j.renene.2024.120453	NOUN
brj-23786	274	6	martín	martín	NOUN
brj-23786	274	7	-	-	PUNCT
brj-23786	274	8	lara	lara	PROPN
brj-23786	274	9	,	,	PUNCT
brj-23786	274	10	m.	m.	NOUN
brj-23786	274	11	,	,	PUNCT
brj-23786	274	12	blázquez	blázquez	NOUN
brj-23786	274	13	,	,	PUNCT
brj-23786	274	14	g.	g.	PROPN
brj-23786	274	15	,	,	PUNCT
brj-23786	274	16	ronda	ronda	PROPN
brj-23786	274	17	,	,	PUNCT
brj-23786	274	18	a.	a.	NOUN
brj-23786	274	19	,	,	PUNCT
brj-23786	274	20	and	and	CCONJ
brj-23786	274	21	calero	calero	NOUN
brj-23786	274	22	,	,	PUNCT
brj-23786	274	23	m.	m.	NOUN
brj-23786	274	24	(	(	PUNCT
brj-23786	274	25	2016	2016	NUM
brj-23786	274	26	)	)	PUNCT
brj-23786	274	27	.	.	PUNCT
brj-23786	275	1	“	"	PUNCT
brj-23786	275	2	kinetic	kinetic	ADJ
brj-23786	275	3	study	study	NOUN
brj-23786	275	4	of	of	ADP
brj-23786	275	5	the	the	DET
brj-23786	275	6	pyrolysis	pyrolysis	NOUN
brj-23786	275	7	of	of	ADP
brj-23786	275	8	pinecone	pinecone	PROPN
brj-23786	275	9	shell	shell	NOUN
brj-23786	275	10	through	through	ADP
brj-23786	275	11	non	non	ADJ
brj-23786	275	12	-	-	ADJ
brj-23786	275	13	isothermal	isothermal	ADJ
brj-23786	275	14	thermogravimetry	thermogravimetry	NOUN
brj-23786	275	15	:	:	PUNCT
brj-23786	275	16	effect	effect	NOUN
brj-23786	275	17	of	of	ADP
brj-23786	275	18	heavy	heavy	ADJ
brj-23786	275	19	metals	metal	NOUN
brj-23786	275	20	incorporated	incorporate	VERB
brj-23786	275	21	by	by	ADP
brj-23786	275	22	biosorption	biosorption	NOUN
brj-23786	275	23	,	,	PUNCT
brj-23786	275	24	”	"	PUNCT
brj-23786	275	25	renewable	renewable	ADJ
brj-23786	275	26	energy	energy	NOUN
brj-23786	275	27	96	96	NUM
brj-23786	275	28	,	,	PUNCT
brj-23786	275	29	613	613	NUM
brj-23786	275	30	-	-	SYM
brj-23786	275	31	624	624	NUM
brj-23786	275	32	.	.	PUNCT
brj-23786	276	1	doi	doi	NOUN
brj-23786	276	2	:	:	PUNCT
brj-23786	276	3	10.1016	10.1016	NUM
brj-23786	276	4	/	/	SYM
brj-23786	276	5	j.renene.2016.05.026	j.renene.2016.05.026	PROPN
brj-23786	276	6	naqvi	naqvi	NOUN
brj-23786	276	7	,	,	PUNCT
brj-23786	276	8	r.	r.	PROPN
brj-23786	276	9	,	,	PUNCT
brj-23786	276	10	tariq	tariq	PROPN
brj-23786	276	11	,	,	PUNCT
brj-23786	276	12	r.	r.	PROPN
brj-23786	276	13	,	,	PUNCT
brj-23786	276	14	hameed	hameed	PROPN
brj-23786	276	15	,	,	PUNCT
brj-23786	276	16	z.	z.	PROPN
brj-23786	276	17	,	,	PUNCT
brj-23786	276	18	ali	ali	PROPN
brj-23786	276	19	,	,	PUNCT
brj-23786	276	20	i.	i.	PROPN
brj-23786	276	21	,	,	PUNCT
brj-23786	276	22	taqvi	taqvi	NOUN
brj-23786	276	23	,	,	PUNCT
brj-23786	276	24	s.	s.	PROPN
brj-23786	276	25	,	,	PUNCT
brj-23786	276	26	naqvi	naqvi	NOUN
brj-23786	276	27	,	,	PUNCT
brj-23786	276	28	m.	m.	NOUN
brj-23786	276	29	,	,	PUNCT
brj-23786	276	30	niazi	niazi	PROPN
brj-23786	276	31	,	,	PUNCT
brj-23786	276	32	m.	m.	NOUN
brj-23786	276	33	,	,	PUNCT
brj-23786	276	34	noor	noor	PROPN
brj-23786	276	35	,	,	PUNCT
brj-23786	276	36	t.	t.	PROPN
brj-23786	276	37	,	,	PUNCT
brj-23786	276	38	and	and	CCONJ
brj-23786	276	39	farooq	farooq	PROPN
brj-23786	276	40	,	,	PUNCT
brj-23786	276	41	w.	w.	PROPN
brj-23786	276	42	(	(	PUNCT
brj-23786	276	43	2018	2018	NUM
brj-23786	276	44	)	)	PUNCT
brj-23786	276	45	.	.	PUNCT
brj-23786	277	1	“	"	PUNCT
brj-23786	277	2	pyrolysis	pyrolysis	NOUN
brj-23786	277	3	of	of	ADP
brj-23786	277	4	high	high	ADJ
brj-23786	277	5	-	-	PUNCT
brj-23786	277	6	ash	ash	NOUN
brj-23786	277	7	sewage	sewage	NOUN
brj-23786	277	8	sludge	sludge	NOUN
brj-23786	277	9	:	:	PUNCT
brj-23786	277	10	thermo	thermo	NOUN
brj-23786	277	11	-	-	PUNCT
brj-23786	277	12	kinetic	kinetic	NOUN
brj-23786	277	13	study	study	NOUN
brj-23786	277	14	using	use	VERB
brj-23786	277	15	tga	tga	PROPN
brj-23786	277	16	and	and	CCONJ
brj-23786	277	17	artificial	artificial	ADJ
brj-23786	277	18	neural	neural	ADJ
brj-23786	277	19	networks	network	NOUN
brj-23786	277	20	,	,	PUNCT
brj-23786	277	21	”	"	PUNCT
brj-23786	277	22	fuel	fuel	NOUN
brj-23786	277	23	233	233	NUM
brj-23786	277	24	,	,	PUNCT
brj-23786	277	25	529	529	NUM
brj-23786	277	26	-	-	SYM
brj-23786	277	27	538	538	NUM
brj-23786	277	28	.	.	PUNCT
brj-23786	278	1	doi	doi	NOUN
brj-23786	278	2	:	:	PUNCT
brj-23786	278	3	10.1016	10.1016	NUM
brj-23786	278	4	/	/	SYM
brj-23786	278	5	j.fuel.2018.06.089	j.fuel.2018.06.089	PROPN
brj-23786	278	6	quan	quan	PROPN
brj-23786	278	7	,	,	PUNCT
brj-23786	278	8	g.	g.	PROPN
brj-23786	278	9	,	,	PUNCT
brj-23786	278	10	wang	wang	PROPN
brj-23786	278	11	,	,	PUNCT
brj-23786	278	12	t.	t.	PROPN
brj-23786	278	13	,	,	PUNCT
brj-23786	278	14	li	li	PROPN
brj-23786	278	15	,	,	PUNCT
brj-23786	278	16	y.	y.	PROPN
brj-23786	278	17	,	,	PUNCT
brj-23786	278	18	zhan	zhan	PROPN
brj-23786	278	19	,	,	PUNCT
brj-23786	278	20	z.	z.	PROPN
brj-23786	278	21	,	,	PUNCT
brj-23786	278	22	and	and	CCONJ
brj-23786	278	23	xia	xia	PROPN
brj-23786	278	24	,	,	PUNCT
brj-23786	278	25	y.	y.	PROPN
brj-23786	278	26	(	(	PUNCT
brj-23786	278	27	2016	2016	NUM
brj-23786	278	28	)	)	PUNCT
brj-23786	278	29	.	.	PUNCT
brj-23786	279	1	“	"	PUNCT
brj-23786	279	2	artificial	artificial	ADJ
brj-23786	279	3	neural	neural	ADJ
brj-23786	279	4	network	network	NOUN
brj-23786	279	5	modeling	modeling	NOUN
brj-23786	279	6	to	to	PART
brj-23786	279	7	evaluate	evaluate	VERB
brj-23786	279	8	the	the	DET
brj-23786	279	9	dynamic	dynamic	ADJ
brj-23786	279	10	flow	flow	NOUN
brj-23786	279	11	stress	stress	NOUN
brj-23786	279	12	of	of	ADP
brj-23786	279	13	7050	7050	NUM
brj-23786	279	14	aluminum	aluminum	NOUN
brj-23786	279	15	alloy	alloy	NOUN
brj-23786	279	16	,	,	PUNCT
brj-23786	279	17	”	"	PUNCT
brj-23786	279	18	journal	journal	NOUN
brj-23786	279	19	of	of	ADP
brj-23786	279	20	peer	peer	NOUN
brj-23786	279	21	-	-	PUNCT
brj-23786	279	22	reviewed	review	VERB
brj-23786	279	23	article	article	NOUN
brj-23786	279	24	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	279	25	xu	xu	PROPN
brj-23786	279	26	et	et	PROPN
brj-23786	279	27	al	al	PROPN
brj-23786	279	28	.	.	PROPN
brj-23786	280	1	(	(	PUNCT
brj-23786	280	2	2024	2024	NUM
brj-23786	280	3	)	)	PUNCT
brj-23786	280	4	.	.	PUNCT
brj-23786	281	1	“	"	PUNCT
brj-23786	281	2	pyrolysis	pyrolysis	NOUN
brj-23786	281	3	kinetics	kinetic	NOUN
brj-23786	281	4	with	with	ADP
brj-23786	281	5	ann	ann	PROPN
brj-23786	281	6	,	,	PUNCT
brj-23786	281	7	”	"	PUNCT
brj-23786	281	8	bioresources	bioresource	NOUN
brj-23786	281	9	19(4	19(4	NUM
brj-23786	281	10	)	)	PUNCT
brj-23786	281	11	,	,	PUNCT
brj-23786	281	12	7513	7513	NUM
brj-23786	281	13	-	-	SYM
brj-23786	281	14	7529	7529	NUM
brj-23786	281	15	.	.	PUNCT
brj-23786	282	1	7528	7528	NUM
brj-23786	282	2	materials	material	NOUN
brj-23786	282	3	engineering	engineering	NOUN
brj-23786	282	4	and	and	CCONJ
brj-23786	282	5	performance	performance	NOUN
brj-23786	282	6	25	25	NUM
brj-23786	282	7	,	,	PUNCT
brj-23786	282	8	553	553	NUM
brj-23786	282	9	-	-	SYM
brj-23786	282	10	564	564	NUM
brj-23786	282	11	.	.	PUNCT
brj-23786	283	1	doi	doi	NOUN
brj-23786	283	2	:	:	PUNCT
brj-23786	283	3	10.1007	10.1007	NUM
brj-23786	283	4	/	/	SYM
brj-23786	283	5	s11665	s11665	NUM
brj-23786	283	6	-	-	PUNCT
brj-23786	283	7	0161884	0161884	NUM
brj-23786	283	8	-	-	PUNCT
brj-23786	283	9	z	z	NOUN
brj-23786	283	10	ragauskas	ragauskas	NOUN
brj-23786	283	11	,	,	PUNCT
brj-23786	283	12	a.	a.	PROPN
brj-23786	283	13	j.	j.	PROPN
brj-23786	283	14	,	,	PUNCT
brj-23786	283	15	williams	williams	PROPN
brj-23786	283	16	,	,	PUNCT
brj-23786	283	17	c.	c.	PROPN
brj-23786	283	18	k.	k.	PROPN
brj-23786	283	19	,	,	PUNCT
brj-23786	283	20	davison	davison	PROPN
brj-23786	283	21	,	,	PUNCT
brj-23786	283	22	b.	b.	PROPN
brj-23786	283	23	h.	h.	PROPN
brj-23786	283	24	,	,	PUNCT
brj-23786	283	25	britovsek	britovsek	PROPN
brj-23786	283	26	,	,	PUNCT
brj-23786	283	27	g.	g.	PROPN
brj-23786	283	28	,	,	PUNCT
brj-23786	283	29	cairney	cairney	PROPN
brj-23786	283	30	,	,	PUNCT
brj-23786	283	31	j.	j.	PROPN
brj-23786	283	32	,	,	PUNCT
brj-23786	283	33	eckert	eckert	PROPN
brj-23786	283	34	,	,	PUNCT
brj-23786	283	35	c.	c.	PROPN
brj-23786	283	36	a.	a.	PROPN
brj-23786	283	37	,	,	PUNCT
brj-23786	283	38	frederick	frederick	PROPN
brj-23786	283	39	,	,	PUNCT
brj-23786	283	40	jr	jr	PROPN
brj-23786	283	41	.	.	PROPN
brj-23786	283	42	,	,	PUNCT
brj-23786	283	43	w.	w.	PROPN
brj-23786	283	44	j.	j.	PROPN
brj-23786	283	45	,	,	PUNCT
brj-23786	283	46	hallett	hallett	PROPN
brj-23786	283	47	,	,	PUNCT
brj-23786	283	48	j.	j.	PROPN
brj-23786	283	49	p.	p.	PROPN
brj-23786	283	50	,	,	PUNCT
brj-23786	283	51	leak	leak	PROPN
brj-23786	283	52	,	,	PUNCT
brj-23786	283	53	d.	d.	PROPN
brj-23786	283	54	j.	j.	PROPN
brj-23786	283	55	,	,	PUNCT
brj-23786	283	56	liotta	liotta	PROPN
brj-23786	283	57	,	,	PUNCT
brj-23786	283	58	c.	c.	PROPN
brj-23786	283	59	l.	l.	PROPN
brj-23786	283	60	,	,	PUNCT
brj-23786	283	61	et	et	PROPN
brj-23786	283	62	al	al	PROPN
brj-23786	283	63	.	.	PUNCT
brj-23786	283	64	(	(	PUNCT
brj-23786	283	65	2006	2006	NUM
brj-23786	283	66	)	)	PUNCT
brj-23786	283	67	.	.	PUNCT
brj-23786	284	1	“	"	PUNCT
brj-23786	284	2	the	the	DET
brj-23786	284	3	path	path	NOUN
brj-23786	284	4	forward	forward	ADV
brj-23786	284	5	for	for	ADP
brj-23786	284	6	biofuels	biofuel	NOUN
brj-23786	284	7	and	and	CCONJ
brj-23786	284	8	biomaterials	biomaterial	NOUN
brj-23786	284	9	,	,	PUNCT
brj-23786	284	10	”	"	PUNCT
brj-23786	284	11	science	science	NOUN
brj-23786	284	12	311	311	NUM
brj-23786	284	13	,	,	PUNCT
brj-23786	284	14	484	484	NUM
brj-23786	284	15	-	-	SYM
brj-23786	284	16	489	489	NUM
brj-23786	284	17	.	.	PUNCT
brj-23786	285	1	doi	doi	NOUN
brj-23786	285	2	:	:	PUNCT
brj-23786	285	3	10.1126	10.1126	NUM
brj-23786	285	4	/	/	SYM
brj-23786	285	5	science.1114736	science.1114736	PROPN
brj-23786	285	6	shen	shen	NOUN
brj-23786	285	7	,	,	PUNCT
brj-23786	285	8	q.	q.	PROPN
brj-23786	285	9	,	,	PUNCT
brj-23786	285	10	zhang	zhang	PROPN
brj-23786	285	11	,	,	PUNCT
brj-23786	285	12	d.	d.	PROPN
brj-23786	285	13	,	,	PUNCT
brj-23786	285	14	xie	xie	PROPN
brj-23786	285	15	,	,	PUNCT
brj-23786	285	16	m.	m.	NOUN
brj-23786	285	17	,	,	PUNCT
brj-23786	285	18	and	and	CCONJ
brj-23786	285	19	he	he	PRON
brj-23786	285	20	,	,	PUNCT
brj-23786	285	21	q.	q.	PROPN
brj-23786	285	22	(	(	PUNCT
brj-23786	285	23	2023	2023	NUM
brj-23786	285	24	)	)	PUNCT
brj-23786	285	25	.	.	PUNCT
brj-23786	286	1	“	"	PUNCT
brj-23786	286	2	multi	multi	ADJ
brj-23786	286	3	-	-	ADJ
brj-23786	286	4	strategy	strategy	ADJ
brj-23786	286	5	enhanced	enhance	VERB
brj-23786	286	6	dung	dung	NOUN
brj-23786	286	7	beetle	beetle	NOUN
brj-23786	286	8	optimizer	optimizer	NOUN
brj-23786	286	9	and	and	CCONJ
brj-23786	286	10	its	its	PRON
brj-23786	286	11	application	application	NOUN
brj-23786	286	12	in	in	ADP
brj-23786	286	13	three	three	NUM
brj-23786	286	14	-	-	PUNCT
brj-23786	286	15	dimensional	dimensional	ADJ
brj-23786	286	16	uav	uav	PROPN
brj-23786	286	17	path	path	NOUN
brj-23786	286	18	planning	planning	NOUN
brj-23786	286	19	,	,	PUNCT
brj-23786	286	20	”	"	PUNCT
brj-23786	286	21	symmetry	symmetry	NOUN
brj-23786	286	22	15(7	15(7	NUM
brj-23786	286	23	)	)	PUNCT
brj-23786	286	24	,	,	PUNCT
brj-23786	286	25	article	article	NOUN
brj-23786	286	26	1432	1432	NUM
brj-23786	286	27	.	.	PUNCT
brj-23786	287	1	doi	doi	NOUN
brj-23786	287	2	:	:	PUNCT
brj-23786	287	3	10.3390	10.3390	NUM
brj-23786	287	4	/	/	SYM
brj-23786	287	5	sym15071432	sym15071432	NOUN
brj-23786	287	6	sunphorka	sunphorka	PROPN
brj-23786	287	7	,	,	PUNCT
brj-23786	287	8	s.	s.	PROPN
brj-23786	287	9	,	,	PUNCT
brj-23786	287	10	chalermsinsuwan	chalermsinsuwan	PROPN
brj-23786	287	11	,	,	PUNCT
brj-23786	287	12	b.	b.	PROPN
brj-23786	287	13	,	,	PUNCT
brj-23786	287	14	and	and	CCONJ
brj-23786	287	15	piumsomboon	piumsomboon	NOUN
brj-23786	287	16	,	,	PUNCT
brj-23786	287	17	p.	p.	NOUN
brj-23786	287	18	(	(	PUNCT
brj-23786	287	19	2017	2017	NUM
brj-23786	287	20	)	)	PUNCT
brj-23786	287	21	.	.	PUNCT
brj-23786	288	1	“	"	PUNCT
brj-23786	288	2	artificial	artificial	ADJ
brj-23786	288	3	neural	neural	ADJ
brj-23786	288	4	network	network	NOUN
brj-23786	288	5	model	model	NOUN
brj-23786	288	6	for	for	ADP
brj-23786	288	7	the	the	DET
brj-23786	288	8	prediction	prediction	NOUN
brj-23786	288	9	of	of	ADP
brj-23786	288	10	kinetic	kinetic	ADJ
brj-23786	288	11	parameters	parameter	NOUN
brj-23786	288	12	of	of	ADP
brj-23786	288	13	biomass	biomass	NOUN
brj-23786	288	14	pyrolysis	pyrolysis	NOUN
brj-23786	288	15	from	from	ADP
brj-23786	288	16	its	its	PRON
brj-23786	288	17	constituents	constituent	NOUN
brj-23786	288	18	,	,	PUNCT
brj-23786	288	19	”	"	PUNCT
brj-23786	288	20	fuel	fuel	NOUN
brj-23786	288	21	193	193	NUM
brj-23786	288	22	,	,	PUNCT
brj-23786	288	23	142	142	NUM
brj-23786	288	24	-	-	SYM
brj-23786	288	25	158	158	NUM
brj-23786	288	26	.	.	PUNCT
brj-23786	289	1	doi	doi	NOUN
brj-23786	289	2	:	:	PUNCT
brj-23786	289	3	10.1016	10.1016	NUM
brj-23786	289	4	/	/	SYM
brj-23786	289	5	j.fuel.2016.12.046	j.fuel.2016.12.046	PROPN
brj-23786	289	6	vo	vo	PROPN
brj-23786	289	7	,	,	PUNCT
brj-23786	289	8	t.	t.	PROPN
brj-23786	289	9	,	,	PUNCT
brj-23786	289	10	tran	tran	PROPN
brj-23786	289	11	,	,	PUNCT
brj-23786	289	12	q.	q.	PROPN
brj-23786	289	13	,	,	PUNCT
brj-23786	289	14	ly	ly	PROPN
brj-23786	289	15	,	,	PUNCT
brj-23786	289	16	h.	h.	PROPN
brj-23786	289	17	,	,	PUNCT
brj-23786	289	18	kwon	kwon	PROPN
brj-23786	289	19	,	,	PUNCT
brj-23786	289	20	b.	b.	PROPN
brj-23786	289	21	,	,	PUNCT
brj-23786	289	22	hwang	hwang	PROPN
brj-23786	289	23	,	,	PUNCT
brj-23786	289	24	h.	h.	PROPN
brj-23786	289	25	,	,	PUNCT
brj-23786	289	26	kim	kim	PROPN
brj-23786	289	27	,	,	PUNCT
brj-23786	289	28	j.	j.	PROPN
brj-23786	289	29	,	,	PUNCT
brj-23786	289	30	and	and	CCONJ
brj-23786	289	31	kim	kim	PROPN
brj-23786	289	32	,	,	PUNCT
brj-23786	289	33	s.	s.	PROPN
brj-23786	289	34	(	(	PUNCT
brj-23786	289	35	2022	2022	NUM
brj-23786	289	36	)	)	PUNCT
brj-23786	289	37	.	.	PUNCT
brj-23786	290	1	“	"	PUNCT
brj-23786	290	2	copyrolysis	copyrolysis	NOUN
brj-23786	290	3	of	of	ADP
brj-23786	290	4	lignocellulosic	lignocellulosic	ADJ
brj-23786	290	5	biomass	biomass	NOUN
brj-23786	290	6	and	and	CCONJ
brj-23786	290	7	plastics	plastic	NOUN
brj-23786	290	8	:	:	PUNCT
brj-23786	290	9	a	a	DET
brj-23786	290	10	comprehensive	comprehensive	ADJ
brj-23786	290	11	study	study	NOUN
brj-23786	290	12	on	on	ADP
brj-23786	290	13	pyrolysis	pyrolysis	NOUN
brj-23786	290	14	kinetics	kinetic	NOUN
brj-23786	290	15	and	and	CCONJ
brj-23786	290	16	characteristics	characteristic	NOUN
brj-23786	290	17	,	,	PUNCT
brj-23786	290	18	”	"	PUNCT
brj-23786	290	19	journal	journal	NOUN
brj-23786	290	20	of	of	ADP
brj-23786	290	21	analytical	analytical	ADJ
brj-23786	290	22	and	and	CCONJ
brj-23786	290	23	applied	applied	ADJ
brj-23786	290	24	pyrolysis	pyrolysis	NOUN
brj-23786	290	25	163	163	NUM
brj-23786	290	26	,	,	PUNCT
brj-23786	290	27	article	article	NOUN
brj-23786	290	28	105464	105464	NUM
brj-23786	290	29	.	.	PUNCT
brj-23786	291	1	doi	doi	NOUN
brj-23786	291	2	:	:	PUNCT
brj-23786	291	3	10.1016	10.1016	NUM
brj-23786	291	4	/	/	SYM
brj-23786	291	5	j.jaap.2022.105464	j.jaap.2022.105464	PROPN
brj-23786	291	6	white	white	PROPN
brj-23786	291	7	,	,	PUNCT
brj-23786	291	8	e.	e.	PROPN
brj-23786	291	9	,	,	PUNCT
brj-23786	291	10	catallo	catallo	PROPN
brj-23786	291	11	,	,	PUNCT
brj-23786	291	12	j.	j.	PROPN
brj-23786	291	13	,	,	PUNCT
brj-23786	291	14	and	and	CCONJ
brj-23786	291	15	legendre	legendre	PROPN
brj-23786	291	16	,	,	PUNCT
brj-23786	291	17	l.	l.	PROPN
brj-23786	291	18	(	(	PUNCT
brj-23786	291	19	2011	2011	NUM
brj-23786	291	20	)	)	PUNCT
brj-23786	291	21	.	.	PUNCT
brj-23786	292	1	“	"	PUNCT
brj-23786	292	2	biomass	biomass	NOUN
brj-23786	292	3	pyrolysis	pyrolysis	NOUN
brj-23786	292	4	kinetics	kinetic	NOUN
brj-23786	292	5	:	:	PUNCT
brj-23786	292	6	a	a	DET
brj-23786	292	7	comparative	comparative	ADJ
brj-23786	292	8	critical	critical	ADJ
brj-23786	292	9	review	review	NOUN
brj-23786	292	10	with	with	ADP
brj-23786	292	11	relevant	relevant	ADJ
brj-23786	292	12	agricultural	agricultural	ADJ
brj-23786	292	13	residue	residue	NOUN
brj-23786	292	14	case	case	NOUN
brj-23786	292	15	studies	study	NOUN
brj-23786	292	16	,	,	PUNCT
brj-23786	292	17	”	"	PUNCT
brj-23786	292	18	journal	journal	NOUN
brj-23786	292	19	of	of	ADP
brj-23786	292	20	analytical	analytical	ADJ
brj-23786	292	21	and	and	CCONJ
brj-23786	292	22	applied	applied	ADJ
brj-23786	292	23	pyrolysis	pyrolysis	NOUN
brj-23786	292	24	91(1	91(1	NOUN
brj-23786	292	25	)	)	PUNCT
brj-23786	292	26	,	,	PUNCT
brj-23786	292	27	1	1	NUM
brj-23786	292	28	-	-	SYM
brj-23786	292	29	33	33	NUM
brj-23786	292	30	.	.	PUNCT
brj-23786	293	1	doi	doi	NOUN
brj-23786	293	2	:	:	PUNCT
brj-23786	293	3	10.1016	10.1016	NUM
brj-23786	293	4	/	/	SYM
brj-23786	293	5	j.jaap.2011.01.004	j.jaap.2011.01.004	PROPN
brj-23786	293	6	wei	wei	PROPN
brj-23786	293	7	,	,	PUNCT
brj-23786	293	8	h.	h.	PROPN
brj-23786	293	9	,	,	PUNCT
brj-23786	293	10	xing	xing	PROPN
brj-23786	293	11	,	,	PUNCT
brj-23786	293	12	j.	j.	PROPN
brj-23786	293	13	,	,	PUNCT
brj-23786	293	14	luo	luo	PROPN
brj-23786	293	15	,	,	PUNCT
brj-23786	293	16	k.	k.	PROPN
brj-23786	293	17	,	,	PUNCT
brj-23786	293	18	peng	peng	PROPN
brj-23786	293	19	,	,	PUNCT
brj-23786	293	20	y.	y.	PROPN
brj-23786	293	21	,	,	PUNCT
brj-23786	293	22	fan	fan	PROPN
brj-23786	293	23	,	,	PUNCT
brj-23786	293	24	j.	j.	PROPN
brj-23786	293	25	,	,	PUNCT
brj-23786	293	26	zhang	zhang	PROPN
brj-23786	293	27	,	,	PUNCT
brj-23786	293	28	k.	k.	PROPN
brj-23786	293	29	,	,	PUNCT
brj-23786	293	30	and	and	CCONJ
brj-23786	293	31	wang	wang	PROPN
brj-23786	293	32	,	,	PUNCT
brj-23786	293	33	h.	h.	PROPN
brj-23786	293	34	(	(	PUNCT
brj-23786	293	35	2023	2023	NUM
brj-23786	293	36	)	)	PUNCT
brj-23786	293	37	.	.	PUNCT
brj-23786	294	1	“	"	PUNCT
brj-23786	294	2	predicting	predict	VERB
brj-23786	294	3	tobacco	tobacco	NOUN
brj-23786	294	4	pyrolysis	pyrolysis	NOUN
brj-23786	294	5	based	base	VERB
brj-23786	294	6	on	on	ADP
brj-23786	294	7	chemical	chemical	ADJ
brj-23786	294	8	constituents	constituent	NOUN
brj-23786	294	9	and	and	CCONJ
brj-23786	294	10	heating	heating	NOUN
brj-23786	294	11	conditions	condition	NOUN
brj-23786	294	12	using	use	VERB
brj-23786	294	13	machine	machine	NOUN
brj-23786	294	14	learning	learning	NOUN
brj-23786	294	15	approaches	approach	NOUN
brj-23786	294	16	,	,	PUNCT
brj-23786	294	17	”	"	PUNCT
brj-23786	294	18	fuel	fuel	NOUN
brj-23786	294	19	335	335	NUM
brj-23786	294	20	,	,	PUNCT
brj-23786	294	21	article	article	NOUN
brj-23786	294	22	126895	126895	NUM
brj-23786	294	23	.	.	PUNCT
brj-23786	295	1	doi	doi	NOUN
brj-23786	295	2	:	:	PUNCT
brj-23786	295	3	10.1016	10.1016	NUM
brj-23786	295	4	/	/	SYM
brj-23786	295	5	j.fuel.2022.126895	j.fuel.2022.126895	PROPN
brj-23786	295	6	xing	xing	PROPN
brj-23786	295	7	,	,	PUNCT
brj-23786	295	8	j.	j.	PROPN
brj-23786	295	9	,	,	PUNCT
brj-23786	295	10	luo	luo	PROPN
brj-23786	295	11	,	,	PUNCT
brj-23786	295	12	k.	k.	PROPN
brj-23786	295	13	,	,	PUNCT
brj-23786	295	14	wang	wang	PROPN
brj-23786	295	15	,	,	PUNCT
brj-23786	295	16	h.	h.	PROPN
brj-23786	295	17	,	,	PUNCT
brj-23786	295	18	gao	gao	PROPN
brj-23786	295	19	,	,	PUNCT
brj-23786	295	20	z.	z.	PROPN
brj-23786	295	21	,	,	PUNCT
brj-23786	295	22	and	and	CCONJ
brj-23786	295	23	fan	fan	PROPN
brj-23786	295	24	,	,	PUNCT
brj-23786	295	25	j.	j.	PROPN
brj-23786	295	26	(	(	PUNCT
brj-23786	295	27	2019	2019	NUM
brj-23786	295	28	)	)	PUNCT
brj-23786	295	29	.	.	PUNCT
brj-23786	296	1	“	"	PUNCT
brj-23786	296	2	a	a	DET
brj-23786	296	3	comprehensive	comprehensive	ADJ
brj-23786	296	4	study	study	NOUN
brj-23786	296	5	on	on	ADP
brj-23786	296	6	estimating	estimate	VERB
brj-23786	296	7	higher	high	ADJ
brj-23786	296	8	heating	heating	NOUN
brj-23786	296	9	value	value	NOUN
brj-23786	296	10	of	of	ADP
brj-23786	296	11	biomass	biomass	NOUN
brj-23786	296	12	from	from	ADP
brj-23786	296	13	proximate	proximate	NOUN
brj-23786	296	14	and	and	CCONJ
brj-23786	296	15	ultimate	ultimate	ADJ
brj-23786	296	16	analysis	analysis	NOUN
brj-23786	296	17	with	with	ADP
brj-23786	296	18	machine	machine	NOUN
brj-23786	296	19	learning	learning	NOUN
brj-23786	296	20	approaches	approach	NOUN
brj-23786	296	21	,	,	PUNCT
brj-23786	296	22	”	"	PUNCT
brj-23786	296	23	energy	energy	NOUN
brj-23786	296	24	188	188	NUM
brj-23786	296	25	,	,	PUNCT
brj-23786	296	26	article	article	NOUN
brj-23786	296	27	116077	116077	NUM
brj-23786	296	28	.	.	PUNCT
brj-23786	297	1	doi	doi	NOUN
brj-23786	297	2	:	:	PUNCT
brj-23786	297	3	10.1016	10.1016	NUM
brj-23786	297	4	/	/	SYM
brj-23786	297	5	j.energy.2019.116077	j.energy.2019.116077	PROPN
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brj-23786	297	7	,	,	PUNCT
brj-23786	297	8	j.	j.	PROPN
brj-23786	297	9	,	,	PUNCT
brj-23786	297	10	and	and	CCONJ
brj-23786	297	11	shen	shen	PROPN
brj-23786	297	12	,	,	PUNCT
brj-23786	297	13	b.	b.	PROPN
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brj-23786	297	15	2022	2022	NUM
brj-23786	297	16	)	)	PUNCT
brj-23786	297	17	.	.	PUNCT
brj-23786	298	1	“	"	PUNCT
brj-23786	298	2	dung	dung	NOUN
brj-23786	298	3	beetle	beetle	NOUN
brj-23786	298	4	optimizer	optimizer	NOUN
brj-23786	298	5	:	:	PUNCT
brj-23786	298	6	a	a	DET
brj-23786	298	7	new	new	ADJ
brj-23786	298	8	meta	meta	ADJ
brj-23786	298	9	-	-	PUNCT
brj-23786	298	10	heuristic	heuristic	ADJ
brj-23786	298	11	algorithm	algorithm	NOUN
brj-23786	298	12	for	for	ADP
brj-23786	298	13	global	global	ADJ
brj-23786	298	14	optimization	optimization	NOUN
brj-23786	298	15	,	,	PUNCT
brj-23786	298	16	”	"	PUNCT
brj-23786	298	17	the	the	DET
brj-23786	298	18	journal	journal	NOUN
brj-23786	298	19	of	of	ADP
brj-23786	298	20	supercomputing	supercompute	VERB
brj-23786	298	21	79	79	NUM
brj-23786	298	22	,	,	PUNCT
brj-23786	298	23	7305	7305	NUM
brj-23786	298	24	-	-	SYM
brj-23786	298	25	7336	7336	NUM
brj-23786	298	26	.	.	PUNCT
brj-23786	299	1	doi	doi	NOUN
brj-23786	299	2	:	:	PUNCT
brj-23786	299	3	10	10	NUM
brj-23786	299	4	.	.	X
brj-23786	299	5	1007	1007	NUM
brj-23786	299	6	/	/	SYM
brj-23786	299	7	s11227	s11227	VERB
brj-23786	299	8	-	-	PUNCT
brj-23786	299	9	022	022	NUM
brj-23786	299	10	-	-	PUNCT
brj-23786	299	11	04959	04959	NUM
brj-23786	299	12	-	-	SYM
brj-23786	299	13	6	6	NUM
brj-23786	299	14	xu	xu	PROPN
brj-23786	299	15	,	,	PUNCT
brj-23786	299	16	l.	l.	PROPN
brj-23786	299	17	,	,	PUNCT
brj-23786	299	18	zhou	zhou	PROPN
brj-23786	299	19	,	,	PUNCT
brj-23786	299	20	j.	j.	PROPN
brj-23786	299	21	,	,	PUNCT
brj-23786	299	22	ni	ni	PROPN
brj-23786	299	23	,	,	PUNCT
brj-23786	299	24	j.	j.	PROPN
brj-23786	299	25	,	,	PUNCT
brj-23786	299	26	li	li	PROPN
brj-23786	299	27	,	,	PUNCT
brj-23786	299	28	y.	y.	PROPN
brj-23786	299	29	,	,	PUNCT
brj-23786	299	30	long	long	ADV
brj-23786	299	31	,	,	PUNCT
brj-23786	299	32	y.	y.	PROPN
brj-23786	299	33	,	,	PUNCT
brj-23786	299	34	and	and	CCONJ
brj-23786	299	35	huang	huang	PROPN
brj-23786	299	36	,	,	PUNCT
brj-23786	299	37	r.	r.	PROPN
brj-23786	299	38	(	(	PUNCT
brj-23786	299	39	2020	2020	NUM
brj-23786	299	40	)	)	PUNCT
brj-23786	299	41	.	.	PUNCT
brj-23786	300	1	“	"	PUNCT
brj-23786	300	2	investigating	investigate	VERB
brj-23786	300	3	the	the	DET
brj-23786	300	4	pyrolysis	pyrolysis	NOUN
brj-23786	300	5	kinetics	kinetic	NOUN
brj-23786	300	6	of	of	ADP
brj-23786	300	7	pinus	pinus	NOUN
brj-23786	300	8	sylvestris	sylvestris	NOUN
brj-23786	300	9	using	use	VERB
brj-23786	300	10	thermogravimetric	thermogravimetric	ADJ
brj-23786	300	11	analysis	analysis	NOUN
brj-23786	300	12	,	,	PUNCT
brj-23786	300	13	”	"	PUNCT
brj-23786	300	14	bioresources	bioresource	NOUN
brj-23786	300	15	15(3	15(3	NUM
brj-23786	300	16	)	)	PUNCT
brj-23786	300	17	,	,	PUNCT
brj-23786	300	18	5577	5577	NUM
brj-23786	300	19	-	-	SYM
brj-23786	300	20	5592	5592	NUM
brj-23786	300	21	.	.	PUNCT
brj-23786	301	1	doi	doi	NOUN
brj-23786	301	2	:	:	PUNCT
brj-23786	301	3	10.15376	10.15376	NUM
brj-23786	301	4	/	/	SYM
brj-23786	301	5	biores.15.3.5577	biores.15.3.5577	PROPN
brj-23786	301	6	-	-	PUNCT
brj-23786	301	7	5592	5592	NUM
brj-23786	301	8	xu	xu	PROPN
brj-23786	301	9	,	,	PUNCT
brj-23786	301	10	l.	l.	PROPN
brj-23786	301	11	,	,	PUNCT
brj-23786	301	12	zhang	zhang	PROPN
brj-23786	301	13	,	,	PUNCT
brj-23786	301	14	y.	y.	PROPN
brj-23786	301	15	,	,	PUNCT
brj-23786	301	16	wang	wang	PROPN
brj-23786	301	17	,	,	PUNCT
brj-23786	301	18	z.	z.	PROPN
brj-23786	301	19	,	,	PUNCT
brj-23786	301	20	guo	guo	PROPN
brj-23786	301	21	,	,	PUNCT
brj-23786	301	22	s.	s.	PROPN
brj-23786	301	23	,	,	PUNCT
brj-23786	301	24	hao	hao	PROPN
brj-23786	301	25	,	,	PUNCT
brj-23786	301	26	y.	y.	PROPN
brj-23786	301	27	,	,	PUNCT
brj-23786	301	28	gao	gao	PROPN
brj-23786	301	29	,	,	PUNCT
brj-23786	301	30	y.	y.	PROPN
brj-23786	301	31	,	,	PUNCT
brj-23786	301	32	xin	xin	PROPN
brj-23786	301	33	,	,	PUNCT
brj-23786	301	34	m.	m.	NOUN
brj-23786	301	35	,	,	PUNCT
brj-23786	301	36	ran	run	VERB
brj-23786	301	37	,	,	PUNCT
brj-23786	301	38	y.	y.	PROPN
brj-23786	301	39	,	,	PUNCT
brj-23786	301	40	li	li	PROPN
brj-23786	301	41	,	,	PUNCT
brj-23786	301	42	s.	s.	PROPN
brj-23786	301	43	,	,	PUNCT
brj-23786	301	44	ji	ji	PROPN
brj-23786	301	45	,	,	PUNCT
brj-23786	301	46	r.	r.	PROPN
brj-23786	301	47	,	,	PUNCT
brj-23786	301	48	li	li	PROPN
brj-23786	301	49	,	,	PUNCT
brj-23786	301	50	h.	h.	PROPN
brj-23786	301	51	,	,	PUNCT
brj-23786	301	52	jiang	jiang	PROPN
brj-23786	301	53	,	,	PUNCT
brj-23786	301	54	h.	h.	PROPN
brj-23786	301	55	,	,	PUNCT
brj-23786	301	56	he	he	PRON
brj-23786	301	57	,	,	PUNCT
brj-23786	301	58	q.	q.	PROPN
brj-23786	301	59	,	,	PUNCT
brj-23786	301	60	and	and	CCONJ
brj-23786	301	61	huang	huang	PROPN
brj-23786	301	62	,	,	PUNCT
brj-23786	301	63	r.	r.	PROPN
brj-23786	301	64	(	(	PUNCT
brj-23786	301	65	2023	2023	NUM
brj-23786	301	66	)	)	PUNCT
brj-23786	301	67	.	.	PUNCT
brj-23786	302	1	“	"	PUNCT
brj-23786	302	2	kinetic	kinetic	ADJ
brj-23786	302	3	analysis	analysis	NOUN
brj-23786	302	4	and	and	CCONJ
brj-23786	302	5	pyrolysis	pyrolysis	NOUN
brj-23786	302	6	behavior	behavior	NOUN
brj-23786	302	7	of	of	ADP
brj-23786	302	8	pine	pine	ADJ
brj-23786	302	9	needles	needle	NOUN
brj-23786	302	10	by	by	ADP
brj-23786	302	11	tg	tg	PROPN
brj-23786	302	12	-	-	PUNCT
brj-23786	302	13	ftir	ftir	PROPN
brj-23786	302	14	and	and	CCONJ
brj-23786	302	15	py	py	PROPN
brj-23786	302	16	-	-	PUNCT
brj-23786	302	17	gc	gc	PROPN
brj-23786	302	18	/	/	SYM
brj-23786	302	19	ms	ms	PROPN
brj-23786	302	20	,	,	PUNCT
brj-23786	302	21	”	"	PUNCT
brj-23786	302	22	bioresources	bioresource	NOUN
brj-23786	302	23	18(3	18(3	NUM
brj-23786	302	24	)	)	PUNCT
brj-23786	302	25	,	,	PUNCT
brj-23786	302	26	64126429	64126429	NUM
brj-23786	302	27	.	.	PUNCT
brj-23786	303	1	doi	doi	NOUN
brj-23786	303	2	:	:	PUNCT
brj-23786	303	3	10.15376	10.15376	NUM
brj-23786	303	4	/	/	SYM
brj-23786	303	5	biores.18.3.6412	biores.18.3.6412	PROPN
brj-23786	303	6	-	-	PUNCT
brj-23786	303	7	6429	6429	NUM
brj-23786	303	8	yang	yang	PROPN
brj-23786	303	9	,	,	PUNCT
brj-23786	303	10	k.	k.	PROPN
brj-23786	303	11	,	,	PUNCT
brj-23786	303	12	wu	wu	PROPN
brj-23786	303	13	,	,	PUNCT
brj-23786	303	14	k.	k.	PROPN
brj-23786	303	15	,	,	PUNCT
brj-23786	303	16	and	and	CCONJ
brj-23786	303	17	zhang	zhang	PROPN
brj-23786	303	18	,	,	PUNCT
brj-23786	303	19	h.	h.	PROPN
brj-23786	303	20	(	(	PUNCT
brj-23786	303	21	2022	2022	NUM
brj-23786	303	22	)	)	PUNCT
brj-23786	303	23	.	.	PUNCT
brj-23786	304	1	“	"	PUNCT
brj-23786	304	2	machine	machine	NOUN
brj-23786	304	3	learning	learning	NOUN
brj-23786	304	4	prediction	prediction	NOUN
brj-23786	304	5	of	of	ADP
brj-23786	304	6	the	the	DET
brj-23786	304	7	yield	yield	NOUN
brj-23786	304	8	and	and	CCONJ
brj-23786	304	9	oxygen	oxygen	NOUN
brj-23786	304	10	content	content	NOUN
brj-23786	304	11	of	of	ADP
brj-23786	304	12	bio	bio	NOUN
brj-23786	304	13	-	-	NOUN
brj-23786	304	14	oil	oil	NOUN
brj-23786	304	15	via	via	ADP
brj-23786	304	16	biomass	biomass	NOUN
brj-23786	304	17	characteristics	characteristic	NOUN
brj-23786	304	18	and	and	CCONJ
brj-23786	304	19	pyrolysis	pyrolysis	NOUN
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brj-23786	304	21	,	,	PUNCT
brj-23786	304	22	”	"	PUNCT
brj-23786	304	23	energy	energy	NOUN
brj-23786	304	24	254	254	NUM
brj-23786	304	25	,	,	PUNCT
brj-23786	304	26	article	article	NOUN
brj-23786	304	27	124320	124320	NUM
brj-23786	304	28	.	.	PUNCT
brj-23786	305	1	doi	doi	NOUN
brj-23786	305	2	:	:	PUNCT
brj-23786	305	3	10	10	NUM
brj-23786	305	4	.	.	X
brj-23786	306	1	1016	1016	NUM
brj-23786	306	2	/	/	SYM
brj-23786	306	3	j.	j.	PROPN
brj-23786	306	4	energy	energy	PROPN
brj-23786	306	5	.	.	PUNCT
brj-23786	307	1	2022	2022	NUM
brj-23786	307	2	.	.	PUNCT
brj-23786	308	1	124320	124320	NUM
brj-23786	308	2	zhang	zhang	PROPN
brj-23786	308	3	,	,	PUNCT
brj-23786	308	4	t.	t.	PROPN
brj-23786	308	5	,	,	PUNCT
brj-23786	308	6	cao	cao	PROPN
brj-23786	308	7	,	,	PUNCT
brj-23786	308	8	d.	d.	PROPN
brj-23786	308	9	,	,	PUNCT
brj-23786	308	10	feng	feng	PROPN
brj-23786	308	11	,	,	PUNCT
brj-23786	308	12	x.	x.	PROPN
brj-23786	308	13	,	,	PUNCT
brj-23786	308	14	zhu	zhu	PROPN
brj-23786	308	15	,	,	PUNCT
brj-23786	308	16	j.	j.	PROPN
brj-23786	308	17	,	,	PUNCT
brj-23786	308	18	lu	lu	PROPN
brj-23786	308	19	,	,	PUNCT
brj-23786	308	20	x.	x.	PROPN
brj-23786	308	21	,	,	PUNCT
brj-23786	308	22	mu	mu	PROPN
brj-23786	308	23	,	,	PUNCT
brj-23786	308	24	l.	l.	PROPN
brj-23786	308	25	,	,	PUNCT
brj-23786	308	26	and	and	CCONJ
brj-23786	308	27	qian	qian	PROPN
brj-23786	308	28	,	,	PUNCT
brj-23786	308	29	h.	h.	PROPN
brj-23786	308	30	(	(	PUNCT
brj-23786	308	31	2022	2022	NUM
brj-23786	308	32	)	)	PUNCT
brj-23786	308	33	.	.	PUNCT
brj-23786	309	1	“	"	PUNCT
brj-23786	309	2	machine	machine	NOUN
brj-23786	309	3	learning	learning	NOUN
brj-23786	309	4	prediction	prediction	NOUN
brj-23786	309	5	of	of	ADP
brj-23786	309	6	bio	bio	ADJ
brj-23786	309	7	-	-	ADJ
brj-23786	309	8	oil	oil	NOUN
brj-23786	309	9	characteristics	characteristic	NOUN
brj-23786	309	10	quantitatively	quantitatively	ADV
brj-23786	309	11	relating	relate	VERB
brj-23786	309	12	to	to	ADP
brj-23786	309	13	biomass	biomass	NOUN
brj-23786	309	14	compositions	composition	NOUN
brj-23786	309	15	and	and	CCONJ
brj-23786	309	16	pyrolysis	pyrolysis	NOUN
brj-23786	309	17	conditions	condition	NOUN
brj-23786	309	18	,	,	PUNCT
brj-23786	309	19	”	"	PUNCT
brj-23786	309	20	fuel	fuel	NOUN
brj-23786	309	21	312	312	NUM
brj-23786	309	22	,	,	PUNCT
brj-23786	309	23	article	article	NOUN
brj-23786	309	24	122812	122812	NUM
brj-23786	309	25	.	.	PUNCT
brj-23786	310	1	doi	doi	NOUN
brj-23786	310	2	:	:	PUNCT
brj-23786	310	3	10.1016	10.1016	NUM
brj-23786	310	4	/	/	SYM
brj-23786	310	5	j.fuel.2021.122812	j.fuel.2021.122812	PROPN
brj-23786	310	6	zha	zha	PROPN
brj-23786	310	7	,	,	PUNCT
brj-23786	310	8	z.	z.	PROPN
brj-23786	310	9	,	,	PUNCT
brj-23786	310	10	ge	ge	PROPN
brj-23786	310	11	,	,	PUNCT
brj-23786	310	12	z.	z.	PROPN
brj-23786	310	13	,	,	PUNCT
brj-23786	310	14	ma	ma	PROPN
brj-23786	310	15	,	,	PUNCT
brj-23786	310	16	y.	y.	PROPN
brj-23786	310	17	,	,	PUNCT
brj-23786	310	18	zeng	zeng	PROPN
brj-23786	310	19	,	,	PUNCT
brj-23786	310	20	m.	m.	NOUN
brj-23786	310	21	,	,	PUNCT
brj-23786	310	22	tao	tao	PROPN
brj-23786	310	23	,	,	PUNCT
brj-23786	310	24	y.	y.	PROPN
brj-23786	310	25	,	,	PUNCT
brj-23786	310	26	and	and	CCONJ
brj-23786	310	27	zhang	zhang	PROPN
brj-23786	310	28	,	,	PUNCT
brj-23786	310	29	h.	h.	PROPN
brj-23786	310	30	(	(	PUNCT
brj-23786	310	31	2022	2022	NUM
brj-23786	310	32	)	)	PUNCT
brj-23786	310	33	.	.	PUNCT
brj-23786	311	1	“	"	PUNCT
brj-23786	311	2	reactivity	reactivity	NOUN
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brj-23786	311	14	gas	gas	NOUN
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brj-23786	311	16	behaviors	behavior	NOUN
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brj-23786	311	18	a	a	DET
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brj-23786	311	27	237	237	NUM
brj-23786	311	28	,	,	PUNCT
brj-23786	311	29	article	article	NOUN
brj-23786	311	30	111837	111837	NUM
brj-23786	311	31	.	.	PUNCT
brj-23786	312	1	doi	doi	NOUN
brj-23786	312	2	:	:	PUNCT
brj-23786	312	3	10.1016	10.1016	NUM
brj-23786	312	4	/	/	SYM
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brj-23786	312	6	peer	peer	NOUN
brj-23786	312	7	-	-	PUNCT
brj-23786	312	8	reviewed	review	VERB
brj-23786	312	9	article	article	NOUN
brj-23786	312	10	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	X
brj-23786	313	1	xu	xu	PROPN
brj-23786	313	2	et	et	PROPN
brj-23786	313	3	al	al	PROPN
brj-23786	313	4	.	.	PROPN
brj-23786	313	5	(	(	PUNCT
brj-23786	313	6	2024	2024	NUM
brj-23786	313	7	)	)	PUNCT
brj-23786	313	8	.	.	PUNCT
brj-23786	314	1	“	"	PUNCT
brj-23786	314	2	pyrolysis	pyrolysis	NOUN
brj-23786	314	3	kinetics	kinetic	NOUN
brj-23786	314	4	with	with	ADP
brj-23786	314	5	ann	ann	PROPN
brj-23786	314	6	,	,	PUNCT
brj-23786	314	7	”	"	PUNCT
brj-23786	314	8	bioresources	bioresource	NOUN
brj-23786	314	9	19(4	19(4	NUM
brj-23786	314	10	)	)	PUNCT
brj-23786	314	11	,	,	PUNCT
brj-23786	314	12	7513	7513	NUM
brj-23786	314	13	-	-	SYM
brj-23786	314	14	7529	7529	NUM
brj-23786	314	15	.	.	PUNCT
brj-23786	315	1	7529	7529	NUM
brj-23786	315	2	zhong	zhong	PROPN
brj-23786	315	3	,	,	PUNCT
brj-23786	315	4	y.	y.	PROPN
brj-23786	315	5	,	,	PUNCT
brj-23786	315	6	ding	ding	NOUN
brj-23786	315	7	,	,	PUNCT
brj-23786	315	8	y.	y.	PROPN
brj-23786	315	9	,	,	PUNCT
brj-23786	315	10	jiang	jiang	PROPN
brj-23786	315	11	,	,	PUNCT
brj-23786	315	12	g.	g.	PROPN
brj-23786	315	13	,	,	PUNCT
brj-23786	315	14	lu	lu	PROPN
brj-23786	315	15	,	,	PUNCT
brj-23786	315	16	k.	k.	PROPN
brj-23786	315	17	,	,	PUNCT
brj-23786	315	18	and	and	CCONJ
brj-23786	315	19	li	li	PROPN
brj-23786	315	20	,	,	PUNCT
brj-23786	315	21	c.	c.	PROPN
brj-23786	315	22	(	(	PUNCT
brj-23786	315	23	2023	2023	NUM
brj-23786	315	24	)	)	PUNCT
brj-23786	315	25	.	.	PUNCT
brj-23786	316	1	“	"	PUNCT
brj-23786	316	2	comparison	comparison	NOUN
brj-23786	316	3	of	of	ADP
brj-23786	316	4	artificial	artificial	ADJ
brj-23786	316	5	neural	neural	ADJ
brj-23786	316	6	networks	network	NOUN
brj-23786	316	7	and	and	CCONJ
brj-23786	316	8	kinetic	kinetic	ADJ
brj-23786	316	9	inverse	inverse	NOUN
brj-23786	316	10	modeling	modeling	NOUN
brj-23786	316	11	to	to	PART
brj-23786	316	12	predict	predict	VERB
brj-23786	316	13	biomass	biomass	NOUN
brj-23786	316	14	pyrolysis	pyrolysis	NOUN
brj-23786	316	15	behavior	behavior	NOUN
brj-23786	316	16	,	,	PUNCT
brj-23786	316	17	”	"	PUNCT
brj-23786	316	18	journal	journal	NOUN
brj-23786	316	19	of	of	ADP
brj-23786	316	20	analytical	analytical	ADJ
brj-23786	316	21	and	and	CCONJ
brj-23786	316	22	applied	applied	ADJ
brj-23786	316	23	pyrolysis	pyrolysis	NOUN
brj-23786	316	24	169	169	NUM
brj-23786	316	25	,	,	PUNCT
brj-23786	316	26	article	article	NOUN
brj-23786	316	27	105802	105802	NUM
brj-23786	316	28	.	.	PUNCT
brj-23786	317	1	doi	doi	NOUN
brj-23786	317	2	:	:	PUNCT
brj-23786	317	3	10	10	NUM
brj-23786	317	4	.	.	X
brj-23786	318	1	1016	1016	NUM
brj-23786	318	2	/	/	SYM
brj-23786	318	3	j.	j.	PROPN
brj-23786	318	4	jaap	jaap	PROPN
brj-23786	318	5	.	.	PROPN
brj-23786	318	6	2022	2022	NUM
brj-23786	318	7	.	.	PUNCT
brj-23786	319	1	105802	105802	NUM
brj-23786	319	2	zhu	zhu	PROPN
brj-23786	319	3	,	,	PUNCT
brj-23786	319	4	y.	y.	PROPN
brj-23786	319	5	,	,	PUNCT
brj-23786	319	6	cao	cao	PROPN
brj-23786	319	7	,	,	PUNCT
brj-23786	319	8	y.	y.	PROPN
brj-23786	319	9	,	,	PUNCT
brj-23786	319	10	liu	liu	PROPN
brj-23786	319	11	,	,	PUNCT
brj-23786	319	12	c.	c.	PROPN
brj-23786	319	13	,	,	PUNCT
brj-23786	319	14	luo	luo	PROPN
brj-23786	319	15	,	,	PUNCT
brj-23786	319	16	r.	r.	PROPN
brj-23786	319	17	,	,	PUNCT
brj-23786	319	18	li	li	PROPN
brj-23786	319	19	,	,	PUNCT
brj-23786	319	20	n.	n.	PROPN
brj-23786	319	21	,	,	PUNCT
brj-23786	319	22	shu	shu	PROPN
brj-23786	319	23	,	,	PUNCT
brj-23786	319	24	g.	g.	PROPN
brj-23786	319	25	,	,	PUNCT
brj-23786	319	26	and	and	CCONJ
brj-23786	319	27	liu	liu	PROPN
brj-23786	319	28	,	,	PUNCT
brj-23786	319	29	q.	q.	PROPN
brj-23786	319	30	(	(	PUNCT
brj-23786	319	31	2020	2020	NUM
brj-23786	319	32	)	)	PUNCT
brj-23786	319	33	.	.	PUNCT
brj-23786	320	1	“	"	PUNCT
brj-23786	320	2	dynamic	dynamic	ADJ
brj-23786	320	3	behavior	behavior	NOUN
brj-23786	320	4	and	and	CCONJ
brj-23786	320	5	modified	modify	VERB
brj-23786	320	6	artificial	artificial	ADJ
brj-23786	320	7	neural	neural	ADJ
brj-23786	320	8	network	network	NOUN
brj-23786	320	9	model	model	NOUN
brj-23786	320	10	for	for	ADP
brj-23786	320	11	predicting	predict	VERB
brj-23786	320	12	flow	flow	NOUN
brj-23786	320	13	stress	stress	NOUN
brj-23786	320	14	during	during	ADP
brj-23786	320	15	hot	hot	ADJ
brj-23786	320	16	deformation	deformation	NOUN
brj-23786	320	17	of	of	ADP
brj-23786	320	18	alloy	alloy	NOUN
brj-23786	320	19	925	925	NUM
brj-23786	320	20	,	,	PUNCT
brj-23786	320	21	”	"	PUNCT
brj-23786	320	22	materials	material	NOUN
brj-23786	320	23	today	today	NOUN
brj-23786	320	24	communications	communication	NOUN
brj-23786	320	25	25	25	NUM
brj-23786	320	26	,	,	PUNCT
brj-23786	320	27	article	article	NOUN
brj-23786	320	28	101329	101329	NUM
brj-23786	320	29	.	.	PUNCT
brj-23786	321	1	doi	doi	NOUN
brj-23786	321	2	:	:	PUNCT
brj-23786	321	3	10	10	NUM
brj-23786	321	4	.	.	X
brj-23786	322	1	1016	1016	NUM
brj-23786	322	2	/	/	SYM
brj-23786	322	3	j.	j.	PROPN
brj-23786	322	4	mtcomm	mtcomm	PROPN
brj-23786	322	5	.	.	PUNCT
brj-23786	323	1	2020	2020	NUM
brj-23786	323	2	.	.	PUNCT
brj-23786	324	1	101329	101329	NUM
brj-23786	324	2	zhu	zhu	PROPN
brj-23786	324	3	,	,	PUNCT
brj-23786	324	4	h.	h.	PROPN
brj-23786	324	5	,	,	PUNCT
brj-23786	324	6	dong	dong	PROPN
brj-23786	324	7	,	,	PUNCT
brj-23786	324	8	z.	z.	PROPN
brj-23786	324	9	,	,	PUNCT
brj-23786	324	10	yu	yu	PROPN
brj-23786	324	11	,	,	PUNCT
brj-23786	324	12	x.	x.	PROPN
brj-23786	324	13	,	,	PUNCT
brj-23786	324	14	cunningham	cunningham	PROPN
brj-23786	324	15	,	,	PUNCT
brj-23786	324	16	g.	g.	PROPN
brj-23786	324	17	,	,	PUNCT
brj-23786	324	18	umashanker	umashanker	NOUN
brj-23786	324	19	,	,	PUNCT
brj-23786	324	20	j.	j.	PROPN
brj-23786	324	21	,	,	PUNCT
brj-23786	324	22	zhang	zhang	PROPN
brj-23786	324	23	,	,	PUNCT
brj-23786	324	24	x.	x.	PROPN
brj-23786	324	25	,	,	PUNCT
brj-23786	324	26	and	and	CCONJ
brj-23786	324	27	cai	cai	X
brj-23786	324	28	,	,	PUNCT
brj-23786	324	29	j.	j.	PROPN
brj-23786	324	30	(	(	PUNCT
brj-23786	324	31	2021	2021	NUM
brj-23786	324	32	)	)	PUNCT
brj-23786	324	33	.	.	PUNCT
brj-23786	325	1	“	"	PUNCT
brj-23786	325	2	a	a	DET
brj-23786	325	3	predictive	predictive	ADJ
brj-23786	325	4	pbm	pbm	NOUN
brj-23786	325	5	-	-	PUNCT
brj-23786	325	6	deam	deam	NOUN
brj-23786	325	7	model	model	NOUN
brj-23786	325	8	for	for	ADP
brj-23786	325	9	lignocellulosic	lignocellulosic	ADJ
brj-23786	325	10	biomass	biomass	NOUN
brj-23786	325	11	pyrolysis	pyrolysis	NOUN
brj-23786	325	12	,	,	PUNCT
brj-23786	325	13	”	"	PUNCT
brj-23786	325	14	journal	journal	NOUN
brj-23786	325	15	of	of	ADP
brj-23786	325	16	analytical	analytical	ADJ
brj-23786	325	17	and	and	CCONJ
brj-23786	325	18	applied	applied	ADJ
brj-23786	325	19	pyrolysis	pyrolysis	NOUN
brj-23786	325	20	157	157	NUM
brj-23786	325	21	,	,	PUNCT
brj-23786	325	22	article	article	NOUN
brj-23786	325	23	105231	105231	NUM
brj-23786	325	24	.	.	PUNCT
brj-23786	326	1	doi	doi	NOUN
brj-23786	326	2	:	:	PUNCT
brj-23786	326	3	10.1016	10.1016	NUM
brj-23786	326	4	/	/	SYM
brj-23786	326	5	j.jaap.2021.105231	j.jaap.2021.105231	PROPN
brj-23786	326	6	zhu	zhu	PROPN
brj-23786	326	7	,	,	PUNCT
brj-23786	326	8	f.	f.	PROPN
brj-23786	326	9	,	,	PUNCT
brj-23786	326	10	li	li	PROPN
brj-23786	326	11	,	,	PUNCT
brj-23786	326	12	g.	g.	PROPN
brj-23786	326	13	,	,	PUNCT
brj-23786	326	14	tang	tang	PROPN
brj-23786	326	15	,	,	PUNCT
brj-23786	326	16	h.	h.	PROPN
brj-23786	326	17	,	,	PUNCT
brj-23786	326	18	li	li	PROPN
brj-23786	326	19	,	,	PUNCT
brj-23786	326	20	y.	y.	PROPN
brj-23786	326	21	,	,	PUNCT
brj-23786	326	22	lv	lv	PROPN
brj-23786	326	23	,	,	PUNCT
brj-23786	326	24	x.	x.	NOUN
brj-23786	326	25	,	,	PUNCT
brj-23786	326	26	and	and	CCONJ
brj-23786	326	27	wang	wang	PROPN
brj-23786	326	28	,	,	PUNCT
brj-23786	326	29	xi	xi	PROPN
brj-23786	326	30	.	.	PUNCT
brj-23786	326	31	(	(	PUNCT
brj-23786	326	32	2024	2024	NUM
brj-23786	326	33	)	)	PUNCT
brj-23786	326	34	.	.	PUNCT
brj-23786	327	1	“	"	PUNCT
brj-23786	327	2	dung	dung	NOUN
brj-23786	327	3	beetle	beetle	NOUN
brj-23786	327	4	optimization	optimization	NOUN
brj-23786	327	5	algorithm	algorithm	NOUN
brj-23786	327	6	based	base	VERB
brj-23786	327	7	on	on	ADP
brj-23786	327	8	quantum	quantum	NOUN
brj-23786	327	9	computing	computing	NOUN
brj-23786	327	10	and	and	CCONJ
brj-23786	327	11	multi	multi	ADJ
brj-23786	327	12	-	-	ADJ
brj-23786	327	13	strategy	strategy	ADJ
brj-23786	327	14	fusion	fusion	NOUN
brj-23786	327	15	for	for	ADP
brj-23786	327	16	solving	solve	VERB
brj-23786	327	17	engineering	engineering	NOUN
brj-23786	327	18	problems	problem	NOUN
brj-23786	327	19	,	,	PUNCT
brj-23786	327	20	”	"	PUNCT
brj-23786	327	21	expert	expert	NOUN
brj-23786	327	22	systems	system	NOUN
brj-23786	327	23	with	with	ADP
brj-23786	327	24	applications	application	NOUN
brj-23786	327	25	236	236	NUM
brj-23786	327	26	,	,	PUNCT
brj-23786	327	27	article	article	NOUN
brj-23786	327	28	121219	121219	NUM
brj-23786	327	29	.	.	PUNCT
brj-23786	328	1	doi	doi	NOUN
brj-23786	328	2	:	:	PUNCT
brj-23786	328	3	10.1016	10.1016	NUM
brj-23786	328	4	/	/	SYM
brj-23786	328	5	j.eswa.2023.121219	j.eswa.2023.121219	ADJ
brj-23786	328	6	article	article	NOUN
brj-23786	328	7	submitted	submit	VERB
brj-23786	328	8	:	:	PUNCT
brj-23786	328	9	july	july	PROPN
brj-23786	328	10	9	9	NUM
brj-23786	328	11	,	,	PUNCT
brj-23786	328	12	2024	2024	NUM
brj-23786	328	13	;	;	PUNCT
brj-23786	328	14	peer	peer	NOUN
brj-23786	328	15	review	review	NOUN
brj-23786	328	16	completed	complete	VERB
brj-23786	328	17	:	:	PUNCT
brj-23786	328	18	august	august	PROPN
brj-23786	328	19	1	1	NUM
brj-23786	328	20	,	,	PUNCT
brj-23786	328	21	2024	2024	NUM
brj-23786	328	22	;	;	PUNCT
brj-23786	328	23	revised	revise	VERB
brj-23786	328	24	version	version	NOUN
brj-23786	328	25	received	receive	VERB
brj-23786	328	26	:	:	PUNCT
brj-23786	328	27	august	august	PROPN
brj-23786	328	28	9	9	NUM
brj-23786	328	29	,	,	PUNCT
brj-23786	328	30	2024	2024	NUM
brj-23786	328	31	;	;	PUNCT
brj-23786	328	32	accepted	accept	VERB
brj-23786	328	33	:	:	PUNCT
brj-23786	328	34	august	august	PROPN
brj-23786	328	35	11	11	NUM
brj-23786	328	36	,	,	PUNCT
brj-23786	328	37	2024	2024	NUM
brj-23786	328	38	;	;	PUNCT
brj-23786	328	39	published	publish	VERB
brj-23786	328	40	:	:	PUNCT
brj-23786	328	41	august	august	PROPN
brj-23786	328	42	26	26	NUM
brj-23786	328	43	,	,	PUNCT
brj-23786	328	44	2024	2024	NUM
brj-23786	328	45	.	.	PUNCT
brj-23786	329	1	doi	doi	NOUN
brj-23786	329	2	:	:	PUNCT
brj-23786	329	3	10.15376	10.15376	NUM
brj-23786	329	4	/	/	SYM
brj-23786	329	5	biores.19.4.7513	biores.19.4.7513	NOUN
brj-23786	329	6	-	-	SYM
brj-23786	329	7	7529	7529	NUM