id	sid	tid	token	lemma	pos
brj-23187	1	1	peer	peer	NOUN
brj-23187	1	2	-	-	PUNCT
brj-23187	1	3	review	review	NOUN
brj-23187	1	4	article	article	NOUN
brj-23187	1	5	peer	peer	NOUN
brj-23187	1	6	-	-	PUNCT
brj-23187	1	7	reviewed	review	VERB
brj-23187	1	8	article	article	NOUN
brj-23187	1	9	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	1	10	fu	fu	PROPN
brj-23187	1	11	et	et	PROPN
brj-23187	1	12	al	al	PROPN
brj-23187	1	13	.	.	PROPN
brj-23187	2	1	(	(	PUNCT
brj-23187	2	2	2024	2024	NUM
brj-23187	2	3	)	)	PUNCT
brj-23187	2	4	.	.	PUNCT
brj-23187	3	1	“	"	PUNCT
brj-23187	3	2	predicting	predict	VERB
brj-23187	3	3	enzymatic	enzymatic	ADJ
brj-23187	3	4	hydrolysis	hydrolysis	NOUN
brj-23187	3	5	,	,	PUNCT
brj-23187	3	6	”	"	PUNCT
brj-23187	3	7	bioresources	bioresource	NOUN
brj-23187	3	8	19(2	19(2	NUM
brj-23187	3	9	)	)	PUNCT
brj-23187	3	10	,	,	PUNCT
brj-23187	3	11	3505	3505	NUM
brj-23187	3	12	-	-	SYM
brj-23187	3	13	3519	3519	NUM
brj-23187	3	14	.	.	PUNCT
brj-23187	4	1	3505	3505	NUM
brj-23187	4	2	online	online	ADJ
brj-23187	4	3	prediction	prediction	NOUN
brj-23187	4	4	of	of	ADP
brj-23187	4	5	the	the	DET
brj-23187	4	6	enzymatic	enzymatic	ADJ
brj-23187	4	7	hydrolysis	hydrolysis	NOUN
brj-23187	4	8	efficiency	efficiency	NOUN
brj-23187	4	9	of	of	ADP
brj-23187	4	10	crop	crop	NOUN
brj-23187	4	11	straw	straw	NOUN
brj-23187	4	12	xu	xu	PROPN
brj-23187	4	13	fu	fu	PROPN
brj-23187	4	14	,	,	PUNCT
brj-23187	4	15	a,1	a,1	PROPN
brj-23187	4	16	fei	fei	PROPN
brj-23187	4	17	yu	yu	PROPN
brj-23187	4	18	,	,	PUNCT
brj-23187	4	19	a,1	a,1	PROPN
brj-23187	4	20	huning	hune	VERB
brj-23187	4	21	zhang	zhang	PROPN
brj-23187	4	22	,	,	PUNCT
brj-23187	4	23	c	c	PROPN
brj-23187	4	24	yunhui	yunhui	PROPN
brj-23187	4	25	luo	luo	PROPN
brj-23187	4	26	,	,	PUNCT
brj-23187	4	27	b	b	PROPN
brj-23187	4	28	,	,	PUNCT
brj-23187	4	29	*	*	PUNCT
brj-23187	4	30	and	and	CCONJ
brj-23187	4	31	lihua	lihua	PROPN
brj-23187	4	32	zang	zang	PROPN
brj-23187	4	33	a	a	PROPN
brj-23187	4	34	,	,	PUNCT
brj-23187	4	35	*	*	PUNCT
brj-23187	4	36	the	the	DET
brj-23187	4	37	extent	extent	NOUN
brj-23187	4	38	of	of	ADP
brj-23187	4	39	removal	removal	NOUN
brj-23187	4	40	of	of	ADP
brj-23187	4	41	lignin	lignin	NOUN
brj-23187	4	42	and	and	CCONJ
brj-23187	4	43	hemicellulose	hemicellulose	NOUN
brj-23187	4	44	are	be	AUX
brj-23187	4	45	crucial	crucial	ADJ
brj-23187	4	46	indicators	indicator	NOUN
brj-23187	4	47	for	for	ADP
brj-23187	4	48	evaluating	evaluate	VERB
brj-23187	4	49	the	the	DET
brj-23187	4	50	efficiency	efficiency	NOUN
brj-23187	4	51	of	of	ADP
brj-23187	4	52	enzymatic	enzymatic	ADJ
brj-23187	4	53	hydrolysis	hydrolysis	NOUN
brj-23187	4	54	of	of	ADP
brj-23187	4	55	crop	crop	NOUN
brj-23187	4	56	straw	straw	NOUN
brj-23187	4	57	.	.	PUNCT
brj-23187	5	1	numerous	numerous	ADJ
brj-23187	5	2	factors	factor	NOUN
brj-23187	5	3	influence	influence	VERB
brj-23187	5	4	these	these	DET
brj-23187	5	5	two	two	NUM
brj-23187	5	6	indices	index	NOUN
brj-23187	5	7	.	.	PUNCT
brj-23187	6	1	establishing	establish	VERB
brj-23187	6	2	a	a	DET
brj-23187	6	3	quantitative	quantitative	ADJ
brj-23187	6	4	model	model	NOUN
brj-23187	6	5	that	that	PRON
brj-23187	6	6	correlates	correlate	VERB
brj-23187	6	7	these	these	DET
brj-23187	6	8	factors	factor	NOUN
brj-23187	6	9	with	with	ADP
brj-23187	6	10	hydrolysis	hydrolysis	NOUN
brj-23187	6	11	efficiency	efficiency	NOUN
brj-23187	6	12	is	be	AUX
brj-23187	6	13	essential	essential	ADJ
brj-23187	6	14	,	,	PUNCT
brj-23187	6	15	as	as	SCONJ
brj-23187	6	16	it	it	PRON
brj-23187	6	17	can	can	AUX
brj-23187	6	18	guide	guide	VERB
brj-23187	6	19	efficient	efficient	ADJ
brj-23187	6	20	hydrolysis	hydrolysis	NOUN
brj-23187	6	21	.	.	PUNCT
brj-23187	7	1	in	in	ADP
brj-23187	7	2	this	this	DET
brj-23187	7	3	study	study	NOUN
brj-23187	7	4	,	,	PUNCT
brj-23187	7	5	a	a	DET
brj-23187	7	6	predictive	predictive	ADJ
brj-23187	7	7	method	method	NOUN
brj-23187	7	8	for	for	ADP
brj-23187	7	9	enzymatic	enzymatic	ADJ
brj-23187	7	10	hydrolysis	hydrolysis	NOUN
brj-23187	7	11	efficiency	efficiency	NOUN
brj-23187	7	12	in	in	ADP
brj-23187	7	13	crop	crop	NOUN
brj-23187	7	14	straw	straw	NOUN
brj-23187	7	15	was	be	AUX
brj-23187	7	16	proposed	propose	VERB
brj-23187	7	17	using	use	VERB
brj-23187	7	18	grey	grey	ADJ
brj-23187	7	19	relational	relational	ADJ
brj-23187	7	20	analysis	analysis	NOUN
brj-23187	7	21	(	(	PUNCT
brj-23187	7	22	gra	gra	PROPN
brj-23187	7	23	)	)	PUNCT
brj-23187	7	24	,	,	PUNCT
brj-23187	7	25	kernel	kernel	PROPN
brj-23187	7	26	principal	principal	PROPN
brj-23187	7	27	component	component	NOUN
brj-23187	7	28	analysis	analysis	NOUN
brj-23187	7	29	(	(	PUNCT
brj-23187	7	30	kpca	kpca	NOUN
brj-23187	7	31	)	)	PUNCT
brj-23187	7	32	,	,	PUNCT
brj-23187	7	33	and	and	CCONJ
brj-23187	7	34	a	a	DET
brj-23187	7	35	least	least	ADJ
brj-23187	7	36	squares	square	NOUN
brj-23187	7	37	support	support	NOUN
brj-23187	7	38	vector	vector	NOUN
brj-23187	7	39	machine	machine	NOUN
brj-23187	7	40	(	(	PUNCT
brj-23187	7	41	lssvm	lssvm	PROPN
brj-23187	7	42	)	)	PUNCT
brj-23187	7	43	.	.	PUNCT
brj-23187	8	1	the	the	DET
brj-23187	8	2	authors	author	NOUN
brj-23187	8	3	collected	collect	VERB
brj-23187	8	4	a	a	DET
brj-23187	8	5	dataset	dataset	NOUN
brj-23187	8	6	from	from	ADP
brj-23187	8	7	actual	actual	ADJ
brj-23187	8	8	production	production	NOUN
brj-23187	8	9	data	datum	NOUN
brj-23187	8	10	and	and	CCONJ
brj-23187	8	11	developed	develop	VERB
brj-23187	8	12	an	an	DET
brj-23187	8	13	efficiency	efficiency	NOUN
brj-23187	8	14	predictive	predictive	ADJ
brj-23187	8	15	model	model	NOUN
brj-23187	8	16	using	use	VERB
brj-23187	8	17	gra	gra	PROPN
brj-23187	8	18	for	for	ADP
brj-23187	8	19	variable	variable	ADJ
brj-23187	8	20	selection	selection	NOUN
brj-23187	8	21	,	,	PUNCT
brj-23187	8	22	kpca	kpca	NOUN
brj-23187	8	23	for	for	ADP
brj-23187	8	24	dimensionality	dimensionality	NOUN
brj-23187	8	25	reduction	reduction	NOUN
brj-23187	8	26	,	,	PUNCT
brj-23187	8	27	and	and	CCONJ
brj-23187	8	28	lssvm	lssvm	VERB
brj-23187	8	29	for	for	ADP
brj-23187	8	30	model	model	NOUN
brj-23187	8	31	training	training	NOUN
brj-23187	8	32	.	.	PUNCT
brj-23187	9	1	this	this	DET
brj-23187	9	2	model	model	NOUN
brj-23187	9	3	allows	allow	VERB
brj-23187	9	4	for	for	ADP
brj-23187	9	5	the	the	DET
brj-23187	9	6	direct	direct	ADJ
brj-23187	9	7	estimation	estimation	NOUN
brj-23187	9	8	of	of	ADP
brj-23187	9	9	the	the	DET
brj-23187	9	10	final	final	ADJ
brj-23187	9	11	enzymatic	enzymatic	ADJ
brj-23187	9	12	hydrolysis	hydrolysis	NOUN
brj-23187	9	13	efficiency	efficiency	NOUN
brj-23187	9	14	based	base	VERB
brj-23187	9	15	on	on	ADP
brj-23187	9	16	production	production	NOUN
brj-23187	9	17	condition	condition	NOUN
brj-23187	9	18	variables	variable	NOUN
brj-23187	9	19	,	,	PUNCT
brj-23187	9	20	which	which	PRON
brj-23187	9	21	can	can	AUX
brj-23187	9	22	include	include	VERB
brj-23187	9	23	enzyme	enzyme	NOUN
brj-23187	9	24	amount	amount	NOUN
brj-23187	9	25	,	,	PUNCT
brj-23187	9	26	temperatures	temperature	NOUN
brj-23187	9	27	,	,	PUNCT
brj-23187	9	28	ph	ph	ADJ
brj-23187	9	29	,	,	PUNCT
brj-23187	9	30	time	time	NOUN
brj-23187	9	31	,	,	PUNCT
brj-23187	9	32	agitation	agitation	NOUN
brj-23187	9	33	,	,	PUNCT
brj-23187	9	34	and	and	CCONJ
brj-23187	9	35	straw	straw	NOUN
brj-23187	9	36	dimensions	dimension	NOUN
brj-23187	9	37	.	.	PUNCT
brj-23187	10	1	extensive	extensive	ADJ
brj-23187	10	2	experimental	experimental	ADJ
brj-23187	10	3	testing	testing	NOUN
brj-23187	10	4	validated	validate	VERB
brj-23187	10	5	the	the	DET
brj-23187	10	6	effectiveness	effectiveness	NOUN
brj-23187	10	7	of	of	ADP
brj-23187	10	8	the	the	DET
brj-23187	10	9	proposed	propose	VERB
brj-23187	10	10	method	method	NOUN
brj-23187	10	11	,	,	PUNCT
brj-23187	10	12	resulting	result	VERB
brj-23187	10	13	in	in	ADP
brj-23187	10	14	minimal	minimal	ADJ
brj-23187	10	15	errors	error	NOUN
brj-23187	10	16	,	,	PUNCT
brj-23187	10	17	a	a	DET
brj-23187	10	18	high	high	ADJ
brj-23187	10	19	degree	degree	NOUN
brj-23187	10	20	of	of	ADP
brj-23187	10	21	fit	fit	ADJ
brj-23187	10	22	,	,	PUNCT
brj-23187	10	23	and	and	CCONJ
brj-23187	10	24	exceptional	exceptional	ADJ
brj-23187	10	25	performance	performance	NOUN
brj-23187	10	26	.	.	PUNCT
brj-23187	11	1	the	the	DET
brj-23187	11	2	methodology	methodology	NOUN
brj-23187	11	3	described	describe	VERB
brj-23187	11	4	in	in	ADP
brj-23187	11	5	this	this	DET
brj-23187	11	6	study	study	NOUN
brj-23187	11	7	can	can	AUX
brj-23187	11	8	serve	serve	VERB
brj-23187	11	9	as	as	ADP
brj-23187	11	10	a	a	DET
brj-23187	11	11	foundation	foundation	NOUN
brj-23187	11	12	for	for	ADP
brj-23187	11	13	optimising	optimise	VERB
brj-23187	11	14	the	the	DET
brj-23187	11	15	design	design	NOUN
brj-23187	11	16	of	of	ADP
brj-23187	11	17	efficient	efficient	ADJ
brj-23187	11	18	enzymatic	enzymatic	ADJ
brj-23187	11	19	hydrolysis	hydrolysis	NOUN
brj-23187	11	20	production	production	NOUN
brj-23187	11	21	processes	process	NOUN
brj-23187	11	22	for	for	ADP
brj-23187	11	23	crop	crop	NOUN
brj-23187	11	24	straw	straw	NOUN
brj-23187	11	25	.	.	PUNCT
brj-23187	12	1	additionally	additionally	ADV
brj-23187	12	2	,	,	PUNCT
brj-23187	12	3	it	it	PRON
brj-23187	12	4	offers	offer	VERB
brj-23187	12	5	valuable	valuable	ADJ
brj-23187	12	6	soft	soft	ADJ
brj-23187	12	7	measurements	measurement	NOUN
brj-23187	12	8	to	to	PART
brj-23187	12	9	support	support	VERB
brj-23187	12	10	efficient	efficient	ADJ
brj-23187	12	11	control	control	NOUN
brj-23187	12	12	of	of	ADP
brj-23187	12	13	the	the	DET
brj-23187	12	14	enzymatic	enzymatic	ADJ
brj-23187	12	15	hydrolysis	hydrolysis	NOUN
brj-23187	12	16	process	process	NOUN
brj-23187	12	17	.	.	PUNCT
brj-23187	13	1	doi	doi	NOUN
brj-23187	13	2	:	:	PUNCT
brj-23187	13	3	10.15376	10.15376	NUM
brj-23187	13	4	/	/	SYM
brj-23187	13	5	biores.19.2.3505	biores.19.2.3505	NOUN
brj-23187	13	6	-	-	PUNCT
brj-23187	13	7	3519	3519	NUM
brj-23187	13	8	keywords	keyword	NOUN
brj-23187	13	9	:	:	PUNCT
brj-23187	13	10	grey	grey	ADJ
brj-23187	13	11	relational	relational	ADJ
brj-23187	13	12	analysis	analysis	NOUN
brj-23187	13	13	(	(	PUNCT
brj-23187	13	14	gra	gra	PROPN
brj-23187	13	15	)	)	PUNCT
brj-23187	13	16	;	;	PUNCT
brj-23187	13	17	kernel	kernel	PROPN
brj-23187	13	18	principal	principal	PROPN
brj-23187	13	19	component	component	NOUN
brj-23187	13	20	analysis	analysis	NOUN
brj-23187	13	21	(	(	PUNCT
brj-23187	13	22	kpca	kpca	PROPN
brj-23187	13	23	)	)	PUNCT
brj-23187	13	24	;	;	PUNCT
brj-23187	13	25	least	least	ADJ
brj-23187	13	26	squares	square	NOUN
brj-23187	13	27	support	support	VERB
brj-23187	13	28	vector	vector	NOUN
brj-23187	13	29	machine	machine	NOUN
brj-23187	13	30	(	(	PUNCT
brj-23187	13	31	lssvm	lssvm	PROPN
brj-23187	13	32	)	)	PUNCT
brj-23187	13	33	;	;	PUNCT
brj-23187	13	34	enzymatic	enzymatic	ADJ
brj-23187	13	35	hydrolysis	hydrolysis	NOUN
brj-23187	13	36	of	of	ADP
brj-23187	13	37	crop	crop	NOUN
brj-23187	13	38	straw	straw	NOUN
brj-23187	13	39	;	;	PUNCT
brj-23187	13	40	lignin	lignin	NOUN
brj-23187	13	41	removal	removal	NOUN
brj-23187	13	42	;	;	PUNCT
brj-23187	13	43	hemicellulose	hemicellulose	NOUN
brj-23187	13	44	removal	removal	NOUN
brj-23187	13	45	contact	contact	NOUN
brj-23187	13	46	information	information	NOUN
brj-23187	13	47	:	:	PUNCT
brj-23187	13	48	a	a	X
brj-23187	13	49	:	:	PUNCT
brj-23187	13	50	college	college	NOUN
brj-23187	13	51	of	of	ADP
brj-23187	13	52	environmental	environmental	ADJ
brj-23187	13	53	science	science	NOUN
brj-23187	13	54	and	and	CCONJ
brj-23187	13	55	engineering	engineering	NOUN
brj-23187	13	56	,	,	PUNCT
brj-23187	13	57	qilu	qilu	NOUN
brj-23187	13	58	university	university	PROPN
brj-23187	13	59	of	of	ADP
brj-23187	13	60	technology	technology	NOUN
brj-23187	13	61	(	(	PUNCT
brj-23187	13	62	shandong	shandong	PROPN
brj-23187	13	63	academy	academy	PROPN
brj-23187	13	64	of	of	ADP
brj-23187	13	65	science	science	PROPN
brj-23187	13	66	)	)	PUNCT
brj-23187	13	67	,	,	PUNCT
brj-23187	13	68	jinan	jinan	PROPN
brj-23187	13	69	250353	250353	NUM
brj-23187	13	70	,	,	PUNCT
brj-23187	13	71	p.	p.	PROPN
brj-23187	13	72	r.	r.	PROPN
brj-23187	13	73	china	china	PROPN
brj-23187	13	74	;	;	PUNCT
brj-23187	13	75	b	b	X
brj-23187	13	76	:	:	PUNCT
brj-23187	13	77	faculty	faculty	NOUN
brj-23187	13	78	of	of	ADP
brj-23187	13	79	light	light	ADJ
brj-23187	13	80	industry	industry	NOUN
brj-23187	13	81	,	,	PUNCT
brj-23187	13	82	qilu	qilu	VERB
brj-23187	13	83	university	university	PROPN
brj-23187	13	84	of	of	ADP
brj-23187	13	85	technology	technology	NOUN
brj-23187	13	86	(	(	PUNCT
brj-23187	13	87	shandong	shandong	PROPN
brj-23187	13	88	academy	academy	PROPN
brj-23187	13	89	of	of	ADP
brj-23187	13	90	science	science	PROPN
brj-23187	13	91	)	)	PUNCT
brj-23187	13	92	,	,	PUNCT
brj-23187	13	93	jinan	jinan	PROPN
brj-23187	13	94	250353	250353	NUM
brj-23187	13	95	,	,	PUNCT
brj-23187	13	96	p.	p.	PROPN
brj-23187	13	97	r.	r.	PROPN
brj-23187	13	98	china	china	PROPN
brj-23187	13	99	;	;	PUNCT
brj-23187	13	100	c	c	X
brj-23187	13	101	:	:	PUNCT
brj-23187	13	102	agricultural	agricultural	ADJ
brj-23187	13	103	technology	technology	NOUN
brj-23187	13	104	promotion	promotion	NOUN
brj-23187	13	105	center	center	NOUN
brj-23187	13	106	in	in	ADP
brj-23187	13	107	yongqiao	yongqiao	PROPN
brj-23187	13	108	district	district	PROPN
brj-23187	13	109	,	,	PUNCT
brj-23187	13	110	suzhou	suzhou	PROPN
brj-23187	13	111	,	,	PUNCT
brj-23187	13	112	234000	234000	NUM
brj-23187	13	113	,	,	PUNCT
brj-23187	13	114	p.	p.	PROPN
brj-23187	13	115	r.	r.	PROPN
brj-23187	13	116	china	china	PROPN
brj-23187	13	117	;	;	PUNCT
brj-23187	13	118	1	1	NUM
brj-23187	13	119	these	these	DET
brj-23187	13	120	authors	author	NOUN
brj-23187	13	121	contributed	contribute	VERB
brj-23187	13	122	equally	equally	ADV
brj-23187	13	123	to	to	ADP
brj-23187	13	124	this	this	DET
brj-23187	13	125	work	work	NOUN
brj-23187	13	126	;	;	PUNCT
brj-23187	13	127	*	*	PUNCT
brj-23187	13	128	corresponding	correspond	VERB
brj-23187	13	129	authors	author	NOUN
brj-23187	13	130	:	:	PUNCT
brj-23187	13	131	lyh@qlu.edu.cn	lyh@qlu.edu.cn	PROPN
brj-23187	13	132	(	(	PUNCT
brj-23187	13	133	y.	y.	PROPN
brj-23187	13	134	luo	luo	PROPN
brj-23187	13	135	)	)	PUNCT
brj-23187	13	136	;	;	PUNCT
brj-23187	13	137	zlh@qlu.edu.cn	zlh@qlu.edu.cn	PROPN
brj-23187	13	138	(	(	PUNCT
brj-23187	13	139	l.	l.	PROPN
brj-23187	13	140	zang	zang	PROPN
brj-23187	13	141	)	)	PUNCT
brj-23187	13	142	introduction	introduction	NOUN
brj-23187	13	143	the	the	DET
brj-23187	13	144	pretreatment	pretreatment	NOUN
brj-23187	13	145	and	and	CCONJ
brj-23187	13	146	utilization	utilization	NOUN
brj-23187	13	147	of	of	ADP
brj-23187	13	148	agricultural	agricultural	ADJ
brj-23187	13	149	waste	waste	NOUN
brj-23187	13	150	have	have	AUX
brj-23187	13	151	garnered	garner	VERB
brj-23187	13	152	increasing	increase	VERB
brj-23187	13	153	attention	attention	NOUN
brj-23187	13	154	in	in	ADP
brj-23187	13	155	the	the	DET
brj-23187	13	156	evolving	evolve	VERB
brj-23187	13	157	landscape	landscape	NOUN
brj-23187	13	158	of	of	ADP
brj-23187	13	159	environmental	environmental	ADJ
brj-23187	13	160	conservation	conservation	NOUN
brj-23187	13	161	and	and	CCONJ
brj-23187	13	162	sustainable	sustainable	ADJ
brj-23187	13	163	development	development	NOUN
brj-23187	13	164	.	.	PUNCT
brj-23187	14	1	the	the	DET
brj-23187	14	2	academic	academic	ADJ
brj-23187	14	3	community	community	NOUN
brj-23187	14	4	widely	widely	ADV
brj-23187	14	5	acknowledges	acknowledge	VERB
brj-23187	14	6	using	use	VERB
brj-23187	14	7	straw	straw	NOUN
brj-23187	14	8	as	as	ADP
brj-23187	14	9	a	a	DET
brj-23187	14	10	common	common	ADJ
brj-23187	14	11	agricultural	agricultural	ADJ
brj-23187	14	12	byproduct	byproduct	NOUN
brj-23187	14	13	(	(	PUNCT
brj-23187	14	14	saravanan	saravanan	PROPN
brj-23187	14	15	et	et	PROPN
brj-23187	14	16	al	al	PROPN
brj-23187	14	17	.	.	PROPN
brj-23187	14	18	2021	2021	NUM
brj-23187	14	19	)	)	PUNCT
brj-23187	14	20	.	.	PUNCT
brj-23187	15	1	when	when	SCONJ
brj-23187	15	2	straw	straw	NOUN
brj-23187	15	3	is	be	AUX
brj-23187	15	4	mishandled	mishandle	VERB
brj-23187	15	5	,	,	PUNCT
brj-23187	15	6	it	it	PRON
brj-23187	15	7	can	can	AUX
brj-23187	15	8	pose	pose	VERB
brj-23187	15	9	significant	significant	ADJ
brj-23187	15	10	environmental	environmental	ADJ
brj-23187	15	11	threats	threat	NOUN
brj-23187	15	12	,	,	PUNCT
brj-23187	15	13	such	such	ADJ
brj-23187	15	14	as	as	ADP
brj-23187	15	15	air	air	NOUN
brj-23187	15	16	pollution	pollution	NOUN
brj-23187	15	17	,	,	PUNCT
brj-23187	15	18	soil	soil	NOUN
brj-23187	15	19	acidification	acidification	NOUN
brj-23187	15	20	,	,	PUNCT
brj-23187	15	21	and	and	CCONJ
brj-23187	15	22	increased	increase	VERB
brj-23187	15	23	greenhouse	greenhouse	NOUN
brj-23187	15	24	gas	gas	NOUN
brj-23187	15	25	emissions	emission	NOUN
brj-23187	15	26	resulting	result	VERB
brj-23187	15	27	from	from	ADP
brj-23187	15	28	open	open	ADJ
brj-23187	15	29	burning	burning	NOUN
brj-23187	15	30	(	(	PUNCT
brj-23187	15	31	usmani	usmani	PROPN
brj-23187	15	32	et	et	PROPN
brj-23187	15	33	al	al	PROPN
brj-23187	15	34	.	.	PROPN
brj-23187	15	35	2021	2021	NUM
brj-23187	15	36	)	)	PUNCT
brj-23187	15	37	.	.	PUNCT
brj-23187	16	1	in	in	ADP
brj-23187	16	2	contrast	contrast	NOUN
brj-23187	16	3	,	,	PUNCT
brj-23187	16	4	crop	crop	NOUN
brj-23187	16	5	straw	straw	NOUN
brj-23187	16	6	is	be	AUX
brj-23187	16	7	rich	rich	ADJ
brj-23187	16	8	in	in	ADP
brj-23187	16	9	lignin	lignin	PROPN
brj-23187	16	10	,	,	PUNCT
brj-23187	16	11	hemicellulose	hemicellulose	NOUN
brj-23187	16	12	,	,	PUNCT
brj-23187	16	13	and	and	CCONJ
brj-23187	16	14	other	other	ADJ
brj-23187	16	15	valuable	valuable	ADJ
brj-23187	16	16	biomass	biomass	NOUN
brj-23187	16	17	components	component	NOUN
brj-23187	16	18	.	.	PUNCT
brj-23187	17	1	these	these	DET
brj-23187	17	2	components	component	NOUN
brj-23187	17	3	can	can	AUX
brj-23187	17	4	be	be	AUX
brj-23187	17	5	harnessed	harness	VERB
brj-23187	17	6	for	for	ADP
brj-23187	17	7	bioenergy	bioenergy	NOUN
brj-23187	17	8	or	or	CCONJ
brj-23187	17	9	bio	bio	NOUN
brj-23187	17	10	-	-	PUNCT
brj-23187	17	11	based	base	VERB
brj-23187	17	12	material	material	NOUN
brj-23187	17	13	production	production	NOUN
brj-23187	17	14	upon	upon	SCONJ
brj-23187	17	15	biodegradation	biodegradation	NOUN
brj-23187	17	16	,	,	PUNCT
brj-23187	17	17	offering	offer	VERB
brj-23187	17	18	economic	economic	ADJ
brj-23187	17	19	benefits	benefit	NOUN
brj-23187	17	20	.	.	PUNCT
brj-23187	18	1	thus	thus	ADV
brj-23187	18	2	,	,	PUNCT
brj-23187	18	3	effective	effective	ADJ
brj-23187	18	4	biodegradation	biodegradation	NOUN
brj-23187	18	5	and	and	CCONJ
brj-23187	18	6	harnessing	harnessing	NOUN
brj-23187	18	7	of	of	ADP
brj-23187	18	8	crop	crop	NOUN
brj-23187	18	9	straw	straw	NOUN
brj-23187	18	10	are	be	AUX
brj-23187	18	11	crucial	crucial	ADJ
brj-23187	18	12	for	for	ADP
brj-23187	18	13	advancing	advance	VERB
brj-23187	18	14	sustainable	sustainable	ADJ
brj-23187	18	15	agricultural	agricultural	ADJ
brj-23187	18	16	practices	practice	NOUN
brj-23187	18	17	and	and	CCONJ
brj-23187	18	18	ensuring	ensure	VERB
brj-23187	18	19	environmental	environmental	ADJ
brj-23187	18	20	protection	protection	NOUN
brj-23187	18	21	(	(	PUNCT
brj-23187	18	22	zhao	zhao	PROPN
brj-23187	18	23	et	et	PROPN
brj-23187	18	24	al	al	PROPN
brj-23187	18	25	.	.	PROPN
brj-23187	18	26	2021	2021	NUM
brj-23187	18	27	)	)	PUNCT
brj-23187	18	28	.	.	PUNCT
brj-23187	19	1	peer	peer	NOUN
brj-23187	19	2	-	-	PUNCT
brj-23187	19	3	reviewed	review	VERB
brj-23187	19	4	article	article	NOUN
brj-23187	19	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	19	6	fu	fu	PROPN
brj-23187	19	7	et	et	PROPN
brj-23187	19	8	al	al	PROPN
brj-23187	19	9	.	.	PROPN
brj-23187	20	1	(	(	PUNCT
brj-23187	20	2	2024	2024	NUM
brj-23187	20	3	)	)	PUNCT
brj-23187	20	4	.	.	PUNCT
brj-23187	21	1	“	"	PUNCT
brj-23187	21	2	predicting	predict	VERB
brj-23187	21	3	enzymatic	enzymatic	ADJ
brj-23187	21	4	hydrolysis	hydrolysis	NOUN
brj-23187	21	5	,	,	PUNCT
brj-23187	21	6	”	"	PUNCT
brj-23187	21	7	bioresources	bioresource	NOUN
brj-23187	21	8	19(2	19(2	NUM
brj-23187	21	9	)	)	PUNCT
brj-23187	21	10	,	,	PUNCT
brj-23187	21	11	3505	3505	NUM
brj-23187	21	12	-	-	SYM
brj-23187	21	13	3519	3519	NUM
brj-23187	21	14	.	.	PUNCT
brj-23187	22	1	3506	3506	NUM
brj-23187	22	2	various	various	ADJ
brj-23187	22	3	techniques	technique	NOUN
brj-23187	22	4	have	have	AUX
brj-23187	22	5	been	be	AUX
brj-23187	22	6	employed	employ	VERB
brj-23187	22	7	to	to	PART
brj-23187	22	8	degrade	degrade	VERB
brj-23187	22	9	crop	crop	NOUN
brj-23187	22	10	straw	straw	NOUN
brj-23187	22	11	,	,	PUNCT
brj-23187	22	12	of	of	ADP
brj-23187	22	13	which	which	PRON
brj-23187	22	14	enzymatic	enzymatic	ADJ
brj-23187	22	15	hydrolysis	hydrolysis	NOUN
brj-23187	22	16	is	be	AUX
brj-23187	22	17	the	the	DET
brj-23187	22	18	most	most	ADV
brj-23187	22	19	prominent	prominent	ADJ
brj-23187	22	20	.	.	PUNCT
brj-23187	23	1	this	this	DET
brj-23187	23	2	process	process	NOUN
brj-23187	23	3	uses	use	VERB
brj-23187	23	4	cellulose	cellulose	NOUN
brj-23187	23	5	and	and	CCONJ
brj-23187	23	6	a	a	DET
brj-23187	23	7	mixture	mixture	NOUN
brj-23187	23	8	of	of	ADP
brj-23187	23	9	enzymes	enzyme	NOUN
brj-23187	23	10	to	to	PART
brj-23187	23	11	facilitate	facilitate	VERB
brj-23187	23	12	the	the	DET
brj-23187	23	13	breakdown	breakdown	NOUN
brj-23187	23	14	of	of	ADP
brj-23187	23	15	polymeric	polymeric	ADJ
brj-23187	23	16	structures	structure	NOUN
brj-23187	23	17	into	into	ADP
brj-23187	23	18	smaller	small	ADJ
brj-23187	23	19	molecular	molecular	ADJ
brj-23187	23	20	entities	entity	NOUN
brj-23187	23	21	,	,	PUNCT
brj-23187	23	22	focusing	focus	VERB
brj-23187	23	23	on	on	ADP
brj-23187	23	24	lignin	lignin	NOUN
brj-23187	23	25	and	and	CCONJ
brj-23187	23	26	hemicellulose	hemicellulose	NOUN
brj-23187	23	27	in	in	ADP
brj-23187	23	28	the	the	DET
brj-23187	23	29	straw	straw	NOUN
brj-23187	23	30	under	under	ADP
brj-23187	23	31	optimal	optimal	ADJ
brj-23187	23	32	temperature	temperature	NOUN
brj-23187	23	33	and	and	CCONJ
brj-23187	23	34	ph	ph	NOUN
brj-23187	23	35	conditions	condition	NOUN
brj-23187	23	36	(	(	PUNCT
brj-23187	23	37	nguyen	nguyen	NOUN
brj-23187	23	38	et	et	PROPN
brj-23187	23	39	al	al	PROPN
brj-23187	23	40	.	.	PROPN
brj-23187	23	41	2020	2020	NUM
brj-23187	23	42	)	)	PUNCT
brj-23187	23	43	.	.	PUNCT
brj-23187	24	1	however	however	ADV
brj-23187	24	2	,	,	PUNCT
brj-23187	24	3	the	the	DET
brj-23187	24	4	removal	removal	NOUN
brj-23187	24	5	efficiencies	efficiency	NOUN
brj-23187	24	6	of	of	ADP
brj-23187	24	7	lignin	lignin	NOUN
brj-23187	24	8	and	and	CCONJ
brj-23187	24	9	hemicellulose	hemicellulose	NOUN
brj-23187	24	10	during	during	ADP
brj-23187	24	11	the	the	DET
brj-23187	24	12	enzymatic	enzymatic	ADJ
brj-23187	24	13	hydrolysis	hydrolysis	NOUN
brj-23187	24	14	of	of	ADP
brj-23187	24	15	straw	straw	NOUN
brj-23187	24	16	are	be	AUX
brj-23187	24	17	influenced	influence	VERB
brj-23187	24	18	by	by	ADP
brj-23187	24	19	multiple	multiple	ADJ
brj-23187	24	20	factors	factor	NOUN
brj-23187	24	21	,	,	PUNCT
brj-23187	24	22	leading	lead	VERB
brj-23187	24	23	to	to	ADP
brj-23187	24	24	intricate	intricate	ADJ
brj-23187	24	25	impacts	impact	NOUN
brj-23187	24	26	on	on	ADP
brj-23187	24	27	the	the	DET
brj-23187	24	28	extent	extent	NOUN
brj-23187	24	29	of	of	ADP
brj-23187	24	30	removal	removal	NOUN
brj-23187	24	31	.	.	PUNCT
brj-23187	25	1	previous	previous	ADJ
brj-23187	25	2	studies	study	NOUN
brj-23187	25	3	have	have	AUX
brj-23187	25	4	highlighted	highlight	VERB
brj-23187	25	5	that	that	SCONJ
brj-23187	25	6	pretreatment	pretreatment	NOUN
brj-23187	25	7	with	with	ADP
brj-23187	25	8	potassium	potassium	NOUN
brj-23187	25	9	ferrate	ferrate	NOUN
brj-23187	25	10	solution	solution	NOUN
brj-23187	25	11	augments	augment	VERB
brj-23187	25	12	the	the	DET
brj-23187	25	13	efficiency	efficiency	NOUN
brj-23187	25	14	of	of	ADP
brj-23187	25	15	the	the	DET
brj-23187	25	16	enzymatic	enzymatic	ADJ
brj-23187	25	17	hydrolysis	hydrolysis	NOUN
brj-23187	25	18	of	of	ADP
brj-23187	25	19	corn	corn	NOUN
brj-23187	25	20	straw	straw	NOUN
brj-23187	25	21	.	.	PUNCT
brj-23187	26	1	however	however	ADV
brj-23187	26	2	,	,	PUNCT
brj-23187	26	3	comprehensive	comprehensive	ADJ
brj-23187	26	4	studies	study	NOUN
brj-23187	26	5	employing	employ	VERB
brj-23187	26	6	effective	effective	ADJ
brj-23187	26	7	mathematical	mathematical	ADJ
brj-23187	26	8	models	model	NOUN
brj-23187	26	9	that	that	PRON
brj-23187	26	10	quantitatively	quantitatively	ADV
brj-23187	26	11	elucidate	elucidate	VERB
brj-23187	26	12	the	the	DET
brj-23187	26	13	relationship	relationship	NOUN
brj-23187	26	14	between	between	ADP
brj-23187	26	15	these	these	DET
brj-23187	26	16	determinants	determinant	NOUN
brj-23187	26	17	and	and	CCONJ
brj-23187	26	18	hydrolytic	hydrolytic	ADJ
brj-23187	26	19	outcomes	outcome	NOUN
brj-23187	26	20	are	be	AUX
brj-23187	26	21	scarce	scarce	ADJ
brj-23187	26	22	.	.	PUNCT
brj-23187	27	1	the	the	DET
brj-23187	27	2	literature	literature	NOUN
brj-23187	27	3	points	point	VERB
brj-23187	27	4	out	out	ADP
brj-23187	27	5	that	that	SCONJ
brj-23187	27	6	the	the	DET
brj-23187	27	7	utilisation	utilisation	NOUN
brj-23187	27	8	of	of	ADP
brj-23187	27	9	potassium	potassium	NOUN
brj-23187	27	10	ferrate	ferrate	NOUN
brj-23187	27	11	composite	composite	ADJ
brj-23187	27	12	solution	solution	NOUN
brj-23187	27	13	as	as	ADP
brj-23187	27	14	a	a	DET
brj-23187	27	15	pretreatment	pretreatment	NOUN
brj-23187	27	16	method	method	NOUN
brj-23187	27	17	boosts	boost	VERB
brj-23187	27	18	the	the	DET
brj-23187	27	19	enzymatic	enzymatic	ADJ
brj-23187	27	20	hydrolysis	hydrolysis	NOUN
brj-23187	27	21	efficiency	efficiency	NOUN
brj-23187	27	22	of	of	ADP
brj-23187	27	23	corn	corn	NOUN
brj-23187	27	24	straw	straw	NOUN
brj-23187	27	25	(	(	PUNCT
brj-23187	27	26	tian	tian	PROPN
brj-23187	27	27	et	et	PROPN
brj-23187	27	28	al	al	PROPN
brj-23187	27	29	.	.	PROPN
brj-23187	27	30	2023	2023	NUM
brj-23187	27	31	)	)	PUNCT
brj-23187	27	32	.	.	PUNCT
brj-23187	28	1	implications	implication	NOUN
brj-23187	28	2	of	of	ADP
brj-23187	28	3	diverse	diverse	ADJ
brj-23187	28	4	naoh	naoh	NOUN
brj-23187	28	5	-	-	PUNCT
brj-23187	28	6	ball	ball	NOUN
brj-23187	28	7	milling	mill	VERB
brj-23187	28	8	composite	composite	ADJ
brj-23187	28	9	pretreatments	pretreatment	NOUN
brj-23187	28	10	have	have	AUX
brj-23187	28	11	been	be	AUX
brj-23187	28	12	reported	report	VERB
brj-23187	28	13	(	(	PUNCT
brj-23187	28	14	yang	yang	PROPN
brj-23187	28	15	et	et	PROPN
brj-23187	28	16	al	al	PROPN
brj-23187	28	17	.	.	PROPN
brj-23187	28	18	2022	2022	NUM
brj-23187	28	19	)	)	PUNCT
brj-23187	28	20	.	.	PUNCT
brj-23187	29	1	this	this	DET
brj-23187	29	2	study	study	NOUN
brj-23187	29	3	examines	examine	VERB
brj-23187	29	4	the	the	DET
brj-23187	29	5	effects	effect	NOUN
brj-23187	29	6	of	of	ADP
brj-23187	29	7	various	various	ADJ
brj-23187	29	8	pretreatment	pretreatment	NOUN
brj-23187	29	9	methods	method	NOUN
brj-23187	29	10	on	on	ADP
brj-23187	29	11	the	the	DET
brj-23187	29	12	efficacy	efficacy	NOUN
brj-23187	29	13	of	of	ADP
brj-23187	29	14	straw	straw	NOUN
brj-23187	29	15	enzymatic	enzymatic	ADJ
brj-23187	29	16	hydrolysis	hydrolysis	NOUN
brj-23187	29	17	by	by	ADP
brj-23187	29	18	applying	apply	VERB
brj-23187	29	19	mathematical	mathematical	ADJ
brj-23187	29	20	models	model	NOUN
brj-23187	29	21	to	to	PART
brj-23187	29	22	clarify	clarify	VERB
brj-23187	29	23	the	the	DET
brj-23187	29	24	connection	connection	NOUN
brj-23187	29	25	between	between	ADP
brj-23187	29	26	these	these	DET
brj-23187	29	27	influencing	influence	VERB
brj-23187	29	28	factors	factor	NOUN
brj-23187	29	29	and	and	CCONJ
brj-23187	29	30	enzymatic	enzymatic	ADJ
brj-23187	29	31	hydrolysis	hydrolysis	NOUN
brj-23187	29	32	efficiency	efficiency	NOUN
brj-23187	29	33	(	(	PUNCT
brj-23187	29	34	kumar	kumar	PROPN
brj-23187	29	35	et	et	PROPN
brj-23187	29	36	al	al	PROPN
brj-23187	29	37	.	.	PROPN
brj-23187	29	38	2022	2022	NUM
brj-23187	29	39	)	)	PUNCT
brj-23187	29	40	.	.	PUNCT
brj-23187	30	1	considering	consider	VERB
brj-23187	30	2	the	the	DET
brj-23187	30	3	challenges	challenge	NOUN
brj-23187	30	4	mentioned	mention	VERB
brj-23187	30	5	above	above	ADV
brj-23187	30	6	,	,	PUNCT
brj-23187	30	7	this	this	DET
brj-23187	30	8	study	study	NOUN
brj-23187	30	9	proposes	propose	VERB
brj-23187	30	10	a	a	DET
brj-23187	30	11	novel	novel	ADJ
brj-23187	30	12	approach	approach	NOUN
brj-23187	30	13	for	for	ADP
brj-23187	30	14	predicting	predict	VERB
brj-23187	30	15	the	the	DET
brj-23187	30	16	enzymatic	enzymatic	ADJ
brj-23187	30	17	hydrolysis	hydrolysis	NOUN
brj-23187	30	18	efficiency	efficiency	NOUN
brj-23187	30	19	of	of	ADP
brj-23187	30	20	crop	crop	NOUN
brj-23187	30	21	straw	straw	NOUN
brj-23187	30	22	by	by	ADP
brj-23187	30	23	combining	combine	VERB
brj-23187	30	24	grey	grey	ADJ
brj-23187	30	25	relational	relational	ADJ
brj-23187	30	26	analysis	analysis	NOUN
brj-23187	30	27	(	(	PUNCT
brj-23187	30	28	gra	gra	PROPN
brj-23187	30	29	)	)	PUNCT
brj-23187	30	30	,	,	PUNCT
brj-23187	30	31	kernel	kernel	PROPN
brj-23187	30	32	principal	principal	PROPN
brj-23187	30	33	component	component	NOUN
brj-23187	30	34	analysis	analysis	NOUN
brj-23187	30	35	(	(	PUNCT
brj-23187	30	36	kpca	kpca	NOUN
brj-23187	30	37	)	)	PUNCT
brj-23187	30	38	,	,	PUNCT
brj-23187	30	39	and	and	CCONJ
brj-23187	30	40	least	least	ADJ
brj-23187	30	41	-	-	PUNCT
brj-23187	30	42	squares	square	NOUN
brj-23187	30	43	support	support	NOUN
brj-23187	30	44	vector	vector	NOUN
brj-23187	30	45	machine	machine	NOUN
brj-23187	30	46	(	(	PUNCT
brj-23187	30	47	lssvm	lssvm	PROPN
brj-23187	30	48	)	)	PUNCT
brj-23187	30	49	(	(	PUNCT
brj-23187	30	50	adnana	adnana	PROPN
brj-23187	30	51	et	et	PROPN
brj-23187	30	52	al	al	PROPN
brj-23187	30	53	.	.	PROPN
brj-23187	30	54	2019	2019	NUM
brj-23187	30	55	)	)	PUNCT
brj-23187	30	56	.	.	PUNCT
brj-23187	31	1	the	the	DET
brj-23187	31	2	proposed	propose	VERB
brj-23187	31	3	method	method	NOUN
brj-23187	31	4	utilises	utilise	NOUN
brj-23187	31	5	gra	gra	VERB
brj-23187	31	6	to	to	PART
brj-23187	31	7	gauge	gauge	VERB
brj-23187	31	8	the	the	DET
brj-23187	31	9	impact	impact	NOUN
brj-23187	31	10	of	of	ADP
brj-23187	31	11	influencing	influence	VERB
brj-23187	31	12	factors	factor	NOUN
brj-23187	31	13	on	on	ADP
brj-23187	31	14	enzymatic	enzymatic	ADJ
brj-23187	31	15	hydrolysis	hydrolysis	NOUN
brj-23187	31	16	efficiency	efficiency	NOUN
brj-23187	31	17	.	.	PUNCT
brj-23187	32	1	additionally	additionally	ADV
brj-23187	32	2	,	,	PUNCT
brj-23187	32	3	it	it	PRON
brj-23187	32	4	identifies	identify	VERB
brj-23187	32	5	pivotal	pivotal	ADJ
brj-23187	32	6	factors	factor	NOUN
brj-23187	32	7	,	,	PUNCT
brj-23187	32	8	harnesses	harness	NOUN
brj-23187	32	9	kpca	kpca	NOUN
brj-23187	32	10	for	for	ADP
brj-23187	32	11	feature	feature	NOUN
brj-23187	32	12	extraction	extraction	NOUN
brj-23187	32	13	,	,	PUNCT
brj-23187	32	14	and	and	CCONJ
brj-23187	32	15	employs	employ	VERB
brj-23187	32	16	lssvm	lssvm	NOUN
brj-23187	32	17	to	to	PART
brj-23187	32	18	craft	craft	VERB
brj-23187	32	19	a	a	DET
brj-23187	32	20	predictive	predictive	ADJ
brj-23187	32	21	model	model	NOUN
brj-23187	32	22	for	for	ADP
brj-23187	32	23	the	the	DET
brj-23187	32	24	extents	extent	NOUN
brj-23187	32	25	of	of	ADP
brj-23187	32	26	lignin	lignin	NOUN
brj-23187	32	27	and	and	CCONJ
brj-23187	32	28	hemicellulose	hemicellulose	NOUN
brj-23187	32	29	removal	removal	NOUN
brj-23187	32	30	,	,	PUNCT
brj-23187	32	31	prioritising	prioritise	VERB
brj-23187	32	32	efficiency	efficiency	NOUN
brj-23187	32	33	,	,	PUNCT
brj-23187	32	34	and	and	CCONJ
brj-23187	32	35	precision	precision	NOUN
brj-23187	32	36	.	.	PUNCT
brj-23187	33	1	this	this	DET
brj-23187	33	2	methodology	methodology	NOUN
brj-23187	33	3	lays	lay	VERB
brj-23187	33	4	the	the	DET
brj-23187	33	5	groundwork	groundwork	NOUN
brj-23187	33	6	for	for	ADP
brj-23187	33	7	refining	refine	VERB
brj-23187	33	8	enzymatic	enzymatic	ADJ
brj-23187	33	9	hydrolysis	hydrolysis	NOUN
brj-23187	33	10	production	production	NOUN
brj-23187	33	11	in	in	ADP
brj-23187	33	12	crops	crop	NOUN
brj-23187	33	13	and	and	CCONJ
brj-23187	33	14	provides	provide	VERB
brj-23187	33	15	a	a	DET
brj-23187	33	16	sophisticated	sophisticated	ADJ
brj-23187	33	17	softmeasurement	softmeasurement	NOUN
brj-23187	33	18	tool	tool	NOUN
brj-23187	33	19	for	for	ADP
brj-23187	33	20	effectively	effectively	ADV
brj-23187	33	21	controlling	control	VERB
brj-23187	33	22	the	the	DET
brj-23187	33	23	enzymatic	enzymatic	ADJ
brj-23187	33	24	hydrolysis	hydrolysis	NOUN
brj-23187	33	25	process	process	NOUN
brj-23187	33	26	(	(	PUNCT
brj-23187	33	27	agrawal	agrawal	NOUN
brj-23187	33	28	et	et	PROPN
brj-23187	33	29	al	al	PROPN
brj-23187	33	30	.	.	PROPN
brj-23187	33	31	2021	2021	NUM
brj-23187	33	32	)	)	PUNCT
brj-23187	33	33	.	.	PUNCT
brj-23187	34	1	background	background	NOUN
brj-23187	34	2	the	the	DET
brj-23187	34	3	procedure	procedure	NOUN
brj-23187	34	4	for	for	ADP
brj-23187	34	5	crop	crop	NOUN
brj-23187	34	6	straw	straw	NOUN
brj-23187	34	7	enzymatic	enzymatic	ADJ
brj-23187	34	8	hydrolysis	hydrolysis	NOUN
brj-23187	34	9	can	can	AUX
brj-23187	34	10	typically	typically	ADV
brj-23187	34	11	be	be	AUX
brj-23187	34	12	divided	divide	VERB
brj-23187	34	13	into	into	ADP
brj-23187	34	14	three	three	NUM
brj-23187	34	15	stages	stage	NOUN
brj-23187	34	16	:	:	PUNCT
brj-23187	34	17	straw	straw	NOUN
brj-23187	34	18	pretreatment	pretreatment	NOUN
brj-23187	34	19	,	,	PUNCT
brj-23187	34	20	three	three	NUM
brj-23187	34	21	-	-	PUNCT
brj-23187	34	22	stage	stage	NOUN
brj-23187	34	23	enzymatic	enzymatic	ADJ
brj-23187	34	24	hydrolysis	hydrolysis	NOUN
brj-23187	34	25	,	,	PUNCT
brj-23187	34	26	and	and	CCONJ
brj-23187	34	27	solid	solid	ADJ
brj-23187	34	28	-	-	PUNCT
brj-23187	34	29	liquid	liquid	ADJ
brj-23187	34	30	separation	separation	NOUN
brj-23187	34	31	.	.	PUNCT
brj-23187	35	1	this	this	PRON
brj-23187	35	2	is	be	AUX
brj-23187	35	3	illustrated	illustrate	VERB
brj-23187	35	4	in	in	ADP
brj-23187	35	5	fig	fig	NOUN
brj-23187	35	6	.	.	PUNCT
brj-23187	36	1	1	1	X
brj-23187	36	2	.	.	X
brj-23187	36	3	the	the	DET
brj-23187	36	4	harvested	harvest	VERB
brj-23187	36	5	biomass	biomass	NOUN
brj-23187	36	6	was	be	AUX
brj-23187	36	7	thoroughly	thoroughly	ADV
brj-23187	36	8	washed	wash	VERB
brj-23187	36	9	during	during	ADP
brj-23187	36	10	the	the	DET
brj-23187	36	11	straw	straw	NOUN
brj-23187	36	12	pretreatment	pretreatment	NOUN
brj-23187	36	13	's	's	PART
brj-23187	36	14	initial	initial	ADJ
brj-23187	36	15	phase	phase	NOUN
brj-23187	36	16	,	,	PUNCT
brj-23187	36	17	followed	follow	VERB
brj-23187	36	18	by	by	ADP
brj-23187	36	19	careful	careful	ADJ
brj-23187	36	20	drying	drying	NOUN
brj-23187	36	21	and	and	CCONJ
brj-23187	36	22	pulverisation	pulverisation	NOUN
brj-23187	36	23	using	use	VERB
brj-23187	36	24	a	a	DET
brj-23187	36	25	specialised	specialised	ADJ
brj-23187	36	26	grinder	grinder	NOUN
brj-23187	36	27	.	.	PUNCT
brj-23187	37	1	subsequently	subsequently	ADV
brj-23187	37	2	,	,	PUNCT
brj-23187	37	3	the	the	DET
brj-23187	37	4	crushed	crushed	ADJ
brj-23187	37	5	straw	straw	NOUN
brj-23187	37	6	was	be	AUX
brj-23187	37	7	transferred	transfer	VERB
brj-23187	37	8	to	to	ADP
brj-23187	37	9	an	an	DET
brj-23187	37	10	enzymatic	enzymatic	ADJ
brj-23187	37	11	hydrolysis	hydrolysis	NOUN
brj-23187	37	12	reaction	reaction	NOUN
brj-23187	37	13	tank	tank	NOUN
brj-23187	37	14	,	,	PUNCT
brj-23187	37	15	where	where	SCONJ
brj-23187	37	16	a	a	DET
brj-23187	37	17	specific	specific	ADJ
brj-23187	37	18	composite	composite	ADJ
brj-23187	37	19	enzyme	enzyme	NOUN
brj-23187	37	20	and	and	CCONJ
brj-23187	37	21	water	water	NOUN
brj-23187	37	22	were	be	AUX
brj-23187	37	23	added	add	VERB
brj-23187	37	24	and	and	CCONJ
brj-23187	37	25	allowed	allow	VERB
brj-23187	37	26	to	to	PART
brj-23187	37	27	stand	stand	VERB
brj-23187	37	28	at	at	ADP
brj-23187	37	29	room	room	NOUN
brj-23187	37	30	temperature	temperature	NOUN
brj-23187	37	31	for	for	ADP
brj-23187	37	32	some	some	DET
brj-23187	37	33	time	time	NOUN
brj-23187	37	34	.	.	PUNCT
brj-23187	38	1	the	the	DET
brj-23187	38	2	second	second	ADJ
brj-23187	38	3	stage	stage	NOUN
brj-23187	38	4	involves	involve	VERB
brj-23187	38	5	a	a	DET
brj-23187	38	6	three	three	NUM
brj-23187	38	7	-	-	PUNCT
brj-23187	38	8	tiered	tiere	VERB
brj-23187	38	9	enzymatic	enzymatic	ADJ
brj-23187	38	10	hydrolysis	hydrolysis	NOUN
brj-23187	38	11	process	process	NOUN
brj-23187	38	12	.	.	PUNCT
brj-23187	39	1	three	three	NUM
brj-23187	39	2	specific	specific	ADJ
brj-23187	39	3	combinations	combination	NOUN
brj-23187	39	4	of	of	ADP
brj-23187	39	5	enzymes	enzyme	NOUN
brj-23187	39	6	and	and	CCONJ
brj-23187	39	7	additives	additive	NOUN
brj-23187	39	8	,	,	PUNCT
brj-23187	39	9	such	such	ADJ
brj-23187	39	10	as	as	ADP
brj-23187	39	11	hydrogen	hydrogen	NOUN
brj-23187	39	12	peroxide	peroxide	NOUN
brj-23187	39	13	,	,	PUNCT
brj-23187	39	14	were	be	AUX
brj-23187	39	15	introduced	introduce	VERB
brj-23187	39	16	into	into	ADP
brj-23187	39	17	the	the	DET
brj-23187	39	18	reaction	reaction	NOUN
brj-23187	39	19	tank	tank	NOUN
brj-23187	39	20	at	at	ADP
brj-23187	39	21	specific	specific	ADJ
brj-23187	39	22	intervals	interval	NOUN
brj-23187	39	23	.	.	PUNCT
brj-23187	40	1	the	the	DET
brj-23187	40	2	conditions	condition	NOUN
brj-23187	40	3	were	be	AUX
brj-23187	40	4	optimised	optimise	VERB
brj-23187	40	5	to	to	PART
brj-23187	40	6	boost	boost	VERB
brj-23187	40	7	the	the	DET
brj-23187	40	8	enzyme	enzyme	NOUN
brj-23187	40	9	activity	activity	NOUN
brj-23187	40	10	and	and	CCONJ
brj-23187	40	11	ensure	ensure	VERB
brj-23187	40	12	efficient	efficient	ADJ
brj-23187	40	13	enzymatic	enzymatic	ADJ
brj-23187	40	14	hydrolysis	hydrolysis	NOUN
brj-23187	40	15	(	(	PUNCT
brj-23187	40	16	huang	huang	PROPN
brj-23187	40	17	et	et	PROPN
brj-23187	40	18	al	al	PROPN
brj-23187	40	19	.	.	PROPN
brj-23187	40	20	2019	2019	NUM
brj-23187	40	21	)	)	PUNCT
brj-23187	40	22	.	.	PUNCT
brj-23187	41	1	the	the	DET
brj-23187	41	2	third	third	ADJ
brj-23187	41	3	stage	stage	NOUN
brj-23187	41	4	centres	centre	NOUN
brj-23187	41	5	on	on	ADP
brj-23187	41	6	solid	solid	ADJ
brj-23187	41	7	-	-	PUNCT
brj-23187	41	8	liquid	liquid	ADJ
brj-23187	41	9	separation	separation	NOUN
brj-23187	41	10	,	,	PUNCT
brj-23187	41	11	a	a	DET
brj-23187	41	12	pivotal	pivotal	ADJ
brj-23187	41	13	process	process	NOUN
brj-23187	41	14	in	in	ADP
brj-23187	41	15	which	which	PRON
brj-23187	41	16	machinery	machinery	NOUN
brj-23187	41	17	or	or	CCONJ
brj-23187	41	18	filtration	filtration	NOUN
brj-23187	41	19	techniques	technique	NOUN
brj-23187	41	20	are	be	AUX
brj-23187	41	21	employed	employ	VERB
brj-23187	41	22	to	to	PART
brj-23187	41	23	distinguish	distinguish	VERB
brj-23187	41	24	and	and	CCONJ
brj-23187	41	25	remove	remove	VERB
brj-23187	41	26	solid	solid	ADJ
brj-23187	41	27	residues	residue	NOUN
brj-23187	41	28	from	from	ADP
brj-23187	41	29	the	the	DET
brj-23187	41	30	liquid	liquid	ADJ
brj-23187	41	31	enzymatic	enzymatic	ADJ
brj-23187	41	32	hydrolysate	hydrolysate	NOUN
brj-23187	41	33	.	.	PUNCT
brj-23187	42	1	this	this	DET
brj-23187	42	2	step	step	NOUN
brj-23187	42	3	ensures	ensure	VERB
brj-23187	42	4	the	the	DET
brj-23187	42	5	purity	purity	NOUN
brj-23187	42	6	of	of	ADP
brj-23187	42	7	the	the	DET
brj-23187	42	8	liquid	liquid	ADJ
brj-23187	42	9	product	product	NOUN
brj-23187	42	10	and	and	CCONJ
brj-23187	42	11	facilitates	facilitate	VERB
brj-23187	42	12	the	the	DET
brj-23187	42	13	subsequent	subsequent	ADJ
brj-23187	42	14	processing	processing	NOUN
brj-23187	42	15	and	and	CCONJ
brj-23187	42	16	analysis	analysis	NOUN
brj-23187	42	17	(	(	PUNCT
brj-23187	42	18	zhu	zhu	X
brj-23187	42	19	et	et	PROPN
brj-23187	42	20	al	al	PROPN
brj-23187	42	21	.	.	PROPN
brj-23187	42	22	2023	2023	NUM
brj-23187	42	23	)	)	PUNCT
brj-23187	42	24	.	.	PUNCT
brj-23187	43	1	peer	peer	NOUN
brj-23187	43	2	-	-	PUNCT
brj-23187	43	3	reviewed	review	VERB
brj-23187	43	4	article	article	NOUN
brj-23187	43	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	43	6	fu	fu	PROPN
brj-23187	43	7	et	et	PROPN
brj-23187	43	8	al	al	PROPN
brj-23187	43	9	.	.	PROPN
brj-23187	44	1	(	(	PUNCT
brj-23187	44	2	2024	2024	NUM
brj-23187	44	3	)	)	PUNCT
brj-23187	44	4	.	.	PUNCT
brj-23187	45	1	“	"	PUNCT
brj-23187	45	2	predicting	predict	VERB
brj-23187	45	3	enzymatic	enzymatic	ADJ
brj-23187	45	4	hydrolysis	hydrolysis	NOUN
brj-23187	45	5	,	,	PUNCT
brj-23187	45	6	”	"	PUNCT
brj-23187	45	7	bioresources	bioresource	NOUN
brj-23187	45	8	19(2	19(2	NUM
brj-23187	45	9	)	)	PUNCT
brj-23187	45	10	,	,	PUNCT
brj-23187	45	11	3505	3505	NUM
brj-23187	45	12	-	-	SYM
brj-23187	45	13	3519	3519	NUM
brj-23187	45	14	.	.	PUNCT
brj-23187	46	1	3507	3507	NUM
brj-23187	46	2	numerous	numerous	ADJ
brj-23187	46	3	factors	factor	NOUN
brj-23187	46	4	influence	influence	VERB
brj-23187	46	5	the	the	DET
brj-23187	46	6	efficiency	efficiency	NOUN
brj-23187	46	7	of	of	ADP
brj-23187	46	8	enzymatic	enzymatic	ADJ
brj-23187	46	9	hydrolysis	hydrolysis	NOUN
brj-23187	46	10	,	,	PUNCT
brj-23187	46	11	including	include	VERB
brj-23187	46	12	straw	straw	NOUN
brj-23187	46	13	length	length	NOUN
brj-23187	46	14	,	,	PUNCT
brj-23187	46	15	reaction	reaction	NOUN
brj-23187	46	16	duration	duration	NOUN
brj-23187	46	17	,	,	PUNCT
brj-23187	46	18	temperature	temperature	NOUN
brj-23187	46	19	,	,	PUNCT
brj-23187	46	20	ph	ph	NOUN
brj-23187	46	21	,	,	PUNCT
brj-23187	46	22	and	and	CCONJ
brj-23187	46	23	other	other	ADJ
brj-23187	46	24	relevant	relevant	ADJ
brj-23187	46	25	variables	variable	NOUN
brj-23187	46	26	.	.	PUNCT
brj-23187	47	1	identifying	identify	VERB
brj-23187	47	2	the	the	DET
brj-23187	47	3	dominant	dominant	ADJ
brj-23187	47	4	factors	factor	NOUN
brj-23187	47	5	and	and	CCONJ
brj-23187	47	6	establishing	establish	VERB
brj-23187	47	7	a	a	DET
brj-23187	47	8	quantitative	quantitative	ADJ
brj-23187	47	9	link	link	NOUN
brj-23187	47	10	between	between	ADP
brj-23187	47	11	them	they	PRON
brj-23187	47	12	and	and	CCONJ
brj-23187	47	13	enzymatic	enzymatic	ADJ
brj-23187	47	14	hydrolysis	hydrolysis	NOUN
brj-23187	47	15	efficiency	efficiency	NOUN
brj-23187	47	16	is	be	AUX
brj-23187	47	17	essential	essential	ADJ
brj-23187	47	18	,	,	PUNCT
brj-23187	47	19	necessitating	necessitate	VERB
brj-23187	47	20	robust	robust	ADJ
brj-23187	47	21	methodologies	methodology	NOUN
brj-23187	47	22	(	(	PUNCT
brj-23187	47	23	guo	guo	PROPN
brj-23187	47	24	et	et	PROPN
brj-23187	47	25	al	al	PROPN
brj-23187	47	26	.	.	PROPN
brj-23187	47	27	2023	2023	NUM
brj-23187	47	28	)	)	PUNCT
brj-23187	47	29	.	.	PUNCT
brj-23187	48	1	fig	fig	NOUN
brj-23187	48	2	.	.	PUNCT
brj-23187	49	1	1	1	X
brj-23187	49	2	.	.	PUNCT
brj-23187	49	3	the	the	DET
brj-23187	49	4	enzymatic	enzymatic	ADJ
brj-23187	49	5	hydrolysis	hydrolysis	NOUN
brj-23187	49	6	process	process	NOUN
brj-23187	49	7	of	of	ADP
brj-23187	49	8	crop	crop	NOUN
brj-23187	49	9	straw	straw	NOUN
brj-23187	49	10	method	method	NOUN
brj-23187	49	11	this	this	DET
brj-23187	49	12	study	study	NOUN
brj-23187	49	13	introduces	introduce	VERB
brj-23187	49	14	a	a	DET
brj-23187	49	15	novel	novel	ADJ
brj-23187	49	16	approach	approach	NOUN
brj-23187	49	17	,	,	PUNCT
brj-23187	49	18	gra	gra	PROPN
brj-23187	49	19	-	-	PUNCT
brj-23187	49	20	kpca	kpca	NOUN
brj-23187	49	21	-	-	PUNCT
brj-23187	49	22	lssvm	lssvm	NOUN
brj-23187	49	23	,	,	PUNCT
brj-23187	49	24	which	which	PRON
brj-23187	49	25	is	be	AUX
brj-23187	49	26	designed	design	VERB
brj-23187	49	27	to	to	PART
brj-23187	49	28	predict	predict	VERB
brj-23187	49	29	the	the	DET
brj-23187	49	30	extents	extent	NOUN
brj-23187	49	31	of	of	ADP
brj-23187	49	32	removal	removal	NOUN
brj-23187	49	33	of	of	ADP
brj-23187	49	34	lignin	lignin	NOUN
brj-23187	49	35	and	and	CCONJ
brj-23187	49	36	hemicellulose	hemicellulose	NOUN
brj-23187	49	37	during	during	ADP
brj-23187	49	38	the	the	DET
brj-23187	49	39	enzymatic	enzymatic	ADJ
brj-23187	49	40	hydrolysis	hydrolysis	NOUN
brj-23187	49	41	of	of	ADP
brj-23187	49	42	crop	crop	NOUN
brj-23187	49	43	straw	straw	NOUN
brj-23187	49	44	,	,	PUNCT
brj-23187	49	45	as	as	SCONJ
brj-23187	49	46	illustrated	illustrate	VERB
brj-23187	49	47	in	in	ADP
brj-23187	49	48	fig	fig	NOUN
brj-23187	49	49	.	.	PUNCT
brj-23187	50	1	2	2	NUM
brj-23187	50	2	.	.	X
brj-23187	50	3	during	during	ADP
brj-23187	50	4	the	the	DET
brj-23187	50	5	offline	offline	ADJ
brj-23187	50	6	training	training	NOUN
brj-23187	50	7	stage	stage	NOUN
brj-23187	50	8	,	,	PUNCT
brj-23187	50	9	the	the	DET
brj-23187	50	10	lssvm	lssvm	NOUN
brj-23187	50	11	model	model	NOUN
brj-23187	50	12	was	be	AUX
brj-23187	50	13	refined	refine	VERB
brj-23187	50	14	using	use	VERB
brj-23187	50	15	both	both	CCONJ
brj-23187	50	16	the	the	DET
brj-23187	50	17	gra	gra	PROPN
brj-23187	50	18	variable	variable	PROPN
brj-23187	50	19	screening	screening	NOUN
brj-23187	50	20	and	and	CCONJ
brj-23187	50	21	kpca	kpca	PROPN
brj-23187	50	22	dimension	dimension	NOUN
brj-23187	50	23	reduction	reduction	NOUN
brj-23187	50	24	techniques	technique	NOUN
brj-23187	50	25	applied	apply	VERB
brj-23187	50	26	to	to	ADP
brj-23187	50	27	the	the	DET
brj-23187	50	28	training	training	NOUN
brj-23187	50	29	set	set	NOUN
brj-23187	50	30	(	(	PUNCT
brj-23187	50	31	xiong	xiong	PROPN
brj-23187	50	32	et	et	PROPN
brj-23187	50	33	al	al	PROPN
brj-23187	50	34	.	.	PROPN
brj-23187	50	35	2018	2018	NUM
brj-23187	50	36	)	)	PUNCT
brj-23187	50	37	.	.	PUNCT
brj-23187	51	1	in	in	ADP
brj-23187	51	2	the	the	DET
brj-23187	51	3	online	online	ADJ
brj-23187	51	4	prediction	prediction	NOUN
brj-23187	51	5	stage	stage	NOUN
brj-23187	51	6	,	,	PUNCT
brj-23187	51	7	the	the	DET
brj-23187	51	8	test	test	NOUN
brj-23187	51	9	data	datum	NOUN
brj-23187	51	10	are	be	AUX
brj-23187	51	11	selected	select	VERB
brj-23187	51	12	based	base	VERB
brj-23187	51	13	on	on	ADP
brj-23187	51	14	the	the	DET
brj-23187	51	15	screening	screening	NOUN
brj-23187	51	16	results	result	NOUN
brj-23187	51	17	and	and	CCONJ
brj-23187	51	18	averaged	average	VERB
brj-23187	51	19	before	before	SCONJ
brj-23187	51	20	their	their	PRON
brj-23187	51	21	dimensions	dimension	NOUN
brj-23187	51	22	are	be	AUX
brj-23187	51	23	reduced	reduce	VERB
brj-23187	51	24	(	(	PUNCT
brj-23187	51	25	adnan	adnan	PROPN
brj-23187	51	26	ikram	ikram	PROPN
brj-23187	51	27	et	et	PROPN
brj-23187	51	28	al	al	PROPN
brj-23187	51	29	.	.	PROPN
brj-23187	51	30	2022	2022	NUM
brj-23187	51	31	)	)	PUNCT
brj-23187	51	32	.	.	PUNCT
brj-23187	52	1	the	the	DET
brj-23187	52	2	well	well	ADV
brj-23187	52	3	-	-	PUNCT
brj-23187	52	4	trained	train	VERB
brj-23187	52	5	lssvm	lssvm	NOUN
brj-23187	52	6	model	model	NOUN
brj-23187	52	7	offers	offer	VERB
brj-23187	52	8	precise	precise	ADJ
brj-23187	52	9	lignin	lignin	NOUN
brj-23187	52	10	and	and	CCONJ
brj-23187	52	11	hemicellulose	hemicellulose	NOUN
brj-23187	52	12	removal	removal	NOUN
brj-23187	52	13	predictions	prediction	NOUN
brj-23187	52	14	.	.	PUNCT
brj-23187	53	1	as	as	SCONJ
brj-23187	53	2	depicted	depict	VERB
brj-23187	53	3	in	in	ADP
brj-23187	53	4	the	the	DET
brj-23187	53	5	figure	figure	NOUN
brj-23187	53	6	,	,	PUNCT
brj-23187	53	7	𝑋1	𝑋1	PROPN
brj-23187	53	8	,	,	PUNCT
brj-23187	53	9	𝑋2	𝑋2	VERB
brj-23187	53	10	,	,	PUNCT
brj-23187	53	11	⋯	⋯	X
brj-23187	53	12	,	,	PUNCT
brj-23187	53	13	𝑋𝑚	𝑋𝑚	PROPN
brj-23187	53	14	denote	denote	VERB
brj-23187	53	15	the	the	DET
brj-23187	53	16	initial	initial	ADJ
brj-23187	53	17	variables	variable	NOUN
brj-23187	53	18	;	;	PUNCT
brj-23187	53	19	𝑋1	𝑋1	PROPN
brj-23187	53	20	′	′	NUM
brj-23187	53	21	,	,	PUNCT
brj-23187	53	22	𝑋2	𝑋2	VERB
brj-23187	53	23	′	′	NUM
brj-23187	53	24	,	,	PUNCT
brj-23187	53	25	⋯	⋯	NOUN
brj-23187	53	26	,	,	PUNCT
brj-23187	53	27	𝑋𝑛	𝑋𝑛	PROPN
brj-23187	53	28	′	′	NOUN
brj-23187	53	29	signify	signify	VERB
brj-23187	53	30	the	the	DET
brj-23187	53	31	selected	select	VERB
brj-23187	53	32	variables	variable	NOUN
brj-23187	53	33	;	;	PUNCT
brj-23187	54	1	𝑃1	𝑃1	NOUN
brj-23187	54	2	,	,	PUNCT
brj-23187	54	3	𝑃2	𝑃2	PROPN
brj-23187	54	4	,	,	PUNCT
brj-23187	54	5	⋯	⋯	PROPN
brj-23187	54	6	,	,	PUNCT
brj-23187	54	7	𝑃𝑧	𝑃𝑧	PROPN
brj-23187	54	8	correspond	correspond	VERB
brj-23187	54	9	to	to	ADP
brj-23187	54	10	the	the	DET
brj-23187	54	11	principal	principal	ADJ
brj-23187	54	12	component	component	NOUN
brj-23187	54	13	variables	variable	NOUN
brj-23187	54	14	after	after	ADP
brj-23187	54	15	dimensionality	dimensionality	NOUN
brj-23187	54	16	reduction	reduction	NOUN
brj-23187	54	17	,	,	PUNCT
brj-23187	54	18	while	while	SCONJ
brj-23187	54	19	𝜓1	𝜓1	NOUN
brj-23187	54	20	and	and	CCONJ
brj-23187	54	21	𝜓2	𝜓2	PROPN
brj-23187	54	22	represent	represent	VERB
brj-23187	54	23	the	the	DET
brj-23187	54	24	two	two	NUM
brj-23187	54	25	enzymatic	enzymatic	ADJ
brj-23187	54	26	hydrolysis	hydrolysis	NOUN
brj-23187	54	27	efficiency	efficiency	NOUN
brj-23187	54	28	indicators	indicator	NOUN
brj-23187	54	29	of	of	ADP
brj-23187	54	30	the	the	DET
brj-23187	54	31	extents	extent	NOUN
brj-23187	54	32	of	of	ADP
brj-23187	54	33	lignin	lignin	NOUN
brj-23187	54	34	removal	removal	NOUN
brj-23187	54	35	and	and	CCONJ
brj-23187	54	36	hemicellulose	hemicellulose	NOUN
brj-23187	54	37	removal	removal	NOUN
brj-23187	54	38	,	,	PUNCT
brj-23187	54	39	respectively	respectively	ADV
brj-23187	54	40	(	(	PUNCT
brj-23187	54	41	liu	liu	PROPN
brj-23187	54	42	et	et	PROPN
brj-23187	54	43	al	al	PROPN
brj-23187	54	44	.	.	PROPN
brj-23187	54	45	2022	2022	NUM
brj-23187	54	46	)	)	PUNCT
brj-23187	54	47	.	.	PUNCT
brj-23187	55	1	fig	fig	NOUN
brj-23187	55	2	.	.	PUNCT
brj-23187	56	1	2	2	X
brj-23187	56	2	.	.	X
brj-23187	56	3	prediction	prediction	NOUN
brj-23187	56	4	of	of	ADP
brj-23187	56	5	straw	straw	NOUN
brj-23187	56	6	enzymatic	enzymatic	ADJ
brj-23187	56	7	hydrolysis	hydrolysis	NOUN
brj-23187	56	8	efficiency	efficiency	NOUN
brj-23187	56	9	based	base	VERB
brj-23187	56	10	on	on	ADP
brj-23187	56	11	gra	gra	PROPN
brj-23187	56	12	-	-	PUNCT
brj-23187	56	13	kpca	kpca	PROPN
brj-23187	56	14	-	-	PUNCT
brj-23187	56	15	lssvm	lssvm	NOUN
brj-23187	56	16	gra	gra	PROPN
brj-23187	56	17	-	-	PUNCT
brj-23187	56	18	based	base	VERB
brj-23187	56	19	variable	variable	ADJ
brj-23187	56	20	selection	selection	NOUN
brj-23187	56	21	the	the	DET
brj-23187	56	22	gra	gra	PROPN
brj-23187	56	23	method	method	NOUN
brj-23187	56	24	enables	enable	VERB
brj-23187	56	25	quantitative	quantitative	ADJ
brj-23187	56	26	assessment	assessment	NOUN
brj-23187	56	27	of	of	ADP
brj-23187	56	28	the	the	DET
brj-23187	56	29	interrelationships	interrelationship	NOUN
brj-23187	56	30	among	among	ADP
brj-23187	56	31	different	different	ADJ
brj-23187	56	32	factors	factor	NOUN
brj-23187	56	33	within	within	ADP
brj-23187	56	34	a	a	DET
brj-23187	56	35	given	give	VERB
brj-23187	56	36	system	system	NOUN
brj-23187	56	37	.	.	PUNCT
brj-23187	57	1	the	the	DET
brj-23187	57	2	fundamental	fundamental	ADJ
brj-23187	57	3	concept	concept	NOUN
brj-23187	57	4	behind	behind	ADP
brj-23187	57	5	gra	gra	PROPN
brj-23187	57	6	is	be	AUX
brj-23187	57	7	to	to	PART
brj-23187	57	8	assess	assess	VERB
brj-23187	57	9	the	the	DET
brj-23187	57	10	strength	strength	NOUN
brj-23187	57	11	of	of	ADP
brj-23187	57	12	a	a	DET
brj-23187	57	13	relationship	relationship	NOUN
brj-23187	57	14	by	by	ADP
brj-23187	57	15	evaluating	evaluate	VERB
brj-23187	57	16	the	the	DET
brj-23187	57	17	congruity	congruity	NOUN
brj-23187	57	18	between	between	ADP
brj-23187	57	19	the	the	DET
brj-23187	57	20	geometric	geometric	ADJ
brj-23187	57	21	configurations	configuration	NOUN
brj-23187	57	22	of	of	ADP
brj-23187	57	23	the	the	DET
brj-23187	57	24	reference	reference	NOUN
brj-23187	57	25	data	datum	NOUN
brj-23187	57	26	column	column	NOUN
brj-23187	57	27	and	and	CCONJ
brj-23187	57	28	multiple	multiple	ADJ
brj-23187	57	29	comparison	comparison	NOUN
brj-23187	57	30	data	datum	NOUN
brj-23187	57	31	columns	column	NOUN
brj-23187	57	32	.	.	PUNCT
brj-23187	58	1	consequently	consequently	ADV
brj-23187	58	2	,	,	PUNCT
brj-23187	58	3	the	the	PRON
brj-23187	58	4	higher	high	ADJ
brj-23187	58	5	the	the	DET
brj-23187	58	6	degree	degree	NOUN
brj-23187	58	7	of	of	ADP
brj-23187	58	8	similarity	similarity	NOUN
brj-23187	58	9	,	,	PUNCT
brj-23187	58	10	the	the	PRON
brj-23187	58	11	stronger	strong	ADJ
brj-23187	58	12	the	the	DET
brj-23187	58	13	correlation	correlation	NOUN
brj-23187	58	14	(	(	PUNCT
brj-23187	58	15	han	han	PROPN
brj-23187	58	16	et	et	PROPN
brj-23187	58	17	al	al	PROPN
brj-23187	58	18	.	.	PROPN
brj-23187	58	19	peer	peer	NOUN
brj-23187	58	20	-	-	PUNCT
brj-23187	58	21	reviewed	review	VERB
brj-23187	58	22	article	article	NOUN
brj-23187	58	23	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	58	24	fu	fu	PROPN
brj-23187	58	25	et	et	PROPN
brj-23187	58	26	al	al	PROPN
brj-23187	58	27	.	.	PROPN
brj-23187	59	1	(	(	PUNCT
brj-23187	59	2	2024	2024	NUM
brj-23187	59	3	)	)	PUNCT
brj-23187	59	4	.	.	PUNCT
brj-23187	60	1	“	"	PUNCT
brj-23187	60	2	predicting	predict	VERB
brj-23187	60	3	enzymatic	enzymatic	ADJ
brj-23187	60	4	hydrolysis	hydrolysis	NOUN
brj-23187	60	5	,	,	PUNCT
brj-23187	60	6	”	"	PUNCT
brj-23187	60	7	bioresources	bioresource	NOUN
brj-23187	60	8	19(2	19(2	NUM
brj-23187	60	9	)	)	PUNCT
brj-23187	60	10	,	,	PUNCT
brj-23187	60	11	3505	3505	NUM
brj-23187	60	12	-	-	SYM
brj-23187	60	13	3519	3519	NUM
brj-23187	60	14	.	.	PUNCT
brj-23187	61	1	3508	3508	NUM
brj-23187	61	2	2022	2022	NUM
brj-23187	61	3	)	)	PUNCT
brj-23187	61	4	.	.	PUNCT
brj-23187	62	1	considering	consider	VERB
brj-23187	62	2	the	the	DET
brj-23187	62	3	analysis	analysis	NOUN
brj-23187	62	4	of	of	ADP
brj-23187	62	5	the	the	DET
brj-23187	62	6	lignin	lignin	NOUN
brj-23187	62	7	removal	removal	NOUN
brj-23187	62	8	as	as	ADP
brj-23187	62	9	an	an	DET
brj-23187	62	10	example	example	NOUN
brj-23187	62	11	,	,	PUNCT
brj-23187	62	12	the	the	DET
brj-23187	62	13	specific	specific	ADJ
brj-23187	62	14	steps	step	NOUN
brj-23187	62	15	of	of	ADP
brj-23187	62	16	variable	variable	ADJ
brj-23187	62	17	selection	selection	NOUN
brj-23187	62	18	using	use	VERB
brj-23187	62	19	gra	gra	PROPN
brj-23187	62	20	were	be	AUX
brj-23187	62	21	as	as	SCONJ
brj-23187	62	22	follows	follow	VERB
brj-23187	62	23	:	:	PUNCT
brj-23187	62	24	(	(	PUNCT
brj-23187	62	25	1	1	X
brj-23187	62	26	)	)	PUNCT
brj-23187	62	27	input	input	NOUN
brj-23187	62	28	and	and	CCONJ
brj-23187	62	29	output	output	NOUN
brj-23187	62	30	sequences	sequence	NOUN
brj-23187	62	31	were	be	AUX
brj-23187	62	32	defined	define	VERB
brj-23187	62	33	.	.	PUNCT
brj-23187	63	1	there	there	PRON
brj-23187	63	2	are	be	VERB
brj-23187	63	3	𝑚	𝑚	ADP
brj-23187	63	4	input	input	NOUN
brj-23187	63	5	sequences	sequence	NOUN
brj-23187	63	6	available	available	ADJ
brj-23187	63	7	,	,	PUNCT
brj-23187	63	8	where	where	SCONJ
brj-23187	63	9	𝑖	𝑖	PRON
brj-23187	63	10	represents	represent	VERB
brj-23187	63	11	{	{	PUNCT
brj-23187	63	12	𝑋𝑖(𝑘	𝑋𝑖(𝑘	NUM
brj-23187	63	13	)	)	PUNCT
brj-23187	63	14	}	}	PUNCT
brj-23187	63	15	,	,	PUNCT
brj-23187	63	16	𝑖	𝑖	SYM
brj-23187	63	17	=	=	SYM
brj-23187	63	18	1,2	1,2	NUM
brj-23187	63	19	,	,	PUNCT
brj-23187	63	20	⋯	⋯	PROPN
brj-23187	63	21	,	,	PUNCT
brj-23187	63	22	𝑚,and	𝑚,and	PRON
brj-23187	63	23	𝑚	𝑚	PROPN
brj-23187	63	24	is	be	AUX
brj-23187	63	25	the	the	DET
brj-23187	63	26	number	number	NOUN
brj-23187	63	27	of	of	ADP
brj-23187	63	28	variables	variable	NOUN
brj-23187	63	29	of	of	ADP
brj-23187	63	30	influencing	influence	VERB
brj-23187	63	31	factors	factor	NOUN
brj-23187	63	32	,	,	PUNCT
brj-23187	63	33	𝑘	𝑘	X
brj-23187	63	34	=	=	SYM
brj-23187	63	35	1	1	NUM
brj-23187	63	36	,	,	PUNCT
brj-23187	63	37	2	2	NUM
brj-23187	63	38	,	,	PUNCT
brj-23187	63	39	⋯	⋯	NOUN
brj-23187	63	40	,	,	PUNCT
brj-23187	63	41	𝐿	𝐿	PROPN
brj-23187	63	42	,	,	PUNCT
brj-23187	63	43	and	and	CCONJ
brj-23187	63	44	𝐿	𝐿	PROPN
brj-23187	63	45	is	be	AUX
brj-23187	63	46	the	the	DET
brj-23187	63	47	length	length	NOUN
brj-23187	63	48	of	of	ADP
brj-23187	63	49	the	the	DET
brj-23187	63	50	sequence	sequence	NOUN
brj-23187	63	51	.	.	PUNCT
brj-23187	64	1	the	the	DET
brj-23187	64	2	output	output	NOUN
brj-23187	64	3	sequence	sequence	NOUN
brj-23187	64	4	,	,	PUNCT
brj-23187	64	5	denoted	denote	VERB
brj-23187	64	6	as	as	ADP
brj-23187	64	7	{	{	PUNCT
brj-23187	64	8	𝜓1(𝑘	𝜓1(𝑘	NOUN
brj-23187	64	9	)	)	PUNCT
brj-23187	64	10	}	}	PUNCT
brj-23187	64	11	,	,	PUNCT
brj-23187	64	12	corresponds	correspond	VERB
brj-23187	64	13	to	to	ADP
brj-23187	64	14	the	the	DET
brj-23187	64	15	extent	extent	NOUN
brj-23187	64	16	of	of	ADP
brj-23187	64	17	lignin	lignin	NOUN
brj-23187	64	18	removal	removal	NOUN
brj-23187	64	19	.	.	PUNCT
brj-23187	65	1	the	the	DET
brj-23187	65	2	data	data	NOUN
brj-23187	65	3	sequences	sequence	NOUN
brj-23187	65	4	were	be	AUX
brj-23187	65	5	subjected	subject	VERB
brj-23187	65	6	to	to	ADP
brj-23187	65	7	dimensionless	dimensionless	NOUN
brj-23187	65	8	processing	processing	NOUN
brj-23187	65	9	by	by	ADP
brj-23187	65	10	averaging	average	VERB
brj-23187	65	11	.	.	PUNCT
brj-23187	66	1	in	in	ADP
brj-23187	66	2	this	this	DET
brj-23187	66	3	process	process	NOUN
brj-23187	66	4	,	,	PUNCT
brj-23187	66	5	each	each	DET
brj-23187	66	6	sequence	sequence	NOUN
brj-23187	66	7	is	be	AUX
brj-23187	66	8	divided	divide	VERB
brj-23187	66	9	by	by	ADP
brj-23187	66	10	its	its	PRON
brj-23187	66	11	respective	respective	ADJ
brj-23187	66	12	mean	mean	ADJ
brj-23187	66	13	values	value	NOUN
brj-23187	66	14	.	.	PUNCT
brj-23187	67	1	for	for	ADP
brj-23187	67	2	clarity	clarity	NOUN
brj-23187	67	3	,	,	PUNCT
brj-23187	67	4	{	{	PUNCT
brj-23187	67	5	𝑋𝑖(𝑘	𝑋𝑖(𝑘	ADV
brj-23187	67	6	)	)	PUNCT
brj-23187	67	7	}	}	PUNCT
brj-23187	67	8	and	and	CCONJ
brj-23187	67	9	{	{	PUNCT
brj-23187	67	10	𝜓1(𝑘	𝜓1(𝑘	NOUN
brj-23187	67	11	)	)	PUNCT
brj-23187	67	12	}	}	PUNCT
brj-23187	67	13	continue	continue	VERB
brj-23187	67	14	to	to	PART
brj-23187	67	15	represent	represent	VERB
brj-23187	67	16	the	the	DET
brj-23187	67	17	input	input	NOUN
brj-23187	67	18	and	and	CCONJ
brj-23187	67	19	output	output	NOUN
brj-23187	67	20	sequences	sequence	NOUN
brj-23187	67	21	after	after	ADP
brj-23187	67	22	averaging	average	VERB
brj-23187	67	23	,	,	PUNCT
brj-23187	67	24	respectively	respectively	ADV
brj-23187	67	25	(	(	PUNCT
brj-23187	67	26	du	du	NOUN
brj-23187	67	27	2022	2022	NUM
brj-23187	67	28	)	)	PUNCT
brj-23187	67	29	.	.	PUNCT
brj-23187	68	1	(	(	PUNCT
brj-23187	68	2	2	2	X
brj-23187	68	3	)	)	PUNCT
brj-23187	68	4	the	the	DET
brj-23187	68	5	correlation	correlation	NOUN
brj-23187	68	6	coefficient	coefficient	NOUN
brj-23187	68	7	was	be	AUX
brj-23187	68	8	calculated	calculate	VERB
brj-23187	68	9	.	.	PUNCT
brj-23187	69	1	the	the	DET
brj-23187	69	2	grey	grey	PROPN
brj-23187	69	3	correlation	correlation	NOUN
brj-23187	69	4	coefficient	coefficient	NOUN
brj-23187	69	5	of	of	ADP
brj-23187	69	6	the	the	DET
brj-23187	69	7	𝑖	𝑖	SYM
brj-23187	69	8	input	input	NOUN
brj-23187	69	9	sequence	sequence	NOUN
brj-23187	69	10	{	{	PUNCT
brj-23187	69	11	𝑋𝑖(𝑘	𝑋𝑖(𝑘	NUM
brj-23187	69	12	)	)	PUNCT
brj-23187	69	13	}	}	PUNCT
brj-23187	69	14	and	and	CCONJ
brj-23187	69	15	the	the	DET
brj-23187	69	16	output	output	NOUN
brj-23187	69	17	sequence	sequence	NOUN
brj-23187	69	18	{	{	PUNCT
brj-23187	69	19	𝜓1(𝑘	𝜓1(𝑘	NOUN
brj-23187	69	20	)	)	PUNCT
brj-23187	69	21	}	}	PUNCT
brj-23187	69	22	at	at	ADP
brj-23187	69	23	𝑘	𝑘	PRON
brj-23187	69	24	can	can	AUX
brj-23187	69	25	be	be	AUX
brj-23187	69	26	calculated	calculate	VERB
brj-23187	69	27	by	by	ADP
brj-23187	69	28	the	the	DET
brj-23187	69	29	following	following	NOUN
brj-23187	69	30	eq	eq	NOUN
brj-23187	69	31	.	.	PROPN
brj-23187	69	32	1	1	NUM
brj-23187	69	33	:	:	PUNCT
brj-23187	69	34	𝜁𝑖𝑜(𝑘	𝜁𝑖𝑜(𝑘	PROPN
brj-23187	69	35	)	)	PUNCT
brj-23187	69	36	=	=	SYM
brj-23187	70	1	min	min	NOUN
brj-23187	70	2	𝑖	𝑖	SYM
brj-23187	70	3	min	min	PROPN
brj-23187	71	1	𝑘	𝑘	PROPN
brj-23187	71	2	|𝜓1(𝑘)−𝑋𝑖(𝑘)|+max	|𝜓1(𝑘)−𝑋𝑖(𝑘)|+max	ADV
brj-23187	71	3	𝑖	𝑖	SYM
brj-23187	71	4	max	max	PROPN
brj-23187	71	5	𝑘	𝑘	X
brj-23187	71	6	|𝜓1(𝑘)−𝑋𝑖(𝑘)|	|𝜓1(𝑘)−𝑋𝑖(𝑘)|	PROPN
brj-23187	71	7	|𝜓1(𝑘)−𝑋𝑖(𝑘)|+𝜌⋅max	|𝜓1(𝑘)−𝑋𝑖(𝑘)|+𝜌⋅max	PROPN
brj-23187	71	8	𝑖	𝑖	SYM
brj-23187	71	9	max	max	PROPN
brj-23187	71	10	𝑘	𝑘	X
brj-23187	71	11	|𝜓1(𝑘)−𝑋𝑖(𝑘)|	|𝜓1(𝑘)−𝑋𝑖(𝑘)|	PROPN
brj-23187	71	12	(	(	PUNCT
brj-23187	71	13	1	1	X
brj-23187	71	14	)	)	PUNCT
brj-23187	71	15	the	the	DET
brj-23187	71	16	resolution	resolution	NOUN
brj-23187	71	17	coefficient	coefficient	NOUN
brj-23187	71	18	,	,	PUNCT
brj-23187	71	19	denoted	denote	VERB
brj-23187	71	20	as	as	ADP
brj-23187	71	21	𝜌(𝜌	𝜌(𝜌	PROPN
brj-23187	71	22	>	>	X
brj-23187	71	23	0	0	NUM
brj-23187	71	24	)	)	PUNCT
brj-23187	71	25	,	,	PUNCT
brj-23187	71	26	determines	determine	VERB
brj-23187	71	27	the	the	DET
brj-23187	71	28	resolution	resolution	NOUN
brj-23187	71	29	of	of	ADP
brj-23187	71	30	the	the	DET
brj-23187	71	31	system	system	NOUN
brj-23187	71	32	,	,	PUNCT
brj-23187	71	33	with	with	ADP
brj-23187	71	34	smaller	small	ADJ
brj-23187	71	35	values	value	NOUN
brj-23187	71	36	indicating	indicate	VERB
brj-23187	71	37	higher	high	ADJ
brj-23187	71	38	resolution	resolution	NOUN
brj-23187	71	39	.	.	PUNCT
brj-23187	72	1	the	the	DET
brj-23187	72	2	value	value	NOUN
brj-23187	72	3	range	range	NOUN
brj-23187	72	4	of	of	ADP
brj-23187	72	5	𝜌	𝜌	PRON
brj-23187	72	6	is	be	AUX
brj-23187	72	7	typically	typically	ADV
brj-23187	72	8	confined	confine	VERB
brj-23187	72	9	to	to	ADP
brj-23187	72	10	(	(	PUNCT
brj-23187	72	11	0,1	0,1	NUM
brj-23187	72	12	)	)	PUNCT
brj-23187	72	13	.	.	PUNCT
brj-23187	73	1	min	min	PROPN
brj-23187	74	1	𝑖	𝑖	SYM
brj-23187	74	2	min	min	PROPN
brj-23187	74	3	𝑘	𝑘	PRON
brj-23187	74	4	|𝜓1(𝑘	|𝜓1(𝑘	NOUN
brj-23187	74	5	)	)	PUNCT
brj-23187	74	6	−	−	NOUN
brj-23187	74	7	𝑋𝑖(𝑘)|	𝑋𝑖(𝑘)|	ADV
brj-23187	74	8	represents	represent	VERB
brj-23187	74	9	the	the	DET
brj-23187	74	10	minimum	minimum	ADJ
brj-23187	74	11	discrepancy	discrepancy	NOUN
brj-23187	74	12	between	between	ADP
brj-23187	74	13	the	the	DET
brj-23187	74	14	two	two	NUM
brj-23187	74	15	poles	pole	NOUN
brj-23187	74	16	,	,	PUNCT
brj-23187	74	17	while	while	SCONJ
brj-23187	74	18	max	max	PROPN
brj-23187	74	19	𝑖	𝑖	PROPN
brj-23187	74	20	max	max	PROPN
brj-23187	74	21	𝑘	𝑘	PRON
brj-23187	74	22	|𝜓1(𝑘	|𝜓1(𝑘	NOUN
brj-23187	74	23	)	)	PUNCT
brj-23187	74	24	−	−	PROPN
brj-23187	74	25	𝑋𝑖(𝑘)|	𝑋𝑖(𝑘)|	ADJ
brj-23187	74	26	denotes	denote	VERB
brj-23187	74	27	the	the	DET
brj-23187	74	28	maximum	maximum	ADJ
brj-23187	74	29	disparity	disparity	NOUN
brj-23187	74	30	between	between	ADP
brj-23187	74	31	the	the	DET
brj-23187	74	32	two	two	NUM
brj-23187	74	33	poles	pole	NOUN
brj-23187	74	34	(	(	PUNCT
brj-23187	74	35	antos	anto	NOUN
brj-23187	74	36	et	et	PROPN
brj-23187	74	37	al	al	PROPN
brj-23187	74	38	.	.	PROPN
brj-23187	74	39	2022	2022	NUM
brj-23187	74	40	)	)	PUNCT
brj-23187	74	41	.	.	PUNCT
brj-23187	75	1	(	(	PUNCT
brj-23187	75	2	3	3	X
brj-23187	75	3	)	)	PUNCT
brj-23187	75	4	the	the	DET
brj-23187	75	5	grey	grey	ADJ
brj-23187	75	6	correlation	correlation	NOUN
brj-23187	75	7	coefficient	coefficient	NOUN
brj-23187	75	8	was	be	AUX
brj-23187	75	9	computed	compute	VERB
brj-23187	75	10	.	.	PUNCT
brj-23187	76	1	the	the	DET
brj-23187	76	2	numerical	numerical	ADJ
brj-23187	76	3	value	value	NOUN
brj-23187	76	4	of	of	ADP
brj-23187	76	5	the	the	DET
brj-23187	76	6	correlation	correlation	NOUN
brj-23187	76	7	degree	degree	NOUN
brj-23187	76	8	between	between	ADP
brj-23187	76	9	the	the	DET
brj-23187	76	10	𝑖	𝑖	SYM
brj-23187	76	11	input	input	NOUN
brj-23187	76	12	sequence	sequence	NOUN
brj-23187	76	13	{	{	PUNCT
brj-23187	76	14	𝑋𝑖(𝑘	𝑋𝑖(𝑘	NUM
brj-23187	76	15	)	)	PUNCT
brj-23187	76	16	}	}	PUNCT
brj-23187	76	17	and	and	CCONJ
brj-23187	76	18	the	the	DET
brj-23187	76	19	output	output	NOUN
brj-23187	76	20	sequence	sequence	NOUN
brj-23187	76	21	{	{	PUNCT
brj-23187	76	22	𝜓1(𝑘	𝜓1(𝑘	NOUN
brj-23187	76	23	)	)	PUNCT
brj-23187	76	24	}	}	PUNCT
brj-23187	76	25	can	can	AUX
brj-23187	76	26	be	be	AUX
brj-23187	76	27	expressed	express	VERB
brj-23187	76	28	as	as	SCONJ
brj-23187	76	29	follows	follow	VERB
brj-23187	76	30	:	:	PUNCT
brj-23187	76	31	𝑟𝑖	𝑟𝑖	ADV
brj-23187	76	32	=	=	SYM
brj-23187	76	33	1	1	NUM
brj-23187	76	34	𝐿	𝐿	PROPN
brj-23187	76	35	∑	∑	PUNCT
brj-23187	76	36	𝜉𝑖𝑜	𝜉𝑖𝑜	VERB
brj-23187	76	37	𝐿	𝐿	PROPN
brj-23187	76	38	𝑘=1	𝑘=1	PROPN
brj-23187	76	39	(	(	PUNCT
brj-23187	76	40	𝑘	𝑘	NOUN
brj-23187	76	41	)	)	PUNCT
brj-23187	76	42	(	(	PUNCT
brj-23187	76	43	2	2	X
brj-23187	76	44	)	)	PUNCT
brj-23187	76	45	for	for	ADP
brj-23187	76	46	each	each	PRON
brj-23187	76	47	of	of	ADP
brj-23187	76	48	the	the	DET
brj-23187	76	49	𝑚	𝑚	PROPN
brj-23187	76	50	input	input	NOUN
brj-23187	76	51	sequences	sequence	NOUN
brj-23187	76	52	,	,	PUNCT
brj-23187	76	53	the	the	DET
brj-23187	76	54	grey	grey	ADJ
brj-23187	76	55	correlation	correlation	NOUN
brj-23187	76	56	degrees	degree	NOUN
brj-23187	76	57	𝑟1	𝑟1	NOUN
brj-23187	76	58	,	,	PUNCT
brj-23187	76	59	𝑟2	𝑟2	NOUN
brj-23187	76	60	,	,	PUNCT
brj-23187	76	61	…	…	PUNCT
brj-23187	76	62	,	,	PUNCT
brj-23187	76	63	𝑟𝑚	𝑟𝑚	PROPN
brj-23187	76	64	were	be	AUX
brj-23187	76	65	determined	determine	VERB
brj-23187	76	66	.	.	PUNCT
brj-23187	77	1	(	(	PUNCT
brj-23187	77	2	4	4	X
brj-23187	77	3	)	)	PUNCT
brj-23187	77	4	reordering	reordering	NOUN
brj-23187	77	5	was	be	AUX
brj-23187	77	6	based	base	VERB
brj-23187	77	7	on	on	ADP
brj-23187	77	8	the	the	DET
brj-23187	77	9	degree	degree	NOUN
brj-23187	77	10	of	of	ADP
brj-23187	77	11	gra	gra	PROPN
brj-23187	77	12	and	and	CCONJ
brj-23187	77	13	variable	variable	ADJ
brj-23187	77	14	screening	screening	NOUN
brj-23187	77	15	.	.	PUNCT
brj-23187	78	1	based	base	VERB
brj-23187	78	2	on	on	ADP
brj-23187	78	3	the	the	DET
brj-23187	78	4	calculated	calculate	VERB
brj-23187	78	5	grey	grey	ADJ
brj-23187	78	6	correlation	correlation	NOUN
brj-23187	78	7	degree	degree	NOUN
brj-23187	78	8	,	,	PUNCT
brj-23187	78	9	the	the	DET
brj-23187	78	10	influencing	influence	VERB
brj-23187	78	11	factor	factor	NOUN
brj-23187	78	12	variables	variable	VERB
brj-23187	78	13	𝑋1	𝑋1	PROPN
brj-23187	78	14	,	,	PUNCT
brj-23187	78	15	𝑋2	𝑋2	VERB
brj-23187	78	16	,	,	PUNCT
brj-23187	78	17	⋯	⋯	PROPN
brj-23187	78	18	,	,	PUNCT
brj-23187	78	19	𝑋𝑚	𝑋𝑚	PROPN
brj-23187	78	20	were	be	AUX
brj-23187	78	21	ranked	rank	VERB
brj-23187	78	22	in	in	ADP
brj-23187	78	23	descending	descend	VERB
brj-23187	78	24	order	order	NOUN
brj-23187	78	25	.	.	PUNCT
brj-23187	79	1	the	the	DET
brj-23187	79	2	dominant	dominant	ADJ
brj-23187	79	3	factor	factor	NOUN
brj-23187	79	4	variables	variable	NOUN
brj-23187	79	5	with	with	ADP
brj-23187	79	6	a	a	DET
brj-23187	79	7	grey	grey	ADJ
brj-23187	79	8	correlation	correlation	NOUN
brj-23187	79	9	degree	degree	NOUN
brj-23187	79	10	greater	great	ADJ
brj-23187	79	11	than	than	ADP
brj-23187	79	12	a	a	DET
brj-23187	79	13	certain	certain	ADJ
brj-23187	79	14	threshold	threshold	NOUN
brj-23187	79	15	𝜂	𝜂	NOUN
brj-23187	79	16	were	be	AUX
brj-23187	79	17	retained	retain	VERB
brj-23187	79	18	and	and	CCONJ
brj-23187	79	19	denoted	denote	VERB
brj-23187	79	20	as	as	ADP
brj-23187	79	21	𝑋1	𝑋1	NOUN
brj-23187	79	22	′	′	NUM
brj-23187	79	23	,	,	PUNCT
brj-23187	79	24	𝑋2	𝑋2	VERB
brj-23187	79	25	′	′	NUM
brj-23187	79	26	,	,	PUNCT
brj-23187	79	27	⋯	⋯	NOUN
brj-23187	79	28	,	,	PUNCT
brj-23187	79	29	𝑋𝑛	𝑋𝑛	PROPN
brj-23187	79	30	′	′	NOUN
brj-23187	79	31	,	,	PUNCT
brj-23187	79	32	where	where	SCONJ
brj-23187	79	33	𝑛	𝑛	DET
brj-23187	79	34	≤	≤	NUM
brj-23187	79	35	𝑚.	𝑚.	ADJ
brj-23187	79	36	𝜂	𝜂	NOUN
brj-23187	79	37	ranges	range	NOUN
brj-23187	79	38	from	from	ADP
brj-23187	79	39	0.7	0.7	NUM
brj-23187	79	40	to	to	PART
brj-23187	79	41	0.8	0.8	NUM
brj-23187	79	42	.	.	PUNCT
brj-23187	80	1	input	input	NOUN
brj-23187	80	2	dimension	dimension	NOUN
brj-23187	80	3	reduction	reduction	NOUN
brj-23187	80	4	based	base	VERB
brj-23187	80	5	on	on	ADP
brj-23187	80	6	kpca	kpca	PROPN
brj-23187	80	7	kpca	kpca	PROPN
brj-23187	80	8	uses	use	VERB
brj-23187	80	9	kernel	kernel	PROPN
brj-23187	80	10	functions	function	NOUN
brj-23187	80	11	to	to	PART
brj-23187	80	12	map	map	VERB
brj-23187	80	13	the	the	DET
brj-23187	80	14	original	original	ADJ
brj-23187	80	15	data	datum	NOUN
brj-23187	80	16	into	into	ADP
brj-23187	80	17	a	a	DET
brj-23187	80	18	high	high	ADJ
brj-23187	80	19	-	-	PUNCT
brj-23187	80	20	dimensional	dimensional	ADJ
brj-23187	80	21	feature	feature	NOUN
brj-23187	80	22	space	space	NOUN
brj-23187	80	23	and	and	CCONJ
brj-23187	80	24	then	then	ADV
brj-23187	80	25	performs	perform	VERB
brj-23187	80	26	principal	principal	ADJ
brj-23187	80	27	component	component	NOUN
brj-23187	80	28	analysis	analysis	NOUN
brj-23187	80	29	(	(	PUNCT
brj-23187	80	30	anowar	anowar	NOUN
brj-23187	80	31	et	et	PROPN
brj-23187	80	32	al	al	PROPN
brj-23187	80	33	.	.	PROPN
brj-23187	80	34	2021	2021	NUM
brj-23187	80	35	)	)	PUNCT
brj-23187	80	36	.	.	PUNCT
brj-23187	81	1	using	use	VERB
brj-23187	81	2	the	the	DET
brj-23187	81	3	lignin	lignin	NOUN
brj-23187	81	4	removal	removal	NOUN
brj-23187	81	5	analysis	analysis	NOUN
brj-23187	81	6	as	as	ADP
brj-23187	81	7	an	an	DET
brj-23187	81	8	example	example	NOUN
brj-23187	81	9	,	,	PUNCT
brj-23187	81	10	each	each	DET
brj-23187	81	11	sample	sample	NOUN
brj-23187	81	12	point	point	NOUN
brj-23187	81	13	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	81	14	is	be	AUX
brj-23187	81	15	an	an	DET
brj-23187	81	16	𝑛-dimensional	𝑛-dimensional	ADJ
brj-23187	81	17	column	column	NOUN
brj-23187	81	18	vector	vector	NOUN
brj-23187	81	19	made	make	VERB
brj-23187	81	20	of	of	ADP
brj-23187	81	21	𝑋1	𝑋1	PROPN
brj-23187	81	22	′	′	NUM
brj-23187	81	23	,	,	PUNCT
brj-23187	81	24	𝑋2	𝑋2	VERB
brj-23187	81	25	′	′	NUM
brj-23187	81	26	,	,	PUNCT
brj-23187	81	27	⋯	⋯	NOUN
brj-23187	81	28	,	,	PUNCT
brj-23187	81	29	𝑋𝑛	𝑋𝑛	PROPN
brj-23187	81	30	′	′	NUM
brj-23187	81	31	.	.	PUNCT
brj-23187	82	1	these	these	DET
brj-23187	82	2	𝑁	𝑁	PROPN
brj-23187	82	3	input	input	NOUN
brj-23187	82	4	samples	sample	NOUN
brj-23187	82	5	form	form	VERB
brj-23187	82	6	the	the	DET
brj-23187	82	7	input	input	NOUN
brj-23187	82	8	matrix	matrix	NOUN
brj-23187	82	9	𝑿	𝑿	NOUN
brj-23187	83	1	=	=	SYM
brj-23187	84	1	[	[	X
brj-23187	84	2	𝒙1	𝒙1	NOUN
brj-23187	84	3	,	,	PUNCT
brj-23187	84	4	𝒙2	𝒙2	PROPN
brj-23187	84	5	,	,	PUNCT
brj-23187	84	6	⋯	⋯	NOUN
brj-23187	84	7	,	,	PUNCT
brj-23187	84	8	𝒙𝑁	𝒙𝑁	PRON
brj-23187	84	9	]	]	PUNCT
brj-23187	84	10	.	.	PUNCT
brj-23187	85	1	using	use	VERB
brj-23187	85	2	a	a	DET
brj-23187	85	3	nonlinear	nonlinear	ADJ
brj-23187	85	4	mapping	mapping	NOUN
brj-23187	85	5	function	function	NOUN
brj-23187	85	6	𝛷	𝛷	NOUN
brj-23187	85	7	,	,	PUNCT
brj-23187	85	8	one	one	PRON
brj-23187	85	9	can	can	AUX
brj-23187	85	10	project	project	VERB
brj-23187	85	11	𝑿	𝑿	PROPN
brj-23187	85	12	into	into	ADP
brj-23187	85	13	a	a	DET
brj-23187	85	14	highdimensional	highdimensional	ADJ
brj-23187	85	15	feature	feature	NOUN
brj-23187	85	16	space	space	NOUN
brj-23187	85	17	f	f	NOUN
brj-23187	85	18	,	,	PUNCT
brj-23187	85	19	then	then	ADV
brj-23187	85	20	the	the	DET
brj-23187	85	21	transformed	transform	VERB
brj-23187	85	22	representation	representation	NOUN
brj-23187	85	23	𝛷	𝛷	PROPN
brj-23187	85	24	(	(	PUNCT
brj-23187	85	25	𝑿	𝑿	PROPN
brj-23187	85	26	)	)	PUNCT
brj-23187	86	1	[	[	X
brj-23187	86	2	𝛷(𝒙1	𝛷(𝒙1	NOUN
brj-23187	86	3	)	)	PUNCT
brj-23187	86	4	,	,	PUNCT
brj-23187	86	5	𝛷(𝒙2	𝛷(𝒙2	PROPN
brj-23187	86	6	)	)	PUNCT
brj-23187	86	7	,	,	PUNCT
brj-23187	86	8	⋯	⋯	NOUN
brj-23187	86	9	,	,	PUNCT
brj-23187	86	10	𝛷(𝒙𝑁	𝛷(𝒙𝑁	PROPN
brj-23187	86	11	)	)	PUNCT
brj-23187	86	12	]	]	PUNCT
brj-23187	86	13	can	can	AUX
brj-23187	86	14	be	be	AUX
brj-23187	86	15	obtained	obtain	VERB
brj-23187	86	16	(	(	PUNCT
brj-23187	86	17	kuang	kuang	PROPN
brj-23187	86	18	et	et	PROPN
brj-23187	86	19	al	al	PROPN
brj-23187	86	20	.	.	PROPN
brj-23187	86	21	2014	2014	NUM
brj-23187	86	22	)	)	PUNCT
brj-23187	86	23	.	.	PUNCT
brj-23187	87	1	if	if	SCONJ
brj-23187	87	2	it	it	PRON
brj-23187	87	3	is	be	AUX
brj-23187	87	4	assumed	assume	VERB
brj-23187	87	5	that	that	SCONJ
brj-23187	87	6	𝑿	𝑿	PROPN
brj-23187	87	7	meets	meet	VERB
brj-23187	87	8	the	the	DET
brj-23187	87	9	centralisation	centralisation	NOUN
brj-23187	87	10	requirement	requirement	NOUN
brj-23187	87	11	in	in	ADP
brj-23187	87	12	the	the	DET
brj-23187	87	13	feature	feature	NOUN
brj-23187	87	14	space	space	NOUN
brj-23187	87	15	,	,	PUNCT
brj-23187	87	16	meaning	mean	VERB
brj-23187	87	17	∑	∑	PROPN
brj-23187	87	18	𝛷𝑁	𝛷𝑁	PROPN
brj-23187	87	19	𝑖=1	𝑖=1	PROPN
brj-23187	87	20	(	(	PUNCT
brj-23187	87	21	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	87	22	)	)	PUNCT
brj-23187	87	23	=	=	SYM
brj-23187	87	24	𝟎	𝟎	PROPN
brj-23187	87	25	,	,	PUNCT
brj-23187	87	26	then	then	ADV
brj-23187	87	27	the	the	DET
brj-23187	87	28	covariance	covariance	NOUN
brj-23187	87	29	matrix	matrix	NOUN
brj-23187	87	30	𝐂f	𝐂f	PROPN
brj-23187	87	31	in	in	ADP
brj-23187	87	32	f	f	PROPN
brj-23187	87	33	can	can	AUX
brj-23187	87	34	be	be	AUX
brj-23187	87	35	expressed	express	VERB
brj-23187	87	36	as	as	ADP
brj-23187	87	37	eq	eq	NOUN
brj-23187	87	38	.	.	PROPN
brj-23187	87	39	3	3	X
brj-23187	87	40	.	.	NUM
brj-23187	87	41	:	:	PUNCT
brj-23187	87	42	peer	peer	NOUN
brj-23187	87	43	-	-	PUNCT
brj-23187	87	44	reviewed	review	VERB
brj-23187	87	45	article	article	NOUN
brj-23187	87	46	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	87	47	fu	fu	PROPN
brj-23187	87	48	et	et	PROPN
brj-23187	87	49	al	al	PROPN
brj-23187	87	50	.	.	PROPN
brj-23187	88	1	(	(	PUNCT
brj-23187	88	2	2024	2024	NUM
brj-23187	88	3	)	)	PUNCT
brj-23187	88	4	.	.	PUNCT
brj-23187	89	1	“	"	PUNCT
brj-23187	89	2	predicting	predict	VERB
brj-23187	89	3	enzymatic	enzymatic	ADJ
brj-23187	89	4	hydrolysis	hydrolysis	NOUN
brj-23187	89	5	,	,	PUNCT
brj-23187	89	6	”	"	PUNCT
brj-23187	89	7	bioresources	bioresource	NOUN
brj-23187	89	8	19(2	19(2	NUM
brj-23187	89	9	)	)	PUNCT
brj-23187	89	10	,	,	PUNCT
brj-23187	89	11	3505	3505	NUM
brj-23187	89	12	-	-	SYM
brj-23187	89	13	3519	3519	NUM
brj-23187	89	14	.	.	PUNCT
brj-23187	90	1	3509	3509	NUM
brj-23187	90	2	𝑪f	𝑪f	PROPN
brj-23187	90	3	=	=	SYM
brj-23187	90	4	1	1	NUM
brj-23187	90	5	𝑁	𝑁	PROPN
brj-23187	90	6	𝛷(𝑿)𝛷(𝑿)t	𝛷(𝑿)𝛷(𝑿)t	NOUN
brj-23187	90	7	=	=	NOUN
brj-23187	90	8	1	1	NUM
brj-23187	90	9	𝑁	𝑁	PROPN
brj-23187	90	10	∑	∑	PROPN
brj-23187	90	11	𝛷𝑁	𝛷𝑁	PROPN
brj-23187	90	12	i=1	i=1	PROPN
brj-23187	90	13	(	(	PUNCT
brj-23187	90	14	𝒙𝑖)𝛷(𝒙𝑖	𝒙𝑖)𝛷(𝒙𝑖	NOUN
brj-23187	90	15	)	)	PUNCT
brj-23187	90	16	t	t	NOUN
brj-23187	90	17	(	(	PUNCT
brj-23187	90	18	3	3	NUM
brj-23187	90	19	)	)	PUNCT
brj-23187	90	20	matrix	matrix	NOUN
brj-23187	90	21	𝐂f	𝐂f	PROPN
brj-23187	90	22	is	be	AUX
brj-23187	90	23	a	a	DET
brj-23187	90	24	square	square	ADJ
brj-23187	90	25	𝑛	𝑛	DET
brj-23187	90	26	×	×	NOUN
brj-23187	90	27	𝑛	𝑛	DET
brj-23187	90	28	matrix	matrix	NOUN
brj-23187	90	29	,	,	PUNCT
brj-23187	90	30	and	and	CCONJ
brj-23187	90	31	an	an	DET
brj-23187	90	32	eigenvector	eigenvector	NOUN
brj-23187	90	33	analysis	analysis	NOUN
brj-23187	90	34	was	be	AUX
brj-23187	90	35	conducted	conduct	VERB
brj-23187	90	36	(	(	PUNCT
brj-23187	90	37	kuang	kuang	PROPN
brj-23187	90	38	et	et	PROPN
brj-23187	90	39	al	al	PROPN
brj-23187	90	40	.	.	PROPN
brj-23187	90	41	2012	2012	NUM
brj-23187	90	42	)	)	PUNCT
brj-23187	90	43	.	.	PUNCT
brj-23187	91	1	letting	let	VERB
brj-23187	91	2	𝜆𝑘	𝜆𝑘	VERB
brj-23187	91	3	,	,	PUNCT
brj-23187	91	4	𝑽𝑘	𝑽𝑘	PROPN
brj-23187	91	5	represent	represent	VERB
brj-23187	91	6	the	the	DET
brj-23187	91	7	𝑘-th	𝑘-th	PROPN
brj-23187	91	8	eigenvalue	eigenvalue	NOUN
brj-23187	91	9	and	and	CCONJ
brj-23187	91	10	the	the	DET
brj-23187	91	11	corresponding	corresponding	ADJ
brj-23187	91	12	eigenvector	eigenvector	NOUN
brj-23187	91	13	of	of	ADP
brj-23187	91	14	𝐂f(where	𝐂f(where	X
brj-23187	91	15	𝑘	𝑘	X
brj-23187	91	16	=	=	SYM
brj-23187	91	17	1,2	1,2	NUM
brj-23187	91	18	,	,	PUNCT
brj-23187	91	19	⋯	⋯	NOUN
brj-23187	91	20	,	,	PUNCT
brj-23187	91	21	𝑛	𝑛	PROPN
brj-23187	91	22	)	)	PUNCT
brj-23187	91	23	,	,	PUNCT
brj-23187	91	24	one	one	PRON
brj-23187	91	25	obtains	obtain	VERB
brj-23187	91	26	:	:	PUNCT
brj-23187	91	27	𝜆𝑘𝑽𝑘	𝜆𝑘𝑽𝑘	X
brj-23187	91	28	=	=	SYM
brj-23187	92	1	𝐂f𝑽𝑘	𝐂f𝑽𝑘	NOUN
brj-23187	92	2	(	(	PUNCT
brj-23187	92	3	4	4	X
brj-23187	92	4	)	)	PUNCT
brj-23187	92	5	substituting	substitute	VERB
brj-23187	92	6	eq	eq	NOUN
brj-23187	92	7	.	.	PROPN
brj-23187	92	8	3	3	NUM
brj-23187	92	9	into	into	ADP
brj-23187	92	10	eq	eq	NOUN
brj-23187	92	11	.	.	PROPN
brj-23187	92	12	4	4	NUM
brj-23187	92	13	and	and	CCONJ
brj-23187	92	14	simplifying	simplifying	NOUN
brj-23187	92	15	,	,	PUNCT
brj-23187	92	16	one	one	NUM
brj-23187	92	17	obtains	obtain	VERB
brj-23187	92	18	eq	eq	NOUN
brj-23187	92	19	.	.	PROPN
brj-23187	92	20	5	5	NUM
brj-23187	92	21	:	:	PUNCT
brj-23187	92	22	𝑽𝑘	𝑽𝑘	PROPN
brj-23187	92	23	=	=	SYM
brj-23187	92	24	∑	∑	PUNCT
brj-23187	92	25	𝛷(𝒙𝑖	𝛷(𝒙𝑖	NOUN
brj-23187	92	26	)	)	PUNCT
brj-23187	92	27	𝛷(𝒙𝑖	𝛷(𝒙𝑖	NOUN
brj-23187	92	28	)	)	PUNCT
brj-23187	92	29	t𝑽𝑘	t𝑽𝑘	ADP
brj-23187	92	30	𝑁𝜆𝑘	𝑁𝜆𝑘	PROPN
brj-23187	92	31	𝑁	𝑁	PROPN
brj-23187	92	32	𝑖=1	𝑖=1	PROPN
brj-23187	92	33	(	(	PUNCT
brj-23187	92	34	5	5	X
brj-23187	92	35	)	)	PUNCT
brj-23187	92	36	the	the	DET
brj-23187	92	37	above	above	ADJ
brj-23187	92	38	equation	equation	NOUN
brj-23187	92	39	can	can	AUX
brj-23187	92	40	be	be	AUX
brj-23187	92	41	further	far	ADV
brj-23187	92	42	written	write	VERB
brj-23187	92	43	as	as	ADP
brj-23187	92	44	:	:	PUNCT
brj-23187	92	45	𝑽𝑘	𝑽𝑘	PROPN
brj-23187	92	46	=	=	PUNCT
brj-23187	92	47	∑	∑	PUNCT
brj-23187	92	48	𝛽𝑘𝑖	𝛽𝑘𝑖	VERB
brj-23187	92	49	𝑁	𝑁	PROPN
brj-23187	92	50	𝑖=1	𝑖=1	PROPN
brj-23187	92	51	𝛷(𝒙𝑖	𝛷(𝒙𝑖	NOUN
brj-23187	92	52	)	)	PUNCT
brj-23187	92	53	=	=	SYM
brj-23187	93	1	𝛷(𝑿)𝜷𝑘	𝛷(𝑿)𝜷𝑘	X
brj-23187	93	2	(	(	PUNCT
brj-23187	93	3	6	6	NUM
brj-23187	93	4	)	)	PUNCT
brj-23187	93	5	the	the	DET
brj-23187	93	6	column	column	NOUN
brj-23187	93	7	vector	vector	NOUN
brj-23187	93	8	𝜷𝑘	𝜷𝑘	NOUN
brj-23187	93	9	=	=	PUNCT
brj-23187	94	1	[	[	X
brj-23187	94	2	𝛽𝑘1	𝛽𝑘1	PROPN
brj-23187	94	3	,	,	PUNCT
brj-23187	94	4	𝛽𝑘2	𝛽𝑘2	X
brj-23187	94	5	,	,	PUNCT
brj-23187	94	6	⋯	⋯	PROPN
brj-23187	94	7	,	,	PUNCT
brj-23187	94	8	𝛽𝑘𝑁]t	𝛽𝑘𝑁]t	NOUN
brj-23187	94	9	is	be	AUX
brj-23187	94	10	substituted	substitute	VERB
brj-23187	94	11	into	into	ADP
brj-23187	94	12	eq	eq	PROPN
brj-23187	94	13	.	.	PROPN
brj-23187	94	14	4	4	NUM
brj-23187	94	15	and	and	CCONJ
brj-23187	94	16	multiplied	multiply	VERB
brj-23187	94	17	by	by	ADP
brj-23187	94	18	the	the	DET
brj-23187	94	19	left	left	NOUN
brj-23187	94	20	with	with	ADP
brj-23187	94	21	𝛷(𝑿)t	𝛷(𝑿)t	ADV
brj-23187	94	22	to	to	PART
brj-23187	94	23	obtain	obtain	VERB
brj-23187	94	24	:	:	PUNCT
brj-23187	94	25	𝜆𝑘𝛷(𝑿)t𝛷(𝑿)𝜷𝑘	𝜆𝑘𝛷(𝑿)t𝛷(𝑿)𝜷𝑘	X
brj-23187	94	26	=	=	SYM
brj-23187	94	27	1	1	NUM
brj-23187	94	28	𝑁	𝑁	PROPN
brj-23187	94	29	𝛷(𝑿)t𝛷(𝑿)𝛷(𝑿)t𝛷(𝑿)𝜷𝑘	𝛷(𝑿)t𝛷(𝑿)𝛷(𝑿)t𝛷(𝑿)𝜷𝑘	NOUN
brj-23187	94	30	(	(	PUNCT
brj-23187	94	31	7	7	NUM
brj-23187	94	32	)	)	PUNCT
brj-23187	94	33	the	the	DET
brj-23187	94	34	𝑁	𝑁	PROPN
brj-23187	94	35	×	×	NOUN
brj-23187	94	36	𝑁	𝑁	ADJ
brj-23187	94	37	dimensional	dimensional	ADJ
brj-23187	94	38	kernel	kernel	NOUN
brj-23187	94	39	matrix	matrix	NOUN
brj-23187	94	40	𝑲	𝑲	NOUN
brj-23187	94	41	was	be	AUX
brj-23187	94	42	introduced	introduce	VERB
brj-23187	94	43	,	,	PUNCT
brj-23187	94	44	and	and	CCONJ
brj-23187	94	45	the	the	DET
brj-23187	94	46	value	value	NOUN
brj-23187	94	47	of	of	ADP
brj-23187	94	48	the	the	DET
brj-23187	94	49	𝑖	𝑖	X
brj-23187	94	50	row	row	NOUN
brj-23187	94	51	𝑗	𝑗	PRON
brj-23187	94	52	column	column	NOUN
brj-23187	94	53	𝑖	𝑖	NOUN
brj-23187	94	54	and	and	CCONJ
brj-23187	94	55	row	row	VERB
brj-23187	94	56	𝑗	𝑗	INTJ
brj-23187	94	57	was	be	AUX
brj-23187	94	58	computed	compute	VERB
brj-23187	94	59	using	use	VERB
brj-23187	94	60	the	the	DET
brj-23187	94	61	following	follow	VERB
brj-23187	94	62	kernel	kernel	PROPN
brj-23187	94	63	function	function	PROPN
brj-23187	94	64	(	(	PUNCT
brj-23187	94	65	anowar	anowar	NOUN
brj-23187	94	66	and	and	CCONJ
brj-23187	94	67	sadaoui	sadaoui	VERB
brj-23187	94	68	2021	2021	NUM
brj-23187	94	69	)	)	PUNCT
brj-23187	94	70	,	,	PUNCT
brj-23187	94	71	𝑲𝑖,𝑗	𝑲𝑖,𝑗	PROPN
brj-23187	94	72	=	=	SYM
brj-23187	94	73	𝛷(𝒙𝑖	𝛷(𝒙𝑖	PROPN
brj-23187	94	74	)	)	PUNCT
brj-23187	94	75	t𝛷(𝒙𝑗	t𝛷(𝒙𝑗	NOUN
brj-23187	94	76	)	)	PUNCT
brj-23187	94	77	=	=	SYM
brj-23187	94	78	𝜿(𝒙𝑖	𝜿(𝒙𝑖	NOUN
brj-23187	94	79	,	,	PUNCT
brj-23187	94	80	𝒙𝑗	𝒙𝑗	NOUN
brj-23187	94	81	)	)	PUNCT
brj-23187	94	82	(	(	PUNCT
brj-23187	94	83	8)	8)	NUM
brj-23187	94	84	where	where	SCONJ
brj-23187	94	85	𝜅(∙,∙	𝜅(∙,∙	NOUN
brj-23187	94	86	)	)	PUNCT
brj-23187	94	87	is	be	AUX
brj-23187	94	88	the	the	DET
brj-23187	94	89	kernel	kernel	PROPN
brj-23187	94	90	function	function	NOUN
brj-23187	94	91	.	.	PUNCT
brj-23187	95	1	the	the	DET
brj-23187	95	2	rbf	rbf	PROPN
brj-23187	95	3	kernel	kernel	PROPN
brj-23187	95	4	function	function	PROPN
brj-23187	95	5	𝜅(𝒙𝑖	𝜅(𝒙𝑖	PROPN
brj-23187	95	6	,	,	PUNCT
brj-23187	95	7	𝒙𝑗	𝒙𝑗	X
brj-23187	95	8	)	)	PUNCT
brj-23187	95	9	=	=	NOUN
brj-23187	95	10	exp	exp	NOUN
brj-23187	95	11	(	(	PUNCT
brj-23187	95	12	−	−	PROPN
brj-23187	95	13	∥∥𝒙𝑖−𝒙𝑗∥∥	∥∥𝒙𝑖−𝒙𝑗∥∥	PROPN
brj-23187	95	14	2	2	NUM
brj-23187	95	15	2𝜎2	2𝜎2	NUM
brj-23187	95	16	)	)	PUNCT
brj-23187	95	17	can	can	AUX
brj-23187	95	18	be	be	AUX
brj-23187	95	19	selected	select	VERB
brj-23187	95	20	,	,	PUNCT
brj-23187	95	21	𝜎	𝜎	PROPN
brj-23187	95	22	is	be	AUX
brj-23187	95	23	the	the	DET
brj-23187	95	24	kernel	kernel	NOUN
brj-23187	95	25	width	width	NOUN
brj-23187	95	26	,	,	PUNCT
brj-23187	95	27	and	and	CCONJ
brj-23187	95	28	the	the	DET
brj-23187	95	29	vector	vector	NOUN
brj-23187	95	30	norm	norm	NOUN
brj-23187	95	31	∥∥𝒙𝑖	∥∥𝒙𝑖	PROPN
brj-23187	95	32	−	−	PROPN
brj-23187	95	33	𝒙𝑗∥∥	𝒙𝑗∥∥	PROPN
brj-23187	95	34	is	be	AUX
brj-23187	95	35	the	the	DET
brj-23187	95	36	euclidean	euclidean	ADJ
brj-23187	95	37	distance	distance	NOUN
brj-23187	95	38	between	between	ADP
brj-23187	95	39	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	95	40	and	and	CCONJ
brj-23187	95	41	𝒙𝑗.	𝒙𝑗.	ADJ
brj-23187	95	42	substituting	substitute	VERB
brj-23187	95	43	𝑲	𝑲	NOUN
brj-23187	95	44	into	into	ADP
brj-23187	95	45	eq	eq	ADP
brj-23187	95	46	.	.	PROPN
brj-23187	95	47	7	7	NUM
brj-23187	95	48	,	,	PUNCT
brj-23187	95	49	one	one	PRON
brj-23187	95	50	obtains	obtain	VERB
brj-23187	95	51	:	:	PUNCT
brj-23187	95	52	𝜆𝑘𝑁𝑲𝜷𝑘	𝜆𝑘𝑁𝑲𝜷𝑘	X
brj-23187	95	53	=	=	PUNCT
brj-23187	95	54	𝑲2𝜷𝑘	𝑲2𝜷𝑘	X
brj-23187	95	55	(	(	PUNCT
brj-23187	95	56	9	9	X
brj-23187	95	57	)	)	PUNCT
brj-23187	95	58	this	this	PRON
brj-23187	95	59	can	can	AUX
brj-23187	95	60	be	be	AUX
brj-23187	95	61	simplified	simplify	VERB
brj-23187	95	62	to	to	PART
brj-23187	95	63	get	get	VERB
brj-23187	95	64	:	:	PUNCT
brj-23187	95	65	𝜆𝑘𝑁𝜷𝑘	𝜆𝑘𝑁𝜷𝑘	X
brj-23187	96	1	=	=	PUNCT
brj-23187	96	2	𝑲𝜷𝑘	𝑲𝜷𝑘	PROPN
brj-23187	96	3	(	(	PUNCT
brj-23187	96	4	10	10	NUM
brj-23187	96	5	)	)	PUNCT
brj-23187	96	6	the	the	DET
brj-23187	96	7	kernel	kernel	PROPN
brj-23187	96	8	matrix	matrix	NOUN
brj-23187	96	9	𝑲	𝑲	NOUN
brj-23187	96	10	in	in	ADP
brj-23187	96	11	the	the	DET
brj-23187	96	12	above	above	ADJ
brj-23187	96	13	equation	equation	NOUN
brj-23187	96	14	can	can	AUX
brj-23187	96	15	be	be	AUX
brj-23187	96	16	computed	compute	VERB
brj-23187	96	17	using	use	VERB
brj-23187	96	18	the	the	DET
brj-23187	96	19	input	input	NOUN
brj-23187	96	20	sample	sample	NOUN
brj-23187	96	21	data	datum	NOUN
brj-23187	96	22	,	,	PUNCT
brj-23187	96	23	as	as	ADP
brj-23187	96	24	per	per	ADP
brj-23187	96	25	eq	eq	NOUN
brj-23187	96	26	.	.	PROPN
brj-23187	96	27	8	8	NUM
brj-23187	96	28	.	.	PUNCT
brj-23187	97	1	through	through	ADP
brj-23187	97	2	solving	solve	VERB
brj-23187	97	3	the	the	DET
brj-23187	97	4	eigenvalues	eigenvalue	NOUN
brj-23187	97	5	and	and	CCONJ
brj-23187	97	6	eigenvectors	eigenvector	NOUN
brj-23187	97	7	of	of	ADP
brj-23187	97	8	the	the	DET
brj-23187	97	9	kernel	kernel	PROPN
brj-23187	97	10	matrix	matrix	NOUN
brj-23187	97	11	𝑲	𝑲	NOUN
brj-23187	97	12	,	,	PUNCT
brj-23187	97	13	𝜆𝑘，𝜷𝑘	𝜆𝑘，𝜷𝑘	NOUN
brj-23187	97	14	,	,	PUNCT
brj-23187	97	15	𝑘	𝑘	NOUN
brj-23187	97	16	=	=	SYM
brj-23187	97	17	1,2	1,2	NUM
brj-23187	97	18	,	,	PUNCT
brj-23187	97	19	⋯	⋯	PROPN
brj-23187	97	20	,	,	PUNCT
brj-23187	97	21	𝑛	𝑛	PROPN
brj-23187	97	22	can	can	AUX
brj-23187	97	23	be	be	AUX
brj-23187	97	24	obtained	obtain	VERB
brj-23187	97	25	(	(	PUNCT
brj-23187	97	26	qin	qin	PROPN
brj-23187	97	27	2012	2012	NUM
brj-23187	97	28	)	)	PUNCT
brj-23187	97	29	.	.	PUNCT
brj-23187	98	1	the	the	DET
brj-23187	98	2	authors	author	NOUN
brj-23187	98	3	sorted	sort	VERB
brj-23187	98	4	the	the	DET
brj-23187	98	5	eigenvalues	eigenvalue	NOUN
brj-23187	98	6	in	in	ADP
brj-23187	98	7	descending	descend	VERB
brj-23187	98	8	order	order	NOUN
brj-23187	98	9	to	to	PART
brj-23187	98	10	reduce	reduce	VERB
brj-23187	98	11	the	the	DET
brj-23187	98	12	data	datum	NOUN
brj-23187	98	13	dimensionality	dimensionality	NOUN
brj-23187	98	14	and	and	CCONJ
brj-23187	98	15	adjusted	adjust	VERB
brj-23187	98	16	the	the	DET
brj-23187	98	17	corresponding	corresponding	ADJ
brj-23187	98	18	feature	feature	NOUN
brj-23187	98	19	vectors	vector	NOUN
brj-23187	98	20	accordingly	accordingly	ADV
brj-23187	98	21	.	.	PUNCT
brj-23187	99	1	next	next	ADV
brj-23187	99	2	,	,	PUNCT
brj-23187	99	3	the	the	DET
brj-23187	99	4	kernel	kernel	PROPN
brj-23187	99	5	principal	principal	PROPN
brj-23187	99	6	component	component	NOUN
brj-23187	99	7	was	be	AUX
brj-23187	99	8	selected	select	VERB
brj-23187	99	9	based	base	VERB
brj-23187	99	10	on	on	ADP
brj-23187	99	11	the	the	DET
brj-23187	99	12	cumulative	cumulative	ADJ
brj-23187	99	13	contribution	contribution	NOUN
brj-23187	99	14	associated	associate	VERB
brj-23187	99	15	with	with	ADP
brj-23187	99	16	the	the	DET
brj-23187	99	17	eigenvalue	eigenvalue	PROPN
brj-23187	99	18	(	(	PUNCT
brj-23187	99	19	the	the	DET
brj-23187	99	20	ratio	ratio	NOUN
brj-23187	99	21	of	of	ADP
brj-23187	99	22	the	the	DET
brj-23187	99	23	variance	variance	NOUN
brj-23187	99	24	of	of	ADP
brj-23187	99	25	the	the	DET
brj-23187	99	26	principal	principal	ADJ
brj-23187	99	27	component	component	NOUN
brj-23187	99	28	to	to	ADP
brj-23187	99	29	the	the	DET
brj-23187	99	30	total	total	ADJ
brj-23187	99	31	variance	variance	NOUN
brj-23187	99	32	of	of	ADP
brj-23187	99	33	the	the	DET
brj-23187	99	34	investigated	investigate	VERB
brj-23187	99	35	variables	variable	NOUN
brj-23187	99	36	)	)	PUNCT
brj-23187	99	37	.	.	PUNCT
brj-23187	100	1	the	the	DET
brj-23187	100	2	cumulative	cumulative	ADJ
brj-23187	100	3	contribution	contribution	NOUN
brj-23187	100	4	value	value	NOUN
brj-23187	100	5	was	be	AUX
brj-23187	100	6	determined	determine	VERB
brj-23187	100	7	by	by	ADP
brj-23187	100	8	adding	add	VERB
brj-23187	100	9	an	an	DET
brj-23187	100	10	eigenvalue	eigenvalue	NOUN
brj-23187	100	11	's	's	PART
brj-23187	100	12	contribution	contribution	NOUN
brj-23187	100	13	to	to	ADP
brj-23187	100	14	the	the	DET
brj-23187	100	15	preceding	precede	VERB
brj-23187	100	16	eigenvalue	eigenvalue	PROPN
brj-23187	100	17	's	's	PART
brj-23187	100	18	cumulative	cumulative	ADJ
brj-23187	100	19	value	value	NOUN
brj-23187	100	20	.	.	PUNCT
brj-23187	101	1	in	in	ADP
brj-23187	101	2	this	this	DET
brj-23187	101	3	study	study	NOUN
brj-23187	101	4	,	,	PUNCT
brj-23187	101	5	the	the	DET
brj-23187	101	6	authors	author	NOUN
brj-23187	101	7	selected	select	VERB
brj-23187	101	8	feature	feature	NOUN
brj-23187	101	9	vectors	vector	NOUN
brj-23187	101	10	corresponding	correspond	VERB
brj-23187	101	11	to	to	AUX
brj-23187	101	12	eigenvalues	eigenvalues	VERB
brj-23187	101	13	with	with	ADP
brj-23187	101	14	a	a	DET
brj-23187	101	15	cumulative	cumulative	ADJ
brj-23187	101	16	contribution	contribution	NOUN
brj-23187	101	17	above	above	ADP
brj-23187	101	18	95	95	NUM
brj-23187	101	19	%	%	NOUN
brj-23187	101	20	,	,	PUNCT
brj-23187	101	21	and	and	CCONJ
brj-23187	101	22	z	z	NOUN
brj-23187	101	23	principal	principal	ADJ
brj-23187	101	24	components	component	NOUN
brj-23187	101	25	were	be	AUX
brj-23187	101	26	determined	determine	VERB
brj-23187	101	27	to	to	PART
brj-23187	101	28	achieve	achieve	VERB
brj-23187	101	29	data	datum	NOUN
brj-23187	101	30	dimensionality	dimensionality	NOUN
brj-23187	101	31	reduction	reduction	NOUN
brj-23187	101	32	.	.	PUNCT
brj-23187	102	1	for	for	ADP
brj-23187	102	2	any	any	DET
brj-23187	102	3	input	input	NOUN
brj-23187	102	4	vector	vector	NOUN
brj-23187	102	5	𝒙	𝒙	PROPN
brj-23187	102	6	,	,	PUNCT
brj-23187	102	7	one	one	PRON
brj-23187	102	8	can	can	AUX
brj-23187	102	9	determine	determine	VERB
brj-23187	102	10	the	the	DET
brj-23187	102	11	𝑧	𝑧	PRON
brj-23187	102	12	principal	principal	ADJ
brj-23187	102	13	components	component	NOUN
brj-23187	102	14	as	as	ADP
brj-23187	102	15	:	:	PUNCT
brj-23187	102	16	𝑝𝑙(𝒙	𝑝𝑙(𝒙	NUM
brj-23187	102	17	)	)	PUNCT
brj-23187	102	18	=	=	PUNCT
brj-23187	102	19	∑	∑	PUNCT
brj-23187	102	20	𝛽𝑘𝑖	𝛽𝑘𝑖	VERB
brj-23187	102	21	𝑁	𝑁	PROPN
brj-23187	102	22	𝑖=1	𝑖=1	PROPN
brj-23187	102	23	𝜅(𝒙	𝜅(𝒙	PROPN
brj-23187	102	24	,	,	PUNCT
brj-23187	102	25	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	102	26	)	)	PUNCT
brj-23187	102	27	(	(	PUNCT
brj-23187	102	28	11	11	NUM
brj-23187	102	29	)	)	PUNCT
brj-23187	102	30	where	where	SCONJ
brj-23187	102	31	𝑙	𝑙	NOUN
brj-23187	102	32	=	=	SYM
brj-23187	102	33	1,2	1,2	NUM
brj-23187	102	34	,	,	PUNCT
brj-23187	102	35	⋯	⋯	PROPN
brj-23187	102	36	,	,	PUNCT
brj-23187	102	37	𝑧.	𝑧.	PROPN
brj-23187	102	38	peer	peer	NOUN
brj-23187	102	39	-	-	PUNCT
brj-23187	102	40	reviewed	review	VERB
brj-23187	102	41	article	article	NOUN
brj-23187	102	42	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	102	43	fu	fu	PROPN
brj-23187	102	44	et	et	PROPN
brj-23187	102	45	al	al	PROPN
brj-23187	102	46	.	.	PROPN
brj-23187	103	1	(	(	PUNCT
brj-23187	103	2	2024	2024	NUM
brj-23187	103	3	)	)	PUNCT
brj-23187	103	4	.	.	PUNCT
brj-23187	104	1	“	"	PUNCT
brj-23187	104	2	predicting	predict	VERB
brj-23187	104	3	enzymatic	enzymatic	ADJ
brj-23187	104	4	hydrolysis	hydrolysis	NOUN
brj-23187	104	5	,	,	PUNCT
brj-23187	104	6	”	"	PUNCT
brj-23187	104	7	bioresources	bioresource	NOUN
brj-23187	104	8	19(2	19(2	NUM
brj-23187	104	9	)	)	PUNCT
brj-23187	104	10	,	,	PUNCT
brj-23187	104	11	3505	3505	NUM
brj-23187	104	12	-	-	SYM
brj-23187	104	13	3519	3519	NUM
brj-23187	104	14	.	.	PUNCT
brj-23187	105	1	3510	3510	NUM
brj-23187	105	2	furthermore	furthermore	ADV
brj-23187	105	3	,	,	PUNCT
brj-23187	105	4	if	if	SCONJ
brj-23187	105	5	𝑿	𝑿	PROPN
brj-23187	105	6	does	do	AUX
brj-23187	105	7	not	not	PART
brj-23187	105	8	satisfy	satisfy	VERB
brj-23187	105	9	the	the	DET
brj-23187	105	10	centralisation	centralisation	NOUN
brj-23187	105	11	requirement	requirement	NOUN
brj-23187	105	12	in	in	ADP
brj-23187	105	13	feature	feature	NOUN
brj-23187	105	14	space	space	NOUN
brj-23187	105	15	f	f	NOUN
brj-23187	105	16	,	,	PUNCT
brj-23187	105	17	it	it	PRON
brj-23187	105	18	is	be	AUX
brj-23187	105	19	sufficient	sufficient	ADJ
brj-23187	105	20	to	to	PART
brj-23187	105	21	substitute	substitute	VERB
brj-23187	105	22	𝑲	𝑲	NOUN
brj-23187	105	23	in	in	ADP
brj-23187	105	24	eq	eq	ADP
brj-23187	105	25	.	.	PROPN
brj-23187	105	26	12	12	NUM
brj-23187	105	27	with	with	ADP
brj-23187	105	28	𝑲′	𝑲′	ADJ
brj-23187	105	29	computed	compute	VERB
brj-23187	105	30	using	use	VERB
brj-23187	105	31	the	the	DET
brj-23187	105	32	following	follow	VERB
brj-23187	105	33	equation	equation	NOUN
brj-23187	105	34	:	:	PUNCT
brj-23187	105	35	𝑲′	𝑲′	ADJ
brj-23187	105	36	=	=	SYM
brj-23187	106	1	𝑲	𝑲	PRON
brj-23187	106	2	−	−	PROPN
brj-23187	106	3	𝑰𝑁𝑲	𝑰𝑁𝑲	PROPN
brj-23187	106	4	−	−	PROPN
brj-23187	106	5	𝑲𝑰𝑁	𝑲𝑰𝑁	PROPN
brj-23187	106	6	+	+	CCONJ
brj-23187	106	7	𝑰𝑁𝑲𝑰𝑁	𝑰𝑁𝑲𝑰𝑁	ADJ
brj-23187	106	8	(	(	PUNCT
brj-23187	106	9	12	12	NUM
brj-23187	106	10	)	)	PUNCT
brj-23187	106	11	where	where	SCONJ
brj-23187	106	12	𝑰𝑁	𝑰𝑁	PROPN
brj-23187	106	13	is	be	AUX
brj-23187	106	14	an	an	DET
brj-23187	106	15	𝑁	𝑁	PROPN
brj-23187	106	16	×	×	NOUN
brj-23187	106	17	𝑁	𝑁	ADJ
brj-23187	106	18	dimensional	dimensional	ADJ
brj-23187	106	19	matrix	matrix	NOUN
brj-23187	106	20	,	,	PUNCT
brj-23187	106	21	and	and	CCONJ
brj-23187	106	22	each	each	DET
brj-23187	106	23	element	element	NOUN
brj-23187	106	24	is	be	AUX
brj-23187	106	25	1	1	NUM
brj-23187	106	26	𝑁	𝑁	PROPN
brj-23187	106	27	.	.	PUNCT
brj-23187	107	1	training	train	VERB
brj-23187	107	2	the	the	DET
brj-23187	107	3	lssvm	lssvm	NOUN
brj-23187	107	4	model	model	NOUN
brj-23187	107	5	support	support	NOUN
brj-23187	107	6	vector	vector	NOUN
brj-23187	107	7	machine	machine	NOUN
brj-23187	107	8	(	(	PUNCT
brj-23187	107	9	svm	svm	PROPN
brj-23187	107	10	)	)	PUNCT
brj-23187	107	11	is	be	AUX
brj-23187	107	12	an	an	DET
brj-23187	107	13	effective	effective	ADJ
brj-23187	107	14	approach	approach	NOUN
brj-23187	107	15	that	that	PRON
brj-23187	107	16	excels	excel	VERB
brj-23187	107	17	at	at	ADP
brj-23187	107	18	handling	handle	VERB
brj-23187	107	19	small	small	ADJ
brj-23187	107	20	samples	sample	NOUN
brj-23187	107	21	and	and	CCONJ
brj-23187	107	22	problems	problem	NOUN
brj-23187	107	23	that	that	PRON
brj-23187	107	24	are	be	AUX
brj-23187	107	25	linearly	linearly	ADV
brj-23187	107	26	separable	separable	ADJ
brj-23187	107	27	.	.	PUNCT
brj-23187	108	1	building	build	VERB
brj-23187	108	2	on	on	ADP
brj-23187	108	3	the	the	DET
brj-23187	108	4	svm	svm	PROPN
brj-23187	108	5	,	,	PUNCT
brj-23187	108	6	the	the	DET
brj-23187	108	7	lssvm	lssvm	NOUN
brj-23187	108	8	method	method	NOUN
brj-23187	108	9	was	be	AUX
brj-23187	108	10	designed	design	VERB
brj-23187	108	11	to	to	PART
brj-23187	108	12	address	address	VERB
brj-23187	108	13	nonlinear	nonlinear	ADJ
brj-23187	108	14	problems	problem	NOUN
brj-23187	108	15	,	,	PUNCT
brj-23187	108	16	offering	offer	VERB
brj-23187	108	17	the	the	DET
brj-23187	108	18	advantage	advantage	NOUN
brj-23187	108	19	of	of	ADP
brj-23187	108	20	reduced	reduced	ADJ
brj-23187	108	21	computational	computational	ADJ
brj-23187	108	22	complexity	complexity	NOUN
brj-23187	108	23	.	.	PUNCT
brj-23187	109	1	compared	compare	VERB
brj-23187	109	2	to	to	ADP
brj-23187	109	3	the	the	DET
brj-23187	109	4	svm	svm	PROPN
brj-23187	109	5	,	,	PUNCT
brj-23187	109	6	the	the	DET
brj-23187	109	7	lssvm	lssvm	NOUN
brj-23187	109	8	employs	employ	VERB
brj-23187	109	9	distinct	distinct	ADJ
brj-23187	109	10	optimisation	optimisation	NOUN
brj-23187	109	11	objectives	objective	NOUN
brj-23187	109	12	,	,	PUNCT
brj-23187	109	13	incorporates	incorporate	VERB
brj-23187	109	14	equality	equality	NOUN
brj-23187	109	15	constraints	constraint	NOUN
brj-23187	109	16	,	,	PUNCT
brj-23187	109	17	and	and	CCONJ
brj-23187	109	18	substitutes	substitute	VERB
brj-23187	109	19	the	the	DET
brj-23187	109	20	original	original	ADJ
brj-23187	109	21	loss	loss	NOUN
brj-23187	109	22	function	function	NOUN
brj-23187	109	23	with	with	ADP
brj-23187	109	24	the	the	DET
brj-23187	109	25	sum	sum	NOUN
brj-23187	109	26	of	of	ADP
brj-23187	109	27	squared	square	VERB
brj-23187	109	28	errors	error	NOUN
brj-23187	109	29	(	(	PUNCT
brj-23187	109	30	tian	tian	ADJ
brj-23187	109	31	2020	2020	NUM
brj-23187	109	32	)	)	PUNCT
brj-23187	109	33	.	.	PUNCT
brj-23187	110	1	to	to	PART
brj-23187	110	2	illustrate	illustrate	VERB
brj-23187	110	3	this	this	PRON
brj-23187	110	4	,	,	PUNCT
brj-23187	110	5	the	the	DET
brj-23187	110	6	authors	author	NOUN
brj-23187	110	7	analysed	analyse	VERB
brj-23187	110	8	the	the	DET
brj-23187	110	9	extent	extent	NOUN
brj-23187	110	10	of	of	ADP
brj-23187	110	11	lignin	lignin	NOUN
brj-23187	110	12	removal	removal	NOUN
brj-23187	110	13	.	.	PUNCT
brj-23187	111	1	here	here	ADV
brj-23187	111	2	,	,	PUNCT
brj-23187	111	3	the	the	DET
brj-23187	111	4	𝑧	𝑧	DET
brj-23187	111	5	principal	principal	ADJ
brj-23187	111	6	components	component	NOUN
brj-23187	111	7	,	,	PUNCT
brj-23187	111	8	obtained	obtain	VERB
brj-23187	111	9	after	after	ADP
brj-23187	111	10	gra	gra	PROPN
brj-23187	111	11	variable	variable	PROPN
brj-23187	111	12	screening	screening	NOUN
brj-23187	111	13	and	and	CCONJ
brj-23187	111	14	kpca	kpca	NOUN
brj-23187	111	15	dimensionality	dimensionality	NOUN
brj-23187	111	16	reduction	reduction	NOUN
brj-23187	111	17	,	,	PUNCT
brj-23187	111	18	serve	serve	VERB
brj-23187	111	19	as	as	ADP
brj-23187	111	20	the	the	DET
brj-23187	111	21	input	input	NOUN
brj-23187	111	22	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	112	1	=	=	PUNCT
brj-23187	113	1	[	[	X
brj-23187	113	2	𝑝1	𝑝1	NOUN
brj-23187	113	3	,	,	PUNCT
brj-23187	113	4	𝑝2	𝑝2	NOUN
brj-23187	113	5	,	,	PUNCT
brj-23187	113	6	⋯	⋯	PROPN
brj-23187	113	7	,	,	PUNCT
brj-23187	113	8	𝑝𝑧	𝑝𝑧	X
brj-23187	113	9	]	]	PUNCT
brj-23187	113	10	.	.	PUNCT
brj-23187	114	1	the	the	DET
brj-23187	114	2	associated	associated	ADJ
brj-23187	114	3	output	output	NOUN
brj-23187	114	4	is	be	AUX
brj-23187	114	5	𝑦𝑖	𝑦𝑖	PROPN
brj-23187	114	6	,	,	PUNCT
brj-23187	114	7	represented	represent	VERB
brj-23187	114	8	by	by	ADP
brj-23187	114	9	𝜓1	𝜓1	NOUN
brj-23187	114	10	.	.	PUNCT
brj-23187	115	1	this	this	DET
brj-23187	115	2	pair	pair	NOUN
brj-23187	115	3	,	,	PUNCT
brj-23187	115	4	{	{	PUNCT
brj-23187	115	5	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	115	6	,	,	PUNCT
brj-23187	115	7	𝑦𝑖	𝑦𝑖	PROPN
brj-23187	115	8	}	}	PUNCT
brj-23187	115	9	,	,	PUNCT
brj-23187	115	10	𝑖	𝑖	SYM
brj-23187	115	11	=	=	SYM
brj-23187	115	12	1,2	1,2	NUM
brj-23187	115	13	,	,	PUNCT
brj-23187	115	14	⋯	⋯	PROPN
brj-23187	115	15	,	,	PUNCT
brj-23187	115	16	𝑁	𝑁	PROPN
brj-23187	115	17	,	,	PUNCT
brj-23187	115	18	forms	form	VERB
brj-23187	115	19	the	the	DET
brj-23187	115	20	training	training	NOUN
brj-23187	115	21	set	set	VERB
brj-23187	115	22	for	for	ADP
brj-23187	115	23	lssvm	lssvm	NOUN
brj-23187	115	24	modelling	modelling	NOUN
brj-23187	115	25	,	,	PUNCT
brj-23187	115	26	leading	lead	VERB
brj-23187	115	27	to	to	ADP
brj-23187	115	28	the	the	DET
brj-23187	115	29	construction	construction	NOUN
brj-23187	115	30	of	of	ADP
brj-23187	115	31	the	the	DET
brj-23187	115	32	following	follow	VERB
brj-23187	115	33	optimisation	optimisation	NOUN
brj-23187	115	34	problem	problem	NOUN
brj-23187	115	35	:	:	PUNCT
brj-23187	115	36	{	{	PUNCT
brj-23187	115	37	argmin	argmin	NOUN
brj-23187	115	38	𝝎,𝝃,𝑏	𝝎,𝝃,𝑏	PROPN
brj-23187	115	39	𝑅(𝝎	𝑅(𝝎	PROPN
brj-23187	115	40	,	,	PUNCT
brj-23187	115	41	𝝃	𝝃	PROPN
brj-23187	115	42	)	)	PUNCT
brj-23187	115	43	=	=	SYM
brj-23187	115	44	1	1	NUM
brj-23187	115	45	2	2	NUM
brj-23187	115	46	𝝎t𝝎	𝝎t𝝎	NOUN
brj-23187	115	47	+	+	CCONJ
brj-23187	115	48	1	1	NUM
brj-23187	115	49	2	2	NUM
brj-23187	115	50	𝑐	𝑐	NOUN
brj-23187	115	51	∑	∑	PUNCT
brj-23187	115	52	𝜉𝑖	𝜉𝑖	ADP
brj-23187	115	53	𝑁	𝑁	PROPN
brj-23187	115	54	𝑖=1	𝑖=1	PROPN
brj-23187	115	55	𝑠.	𝑠.	NOUN
brj-23187	115	56	𝑡.	𝑡.	NOUN
brj-23187	115	57	𝑦𝑖	𝑦𝑖	PROPN
brj-23187	116	1	=	=	PUNCT
brj-23187	116	2	𝝎t𝜑(𝒙𝑖	𝝎t𝜑(𝒙𝑖	X
brj-23187	116	3	)	)	PUNCT
brj-23187	117	1	+	+	CCONJ
brj-23187	117	2	𝑏	𝑏	PROPN
brj-23187	117	3	+	+	CCONJ
brj-23187	117	4	𝜉𝑖	𝜉𝑖	ADV
brj-23187	117	5	,	,	PUNCT
brj-23187	117	6	𝑖	𝑖	NOUN
brj-23187	117	7	=	=	SYM
brj-23187	117	8	1,2	1,2	NUM
brj-23187	117	9	,	,	PUNCT
brj-23187	117	10	⋯	⋯	VERB
brj-23187	117	11	,	,	PUNCT
brj-23187	117	12	𝑁	𝑁	PROPN
brj-23187	117	13	(	(	PUNCT
brj-23187	117	14	13	13	NUM
brj-23187	117	15	)	)	PUNCT
brj-23187	117	16	where	where	SCONJ
brj-23187	117	17	𝑅(𝝎	𝑅(𝝎	ADV
brj-23187	117	18	,	,	PUNCT
brj-23187	117	19	𝝃	𝝃	NOUN
brj-23187	117	20	)	)	PUNCT
brj-23187	117	21	represents	represent	VERB
brj-23187	117	22	the	the	DET
brj-23187	117	23	loss	loss	NOUN
brj-23187	117	24	function	function	NOUN
brj-23187	117	25	,	,	PUNCT
brj-23187	117	26	𝝎	𝝎	PRON
brj-23187	117	27	denotes	denote	VERB
brj-23187	117	28	the	the	DET
brj-23187	117	29	weight	weight	NOUN
brj-23187	117	30	parameter	parameter	NOUN
brj-23187	117	31	,	,	PUNCT
brj-23187	117	32	𝝃	𝝃	PROPN
brj-23187	118	1	=	=	PUNCT
brj-23187	119	1	[	[	X
brj-23187	119	2	𝜉𝑖	𝜉𝑖	X
brj-23187	119	3	]	]	X
brj-23187	119	4	,	,	PUNCT
brj-23187	119	5	𝑖	𝑖	SYM
brj-23187	119	6	=	=	SYM
brj-23187	119	7	1,2	1,2	NUM
brj-23187	119	8	,	,	PUNCT
brj-23187	119	9	…	…	PUNCT
brj-23187	119	10	,	,	PUNCT
brj-23187	119	11	𝑁	𝑁	PROPN
brj-23187	119	12	,	,	PUNCT
brj-23187	119	13	signifies	signify	VERB
brj-23187	119	14	the	the	DET
brj-23187	119	15	error	error	NOUN
brj-23187	119	16	variable	variable	NOUN
brj-23187	119	17	with	with	ADP
brj-23187	119	18	𝜉𝑖	𝜉𝑖	PRON
brj-23187	119	19	as	as	ADP
brj-23187	119	20	its	its	PRON
brj-23187	119	21	component	component	NOUN
brj-23187	119	22	,	,	PUNCT
brj-23187	119	23	𝑏	𝑏	PROPN
brj-23187	119	24	indicates	indicate	VERB
brj-23187	119	25	the	the	DET
brj-23187	119	26	deviation	deviation	NOUN
brj-23187	119	27	term	term	NOUN
brj-23187	119	28	,	,	PUNCT
brj-23187	119	29	and	and	CCONJ
brj-23187	119	30	𝑐	𝑐	X
brj-23187	119	31	>	>	SYM
brj-23187	119	32	0	0	NUM
brj-23187	119	33	serves	serve	VERB
brj-23187	119	34	as	as	ADP
brj-23187	119	35	the	the	DET
brj-23187	119	36	penalty	penalty	NOUN
brj-23187	119	37	coefficient	coefficient	NOUN
brj-23187	119	38	.	.	PUNCT
brj-23187	120	1	to	to	PART
brj-23187	120	2	solve	solve	VERB
brj-23187	120	3	the	the	DET
brj-23187	120	4	optimisation	optimisation	NOUN
brj-23187	120	5	problem	problem	NOUN
brj-23187	120	6	,	,	PUNCT
brj-23187	120	7	a	a	DET
brj-23187	120	8	lagrangian	lagrangian	ADJ
brj-23187	120	9	function	function	NOUN
brj-23187	120	10	is	be	AUX
brj-23187	120	11	constructed	construct	VERB
brj-23187	120	12	(	(	PUNCT
brj-23187	120	13	chen	chen	PROPN
brj-23187	120	14	and	and	CCONJ
brj-23187	120	15	zhou	zhou	PROPN
brj-23187	120	16	2018	2018	NUM
brj-23187	120	17	):	):	PUNCT
brj-23187	120	18	𝐿(𝝎	𝐿(𝝎	PROPN
brj-23187	120	19	,	,	PUNCT
brj-23187	120	20	𝑏	𝑏	NOUN
brj-23187	120	21	,	,	PUNCT
brj-23187	120	22	𝝃	𝝃	PROPN
brj-23187	120	23	,	,	PUNCT
brj-23187	120	24	𝜶	𝜶	NOUN
brj-23187	120	25	)	)	PUNCT
brj-23187	120	26	=	=	SYM
brj-23187	120	27	1	1	NUM
brj-23187	120	28	2	2	NUM
brj-23187	120	29	𝝎t𝝎	𝝎t𝝎	NOUN
brj-23187	120	30	+	+	CCONJ
brj-23187	120	31	1	1	NUM
brj-23187	120	32	2	2	NUM
brj-23187	120	33	𝑐	𝑐	NOUN
brj-23187	120	34	∑	∑	PUNCT
brj-23187	120	35	𝜉𝑖	𝜉𝑖	ADP
brj-23187	120	36	2𝑁	2𝑁	ADJ
brj-23187	120	37	𝑖=1	𝑖=1	PUNCT
brj-23187	120	38	−	−	PROPN
brj-23187	120	39	∑	∑	PUNCT
brj-23187	120	40	{	{	PUNCT
brj-23187	120	41	𝛼𝑖[𝝎	𝛼𝑖[𝝎	PROPN
brj-23187	120	42	t𝜑(𝒙𝑖	t𝜑(𝒙𝑖	PROPN
brj-23187	120	43	)	)	PUNCT
brj-23187	121	1	+	+	CCONJ
brj-23187	121	2	𝑏	𝑏	PROPN
brj-23187	122	1	+	+	CCONJ
brj-23187	122	2	𝜉𝑖	𝜉𝑖	ADP
brj-23187	122	3	−	−	NOUN
brj-23187	122	4	𝑦𝑖	𝑦𝑖	NOUN
brj-23187	122	5	]	]	X
brj-23187	122	6	}	}	PUNCT
brj-23187	122	7	𝑁	𝑁	PROPN
brj-23187	122	8	𝑖=1	𝑖=1	PROPN
brj-23187	122	9	(	(	PUNCT
brj-23187	122	10	14	14	NUM
brj-23187	122	11	)	)	PUNCT
brj-23187	122	12	where	where	SCONJ
brj-23187	122	13	the	the	DET
brj-23187	122	14	lagrangian	lagrangian	ADJ
brj-23187	122	15	multiplier	multipli	ADJ
brj-23187	122	16	𝛼𝑖	𝛼𝑖	ADP
brj-23187	122	17	>	>	X
brj-23187	122	18	0	0	PUNCT
brj-23187	123	1	(	(	PUNCT
brj-23187	123	2	𝑖	𝑖	SYM
brj-23187	123	3	=	=	SYM
brj-23187	123	4	1	1	NUM
brj-23187	123	5	,	,	PUNCT
brj-23187	123	6	2	2	NUM
brj-23187	123	7	,	,	PUNCT
brj-23187	123	8	.	.	PUNCT
brj-23187	123	9	.	.	PUNCT
brj-23187	123	10	.	.	PUNCT
brj-23187	123	11	,	,	PUNCT
brj-23187	123	12	n	n	CCONJ
brj-23187	123	13	)	)	PUNCT
brj-23187	123	14	.	.	PUNCT
brj-23187	124	1	the	the	DET
brj-23187	124	2	partial	partial	ADJ
brj-23187	124	3	derivatives	derivative	NOUN
brj-23187	124	4	of	of	ADP
brj-23187	124	5	the	the	DET
brj-23187	124	6	lagrangian	lagrangian	ADJ
brj-23187	124	7	function	function	NOUN
brj-23187	124	8	𝐿(𝝎	𝐿(𝝎	PROPN
brj-23187	124	9	,	,	PUNCT
brj-23187	124	10	𝑏	𝑏	NOUN
brj-23187	124	11	,	,	PUNCT
brj-23187	124	12	𝝃	𝝃	PROPN
brj-23187	124	13	,	,	PUNCT
brj-23187	124	14	𝜶	𝜶	NOUN
brj-23187	124	15	)	)	PUNCT
brj-23187	124	16	for	for	ADP
brj-23187	124	17	𝝎	𝝎	PRON
brj-23187	124	18	,	,	PUNCT
brj-23187	124	19	𝑏	𝑏	NOUN
brj-23187	124	20	,	,	PUNCT
brj-23187	124	21	𝝃	𝝃	PROPN
brj-23187	124	22	,	,	PUNCT
brj-23187	124	23	𝜶	𝜶	PRON
brj-23187	124	24	are	be	AUX
brj-23187	124	25	as	as	SCONJ
brj-23187	124	26	follows	follow	VERB
brj-23187	124	27	:	:	PUNCT
brj-23187	124	28	{	{	PUNCT
brj-23187	124	29	∂𝐿	∂𝐿	PROPN
brj-23187	124	30	∂𝝎	∂𝝎	PROPN
brj-23187	124	31	=	=	SYM
brj-23187	124	32	𝟎	𝟎	PROPN
brj-23187	124	33	⇒	⇒	NOUN
brj-23187	124	34	𝝎	𝝎	X
brj-23187	124	35	=	=	X
brj-23187	124	36	∑	∑	PUNCT
brj-23187	124	37	𝛼𝑖	𝛼𝑖	ADP
brj-23187	124	38	𝑁	𝑁	PROPN
brj-23187	124	39	𝑖=1	𝑖=1	PROPN
brj-23187	124	40	𝜑(𝒙𝑖	𝜑(𝒙𝑖	NOUN
brj-23187	124	41	)	)	PUNCT
brj-23187	124	42	∂𝐿	∂𝐿	PROPN
brj-23187	124	43	∂𝑏	∂𝑏	PROPN
brj-23187	124	44	=	=	SYM
brj-23187	124	45	0	0	NUM
brj-23187	124	46	⇒	⇒	NOUN
brj-23187	124	47	∑	∑	PROPN
brj-23187	124	48	𝛼𝑖	𝛼𝑖	ADP
brj-23187	124	49	𝑁	𝑁	PROPN
brj-23187	124	50	𝑖=1	𝑖=1	PUNCT
brj-23187	124	51	=	=	SYM
brj-23187	124	52	0	0	NUM
brj-23187	124	53	∂𝐿	∂𝐿	PROPN
brj-23187	124	54	∂𝜉𝑖	∂𝜉𝑖	NOUN
brj-23187	124	55	=	=	SYM
brj-23187	124	56	0	0	NUM
brj-23187	125	1	⇒	⇒	NOUN
brj-23187	125	2	𝛼𝑖	𝛼𝑖	X
brj-23187	125	3	=	=	SYM
brj-23187	125	4	𝑐𝜉𝑖	𝑐𝜉𝑖	PROPN
brj-23187	125	5	,	,	PUNCT
brj-23187	125	6	𝑖	𝑖	NOUN
brj-23187	125	7	=	=	SYM
brj-23187	125	8	1,2	1,2	NUM
brj-23187	125	9	,	,	PUNCT
brj-23187	125	10	…	…	PUNCT
brj-23187	125	11	,	,	PUNCT
brj-23187	125	12	𝑁	𝑁	PROPN
brj-23187	125	13	∂𝐿	∂𝐿	PROPN
brj-23187	125	14	∂𝛼𝑖	∂𝛼𝑖	PROPN
brj-23187	125	15	=	=	SYM
brj-23187	125	16	0	0	NUM
brj-23187	125	17	⇒	⇒	PROPN
brj-23187	125	18	𝝎t𝜑(𝒙𝑖	𝝎t𝜑(𝒙𝑖	ADV
brj-23187	125	19	)	)	PUNCT
brj-23187	126	1	+	+	CCONJ
brj-23187	126	2	𝑏	𝑏	PROPN
brj-23187	126	3	+	+	CCONJ
brj-23187	126	4	𝜉𝑖	𝜉𝑖	ADP
brj-23187	126	5	−	−	NOUN
brj-23187	126	6	𝑦𝑖	𝑦𝑖	PROPN
brj-23187	126	7	=	=	SYM
brj-23187	126	8	0	0	PROPN
brj-23187	126	9	,	,	PUNCT
brj-23187	126	10	𝑖	𝑖	NOUN
brj-23187	126	11	=	=	SYM
brj-23187	126	12	1,2	1,2	NUM
brj-23187	126	13	,	,	PUNCT
brj-23187	126	14	…	…	PUNCT
brj-23187	126	15	,	,	PUNCT
brj-23187	126	16	𝑁	𝑁	PROPN
brj-23187	126	17	(	(	PUNCT
brj-23187	126	18	15	15	NUM
brj-23187	126	19	)	)	PUNCT
brj-23187	126	20	according	accord	VERB
brj-23187	126	21	to	to	ADP
brj-23187	126	22	eq	eq	PROPN
brj-23187	126	23	.	.	PROPN
brj-23187	126	24	15	15	NUM
brj-23187	126	25	,	,	PUNCT
brj-23187	126	26	the	the	DET
brj-23187	126	27	following	follow	VERB
brj-23187	126	28	system	system	NOUN
brj-23187	126	29	of	of	ADP
brj-23187	126	30	linear	linear	PROPN
brj-23187	126	31	equations	equation	NOUN
brj-23187	126	32	can	can	AUX
brj-23187	126	33	be	be	AUX
brj-23187	126	34	derived	derive	VERB
brj-23187	126	35	by	by	ADP
brj-23187	126	36	eliminating	eliminate	VERB
brj-23187	126	37	𝝎	𝝎	PRON
brj-23187	126	38	and	and	CCONJ
brj-23187	126	39	𝜉𝑖	𝜉𝑖	ADV
brj-23187	126	40	:	:	PUNCT
brj-23187	126	41	[	[	PUNCT
brj-23187	126	42	0	0	NUM
brj-23187	126	43	𝟏𝑁	𝟏𝑁	NOUN
brj-23187	126	44	t	t	PROPN
brj-23187	126	45	𝟏𝑁	𝟏𝑁	NOUN
brj-23187	127	1	𝜽	𝜽	PROPN
brj-23187	127	2	+	+	PROPN
brj-23187	127	3	1	1	NUM
brj-23187	127	4	𝑐	𝑐	PROPN
brj-23187	127	5	𝑰𝑁	𝑰𝑁	PROPN
brj-23187	127	6	]	]	PUNCT
brj-23187	128	1	[	[	X
brj-23187	128	2	𝑏	𝑏	X
brj-23187	128	3	𝜶	𝜶	NOUN
brj-23187	128	4	]	]	PUNCT
brj-23187	128	5	=	=	PUNCT
brj-23187	128	6	[	[	PUNCT
brj-23187	128	7	0	0	NUM
brj-23187	128	8	𝒚	𝒚	NOUN
brj-23187	128	9	]	]	X
brj-23187	128	10	(	(	PUNCT
brj-23187	128	11	16	16	NUM
brj-23187	128	12	)	)	PUNCT
brj-23187	128	13	peer	peer	NOUN
brj-23187	128	14	-	-	PUNCT
brj-23187	128	15	reviewed	review	VERB
brj-23187	128	16	article	article	NOUN
brj-23187	128	17	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	128	18	fu	fu	PROPN
brj-23187	128	19	et	et	PROPN
brj-23187	128	20	al	al	PROPN
brj-23187	128	21	.	.	PROPN
brj-23187	128	22	(	(	PUNCT
brj-23187	128	23	2024	2024	NUM
brj-23187	128	24	)	)	PUNCT
brj-23187	128	25	.	.	PUNCT
brj-23187	129	1	“	"	PUNCT
brj-23187	129	2	predicting	predict	VERB
brj-23187	129	3	enzymatic	enzymatic	ADJ
brj-23187	129	4	hydrolysis	hydrolysis	NOUN
brj-23187	129	5	,	,	PUNCT
brj-23187	129	6	”	"	PUNCT
brj-23187	129	7	bioresources	bioresource	NOUN
brj-23187	129	8	19(2	19(2	NUM
brj-23187	129	9	)	)	PUNCT
brj-23187	129	10	,	,	PUNCT
brj-23187	129	11	3505	3505	NUM
brj-23187	129	12	-	-	SYM
brj-23187	129	13	3519	3519	NUM
brj-23187	129	14	.	.	PUNCT
brj-23187	130	1	3511	3511	NUM
brj-23187	130	2	here	here	ADV
brj-23187	130	3	,	,	PUNCT
brj-23187	130	4	𝒚	𝒚	X
brj-23187	130	5	=	=	PUNCT
brj-23187	131	1	[	[	X
brj-23187	131	2	𝑦1	𝑦1	PROPN
brj-23187	131	3	,	,	PUNCT
brj-23187	131	4	⋯	⋯	PROPN
brj-23187	131	5	,	,	PUNCT
brj-23187	131	6	𝑦𝑁]t	𝑦𝑁]t	PROPN
brj-23187	131	7	,	,	PUNCT
brj-23187	131	8	𝟏𝑁	𝟏𝑁	NOUN
brj-23187	131	9	=	=	PUNCT
brj-23187	132	1	[	[	X
brj-23187	132	2	1	1	NUM
brj-23187	132	3	,	,	PUNCT
brj-23187	132	4	⋯	⋯	NOUN
brj-23187	132	5	,	,	PUNCT
brj-23187	132	6	1]t	1]t	NUM
brj-23187	132	7	,	,	PUNCT
brj-23187	132	8	𝑰𝑁	𝑰𝑁	PROPN
brj-23187	132	9	is	be	AUX
brj-23187	132	10	the	the	DET
brj-23187	132	11	identity	identity	NOUN
brj-23187	132	12	matrix	matrix	NOUN
brj-23187	132	13	,	,	PUNCT
brj-23187	132	14	𝜶	𝜶	NOUN
brj-23187	132	15	=	=	PUNCT
brj-23187	133	1	[	[	X
brj-23187	133	2	𝛼1	𝛼1	NOUN
brj-23187	133	3	,	,	PUNCT
brj-23187	133	4	⋯	⋯	PROPN
brj-23187	133	5	,	,	PUNCT
brj-23187	133	6	𝛼𝑁]t	𝛼𝑁]t	NOUN
brj-23187	133	7	,	,	PUNCT
brj-23187	133	8	𝜽𝑖,𝑗	𝜽𝑖,𝑗	NOUN
brj-23187	133	9	=	=	SYM
brj-23187	133	10	𝜑(𝒙𝑖	𝜑(𝒙𝑖	NOUN
brj-23187	133	11	)	)	PUNCT
brj-23187	133	12	t𝜑(𝒙𝑗	t𝜑(𝒙𝑗	PROPN
brj-23187	133	13	)	)	PUNCT
brj-23187	133	14	,	,	PUNCT
brj-23187	133	15	𝑖	𝑖	SYM
brj-23187	133	16	,	,	PUNCT
brj-23187	133	17	𝑗	𝑗	NOUN
brj-23187	133	18	=	=	SYM
brj-23187	133	19	1	1	NUM
brj-23187	133	20	,	,	PUNCT
brj-23187	133	21	⋯	⋯	PROPN
brj-23187	133	22	,	,	PUNCT
brj-23187	133	23	𝑁.	𝑁.	PROPN
brj-23187	133	24	𝜽𝑖,𝑗	𝜽𝑖,𝑗	PUNCT
brj-23187	133	25	can	can	AUX
brj-23187	133	26	be	be	AUX
brj-23187	133	27	calculated	calculate	VERB
brj-23187	133	28	by	by	ADP
brj-23187	133	29	kernel	kernel	PROPN
brj-23187	133	30	function	function	PROPN
brj-23187	133	31	:	:	PUNCT
brj-23187	133	32	𝜽𝑖,𝑗	𝜽𝑖,𝑗	X
brj-23187	133	33	=	=	SYM
brj-23187	133	34	𝜅(𝒙𝑖	𝜅(𝒙𝑖	X
brj-23187	133	35	,	,	PUNCT
brj-23187	133	36	𝒙𝑗	𝒙𝑗	X
brj-23187	133	37	)	)	PUNCT
brj-23187	133	38	=	=	PUNCT
brj-23187	133	39	𝜑(𝒙𝑖	𝜑(𝒙𝑖	NOUN
brj-23187	133	40	)	)	PUNCT
brj-23187	133	41	t𝜑(𝒙𝑗	t𝜑(𝒙𝑗	NOUN
brj-23187	133	42	)	)	PUNCT
brj-23187	133	43	(	(	PUNCT
brj-23187	133	44	17	17	NUM
brj-23187	133	45	)	)	PUNCT
brj-23187	133	46	for	for	ADP
brj-23187	133	47	optimal	optimal	ADJ
brj-23187	133	48	lssvm	lssvm	NOUN
brj-23187	133	49	performance	performance	NOUN
brj-23187	133	50	,	,	PUNCT
brj-23187	133	51	the	the	DET
brj-23187	133	52	choice	choice	NOUN
brj-23187	133	53	of	of	ADP
brj-23187	133	54	a	a	DET
brj-23187	133	55	suitable	suitable	ADJ
brj-23187	133	56	kernel	kernel	NOUN
brj-23187	133	57	function	function	NOUN
brj-23187	133	58	,	,	PUNCT
brj-23187	133	59	𝜅(∙,∙	𝜅(∙,∙	NOUN
brj-23187	133	60	)	)	PUNCT
brj-23187	133	61	,	,	PUNCT
brj-23187	133	62	is	be	AUX
brj-23187	133	63	pivotal	pivotal	ADJ
brj-23187	133	64	.	.	PUNCT
brj-23187	134	1	common	common	ADJ
brj-23187	134	2	kernel	kernel	NOUN
brj-23187	134	3	functions	function	NOUN
brj-23187	134	4	include	include	VERB
brj-23187	134	5	the	the	DET
brj-23187	134	6	polynomial	polynomial	ADJ
brj-23187	134	7	,	,	PUNCT
brj-23187	134	8	rbf	rbf	PROPN
brj-23187	134	9	(	(	PUNCT
brj-23187	134	10	radial	radial	ADJ
brj-23187	134	11	basis	basis	NOUN
brj-23187	134	12	function	function	NOUN
brj-23187	134	13	)	)	PUNCT
brj-23187	134	14	,	,	PUNCT
brj-23187	134	15	and	and	CCONJ
brj-23187	134	16	linear	linear	ADJ
brj-23187	134	17	kernels	kernel	NOUN
brj-23187	134	18	.	.	PUNCT
brj-23187	135	1	given	give	VERB
brj-23187	135	2	its	its	PRON
brj-23187	135	3	widespread	widespread	ADJ
brj-23187	135	4	use	use	NOUN
brj-23187	135	5	in	in	ADP
brj-23187	135	6	tackling	tackle	VERB
brj-23187	135	7	nonlinear	nonlinear	ADJ
brj-23187	135	8	problems	problem	NOUN
brj-23187	135	9	,	,	PUNCT
brj-23187	135	10	the	the	DET
brj-23187	135	11	rbf	rbf	PROPN
brj-23187	135	12	was	be	AUX
brj-23187	135	13	deemed	deem	VERB
brj-23187	135	14	suitable	suitable	ADJ
brj-23187	135	15	for	for	ADP
brj-23187	135	16	this	this	DET
brj-23187	135	17	study	study	NOUN
brj-23187	135	18	(	(	PUNCT
brj-23187	135	19	wang	wang	PROPN
brj-23187	135	20	and	and	CCONJ
brj-23187	135	21	hu	hu	PROPN
brj-23187	135	22	2015	2015	NUM
brj-23187	135	23	)	)	PUNCT
brj-23187	135	24	.	.	PUNCT
brj-23187	136	1	therefore	therefore	ADV
brj-23187	136	2	,	,	PUNCT
brj-23187	136	3	the	the	DET
brj-23187	136	4	rbf	rbf	PROPN
brj-23187	136	5	is	be	AUX
brj-23187	136	6	selected	select	VERB
brj-23187	136	7	as	as	SCONJ
brj-23187	136	8	follows	follow	VERB
brj-23187	136	9	:	:	PUNCT
brj-23187	136	10	𝜅(𝒙𝑖	𝜅(𝒙𝑖	X
brj-23187	136	11	,	,	PUNCT
brj-23187	136	12	𝒙𝑗	𝒙𝑗	VERB
brj-23187	136	13	)	)	PUNCT
brj-23187	136	14	=	=	NOUN
brj-23187	136	15	exp	exp	NOUN
brj-23187	136	16	(	(	PUNCT
brj-23187	136	17	−	−	PROPN
brj-23187	136	18	∥∥𝒙𝑖−𝒙𝑗∥∥	∥∥𝒙𝑖−𝒙𝑗∥∥	PROPN
brj-23187	136	19	2	2	NUM
brj-23187	136	20	2𝜎2	2𝜎2	NUM
brj-23187	136	21	)	)	PUNCT
brj-23187	136	22	(	(	PUNCT
brj-23187	136	23	18	18	NUM
brj-23187	136	24	)	)	PUNCT
brj-23187	136	25	here	here	ADV
brj-23187	136	26	,	,	PUNCT
brj-23187	136	27	𝜎	𝜎	PROPN
brj-23187	136	28	is	be	AUX
brj-23187	136	29	the	the	DET
brj-23187	136	30	kernel	kernel	NOUN
brj-23187	136	31	width	width	NOUN
brj-23187	136	32	,	,	PUNCT
brj-23187	136	33	and	and	CCONJ
brj-23187	136	34	the	the	DET
brj-23187	136	35	vector	vector	NOUN
brj-23187	136	36	norm	norm	NOUN
brj-23187	136	37	∥∥𝒙𝑖	∥∥𝒙𝑖	PROPN
brj-23187	136	38	−	−	PROPN
brj-23187	136	39	𝒙𝑗∥∥	𝒙𝑗∥∥	PROPN
brj-23187	136	40	is	be	AUX
brj-23187	136	41	the	the	DET
brj-23187	136	42	euclidean	euclidean	ADJ
brj-23187	136	43	distance	distance	NOUN
brj-23187	136	44	between	between	ADP
brj-23187	136	45	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	136	46	and	and	CCONJ
brj-23187	136	47	𝒙𝑗.	𝒙𝑗.	ADJ
brj-23187	136	48	in	in	ADP
brj-23187	136	49	summary	summary	NOUN
brj-23187	136	50	,	,	PUNCT
brj-23187	136	51	using	use	VERB
brj-23187	136	52	the	the	DET
brj-23187	136	53	training	training	NOUN
brj-23187	136	54	data	datum	NOUN
brj-23187	136	55	,	,	PUNCT
brj-23187	136	56	it	it	PRON
brj-23187	136	57	is	be	AUX
brj-23187	136	58	possible	possible	ADJ
brj-23187	136	59	to	to	PART
brj-23187	136	60	estimate	estimate	VERB
brj-23187	136	61	the	the	DET
brj-23187	136	62	parameters	parameter	NOUN
brj-23187	136	63	𝑏	𝑏	PROPN
brj-23187	136	64	and	and	CCONJ
brj-23187	136	65	𝜶	𝜶	PRON
brj-23187	136	66	,	,	PUNCT
brj-23187	136	67	enabling	enable	VERB
brj-23187	136	68	one	one	NUM
brj-23187	136	69	to	to	PART
brj-23187	136	70	derive	derive	VERB
brj-23187	136	71	the	the	DET
brj-23187	136	72	lssvm	lssvm	NOUN
brj-23187	136	73	regression	regression	NOUN
brj-23187	136	74	function	function	NOUN
brj-23187	136	75	model	model	NOUN
brj-23187	136	76	.	.	PUNCT
brj-23187	137	1	consequently	consequently	ADV
brj-23187	137	2	,	,	PUNCT
brj-23187	137	3	accurate	accurate	ADJ
brj-23187	137	4	predictions	prediction	NOUN
brj-23187	137	5	for	for	ADP
brj-23187	137	6	the	the	DET
brj-23187	137	7	new	new	ADJ
brj-23187	137	8	test	test	NOUN
brj-23187	137	9	samples	sample	NOUN
brj-23187	137	10	𝒙	𝒙	PRON
brj-23187	137	11	can	can	AUX
brj-23187	137	12	be	be	AUX
brj-23187	137	13	obtained	obtain	VERB
brj-23187	137	14	.	.	PUNCT
brj-23187	138	1	the	the	DET
brj-23187	138	2	result	result	NOUN
brj-23187	138	3	is	be	AUX
brj-23187	138	4	as	as	SCONJ
brj-23187	138	5	follows	follow	NOUN
brj-23187	138	6	,	,	PUNCT
brj-23187	138	7	𝑓(𝒙	𝑓(𝒙	NOUN
brj-23187	138	8	)	)	PUNCT
brj-23187	139	1	=	=	PUNCT
brj-23187	139	2	∑	∑	PUNCT
brj-23187	139	3	𝛼𝑖	𝛼𝑖	ADP
brj-23187	139	4	𝑁	𝑁	PROPN
brj-23187	139	5	𝑖=1	𝑖=1	PROPN
brj-23187	139	6	𝜅(𝒙	𝜅(𝒙	PROPN
brj-23187	139	7	,	,	PUNCT
brj-23187	139	8	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	139	9	)	)	PUNCT
brj-23187	140	1	+	+	CCONJ
brj-23187	140	2	𝑏	𝑏	PROPN
brj-23187	140	3	(	(	PUNCT
brj-23187	140	4	19	19	NUM
brj-23187	140	5	)	)	PUNCT
brj-23187	140	6	where	where	SCONJ
brj-23187	140	7	the	the	DET
brj-23187	140	8	kernel	kernel	NOUN
brj-23187	140	9	function	function	VERB
brj-23187	140	10	𝜅(𝒙	𝜅(𝒙	PROPN
brj-23187	140	11	,	,	PUNCT
brj-23187	140	12	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	140	13	)	)	PUNCT
brj-23187	140	14	is	be	AUX
brj-23187	140	15	calculated	calculate	VERB
brj-23187	140	16	according	accord	VERB
brj-23187	140	17	to	to	ADP
brj-23187	140	18	eq	eq	PROPN
brj-23187	140	19	.	.	PROPN
brj-23187	140	20	18	18	NUM
brj-23187	140	21	,	,	PUNCT
brj-23187	140	22	and	and	CCONJ
brj-23187	140	23	𝒙𝑖	𝒙𝑖	NOUN
brj-23187	140	24	is	be	AUX
brj-23187	140	25	the	the	DET
brj-23187	140	26	training	training	NOUN
brj-23187	140	27	sample	sample	NOUN
brj-23187	140	28	vector	vector	NOUN
brj-23187	140	29	(	(	PUNCT
brj-23187	140	30	yuan	yuan	NOUN
brj-23187	140	31	et	et	PROPN
brj-23187	140	32	al	al	PROPN
brj-23187	140	33	.	.	PROPN
brj-23187	140	34	2015	2015	NUM
brj-23187	140	35	)	)	PUNCT
brj-23187	140	36	.	.	PUNCT
brj-23187	141	1	prediction	prediction	NOUN
brj-23187	141	2	of	of	ADP
brj-23187	141	3	enzymatic	enzymatic	ADJ
brj-23187	141	4	hydrolysis	hydrolysis	NOUN
brj-23187	141	5	efficiency	efficiency	NOUN
brj-23187	141	6	in	in	ADP
brj-23187	141	7	the	the	DET
brj-23187	141	8	online	online	ADJ
brj-23187	141	9	prediction	prediction	NOUN
brj-23187	141	10	phase	phase	NOUN
brj-23187	141	11	,	,	PUNCT
brj-23187	141	12	as	as	SCONJ
brj-23187	141	13	shown	show	VERB
brj-23187	141	14	in	in	ADP
brj-23187	141	15	fig	fig	NOUN
brj-23187	141	16	.	.	PUNCT
brj-23187	142	1	2	2	NUM
brj-23187	142	2	,	,	PUNCT
brj-23187	142	3	data	datum	NOUN
brj-23187	142	4	from	from	ADP
brj-23187	142	5	m	m	PRON
brj-23187	142	6	influencing	influence	VERB
brj-23187	142	7	variables	variable	NOUN
brj-23187	142	8	in	in	ADP
brj-23187	142	9	the	the	DET
brj-23187	142	10	actual	actual	ADJ
brj-23187	142	11	project	project	NOUN
brj-23187	142	12	is	be	AUX
brj-23187	142	13	first	first	ADV
brj-23187	142	14	collected	collect	VERB
brj-23187	142	15	.	.	PUNCT
brj-23187	143	1	the	the	DET
brj-23187	143	2	authors	author	NOUN
brj-23187	143	3	selected	select	VERB
brj-23187	143	4	and	and	CCONJ
brj-23187	143	5	averaged	average	VERB
brj-23187	143	6	the	the	DET
brj-23187	143	7	test	test	NOUN
brj-23187	143	8	data	datum	NOUN
brj-23187	143	9	based	base	VERB
brj-23187	143	10	on	on	ADP
brj-23187	143	11	the	the	DET
brj-23187	143	12	screening	screen	VERB
brj-23187	143	13	outcomes	outcome	NOUN
brj-23187	143	14	from	from	ADP
brj-23187	143	15	gra	gra	PROPN
brj-23187	143	16	-	-	PUNCT
brj-23187	143	17	based	base	VERB
brj-23187	143	18	variable	variable	ADJ
brj-23187	143	19	selection	selection	NOUN
brj-23187	143	20	.	.	PUNCT
brj-23187	144	1	drawing	draw	VERB
brj-23187	144	2	from	from	ADP
brj-23187	144	3	the	the	DET
brj-23187	144	4	insights	insight	NOUN
brj-23187	144	5	in	in	ADP
brj-23187	144	6	input	input	NOUN
brj-23187	144	7	dimension	dimension	NOUN
brj-23187	144	8	reduction	reduction	NOUN
brj-23187	144	9	based	base	VERB
brj-23187	144	10	on	on	ADP
brj-23187	144	11	kpca	kpca	NOUN
brj-23187	144	12	and	and	CCONJ
brj-23187	144	13	using	use	VERB
brj-23187	144	14	eq	eq	ADP
brj-23187	144	15	.	.	PROPN
brj-23187	144	16	11	11	NUM
brj-23187	144	17	,	,	PUNCT
brj-23187	144	18	these	these	DET
brj-23187	144	19	data	datum	NOUN
brj-23187	144	20	were	be	AUX
brj-23187	144	21	employed	employ	VERB
brj-23187	144	22	for	for	ADP
brj-23187	144	23	dimensionality	dimensionality	NOUN
brj-23187	144	24	reduction	reduction	NOUN
brj-23187	144	25	.	.	PUNCT
brj-23187	145	1	finally	finally	ADV
brj-23187	145	2	,	,	PUNCT
brj-23187	145	3	using	use	VERB
brj-23187	145	4	the	the	DET
brj-23187	145	5	trained	train	VERB
brj-23187	145	6	lssvm	lssvm	NOUN
brj-23187	145	7	model	model	NOUN
brj-23187	145	8	,	,	PUNCT
brj-23187	145	9	the	the	DET
brj-23187	145	10	enzymatic	enzymatic	ADJ
brj-23187	145	11	hydrolysis	hydrolysis	NOUN
brj-23187	145	12	efficiency	efficiency	NOUN
brj-23187	145	13	was	be	AUX
brj-23187	145	14	predicted	predict	VERB
brj-23187	145	15	,	,	PUNCT
brj-23187	145	16	particularly	particularly	ADV
brj-23187	145	17	the	the	DET
brj-23187	145	18	predicted	predict	VERB
brj-23187	145	19	outcomes	outcome	NOUN
brj-23187	145	20	of	of	ADP
brj-23187	145	21	the	the	DET
brj-23187	145	22	lignin	lignin	NOUN
brj-23187	145	23	and	and	CCONJ
brj-23187	145	24	hemicellulose	hemicellulose	NOUN
brj-23187	145	25	removal	removal	NOUN
brj-23187	145	26	values	value	NOUN
brj-23187	145	27	,	,	PUNCT
brj-23187	145	28	as	as	SCONJ
brj-23187	145	29	determined	determine	VERB
brj-23187	145	30	by	by	ADP
brj-23187	145	31	eq	eq	PROPN
brj-23187	145	32	.	.	PROPN
brj-23187	145	33	19	19	NUM
brj-23187	145	34	.	.	PUNCT
brj-23187	145	35	test	test	NOUN
brj-23187	145	36	verification	verification	NOUN
brj-23187	145	37	process	process	NOUN
brj-23187	145	38	and	and	CCONJ
brj-23187	145	39	data	datum	NOUN
brj-23187	145	40	this	this	DET
brj-23187	145	41	study	study	NOUN
brj-23187	145	42	used	use	VERB
brj-23187	145	43	data	datum	NOUN
brj-23187	145	44	from	from	ADP
brj-23187	145	45	the	the	DET
brj-23187	145	46	crop	crop	NOUN
brj-23187	145	47	straw	straw	VERB
brj-23187	145	48	enzymatic	enzymatic	ADJ
brj-23187	145	49	hydrolysis	hydrolysis	NOUN
brj-23187	145	50	production	production	NOUN
brj-23187	145	51	process	process	NOUN
brj-23187	145	52	of	of	ADP
brj-23187	145	53	zhongnong	zhongnong	PROPN
brj-23187	145	54	jiemei	jiemei	PROPN
brj-23187	145	55	,	,	PUNCT
brj-23187	145	56	ltd	ltd	PROPN
brj-23187	145	57	.	.	PROPN
brj-23187	145	58	co.	co.	PROPN
brj-23187	145	59	,	,	PUNCT
brj-23187	145	60	suzhou	suzhou	PROPN
brj-23187	145	61	(	(	PUNCT
brj-23187	145	62	anhui	anhui	PROPN
brj-23187	145	63	,	,	PUNCT
brj-23187	145	64	china	china	PROPN
brj-23187	145	65	)	)	PUNCT
brj-23187	145	66	.	.	PUNCT
brj-23187	146	1	through	through	ADP
brj-23187	146	2	rigorous	rigorous	ADJ
brj-23187	146	3	research	research	NOUN
brj-23187	146	4	and	and	CCONJ
brj-23187	146	5	meticulous	meticulous	ADJ
brj-23187	146	6	analysis	analysis	NOUN
brj-23187	146	7	,	,	PUNCT
brj-23187	146	8	15	15	NUM
brj-23187	146	9	influencing	influence	VERB
brj-23187	146	10	factors	factor	NOUN
brj-23187	146	11	were	be	AUX
brj-23187	146	12	selected	select	VERB
brj-23187	146	13	:	:	PUNCT
brj-23187	146	14	the	the	DET
brj-23187	146	15	length	length	NOUN
brj-23187	146	16	of	of	ADP
brj-23187	146	17	crushed	crushed	ADJ
brj-23187	146	18	straw	straw	NOUN
brj-23187	146	19	(	(	PUNCT
brj-23187	146	20	𝑋1	𝑋1	PROPN
brj-23187	146	21	)	)	PUNCT
brj-23187	146	22	,	,	PUNCT
brj-23187	146	23	the	the	DET
brj-23187	146	24	first	first	ADJ
brj-23187	146	25	stage	stage	NOUN
brj-23187	146	26	reaction	reaction	NOUN
brj-23187	146	27	temperature	temperature	NOUN
brj-23187	146	28	(	(	PUNCT
brj-23187	146	29	𝑋2	𝑋2	PROPN
brj-23187	146	30	)	)	PUNCT
brj-23187	146	31	,	,	PUNCT
brj-23187	146	32	the	the	DET
brj-23187	146	33	first	first	ADJ
brj-23187	146	34	stage	stage	NOUN
brj-23187	146	35	reaction	reaction	NOUN
brj-23187	146	36	ph	ph	NOUN
brj-23187	146	37	(	(	PUNCT
brj-23187	146	38	𝑋3	𝑋3	NOUN
brj-23187	146	39	)	)	PUNCT
brj-23187	146	40	,	,	PUNCT
brj-23187	146	41	the	the	DET
brj-23187	146	42	first	first	ADJ
brj-23187	146	43	stage	stage	NOUN
brj-23187	146	44	reaction	reaction	NOUN
brj-23187	146	45	time	time	NOUN
brj-23187	146	46	(	(	PUNCT
brj-23187	146	47	𝑋4	𝑋4	PROPN
brj-23187	146	48	)	)	PUNCT
brj-23187	146	49	,	,	PUNCT
brj-23187	146	50	the	the	DET
brj-23187	146	51	second	second	ADJ
brj-23187	146	52	stage	stage	NOUN
brj-23187	146	53	reaction	reaction	NOUN
brj-23187	146	54	temperature	temperature	NOUN
brj-23187	146	55	(	(	PUNCT
brj-23187	146	56	𝑋5	𝑋5	PROPN
brj-23187	146	57	)	)	PUNCT
brj-23187	146	58	,	,	PUNCT
brj-23187	146	59	the	the	DET
brj-23187	146	60	second	second	ADJ
brj-23187	146	61	stage	stage	NOUN
brj-23187	146	62	reaction	reaction	NOUN
brj-23187	146	63	ph	ph	PROPN
brj-23187	146	64	(	(	PUNCT
brj-23187	146	65	𝑋6	𝑋6	NOUN
brj-23187	146	66	)	)	PUNCT
brj-23187	146	67	,	,	PUNCT
brj-23187	146	68	the	the	DET
brj-23187	146	69	second	second	ADJ
brj-23187	146	70	stage	stage	NOUN
brj-23187	146	71	reaction	reaction	NOUN
brj-23187	146	72	time	time	NOUN
brj-23187	146	73	(	(	PUNCT
brj-23187	146	74	𝑋7	𝑋7	NOUN
brj-23187	146	75	)	)	PUNCT
brj-23187	146	76	,	,	PUNCT
brj-23187	146	77	the	the	DET
brj-23187	146	78	third	third	ADJ
brj-23187	146	79	stage	stage	NOUN
brj-23187	146	80	reaction	reaction	NOUN
brj-23187	146	81	temperature	temperature	NOUN
brj-23187	146	82	(	(	PUNCT
brj-23187	146	83	𝑋8	𝑋8	NOUN
brj-23187	146	84	)	)	PUNCT
brj-23187	146	85	,	,	PUNCT
brj-23187	146	86	the	the	DET
brj-23187	146	87	third	third	ADJ
brj-23187	146	88	stage	stage	NOUN
brj-23187	146	89	reaction	reaction	NOUN
brj-23187	146	90	ph	ph	PROPN
brj-23187	146	91	(	(	PUNCT
brj-23187	146	92	𝑋9	𝑋9	PROPN
brj-23187	146	93	)	)	PUNCT
brj-23187	146	94	,	,	PUNCT
brj-23187	146	95	the	the	DET
brj-23187	146	96	third	third	ADJ
brj-23187	146	97	stage	stage	NOUN
brj-23187	146	98	reaction	reaction	NOUN
brj-23187	146	99	time	time	NOUN
brj-23187	146	100	(	(	PUNCT
brj-23187	146	101	𝑋10	𝑋10	PROPN
brj-23187	146	102	)	)	PUNCT
brj-23187	146	103	,	,	PUNCT
brj-23187	146	104	the	the	DET
brj-23187	146	105	amount	amount	NOUN
brj-23187	146	106	of	of	ADP
brj-23187	146	107	crop	crop	NOUN
brj-23187	146	108	straw	straw	NOUN
brj-23187	146	109	added	add	VERB
brj-23187	146	110	(	(	PUNCT
brj-23187	146	111	𝑋11	𝑋11	PROPN
brj-23187	146	112	)	)	PUNCT
brj-23187	146	113	,	,	PUNCT
brj-23187	146	114	the	the	DET
brj-23187	146	115	amount	amount	NOUN
brj-23187	146	116	of	of	ADP
brj-23187	146	117	water	water	NOUN
brj-23187	146	118	added	add	VERB
brj-23187	146	119	(	(	PUNCT
brj-23187	146	120	𝑋12	𝑋12	PROPN
brj-23187	146	121	)	)	PUNCT
brj-23187	146	122	,	,	PUNCT
brj-23187	146	123	the	the	DET
brj-23187	146	124	volume	volume	NOUN
brj-23187	146	125	of	of	ADP
brj-23187	146	126	the	the	DET
brj-23187	146	127	enzymatic	enzymatic	ADJ
brj-23187	146	128	hydrolysis	hydrolysis	NOUN
brj-23187	146	129	tank	tank	NOUN
brj-23187	146	130	(	(	PUNCT
brj-23187	146	131	𝑋13	𝑋13	PROPN
brj-23187	146	132	)	)	PUNCT
brj-23187	146	133	,	,	PUNCT
brj-23187	146	134	the	the	DET
brj-23187	146	135	speed	speed	NOUN
brj-23187	146	136	of	of	ADP
brj-23187	146	137	the	the	DET
brj-23187	146	138	enzymatic	enzymatic	ADJ
brj-23187	146	139	hydrolysis	hydrolysis	NOUN
brj-23187	146	140	tank	tank	NOUN
brj-23187	146	141	(	(	PUNCT
brj-23187	146	142	𝑋14	𝑋14	PROPN
brj-23187	146	143	)	)	PUNCT
brj-23187	146	144	,	,	PUNCT
brj-23187	146	145	and	and	CCONJ
brj-23187	146	146	room	room	NOUN
brj-23187	146	147	temperature	temperature	NOUN
brj-23187	146	148	(	(	PUNCT
brj-23187	146	149	𝑋15	𝑋15	PROPN
brj-23187	146	150	)	)	PUNCT
brj-23187	146	151	.	.	PUNCT
brj-23187	147	1	additionally	additionally	ADV
brj-23187	147	2	,	,	PUNCT
brj-23187	147	3	the	the	DET
brj-23187	147	4	corresponding	corresponding	ADJ
brj-23187	147	5	extents	extent	NOUN
brj-23187	147	6	of	of	ADP
brj-23187	147	7	lignin	lignin	NOUN
brj-23187	147	8	removal	removal	NOUN
brj-23187	147	9	and	and	CCONJ
brj-23187	147	10	hemicellulose	hemicellulose	NOUN
brj-23187	147	11	removal	removal	NOUN
brj-23187	147	12	,	,	PUNCT
brj-23187	147	13	i.e.	i.e.	X
brj-23187	147	14	,	,	PUNCT
brj-23187	147	15	𝜓1	𝜓1	NOUN
brj-23187	147	16	and	and	CCONJ
brj-23187	147	17	𝜓2	𝜓2	NOUN
brj-23187	147	18	,	,	PUNCT
brj-23187	147	19	were	be	AUX
brj-23187	147	20	recorded	record	VERB
brj-23187	147	21	.	.	PUNCT
brj-23187	148	1	the	the	DET
brj-23187	148	2	collected	collect	VERB
brj-23187	148	3	data	datum	NOUN
brj-23187	148	4	were	be	AUX
brj-23187	148	5	organised	organise	VERB
brj-23187	148	6	into	into	ADP
brj-23187	148	7	training	training	NOUN
brj-23187	148	8	peer	peer	NOUN
brj-23187	148	9	-	-	PUNCT
brj-23187	148	10	reviewed	review	VERB
brj-23187	148	11	article	article	NOUN
brj-23187	148	12	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	148	13	fu	fu	PROPN
brj-23187	148	14	et	et	PROPN
brj-23187	148	15	al	al	PROPN
brj-23187	148	16	.	.	PROPN
brj-23187	149	1	(	(	PUNCT
brj-23187	149	2	2024	2024	NUM
brj-23187	149	3	)	)	PUNCT
brj-23187	149	4	.	.	PUNCT
brj-23187	150	1	“	"	PUNCT
brj-23187	150	2	predicting	predict	VERB
brj-23187	150	3	enzymatic	enzymatic	ADJ
brj-23187	150	4	hydrolysis	hydrolysis	NOUN
brj-23187	150	5	,	,	PUNCT
brj-23187	150	6	”	"	PUNCT
brj-23187	150	7	bioresources	bioresource	NOUN
brj-23187	150	8	19(2	19(2	NUM
brj-23187	150	9	)	)	PUNCT
brj-23187	150	10	,	,	PUNCT
brj-23187	150	11	3505	3505	NUM
brj-23187	150	12	-	-	SYM
brj-23187	150	13	3519	3519	NUM
brj-23187	150	14	.	.	PUNCT
brj-23187	151	1	3512	3512	NUM
brj-23187	151	2	and	and	CCONJ
brj-23187	151	3	testing	testing	NOUN
brj-23187	151	4	datasets	dataset	NOUN
brj-23187	151	5	.	.	PUNCT
brj-23187	152	1	the	the	DET
brj-23187	152	2	dataset	dataset	NOUN
brj-23187	152	3	comprised	comprise	VERB
brj-23187	152	4	of	of	ADP
brj-23187	152	5	200	200	NUM
brj-23187	152	6	sample	sample	NOUN
brj-23187	152	7	groups	group	NOUN
brj-23187	152	8	.	.	PUNCT
brj-23187	153	1	of	of	ADP
brj-23187	153	2	these	these	PRON
brj-23187	153	3	,	,	PUNCT
brj-23187	153	4	160	160	NUM
brj-23187	153	5	groups	group	NOUN
brj-23187	153	6	were	be	AUX
brj-23187	153	7	designated	designate	VERB
brj-23187	153	8	for	for	ADP
brj-23187	153	9	training	training	NOUN
brj-23187	153	10	,	,	PUNCT
brj-23187	153	11	and	and	CCONJ
brj-23187	153	12	the	the	DET
brj-23187	153	13	remaining	remain	VERB
brj-23187	153	14	40	40	NUM
brj-23187	153	15	groups	group	NOUN
brj-23187	153	16	served	serve	VERB
brj-23187	153	17	as	as	ADP
brj-23187	153	18	test	test	NOUN
brj-23187	153	19	sets	set	NOUN
brj-23187	153	20	for	for	ADP
brj-23187	153	21	evaluation	evaluation	NOUN
brj-23187	153	22	.	.	PUNCT
brj-23187	154	1	evaluating	evaluate	VERB
brj-23187	154	2	indicators	indicator	NOUN
brj-23187	154	3	to	to	PART
brj-23187	154	4	evaluate	evaluate	VERB
brj-23187	154	5	the	the	DET
brj-23187	154	6	efficacy	efficacy	NOUN
brj-23187	154	7	of	of	ADP
brj-23187	154	8	the	the	DET
brj-23187	154	9	model	model	NOUN
brj-23187	154	10	,	,	PUNCT
brj-23187	154	11	two	two	NUM
brj-23187	154	12	evaluation	evaluation	NOUN
brj-23187	154	13	metrics	metric	NOUN
brj-23187	154	14	were	be	AUX
brj-23187	154	15	employed	employ	VERB
brj-23187	154	16	,	,	PUNCT
brj-23187	154	17	namely	namely	ADV
brj-23187	154	18	the	the	DET
brj-23187	154	19	root	root	NOUN
brj-23187	154	20	mean	mean	VERB
brj-23187	154	21	square	square	ADJ
brj-23187	154	22	error	error	NOUN
brj-23187	154	23	(	(	PUNCT
brj-23187	154	24	rmse	rmse	NOUN
brj-23187	154	25	)	)	PUNCT
brj-23187	154	26	and	and	CCONJ
brj-23187	154	27	the	the	DET
brj-23187	154	28	coefficient	coefficient	NOUN
brj-23187	154	29	of	of	ADP
brj-23187	154	30	determination	determination	NOUN
brj-23187	154	31	(	(	PUNCT
brj-23187	154	32	r2	r2	NOUN
brj-23187	154	33	):	):	PUNCT
brj-23187	154	34	𝑅𝑀𝑆𝐸	𝑅𝑀𝑆𝐸	PROPN
brj-23187	154	35	=	=	PRON
brj-23187	154	36	√∑	√∑	PUNCT
brj-23187	154	37	(	(	PUNCT
brj-23187	154	38	𝑦𝑜𝑏𝑠−𝑦𝑝𝑟𝑒𝑑	𝑦𝑜𝑏𝑠−𝑦𝑝𝑟𝑒𝑑	NOUN
brj-23187	154	39	)	)	PUNCT
brj-23187	154	40	2𝑛	2𝑛	PROPN
brj-23187	154	41	𝑖=1	𝑖=1	PUNCT
brj-23187	154	42	𝑛	𝑛	DET
brj-23187	154	43	r2	r2	NOUN
brj-23187	154	44	=	=	NOUN
brj-23187	154	45	1	1	NUM
brj-23187	154	46	−	−	NOUN
brj-23187	154	47	∑	∑	PUNCT
brj-23187	154	48	(	(	PUNCT
brj-23187	154	49	𝑦𝑜𝑏𝑠−𝑦𝑝𝑟𝑒𝑑	𝑦𝑜𝑏𝑠−𝑦𝑝𝑟𝑒𝑑	PROPN
brj-23187	154	50	)	)	PUNCT
brj-23187	154	51	2𝑛	2𝑛	PROPN
brj-23187	154	52	𝑖=1	𝑖=1	PUNCT
brj-23187	155	1	∑	∑	PROPN
brj-23187	155	2	(	(	PUNCT
brj-23187	155	3	𝑦𝑜𝑏𝑠−	𝑦𝑜𝑏𝑠−	NUM
brj-23187	155	4	�	�	PROPN
brj-23187	155	5	⃐	⃐	NUM
brj-23187	155	6	�	�	PROPN
brj-23187	155	7	𝑜𝑏𝑠	𝑜𝑏𝑠	NOUN
brj-23187	155	8	)	)	PUNCT
brj-23187	155	9	2𝑛	2𝑛	PROPN
brj-23187	155	10	𝑖=1	𝑖=1	PUNCT
brj-23187	155	11	(	(	PUNCT
brj-23187	155	12	20	20	NUM
brj-23187	155	13	)	)	PUNCT
brj-23187	155	14	the	the	DET
brj-23187	155	15	formula	formula	NOUN
brj-23187	155	16	uses	use	VERB
brj-23187	155	17	the	the	DET
brj-23187	155	18	variables	variable	NOUN
brj-23187	155	19	𝑦obs	𝑦ob	NOUN
brj-23187	155	20	and	and	CCONJ
brj-23187	155	21	𝑦pred	𝑦pre	VERB
brj-23187	155	22	,	,	PUNCT
brj-23187	155	23	to	to	PART
brj-23187	155	24	represent	represent	VERB
brj-23187	155	25	the	the	DET
brj-23187	155	26	observed	observe	VERB
brj-23187	155	27	and	and	CCONJ
brj-23187	155	28	predicted	predict	VERB
brj-23187	155	29	values	value	NOUN
brj-23187	155	30	,	,	PUNCT
brj-23187	155	31	respectively	respectively	ADV
brj-23187	155	32	.	.	PUNCT
brj-23187	156	1	additionally	additionally	ADV
brj-23187	156	2	,	,	PUNCT
brj-23187	156	3	�	�	PROPN
brj-23187	156	4	⃐	⃐	NUM
brj-23187	156	5	�	�	PROPN
brj-23187	156	6	𝑜𝑏𝑠	𝑜𝑏𝑠	NOUN
brj-23187	156	7	represents	represent	VERB
brj-23187	156	8	the	the	DET
brj-23187	156	9	average	average	NOUN
brj-23187	156	10	of	of	ADP
brj-23187	156	11	all	all	DET
brj-23187	156	12	observed	observed	ADJ
brj-23187	156	13	values	value	NOUN
brj-23187	156	14	,	,	PUNCT
brj-23187	156	15	and	and	CCONJ
brj-23187	156	16	𝑛	𝑛	PRON
brj-23187	156	17	denotes	denote	VERB
brj-23187	156	18	the	the	DET
brj-23187	156	19	total	total	ADJ
brj-23187	156	20	number	number	NOUN
brj-23187	156	21	of	of	ADP
brj-23187	156	22	samples	sample	NOUN
brj-23187	156	23	.	.	PUNCT
brj-23187	157	1	the	the	DET
brj-23187	157	2	rmse	rmse	ADJ
brj-23187	157	3	quantifies	quantify	VERB
brj-23187	157	4	the	the	DET
brj-23187	157	5	difference	difference	NOUN
brj-23187	157	6	between	between	ADP
brj-23187	157	7	the	the	DET
brj-23187	157	8	predicted	predict	VERB
brj-23187	157	9	and	and	CCONJ
brj-23187	157	10	actual	actual	ADJ
brj-23187	157	11	values	value	NOUN
brj-23187	157	12	.	.	PUNCT
brj-23187	158	1	the	the	DET
brj-23187	158	2	rmse	rmse	PROPN
brj-23187	158	3	value	value	NOUN
brj-23187	158	4	typically	typically	ADV
brj-23187	158	5	ranges	range	VERB
brj-23187	158	6	between	between	ADP
brj-23187	158	7	0	0	NUM
brj-23187	158	8	and	and	CCONJ
brj-23187	158	9	1	1	NUM
brj-23187	158	10	,	,	PUNCT
brj-23187	158	11	where	where	SCONJ
brj-23187	158	12	values	value	NOUN
brj-23187	158	13	closer	close	ADV
brj-23187	158	14	to	to	ADP
brj-23187	158	15	0	0	NUM
brj-23187	158	16	indicate	indicate	VERB
brj-23187	158	17	high	high	ADJ
brj-23187	158	18	accuracy	accuracy	NOUN
brj-23187	158	19	.	.	PUNCT
brj-23187	159	1	in	in	ADP
brj-23187	159	2	contrast	contrast	NOUN
brj-23187	159	3	,	,	PUNCT
brj-23187	159	4	r2	r2	NOUN
brj-23187	159	5	measures	measure	NOUN
brj-23187	159	6	how	how	SCONJ
brj-23187	159	7	well	well	ADV
brj-23187	159	8	the	the	DET
brj-23187	159	9	predicted	predict	VERB
brj-23187	159	10	values	value	NOUN
brj-23187	159	11	fit	fit	VERB
brj-23187	159	12	the	the	DET
brj-23187	159	13	actual	actual	ADJ
brj-23187	159	14	values	value	NOUN
brj-23187	159	15	.	.	PUNCT
brj-23187	160	1	a	a	DET
brj-23187	160	2	higher	high	ADJ
brj-23187	160	3	r2	r2	NOUN
brj-23187	160	4	value	value	NOUN
brj-23187	160	5	suggests	suggest	VERB
brj-23187	160	6	a	a	DET
brj-23187	160	7	better	well	ADJ
brj-23187	160	8	fit	fit	NOUN
brj-23187	160	9	of	of	ADP
brj-23187	160	10	the	the	DET
brj-23187	160	11	model	model	NOUN
brj-23187	160	12	(	(	PUNCT
brj-23187	160	13	wang	wang	PROPN
brj-23187	160	14	et	et	PROPN
brj-23187	160	15	al	al	PROPN
brj-23187	160	16	.	.	PROPN
brj-23187	160	17	2022	2022	NUM
brj-23187	160	18	)	)	PUNCT
brj-23187	160	19	.	.	PUNCT
brj-23187	161	1	results	result	NOUN
brj-23187	161	2	and	and	CCONJ
brj-23187	161	3	analysis	analysis	NOUN
brj-23187	161	4	analysis	analysis	NOUN
brj-23187	161	5	of	of	ADP
brj-23187	161	6	the	the	DET
brj-23187	161	7	effect	effect	NOUN
brj-23187	161	8	during	during	ADP
brj-23187	161	9	the	the	DET
brj-23187	161	10	training	training	NOUN
brj-23187	161	11	stage	stage	NOUN
brj-23187	161	12	,	,	PUNCT
brj-23187	161	13	the	the	DET
brj-23187	161	14	variables	variable	NOUN
brj-23187	161	15	were	be	AUX
brj-23187	161	16	screened	screen	VERB
brj-23187	161	17	,	,	PUNCT
brj-23187	161	18	a	a	DET
brj-23187	161	19	dimensionless	dimensionless	NOUN
brj-23187	161	20	averaging	averaging	NOUN
brj-23187	161	21	of	of	ADP
brj-23187	161	22	the	the	DET
brj-23187	161	23	samples	sample	NOUN
brj-23187	161	24	was	be	AUX
brj-23187	161	25	performed	perform	VERB
brj-23187	161	26	,	,	PUNCT
brj-23187	161	27	and	and	CCONJ
brj-23187	161	28	a	a	DET
brj-23187	161	29	grey	grey	ADJ
brj-23187	161	30	correlation	correlation	NOUN
brj-23187	161	31	analysis	analysis	NOUN
brj-23187	161	32	conducted	conduct	VERB
brj-23187	161	33	.	.	PUNCT
brj-23187	162	1	for	for	ADP
brj-23187	162	2	the	the	DET
brj-23187	162	3	lignin	lignin	PROPN
brj-23187	162	4	removal	removal	NOUN
brj-23187	162	5	analysis	analysis	NOUN
brj-23187	162	6	,	,	PUNCT
brj-23187	162	7	the	the	DET
brj-23187	162	8	resolution	resolution	NOUN
brj-23187	162	9	coefficient	coefficient	NOUN
brj-23187	162	10	𝜌	𝜌	PART
brj-23187	162	11	was	be	AUX
brj-23187	162	12	set	set	VERB
brj-23187	162	13	to	to	ADP
brj-23187	162	14	0.4	0.4	NUM
brj-23187	162	15	,	,	PUNCT
brj-23187	162	16	and	and	CCONJ
brj-23187	162	17	then	then	ADV
brj-23187	162	18	computed	compute	VERB
brj-23187	162	19	the	the	DET
brj-23187	162	20	correlation	correlation	NOUN
brj-23187	162	21	degree	degree	NOUN
brj-23187	162	22	was	be	AUX
brj-23187	162	23	computed	compute	VERB
brj-23187	162	24	.	.	PUNCT
brj-23187	163	1	this	this	PRON
brj-23187	163	2	resulted	result	VERB
brj-23187	163	3	in	in	ADP
brj-23187	163	4	the	the	DET
brj-23187	163	5	following	follow	VERB
brj-23187	163	6	correlation	correlation	NOUN
brj-23187	163	7	degrees	degree	NOUN
brj-23187	163	8	:	:	PUNCT
brj-23187	163	9	𝑟1	𝑟1	NOUN
brj-23187	163	10	=	=	PUNCT
brj-23187	163	11	0.642	0.642	NUM
brj-23187	163	12	,	,	PUNCT
brj-23187	163	13	𝑟2	𝑟2	NOUN
brj-23187	163	14	=	=	SYM
brj-23187	163	15	0.778	0.778	NUM
brj-23187	163	16	,	,	PUNCT
brj-23187	163	17	𝑟3	𝑟3	NOUN
brj-23187	163	18	=	=	NUM
brj-23187	163	19	0.699	0.699	NUM
brj-23187	163	20	,	,	PUNCT
brj-23187	163	21	𝑟4	𝑟4	PROPN
brj-23187	163	22	=	=	SYM
brj-23187	163	23	0.747	0.747	NUM
brj-23187	163	24	,	,	PUNCT
brj-23187	163	25	𝑟5	𝑟5	NOUN
brj-23187	163	26	=	=	NOUN
brj-23187	163	27	0.770	0.770	NUM
brj-23187	163	28	,	,	PUNCT
brj-23187	163	29	𝑟6	𝑟6	NOUN
brj-23187	163	30	=	=	NOUN
brj-23187	163	31	0.717	0.717	NUM
brj-23187	163	32	,	,	PUNCT
brj-23187	163	33	𝑟7	𝑟7	NOUN
brj-23187	163	34	=	=	PUNCT
brj-23187	163	35	0.751	0.751	NUM
brj-23187	163	36	,	,	PUNCT
brj-23187	163	37	𝑟8	𝑟8	ADV
brj-23187	163	38	=	=	SYM
brj-23187	163	39	0.731	0.731	NUM
brj-23187	163	40	,	,	PUNCT
brj-23187	163	41	𝑟9	𝑟9	NOUN
brj-23187	163	42	=	=	NOUN
brj-23187	163	43	0.758	0.758	NUM
brj-23187	163	44	,	,	PUNCT
brj-23187	163	45	𝑟10	𝑟10	NOUN
brj-23187	163	46	=	=	SYM
brj-23187	163	47	0.764	0.764	NUM
brj-23187	163	48	,	,	PUNCT
brj-23187	163	49	𝑟11	𝑟11	NOUN
brj-23187	163	50	=	=	NOUN
brj-23187	163	51	0.672	0.672	NUM
brj-23187	163	52	,	,	PUNCT
brj-23187	163	53	𝑟12	𝑟12	PROPN
brj-23187	163	54	=	=	SYM
brj-23187	163	55	0.592	0.592	NUM
brj-23187	163	56	,	,	PUNCT
brj-23187	163	57	𝑟13	𝑟13	NOUN
brj-23187	163	58	=	=	PUNCT
brj-23187	163	59	0.545	0.545	NUM
brj-23187	163	60	,	,	PUNCT
brj-23187	163	61	and	and	CCONJ
brj-23187	163	62	𝑟14	𝑟14	NUM
brj-23187	163	63	=	=	SYM
brj-23187	163	64	0.592	0.592	NUM
brj-23187	163	65	,	,	PUNCT
brj-23187	163	66	and	and	CCONJ
brj-23187	163	67	𝑟15	𝑟15	NOUN
brj-23187	163	68	=	=	SYM
brj-23187	163	69	0.593	0.593	NUM
brj-23187	163	70	.	.	PUNCT
brj-23187	164	1	based	base	VERB
brj-23187	164	2	on	on	ADP
brj-23187	164	3	the	the	DET
brj-23187	164	4	degree	degree	NOUN
brj-23187	164	5	of	of	ADP
brj-23187	164	6	correlation	correlation	NOUN
brj-23187	164	7	,	,	PUNCT
brj-23187	164	8	the	the	DET
brj-23187	164	9	influencing	influence	VERB
brj-23187	164	10	factors	factor	NOUN
brj-23187	164	11	were	be	AUX
brj-23187	164	12	arranged	arrange	VERB
brj-23187	164	13	in	in	ADP
brj-23187	164	14	descending	descend	VERB
brj-23187	164	15	order	order	NOUN
brj-23187	164	16	:	:	PUNCT
brj-23187	164	17	𝑋2	𝑋2	VERB
brj-23187	164	18	>	>	X
brj-23187	164	19	𝑋5	𝑋5	PROPN
brj-23187	164	20	>	>	X
brj-23187	165	1	𝑋10	𝑋10	PROPN
brj-23187	165	2	>	>	X
brj-23187	165	3	𝑋9	𝑋9	PROPN
brj-23187	165	4	>	>	X
brj-23187	165	5	𝑋7	𝑋7	PROPN
brj-23187	165	6	>	>	X
brj-23187	165	7	𝑋4	𝑋4	X
brj-23187	165	8	>	>	X
brj-23187	165	9	𝑋	𝑋	PROPN
brj-23187	165	10	8	8	NUM
brj-23187	165	11	>	>	NOUN
brj-23187	165	12	𝑋6	𝑋6	NOUN
brj-23187	165	13	>	>	X
brj-23187	165	14	𝑋3	𝑋3	NOUN
brj-23187	165	15	>	>	X
brj-23187	166	1	𝑋11	𝑋11	PROPN
brj-23187	166	2	>	>	X
brj-23187	166	3	𝑋1	𝑋1	PROPN
brj-23187	166	4	>	>	X
brj-23187	166	5	𝑋15	𝑋15	PROPN
brj-23187	166	6	>	>	PUNCT
brj-23187	166	7	𝑋14	𝑋14	PROPN
brj-23187	166	8	>	>	X
brj-23187	166	9	𝑋12	𝑋12	PROPN
brj-23187	166	10	>	>	X
brj-23187	166	11	𝑋13	𝑋13	PROPN
brj-23187	166	12	.	.	PUNCT
brj-23187	167	1	using	use	VERB
brj-23187	167	2	a	a	DET
brj-23187	167	3	threshold	threshold	NOUN
brj-23187	167	4	value	value	NOUN
brj-23187	167	5	of	of	ADP
brj-23187	167	6	0.65	0.65	NUM
brj-23187	167	7	,	,	PUNCT
brj-23187	167	8	twelve	twelve	NUM
brj-23187	167	9	influencing	influence	VERB
brj-23187	167	10	factors	factor	NOUN
brj-23187	167	11	were	be	AUX
brj-23187	167	12	selected	select	VERB
brj-23187	167	13	:	:	PUNCT
brj-23187	167	14	𝑋2	𝑋2	ADJ
brj-23187	167	15	,	,	PUNCT
brj-23187	167	16	𝑋5	𝑋5	NOUN
brj-23187	167	17	,	,	PUNCT
brj-23187	167	18	𝑋10	𝑋10	PROPN
brj-23187	167	19	,	,	PUNCT
brj-23187	167	20	𝑋9	𝑋9	PROPN
brj-23187	167	21	,	,	PUNCT
brj-23187	167	22	𝑋7	𝑋7	PROPN
brj-23187	167	23	,	,	PUNCT
brj-23187	167	24	𝑋4	𝑋4	VERB
brj-23187	167	25	,	,	PUNCT
brj-23187	167	26	𝑋8	𝑋8	NOUN
brj-23187	167	27	,	,	PUNCT
brj-23187	167	28	𝑋6	𝑋6	NOUN
brj-23187	167	29	,	,	PUNCT
brj-23187	167	30	𝑋3	𝑋3	NOUN
brj-23187	167	31	,	,	PUNCT
brj-23187	167	32	𝑋11	𝑋11	PROPN
brj-23187	167	33	,	,	PUNCT
brj-23187	167	34	𝑋1	𝑋1	PROPN
brj-23187	167	35	,	,	PUNCT
brj-23187	167	36	and	and	CCONJ
brj-23187	167	37	𝑋15	𝑋15	PROPN
brj-23187	167	38	.	.	PUNCT
brj-23187	168	1	the	the	DET
brj-23187	168	2	data	datum	NOUN
brj-23187	168	3	for	for	ADP
brj-23187	168	4	the	the	DET
brj-23187	168	5	influencing	influence	VERB
brj-23187	168	6	factors	factor	NOUN
brj-23187	168	7	were	be	AUX
brj-23187	168	8	first	first	ADV
brj-23187	168	9	screened	screen	VERB
brj-23187	168	10	using	use	VERB
brj-23187	168	11	gra	gra	PROPN
brj-23187	168	12	and	and	CCONJ
brj-23187	168	13	then	then	ADV
brj-23187	168	14	subjected	subject	VERB
brj-23187	168	15	to	to	ADP
brj-23187	168	16	kpca	kpca	NOUN
brj-23187	168	17	dimensionality	dimensionality	NOUN
brj-23187	168	18	reduction	reduction	NOUN
brj-23187	168	19	.	.	PUNCT
brj-23187	169	1	for	for	ADP
brj-23187	169	2	instance	instance	NOUN
brj-23187	169	3	,	,	PUNCT
brj-23187	169	4	table	table	NOUN
brj-23187	169	5	1	1	NUM
brj-23187	169	6	lists	list	VERB
brj-23187	169	7	the	the	DET
brj-23187	169	8	12	12	NUM
brj-23187	169	9	eigenvalues	eigenvalue	NOUN
brj-23187	169	10	(	(	PUNCT
brj-23187	169	11	in	in	ADP
brj-23187	169	12	descending	descend	VERB
brj-23187	169	13	order	order	NOUN
brj-23187	169	14	)	)	PUNCT
brj-23187	169	15	and	and	CCONJ
brj-23187	169	16	their	their	PRON
brj-23187	169	17	associated	associate	VERB
brj-23187	169	18	and	and	CCONJ
brj-23187	169	19	cumulative	cumulative	ADJ
brj-23187	169	20	contribution	contribution	NOUN
brj-23187	169	21	values	value	NOUN
brj-23187	169	22	,	,	PUNCT
brj-23187	169	23	considering	consider	VERB
brj-23187	169	24	the	the	DET
brj-23187	169	25	extent	extent	NOUN
brj-23187	169	26	of	of	ADP
brj-23187	169	27	lignin	lignin	NOUN
brj-23187	169	28	removal	removal	NOUN
brj-23187	169	29	.	.	PUNCT
brj-23187	170	1	table	table	NOUN
brj-23187	170	2	1	1	NUM
brj-23187	170	3	shows	show	VERB
brj-23187	170	4	that	that	SCONJ
brj-23187	170	5	,	,	PUNCT
brj-23187	170	6	in	in	ADP
brj-23187	170	7	the	the	DET
brj-23187	170	8	training	training	NOUN
brj-23187	170	9	phase	phase	NOUN
brj-23187	170	10	,	,	PUNCT
brj-23187	170	11	there	there	PRON
brj-23187	170	12	were	be	VERB
brj-23187	170	13	four	four	NUM
brj-23187	170	14	principal	principal	ADJ
brj-23187	170	15	components	component	NOUN
brj-23187	170	16	with	with	ADP
brj-23187	170	17	a	a	DET
brj-23187	170	18	cumulative	cumulative	ADJ
brj-23187	170	19	contribution	contribution	NOUN
brj-23187	170	20	exceeding	exceed	VERB
brj-23187	170	21	95	95	NUM
brj-23187	170	22	%	%	NOUN
brj-23187	170	23	.	.	PUNCT
brj-23187	171	1	using	use	VERB
brj-23187	171	2	the	the	DET
brj-23187	171	3	method	method	NOUN
brj-23187	171	4	detailed	detail	VERB
brj-23187	171	5	in	in	ADP
brj-23187	171	6	input	input	NOUN
brj-23187	171	7	dimension	dimension	NOUN
brj-23187	171	8	reduction	reduction	NOUN
brj-23187	171	9	based	base	VERB
brj-23187	171	10	on	on	ADP
brj-23187	171	11	kpca	kpca	PROPN
brj-23187	171	12	,	,	PUNCT
brj-23187	171	13	the	the	DET
brj-23187	171	14	training	training	NOUN
brj-23187	171	15	data	datum	NOUN
brj-23187	171	16	were	be	AUX
brj-23187	171	17	reduced	reduce	VERB
brj-23187	171	18	to	to	ADP
brj-23187	171	19	four	four	NUM
brj-23187	171	20	principal	principal	ADJ
brj-23187	171	21	components	component	NOUN
brj-23187	171	22	and	and	CCONJ
brj-23187	171	23	they	they	PRON
brj-23187	171	24	were	be	AUX
brj-23187	171	25	used	use	VERB
brj-23187	171	26	for	for	ADP
brj-23187	171	27	the	the	DET
brj-23187	171	28	lssvm	lssvm	NOUN
brj-23187	171	29	modelling	modelling	NOUN
brj-23187	171	30	.	.	PUNCT
brj-23187	172	1	the	the	DET
brj-23187	172	2	penalty	penalty	NOUN
brj-23187	172	3	coefficient	coefficient	NOUN
brj-23187	172	4	𝑐	𝑐	PROPN
brj-23187	172	5	and	and	CCONJ
brj-23187	172	6	kernel	kernel	PROPN
brj-23187	172	7	function	function	NOUN
brj-23187	172	8	width	width	VERB
brj-23187	172	9	𝜎	𝜎	PROPN
brj-23187	172	10	of	of	ADP
brj-23187	172	11	the	the	DET
brj-23187	172	12	lssvm	lssvm	NOUN
brj-23187	172	13	model	model	NOUN
brj-23187	172	14	were	be	AUX
brj-23187	172	15	chosen	choose	VERB
brj-23187	172	16	as	as	ADP
brj-23187	172	17	30	30	NUM
brj-23187	172	18	and	and	CCONJ
brj-23187	172	19	0.01	0.01	NUM
brj-23187	172	20	,	,	PUNCT
brj-23187	172	21	respectively	respectively	ADV
brj-23187	172	22	.	.	PUNCT
brj-23187	173	1	upon	upon	SCONJ
brj-23187	173	2	completing	complete	VERB
brj-23187	173	3	the	the	DET
brj-23187	173	4	modelling	modelling	NOUN
brj-23187	173	5	,	,	PUNCT
brj-23187	173	6	the	the	DET
brj-23187	173	7	authors	author	NOUN
brj-23187	173	8	employed	employ	VERB
brj-23187	173	9	the	the	DET
brj-23187	173	10	method	method	NOUN
brj-23187	173	11	described	describe	VERB
brj-23187	173	12	in	in	ADP
brj-23187	173	13	prediction	prediction	NOUN
brj-23187	173	14	of	of	ADP
brj-23187	173	15	enzymatic	enzymatic	ADJ
brj-23187	173	16	hydrolysis	hydrolysis	NOUN
brj-23187	173	17	efficiency	efficiency	NOUN
brj-23187	173	18	to	to	PART
brj-23187	173	19	test	test	VERB
brj-23187	173	20	and	and	CCONJ
brj-23187	173	21	validate	validate	VERB
brj-23187	173	22	the	the	DET
brj-23187	173	23	data	datum	NOUN
brj-23187	173	24	in	in	ADP
brj-23187	173	25	the	the	DET
brj-23187	173	26	test	test	NOUN
brj-23187	173	27	set	set	VERB
brj-23187	173	28	.	.	PUNCT
brj-23187	174	1	peer	peer	NOUN
brj-23187	174	2	-	-	PUNCT
brj-23187	174	3	reviewed	review	VERB
brj-23187	174	4	article	article	NOUN
brj-23187	174	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	174	6	fu	fu	PROPN
brj-23187	174	7	et	et	PROPN
brj-23187	174	8	al	al	PROPN
brj-23187	174	9	.	.	PROPN
brj-23187	175	1	(	(	PUNCT
brj-23187	175	2	2024	2024	NUM
brj-23187	175	3	)	)	PUNCT
brj-23187	175	4	.	.	PUNCT
brj-23187	176	1	“	"	PUNCT
brj-23187	176	2	predicting	predict	VERB
brj-23187	176	3	enzymatic	enzymatic	ADJ
brj-23187	176	4	hydrolysis	hydrolysis	NOUN
brj-23187	176	5	,	,	PUNCT
brj-23187	176	6	”	"	PUNCT
brj-23187	176	7	bioresources	bioresource	NOUN
brj-23187	176	8	19(2	19(2	NUM
brj-23187	176	9	)	)	PUNCT
brj-23187	176	10	,	,	PUNCT
brj-23187	176	11	3505	3505	NUM
brj-23187	176	12	-	-	SYM
brj-23187	176	13	3519	3519	NUM
brj-23187	176	14	.	.	PUNCT
brj-23187	177	1	3513	3513	NUM
brj-23187	177	2	table	table	NOUN
brj-23187	177	3	1	1	NUM
brj-23187	177	4	.	.	PUNCT
brj-23187	177	5	kernel	kernel	PROPN
brj-23187	177	6	principal	principal	PROPN
brj-23187	177	7	component	component	NOUN
brj-23187	177	8	analysis	analysis	NOUN
brj-23187	177	9	results	result	VERB
brj-23187	177	10	serial	serial	ADJ
brj-23187	177	11	number	number	NOUN
brj-23187	177	12	eigenvalue	eigenvalue	NOUN
brj-23187	177	13	contributions	contribution	NOUN
brj-23187	177	14	(	(	PUNCT
brj-23187	177	15	%	%	INTJ
brj-23187	177	16	)	)	PUNCT
brj-23187	177	17	cumulative	cumulative	ADJ
brj-23187	177	18	contribution	contribution	NOUN
brj-23187	177	19	(	(	PUNCT
brj-23187	177	20	%	%	INTJ
brj-23187	177	21	)	)	PUNCT
brj-23187	177	22	1	1	NUM
brj-23187	177	23	8.712	8.712	NUM
brj-23187	177	24	37.301	37.301	NUM
brj-23187	177	25	37.301	37.301	NUM
brj-23187	177	26	2	2	NUM
brj-23187	177	27	3.421	3.421	NUM
brj-23187	177	28	27.049	27.049	NUM
brj-23187	177	29	64.351	64.351	NUM
brj-23187	177	30	3	3	NUM
brj-23187	177	31	1.413	1.413	NUM
brj-23187	177	32	22.278	22.278	NUM
brj-23187	177	33	86.629	86.629	NUM
brj-23187	177	34	4	4	NUM
brj-23187	177	35	1.043	1.043	NUM
brj-23187	177	36	12.877	12.877	NUM
brj-23187	177	37	99.507	99.507	NUM
brj-23187	177	38	5	5	NUM
brj-23187	177	39	0.673	0.673	NUM
brj-23187	177	40	0.286	0.286	NUM
brj-23187	177	41	99.793	99.793	NUM
brj-23187	177	42	6	6	NUM
brj-23187	177	43	0.452	0.452	NUM
brj-23187	177	44	0.101	0.101	NUM
brj-23187	177	45	99.894	99.894	NUM
brj-23187	177	46	7	7	NUM
brj-23187	177	47	0.032	0.032	NUM
brj-23187	177	48	0.033	0.033	NUM
brj-23187	177	49	99.932	99.932	NUM
brj-23187	177	50	8	8	NUM
brj-23187	177	51	0.014	0.014	NUM
brj-23187	177	52	0.025	0.025	NUM
brj-23187	177	53	99.957	99.957	NUM
brj-23187	177	54	9	9	NUM
brj-23187	177	55	0.004	0.004	NUM
brj-23187	177	56	0.017	0.017	NUM
brj-23187	177	57	99.974	99.974	NUM
brj-23187	177	58	10	10	NUM
brj-23187	177	59	0.003	0.003	NUM
brj-23187	177	60	0.015	0.015	NUM
brj-23187	177	61	99.990	99.990	NUM
brj-23187	177	62	11	11	NUM
brj-23187	177	63	0.002	0.002	NUM
brj-23187	177	64	0.005	0.005	NUM
brj-23187	177	65	99.996	99.996	NUM
brj-23187	177	66	12	12	NUM
brj-23187	177	67	0.003	0.003	NUM
brj-23187	177	68	0.004	0.004	NUM
brj-23187	177	69	100	100	NUM
brj-23187	177	70	figures	figure	NOUN
brj-23187	177	71	3	3	NUM
brj-23187	177	72	and	and	CCONJ
brj-23187	177	73	4	4	NUM
brj-23187	177	74	depict	depict	VERB
brj-23187	177	75	the	the	DET
brj-23187	177	76	results	result	NOUN
brj-23187	177	77	of	of	ADP
brj-23187	177	78	the	the	DET
brj-23187	177	79	model	model	NOUN
brj-23187	177	80	training	training	NOUN
brj-23187	177	81	,	,	PUNCT
brj-23187	177	82	prediction	prediction	NOUN
brj-23187	177	83	,	,	PUNCT
brj-23187	177	84	and	and	CCONJ
brj-23187	177	85	error	error	NOUN
brj-23187	177	86	analysis	analysis	NOUN
brj-23187	177	87	for	for	ADP
brj-23187	177	88	the	the	DET
brj-23187	177	89	final	final	ADJ
brj-23187	177	90	removal	removal	NOUN
brj-23187	177	91	values	value	NOUN
brj-23187	177	92	of	of	ADP
brj-23187	177	93	lignin	lignin	NOUN
brj-23187	177	94	and	and	CCONJ
brj-23187	177	95	hemicellulose	hemicellulose	NOUN
brj-23187	177	96	.	.	PUNCT
brj-23187	178	1	the	the	DET
brj-23187	178	2	figures	figure	NOUN
brj-23187	178	3	show	show	VERB
brj-23187	178	4	the	the	DET
brj-23187	178	5	training	training	NOUN
brj-23187	178	6	and	and	CCONJ
brj-23187	178	7	prediction	prediction	NOUN
brj-23187	178	8	errors	error	NOUN
brj-23187	178	9	,	,	PUNCT
brj-23187	178	10	representing	represent	VERB
brj-23187	178	11	the	the	DET
brj-23187	178	12	differences	difference	NOUN
brj-23187	178	13	between	between	ADP
brj-23187	178	14	the	the	DET
brj-23187	178	15	measured	measure	VERB
brj-23187	178	16	and	and	CCONJ
brj-23187	178	17	predicted	predict	VERB
brj-23187	178	18	or	or	CCONJ
brj-23187	178	19	actual	actual	ADJ
brj-23187	178	20	training	training	NOUN
brj-23187	178	21	values	value	NOUN
brj-23187	178	22	.	.	PUNCT
brj-23187	179	1	fig	fig	NOUN
brj-23187	179	2	.	.	PUNCT
brj-23187	180	1	3	3	X
brj-23187	180	2	.	.	X
brj-23187	180	3	lignin	lignin	NOUN
brj-23187	180	4	removal	removal	NOUN
brj-23187	180	5	modelling	modelling	NOUN
brj-23187	180	6	and	and	CCONJ
brj-23187	180	7	prediction	prediction	NOUN
brj-23187	180	8	results	result	VERB
brj-23187	180	9	peer	peer	NOUN
brj-23187	180	10	-	-	PUNCT
brj-23187	180	11	reviewed	review	VERB
brj-23187	180	12	article	article	NOUN
brj-23187	180	13	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	180	14	fu	fu	PROPN
brj-23187	180	15	et	et	PROPN
brj-23187	180	16	al	al	PROPN
brj-23187	180	17	.	.	PROPN
brj-23187	181	1	(	(	PUNCT
brj-23187	181	2	2024	2024	NUM
brj-23187	181	3	)	)	PUNCT
brj-23187	181	4	.	.	PUNCT
brj-23187	182	1	“	"	PUNCT
brj-23187	182	2	predicting	predict	VERB
brj-23187	182	3	enzymatic	enzymatic	ADJ
brj-23187	182	4	hydrolysis	hydrolysis	NOUN
brj-23187	182	5	,	,	PUNCT
brj-23187	182	6	”	"	PUNCT
brj-23187	182	7	bioresources	bioresource	NOUN
brj-23187	182	8	19(2	19(2	NUM
brj-23187	182	9	)	)	PUNCT
brj-23187	182	10	,	,	PUNCT
brj-23187	182	11	3505	3505	NUM
brj-23187	182	12	-	-	SYM
brj-23187	182	13	3519	3519	NUM
brj-23187	182	14	.	.	PUNCT
brj-23187	183	1	3514	3514	NUM
brj-23187	183	2	fig	fig	NOUN
brj-23187	183	3	.	.	PUNCT
brj-23187	184	1	4	4	X
brj-23187	184	2	.	.	X
brj-23187	184	3	hemicellulose	hemicellulose	NOUN
brj-23187	184	4	removal	removal	NOUN
brj-23187	184	5	modelling	modelling	NOUN
brj-23187	184	6	and	and	CCONJ
brj-23187	184	7	prediction	prediction	NOUN
brj-23187	184	8	results	result	NOUN
brj-23187	184	9	from	from	ADP
brj-23187	184	10	figs	fig	NOUN
brj-23187	184	11	.	.	PUNCT
brj-23187	184	12	3	3	NUM
brj-23187	184	13	and	and	CCONJ
brj-23187	184	14	4	4	NUM
brj-23187	184	15	,	,	PUNCT
brj-23187	184	16	it	it	PRON
brj-23187	184	17	was	be	AUX
brj-23187	184	18	inferred	infer	VERB
brj-23187	184	19	that	that	SCONJ
brj-23187	184	20	the	the	DET
brj-23187	184	21	method	method	NOUN
brj-23187	184	22	described	describe	VERB
brj-23187	184	23	in	in	ADP
brj-23187	184	24	this	this	DET
brj-23187	184	25	study	study	NOUN
brj-23187	184	26	accurately	accurately	ADV
brj-23187	184	27	modeled	model	VERB
brj-23187	184	28	and	and	CCONJ
brj-23187	184	29	predicted	predict	VERB
brj-23187	184	30	the	the	DET
brj-23187	184	31	lignin	lignin	NOUN
brj-23187	184	32	removal	removal	NOUN
brj-23187	184	33	.	.	PUNCT
brj-23187	185	1	the	the	DET
brj-23187	185	2	rmse	rmse	NOUN
brj-23187	185	3	of	of	ADP
brj-23187	185	4	training	training	NOUN
brj-23187	185	5	was	be	AUX
brj-23187	185	6	4.50	4.50	NUM
brj-23187	185	7	,	,	PUNCT
brj-23187	185	8	the	the	DET
brj-23187	185	9	fitting	fitting	ADJ
brj-23187	185	10	degree	degree	NOUN
brj-23187	185	11	was	be	AUX
brj-23187	185	12	0.78	0.78	NUM
brj-23187	185	13	,	,	PUNCT
brj-23187	185	14	the	the	DET
brj-23187	185	15	rmse	rmse	NOUN
brj-23187	185	16	of	of	ADP
brj-23187	185	17	testing	testing	NOUN
brj-23187	185	18	was	be	AUX
brj-23187	185	19	5.11	5.11	NUM
brj-23187	185	20	,	,	PUNCT
brj-23187	185	21	and	and	CCONJ
brj-23187	185	22	the	the	DET
brj-23187	185	23	fitting	fitting	ADJ
brj-23187	185	24	degree	degree	NOUN
brj-23187	185	25	was	be	AUX
brj-23187	185	26	0.73	0.73	NUM
brj-23187	185	27	;	;	PUNCT
brj-23187	185	28	for	for	ADP
brj-23187	185	29	the	the	DET
brj-23187	185	30	modelling	modelling	NOUN
brj-23187	185	31	and	and	CCONJ
brj-23187	185	32	prediction	prediction	NOUN
brj-23187	185	33	of	of	ADP
brj-23187	185	34	hemicellulose	hemicellulose	NOUN
brj-23187	185	35	removal	removal	NOUN
brj-23187	185	36	,	,	PUNCT
brj-23187	185	37	the	the	DET
brj-23187	185	38	rmse	rmse	NOUN
brj-23187	185	39	during	during	ADP
brj-23187	185	40	training	training	NOUN
brj-23187	185	41	was	be	AUX
brj-23187	185	42	4.64	4.64	NUM
brj-23187	185	43	,	,	PUNCT
brj-23187	185	44	the	the	DET
brj-23187	185	45	fitting	fitting	ADJ
brj-23187	185	46	degree	degree	NOUN
brj-23187	185	47	was	be	AUX
brj-23187	185	48	0.72	0.72	NUM
brj-23187	185	49	,	,	PUNCT
brj-23187	185	50	the	the	DET
brj-23187	185	51	rmse	rmse	NOUN
brj-23187	185	52	during	during	ADP
brj-23187	185	53	testing	testing	NOUN
brj-23187	185	54	was	be	AUX
brj-23187	185	55	5.14	5.14	NUM
brj-23187	185	56	,	,	PUNCT
brj-23187	185	57	and	and	CCONJ
brj-23187	185	58	the	the	DET
brj-23187	185	59	fitting	fitting	ADJ
brj-23187	185	60	degree	degree	NOUN
brj-23187	185	61	was	be	AUX
brj-23187	185	62	0.70	0.70	NUM
brj-23187	185	63	.	.	PUNCT
brj-23187	186	1	the	the	DET
brj-23187	186	2	proposed	propose	VERB
brj-23187	186	3	method	method	NOUN
brj-23187	186	4	demonstrated	demonstrate	VERB
brj-23187	186	5	robust	robust	ADJ
brj-23187	186	6	modelling	modelling	NOUN
brj-23187	186	7	and	and	CCONJ
brj-23187	186	8	prediction	prediction	NOUN
brj-23187	186	9	capabilities	capability	NOUN
brj-23187	186	10	for	for	ADP
brj-23187	186	11	lignin	lignin	NOUN
brj-23187	186	12	and	and	CCONJ
brj-23187	186	13	hemicellulose	hemicellulose	NOUN
brj-23187	186	14	removal	removal	NOUN
brj-23187	186	15	.	.	PUNCT
brj-23187	187	1	additionally	additionally	ADV
brj-23187	187	2	,	,	PUNCT
brj-23187	187	3	the	the	DET
brj-23187	187	4	random	random	ADJ
brj-23187	187	5	selection	selection	NOUN
brj-23187	187	6	of	of	ADP
brj-23187	187	7	actual	actual	ADJ
brj-23187	187	8	industrial	industrial	ADJ
brj-23187	187	9	data	datum	NOUN
brj-23187	187	10	for	for	ADP
brj-23187	187	11	this	this	DET
brj-23187	187	12	study	study	NOUN
brj-23187	187	13	led	lead	VERB
brj-23187	187	14	to	to	ADP
brj-23187	187	15	fewer	few	ADJ
brj-23187	187	16	edge	edge	NOUN
brj-23187	187	17	data	datum	NOUN
brj-23187	187	18	points	point	NOUN
brj-23187	187	19	in	in	ADP
brj-23187	187	20	the	the	DET
brj-23187	187	21	high	high	ADV
brj-23187	187	22	-	-	PUNCT
brj-23187	187	23	dimensional	dimensional	ADJ
brj-23187	187	24	space	space	NOUN
brj-23187	187	25	of	of	ADP
brj-23187	187	26	the	the	DET
brj-23187	187	27	dataset	dataset	NOUN
brj-23187	187	28	,	,	PUNCT
brj-23187	187	29	enhancing	enhance	VERB
brj-23187	187	30	the	the	DET
brj-23187	187	31	predictive	predictive	ADJ
brj-23187	187	32	outcomes	outcome	NOUN
brj-23187	187	33	at	at	ADP
brj-23187	187	34	the	the	DET
brj-23187	187	35	inference	inference	NOUN
brj-23187	187	36	stage	stage	NOUN
brj-23187	187	37	.	.	PUNCT
brj-23187	188	1	comparative	comparative	ADJ
brj-23187	188	2	analysis	analysis	NOUN
brj-23187	188	3	the	the	DET
brj-23187	188	4	authors	author	NOUN
brj-23187	188	5	verified	verify	VERB
brj-23187	188	6	the	the	DET
brj-23187	188	7	efficacy	efficacy	NOUN
brj-23187	188	8	of	of	ADP
brj-23187	188	9	their	their	PRON
brj-23187	188	10	proposed	propose	VERB
brj-23187	188	11	method	method	NOUN
brj-23187	188	12	through	through	ADP
brj-23187	188	13	a	a	DET
brj-23187	188	14	comparative	comparative	ADJ
brj-23187	188	15	study	study	NOUN
brj-23187	188	16	that	that	PRON
brj-23187	188	17	examined	examine	VERB
brj-23187	188	18	various	various	ADJ
brj-23187	188	19	resolution	resolution	NOUN
brj-23187	188	20	coefficients	coefficient	NOUN
brj-23187	188	21	(	(	PUNCT
brj-23187	188	22	𝜌	𝜌	NOUN
brj-23187	188	23	)	)	PUNCT
brj-23187	188	24	,	,	PUNCT
brj-23187	188	25	penalty	penalty	NOUN
brj-23187	188	26	coefficients	coefficient	NOUN
brj-23187	188	27	(	(	PUNCT
brj-23187	188	28	𝑐	𝑐	NOUN
brj-23187	188	29	)	)	PUNCT
brj-23187	188	30	,	,	PUNCT
brj-23187	188	31	and	and	CCONJ
brj-23187	188	32	kernel	kernel	PROPN
brj-23187	188	33	function	function	NOUN
brj-23187	188	34	widths	width	NOUN
brj-23187	188	35	(	(	PUNCT
brj-23187	188	36	𝜎	𝜎	NOUN
brj-23187	188	37	)	)	PUNCT
brj-23187	188	38	.	.	PUNCT
brj-23187	189	1	the	the	DET
brj-23187	189	2	effectiveness	effectiveness	NOUN
brj-23187	189	3	of	of	ADP
brj-23187	189	4	the	the	DET
brj-23187	189	5	gra	gra	PROPN
brj-23187	189	6	variable	variable	NOUN
brj-23187	189	7	-	-	PUNCT
brj-23187	189	8	screening	screen	VERB
brj-23187	189	9	module	module	NOUN
brj-23187	189	10	in	in	ADP
brj-23187	189	11	the	the	DET
brj-23187	189	12	proposed	propose	VERB
brj-23187	189	13	method	method	NOUN
brj-23187	189	14	(	(	PUNCT
brj-23187	189	15	gra	gra	PROPN
brj-23187	189	16	-	-	PUNCT
brj-23187	189	17	kpca	kpca	NOUN
brj-23187	189	18	-	-	PUNCT
brj-23187	189	19	lssvm	lssvm	NOUN
brj-23187	189	20	)	)	PUNCT
brj-23187	189	21	was	be	AUX
brj-23187	189	22	verified	verify	VERB
brj-23187	189	23	and	and	CCONJ
brj-23187	189	24	compared	compare	VERB
brj-23187	189	25	with	with	ADP
brj-23187	189	26	that	that	PRON
brj-23187	189	27	of	of	ADP
brj-23187	189	28	the	the	DET
brj-23187	189	29	nongra	nongra	NOUN
brj-23187	189	30	module	module	NOUN
brj-23187	189	31	(	(	PUNCT
brj-23187	189	32	kpca	kpca	NOUN
brj-23187	189	33	-	-	PUNCT
brj-23187	189	34	lssvm	lssvm	NOUN
brj-23187	189	35	)	)	PUNCT
brj-23187	189	36	.	.	PUNCT
brj-23187	190	1	the	the	DET
brj-23187	190	2	results	result	NOUN
brj-23187	190	3	are	be	AUX
brj-23187	190	4	illustrated	illustrate	VERB
brj-23187	190	5	in	in	ADP
brj-23187	190	6	figs	fig	NOUN
brj-23187	190	7	.	.	PUNCT
brj-23187	191	1	5	5	NUM
brj-23187	191	2	and	and	CCONJ
brj-23187	191	3	6	6	NUM
brj-23187	191	4	in	in	ADP
brj-23187	191	5	table	table	NOUN
brj-23187	191	6	2	2	NUM
brj-23187	191	7	.	.	PUNCT
brj-23187	191	8	peer	peer	NOUN
brj-23187	191	9	-	-	PUNCT
brj-23187	191	10	reviewed	review	VERB
brj-23187	191	11	article	article	NOUN
brj-23187	191	12	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	191	13	fu	fu	PROPN
brj-23187	191	14	et	et	PROPN
brj-23187	191	15	al	al	PROPN
brj-23187	191	16	.	.	PROPN
brj-23187	192	1	(	(	PUNCT
brj-23187	192	2	2024	2024	NUM
brj-23187	192	3	)	)	PUNCT
brj-23187	192	4	.	.	PUNCT
brj-23187	193	1	“	"	PUNCT
brj-23187	193	2	predicting	predict	VERB
brj-23187	193	3	enzymatic	enzymatic	ADJ
brj-23187	193	4	hydrolysis	hydrolysis	NOUN
brj-23187	193	5	,	,	PUNCT
brj-23187	193	6	”	"	PUNCT
brj-23187	193	7	bioresources	bioresource	NOUN
brj-23187	193	8	19(2	19(2	NUM
brj-23187	193	9	)	)	PUNCT
brj-23187	193	10	,	,	PUNCT
brj-23187	193	11	3505	3505	NUM
brj-23187	193	12	-	-	SYM
brj-23187	193	13	3519	3519	NUM
brj-23187	193	14	.	.	PUNCT
brj-23187	194	1	3515	3515	NUM
brj-23187	194	2	fig	fig	NOUN
brj-23187	194	3	.	.	PUNCT
brj-23187	195	1	5	5	X
brj-23187	195	2	.	.	X
brj-23187	195	3	prediction	prediction	NOUN
brj-23187	195	4	results	result	NOUN
brj-23187	195	5	and	and	CCONJ
brj-23187	195	6	errors	error	NOUN
brj-23187	195	7	of	of	ADP
brj-23187	195	8	lignin	lignin	PROPN
brj-23187	195	9	removal	removal	NOUN
brj-23187	195	10	fig	fig	NOUN
brj-23187	195	11	.	.	PUNCT
brj-23187	196	1	6	6	NUM
brj-23187	196	2	.	.	X
brj-23187	196	3	prediction	prediction	NOUN
brj-23187	196	4	results	result	NOUN
brj-23187	196	5	and	and	CCONJ
brj-23187	196	6	errors	error	NOUN
brj-23187	196	7	of	of	ADP
brj-23187	196	8	hemicellulose	hemicellulose	NOUN
brj-23187	196	9	removal	removal	NOUN
brj-23187	196	10	peer	peer	NOUN
brj-23187	196	11	-	-	PUNCT
brj-23187	196	12	reviewed	review	VERB
brj-23187	196	13	article	article	NOUN
brj-23187	196	14	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	196	15	fu	fu	PROPN
brj-23187	196	16	et	et	PROPN
brj-23187	196	17	al	al	PROPN
brj-23187	196	18	.	.	PROPN
brj-23187	197	1	(	(	PUNCT
brj-23187	197	2	2024	2024	NUM
brj-23187	197	3	)	)	PUNCT
brj-23187	197	4	.	.	PUNCT
brj-23187	198	1	“	"	PUNCT
brj-23187	198	2	predicting	predict	VERB
brj-23187	198	3	enzymatic	enzymatic	ADJ
brj-23187	198	4	hydrolysis	hydrolysis	NOUN
brj-23187	198	5	,	,	PUNCT
brj-23187	198	6	”	"	PUNCT
brj-23187	198	7	bioresources	bioresource	NOUN
brj-23187	198	8	19(2	19(2	NUM
brj-23187	198	9	)	)	PUNCT
brj-23187	198	10	,	,	PUNCT
brj-23187	198	11	3505	3505	NUM
brj-23187	198	12	-	-	SYM
brj-23187	198	13	3519	3519	NUM
brj-23187	198	14	.	.	PUNCT
brj-23187	199	1	3516	3516	NUM
brj-23187	199	2	table	table	NOUN
brj-23187	199	3	2	2	NUM
brj-23187	199	4	.	.	PUNCT
brj-23187	199	5	analysis	analysis	NOUN
brj-23187	199	6	of	of	ADP
brj-23187	199	7	removal	removal	NOUN
brj-23187	199	8	error	error	NOUN
brj-23187	199	9	results	result	NOUN
brj-23187	199	10	method	method	NOUN
brj-23187	199	11	of	of	ADP
brj-23187	199	12	this	this	DET
brj-23187	199	13	article	article	NOUN
brj-23187	199	14	(	(	PUNCT
brj-23187	199	15	𝜌	𝜌	X
brj-23187	199	16	=	=	SYM
brj-23187	199	17	0.4	0.4	NUM
brj-23187	199	18	,	,	PUNCT
brj-23187	199	19	𝑐	𝑐	NOUN
brj-23187	199	20	=	=	SYM
brj-23187	199	21	30	30	NUM
brj-23187	199	22	,	,	PUNCT
brj-23187	199	23	𝜎	𝜎	NOUN
brj-23187	199	24	=	=	NOUN
brj-23187	199	25	0.01	0.01	NUM
brj-23187	199	26	)	)	PUNCT
brj-23187	199	27	kpca	kpca	NOUN
brj-23187	199	28	-	-	PUNCT
brj-23187	199	29	lssvm	lssvm	NOUN
brj-23187	199	30	(	(	PUNCT
brj-23187	199	31	𝜌	𝜌	X
brj-23187	199	32	=	=	SYM
brj-23187	199	33	0.4	0.4	NUM
brj-23187	199	34	,	,	PUNCT
brj-23187	199	35	𝑐	𝑐	NOUN
brj-23187	199	36	=	=	SYM
brj-23187	199	37	30	30	NUM
brj-23187	199	38	,	,	PUNCT
brj-23187	199	39	𝜎	𝜎	NOUN
brj-23187	199	40	=	=	NOUN
brj-23187	199	41	0.01	0.01	NUM
brj-23187	199	42	)	)	PUNCT
brj-23187	199	43	method	method	NOUN
brj-23187	199	44	of	of	ADP
brj-23187	199	45	this	this	DET
brj-23187	199	46	article	article	NOUN
brj-23187	199	47	(	(	PUNCT
brj-23187	199	48	𝜌	𝜌	X
brj-23187	199	49	=	=	SYM
brj-23187	199	50	0.4	0.4	NUM
brj-23187	199	51	,	,	PUNCT
brj-23187	199	52	𝑐	𝑐	NOUN
brj-23187	199	53	=	=	SYM
brj-23187	199	54	20	20	NUM
brj-23187	199	55	,	,	PUNCT
brj-23187	199	56	𝜎	𝜎	NOUN
brj-23187	199	57	=	=	NOUN
brj-23187	199	58	0.04	0.04	NUM
brj-23187	199	59	)	)	PUNCT
brj-23187	199	60	method	method	NOUN
brj-23187	199	61	of	of	ADP
brj-23187	199	62	this	this	DET
brj-23187	199	63	article	article	NOUN
brj-23187	199	64	(	(	PUNCT
brj-23187	199	65	𝜌	𝜌	X
brj-23187	199	66	=	=	SYM
brj-23187	199	67	0.6	0.6	NUM
brj-23187	199	68	,	,	PUNCT
brj-23187	199	69	𝑐	𝑐	NOUN
brj-23187	199	70	=	=	SYM
brj-23187	199	71	30	30	NUM
brj-23187	199	72	,	,	PUNCT
brj-23187	199	73	𝜎	𝜎	NOUN
brj-23187	199	74	=	=	NOUN
brj-23187	199	75	0.01	0.01	NUM
brj-23187	199	76	)	)	PUNCT
brj-23187	199	77	rmse	rmse	NOUN
brj-23187	199	78	𝝍𝟏	𝝍𝟏	ADJ
brj-23187	199	79	𝝍𝟐	𝝍𝟐	NOUN
brj-23187	199	80	5.11	5.11	NUM
brj-23187	199	81	5.14	5.14	NUM
brj-23187	199	82	6.14	6.14	NUM
brj-23187	199	83	6.29	6.29	NUM
brj-23187	199	84	5.24	5.24	NUM
brj-23187	199	85	5.26	5.26	NUM
brj-23187	199	86	5.39	5.39	NUM
brj-23187	199	87	5.30	5.30	NUM
brj-23187	199	88	r2	r2	NOUN
brj-23187	199	89	𝝍𝟏	𝝍𝟏	ADJ
brj-23187	199	90	𝝍𝟐	𝝍𝟐	NOUN
brj-23187	199	91	0.73	0.73	NUM
brj-23187	199	92	0.70	0.70	NUM
brj-23187	199	93	0.67	0.67	NUM
brj-23187	199	94	0.64	0.64	NUM
brj-23187	199	95	0.72	0.72	NUM
brj-23187	199	96	0.69	0.69	NUM
brj-23187	199	97	0.72	0.72	NUM
brj-23187	199	98	0.69	0.69	NUM
brj-23187	199	99	table	table	NOUN
brj-23187	199	100	2	2	NUM
brj-23187	199	101	shows	show	VERB
brj-23187	199	102	that	that	SCONJ
brj-23187	199	103	the	the	DET
brj-23187	199	104	kpca	kpca	NOUN
brj-23187	199	105	-	-	PUNCT
brj-23187	199	106	lssvm	lssvm	NOUN
brj-23187	199	107	method	method	NOUN
brj-23187	199	108	provided	provide	VERB
brj-23187	199	109	accurate	accurate	ADJ
brj-23187	199	110	rmse	rmse	NOUN
brj-23187	199	111	predictions	prediction	NOUN
brj-23187	199	112	for	for	ADP
brj-23187	199	113	lignin	lignin	NOUN
brj-23187	199	114	and	and	CCONJ
brj-23187	199	115	hemicellulose	hemicellulose	NOUN
brj-23187	199	116	removal	removal	NOUN
brj-23187	199	117	values	value	NOUN
brj-23187	199	118	,	,	PUNCT
brj-23187	199	119	measured	measure	VERB
brj-23187	199	120	at	at	ADP
brj-23187	199	121	6.14	6.14	NUM
brj-23187	199	122	and	and	CCONJ
brj-23187	199	123	6.29	6.29	NUM
brj-23187	199	124	,	,	PUNCT
brj-23187	199	125	respectively	respectively	ADV
brj-23187	199	126	.	.	PUNCT
brj-23187	200	1	high	high	ADJ
brj-23187	200	2	r2	r2	PROPN
brj-23187	200	3	values	value	NOUN
brj-23187	200	4	of	of	ADP
brj-23187	200	5	0.67	0.67	NUM
brj-23187	200	6	and	and	CCONJ
brj-23187	200	7	0.64	0.64	NUM
brj-23187	200	8	were	be	AUX
brj-23187	200	9	obtained	obtain	VERB
brj-23187	200	10	for	for	ADP
brj-23187	200	11	lignin	lignin	NOUN
brj-23187	200	12	and	and	CCONJ
brj-23187	200	13	hemicellulose	hemicellulose	NOUN
brj-23187	200	14	removal	removal	NOUN
brj-23187	200	15	,	,	PUNCT
brj-23187	200	16	respectively	respectively	ADV
brj-23187	200	17	.	.	PUNCT
brj-23187	201	1	the	the	DET
brj-23187	201	2	proposed	propose	VERB
brj-23187	201	3	method	method	NOUN
brj-23187	201	4	(	(	PUNCT
brj-23187	201	5	𝜌	𝜌	X
brj-23187	201	6	0.4	0.4	NUM
brj-23187	201	7	,	,	PUNCT
brj-23187	201	8	𝑐	𝑐	PROPN
brj-23187	201	9	30	30	NUM
brj-23187	201	10	,	,	PUNCT
brj-23187	201	11	𝜎	𝜎	PROPN
brj-23187	201	12	0.01	0.01	NUM
brj-23187	201	13	)	)	PUNCT
brj-23187	201	14	yielded	yield	VERB
brj-23187	201	15	rmse	rmse	ADJ
brj-23187	201	16	values	value	NOUN
brj-23187	201	17	of	of	ADP
brj-23187	201	18	5.11	5.11	NUM
brj-23187	201	19	and	and	CCONJ
brj-23187	201	20	5.14	5.14	NUM
brj-23187	201	21	for	for	ADP
brj-23187	201	22	the	the	DET
brj-23187	201	23	predicted	predict	VERB
brj-23187	201	24	lignin	lignin	NOUN
brj-23187	201	25	and	and	CCONJ
brj-23187	201	26	hemicellulose	hemicellulose	NOUN
brj-23187	201	27	removal	removal	NOUN
brj-23187	201	28	,	,	PUNCT
brj-23187	201	29	respectively	respectively	ADV
brj-23187	201	30	,	,	PUNCT
brj-23187	201	31	with	with	ADP
brj-23187	201	32	corresponding	correspond	VERB
brj-23187	201	33	r2	r2	NOUN
brj-23187	201	34	values	value	NOUN
brj-23187	201	35	of	of	ADP
brj-23187	201	36	0.73	0.73	NUM
brj-23187	201	37	and	and	CCONJ
brj-23187	201	38	0.7	0.7	NUM
brj-23187	201	39	.	.	PUNCT
brj-23187	202	1	the	the	DET
brj-23187	202	2	results	result	NOUN
brj-23187	202	3	obtained	obtain	VERB
brj-23187	202	4	by	by	ADP
brj-23187	202	5	this	this	DET
brj-23187	202	6	method	method	NOUN
brj-23187	202	7	demonstrate	demonstrate	VERB
brj-23187	202	8	a	a	DET
brj-23187	202	9	high	high	ADJ
brj-23187	202	10	level	level	NOUN
brj-23187	202	11	of	of	ADP
brj-23187	202	12	prediction	prediction	NOUN
brj-23187	202	13	accuracy	accuracy	NOUN
brj-23187	202	14	,	,	PUNCT
brj-23187	202	15	minimal	minimal	ADJ
brj-23187	202	16	error	error	NOUN
brj-23187	202	17	,	,	PUNCT
brj-23187	202	18	and	and	CCONJ
brj-23187	202	19	a	a	DET
brj-23187	202	20	substantial	substantial	ADJ
brj-23187	202	21	degree	degree	NOUN
brj-23187	202	22	of	of	ADP
brj-23187	202	23	model	model	NOUN
brj-23187	202	24	fitting	fit	VERB
brj-23187	202	25	.	.	PUNCT
brj-23187	203	1	using	use	VERB
brj-23187	203	2	gra	gra	PROPN
brj-23187	203	3	for	for	ADP
brj-23187	203	4	variable	variable	ADJ
brj-23187	203	5	selection	selection	NOUN
brj-23187	203	6	considerably	considerably	ADV
brj-23187	203	7	improved	improve	VERB
brj-23187	203	8	performance	performance	NOUN
brj-23187	203	9	in	in	ADP
brj-23187	203	10	modelling	modelling	NOUN
brj-23187	203	11	and	and	CCONJ
brj-23187	203	12	prediction	prediction	NOUN
brj-23187	203	13	.	.	PUNCT
brj-23187	204	1	simultaneously	simultaneously	ADV
brj-23187	204	2	,	,	PUNCT
brj-23187	204	3	it	it	PRON
brj-23187	204	4	is	be	AUX
brj-23187	204	5	evident	evident	ADJ
brj-23187	204	6	that	that	SCONJ
brj-23187	204	7	adjusting	adjust	VERB
brj-23187	204	8	the	the	DET
brj-23187	204	9	𝜌	𝜌	X
brj-23187	204	10	value	value	NOUN
brj-23187	204	11	to	to	ADP
brj-23187	204	12	0.6	0.6	NUM
brj-23187	204	13	(	(	PUNCT
brj-23187	204	14	𝜌	𝜌	X
brj-23187	204	15	0.6	0.6	NUM
brj-23187	204	16	,	,	PUNCT
brj-23187	204	17	𝑐	𝑐	PROPN
brj-23187	204	18	30	30	NUM
brj-23187	204	19	,	,	PUNCT
brj-23187	204	20	𝜎	𝜎	PROPN
brj-23187	204	21	0.01	0.01	NUM
brj-23187	204	22	)	)	PUNCT
brj-23187	204	23	within	within	ADP
brj-23187	204	24	this	this	DET
brj-23187	204	25	approach	approach	NOUN
brj-23187	204	26	led	lead	VERB
brj-23187	204	27	to	to	ADP
brj-23187	204	28	an	an	DET
brj-23187	204	29	increase	increase	NOUN
brj-23187	204	30	in	in	ADP
brj-23187	204	31	the	the	DET
brj-23187	204	32	corresponding	corresponding	ADJ
brj-23187	204	33	rmse	rmse	NOUN
brj-23187	204	34	values	value	NOUN
brj-23187	204	35	for	for	ADP
brj-23187	204	36	predicting	predict	VERB
brj-23187	204	37	lignin	lignin	NOUN
brj-23187	204	38	and	and	CCONJ
brj-23187	204	39	hemicellulose	hemicellulose	NOUN
brj-23187	204	40	removal	removal	NOUN
brj-23187	204	41	,	,	PUNCT
brj-23187	204	42	with	with	ADP
brj-23187	204	43	values	value	NOUN
brj-23187	204	44	of	of	ADP
brj-23187	204	45	5.39	5.39	NUM
brj-23187	204	46	and	and	CCONJ
brj-23187	204	47	5.30	5.30	NUM
brj-23187	204	48	,	,	PUNCT
brj-23187	204	49	respectively	respectively	ADV
brj-23187	204	50	.	.	PUNCT
brj-23187	205	1	concurrently	concurrently	ADV
brj-23187	205	2	,	,	PUNCT
brj-23187	205	3	r2	r2	PROPN
brj-23187	205	4	shows	show	VERB
brj-23187	205	5	a	a	DET
brj-23187	205	6	minor	minor	ADJ
brj-23187	205	7	decline	decline	NOUN
brj-23187	205	8	to	to	ADP
brj-23187	205	9	0.72	0.72	NUM
brj-23187	205	10	and	and	CCONJ
brj-23187	205	11	0.69	0.69	NUM
brj-23187	205	12	.	.	PUNCT
brj-23187	206	1	through	through	ADP
brj-23187	206	2	changing	change	VERB
brj-23187	206	3	the	the	DET
brj-23187	206	4	parameters	parameter	NOUN
brj-23187	206	5	𝑐	𝑐	PROPN
brj-23187	206	6	and	and	CCONJ
brj-23187	206	7	𝜎	𝜎	PROPN
brj-23187	206	8	(	(	PUNCT
brj-23187	206	9	𝜌	𝜌	X
brj-23187	206	10	=	=	SYM
brj-23187	206	11	0.4	0.4	NUM
brj-23187	206	12	,	,	PUNCT
brj-23187	206	13	𝑐	𝑐	NOUN
brj-23187	206	14	=	=	SYM
brj-23187	206	15	20	20	NUM
brj-23187	206	16	,	,	PUNCT
brj-23187	206	17	𝜎	𝜎	NOUN
brj-23187	206	18	=	=	NOUN
brj-23187	206	19	0.04	0.04	NUM
brj-23187	206	20	)	)	PUNCT
brj-23187	206	21	,	,	PUNCT
brj-23187	206	22	the	the	DET
brj-23187	206	23	corresponding	correspond	VERB
brj-23187	206	24	rmse	rmse	NOUN
brj-23187	206	25	increased	increase	VERB
brj-23187	206	26	to	to	ADP
brj-23187	206	27	5.24	5.24	NUM
brj-23187	206	28	and	and	CCONJ
brj-23187	206	29	5.26	5.26	NUM
brj-23187	206	30	,	,	PUNCT
brj-23187	206	31	and	and	CCONJ
brj-23187	206	32	r2	r2	PROPN
brj-23187	206	33	decreased	decrease	VERB
brj-23187	206	34	to	to	ADP
brj-23187	206	35	0.72	0.72	NUM
brj-23187	206	36	and	and	CCONJ
brj-23187	206	37	0.69	0.69	NUM
brj-23187	206	38	.	.	PUNCT
brj-23187	207	1	the	the	DET
brj-23187	207	2	observation	observation	NOUN
brj-23187	207	3	mentioned	mention	VERB
brj-23187	207	4	above	above	ADV
brj-23187	207	5	suggests	suggest	VERB
brj-23187	207	6	that	that	SCONJ
brj-23187	207	7	variations	variation	NOUN
brj-23187	207	8	in	in	ADP
brj-23187	207	9	𝜌	𝜌	ADP
brj-23187	207	10	,	,	PUNCT
brj-23187	207	11	𝑐	𝑐	NOUN
brj-23187	207	12	,	,	PUNCT
brj-23187	207	13	and	and	CCONJ
brj-23187	207	14	𝜎	𝜎	PROPN
brj-23187	207	15	will	will	AUX
brj-23187	207	16	exert	exert	VERB
brj-23187	207	17	a	a	DET
brj-23187	207	18	substantial	substantial	ADJ
brj-23187	207	19	impact	impact	NOUN
brj-23187	207	20	on	on	ADP
brj-23187	207	21	both	both	CCONJ
brj-23187	207	22	the	the	DET
brj-23187	207	23	accuracy	accuracy	NOUN
brj-23187	207	24	of	of	ADP
brj-23187	207	25	predictions	prediction	NOUN
brj-23187	207	26	and	and	CCONJ
brj-23187	207	27	the	the	DET
brj-23187	207	28	degree	degree	NOUN
brj-23187	207	29	of	of	ADP
brj-23187	207	30	model	model	NOUN
brj-23187	207	31	fitting	fitting	ADJ
brj-23187	207	32	.	.	PUNCT
brj-23187	208	1	the	the	DET
brj-23187	208	2	appropriate	appropriate	ADJ
brj-23187	208	3	selection	selection	NOUN
brj-23187	208	4	of	of	ADP
brj-23187	208	5	𝜌	𝜌	X
brj-23187	208	6	,	,	PUNCT
brj-23187	208	7	𝑐	𝑐	NOUN
brj-23187	208	8	,	,	PUNCT
brj-23187	208	9	and	and	CCONJ
brj-23187	208	10	𝜎	𝜎	PROPN
brj-23187	208	11	values	value	NOUN
brj-23187	208	12	can	can	AUX
brj-23187	208	13	effectively	effectively	ADV
brj-23187	208	14	minimise	minimise	VERB
brj-23187	208	15	prediction	prediction	NOUN
brj-23187	208	16	errors	error	NOUN
brj-23187	208	17	and	and	CCONJ
brj-23187	208	18	enhance	enhance	VERB
brj-23187	208	19	the	the	DET
brj-23187	208	20	degree	degree	NOUN
brj-23187	208	21	of	of	ADP
brj-23187	208	22	model	model	NOUN
brj-23187	208	23	fitting	fitting	ADJ
brj-23187	208	24	.	.	PUNCT
brj-23187	209	1	this	this	DET
brj-23187	209	2	study	study	NOUN
brj-23187	209	3	used	use	VERB
brj-23187	209	4	the	the	DET
brj-23187	209	5	grid	grid	NOUN
brj-23187	209	6	search	search	NOUN
brj-23187	209	7	method	method	NOUN
brj-23187	209	8	to	to	PART
brj-23187	209	9	determine	determine	VERB
brj-23187	209	10	the	the	DET
brj-23187	209	11	optimal	optimal	ADJ
brj-23187	209	12	parameters	parameter	NOUN
brj-23187	209	13	.	.	PUNCT
brj-23187	210	1	in	in	ADP
brj-23187	210	2	addition	addition	NOUN
brj-23187	210	3	,	,	PUNCT
brj-23187	210	4	advanced	advanced	ADJ
brj-23187	210	5	optimisation	optimisation	NOUN
brj-23187	210	6	techniques	technique	NOUN
brj-23187	210	7	,	,	PUNCT
brj-23187	210	8	such	such	ADJ
brj-23187	210	9	as	as	ADP
brj-23187	210	10	particle	particle	NOUN
brj-23187	210	11	swarm	swarm	NOUN
brj-23187	210	12	optimisation	optimisation	NOUN
brj-23187	210	13	and	and	CCONJ
brj-23187	210	14	genetic	genetic	ADJ
brj-23187	210	15	algorithms	algorithm	NOUN
brj-23187	210	16	,	,	PUNCT
brj-23187	210	17	can	can	AUX
brj-23187	210	18	be	be	AUX
brj-23187	210	19	employed	employ	VERB
brj-23187	210	20	for	for	ADP
brj-23187	210	21	further	further	ADJ
brj-23187	210	22	refinement	refinement	NOUN
brj-23187	210	23	.	.	PUNCT
brj-23187	211	1	conclusions	conclusion	NOUN
brj-23187	211	2	the	the	DET
brj-23187	211	3	extents	extent	NOUN
brj-23187	211	4	of	of	ADP
brj-23187	211	5	lignin	lignin	NOUN
brj-23187	211	6	and	and	CCONJ
brj-23187	211	7	hemicellulose	hemicellulose	NOUN
brj-23187	211	8	removal	removal	NOUN
brj-23187	211	9	are	be	AUX
brj-23187	211	10	crucial	crucial	ADJ
brj-23187	211	11	for	for	ADP
brj-23187	211	12	assessing	assess	VERB
brj-23187	211	13	crop	crop	NOUN
brj-23187	211	14	straw	straw	NOUN
brj-23187	211	15	’s	’s	PART
brj-23187	211	16	efficiency	efficiency	NOUN
brj-23187	211	17	in	in	ADP
brj-23187	211	18	enzymatic	enzymatic	ADJ
brj-23187	211	19	hydrolysis	hydrolysis	NOUN
brj-23187	211	20	.	.	PUNCT
brj-23187	212	1	this	this	DET
brj-23187	212	2	study	study	NOUN
brj-23187	212	3	proposes	propose	VERB
brj-23187	212	4	an	an	DET
brj-23187	212	5	efficient	efficient	ADJ
brj-23187	212	6	prediction	prediction	NOUN
brj-23187	212	7	method	method	NOUN
brj-23187	212	8	for	for	ADP
brj-23187	212	9	the	the	DET
brj-23187	212	10	two	two	NUM
brj-23187	212	11	straw	straw	NOUN
brj-23187	212	12	enzymatic	enzymatic	ADJ
brj-23187	212	13	hydrolysis	hydrolysis	NOUN
brj-23187	212	14	efficiency	efficiency	NOUN
brj-23187	212	15	indicators	indicator	NOUN
brj-23187	212	16	based	base	VERB
brj-23187	212	17	on	on	ADP
brj-23187	212	18	grakpca	grakpca	NOUN
brj-23187	212	19	-	-	PUNCT
brj-23187	212	20	lssvm	lssvm	NOUN
brj-23187	212	21	.	.	PUNCT
brj-23187	213	1	1	1	X
brj-23187	213	2	.	.	X
brj-23187	214	1	first	first	ADV
brj-23187	214	2	,	,	PUNCT
brj-23187	214	3	a	a	DET
brj-23187	214	4	prediction	prediction	NOUN
brj-23187	214	5	model	model	NOUN
brj-23187	214	6	for	for	ADP
brj-23187	214	7	the	the	DET
brj-23187	214	8	enzymatic	enzymatic	ADJ
brj-23187	214	9	hydrolysis	hydrolysis	NOUN
brj-23187	214	10	efficiency	efficiency	NOUN
brj-23187	214	11	was	be	AUX
brj-23187	214	12	developed	develop	VERB
brj-23187	214	13	by	by	ADP
brj-23187	214	14	employing	employ	VERB
brj-23187	214	15	gra	gra	PROPN
brj-23187	214	16	variable	variable	ADJ
brj-23187	214	17	screening	screening	NOUN
brj-23187	214	18	,	,	PUNCT
brj-23187	214	19	kpca	kpca	PROPN
brj-23187	214	20	input	input	NOUN
brj-23187	214	21	dimension	dimension	NOUN
brj-23187	214	22	reduction	reduction	NOUN
brj-23187	214	23	,	,	PUNCT
brj-23187	214	24	and	and	CCONJ
brj-23187	214	25	lssvm	lssvm	NOUN
brj-23187	214	26	model	model	NOUN
brj-23187	214	27	training	training	NOUN
brj-23187	214	28	using	use	VERB
brj-23187	214	29	actual	actual	ADJ
brj-23187	214	30	production	production	NOUN
brj-23187	214	31	data	datum	NOUN
brj-23187	214	32	.	.	PUNCT
brj-23187	215	1	2	2	X
brj-23187	215	2	.	.	NUM
brj-23187	215	3	subsequently	subsequently	ADV
brj-23187	215	4	,	,	PUNCT
brj-23187	215	5	this	this	DET
brj-23187	215	6	model	model	NOUN
brj-23187	215	7	was	be	AUX
brj-23187	215	8	applied	apply	VERB
brj-23187	215	9	using	use	VERB
brj-23187	215	10	production	production	NOUN
brj-23187	215	11	condition	condition	NOUN
brj-23187	215	12	data	datum	NOUN
brj-23187	215	13	to	to	PART
brj-23187	215	14	accurately	accurately	ADV
brj-23187	215	15	estimate	estimate	VERB
brj-23187	215	16	the	the	DET
brj-23187	215	17	final	final	ADJ
brj-23187	215	18	enzymatic	enzymatic	ADJ
brj-23187	215	19	hydrolysis	hydrolysis	NOUN
brj-23187	215	20	efficiency	efficiency	NOUN
brj-23187	215	21	in	in	ADP
brj-23187	215	22	real	real	ADJ
brj-23187	215	23	-	-	PUNCT
brj-23187	215	24	time	time	NOUN
brj-23187	215	25	.	.	PUNCT
brj-23187	216	1	peer	peer	NOUN
brj-23187	216	2	-	-	PUNCT
brj-23187	216	3	reviewed	review	VERB
brj-23187	216	4	article	article	NOUN
brj-23187	216	5	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	216	6	fu	fu	PROPN
brj-23187	216	7	et	et	PROPN
brj-23187	216	8	al	al	PROPN
brj-23187	216	9	.	.	PROPN
brj-23187	217	1	(	(	PUNCT
brj-23187	217	2	2024	2024	NUM
brj-23187	217	3	)	)	PUNCT
brj-23187	217	4	.	.	PUNCT
brj-23187	218	1	“	"	PUNCT
brj-23187	218	2	predicting	predict	VERB
brj-23187	218	3	enzymatic	enzymatic	ADJ
brj-23187	218	4	hydrolysis	hydrolysis	NOUN
brj-23187	218	5	,	,	PUNCT
brj-23187	218	6	”	"	PUNCT
brj-23187	218	7	bioresources	bioresource	NOUN
brj-23187	218	8	19(2	19(2	NUM
brj-23187	218	9	)	)	PUNCT
brj-23187	218	10	,	,	PUNCT
brj-23187	218	11	3505	3505	NUM
brj-23187	218	12	-	-	SYM
brj-23187	218	13	3519	3519	NUM
brj-23187	218	14	.	.	PUNCT
brj-23187	219	1	3517	3517	NUM
brj-23187	219	2	3	3	NUM
brj-23187	219	3	.	.	PUNCT
brj-23187	220	1	the	the	DET
brj-23187	220	2	effectiveness	effectiveness	NOUN
brj-23187	220	3	of	of	ADP
brj-23187	220	4	this	this	DET
brj-23187	220	5	method	method	NOUN
brj-23187	220	6	was	be	AUX
brj-23187	220	7	validated	validate	VERB
brj-23187	220	8	through	through	ADP
brj-23187	220	9	numerous	numerous	ADJ
brj-23187	220	10	experimental	experimental	ADJ
brj-23187	220	11	tests	test	NOUN
brj-23187	220	12	.	.	PUNCT
brj-23187	221	1	through	through	ADP
brj-23187	221	2	utilising	utilise	VERB
brj-23187	221	3	the	the	DET
brj-23187	221	4	acquired	acquire	VERB
brj-23187	221	5	model	model	NOUN
brj-23187	221	6	for	for	ADP
brj-23187	221	7	prediction	prediction	NOUN
brj-23187	221	8	,	,	PUNCT
brj-23187	221	9	the	the	DET
brj-23187	221	10	authors	author	NOUN
brj-23187	221	11	observed	observe	VERB
brj-23187	221	12	minimal	minimal	ADJ
brj-23187	221	13	errors	error	NOUN
brj-23187	221	14	and	and	CCONJ
brj-23187	221	15	achieved	achieve	VERB
brj-23187	221	16	a	a	DET
brj-23187	221	17	high	high	ADJ
brj-23187	221	18	level	level	NOUN
brj-23187	221	19	of	of	ADP
brj-23187	221	20	fitting	fitting	ADJ
brj-23187	221	21	accuracy	accuracy	NOUN
brj-23187	221	22	,	,	PUNCT
brj-23187	221	23	indicating	indicate	VERB
brj-23187	221	24	exceptional	exceptional	ADJ
brj-23187	221	25	performance	performance	NOUN
brj-23187	221	26	.	.	PUNCT
brj-23187	222	1	as	as	ADP
brj-23187	222	2	a	a	DET
brj-23187	222	3	broader	broad	ADJ
brj-23187	222	4	conclusion	conclusion	NOUN
brj-23187	222	5	,	,	PUNCT
brj-23187	222	6	the	the	DET
brj-23187	222	7	method	method	NOUN
brj-23187	222	8	introduced	introduce	VERB
brj-23187	222	9	in	in	ADP
brj-23187	222	10	this	this	DET
brj-23187	222	11	paper	paper	NOUN
brj-23187	222	12	offers	offer	VERB
brj-23187	222	13	an	an	DET
brj-23187	222	14	optimised	optimise	VERB
brj-23187	222	15	design	design	NOUN
brj-23187	222	16	basis	basis	NOUN
brj-23187	222	17	for	for	ADP
brj-23187	222	18	the	the	DET
brj-23187	222	19	efficient	efficient	ADJ
brj-23187	222	20	enzymatic	enzymatic	ADJ
brj-23187	222	21	hydrolysis	hydrolysis	NOUN
brj-23187	222	22	of	of	ADP
brj-23187	222	23	crops	crop	NOUN
brj-23187	222	24	and	and	CCONJ
brj-23187	222	25	provides	provide	VERB
brj-23187	222	26	soft	soft	ADJ
brj-23187	222	27	sensor	sensor	NOUN
brj-23187	222	28	support	support	NOUN
brj-23187	222	29	for	for	ADP
brj-23187	222	30	effectively	effectively	ADV
brj-23187	222	31	controlling	control	VERB
brj-23187	222	32	the	the	DET
brj-23187	222	33	enzymatic	enzymatic	ADJ
brj-23187	222	34	hydrolysis	hydrolysis	NOUN
brj-23187	222	35	process	process	NOUN
brj-23187	222	36	.	.	PUNCT
brj-23187	223	1	however	however	ADV
brj-23187	223	2	,	,	PUNCT
brj-23187	223	3	the	the	DET
brj-23187	223	4	prediction	prediction	NOUN
brj-23187	223	5	accuracy	accuracy	NOUN
brj-23187	223	6	of	of	ADP
brj-23187	223	7	the	the	DET
brj-23187	223	8	methodology	methodology	NOUN
brj-23187	223	9	presented	present	VERB
brj-23187	223	10	in	in	ADP
brj-23187	223	11	this	this	DET
brj-23187	223	12	paper	paper	NOUN
brj-23187	223	13	was	be	AUX
brj-23187	223	14	constrained	constrain	VERB
brj-23187	223	15	by	by	ADP
brj-23187	223	16	the	the	DET
brj-23187	223	17	limited	limited	ADJ
brj-23187	223	18	scale	scale	NOUN
brj-23187	223	19	of	of	ADP
brj-23187	223	20	training	training	NOUN
brj-23187	223	21	samples	sample	NOUN
brj-23187	223	22	and	and	CCONJ
brj-23187	223	23	the	the	DET
brj-23187	223	24	absence	absence	NOUN
brj-23187	223	25	of	of	ADP
brj-23187	223	26	sophisticated	sophisticated	ADJ
brj-23187	223	27	parameter	parameter	NOUN
brj-23187	223	28	optimization	optimization	NOUN
brj-23187	223	29	strategies	strategy	NOUN
brj-23187	223	30	.	.	PUNCT
brj-23187	224	1	future	future	ADJ
brj-23187	224	2	work	work	NOUN
brj-23187	224	3	should	should	AUX
brj-23187	224	4	concentrate	concentrate	VERB
brj-23187	224	5	on	on	ADP
brj-23187	224	6	assembling	assemble	VERB
brj-23187	224	7	more	more	ADV
brj-23187	224	8	extensive	extensive	ADJ
brj-23187	224	9	datasets	dataset	NOUN
brj-23187	224	10	,	,	PUNCT
brj-23187	224	11	alongside	alongside	ADP
brj-23187	224	12	the	the	DET
brj-23187	224	13	utilization	utilization	NOUN
brj-23187	224	14	of	of	ADP
brj-23187	224	15	advanced	advanced	ADJ
brj-23187	224	16	modelling	modelling	NOUN
brj-23187	224	17	algorithms	algorithm	NOUN
brj-23187	224	18	and	and	CCONJ
brj-23187	224	19	refined	refined	ADJ
brj-23187	224	20	parameter	parameter	NOUN
brj-23187	224	21	optimization	optimization	NOUN
brj-23187	224	22	techniques	technique	NOUN
brj-23187	224	23	.	.	PUNCT
brj-23187	225	1	such	such	DET
brj-23187	225	2	an	an	DET
brj-23187	225	3	approach	approach	NOUN
brj-23187	225	4	has	have	VERB
brj-23187	225	5	potential	potential	NOUN
brj-23187	225	6	to	to	PART
brj-23187	225	7	amplify	amplify	VERB
brj-23187	225	8	the	the	DET
brj-23187	225	9	accuracy	accuracy	NOUN
brj-23187	225	10	of	of	ADP
brj-23187	225	11	predictions	prediction	NOUN
brj-23187	225	12	and	and	CCONJ
brj-23187	225	13	bolster	bolster	VERB
brj-23187	225	14	the	the	DET
brj-23187	225	15	generalizability	generalizability	NOUN
brj-23187	225	16	of	of	ADP
brj-23187	225	17	the	the	DET
brj-23187	225	18	model	model	NOUN
brj-23187	225	19	.	.	PUNCT
brj-23187	226	1	acknowledgments	acknowledgment	NOUN
brj-23187	226	2	this	this	DET
brj-23187	226	3	work	work	NOUN
brj-23187	226	4	is	be	AUX
brj-23187	226	5	supported	support	VERB
brj-23187	226	6	by	by	ADP
brj-23187	226	7	the	the	DET
brj-23187	226	8	major	major	ADJ
brj-23187	226	9	industrial	industrial	ADJ
brj-23187	226	10	projects	project	NOUN
brj-23187	226	11	to	to	PART
brj-23187	226	12	transform	transform	VERB
brj-23187	226	13	old	old	ADJ
brj-23187	226	14	and	and	CCONJ
brj-23187	226	15	new	new	ADJ
brj-23187	226	16	growth	growth	NOUN
brj-23187	226	17	drivers	driver	NOUN
brj-23187	226	18	in	in	ADP
brj-23187	226	19	shandong	shandong	PROPN
brj-23187	226	20	province	province	PROPN
brj-23187	226	21	“	"	PUNCT
brj-23187	226	22	research	research	NOUN
brj-23187	226	23	and	and	CCONJ
brj-23187	226	24	industrial	industrial	ADJ
brj-23187	226	25	application	application	NOUN
brj-23187	226	26	of	of	ADP
brj-23187	226	27	citric	citric	ADJ
brj-23187	226	28	acid	acid	NOUN
brj-23187	226	29	green	green	PROPN
brj-23187	226	30	bio	bio	PROPN
brj-23187	226	31	-	-	ADJ
brj-23187	226	32	manufacturing	manufacturing	ADJ
brj-23187	226	33	technology	technology	NOUN
brj-23187	226	34	”	"	PUNCT
brj-23187	226	35	.	.	PUNCT
brj-23187	227	1	references	reference	NOUN
brj-23187	227	2	cited	cite	VERB
brj-23187	227	3	adnana	adnana	PROPN
brj-23187	227	4	,	,	PUNCT
brj-23187	227	5	r.	r.	PROPN
brj-23187	227	6	m.	m.	PROPN
brj-23187	227	7	,	,	PUNCT
brj-23187	227	8	lianga	lianga	ADV
brj-23187	227	9	,	,	PUNCT
brj-23187	227	10	z.	z.	PROPN
brj-23187	227	11	,	,	PUNCT
brj-23187	227	12	heddamb	heddamb	PROPN
brj-23187	227	13	,	,	PUNCT
brj-23187	227	14	s.	s.	PROPN
brj-23187	227	15	,	,	PUNCT
brj-23187	227	16	zounemat	zounemat	PROPN
brj-23187	227	17	-	-	PUNCT
brj-23187	227	18	kermanic	kermanic	ADJ
brj-23187	227	19	,	,	PUNCT
brj-23187	227	20	m.	m.	NOUN
brj-23187	227	21	,	,	PUNCT
brj-23187	227	22	and	and	CCONJ
brj-23187	227	23	kisid	kisid	PROPN
brj-23187	227	24	,	,	PUNCT
brj-23187	227	25	o.	o.	PROPN
brj-23187	227	26	l.	l.	PROPN
brj-23187	227	27	b.q	b.q	PROPN
brj-23187	228	1	.	.	PROPN
brj-23187	229	1	(	(	PUNCT
brj-23187	229	2	2019	2019	NUM
brj-23187	229	3	)	)	PUNCT
brj-23187	229	4	.	.	PUNCT
brj-23187	230	1	“	"	PUNCT
brj-23187	230	2	least	least	ADJ
brj-23187	230	3	square	square	ADJ
brj-23187	230	4	support	support	NOUN
brj-23187	230	5	vector	vector	NOUN
brj-23187	230	6	machine	machine	NOUN
brj-23187	230	7	and	and	CCONJ
brj-23187	230	8	multivariate	multivariate	VERB
brj-23187	230	9	adaptive	adaptive	ADJ
brj-23187	230	10	regression	regression	NOUN
brj-23187	230	11	splines	spline	NOUN
brj-23187	230	12	for	for	ADP
brj-23187	230	13	streamflow	streamflow	NOUN
brj-23187	230	14	prediction	prediction	NOUN
brj-23187	230	15	in	in	ADP
brj-23187	230	16	mountainous	mountainous	ADJ
brj-23187	230	17	basin	basin	NOUN
brj-23187	230	18	using	use	VERB
brj-23187	230	19	hydro	hydro	NOUN
brj-23187	230	20	-	-	PUNCT
brj-23187	230	21	meteorological	meteorological	ADJ
brj-23187	230	22	data	datum	NOUN
brj-23187	230	23	as	as	ADP
brj-23187	230	24	inputs	input	NOUN
brj-23187	230	25	,	,	PUNCT
brj-23187	230	26	”	"	PUNCT
brj-23187	230	27	journal	journal	NOUN
brj-23187	230	28	of	of	ADP
brj-23187	230	29	hydrology	hydrology	NOUN
brj-23187	230	30	586	586	NUM
brj-23187	230	31	,	,	PUNCT
brj-23187	230	32	article	article	NOUN
brj-23187	230	33	i	i	PROPN
brj-23187	230	34	d	d	PROPN
brj-23187	230	35	124371	124371	NUM
brj-23187	230	36	.	.	PUNCT
brj-23187	231	1	doi	doi	NOUN
brj-23187	231	2	:	:	PUNCT
brj-23187	231	3	10.1016	10.1016	NUM
brj-23187	231	4	/	/	SYM
brj-23187	231	5	j.jhydrol.2019.124371	j.jhydrol.2019.124371	PROPN
brj-23187	231	6	agrawal	agrawal	PROPN
brj-23187	231	7	,	,	PUNCT
brj-23187	231	8	r.	r.	PROPN
brj-23187	231	9	,	,	PUNCT
brj-23187	231	10	verma	verma	PROPN
brj-23187	231	11	,	,	PUNCT
brj-23187	231	12	a.	a.	NOUN
brj-23187	231	13	,	,	PUNCT
brj-23187	231	14	singhania	singhania	PROPN
brj-23187	231	15	,	,	PUNCT
brj-23187	231	16	r.	r.	PROPN
brj-23187	231	17	r.	r.	PROPN
brj-23187	231	18	,	,	PUNCT
brj-23187	231	19	varjani	varjani	PROPN
brj-23187	231	20	,	,	PUNCT
brj-23187	231	21	s.	s.	PROPN
brj-23187	231	22	,	,	PUNCT
brj-23187	231	23	cheng	cheng	PROPN
brj-23187	231	24	,	,	PUNCT
brj-23187	231	25	d.-d	d.-d	PROPN
brj-23187	231	26	.	.	PUNCT
brj-23187	231	27	,	,	PUNCT
brj-23187	231	28	and	and	CCONJ
brj-23187	231	29	patel	patel	PROPN
brj-23187	231	30	,	,	PUNCT
brj-23187	231	31	a.	a.	PROPN
brj-23187	231	32	k.	k.	PROPN
brj-23187	231	33	(	(	PUNCT
brj-23187	231	34	2021	2021	NUM
brj-23187	231	35	)	)	PUNCT
brj-23187	231	36	.	.	PUNCT
brj-23187	232	1	“	"	PUNCT
brj-23187	232	2	current	current	ADJ
brj-23187	232	3	understanding	understanding	NOUN
brj-23187	232	4	of	of	ADP
brj-23187	232	5	the	the	DET
brj-23187	232	6	inhibition	inhibition	NOUN
brj-23187	232	7	factors	factor	NOUN
brj-23187	232	8	and	and	CCONJ
brj-23187	232	9	their	their	PRON
brj-23187	232	10	mechanism	mechanism	NOUN
brj-23187	232	11	of	of	ADP
brj-23187	232	12	action	action	NOUN
brj-23187	232	13	for	for	ADP
brj-23187	232	14	the	the	DET
brj-23187	232	15	lignocellulosic	lignocellulosic	ADJ
brj-23187	232	16	biomass	biomass	NOUN
brj-23187	232	17	hydrolysis	hydrolysis	NOUN
brj-23187	232	18	,	,	PUNCT
brj-23187	232	19	”	"	PUNCT
brj-23187	232	20	bioresource	bioresource	ADP
brj-23187	232	21	technology	technology	NOUN
brj-23187	232	22	332	332	NUM
brj-23187	232	23	,	,	PUNCT
brj-23187	232	24	article	article	NOUN
brj-23187	232	25	i	i	PROPN
brj-23187	232	26	d	d	PROPN
brj-23187	232	27	125042	125042	NUM
brj-23187	232	28	.	.	PUNCT
brj-23187	233	1	doi	doi	NOUN
brj-23187	233	2	:	:	PUNCT
brj-23187	233	3	10.1016	10.1016	NUM
brj-23187	233	4	/	/	SYM
brj-23187	233	5	j.biortech.2021.125042	j.biortech.2021.125042	PROPN
brj-23187	233	6	anowar	anowar	PROPN
brj-23187	233	7	,	,	PUNCT
brj-23187	233	8	f.	f.	PROPN
brj-23187	233	9	,	,	PUNCT
brj-23187	233	10	and	and	CCONJ
brj-23187	233	11	sadaoui	sadaoui	PROPN
brj-23187	233	12	,	,	PUNCT
brj-23187	233	13	s.	s.	PROPN
brj-23187	233	14	(	(	PUNCT
brj-23187	233	15	2021	2021	NUM
brj-23187	233	16	)	)	PUNCT
brj-23187	233	17	.	.	PUNCT
brj-23187	234	1	“	"	PUNCT
brj-23187	234	2	incremental	incremental	ADJ
brj-23187	234	3	learning	learning	NOUN
brj-23187	234	4	framework	framework	NOUN
brj-23187	234	5	for	for	ADP
brj-23187	234	6	real	real	ADJ
brj-23187	234	7	-	-	PUNCT
brj-23187	234	8	world	world	NOUN
brj-23187	234	9	fraud	fraud	NOUN
brj-23187	234	10	detection	detection	NOUN
brj-23187	234	11	environment	environment	NOUN
brj-23187	234	12	,	,	PUNCT
brj-23187	234	13	”	"	PUNCT
brj-23187	234	14	computational	computational	ADJ
brj-23187	234	15	intelligence	intelligence	NOUN
brj-23187	234	16	37(1	37(1	NUM
brj-23187	234	17	)	)	PUNCT
brj-23187	234	18	,	,	PUNCT
brj-23187	234	19	635	635	NUM
brj-23187	234	20	-	-	SYM
brj-23187	234	21	656	656	NUM
brj-23187	234	22	.	.	PUNCT
brj-23187	235	1	doi	doi	NOUN
brj-23187	235	2	:	:	PUNCT
brj-23187	235	3	10.1111	10.1111	NUM
brj-23187	235	4	/	/	SYM
brj-23187	235	5	coin.12434	coin.12434	NOUN
brj-23187	235	6	anowar	anowar	NOUN
brj-23187	235	7	,	,	PUNCT
brj-23187	235	8	f.	f.	PROPN
brj-23187	235	9	,	,	PUNCT
brj-23187	235	10	sadaoui	sadaoui	PROPN
brj-23187	235	11	,	,	PUNCT
brj-23187	235	12	s.	s.	PROPN
brj-23187	235	13	,	,	PUNCT
brj-23187	235	14	and	and	CCONJ
brj-23187	235	15	selim	selim	PROPN
brj-23187	235	16	,	,	PUNCT
brj-23187	235	17	b.	b.	PROPN
brj-23187	235	18	(	(	PUNCT
brj-23187	235	19	2021	2021	NUM
brj-23187	235	20	)	)	PUNCT
brj-23187	235	21	.	.	PUNCT
brj-23187	236	1	“	"	PUNCT
brj-23187	236	2	conceptual	conceptual	ADJ
brj-23187	236	3	and	and	CCONJ
brj-23187	236	4	empirical	empirical	ADJ
brj-23187	236	5	comparison	comparison	NOUN
brj-23187	236	6	of	of	ADP
brj-23187	236	7	dimensionality	dimensionality	NOUN
brj-23187	236	8	reduction	reduction	NOUN
brj-23187	236	9	algorithms	algorithm	NOUN
brj-23187	236	10	(	(	PUNCT
brj-23187	236	11	pca	pca	PROPN
brj-23187	236	12	,	,	PUNCT
brj-23187	236	13	kpca	kpca	PROPN
brj-23187	236	14	,	,	PUNCT
brj-23187	236	15	lda	lda	PROPN
brj-23187	236	16	,	,	PUNCT
brj-23187	236	17	mds	mds	PROPN
brj-23187	236	18	,	,	PUNCT
brj-23187	236	19	svd	svd	PROPN
brj-23187	236	20	,	,	PUNCT
brj-23187	236	21	lle	lle	PROPN
brj-23187	236	22	,	,	PUNCT
brj-23187	236	23	isomap	isomap	NOUN
brj-23187	236	24	,	,	PUNCT
brj-23187	236	25	le	le	X
brj-23187	236	26	,	,	PUNCT
brj-23187	236	27	ica	ica	PROPN
brj-23187	236	28	,	,	PUNCT
brj-23187	236	29	t	t	PROPN
brj-23187	236	30	-	-	PUNCT
brj-23187	236	31	sne	sne	NOUN
brj-23187	236	32	)	)	PUNCT
brj-23187	236	33	,	,	PUNCT
brj-23187	236	34	”	"	PUNCT
brj-23187	236	35	computer	computer	NOUN
brj-23187	236	36	science	science	NOUN
brj-23187	236	37	review	review	NOUN
brj-23187	236	38	40	40	NUM
brj-23187	236	39	,	,	PUNCT
brj-23187	236	40	article	article	NOUN
brj-23187	236	41	i	i	PROPN
brj-23187	236	42	d	d	PROPN
brj-23187	236	43	100378	100378	NUM
brj-23187	236	44	.	.	PUNCT
brj-23187	237	1	doi	doi	NOUN
brj-23187	237	2	:	:	PUNCT
brj-23187	237	3	10.1016	10.1016	NUM
brj-23187	237	4	/	/	SYM
brj-23187	237	5	j.cosrev.2021.100378	j.cosrev.2021.100378	PROPN
brj-23187	237	6	antos	anto	VERB
brj-23187	237	7	,	,	PUNCT
brj-23187	237	8	j.	j.	PROPN
brj-23187	237	9	,	,	PUNCT
brj-23187	237	10	kubalcik	kubalcik	PROPN
brj-23187	237	11	,	,	PUNCT
brj-23187	237	12	m.	m.	NOUN
brj-23187	237	13	,	,	PUNCT
brj-23187	237	14	and	and	CCONJ
brj-23187	237	15	kuritka	kuritka	PROPN
brj-23187	237	16	,	,	PUNCT
brj-23187	237	17	i.	i.	NOUN
brj-23187	237	18	(	(	PUNCT
brj-23187	237	19	2022	2022	NUM
brj-23187	237	20	)	)	PUNCT
brj-23187	237	21	.	.	PUNCT
brj-23187	238	1	“	"	PUNCT
brj-23187	238	2	scalable	scalable	ADJ
brj-23187	238	3	non	non	ADJ
brj-23187	238	4	-	-	ADJ
brj-23187	238	5	dimensional	dimensional	ADJ
brj-23187	238	6	model	model	NOUN
brj-23187	238	7	predictive	predictive	ADJ
brj-23187	238	8	control	control	NOUN
brj-23187	238	9	of	of	ADP
brj-23187	238	10	liquid	liquid	ADJ
brj-23187	238	11	level	level	NOUN
brj-23187	238	12	in	in	ADP
brj-23187	238	13	generally	generally	ADV
brj-23187	238	14	shaped	shape	VERB
brj-23187	238	15	tanks	tank	NOUN
brj-23187	238	16	using	use	VERB
brj-23187	238	17	rbf	rbf	PROPN
brj-23187	238	18	neural	neural	ADJ
brj-23187	238	19	network	network	NOUN
brj-23187	238	20	,	,	PUNCT
brj-23187	238	21	”	"	PUNCT
brj-23187	238	22	international	international	ADJ
brj-23187	238	23	journal	journal	NOUN
brj-23187	238	24	of	of	ADP
brj-23187	238	25	control	control	NOUN
brj-23187	238	26	and	and	CCONJ
brj-23187	238	27	automation	automation	NOUN
brj-23187	238	28	systems	system	NOUN
brj-23187	238	29	20	20	NUM
brj-23187	238	30	,	,	PUNCT
brj-23187	238	31	1041	1041	NUM
brj-23187	238	32	-	-	SYM
brj-23187	238	33	1050	1050	NUM
brj-23187	238	34	.	.	PUNCT
brj-23187	239	1	doi	doi	NOUN
brj-23187	239	2	:	:	PUNCT
brj-23187	239	3	10.1007	10.1007	NUM
brj-23187	239	4	/	/	SYM
brj-23187	239	5	s12555	s12555	NOUN
brj-23187	239	6	-	-	PUNCT
brj-23187	239	7	020	020	NUM
brj-23187	239	8	-	-	PUNCT
brj-23187	239	9	0904	0904	NUM
brj-23187	239	10	-	-	SYM
brj-23187	239	11	9	9	NUM
brj-23187	239	12	chen	chen	PROPN
brj-23187	239	13	,	,	PUNCT
brj-23187	239	14	l.	l.	PROPN
brj-23187	239	15	,	,	PUNCT
brj-23187	239	16	and	and	CCONJ
brj-23187	239	17	zhou	zhou	PROPN
brj-23187	239	18	,	,	PUNCT
brj-23187	239	19	s.-s	s.-	NOUN
brj-23187	239	20	.	.	PUNCT
brj-23187	240	1	(	(	PUNCT
brj-23187	240	2	2018	2018	NUM
brj-23187	240	3	)	)	PUNCT
brj-23187	240	4	.	.	PUNCT
brj-23187	241	1	“	"	PUNCT
brj-23187	241	2	sparse	sparse	ADJ
brj-23187	241	3	algorithm	algorithm	NOUN
brj-23187	241	4	for	for	ADP
brj-23187	241	5	robust	robust	ADJ
brj-23187	241	6	lssvm	lssvm	NOUN
brj-23187	241	7	in	in	ADP
brj-23187	241	8	primal	primal	ADJ
brj-23187	241	9	space	space	NOUN
brj-23187	241	10	,	,	PUNCT
brj-23187	241	11	”	"	PUNCT
brj-23187	241	12	neurocomputing	neurocompute	VERB
brj-23187	241	13	275	275	NUM
brj-23187	241	14	,	,	PUNCT
brj-23187	241	15	article	article	NOUN
brj-23187	241	16	i	i	PROPN
brj-23187	241	17	d	d	PROPN
brj-23187	241	18	2880	2880	NUM
brj-23187	241	19	-	-	SYM
brj-23187	241	20	2891	2891	NUM
brj-23187	241	21	.	.	PUNCT
brj-23187	242	1	doi	doi	NOUN
brj-23187	242	2	:	:	PUNCT
brj-23187	242	3	10.1016	10.1016	NUM
brj-23187	242	4	/	/	SYM
brj-23187	242	5	j.neucom.2017.10.011	j.neucom.2017.10.011	PROPN
brj-23187	242	6	https://doi.org/10.1016/j.neucom.2017.10.011	https://doi.org/10.1016/j.neucom.2017.10.011	PROPN
brj-23187	242	7	peer	peer	NOUN
brj-23187	242	8	-	-	PUNCT
brj-23187	242	9	reviewed	review	VERB
brj-23187	242	10	article	article	NOUN
brj-23187	242	11	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	242	12	fu	fu	PROPN
brj-23187	242	13	et	et	PROPN
brj-23187	242	14	al	al	PROPN
brj-23187	242	15	.	.	PROPN
brj-23187	243	1	(	(	PUNCT
brj-23187	243	2	2024	2024	NUM
brj-23187	243	3	)	)	PUNCT
brj-23187	243	4	.	.	PUNCT
brj-23187	244	1	“	"	PUNCT
brj-23187	244	2	predicting	predict	VERB
brj-23187	244	3	enzymatic	enzymatic	ADJ
brj-23187	244	4	hydrolysis	hydrolysis	NOUN
brj-23187	244	5	,	,	PUNCT
brj-23187	244	6	”	"	PUNCT
brj-23187	244	7	bioresources	bioresource	NOUN
brj-23187	244	8	19(2	19(2	NUM
brj-23187	244	9	)	)	PUNCT
brj-23187	244	10	,	,	PUNCT
brj-23187	244	11	3505	3505	NUM
brj-23187	244	12	-	-	SYM
brj-23187	244	13	3519	3519	NUM
brj-23187	244	14	.	.	PUNCT
brj-23187	245	1	3518	3518	NUM
brj-23187	245	2	du	du	PROPN
brj-23187	245	3	,	,	PUNCT
brj-23187	245	4	e.	e.	PROPN
brj-23187	245	5	(	(	PUNCT
brj-23187	245	6	2022	2022	NUM
brj-23187	245	7	)	)	PUNCT
brj-23187	245	8	.	.	PUNCT
brj-23187	246	1	“	"	PUNCT
brj-23187	246	2	impact	impact	NOUN
brj-23187	246	3	of	of	ADP
brj-23187	246	4	bank	bank	NOUN
brj-23187	246	5	research	research	NOUN
brj-23187	246	6	and	and	CCONJ
brj-23187	246	7	development	development	NOUN
brj-23187	246	8	on	on	ADP
brj-23187	246	9	total	total	ADJ
brj-23187	246	10	factor	factor	NOUN
brj-23187	246	11	productivity	productivity	NOUN
brj-23187	246	12	and	and	CCONJ
brj-23187	246	13	performance	performance	NOUN
brj-23187	246	14	evaluation	evaluation	NOUN
brj-23187	246	15	by	by	ADP
brj-23187	246	16	rbf	rbf	PROPN
brj-23187	246	17	network	network	NOUN
brj-23187	246	18	,	,	PUNCT
brj-23187	246	19	”	"	PUNCT
brj-23187	246	20	the	the	DET
brj-23187	246	21	journal	journal	NOUN
brj-23187	246	22	of	of	ADP
brj-23187	246	23	supercomputing	supercompute	VERB
brj-23187	246	24	78	78	NUM
brj-23187	246	25	,	,	PUNCT
brj-23187	246	26	12070	12070	NUM
brj-23187	246	27	-	-	SYM
brj-23187	246	28	12092	12092	NUM
brj-23187	246	29	.	.	PUNCT
brj-23187	247	1	doi	doi	NOUN
brj-23187	247	2	:	:	PUNCT
brj-23187	247	3	10.1007	10.1007	NUM
brj-23187	247	4	/	/	SYM
brj-23187	247	5	s11227	s11227	VERB
brj-23187	247	6	-	-	PUNCT
brj-23187	247	7	022	022	NUM
brj-23187	247	8	-	-	PUNCT
brj-23187	247	9	04358	04358	NUM
brj-23187	247	10	-	-	PUNCT
brj-23187	247	11	x	x	SYM
brj-23187	247	12	guo	guo	PROPN
brj-23187	247	13	,	,	PUNCT
brj-23187	247	14	j.-y	j.-y	PROPN
brj-23187	247	15	.	.	PROPN
brj-23187	247	16	,	,	PUNCT
brj-23187	247	17	yu	yu	PROPN
brj-23187	247	18	,	,	PUNCT
brj-23187	247	19	h.	h.	PROPN
brj-23187	247	20	,	,	PUNCT
brj-23187	247	21	and	and	CCONJ
brj-23187	247	22	li	li	PROPN
brj-23187	247	23	,	,	PUNCT
brj-23187	247	24	y.	y.	PROPN
brj-23187	247	25	(	(	PUNCT
brj-23187	247	26	2023	2023	NUM
brj-23187	247	27	)	)	PUNCT
brj-23187	247	28	.	.	PUNCT
brj-23187	248	1	“	"	PUNCT
brj-23187	248	2	related	related	ADJ
brj-23187	248	3	and	and	CCONJ
brj-23187	248	4	independent	independent	ADJ
brj-23187	248	5	variable	variable	ADJ
brj-23187	248	6	fault	fault	NOUN
brj-23187	248	7	detection	detection	NOUN
brj-23187	248	8	method	method	NOUN
brj-23187	248	9	based	base	VERB
brj-23187	248	10	on	on	ADP
brj-23187	248	11	kpca	kpca	NOUN
brj-23187	248	12	-	-	PUNCT
brj-23187	248	13	svm	svm	NOUN
brj-23187	248	14	,	,	PUNCT
brj-23187	248	15	”	"	PUNCT
brj-23187	248	16	journal	journal	NOUN
brj-23187	248	17	of	of	ADP
brj-23187	248	18	shenzhen	shenzhen	PROPN
brj-23187	248	19	university	university	PROPN
brj-23187	248	20	science	science	NOUN
brj-23187	248	21	and	and	CCONJ
brj-23187	248	22	engineering	engineering	NOUN
brj-23187	248	23	40(1	40(1	PROPN
brj-23187	248	24	)	)	PUNCT
brj-23187	248	25	,	,	PUNCT
brj-23187	248	26	14	14	NUM
brj-23187	248	27	-	-	SYM
brj-23187	248	28	21	21	NUM
brj-23187	248	29	.	.	PUNCT
brj-23187	249	1	doi	doi	NOUN
brj-23187	249	2	:	:	PUNCT
brj-23187	249	3	10.3724	10.3724	NUM
brj-23187	249	4	/	/	SYM
brj-23187	249	5	sp.j.1249.2023.01014	sp.j.1249.2023.01014	PROPN
brj-23187	249	6	han	han	PROPN
brj-23187	249	7	,	,	PUNCT
brj-23187	249	8	y.-m	y.-m	PROPN
brj-23187	249	9	.	.	PROPN
brj-23187	249	10	,	,	PUNCT
brj-23187	249	11	cao	cao	PROPN
brj-23187	249	12	,	,	PUNCT
brj-23187	249	13	l.	l.	PROPN
brj-23187	249	14	,	,	PUNCT
brj-23187	249	15	geng	geng	PROPN
brj-23187	249	16	,	,	PUNCT
brj-23187	249	17	z.-q	z.-q	PROPN
brj-23187	249	18	.	.	PROPN
brj-23187	249	19	,	,	PUNCT
brj-23187	249	20	ping	ping	PROPN
brj-23187	249	21	,	,	PUNCT
brj-23187	249	22	w.-y	w.-y	NOUN
brj-23187	249	23	.	.	PUNCT
brj-23187	249	24	,	,	PUNCT
brj-23187	249	25	zuo	zuo	PROPN
brj-23187	249	26	,	,	PUNCT
brj-23187	249	27	x.-y	x.-y	NOUN
brj-23187	249	28	.	.	PROPN
brj-23187	249	29	,	,	PUNCT
brj-23187	249	30	fane	fane	NOUN
brj-23187	249	31	,	,	PUNCT
brj-23187	249	32	j.-z	j.-z	PROPN
brj-23187	249	33	.	.	PUNCT
brj-23187	249	34	,	,	PUNCT
brj-23187	249	35	wan	wan	PROPN
brj-23187	249	36	,	,	PUNCT
brj-23187	249	37	j.	j.	PROPN
brj-23187	249	38	,	,	PUNCT
brj-23187	249	39	and	and	CCONJ
brj-23187	249	40	lu	lu	PROPN
brj-23187	249	41	,	,	PUNCT
brj-23187	249	42	g.	g.	PROPN
brj-23187	249	43	(	(	PUNCT
brj-23187	249	44	2022	2022	NUM
brj-23187	249	45	)	)	PUNCT
brj-23187	249	46	.	.	PUNCT
brj-23187	250	1	“	"	PUNCT
brj-23187	250	2	novel	novel	ADJ
brj-23187	250	3	economy	economy	NOUN
brj-23187	250	4	and	and	CCONJ
brj-23187	250	5	carbon	carbon	NOUN
brj-23187	250	6	emissions	emission	NOUN
brj-23187	250	7	prediction	prediction	NOUN
brj-23187	250	8	model	model	NOUN
brj-23187	250	9	of	of	ADP
brj-23187	250	10	different	different	ADJ
brj-23187	250	11	countries	country	NOUN
brj-23187	250	12	or	or	CCONJ
brj-23187	250	13	regions	region	NOUN
brj-23187	250	14	in	in	ADP
brj-23187	250	15	the	the	DET
brj-23187	250	16	world	world	NOUN
brj-23187	250	17	for	for	ADP
brj-23187	250	18	energy	energy	NOUN
brj-23187	250	19	optimization	optimization	NOUN
brj-23187	250	20	using	use	VERB
brj-23187	250	21	improved	improve	VERB
brj-23187	250	22	residual	residual	ADJ
brj-23187	250	23	neural	neural	ADJ
brj-23187	250	24	network	network	NOUN
brj-23187	250	25	,	,	PUNCT
brj-23187	250	26	”	"	PUNCT
brj-23187	250	27	science	science	NOUN
brj-23187	250	28	of	of	ADP
brj-23187	250	29	the	the	DET
brj-23187	250	30	total	total	ADJ
brj-23187	250	31	environment	environment	NOUN
brj-23187	250	32	860	860	NUM
brj-23187	250	33	,	,	PUNCT
brj-23187	250	34	article	article	NOUN
brj-23187	250	35	i	i	PROPN
brj-23187	250	36	d	d	PROPN
brj-23187	250	37	160410	160410	NUM
brj-23187	250	38	.	.	PUNCT
brj-23187	251	1	doi	doi	NOUN
brj-23187	251	2	:	:	PUNCT
brj-23187	251	3	10.1016	10.1016	NUM
brj-23187	251	4	/	/	SYM
brj-23187	251	5	j.scitotenv.2022.160410	j.scitotenv.2022.160410	PROPN
brj-23187	251	6	huang	huang	PROPN
brj-23187	251	7	,	,	PUNCT
brj-23187	251	8	c.-x	c.-x	PROPN
brj-23187	251	9	.	.	PROPN
brj-23187	251	10	,	,	PUNCT
brj-23187	251	11	lin	lin	PROPN
brj-23187	251	12	,	,	PUNCT
brj-23187	251	13	w.-q	w.-q	PROPN
brj-23187	251	14	.	.	PUNCT
brj-23187	251	15	,	,	PUNCT
brj-23187	251	16	lai	lai	PROPN
brj-23187	251	17	,	,	PUNCT
brj-23187	251	18	c.-h	c.-h	PROPN
brj-23187	251	19	.	.	PUNCT
brj-23187	251	20	,	,	PUNCT
brj-23187	251	21	li	li	PROPN
brj-23187	251	22	,	,	PUNCT
brj-23187	251	23	x.	x.	PROPN
brj-23187	251	24	,	,	PUNCT
brj-23187	251	25	jin	jin	NOUN
brj-23187	251	26	,	,	PUNCT
brj-23187	251	27	y.-g	y.-g	PROPN
brj-23187	251	28	.	.	PUNCT
brj-23187	251	29	,	,	PUNCT
brj-23187	251	30	and	and	CCONJ
brj-23187	251	31	yong	yong	PROPN
brj-23187	251	32	,	,	PUNCT
brj-23187	251	33	q.	q.	PROPN
brj-23187	251	34	(	(	PUNCT
brj-23187	251	35	2019	2019	NUM
brj-23187	251	36	)	)	PUNCT
brj-23187	251	37	.	.	PUNCT
brj-23187	252	1	“	"	PUNCT
brj-23187	252	2	coupling	couple	VERB
brj-23187	252	3	the	the	DET
brj-23187	252	4	post	post	ADJ
brj-23187	252	5	-	-	ADJ
brj-23187	252	6	extraction	extraction	NOUN
brj-23187	252	7	process	process	NOUN
brj-23187	252	8	to	to	PART
brj-23187	252	9	remove	remove	VERB
brj-23187	252	10	residual	residual	ADJ
brj-23187	252	11	lignin	lignin	NOUN
brj-23187	252	12	and	and	CCONJ
brj-23187	252	13	alter	alter	VERB
brj-23187	252	14	the	the	DET
brj-23187	252	15	recalcitrant	recalcitrant	ADJ
brj-23187	252	16	structures	structure	NOUN
brj-23187	252	17	for	for	ADP
brj-23187	252	18	improving	improve	VERB
brj-23187	252	19	the	the	DET
brj-23187	252	20	enzymatic	enzymatic	ADJ
brj-23187	252	21	digestibility	digestibility	NOUN
brj-23187	252	22	of	of	ADP
brj-23187	252	23	acid	acid	NOUN
brj-23187	252	24	-	-	PUNCT
brj-23187	252	25	pretreated	pretreate	VERB
brj-23187	252	26	bamboo	bamboo	NOUN
brj-23187	252	27	residues	residue	NOUN
brj-23187	252	28	,	,	PUNCT
brj-23187	252	29	”	"	PUNCT
brj-23187	252	30	bioresource	bioresource	ADJ
brj-23187	252	31	technology	technology	NOUN
brj-23187	252	32	285	285	NUM
brj-23187	252	33	,	,	PUNCT
brj-23187	252	34	article	article	NOUN
brj-23187	252	35	i	i	PROPN
brj-23187	252	36	d	d	PROPN
brj-23187	252	37	12355	12355	NUM
brj-23187	252	38	.	.	PUNCT
brj-23187	253	1	doi	doi	NOUN
brj-23187	253	2	:	:	PUNCT
brj-23187	253	3	10.1016	10.1016	NUM
brj-23187	253	4	/	/	SYM
brj-23187	253	5	j.biortech.2019.121355	j.biortech.2019.121355	PROPN
brj-23187	253	6	ikram	ikram	PROPN
brj-23187	253	7	,	,	PUNCT
brj-23187	253	8	r.	r.	PROPN
brj-23187	253	9	m.	m.	PROPN
brj-23187	253	10	a.	a.	PROPN
brj-23187	253	11	,	,	PUNCT
brj-23187	253	12	dai	dai	PROPN
brj-23187	253	13	,	,	PUNCT
brj-23187	253	14	h.-l	h.-l	PROPN
brj-23187	253	15	.	.	PUNCT
brj-23187	253	16	,	,	PUNCT
brj-23187	253	17	ewees	ewees	PROPN
brj-23187	253	18	,	,	PUNCT
brj-23187	253	19	a.	a.	NOUN
brj-23187	253	20	,	,	PUNCT
brj-23187	253	21	shiri	shiri	PROPN
brj-23187	253	22	,	,	PUNCT
brj-23187	253	23	j.	j.	PROPN
brj-23187	253	24	,	,	PUNCT
brj-23187	253	25	kisi	kisi	PROPN
brj-23187	253	26	,	,	PUNCT
brj-23187	253	27	o.	o.	NOUN
brj-23187	253	28	,	,	PUNCT
brj-23187	253	29	and	and	CCONJ
brj-23187	253	30	zounemat	zounemat	NOUN
brj-23187	253	31	-	-	PUNCT
brj-23187	253	32	kermani	kermani	NOUN
brj-23187	253	33	,	,	PUNCT
brj-23187	253	34	m.	m.	NOUN
brj-23187	253	35	(	(	PUNCT
brj-23187	253	36	2022	2022	NUM
brj-23187	253	37	)	)	PUNCT
brj-23187	253	38	.	.	PUNCT
brj-23187	254	1	“	"	PUNCT
brj-23187	254	2	application	application	NOUN
brj-23187	254	3	of	of	ADP
brj-23187	254	4	improved	improved	ADJ
brj-23187	254	5	version	version	NOUN
brj-23187	254	6	of	of	ADP
brj-23187	254	7	multiverse	multiverse	NOUN
brj-23187	254	8	optimizer	optimizer	NOUN
brj-23187	254	9	algorithm	algorithm	NOUN
brj-23187	254	10	for	for	ADP
brj-23187	254	11	modeling	model	VERB
brj-23187	254	12	solar	solar	ADJ
brj-23187	254	13	radiation	radiation	NOUN
brj-23187	254	14	,	,	PUNCT
brj-23187	254	15	”	"	PUNCT
brj-23187	254	16	energy	energy	NOUN
brj-23187	254	17	reports	report	NOUN
brj-23187	254	18	8	8	NUM
brj-23187	254	19	,	,	PUNCT
brj-23187	254	20	12063	12063	NUM
brj-23187	254	21	-	-	SYM
brj-23187	254	22	12080	12080	NUM
brj-23187	254	23	.	.	PUNCT
brj-23187	255	1	doi	doi	NOUN
brj-23187	255	2	:	:	PUNCT
brj-23187	255	3	10.1016	10.1016	NUM
brj-23187	255	4	/	/	SYM
brj-23187	255	5	j.egyr.2022.09.015	j.egyr.2022.09.015	PROPN
brj-23187	255	6	kuang	kuang	PROPN
brj-23187	255	7	,	,	PUNCT
brj-23187	255	8	f.-j	f.-j	PROPN
brj-23187	255	9	.	.	PROPN
brj-23187	255	10	,	,	PUNCT
brj-23187	255	11	xu	xu	PROPN
brj-23187	255	12	,	,	PUNCT
brj-23187	255	13	w.-h	w.-h	NOUN
brj-23187	255	14	.	.	PUNCT
brj-23187	255	15	,	,	PUNCT
brj-23187	255	16	zhang	zhang	PROPN
brj-23187	255	17	,	,	PUNCT
brj-23187	255	18	s.-y	s.-y	NOUN
brj-23187	255	19	.	.	PUNCT
brj-23187	255	20	,	,	PUNCT
brj-23187	255	21	wang	wang	PROPN
brj-23187	255	22	,	,	PUNCT
brj-23187	255	23	y.-h	y.-h	PROPN
brj-23187	255	24	.	.	PROPN
brj-23187	255	25	,	,	PUNCT
brj-23187	255	26	and	and	CCONJ
brj-23187	255	27	liu	liu	PROPN
brj-23187	255	28	,	,	PUNCT
brj-23187	255	29	k.w	k.w	PROPN
brj-23187	255	30	.	.	PROPN
brj-23187	255	31	(	(	PUNCT
brj-23187	255	32	2012	2012	NUM
brj-23187	255	33	)	)	PUNCT
brj-23187	255	34	.	.	PUNCT
brj-23187	256	1	“	"	PUNCT
brj-23187	256	2	a	a	DET
brj-23187	256	3	novel	novel	ADJ
brj-23187	256	4	approach	approach	NOUN
brj-23187	256	5	of	of	ADP
brj-23187	256	6	kpca	kpca	NOUN
brj-23187	256	7	and	and	CCONJ
brj-23187	256	8	svm	svm	VERB
brj-23187	256	9	for	for	ADP
brj-23187	256	10	intrusion	intrusion	NOUN
brj-23187	256	11	detection	detection	NOUN
brj-23187	256	12	,	,	PUNCT
brj-23187	256	13	”	"	PUNCT
brj-23187	256	14	journal	journal	NOUN
brj-23187	256	15	of	of	ADP
brj-23187	256	16	computational	computational	ADJ
brj-23187	256	17	information	information	NOUN
brj-23187	256	18	systems	system	NOUN
brj-23187	256	19	8(8	8(8	NUM
brj-23187	256	20	)	)	PUNCT
brj-23187	256	21	,	,	PUNCT
brj-23187	256	22	3237	3237	NUM
brj-23187	256	23	-	-	SYM
brj-23187	256	24	3244	3244	NUM
brj-23187	256	25	.	.	PUNCT
brj-23187	257	1	kuang	kuang	PROPN
brj-23187	257	2	,	,	PUNCT
brj-23187	257	3	f.-j	f.-j	PROPN
brj-23187	257	4	.	.	PROPN
brj-23187	257	5	,	,	PUNCT
brj-23187	257	6	xua	xua	PROPN
brj-23187	257	7	,	,	PUNCT
brj-23187	257	8	w.-h	w.-h	NOUN
brj-23187	257	9	.	.	PUNCT
brj-23187	257	10	,	,	PUNCT
brj-23187	257	11	and	and	CCONJ
brj-23187	257	12	zhang	zhang	PROPN
brj-23187	257	13	,	,	PUNCT
brj-23187	257	14	s.-y	s.-y	NOUN
brj-23187	257	15	.	.	PUNCT
brj-23187	258	1	(	(	PUNCT
brj-23187	258	2	2014	2014	NUM
brj-23187	258	3	)	)	PUNCT
brj-23187	258	4	.	.	PUNCT
brj-23187	259	1	“	"	PUNCT
brj-23187	259	2	a	a	DET
brj-23187	259	3	novel	novel	ADJ
brj-23187	259	4	hybrid	hybrid	ADJ
brj-23187	259	5	kpca	kpca	NOUN
brj-23187	259	6	and	and	CCONJ
brj-23187	259	7	svm	svm	VERB
brj-23187	259	8	with	with	ADP
brj-23187	259	9	ga	ga	PROPN
brj-23187	259	10	model	model	NOUN
brj-23187	259	11	for	for	ADP
brj-23187	259	12	intrusion	intrusion	NOUN
brj-23187	259	13	detection	detection	NOUN
brj-23187	259	14	,	,	PUNCT
brj-23187	259	15	”	"	PUNCT
brj-23187	259	16	applied	apply	VERB
brj-23187	259	17	soft	soft	ADJ
brj-23187	259	18	computing	computing	NOUN
brj-23187	259	19	18	18	NUM
brj-23187	259	20	,	,	PUNCT
brj-23187	259	21	178	178	NUM
brj-23187	259	22	-	-	SYM
brj-23187	259	23	184	184	NUM
brj-23187	259	24	.	.	PUNCT
brj-23187	260	1	doi	doi	NOUN
brj-23187	260	2	:	:	PUNCT
brj-23187	260	3	10.1016	10.1016	NUM
brj-23187	260	4	/	/	SYM
brj-23187	260	5	j.asoc.2014.01.028	j.asoc.2014.01.028	PROPN
brj-23187	260	6	kumar	kumar	PROPN
brj-23187	260	7	,	,	PUNCT
brj-23187	260	8	p.	p.	PROPN
brj-23187	260	9	,	,	PUNCT
brj-23187	260	10	kumar	kumar	PROPN
brj-23187	260	11	,	,	PUNCT
brj-23187	260	12	v.	v.	PROPN
brj-23187	260	13	,	,	PUNCT
brj-23187	260	14	adelodun	adelodun	PROPN
brj-23187	260	15	,	,	PUNCT
brj-23187	260	16	b.	b.	PROPN
brj-23187	260	17	,	,	PUNCT
brj-23187	260	18	bedekovic	bedekovic	PROPN
brj-23187	260	19	,	,	PUNCT
brj-23187	260	20	d.	d.	PROPN
brj-23187	260	21	,	,	PUNCT
brj-23187	260	22	kos	kos	PROPN
brj-23187	260	23	,	,	PUNCT
brj-23187	260	24	i.	i.	PROPN
brj-23187	260	25	,	,	PUNCT
brj-23187	260	26	širic	širic	ADJ
brj-23187	260	27	´	´	PROPN
brj-23187	260	28	,	,	PUNCT
brj-23187	260	29	i.	i.	NOUN
brj-23187	260	30	,	,	PUNCT
brj-23187	260	31	alamri	alamri	PROPN
brj-23187	260	32	,	,	PUNCT
brj-23187	260	33	s.	s.	PROPN
brj-23187	260	34	a.	a.	PROPN
brj-23187	260	35	m.	m.	PROPN
brj-23187	260	36	,	,	PUNCT
brj-23187	260	37	alrumman	alrumman	PROPN
brj-23187	260	38	,	,	PUNCT
brj-23187	260	39	s.	s.	PROPN
brj-23187	260	40	a.	a.	PROPN
brj-23187	260	41	,	,	PUNCT
brj-23187	260	42	eid	eid	PROPN
brj-23187	260	43	,	,	PUNCT
brj-23187	260	44	e.	e.	PROPN
brj-23187	260	45	m.	m.	PROPN
brj-23187	260	46	,	,	PUNCT
brj-23187	260	47	fayssal	fayssal	NOUN
brj-23187	260	48	,	,	PUNCT
brj-23187	260	49	s.	s.	PROPN
brj-23187	260	50	a.	a.	PROPN
brj-23187	260	51	,	,	PUNCT
brj-23187	260	52	et	et	PROPN
brj-23187	260	53	al	al	PROPN
brj-23187	260	54	.	.	PROPN
brj-23187	260	55	(	(	PUNCT
brj-23187	260	56	2022	2022	NUM
brj-23187	260	57	)	)	PUNCT
brj-23187	260	58	.	.	PUNCT
brj-23187	261	1	“	"	PUNCT
brj-23187	261	2	sustainable	sustainable	ADJ
brj-23187	261	3	use	use	NOUN
brj-23187	261	4	of	of	ADP
brj-23187	261	5	sewage	sewage	NOUN
brj-23187	261	6	sludge	sludge	NOUN
brj-23187	261	7	as	as	ADP
brj-23187	261	8	a	a	DET
brj-23187	261	9	casing	casing	NOUN
brj-23187	261	10	material	material	NOUN
brj-23187	261	11	for	for	ADP
brj-23187	261	12	button	button	NOUN
brj-23187	261	13	mushroom	mushroom	NOUN
brj-23187	261	14	(	(	PUNCT
brj-23187	261	15	agaricus	agaricus	NOUN
brj-23187	261	16	bisporus	bisporus	NOUN
brj-23187	261	17	)	)	PUNCT
brj-23187	261	18	cultivation	cultivation	NOUN
brj-23187	261	19	:	:	PUNCT
brj-23187	261	20	experimental	experimental	ADJ
brj-23187	261	21	and	and	CCONJ
brj-23187	261	22	prediction	prediction	NOUN
brj-23187	261	23	modeling	model	VERB
brj-23187	261	24	studies	study	NOUN
brj-23187	261	25	for	for	ADP
brj-23187	261	26	uptake	uptake	NOUN
brj-23187	261	27	of	of	ADP
brj-23187	261	28	metal	metal	NOUN
brj-23187	261	29	,	,	PUNCT
brj-23187	261	30	”	"	PUNCT
brj-23187	261	31	journal	journal	NOUN
brj-23187	261	32	of	of	ADP
brj-23187	261	33	fungi	fungi	PROPN
brj-23187	261	34	8(2	8(2	NUM
brj-23187	261	35	)	)	PUNCT
brj-23187	261	36	,	,	PUNCT
brj-23187	261	37	article	article	NOUN
brj-23187	261	38	112	112	NUM
brj-23187	261	39	.	.	PUNCT
brj-23187	262	1	doi	doi	NOUN
brj-23187	262	2	:	:	PUNCT
brj-23187	262	3	10.3390	10.3390	NUM
brj-23187	262	4	/	/	SYM
brj-23187	262	5	jof8020112	jof8020112	PROPN
brj-23187	262	6	liu	liu	PROPN
brj-23187	262	7	,	,	PUNCT
brj-23187	262	8	y.	y.	PROPN
brj-23187	262	9	,	,	PUNCT
brj-23187	262	10	cao	cao	PROPN
brj-23187	262	11	,	,	PUNCT
brj-23187	262	12	y.	y.	PROPN
brj-23187	262	13	,	,	PUNCT
brj-23187	262	14	wang	wang	PROPN
brj-23187	262	15	,	,	PUNCT
brj-23187	262	16	l.	l.	PROPN
brj-23187	262	17	,	,	PUNCT
brj-23187	262	18	chen	chen	PROPN
brj-23187	262	19	,	,	PUNCT
brj-23187	262	20	z.-s	z.-s	PROPN
brj-23187	262	21	.	.	PUNCT
brj-23187	262	22	,	,	PUNCT
brj-23187	262	23	and	and	CCONJ
brj-23187	262	24	qin	qin	INTJ
brj-23187	262	25	,	,	PUNCT
brj-23187	262	26	y.	y.	PROPN
brj-23187	262	27	(	(	PUNCT
brj-23187	262	28	2022	2022	NUM
brj-23187	262	29	)	)	PUNCT
brj-23187	262	30	.	.	PUNCT
brj-23187	263	1	“	"	PUNCT
brj-23187	263	2	prediction	prediction	NOUN
brj-23187	263	3	of	of	ADP
brj-23187	263	4	the	the	DET
brj-23187	263	5	durability	durability	NOUN
brj-23187	263	6	of	of	ADP
brj-23187	263	7	high	high	ADJ
brj-23187	263	8	-	-	PUNCT
brj-23187	263	9	performance	performance	NOUN
brj-23187	263	10	concrete	concrete	NOUN
brj-23187	263	11	using	use	VERB
brj-23187	263	12	an	an	DET
brj-23187	263	13	integrated	integrate	VERB
brj-23187	263	14	rf	rf	NOUN
brj-23187	263	15	-	-	PUNCT
brj-23187	263	16	lssvm	lssvm	ADJ
brj-23187	263	17	model	model	NOUN
brj-23187	263	18	,	,	PUNCT
brj-23187	263	19	”	"	PUNCT
brj-23187	263	20	construction	construction	NOUN
brj-23187	263	21	and	and	CCONJ
brj-23187	263	22	building	building	NOUN
brj-23187	263	23	materials	material	NOUN
brj-23187	263	24	356	356	NUM
brj-23187	263	25	,	,	PUNCT
brj-23187	263	26	article	article	NOUN
brj-23187	263	27	i	i	PROPN
brj-23187	263	28	d	d	PROPN
brj-23187	263	29	129232	129232	NUM
brj-23187	263	30	.	.	PUNCT
brj-23187	264	1	doi	doi	NOUN
brj-23187	264	2	:	:	PUNCT
brj-23187	264	3	10.1016	10.1016	NUM
brj-23187	264	4	/	/	SYM
brj-23187	264	5	j.conbuildmat.2022.129232	j.conbuildmat.2022.129232	PROPN
brj-23187	264	6	nguyen	nguyen	NOUN
brj-23187	264	7	,	,	PUNCT
brj-23187	264	8	l.	l.	PROPN
brj-23187	264	9	t.	t.	PROPN
brj-23187	264	10	,	,	PUNCT
brj-23187	264	11	phan	phan	PROPN
brj-23187	264	12	,	,	PUNCT
brj-23187	264	13	d.	d.	PROPN
brj-23187	264	14	p.	p.	PROPN
brj-23187	264	15	,	,	PUNCT
brj-23187	264	16	sarwar	sarwar	PROPN
brj-23187	264	17	,	,	PUNCT
brj-23187	264	18	a.	a.	NOUN
brj-23187	264	19	,	,	PUNCT
brj-23187	264	20	tran	tran	PROPN
brj-23187	264	21	,	,	PUNCT
brj-23187	264	22	m.	m.	PROPN
brj-23187	264	23	h.	h.	PROPN
brj-23187	264	24	,	,	PUNCT
brj-23187	264	25	lee	lee	PROPN
brj-23187	264	26	,	,	PUNCT
brj-23187	264	27	o.	o.	PROPN
brj-23187	264	28	k.	k.	PROPN
brj-23187	264	29	,	,	PUNCT
brj-23187	264	30	and	and	CCONJ
brj-23187	264	31	lee	lee	PROPN
brj-23187	264	32	,	,	PUNCT
brj-23187	264	33	e.	e.	PROPN
brj-23187	264	34	y.	y.	PROPN
brj-23187	264	35	(	(	PUNCT
brj-23187	264	36	2020	2020	NUM
brj-23187	264	37	)	)	PUNCT
brj-23187	264	38	.	.	PUNCT
brj-23187	265	1	“	"	PUNCT
brj-23187	265	2	valorization	valorization	NOUN
brj-23187	265	3	of	of	ADP
brj-23187	265	4	industrial	industrial	ADJ
brj-23187	265	5	lignin	lignin	NOUN
brj-23187	265	6	to	to	ADP
brj-23187	265	7	value	value	NOUN
brj-23187	265	8	-	-	PUNCT
brj-23187	265	9	added	add	VERB
brj-23187	265	10	chemicals	chemical	NOUN
brj-23187	265	11	by	by	ADP
brj-23187	265	12	chemical	chemical	ADJ
brj-23187	265	13	depolymerization	depolymerization	NOUN
brj-23187	265	14	and	and	CCONJ
brj-23187	265	15	biological	biological	ADJ
brj-23187	265	16	conversion	conversion	NOUN
brj-23187	265	17	,	,	PUNCT
brj-23187	265	18	”	"	PUNCT
brj-23187	265	19	industrial	industrial	ADJ
brj-23187	265	20	crops	crop	NOUN
brj-23187	265	21	&	&	CCONJ
brj-23187	265	22	products	product	NOUN
brj-23187	265	23	161	161	NUM
brj-23187	265	24	,	,	PUNCT
brj-23187	265	25	article	article	NOUN
brj-23187	265	26	i	i	PROPN
brj-23187	265	27	d	d	PROPN
brj-23187	265	28	113219	113219	NUM
brj-23187	265	29	.	.	PUNCT
brj-23187	266	1	doi	doi	NOUN
brj-23187	266	2	:	:	PUNCT
brj-23187	266	3	10.1016	10.1016	NUM
brj-23187	266	4	/	/	SYM
brj-23187	266	5	j.indcrop.2020.113219	j.indcrop.2020.113219	PROPN
brj-23187	266	6	qin	qin	PROPN
brj-23187	266	7	,	,	PUNCT
brj-23187	266	8	s.-j	s.-j	PROPN
brj-23187	266	9	.	.	PUNCT
brj-23187	267	1	(	(	PUNCT
brj-23187	267	2	2012	2012	NUM
brj-23187	267	3	)	)	PUNCT
brj-23187	267	4	.	.	PUNCT
brj-23187	268	1	"	"	PUNCT
brj-23187	268	2	survey	survey	NOUN
brj-23187	268	3	on	on	ADP
brj-23187	268	4	data	data	NOUN
brj-23187	268	5	-	-	PUNCT
brj-23187	268	6	driven	drive	VERB
brj-23187	268	7	industrial	industrial	ADJ
brj-23187	268	8	process	process	NOUN
brj-23187	268	9	monitoring	monitoring	NOUN
brj-23187	268	10	and	and	CCONJ
brj-23187	268	11	diagnosis	diagnosis	NOUN
brj-23187	268	12	,	,	PUNCT
brj-23187	268	13	"	"	PUNCT
brj-23187	268	14	annual	annual	ADJ
brj-23187	268	15	reviews	review	NOUN
brj-23187	268	16	in	in	ADP
brj-23187	268	17	control	control	NOUN
brj-23187	268	18	36(2	36(2	NUM
brj-23187	268	19	)	)	PUNCT
brj-23187	268	20	,	,	PUNCT
brj-23187	268	21	220	220	NUM
brj-23187	268	22	-	-	SYM
brj-23187	268	23	234	234	NUM
brj-23187	268	24	.	.	PUNCT
brj-23187	269	1	doi	doi	NOUN
brj-23187	269	2	:	:	PUNCT
brj-23187	269	3	10.1016	10.1016	NUM
brj-23187	269	4	/	/	SYM
brj-23187	269	5	j.arcontrol.2012.09.004	j.arcontrol.2012.09.004	PROPN
brj-23187	269	6	saravanan	saravanan	PROPN
brj-23187	269	7	,	,	PUNCT
brj-23187	269	8	a.	a.	PROPN
brj-23187	269	9	,	,	PUNCT
brj-23187	269	10	senthil	senthil	PROPN
brj-23187	269	11	kumar	kumar	PROPN
brj-23187	269	12	,	,	PUNCT
brj-23187	269	13	p.	p.	PROPN
brj-23187	269	14	,	,	PUNCT
brj-23187	269	15	jeevanantham	jeevanantham	PROPN
brj-23187	269	16	s.	s.	PROPN
brj-23187	269	17	,	,	PUNCT
brj-23187	269	18	karishma	karishma	PROPN
brj-23187	269	19	,	,	PUNCT
brj-23187	269	20	s.	s.	PROPN
brj-23187	269	21	,	,	PUNCT
brj-23187	269	22	and	and	CCONJ
brj-23187	269	23	vo	vo	NOUN
brj-23187	269	24	,	,	PUNCT
brj-23187	269	25	d.	d.	PROPN
brj-23187	269	26	n.	n.	PROPN
brj-23187	269	27	(	(	PUNCT
brj-23187	269	28	2021	2021	NUM
brj-23187	269	29	)	)	PUNCT
brj-23187	269	30	.	.	PUNCT
brj-23187	270	1	“	"	PUNCT
brj-23187	270	2	recent	recent	ADJ
brj-23187	270	3	advances	advance	NOUN
brj-23187	270	4	and	and	CCONJ
brj-23187	270	5	sustainable	sustainable	ADJ
brj-23187	270	6	development	development	NOUN
brj-23187	270	7	of	of	ADP
brj-23187	270	8	biofuels	biofuel	NOUN
brj-23187	270	9	production	production	NOUN
brj-23187	270	10	from	from	ADP
brj-23187	270	11	lignocellulosic	lignocellulosic	ADJ
brj-23187	270	12	biomass	biomass	NOUN
brj-23187	270	13	,	,	PUNCT
brj-23187	270	14	”	"	PUNCT
brj-23187	270	15	bioresource	bioresource	ADP
brj-23187	270	16	technol	technol	NOUN
brj-23187	270	17	.	.	PUNCT
brj-23187	270	18	344	344	NUM
brj-23187	270	19	,	,	PUNCT
brj-23187	270	20	article	article	NOUN
brj-23187	270	21	i	i	PROPN
brj-23187	270	22	d	d	PROPN
brj-23187	270	23	126203	126203	NUM
brj-23187	270	24	.	.	PUNCT
brj-23187	271	1	doi	doi	NOUN
brj-23187	271	2	:	:	PUNCT
brj-23187	271	3	10.1016	10.1016	NUM
brj-23187	271	4	/	/	SYM
brj-23187	271	5	j.biortech.2021.126203	j.biortech.2021.126203	PROPN
brj-23187	271	6	tian	tian	PROPN
brj-23187	271	7	,	,	PUNCT
brj-23187	271	8	x.	x.	PROPN
brj-23187	271	9	,	,	PUNCT
brj-23187	271	10	cheng	cheng	PROPN
brj-23187	271	11	,	,	PUNCT
brj-23187	271	12	h.-y	h.-y	NOUN
brj-23187	271	13	.	.	PUNCT
brj-23187	271	14	,	,	PUNCT
brj-23187	271	15	zhang	zhang	PROPN
brj-23187	271	16	,	,	PUNCT
brj-23187	271	17	h.-b	h.-b	PROPN
brj-23187	271	18	.	.	PROPN
brj-23187	271	19	,	,	PUNCT
brj-23187	271	20	ren	ren	PROPN
brj-23187	271	21	,	,	PUNCT
brj-23187	271	22	y.-s	y.-	NOUN
brj-23187	271	23	.	.	PUNCT
brj-23187	271	24	,	,	PUNCT
brj-23187	271	25	wang	wang	PROPN
brj-23187	271	26	,	,	PUNCT
brj-23187	271	27	y.-m	y.-m	PROPN
brj-23187	271	28	.	.	PROPN
brj-23187	271	29	,	,	PUNCT
brj-23187	271	30	luo	luo	PROPN
brj-23187	271	31	,	,	PUNCT
brj-23187	271	32	y.	y.	NOUN
brj-23187	271	33	,	,	PUNCT
brj-23187	271	34	and	and	CCONJ
brj-23187	271	35	liu	liu	PROPN
brj-23187	271	36	,	,	PUNCT
brj-23187	271	37	n.	n.	PROPN
brj-23187	271	38	(	(	PUNCT
brj-23187	271	39	2023	2023	NUM
brj-23187	271	40	)	)	PUNCT
brj-23187	271	41	.	.	PUNCT
brj-23187	272	1	“	"	PUNCT
brj-23187	272	2	mechanism	mechanism	NOUN
brj-23187	272	3	of	of	ADP
brj-23187	272	4	composite	composite	ADJ
brj-23187	272	5	ferrate	ferrate	NOUN
brj-23187	272	6	solution	solution	NOUN
brj-23187	272	7	pretreatment	pretreatment	NOUN
brj-23187	272	8	for	for	ADP
brj-23187	272	9	promoting	promote	VERB
brj-23187	272	10	https://doi.org/10.1016/j.conbuildmat.2022.129232	https://doi.org/10.1016/j.conbuildmat.2022.129232	PROPN
brj-23187	272	11	peer	peer	NOUN
brj-23187	272	12	-	-	PUNCT
brj-23187	272	13	reviewed	review	VERB
brj-23187	272	14	article	article	NOUN
brj-23187	272	15	bioresources.cnr.ncsu.edu	bioresources.cnr.ncsu.edu	VERB
brj-23187	272	16	fu	fu	PROPN
brj-23187	272	17	et	et	PROPN
brj-23187	272	18	al	al	PROPN
brj-23187	272	19	.	.	PROPN
brj-23187	273	1	(	(	PUNCT
brj-23187	273	2	2024	2024	NUM
brj-23187	273	3	)	)	PUNCT
brj-23187	273	4	.	.	PUNCT
brj-23187	274	1	“	"	PUNCT
brj-23187	274	2	predicting	predict	VERB
brj-23187	274	3	enzymatic	enzymatic	ADJ
brj-23187	274	4	hydrolysis	hydrolysis	NOUN
brj-23187	274	5	,	,	PUNCT
brj-23187	274	6	”	"	PUNCT
brj-23187	274	7	bioresources	bioresource	NOUN
brj-23187	274	8	19(2	19(2	NUM
brj-23187	274	9	)	)	PUNCT
brj-23187	274	10	,	,	PUNCT
brj-23187	274	11	3505	3505	NUM
brj-23187	274	12	-	-	SYM
brj-23187	274	13	3519	3519	NUM
brj-23187	274	14	.	.	PUNCT
brj-23187	275	1	3519	3519	NUM
brj-23187	275	2	enzymatic	enzymatic	ADJ
brj-23187	275	3	hydrolysis	hydrolysis	NOUN
brj-23187	275	4	efficiency	efficiency	NOUN
brj-23187	275	5	of	of	ADP
brj-23187	275	6	corn	corn	NOUN
brj-23187	275	7	stover	stover	NOUN
brj-23187	275	8	,	,	PUNCT
brj-23187	275	9	”	"	PUNCT
brj-23187	275	10	acta	acta	PROPN
brj-23187	275	11	scientiae	scientiae	VERB
brj-23187	275	12	circumstantiae	circumstantiae	NOUN
brj-23187	275	13	43(4	43(4	NOUN
brj-23187	275	14	)	)	PUNCT
brj-23187	275	15	,	,	PUNCT
brj-23187	275	16	417	417	NUM
brj-23187	275	17	-	-	SYM
brj-23187	275	18	426	426	NUM
brj-23187	275	19	.	.	PUNCT
brj-23187	276	1	doi	doi	NOUN
brj-23187	276	2	:	:	PUNCT
brj-23187	276	3	10.13671	10.13671	NUM
brj-23187	276	4	/	/	SYM
brj-23187	276	5	j.hjkxxb.2022.0351	j.hjkxxb.2022.0351	PROPN
brj-23187	276	6	tian	tian	PROPN
brj-23187	276	7	,	,	PUNCT
brj-23187	276	8	z.-d	z.-d	PROPN
brj-23187	276	9	.	.	PUNCT
brj-23187	277	1	(	(	PUNCT
brj-23187	277	2	2020	2020	NUM
brj-23187	277	3	)	)	PUNCT
brj-23187	277	4	.	.	PUNCT
brj-23187	278	1	“	"	PUNCT
brj-23187	278	2	short	short	ADJ
brj-23187	278	3	-	-	PUNCT
brj-23187	278	4	term	term	NOUN
brj-23187	278	5	wind	wind	NOUN
brj-23187	278	6	speed	speed	NOUN
brj-23187	278	7	prediction	prediction	NOUN
brj-23187	278	8	based	base	VERB
brj-23187	278	9	on	on	ADP
brj-23187	278	10	lmd	lmd	PROPN
brj-23187	278	11	and	and	CCONJ
brj-23187	278	12	improved	improve	VERB
brj-23187	278	13	fa	fa	PROPN
brj-23187	278	14	optimized	optimize	VERB
brj-23187	278	15	combined	combine	VERB
brj-23187	278	16	kernel	kernel	PROPN
brj-23187	278	17	function	function	PROPN
brj-23187	278	18	lssvm	lssvm	PROPN
brj-23187	278	19	,	,	PUNCT
brj-23187	278	20	”	"	PUNCT
brj-23187	278	21	engineering	engineering	NOUN
brj-23187	278	22	applications	application	NOUN
brj-23187	278	23	of	of	ADP
brj-23187	278	24	artificial	artificial	ADJ
brj-23187	278	25	intelligence	intelligence	NOUN
brj-23187	278	26	91	91	NUM
brj-23187	278	27	,	,	PUNCT
brj-23187	278	28	article	article	NOUN
brj-23187	278	29	i	i	PROPN
brj-23187	278	30	d	d	PROPN
brj-23187	278	31	103573	103573	NUM
brj-23187	278	32	.	.	PUNCT
brj-23187	279	1	doi	doi	NOUN
brj-23187	279	2	:	:	PUNCT
brj-23187	279	3	10.1016	10.1016	NUM
brj-23187	279	4	/	/	SYM
brj-23187	279	5	j.engappai.2020.103573	j.engappai.2020.103573	PROPN
brj-23187	279	6	usmani	usmani	PROPN
brj-23187	279	7	,	,	PUNCT
brj-23187	279	8	z.	z.	PROPN
brj-23187	279	9	,	,	PUNCT
brj-23187	279	10	sharma	sharma	PROPN
brj-23187	279	11	,	,	PUNCT
brj-23187	279	12	m.	m.	NOUN
brj-23187	279	13	,	,	PUNCT
brj-23187	279	14	awasthi	awasthi	PROPN
brj-23187	279	15	,	,	PUNCT
brj-23187	279	16	a.	a.	PROPN
brj-23187	279	17	k.	k.	PROPN
brj-23187	279	18	,	,	PUNCT
brj-23187	279	19	sivakumar	sivakumar	PROPN
brj-23187	279	20	,	,	PUNCT
brj-23187	279	21	n.	n.	NOUN
brj-23187	279	22	,	,	PUNCT
brj-23187	279	23	lukk	lukk	ADJ
brj-23187	279	24	,	,	PUNCT
brj-23187	279	25	t.	t.	PROPN
brj-23187	279	26	,	,	PUNCT
brj-23187	279	27	pecoraro	pecoraro	NOUN
brj-23187	279	28	,	,	PUNCT
brj-23187	279	29	l.	l.	PROPN
brj-23187	279	30	,	,	PUNCT
brj-23187	279	31	thakur	thakur	PROPN
brj-23187	279	32	,	,	PUNCT
brj-23187	279	33	v.	v.	PROPN
brj-23187	279	34	k.	k.	PROPN
brj-23187	279	35	,	,	PUNCT
brj-23187	279	36	roberts	roberts	PROPN
brj-23187	279	37	,	,	PUNCT
brj-23187	279	38	d.	d.	PROPN
brj-23187	279	39	,	,	PUNCT
brj-23187	279	40	newbold	newbold	PROPN
brj-23187	279	41	,	,	PUNCT
brj-23187	279	42	j.	j.	PROPN
brj-23187	279	43	,	,	PUNCT
brj-23187	279	44	and	and	CCONJ
brj-23187	279	45	gupta	gupta	PROPN
brj-23187	279	46	,	,	PUNCT
brj-23187	279	47	v.	v.	PROPN
brj-23187	279	48	k.	k.	PROPN
brj-23187	279	49	(	(	PUNCT
brj-23187	279	50	2021	2021	NUM
brj-23187	279	51	)	)	PUNCT
brj-23187	279	52	.	.	PUNCT
brj-23187	280	1	“	"	PUNCT
brj-23187	280	2	bioprocessing	bioprocesse	VERB
brj-23187	280	3	of	of	ADP
brj-23187	280	4	waste	waste	NOUN
brj-23187	280	5	biomass	biomass	NOUN
brj-23187	280	6	for	for	ADP
brj-23187	280	7	sustainable	sustainable	ADJ
brj-23187	280	8	product	product	NOUN
brj-23187	280	9	development	development	NOUN
brj-23187	280	10	and	and	CCONJ
brj-23187	280	11	minimizing	minimize	VERB
brj-23187	280	12	environmental	environmental	ADJ
brj-23187	280	13	impact	impact	NOUN
brj-23187	280	14	,	,	PUNCT
brj-23187	280	15	”	"	PUNCT
brj-23187	280	16	bioresource	bioresource	ADP
brj-23187	280	17	technol	technol	NOUN
brj-23187	280	18	.	.	PROPN
brj-23187	280	19	322	322	NUM
brj-23187	280	20	,	,	PUNCT
brj-23187	280	21	article	article	NOUN
brj-23187	280	22	i	i	PROPN
brj-23187	280	23	d	d	PROPN
brj-23187	280	24	124548	124548	NUM
brj-23187	280	25	.	.	PUNCT
brj-23187	281	1	doi	doi	NOUN
brj-23187	281	2	:	:	PUNCT
brj-23187	281	3	10.1016	10.1016	NUM
brj-23187	281	4	/	/	SYM
brj-23187	281	5	j.biortech.2020.124548	j.biortech.2020.124548	PROPN
brj-23187	281	6	wang	wang	PROPN
brj-23187	281	7	,	,	PUNCT
brj-23187	281	8	j.-z	j.-z	PROPN
brj-23187	281	9	.	.	PUNCT
brj-23187	281	10	,	,	PUNCT
brj-23187	281	11	and	and	CCONJ
brj-23187	281	12	hu	hu	PROPN
brj-23187	281	13	,	,	PUNCT
brj-23187	281	14	j.-m	j.-m	PROPN
brj-23187	281	15	.	.	PUNCT
brj-23187	282	1	(	(	PUNCT
brj-23187	282	2	2015	2015	NUM
brj-23187	282	3	)	)	PUNCT
brj-23187	282	4	.	.	PUNCT
brj-23187	283	1	“	"	PUNCT
brj-23187	283	2	a	a	DET
brj-23187	283	3	robust	robust	ADJ
brj-23187	283	4	combination	combination	NOUN
brj-23187	283	5	approach	approach	NOUN
brj-23187	283	6	for	for	ADP
brj-23187	283	7	short	short	ADJ
brj-23187	283	8	-	-	PUNCT
brj-23187	283	9	term	term	NOUN
brj-23187	283	10	wind	wind	NOUN
brj-23187	283	11	speed	speed	NOUN
brj-23187	283	12	forecasting	forecasting	NOUN
brj-23187	283	13	and	and	CCONJ
brj-23187	283	14	analysis	analysis	NOUN
brj-23187	283	15	–	–	PUNCT
brj-23187	283	16	combination	combination	NOUN
brj-23187	283	17	of	of	ADP
brj-23187	283	18	the	the	DET
brj-23187	283	19	arima	arima	PROPN
brj-23187	283	20	(	(	PUNCT
brj-23187	283	21	autoregressive	autoregressive	ADJ
brj-23187	283	22	integrated	integrated	ADJ
brj-23187	283	23	moving	move	VERB
brj-23187	283	24	average	average	NOUN
brj-23187	283	25	)	)	PUNCT
brj-23187	283	26	,	,	PUNCT
brj-23187	283	27	elm	elm	NOUN
brj-23187	283	28	(	(	PUNCT
brj-23187	283	29	extreme	extreme	ADJ
brj-23187	283	30	learning	learning	NOUN
brj-23187	283	31	machine	machine	NOUN
brj-23187	283	32	)	)	PUNCT
brj-23187	283	33	,	,	PUNCT
brj-23187	283	34	svm	svm	PROPN
brj-23187	283	35	(	(	PUNCT
brj-23187	283	36	support	support	NOUN
brj-23187	283	37	vector	vector	NOUN
brj-23187	283	38	machine	machine	NOUN
brj-23187	283	39	)	)	PUNCT
brj-23187	283	40	and	and	CCONJ
brj-23187	283	41	lssvm	lssvm	INTJ
brj-23187	283	42	(	(	PUNCT
brj-23187	283	43	least	least	ADJ
brj-23187	283	44	square	square	ADJ
brj-23187	283	45	svm	svm	NOUN
brj-23187	283	46	)	)	PUNCT
brj-23187	283	47	forecasts	forecast	NOUN
brj-23187	283	48	using	use	VERB
brj-23187	283	49	a	a	DET
brj-23187	283	50	gpr	gpr	PROPN
brj-23187	283	51	(	(	PUNCT
brj-23187	283	52	gaussian	gaussian	ADJ
brj-23187	283	53	process	process	NOUN
brj-23187	283	54	regression	regression	NOUN
brj-23187	283	55	)	)	PUNCT
brj-23187	283	56	model	model	NOUN
brj-23187	283	57	,	,	PUNCT
brj-23187	283	58	”	"	PUNCT
brj-23187	283	59	energy	energy	NOUN
brj-23187	283	60	93	93	NUM
brj-23187	283	61	,	,	PUNCT
brj-23187	283	62	41	41	NUM
brj-23187	283	63	-	-	SYM
brj-23187	283	64	56	56	NUM
brj-23187	283	65	.	.	PUNCT
brj-23187	284	1	doi	doi	NOUN
brj-23187	284	2	:	:	PUNCT
brj-23187	284	3	10.1016	10.1016	NUM
brj-23187	284	4	/	/	SYM
brj-23187	284	5	j.energy.2015.08.045	j.energy.2015.08.045	NUM
brj-23187	284	6	wang	wang	PROPN
brj-23187	284	7	,	,	PUNCT
brj-23187	284	8	y.-k	y.-k	PROPN
brj-23187	284	9	.	.	PUNCT
brj-23187	284	10	,	,	PUNCT
brj-23187	284	11	tang	tang	PROPN
brj-23187	284	12	,	,	PUNCT
brj-23187	284	13	h.-m	h.-m	NOUN
brj-23187	284	14	.	.	PUNCT
brj-23187	284	15	,	,	PUNCT
brj-23187	284	16	huang	huang	PROPN
brj-23187	284	17	,	,	PUNCT
brj-23187	284	18	j.-s	j.-s	PROPN
brj-23187	284	19	.	.	PUNCT
brj-23187	284	20	,	,	PUNCT
brj-23187	284	21	wen	wen	PROPN
brj-23187	284	22	,	,	PUNCT
brj-23187	284	23	t.	t.	PROPN
brj-23187	284	24	,	,	PUNCT
brj-23187	284	25	ma	ma	PROPN
brj-23187	284	26	,	,	PUNCT
brj-23187	284	27	j.-w	j.-w	PROPN
brj-23187	284	28	.	.	PROPN
brj-23187	284	29	,	,	PUNCT
brj-23187	284	30	and	and	CCONJ
brj-23187	284	31	zhang	zhang	PROPN
brj-23187	284	32	,	,	PUNCT
brj-23187	284	33	j.-r	j.-r	PROPN
brj-23187	284	34	.	.	PUNCT
brj-23187	285	1	(	(	PUNCT
brj-23187	285	2	2022	2022	NUM
brj-23187	285	3	)	)	PUNCT
brj-23187	285	4	.	.	PUNCT
brj-23187	286	1	“	"	PUNCT
brj-23187	286	2	a	a	DET
brj-23187	286	3	comparative	comparative	ADJ
brj-23187	286	4	study	study	NOUN
brj-23187	286	5	of	of	ADP
brj-23187	286	6	different	different	ADJ
brj-23187	286	7	machine	machine	NOUN
brj-23187	286	8	learning	learning	NOUN
brj-23187	286	9	methods	method	NOUN
brj-23187	286	10	for	for	ADP
brj-23187	286	11	reservoir	reservoir	PROPN
brj-23187	286	12	landslide	landslide	NOUN
brj-23187	286	13	displacement	displacement	NOUN
brj-23187	286	14	prediction	prediction	NOUN
brj-23187	286	15	,	,	PUNCT
brj-23187	286	16	”	"	PUNCT
brj-23187	286	17	engineering	engineering	NOUN
brj-23187	286	18	geology	geology	NOUN
brj-23187	286	19	298	298	NUM
brj-23187	286	20	,	,	PUNCT
brj-23187	286	21	article	article	NOUN
brj-23187	286	22	i	i	PROPN
brj-23187	286	23	d	d	PROPN
brj-23187	286	24	106544	106544	NUM
brj-23187	286	25	.	.	PUNCT
brj-23187	287	1	doi	doi	NOUN
brj-23187	287	2	:	:	PUNCT
brj-23187	287	3	10.1016	10.1016	NUM
brj-23187	287	4	/	/	SYM
brj-23187	287	5	j.enggeo.2022.106544	j.enggeo.2022.106544	PROPN
brj-23187	287	6	xiong	xiong	PROPN
brj-23187	287	7	,	,	PUNCT
brj-23187	287	8	j.	j.	PROPN
brj-23187	287	9	,	,	PUNCT
brj-23187	287	10	wang	wang	PROPN
brj-23187	287	11	,	,	PUNCT
brj-23187	287	12	t.	t.	PROPN
brj-23187	287	13	,	,	PUNCT
brj-23187	287	14	and	and	CCONJ
brj-23187	287	15	li	li	PROPN
brj-23187	287	16	,	,	PUNCT
brj-23187	287	17	r.	r.	PROPN
brj-23187	287	18	(	(	PUNCT
brj-23187	287	19	2018	2018	NUM
brj-23187	287	20	)	)	PUNCT
brj-23187	287	21	.	.	PUNCT
brj-23187	288	1	“	"	PUNCT
brj-23187	288	2	research	research	NOUN
brj-23187	288	3	on	on	ADP
brj-23187	288	4	a	a	DET
brj-23187	288	5	hybrid	hybrid	ADJ
brj-23187	288	6	lssvm	lssvm	NOUN
brj-23187	288	7	intelligent	intelligent	ADJ
brj-23187	288	8	algorithm	algorithm	NOUN
brj-23187	288	9	in	in	ADP
brj-23187	288	10	short	short	ADJ
brj-23187	288	11	term	term	NOUN
brj-23187	288	12	load	load	NOUN
brj-23187	288	13	forecasting	forecasting	NOUN
brj-23187	288	14	,	,	PUNCT
brj-23187	288	15	”	"	PUNCT
brj-23187	288	16	cluster	cluster	NOUN
brj-23187	288	17	computing	compute	VERB
brj-23187	288	18	22(suppl4	22(suppl4	NOUN
brj-23187	288	19	)	)	PUNCT
brj-23187	288	20	,	,	PUNCT
brj-23187	288	21	8271	8271	NUM
brj-23187	288	22	-	-	SYM
brj-23187	288	23	8278	8278	NUM
brj-23187	288	24	.	.	PUNCT
brj-23187	289	1	doi	doi	NOUN
brj-23187	289	2	:	:	PUNCT
brj-23187	289	3	10.1007	10.1007	NUM
brj-23187	289	4	/	/	SYM
brj-23187	289	5	s10586	s10586	PROPN
brj-23187	289	6	-	-	PUNCT
brj-23187	289	7	018	018	NUM
brj-23187	289	8	-	-	PUNCT
brj-23187	289	9	1740	1740	NUM
brj-23187	289	10	-	-	PUNCT
brj-23187	289	11	z	z	PROPN
brj-23187	289	12	yang	yang	PROPN
brj-23187	289	13	,	,	PUNCT
brj-23187	289	14	j.	j.	PROPN
brj-23187	289	15	,	,	PUNCT
brj-23187	289	16	yang	yang	PROPN
brj-23187	289	17	,	,	PUNCT
brj-23187	289	18	x.-q	x.-q	PROPN
brj-23187	289	19	.	.	PROPN
brj-23187	289	20	,	,	PUNCT
brj-23187	289	21	and	and	CCONJ
brj-23187	289	22	han	han	PROPN
brj-23187	289	23	,	,	PUNCT
brj-23187	289	24	l.-j	l.-j	PROPN
brj-23187	289	25	.	.	PUNCT
brj-23187	290	1	(	(	PUNCT
brj-23187	290	2	2022	2022	NUM
brj-23187	290	3	)	)	PUNCT
brj-23187	290	4	.	.	PUNCT
brj-23187	291	1	“	"	PUNCT
brj-23187	291	2	effects	effect	NOUN
brj-23187	291	3	of	of	ADP
brj-23187	291	4	different	different	ADJ
brj-23187	291	5	naoh	naoh	NOUN
brj-23187	291	6	/	/	SYM
brj-23187	291	7	ball	ball	NOUN
brj-23187	291	8	milling	mill	VERB
brj-23187	291	9	combined	combine	VERB
brj-23187	291	10	pretreatments	pretreatment	NOUN
brj-23187	291	11	on	on	ADP
brj-23187	291	12	the	the	DET
brj-23187	291	13	enzymatic	enzymatic	ADJ
brj-23187	291	14	hydrolysis	hydrolysis	NOUN
brj-23187	291	15	of	of	ADP
brj-23187	291	16	corn	corn	NOUN
brj-23187	291	17	stalks	stalk	NOUN
brj-23187	291	18	,	,	PUNCT
brj-23187	291	19	”	"	PUNCT
brj-23187	291	20	transactions	transaction	NOUN
brj-23187	291	21	of	of	ADP
brj-23187	291	22	the	the	DET
brj-23187	291	23	chinese	chinese	ADJ
brj-23187	291	24	society	society	NOUN
brj-23187	291	25	of	of	ADP
brj-23187	291	26	agricultural	agricultural	ADJ
brj-23187	291	27	engineering	engineering	NOUN
brj-23187	291	28	(	(	PUNCT
brj-23187	291	29	transactions	transaction	NOUN
brj-23187	291	30	of	of	ADP
brj-23187	291	31	the	the	DET
brj-23187	291	32	csae	csae	NOUN
brj-23187	291	33	)	)	PUNCT
brj-23187	291	34	38(15	38(15	NUM
brj-23187	291	35	)	)	PUNCT
brj-23187	291	36	,	,	PUNCT
brj-23187	291	37	226	226	NUM
brj-23187	291	38	-	-	SYM
brj-23187	291	39	233	233	NUM
brj-23187	291	40	.	.	PUNCT
brj-23187	292	1	doi	doi	NOUN
brj-23187	292	2	:	:	PUNCT
brj-23187	292	3	10.11975	10.11975	NUM
brj-23187	292	4	/	/	SYM
brj-23187	292	5	j.issn.1002	j.issn.1002	ADV
brj-23187	292	6	-	-	PUNCT
brj-23187	292	7	6819.2022.15.024	6819.2022.15.024	NOUN
brj-23187	292	8	yuan	yuan	NOUN
brj-23187	292	9	,	,	PUNCT
brj-23187	292	10	x.-h	x.-h	PROPN
brj-23187	292	11	.	.	PROPN
brj-23187	292	12	,	,	PUNCT
brj-23187	292	13	chen	chen	PROPN
brj-23187	292	14	,	,	PUNCT
brj-23187	292	15	c.	c.	PROPN
brj-23187	292	16	,	,	PUNCT
brj-23187	292	17	yuan	yuan	PROPN
brj-23187	292	18	,	,	PUNCT
brj-23187	292	19	y.-b	y.-b	PROPN
brj-23187	292	20	.	.	PROPN
brj-23187	292	21	,	,	PUNCT
brj-23187	292	22	huang	huang	PROPN
brj-23187	292	23	,	,	PUNCT
brj-23187	292	24	y.-h	y.-h	PROPN
brj-23187	292	25	.	.	PROPN
brj-23187	292	26	,	,	PUNCT
brj-23187	292	27	and	and	CCONJ
brj-23187	292	28	tan	tan	PROPN
brj-23187	292	29	,	,	PUNCT
brj-23187	292	30	q.-x	q.-x	PROPN
brj-23187	292	31	.	.	PUNCT
brj-23187	293	1	(	(	PUNCT
brj-23187	293	2	2015	2015	NUM
brj-23187	293	3	)	)	PUNCT
brj-23187	293	4	.	.	PUNCT
brj-23187	294	1	“	"	PUNCT
brj-23187	294	2	short	short	ADJ
brj-23187	294	3	-	-	PUNCT
brj-23187	294	4	term	term	NOUN
brj-23187	294	5	wind	wind	NOUN
brj-23187	294	6	power	power	NOUN
brj-23187	294	7	prediction	prediction	NOUN
brj-23187	294	8	based	base	VERB
brj-23187	294	9	on	on	ADP
brj-23187	294	10	lssvm	lssvm	PROPN
brj-23187	294	11	–	–	PUNCT
brj-23187	294	12	gsa	gsa	PROPN
brj-23187	294	13	model	model	NOUN
brj-23187	294	14	,	,	PUNCT
brj-23187	294	15	”	"	PUNCT
brj-23187	294	16	energy	energy	NOUN
brj-23187	294	17	conversion	conversion	NOUN
brj-23187	294	18	and	and	CCONJ
brj-23187	294	19	management	management	NOUN
brj-23187	294	20	101	101	NUM
brj-23187	294	21	,	,	PUNCT
brj-23187	294	22	393	393	NUM
brj-23187	294	23	-	-	SYM
brj-23187	294	24	401	401	NUM
brj-23187	294	25	.	.	PUNCT
brj-23187	295	1	doi	doi	NOUN
brj-23187	295	2	:	:	PUNCT
brj-23187	295	3	10.1016	10.1016	NUM
brj-23187	295	4	/	/	SYM
brj-23187	295	5	j.enconman.2015.05.065	j.enconman.2015.05.065	PROPN
brj-23187	295	6	zhao	zhao	PROPN
brj-23187	295	7	,	,	PUNCT
brj-23187	295	8	l.	l.	PROPN
brj-23187	295	9	,	,	PUNCT
brj-23187	295	10	sun	sun	PROPN
brj-23187	295	11	,	,	PUNCT
brj-23187	295	12	z.	z.	PROPN
brj-23187	295	13	f.	f.	PROPN
brj-23187	295	14	,	,	PUNCT
brj-23187	295	15	zhang	zhang	PROPN
brj-23187	295	16	,	,	PUNCT
brj-23187	295	17	c.	c.	PROPN
brj-23187	295	18	c.	c.	PROPN
brj-23187	295	19	,	,	PUNCT
brj-23187	295	20	nan	nan	PROPN
brj-23187	295	21	,	,	PUNCT
brj-23187	295	22	j.	j.	PROPN
brj-23187	295	23	,	,	PUNCT
brj-23187	295	24	ren	ren	PROPN
brj-23187	295	25	,	,	PUNCT
brj-23187	295	26	n.	n.	PROPN
brj-23187	295	27	q.	q.	PROPN
brj-23187	295	28	,	,	PUNCT
brj-23187	295	29	lee	lee	PROPN
brj-23187	295	30	,	,	PUNCT
brj-23187	295	31	d.	d.	PROPN
brj-23187	295	32	j.	j.	PROPN
brj-23187	295	33	,	,	PUNCT
brj-23187	295	34	and	and	CCONJ
brj-23187	295	35	chen	chen	PROPN
brj-23187	295	36	,	,	PUNCT
brj-23187	295	37	c.	c.	PROPN
brj-23187	295	38	(	(	PUNCT
brj-23187	295	39	2021	2021	NUM
brj-23187	295	40	)	)	PUNCT
brj-23187	295	41	.	.	PUNCT
brj-23187	296	1	“	"	PUNCT
brj-23187	296	2	advances	advance	NOUN
brj-23187	296	3	in	in	ADP
brj-23187	296	4	pretreatment	pretreatment	NOUN
brj-23187	296	5	of	of	ADP
brj-23187	296	6	lignocellulosic	lignocellulosic	ADJ
brj-23187	296	7	biomass	biomass	NOUN
brj-23187	296	8	for	for	ADP
brj-23187	296	9	bioenergy	bioenergy	NOUN
brj-23187	296	10	production	production	NOUN
brj-23187	296	11	:	:	PUNCT
brj-23187	296	12	challenges	challenge	NOUN
brj-23187	296	13	and	and	CCONJ
brj-23187	296	14	perspectives	perspective	NOUN
brj-23187	296	15	,	,	PUNCT
brj-23187	296	16	”	"	PUNCT
brj-23187	296	17	bioresource	bioresource	ADP
brj-23187	296	18	technol	technol	NOUN
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brj-23187	296	20	343	343	NUM
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brj-23187	296	22	article	article	NOUN
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brj-23187	297	2	:	:	PUNCT
brj-23187	297	3	10.1016	10.1016	NUM
brj-23187	297	4	/	/	SYM
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brj-23187	297	6	zhu	zhu	PROPN
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brj-23187	297	8	j.-b	j.-b	PROPN
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brj-23187	297	10	,	,	PUNCT
brj-23187	297	11	song	song	NOUN
brj-23187	297	12	,	,	PUNCT
brj-23187	297	13	w.-l	w.-l	PROPN
brj-23187	297	14	.	.	PUNCT
brj-23187	297	15	,	,	PUNCT
brj-23187	297	16	chen	chen	PROPN
brj-23187	297	17	,	,	PUNCT
brj-23187	297	18	x.	x.	NOUN
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brj-23187	297	20	and	and	CCONJ
brj-23187	297	21	sun	sun	NOUN
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brj-23187	297	23	s.-n	s.-n	PROPN
brj-23187	297	24	.	.	PUNCT
brj-23187	298	1	(	(	PUNCT
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brj-23187	298	3	)	)	PUNCT
brj-23187	298	4	.	.	PUNCT
brj-23187	299	1	“	"	PUNCT
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brj-23187	299	3	process	process	NOUN
brj-23187	299	4	to	to	PART
brj-23187	299	5	produce	produce	VERB
brj-23187	299	6	biohydrogen	biohydrogen	NOUN
brj-23187	299	7	from	from	ADP
brj-23187	299	8	wheat	wheat	NOUN
brj-23187	299	9	straw	straw	NOUN
brj-23187	299	10	by	by	ADP
brj-23187	299	11	enzymatic	enzymatic	ADJ
brj-23187	299	12	saccharification	saccharification	NOUN
brj-23187	299	13	and	and	CCONJ
brj-23187	299	14	dark	dark	ADJ
brj-23187	299	15	fermentation	fermentation	NOUN
brj-23187	299	16	,	,	PUNCT
brj-23187	299	17	”	"	PUNCT
brj-23187	299	18	science	science	NOUN
brj-23187	299	19	direct	direct	ADJ
brj-23187	299	20	48	48	NUM
brj-23187	299	21	,	,	PUNCT
brj-23187	299	22	11153	11153	NUM
brj-23187	299	23	-	-	SYM
brj-23187	299	24	11161	11161	NUM
brj-23187	299	25	.	.	PUNCT
brj-23187	300	1	doi	doi	NOUN
brj-23187	300	2	:	:	PUNCT
brj-23187	300	3	10.1016	10.1016	NUM
brj-23187	300	4	/	/	SYM
brj-23187	300	5	j.ijhydene.2022.05.056	j.ijhydene.2022.05.056	PROPN
brj-23187	300	6	article	article	NOUN
brj-23187	300	7	submitted	submit	VERB
brj-23187	300	8	:	:	PUNCT
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brj-23187	300	10	7	7	NUM
brj-23187	300	11	,	,	PUNCT
brj-23187	300	12	2023	2023	NUM
brj-23187	300	13	;	;	PUNCT
brj-23187	300	14	peer	peer	NOUN
brj-23187	300	15	review	review	NOUN
brj-23187	300	16	completed	complete	VERB
brj-23187	300	17	:	:	PUNCT
brj-23187	300	18	march	march	PROPN
brj-23187	300	19	22	22	NUM
brj-23187	300	20	,	,	PUNCT
brj-23187	300	21	2024	2024	NUM
brj-23187	300	22	;	;	PUNCT
brj-23187	300	23	revised	revise	VERB
brj-23187	300	24	version	version	NOUN
brj-23187	300	25	received	receive	VERB
brj-23187	300	26	and	and	CCONJ
brj-23187	300	27	accepted	accept	VERB
brj-23187	300	28	:	:	PUNCT
brj-23187	300	29	april	april	PROPN
brj-23187	300	30	6	6	NUM
brj-23187	300	31	,	,	PUNCT
brj-23187	300	32	2024	2024	NUM
brj-23187	300	33	;	;	PUNCT
brj-23187	300	34	published	publish	VERB
brj-23187	300	35	:	:	PUNCT
brj-23187	300	36	april	april	PROPN
brj-23187	300	37	17	17	NUM
brj-23187	300	38	,	,	PUNCT
brj-23187	300	39	2024	2024	NUM
brj-23187	300	40	.	.	PUNCT
brj-23187	301	1	doi	doi	NOUN
brj-23187	301	2	:	:	PUNCT
brj-23187	301	3	10.15376	10.15376	NUM
brj-23187	301	4	/	/	SYM
brj-23187	301	5	biores.19.2.3505	biores.19.2.3505	PROPN
brj-23187	301	6	-	-	PUNCT
brj-23187	301	7	3519	3519	NUM