Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

No. of ParentsGenotyped	No. of Siblings per Family

2	3	4	5	6	Total

0	3	2	0	0	0	5

1	32	22	9	1	1	65

2	16	29	17	2	1	65

Total	51	53	26	3	2	135


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Mortality law	Function form for $\mu_x$	Parametercount	AIC

Gompertz	$e^{\alpha+\beta x}$	2	27,318.5

Makeham-Beard	$\frac{e^\epsilon~+~e^{\alpha+\beta x}}{1~+~e^{\alpha+\rho+\beta x}}$	4	27,276.3

Hermite I	Equation (4) with $m_0~=~m_1~=~0$	2	27,279.4

Hermite II	Equation (4) with $m_1$ = 0	3	27,280.9

Hermite III	Equation (4) with $m_0$ = 0	3	27,280.2

Hermite IV	Equation (4)	4	27,275.4


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	Drinking at night (DV）

	b	SE

Negative Interpersonal Interactions

Intercept	2.59**	.098

Implicitself-esteem	.051	.039

Explicitself-esteem	.020	.062

Positive interpersonal interactions	.015	.019

Negative interpersonal interactions	.019	.033

Implicit self-esteem × negative interpersonal	-.044*	.020

Explicit self-esteem × negative interpersonal	.004	.031


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Table 1 - Clinical parameters.

Parameter	Insulinglargine	Insulin detemir

Once dailyinjection	Twice dailyinjection

Initial mean bodyweight (kg)	87.4	87.4	87.4

Final weight (kg)*	91.3	89.7	91.1

Initial doses (IU)	12	12	12

Final doses (IU/kg)	0.44	0.52	1

Average dose (IU)	26.09	29.32	51.55

Note. Estimated and adapted from Rosenstock et al. [22].* This indicator was calculated adding to the initial mean bodyweight the mean change registered at the end of the trial for eachinsulin scheme.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Component	Proportion(%）	Number ofinterview

Brick	Mortar	Concrete	Roofing material	Steel	Wood	Other	Total

Brick-concrete structure	Mean	56.5	10.5	15	6	4	5	3	100	16

SD	19.29	6.22	6.02	3.63	2.52	3.39	2.06

Frame structure	Mean	24.5	9.5	50.5	4.5	6.5	1.5	3	100	12

SD	13.56	5.91	21.07	1.81	5.04	1.33	1.85


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Model	Sum of squares	Mean square	$Corrected~R^2$	Standard error

Regression	Residual	Regression	Residual	A	B	C	D

$\text{I}~\left(\delta_{\gamma}\right)$	72468.7	0.227	18117.2	0.227	0.989	4.99	21.84	95.03	2.20

 $\Pi~\left(\delta_{\mathrm{β}}\right)$	86010.2	0.003	21502.6	0.003	1.00	0.97	6.33	4.56	0.14


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Primer	Sequences (5' to 3')	G+C content $(\%)$ 	Number of fragments	Size range of fragments (bp)

Pangio piperata	P. filinaris	P. piperata	P. filinaris

OPA-03	AGT CAG CCA C	60	3-4	9-14	300-1500	250-1700

OPA-09	GGG TAA CGC C	70	7	6-7	400-1700	350-1700

OPA-11	CAA TCA CCG T	50	3-4	3	500-780	500-680

OPA-13	CAG CAC CCA C	70	8-9	2-5	280-900	480-1200

OPA-18	CAA ACG TCG G	60	6-10	9-10	250-1500	380-2000


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Strain	Origin	 Maturity(age-class)	Longevity(age-class)	Source

 1 Assinica	Assinica Lake, Broadback River system, Que.	2-4	7	Webster and Flick 1981

 2 Temiscamie	Temiscamie River, tributary to Lake Albanel, Que.	1-3	5-6	Webster and Flick 1981

 3 Horn	Horn Lake, SW Adirondacks, N.Y.	3	4	Keller 1979

 4 Domestic (Cortland or New York)	Domestic strains, N.Y. state hatchery system	0-1	2	Webster and Flick 1981

 5 Assinica $\times$ Domestic (F1)	First generation hybrid	1-2	3-4	File data

 6 Temiscamie $\times$ Domestic (F1)	First generation hybrid	1-2	3-4	File data

 7 Assinica $\times$ Domestic (F2)	Second generation hybrid	1-2	3-4	File data

 8 Temiscamie $\times$ Domestic (F2)	Second generation hybrid	1-2	3-4	File data

 9 Assinica $\times$ Domestic (challenged)	First generation hybrid, acid challenged Domestic	1-2	3-4	File data

10 Temiscamie $\times$ Domestic (challenged)	First generation hybrid, acid challenged Domestic	1-2	3-4	File data

11 Temiscamie $\times$ Domestic (acclimated)	First generation hybrid, acid acclimated	1-2	3-4	File data

12 Little Tupper	Little Tupper Lake, N Adirondacks, N.Y.	2-3	5	Keller 1979

13 Little Tupper (acclimated)	Little Tupper Lake, acid acclimated	2-3	5	Keller 1979


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Device type	TrainingNo. of benigninstances	Optimization	Testing

	No. of benigninstances	No. of maliciousinstances 	No. of benigninstances	No. ofmaliciousinstances

Baby monitor	53,379	53,379	307,812	53,379	615,625

Doorbell	25,029	25,029	428,383	25,029	856,767

Security camera	69,148	69,148	1,050,750	69,148	2,101,502

Thermostat	4371	4370	274,254	4370	548,509

Webcam	15,607	15,605	107,690	15,605	215,382


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

A. R$_{\mathrm{PC}}$ Single-Value Examples

BMT	Example	R$_{\mathrm{PC}}$	P$_{\mathrm{C}}$

F-Type	Check glucose level threetimes a day	3	Actualfrequency (ex. 2)

D-Type	Exercise for 30 min	30 (min)	Actual exerciseduration (ex.25 min)

C-Type	Join patient care portal	1	Joined (1)

M-Type	Drink 2 L of water a day	2 (L)	Actual amountof waterconsumed (ex.1.5 L)

T-Type	Take medication atnoon Tolerance value: 30 min	1 (no tolerancevalue) 30(with tolerancevalue)	Whether actualbehaviorhappens (1) ornot (0) - (notolerance value)Tolerance value– actual timepassed (withtolerance value)

B.R$_{\mathrm{PC}}$ Combined-Value Examples

CBMT	Example		R$_{\mathrm{PC}}$

FT-Type	Take medication three times aday after having a mealTolerance value:30 min		3,30

FM-Type	Drink 200 ml water ten timesa day		10,200

DT-Type	Walk for 30 min at 7 A.M.		30,1


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Matrix	Individual Release	Dual Release

Un-crosslinked	Crosslinked	Un-crosslinked	Crosslinked

Eosin	Curcumin	Eosin	Curcumin	Eosin	Curcumin	Eosin	Curcumin

Alginate	100	100	56	86	100	100	92	90

$MaterBi^®$	18	74	n/a	n/a	40	70	n/a	n/a

50/50	98	93	72	43	86	67	73	34

30/70	72	49	60	23	92	40	86	22


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

一般外墙抹灰材料的颜色和色感	普通水泥砂浆的配色和掺料

材 料	颜 色	质 感	颜 色	加入颜料的名称、用量

1 : 1: 6 水泥砂浆喷毛	灰色	毛	浅灰	加老粉 $10 \% \sim 20 \%$

 1 : 2 普通水泥抹光 	深灰色	光	中黄	铬酸钡或氧化铁黄 5%~15%

普通水泥浆拉毛	深灰色	粗毛	土红	二氧化铁 $7 \% \sim 21 \%$

白水泥砂浆抹光	白色	光	青色	群青 7%~21%

水刷石	各种颜色	粗糙	灰绿	氧化铬绿 5%~15%

纸筋石灰抹面	白色	光	淡褐	二氧化锰或氧化铁红 2%~16%

清水墙	砖色	横线条	深褐	氧化铁红加少量炭黑 5%~10%

			灰黑	炭黑 5%~15%


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

车 刀 类 型	 工件材料	加工性质	磨钝标准 VB / mm

高速钢	硬质合金

 外圆车刀、端面车刀、镗孔刀	碳钢、合金钢	粗车	1.5~2.0	1.0~1.4

精车	1.0	0.4~0.6

灰铸铁、可锻铸铁	粗车	2.0~3.0	0.8~1.0

半精车	1.5~2.0	0.6~0.8

耐热钢、不锈钢	粗、精车	1.0	1.0

钛合金	粗、半精车		0.4~0.5

淬火钢	精车		0.8~1.0


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	JudgeA	Reliabilityof A	JudgeB	Reliabilityof B	JudgeC	Reliabilityof C	Majorityvote

a	1	$ r(A,\mathbf{a}) $	0	$ r(B,\mathbf{a}) $	1	r(C, a)

b	0	$ r(A,\mathbf{b}) $	1	r(B, b)	1	r(C, b)

$ a \land b$	0		0		1


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

% w/w of binderper tablet	Tablet ingredients

Binder (mg)	Paracetamol (mg) model drug	Lactose (mg) diluents	Talc (mg) lubricant	Tablet weight (mg)

1.0	3.0	250	44.0	3.0	300

1.5	4.5	250	42.5	3.0	300

2.0	6.0	250	41.0	3.0	300

2.5	7.5	250	39.5	3.0	300

3.0	9.0	250	38.0	3.0	300


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Number ofOAs	pH ofsolution	Dosage of$Fe_3O_4/AC$	Initial concentrationof Cu(II)

1	1	1	1

2	1	2	2

3	1	3	3

4	2	1	2

5	2	2	3

6	2	3	1

7	3	1	3

8	3	2	1

9	3	3	2


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Component	Type	Density $(\times10^3\ \mathrm{kg/m^3})$	Elastic $(\times10^{5}$MPa)	Yield strength $(\times10^{5}$MPa)

Conventional cable dome

Ridge cable	GALFAN, 1670 MPa	7.85	1.60	1670

Hoop cable and diagonal cable	GALFAN, 1670 MPa	7.85	1.60	1670

Strut and inner rigid ring	Q345B	7.85	2.06	310

Suspen-dome

Single-layer reticulated shell	Q345B	7.85	2.06	310

Hoop cable and diagonal cable	GALFAN, 1670 MPa	7.85	1.60	1670

Strut and inner rigid ring	Q345B	7.85	2.06	310

Geiger-type RBCD

Ridge beam	Q345B	7.85	2.06	310

Hoop cable and diagonal cable	GALFAN, 1670 MPa	7.85	1.60	1670

Strut and inner rigid ring	Q345B	7.85	2.06	310


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Country	Consumption Function	Long Run MPC

Ours	Singh-Drost

1. Canada	Davis	0.948	0.930

2. Finland	Modified Davis/DEF	0.896/0.895	0.896

3. Guatemala	Modified Davis/DEF	0.966/0.967	0.966

4. Honduras	Davis/DEF	0.941/0.949	0.944

5. India	Davis/Modified Davis/DEF	0.915/0.933/0·928	0.933

6. Japan	DEF	0.802	0.813

7. Philippines	Davis	0.941	0.914

8. Sweden	DEF	0.901	0.893

9. U.K.	Davis/DEF	0.989/0.932	0.944

10. U.S.A.	Davis	0.939	0.936


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	Derivationcohort N = 468patients, 646records	Validationcohort N = 193patients, 215records

Demographic characteristics

 Age (mean, std)	71.9 (5.36)	71.0 (5.11)

 Male (%)	169 (36.1)	67 (34.7)

Race (N, %）

Caucasian	419 (89.5)	173 (89.6)

African American	39 (8.3)	15 (7.8)

Asian or IndianSubcontinent	6 (1.3)	2 (1.0)

Other	4 (0.9)	3 (1.6)

Ethnicity

Hispanic (N，%）	14 (3.0)	5 (2.6)

 BSA m2 (mean, std),	1.91 (0.3)	1.90 (0.3)

Clinical characteristics（N, %）

Smoking	22 (4.7)	4 (2.1)

Diabetes	77 (16.5) 	25 (13.0)

Liver disease	4 (0.9)	4 (2.1)

 Baseline INR (mean, std)	1.01 (0.06)	1.01 (0.05)

Target INR (N, %)

 Target 1.8	286 (61.1)	126 (65.3)

 Target 2.5	182 (38.9)	67 (34.7)

Primary indication (N, %）

Hip replacement	126 (26.9)	52 (26.9)

Knee replacement	342 (73.1)	141 (73.1)


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Nomenclature

$C_n$	is theconcentration of the considered particle classin the flotation cell (g/L)

$C_nf$	is the concentration of particle class n in the froth(g/L)

$C_0f$	is the concentration of particle class n at thepulp/froth interface (g/L)

$c_{\text{pulp}}$	is the pulp slurry concentration (g/L)

$dM_f /dt$	is the particle downward flow from the froth in thepulp due to drainage (g/min)

ERIC	residual equivalent flexo ink in the pulp (ppm)

FRT	is the froth retention time (s)

h	is the froth thickness (cm)

$J_g$	is the gas superficial velocity (cm/s)

$J_f$	is the water superficial velocity in the froth (cm/s)

$k_n$	is the flotation rate constant of particle class n(1/min)

$K_n$	is the experimental flotation coefficient of particleclass n (1/m)

$L_d$	is the water drainage rateconstant(1/s)

$Q_d$	is the water drainage flow ($m^3/h$)

$Q_g$	is the water upward flow in the froth ($m^3 /h$)

$\ Q_{f}^{0} $	is the water upward flow in the froth in the absenceof drainage ($m^3 /h$)

$Q_g$	is the gas flow ($m^3 /h$)

$Q_{i n}$	is the water flow at the inlet of the flotation unit($m^3/h$)

$Q_{out}$	is the water flow at the outlet of the flotation unit($m^3/h$)

$r_{flexo}$	is the average diameter of the reference flexo inkparticles (0.5 μm)

$r_{ink}$	is the average diameter of ink particle (μm)

S	is the cross-sectional area of the flotation column($m^2$)

t	is the flotation time (min)

V	is the flotation cell capacity ($m^3$)

Greek letters

$\alpha$ 	correction coefficient used in Eq. (7)

$\delta $	is theparticle drainage coefficient

$\varepsilon $	is the water volume fraction in the froth

$\varepsilon _0$	is the water volume fraction at the froth/pulp slurryinterface

$\phi $	is the particle entrainment coefficient


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Fish groups	Fish name	Market$share^a$（%）	$\mathrm{EPA}\&\text{DHA}^{\mathrm{b}}$(mg/g）

Tuna	Yellowfin tuna	33.8	0.75

Bluefin tuna	3.4	1.47-46

Albacore tuna	19.2	1.87

Southern bluefin	1.9	0.09-40

Bigeye tuna	35.0	2.3

Other tuna	6.7	11.6

Seabream and Flat fish	Red seabream	46.2	9.1-18.7

Porgy	3.8	4.4

Black seabream	2.3	6.7

Flounder	40.0	1.64-11.8

Flatfish	7.6	4.1-6.7


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Source of uncertainty	σ	$dσ / dt$	$dσ / d\phi$

CLAS acceptance

- inhomogeneities	6% 	6%	6%

- resolutions	2%	2%	-

- $σ_{gen }(Q^{2}, x_{\mathrm{B}}, t)$	5%	5%	-

- $~\mathcal{W}_{{gen }}(\cos θ_{N},φ_{N},\phi )$	8%	8%	-

- radiative corrections	4%	-	2%

- binning	5%	5%	-

- ηMC	4%	2-7%	2-20%

Electron detection

- ηCC	1.5%	-	-

- ηEC	2%	-	-

Background subtraction	7-11%	-	-

Point to point	16-18%	13-14%	7-21%

Normalization	3%	9-12%	14-16%


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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Toxic substance	Concentration (mM)	Pluronic (0.01%,w/v)	Surviving cells

Ethanol	330	Yes	+

330	No	+

490	Yes	0

490	No	0

2-Propanol	130	Yes	+

130	No	+

250	Yes	0

250	No	0

2-Butanol	70	Yes	+

70	No	+

110	Yes	0

110	No	0

Radicicol	0.2 μM	Yes	+

0.2 μM	No	+

2 μM	Yes	0

2 μM	No	0


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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Model	No. of fittedparameters	HPLC data	SPEC data

df	WSS	 Modelcomparison	 F	df	WSS	 Modelcomparison	F

Ⅰ	4	29	11.33			31	7.60

Ⅱ	5	28	2.72	Ⅱ vs. Ⅰ	88.6*	30	0.86	Ⅱ vs. Ⅰ	235.1*

Ⅲ	7	26	1.45	Ⅲ vs. Ⅱ	11.4*

Ⅳ	6	27	2.72	Ⅲ vs. Ⅳ	22.8*

Ⅴ	6	27	2.82	Ⅲ vs. Ⅴ	24.6*


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Water samples	$COD^{standard~method}$(A)	$COD^{CL~method}$(B)	R.D.$(\%)^a$

Saponin wastewater	3178	3070	-3.40

Dyeing wastewater 1	350.6	341.6	-2.57

Dyeing wastewater 2	447.8	450.6	0.63

Garbage leakage liquid	446.4	416.6	-6.67

Organic wastewater	196.5	206.7	5.19

East Lake water	28.7	25.2	-12.2


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Hydraulic unit	1	2	3

Location in EGr bog	Bottom	Middle	Top

Calibrated horizontal hydraulic conductivity (cm $s^{-1}$)	$10^{-4·5}$	$10^{-5·6}$	1

Calibrated vertical hydraulic conductivity (cm $s^{-1}$)	$10^{-2·2}$	$10^{-6}$	10

Calibrated anisotropy ratio ($K_h/K_v$)	$10^{-3·3}$	2·3	0·1

Measured horizontal hydraulic conductivity (cm $s^{-1}$)	$10^{-3·5}$	$10^{-5·6}$	Not measured

Measured vertical hydraulic conductivity (cm $s^{-1}$)	$10^{-3·2}$	$10^{-4}$	$10^{-2}$

Measured anisotropy ratio ($K_h/K_v$)	0·5	0·02	Not applicable

Degree of decomposition (Von post scale)	H3 - H4	H8	H1 - H4


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

cyclopeptide (code)	amino acid $sequence^{a}$	molecular formula	protonated ion mass $(m/z)^{b}$

Seg-A	cyclo-(Gly-Val-Pro-Val-Trp-Ala)	$\mathrm{C_{31}H_{43}N_{7}O_{6}}$	$610.32^{20}$

cyclolinopeptide A (1)	cyclo-(Ile-Leu-Val-Pro-Pro-Phe-Phe-Leu-Ile)	$C_{57}H_{85}N_{9}o_{9}$	$1040.65^{1}$

cyclolinopeptide B (2)	cyclo-(Met-Leu-Ile-Pro-Pro-Phe-Phe-Val-Ile)	$\mathrm{C_{56}H_{83}N_{9}O_{9}S}$	$1058.61^{4}$

cyclolinopeptide C (3)	cyclo-(Mso-Leu-Ile-Pro-Pro-Phe-Phe-Val-Ile)	$\mathrm{C_{56}H_{83}N_{9}O_{10}S}$	$1074.56^{4}$

cyclolinopeptide D (4)	cyclo-(Mso-Leu-Leu-Pro-Phe-Phe-Trp-Ile)	$C_{57}H_{77}N_{9}O{9}S$	$1064.54^{4}$

cyclolinopeptide E (5)	cyclo-(Mso-Leu-Val-Phe-Pro-Leu-Phe-Ile)	$C_{51}H_{76}N_{8}O_{9}S$	$977.52^{4}$

cyclolinopeptide F (6)	cyclo-(Mso-Leu-Mso-Pro-Phe-Phe-Trp-Val)	$C_{55}H_{73}N_{9}O_{10}S_{2}$	$1084.47^{5}$

cyclolinopeptide G (7)	cyclo-(Mso-Leu-Mso-Pro-Phe-Phe-Trp-Ile)	$C_{56}H_{75}N_{9}O_{10}S_{2}$	$1098.50^{5}$

cyclolinopeptide H (8)	cyclo-(Mso-Leu-Met-Pro-Phe-Phe-Trp-Ile)	$C_{56}H_{75}N_{9}O_{9}S_{2}$	$1082.38^{5}$

cyclolinopeptide I (9)	cyclo-(Met-Leu-Mso-Pro-Phe-Phe-Trp-Val)	$C_{55}H_{73}N_{9}O_{9}S_{2}$	$1068.35^{5}$


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

指 示 剂	变色范围 pH	配 制 方 法

 甲基橙-二甲基赛安路 FF 混合指示剂 ( 也称遮蔽指示剂 )	红 3.0~4.4 黄	 称取甲基橙 1.0g，用 500mL 水完全溶解。另称 1.8g 蓝色染料二甲基赛安路 FF , 用 500mL 酒精完全溶解 ，然后将两种指示剂混合均匀。取 2 滴指示剂用于酸碱滴定 ，检验是否有明显的颜色变化。如终点呈蓝灰色 , 可在指示剂中滴加甲基橙少许 ( 0.1% ) ;如终点呈灰绿色稍带红 , 可滴加少许蓝色染料。调至有敏锐的终点 ( 即从碱性变到酸性由绿色变为浅灰或无色 ) 后 , 贮存于棕色瓶中

甲 基红	红 4.2~6.2 黄	 0.10g 溶于 18.60mL $0.02mol\cdot L^{-1}~NaOH$ 中,用水稀释至 250mL

溴百里酚蓝 ( 溴麝香草酚蓝 ）	黄 6.0~7.6 蓝	 0.10g 溶于 8.0mL $0.02mol\cdot L^{-1}~NaOH$ 中,用水稀释至 250mL

中性红	红 6.8~8.0 黄	0.10g 溶于 70mL 乙醇中，用水稀释至 100mL

 百里酚蓝 ( 麝香草酚蓝 )(第二次变色)	黄 8.0~9.6 蓝	 0.10g 溶于 10.75mL $0.02mol\cdot L^{-1}~NaOH$ 中,用水稀释至250mL;0.10g 溶于 100mL 20\%乙醇中

酚酞	无色 7.4~10.0 红	1.0g 溶于 60mL 乙醇中，用水稀释至 100mL

邻甲酚酞	无色 8.2~10.4 红	0.10g 溶于 250mL 乙醇

靛蓝二磺酸钠( 靛红)	蓝 11.6~14.0 黄	0.25g 溶于 100mL 50%乙醇

溴酚蓝	黄 3.0~4.6 蓝	0.1g 指示剂溶于 100mL 20%乙醇

刚果红	蓝紫 3.0~5.2 红	0.1% 水溶液

溴甲酚绿	黄 3.8~5.4 蓝	0.1g 指示剂溶于 100mL 20%乙醇

溴酚红	黄 5.0~6.8 红	0.1g 或 0.04g指示剂溶于 100mL 20%乙醇

酚红	黄 6.8~8.0 红	0.1g 指示剂溶于 100mL 20%乙醇

中性红	红 6.8~8.0 亮黄	0.1g 指示剂溶于 100mL 60%乙醇

百里酚酞	无色 9.4~10.6 蓝	0.1g 指示剂溶于 100mL 90%乙醇


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	Level of Agreement between Codes	Figures	RelevantSections

Gas surface density (cylin-drically binned)	averaged fractional deviation for 2 < r < 10 kpe = 32.2% (0.121 dex) (see footnote 70)	Figure 5	Section 6.1

Gas surface density (verticallybinned)	averaged fractional deviation for z< 0.6 kpc = 30.4% (0.115 dex)	Figure 7	Section 6.1

Gas average vertical height	averaged fractional deviation for 2 < r< 10 kpc = 19.1% (0.076 dex)	Figure 9	Section 6.1

Gas rotation velocity	averaged fractional deviation for 2 < r< 10 kpc = 2.8% (0.012 dex)	Figure 11	Section 6.2

Gas velocity dispersion	averaged fractional deviation for 2 < r < 10 kpc = 17.8% (0.071 dex)	Figure 13	Section 6.2

Gas density probabilitydistribution	averaged fractional deviation in $10^{-25}<\rho<10^{-22}\:{g\:cm}^{-3}=28.6\%\:(0.109\:\mathrm{dex})$, up to morethan an order of magnitude difference at $\rho>10^{-22}\:\mathrm{g}\:\mathrm{cm}^{-3}$	Figure 19	Section 6.3

Newly formed stellar surfacedensity	averaged fractional deviation for 2 < r < 10 kpc = 53.9% (0.187 dex)	Figure 22	Section 6.4

Newly formed stellar clumpmass function	all data points lie within a factor of ~3 from the mean at each mass	Figure 23	Section 6.4

Newly formed stellar rotationvelocity	averaged fractional deviation for 2 < r < 10 kpc = 2.5% (0.011 dex)	Figure 24	Section 6.5

Newly formed stellar velocitydispersion	averaged fractional deviation for 2 < r <10 kpc = 11.2% (0.046 dex)	Figure 25	Section 6.5

Galaxy-wide star formation rate	averaged fractional deviation for 50 < t< 500 Myr = 32.8% (0.123 dex)	Figure 26	Section 6.6

KS relation (azimuthallyaveraged)	all data points lie within a factor of ~3 from the mean at each $\begin{matrix}\sum_{gas}\end{matrix}$	Figure 28	Section 6.6

KS relation (patch-averaged)	all data points lie within a factor of ~3 from the mean at each $\begin{matrix}\sum_{gas}\end{matrix}$	Figure 31	Section 6.6


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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Plantmaterial	Elemental composition	ADF	ADSOM

Carbon	Nitrogen

Reed	48.55	2.13	51.6	37.0

Japanese cedar	51.91	1.01	93.9	5.9

Moso bamboo	50.41	0.88	79.3	19.7

L. eduilis	49.96	0.86	84.9	13.8


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Table 2 - Values of $C_1$ and n for the various exposureconditions and concrete mixes

Exposurecondition	Concrete mix	$C_1$[% wt.of concrete]	n

Spray zone	C1 	0.24 	0.47

C2	0.20	0.51

C3	0.22	0.48

Tidal zone	C1	0.38	0.37

Atmosphericzone	C1	0.12 	0.54

C2	0.09	0.69

C3	0.10	0.59

Dockyard 20	C1 	0.21 	0.47

C2	0.14	0.54

C3	0.12	0.59

Dockyard 21	C3	0.31	0.33


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realincidents	detectedincidents	%detection	false alarmnumberper camera	% offalsealarm

242	240	99 %	1	0 %


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

FOCUS STEP1Scenario	Day afteroverallmaximum	PEC$_{SW}$(ug/L）	$ \mathrm{PEC}_{\mathrm{SED}}(\mu \mathrm{g} / \mathrm{kg}) $

Actual	TWA	Actual	TWA

Pome fruit$(2 \times 288 \mathrm{~g}$as/ha)	RH-2651

0 h	43.7		44.8

7 d		42.7		44.1

21 d		42.4		44.3

RH-2703


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	Formula

Materials	$T_1$	$T_2$	$T_3$	$T_4$

Cement (Portland),gr	400	410	420	430

Sand, 0-2 mm	846	584	700	670

Aggregate,2-4mm	522	520	512	310

Aggregate,4-8mm	432	686	598	890

Water,ml	180	180	180	180

Additives,ml	4	4	4	4

Initial activity $\mathrm{A}_o(\mathrm{kBq})$${}^{137}Cs$	Per sample60,0


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
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Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	FPKM values (standard deviation)

JGIproteinID	RWS24hrs	RWS+Bacteria 24hrs	RWS+Bacteria 72hrs	Pfam/Interprodomain	Best Blastp hit [taxon] (sequence identity)

1210207	0	1.75(0.95)	0.28 (0.05)	ND	Hypothetical protein CONLIGDRAFT_716048[Coniochaeta ligniaria NRRL 30616] (79%)

1278719	0	3.62(1.25)	0.67 (0.33)	ND	Hypothetical protein CONLIGDRAFT_440819[Coniochaeta ligniaria NRRL 30616] (44%)

1286908	 0.22(0.06)	34.10(8.26)	1.15 (0.37)	ND	Galactose oxidase protein [Rutstroemia sp. NJR-2017aWRK4] (43%)

302642	 0.77(0.18)	53.63(7.40)	117 (4.44)	Domain of unknownfunction (DUF3328)	tat pathway signal sequence [Coniochaeta ligniaria NRRL30616] (68%)

501728	 2.65(1.17)	540.24(65.85)	 2065.39(180.59)	ND	Hypothetical protein CH63R_10743 [Colletotrichumhigginsianum IMI 349063] (57%)

$977649^a$	 4.05(1.74)	715.78(107.07)	2366.56(190.62)	Multicopper oxidase	Bilirubin oxidase [Colletotrichum higginsianum IMI349063] (73%)

1292083* 	 0.17(0.05)	74.30(32.32)	 920.94(210.37)	Multicopper oxidase	Multicopper oxidase $[\text { Meliniomyces bicolor E}]$(75\%)

1084612	 3.82(0.95)	316.75(145.34)	 4236.81(1263.20)	ND	Hypothetical protein CONLIGDRAFT_68186 [Coniochaetaligniaria NRRL 30616] (64%)

390783	 2.93(0.95)	285.23(122.35)	 2551.26(795.94)	ND	NM

1046446	0	1.39(0.31)	1.24 (0.35)	Glycoside hydrolasesuperfamily	Glycoside hydrolase family 79 protein [Hyaloscyphavariabilis F] (74%)

1079026	3 (0.36)	446.63(8.36)	507.85 (91.67)	ND	Hypothetical protein DL546_000384 [Coniochaetapulveracea] (50\%)

1232275	 5.14(1.25)	415.10(24.74)	444.79 (33.37)	Conidiation protein 6	Putative protein of unknown function [Podospora comata]（83%）

1211584	 0.80(0.12)	261.08(34.52)	306.38 (49.42)	ND	 Hypothetical protein FIE12Z_3876 [Fusarium sp.FIESC_12] (44%)

1071462	 4.77(0.06)	686.83(77.11)	880.60 (81.03)	ND	Hypothetical protein DL546_000384 [Coniochaetapulveracea] (52\%)

$496210^a$	 4.88(2.00)	532.48(69.90)	777.69 (74)	Multicopper oxidase	Bilirubin oxidase [Colletotrichum incanum] (70%)

496226	 3.07(2.04)	552.45(56.75)	880.08 (80.04)	ND	Hypothetical protein VD0004_g3696 [Verticillium dahliae](61%)


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You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Figure 4data	type of data points	no. of data points $(n)$ used inregression	reactivityratio(s)	 standarddeviation $( \pm)$	95% confidenceinterval

4a	1-4% conversion from each of ten experiments	10	$r_{\mathrm{DMA}}=1.120$	0.126	0.871-1.483

$r_{\text {FOSA }}=1.678$	0.204	1.273-2.266

4b	10% conversion from ten experiments	10	$r_{\mathrm{DMA}}=1.132$	0.129	0.878-1.506

$r_{\text {FOSA }}=1.692$	0.208	1.281-2.298

4c	incremental conversion across all conversions from ten experiments	114	$r_{\mathrm{DMA}}=1.126$	0.031	1.067-1.191

$r_{\text {FOSA }}=1.624$	0.048	1.530-1.726

4d	incremental conversion across all conversions from fourexperiments (subset of 10)	52	$r_{\mathrm{DMA}}=0.887$	0.028	0.832-0.946

$r_{\text {FOSA }}=1.299$	0.035	1.232-1.373

4e	incremental conversion across all conversions from fiveexperiments (different subset of 10)	62	$r_{\mathrm{DMA}}=1.266$	0.041	1.187-1.353

$r_{\text {FOSA }}=1.883$	0.072	1.748-2.033


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Site	Elevation (m)	Approximate size (ha)or dimensions	Type of aquatic habitat	Years

Ponds and Reservoirs

Yoncalla	120	2 ha	Adjacent unused loggingponds	1993-94

Cooper	244	ca. 150 m × 2.5 km	Artificial reservoir	1994

Alligator	895	1 ha	Impoundment of wetland	1995, 1997

Carmine	730	2 ha	Impoundment of wetland	1997-98, 2007

Blue Bluff	730	0.5 ha	Former gravel borrow pit	1994, 1996,2007

Rawlins	724	0.5 ha	Impoundment ofdepression	1995-97

Streams and Rivers

Cow Creek	305	2-3 m wide	Creek	1996

Jackson Creek	430	2 m wide	Creek	1994, 1996-97

S. Umpqua River	425	15 m wide	Small river	1997-98

Jenny Creek	1,115	2-3 m wide	Creek	1994-96


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	GG	MBP

	N	J1	A	N	J1	J2	J3	A

Fecundity	0	0	0.49	0	0	0	0	0.4

Survival	0.55D			0.3D

Survival		0.85	0.85		0.85

Survival						0.9

Survival							0.95	0.95


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Boundary	Alpha 1	U	P_rgh

Inlet	Fixedvalue	Fixedvalue	Zerogradient

Outlet	Zerogradient	Zerogradient	Fixedvalue

Atmosphere	Inletoutlet	Zerogradient	Fixedvalue

Bottom	Zerogradient	Fixedvalue	Zerogradient

Sidewall	Zerogradient	Fixedvalue	Zerogradient

Symmetry plane	SP	SP	SP

Hydrofoil/hull	Zerogradient	Slip	Zerogradient


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

原 申 請 內 容	擬 變 更 後 內 容	變 更 原 因

優 先 序	項 目名 稱	規 格	數 量	預 估單 價	預 估總 價	優 先 序	項 目名 稱	規 格	数 量	預 估單 價	預 估總 價

A-107-107	虛 擬 射 擊 體感 遊 戲 VR頭 盔 顯 示 器	1.2K 畫 質 以 上。2.2GDDR 含 以 上 記憶 體。3.178 度 視 角。4.虛 擬 射 擊 體 感 遊 戲連 線 版 系 統。5.保 固 半 年。	2 組	20,000	40,000	A-107-107	虛 擬 射 擊 體感 遊 戲 VR頭 盔 顯 示 器	1.2K 畫 質 以 上。2.110 度 視 角。3.虛 擬 射 擊 體 感 遊 戲連 線 版 系 統。4.保 固 半 年。	2組	20,000	40,000	因 規 格 誤植，擬 申 請變 更 規 格 。

A-107-132	VR 騎 馬 機頭 盔 組	1.2K 畫 質 以 上。2.1GDDR(含)以 上 記憶 體。3.178度 視 角。4.VR 騎 馬 機 連 線 版系 統。5.保 固 半 年。	1 組	20,000	20,000	A-107-132	VR 騎 馬 機頭 盔 組	1.2K 畫 質 以 上。2.110 度 視 角。3.VR 騎 馬 機 連 線 版系 統。4.保 固 半 年。	1組	20,000	20,000	因 規 格 誤植，擬 申 請變 更 規 格。

原 申 請 金 額 小 計	60,000	變 更 後 金 額 小 計	60,000


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Run type	Total run time(min)	Room temperature flexure(ksi)	600°F flexure(ksi)

Recipe	332	61	37

332	54	35

332	55	45

AI	309	71	45

237	72	39

387	65	38

Modified recipe*	350	79	24

350	82	22


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Satisfaction (Model 1)

Independent variables	Dependent variable

$\beta$	T

Constant	0.308	0.856

Social and cultural facilities	0.015	0.161

Education facilities	0.161	$2.968^{**}$

Quality of environment	-0.126	$-2.437^{**}$

Sufficiency of health services	0.043	0.461

Safety	0.210	$3.762^{**}$

Quality of health services	0.078	1.385

Public transport	0.111	$1.948^{**}$

Neighborhood	0.160	$2.913^{**}$

Model F	11.946

$R^{2}$	0.247

Adjusted $R^{2}$	0.227


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	 Male (N = 243)	Female (N = 213)

Ranking	Parts	Score	Parts	Score

1	Face	2.75	Face	2.88

2	Expression	2.25	Expression	2.35

3	Body Shape	2.23	Voice	2.28

4 	Voice 	2.14	Body Shape	2.25

5	Hairstyle	2.11	Hairstyle	2.18

6	Action	1.84	Action	2.05


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Classification accuracy (%）

Deletion	Imputation	Local-validity

68.67	70.67	80.33


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Type of bond	Index number	Ref.

Dark red pigment	Purple pigment

Fe-O (haematite)	0,1	0,1	[26]

Si-O-Si stretching	2	2	[27]

Si-O in clay	3,4	3,4,5	[27]

$ν_s(C-O)~+~δ(OCO)$ (hydratedmagnesium oxalate)	5	6	[28]

H-O-H bending	6,7	7,8	[10]

O-H bending	8	9	[10]

Mixture of O-H and water H-O-Hstretching	9,10,11,12	10,11,12	[29]

O-H stretching (crystallinehydroxyl)	13	13	[29]


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Weatherstation (alt)	Geographicalcoordinates	Air temperature(℃,annualmean）	Rain(mm,annualmean total)	Number ofdays withsnowfall	Number ofdays withheavysnowfall	Average snowdepth (cm)

Latitude	Longitude	Annual	1 November–31 April

Vf. Omu(2505 m)	45° 27'	25°27'	-2.5	1065.9	133.7	92.4	36.7	54.3

Sinaia(1500 m)	45°23'	25° 30'	3.7	1226.9	90.6	23	14.5 m	28.4


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Sample	$n_{1 \text { slope }}$$\omega \longrightarrow 0$	$n_{2 \text { slope }}$$\omega \longrightarrow 0$	$n_{1 \text { slope }}$$\omega \longrightarrow \infty$	$n_{2 \text { slope }}$$\omega \longrightarrow \infty$	$n_{\tan }$	eqs. (1) and (2)

$n_1 \omega \rightarrow 0$	$n_2 \omega \rightarrow 0$	$n_1 \omega \rightarrow \infty$	$n_2 \omega \rightarrow \infty$

SEBS-MAH34	0.67	0.80	0.38	0.38	0.54	0.5	0.5	0.5	0.5

SEBS-MAH54	0.50	0.60	0.52	0.52	0.54	0.5	0.5	0.5	0.5

SEBS-MAH74	0.20	0.40	0.50	0.50	0.54	0.5	0.3	0.4	0.4

						0.3	0.56	一	一

						0.3	0.3	一	一


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Studies	Interventions	Outcomes	Instruments 	$Effect~size^a$

Short term(0-<3 mo)	Mediumterm(3-6 mo)	Long term

（>6-12 mo）	(>12-24 mo)	>24 mo

			FQ-EOI	-.15	.033	-	-	-

		Carers' generalhealth	SF-12-PH	.14 	.35	-	-	-

			SF-12-MH	.062 	.35	-	-	-

McCannet al. (2010)	Self-helpbibliotherapy	Social problem-solving ability	SPSI-R:S	P> .05	P> .05	-	-	-


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	266 nm	532 nm	580 nm	634 nm	690 nm	730 nm	$1064 \mathrm{~nm}$

	K	$K_{2}$	K	$K_{2}$	K	$K_{2}$	K	$K_{2}$	K	$K_{2}$	K	$K_{2}$	K	$K_{2}$

$\mathrm{K}\mathrm(KI)_{2}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	2	$3^{a}$

 $\mathrm{K}\mathrm(KI)_{3}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	35	16

 $\mathrm{K}(\mathrm{KI})_{4}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	4	8

$\mathrm{K}(\mathrm{KI})_{5}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	10	$\cdots$	72

$\mathrm{K}(\mathrm{KI})_{6}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	50

$\mathrm{K}(\mathrm{KI})_{7}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	13	$\cdots$	36	$\cdots$	52	$\cdots$	70

 $\mathrm{K}(\mathrm{KI})_{8}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	28	$\cdots$	46	$\cdots$	73

 $\mathrm{K}(\mathrm{KI})_{9}^{-}$	$\cdots$	$\cdots$	$\cdots$	8	$\cdots$	11	$\cdots$	25	$\cdots$	43	20	$50^{a}$	b	b

$\mathrm{K}(\mathrm{KI})_{11}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	35	$\cdots$	50	5	$60^{a}$	$\cdots$	85

 $\mathrm{K}(\mathrm{KI})_{12}^{-}$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	$\cdots$	50	$\cdots$	65	$\cdots$	90

$\mathrm{K}(\mathrm{KI})_{13}^{-}$	$\cdots$	$\cdots$	25	$\cdots$	42	$\cdots$	70	$17^{a}$	40	$20^{a}$	42	$21^{a}$	b	b


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Parameter	Value	Units

Bed width $D$	100	mm

Bed height $W$	80	mm

Particle diameter distribution	2.85-3.15	mm

Particle density $\rho$	2490	$\mathrm{kg/m^3}$

Coefficient of restitution

$\text{particle/particle } e_{\text{p}}$	0.3-0.9

$\text{particle/wall } e_{\text{w}}$	0.3-0.9

Friction coefficient

$\text{particle/particle } \mu_{\text{p}}$	0.4943

$\text{particle/wall } \mu_{\text{w}}$	0.4480

Damping coefficient

$\text{particle/particle } C_{\text{n,p}}$	0.0417	$\mathrm{N} /(\mathrm{m} / \mathrm{s})$

$\text{particle/wall } C_{\text{n,w}}$	0.00833	$\mathrm{N} /(\mathrm{m} / \mathrm{s})$

Normal spring coefficient

$\text{particle/particle } K_{\text{n,p}}$	5900	$\text{N/m}$

$\text{particle/wall } K_{\text{n,w}}$	11 800	$\text{N/m}$

Tangential spring coefficient

$\text{particle/particle } K_{\text{s,p}}$	5900	$\text{N/m}$

$\text{particle/wall } K_{\text{s,w}}$	11800	$\text{N/m}$

$\text{Time step } \Delta t$	$3.2\times10^{-6}\:\min$	sec


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Error Threshold	 Arousal Ensemble Classifiers (3-fold,10-fold CV)

 Optimal Classifier Set	Full Classifier Set

 Averaged Voting	 Weighted Voting	 Averaged Voting	Weighted Voting

0.2	70.4	73.9	77.4	82.6	54.8	65.2	73.9	80.4

0.5	95.7	93.5	97.4	95.6	94.8	93.5	96.5	95.7

1.0	99.1	97.8	99.1	100	99.1	99.5	99.1	99.5

MAE	0.24	0.15	0.14	0.12	0.29	0.21	0.16	0.14


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

属 性	方 法

alpha	initDeviceOrientationEvent

beta

gamma

webkitCompassAccuracy

webkitCompassHeading


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Filler/pigment	Morphology ofparticles	CPVC(%)	$pH^{21}$	$Conductivity^{21}$$(\mu S/cm)$

Filler based on graphite

$C_{natural}$	Lamellar	44	5.9	494

$C_{natural} /PANI$	Lamellar	33	2.0	5420

Fillers based on silicates

$Mg_3 (Si_4 O_{10})(OH)_2$	Lamellar	47	8.9	103

$Mg_3 (Si_4 O_{10})(OH)_2$/PANI	Lamellar	37	4.4	1849

$Al_6 Si_2 O_{13}$	Lamellar	33	5.9	21

$Al_6 Si_2 O_{13}$/PANI	Lamellar	31	2.4	2160

Comparative pigments

Zn-Alorthophosphate	Isometric	41	6.1	205

PANI	Isometric	32	1.4	12600


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

TestNo。	Depth at which theplate was located, m	Tested soil	Values of the modulus of compres-sibility

for a pressureof 2.5 kg/$$\text{cm}^2$$	for a pressureof 4.0 kg/$$\text{cm}^2$$

4	7.05	Medium sand withgravel and pebbles	700	700

5	13。00	Silty sand	350	300

8	8。53	Medium sand withgravel and pebbles	660	540

9	7。00	Medium clayey sand	350	240

17	10。08	Loam	200	140

18	11。90	Silty sand	520	350

10	7。15	Medium sand withpebbles	980	630

13	12。03	Silty sand	350	350

11	5。53	Medium sand	1640	1300

14	7。70	Sandy ioam	400	320

15	9。05	Silty sand	700	500

16	11。35	Silty sand	490	230

19	6。90	Loam	350	300

20	9.50	Silty sand	410	370


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Solution 85 (nonlinear Yarkovsky model)

Epoch	2011-January-1.0 TDB

Semimajor axis (a)	1.126391025996 (42) au

Eccentricity(e)	0.203745112(21)

Perihelion dist. (q)	0.896894360(24) au

Perihelion time $(t_p)$	2010-August-30.6419463(30) TDB

Long. of asc.node (Ω)	2.0608668(37)°

$Arg. of perihelion (ω)$	66.2230699(55)°

Inclination (i)	6.0349391(27)°

$Bulk density (ρ)$	$1181.1(6.3) kg/m^{3†}$

$\chi^{2 \ddagger}$	68.37

Solution 87 (transverse Yarkovsky model,d=2.25)

Epoch	2011-January-1.0 TDB

Semimajor axis (a)	1.126391026404(40) au

Eccentricity (e)	0.203745114(21)

Perihelion dist.(q)	0.896894358(24) au

Perihelion time $(t_p)$	2010-August-30.6419468(30) TDB

Long.of asc.node (Ω)	2.0608670(37)°

$Arg. of perihelion (ω)$	66.2230705(55)°

Inclination (i)	6.0349388(27)°

Transverse accel.$(A_T)$	$-4.618(24) × 10^{-14} au/d^2$

$\chi^{2 \ddagger}$	68.73


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

企 業 名 稱	職稱	姓名或代表人	持有股份

股數（股）	持股比率

MEC ELECTRONICS(HK) COMPANYLIMITED	董事	彭國銘	0	0%

董事	袁万丁	0	0%

MEC ULTRAMAX(H.K.) COMPANYLIMITED	董事	彭國銘	0	0%

董事	袁万丁	0	0%

MEC BEST KNOWNCOMPANY LIMITED	董事	彭國銘	0	0%

董事	袁万丁	0	0%

HOMEPRIDETECHNOLOGYLIMITED	董事	彭國銘	0	0%

董事	袁万丁	0	%0

MEC ELECTRONICSPHILIPPINESCORPORATION	董事長	楊維顏	0	0%

董事	彭國銘	0	0%

董事	呂怡興	0	0%

董事	OLIVIA T.DE PERIO	0	0%

董事	CUA,JULIE	0	0%

總經理	呂怡興	0	0%

龍翰電子（蘇州）有限公司（註）	董事長	彭國銘	-	-

董事	袁万丁	-	-

董事	楊宗霖	-	-

監事	王雪慧	-	-

總經理	彭國銘	-	-

蘇州瀚騰電子科技有限公司（註）	董事長	彭國銘	-	-

董事	袁万丁	-	-

董事	楊宗霖	-	-

監事	王雪慧	-	-

總經理	闕河宗	-	-

東莞奇翰電子有限公司( 註 )	董事長	彭國銘	-	-

董事	楊宗霖	-	-

董事	林盈運	-	-

監事	王雪慧	-	-

總經理	林盈運	-	-

MEC IMEX (USA), Inc.	 董事/代表人	楊維鑫	0	0%


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Step	Selection valve position (PSV)	Action	Time $(s)^{a}$ 	Description

Determination of P(V): sequence 1

A	1	Aspiration	5	Ascorbic acid toward HC

B	2	Aspiration	5	P(V)sample/standard towardHC (to select with $SV_{1}$ )

C	4	Aspiration	5	Ammonium molybdate toward HC

D	6	Delivery	120	Delivery to the $RC_{1} $ and detector (to select with $SV_{2}$ )

Determination As(V): sequence 2

E	1	Aspiration	5	Ascorbic acid toward HC

F	2	Aspiration	5	As(V) sample/standard toward HC(to select with $SV_{1}$ )

G	4	Aspiration	5	Ammonium molybdate toward HC

H	5	Delivery	120	Delivery to the $RC_{2}$ (55°C) and detector (to select with $VS_{2}$ )

Determination of As(Ill): sequence 3

I	1	Aspiration	5	Ascorbic acid toward HC

J	2	Aspiration	5	As(Ill) sample/standard toward HC(To select with $SV_{1}$ )

K	3	Aspiration	2	$KIO_{3}$ toward HC

L	4	Aspiration	5	Ammonium moly bdate toward HC

M	5	Delivery	$130^{b} $	Delivery to the $RC_{2}$ (55°C) and detector (to select with $SV_{2}$ )


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Solution method	Stochastic $H_∞-\gamma$	Stochastic $H_2$ upper bound -M

$Quadratic^2$	No solution	No solution

Robust (Finsler)	1.36 (Lemma 3)	5.16 (Corollary 1)

Improved solution	1.32, $\epsilon$ = 0.001 (Theorem 2)	5.01 (Corollary 2)

Gain scheduling	0.47 (Corollary 3)	1.1, Equation (27)


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

工程类别	项目名称	规 模	备 注

大 型	中 型	小 型

城市道路	路基工程	 城市快速路、主干道路基工程≥5 km,单项工程合同额≥3 000万元	 城市快速路、主(次)干道路基工程2~5 km,单项工程合同额1000万~3000万元	 城市次干道路基工程<2 km,单项工程合同额<1000万元	 含城市快速路、城市环路,不含城际间公路

路面工程	 高等级路面≥10 万$m^{2}$,单项工程合同额≥3 000万元 	 高等级路面5万~10万 $m^{2}$,单项工程合同额$1000$万~3000万元	 次高等级路面,单项工程合同额<1000万元

城市公共广场	广场工程	 广场面积 ≥5 万$m^{2}$,单项工程合同额≥3000万元	 广场面积 } 2万~ 5万 } $m^{2}$, 单项工程合同额1 000万~3 000 万元 	 单项工程合同额<1000万元	含体育场

城市桥梁	桥梁工程	 单跨跨度≥40 m;单项工程合同额≥3 000万元	 单跨的跨度20~40 m;单项工程合同额1000万~3000万元	 单跨跨度<20 m;单项工程合同额<1000万元	含过街天桥

地下交通	隧道工程	 内径(宽或高)≥5 m或单洞洞长≥1000 m,单项工程合同额≥3000万元	 内径(宽或高)3~5m,单项工程合同额1000万~3000万元	 内径(宽或长)<3 m,单项工程合同额<1000万元	 含地下过街通道;小型工程不含盾构施工

车站工程	 单项工程合同≥3000万元	 单项工程合同<3000万元		 小型工程不含车站工程

城市供水	供水厂	 日处理量≥5万t,单项工程合同额≥3000万元	 日处理量3万~5万t,单项工程合同额1000万~3000万元	 日处理量<3万t,单项工程合同额<1000万元	 含中水工程,加压站工程

供水管道	 管径≥1.5m,单项工程合同额≥3000万元	 管径0.8~1.5 m,单项工程合同额1000万~3000万元	 管径 <0.8 m, 单项工程合同额 < 1000万元	 含中水工程,本表中的管径为公称直径DN


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	Distress Group H,D	Recovery Group D,H

	NYSE inS#P 400	 NYSEOutsideS#P 400	NYSE inS#P 400	 NYSEOutsideS#P 400

CompustatSample	115	229	82	154

InsufficientCRSP Data	14	119	10	64

Sample Size	101	110	72	90


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

願或 .	栗恕 .	朱安仁 .	杜思進 .	田友信 .	徐輝 .	石璞 .	傅鑼 .

						由教驗陞 .	人 内才 . 黄人 .

	盧淵 .	劉# .	王翼 .	齊泰 .	葛瑾 .	葉# .	許濂 .

	太 新學 建生 . 人 .	進 江士 . 陵人 .	進 魚士 . 臺人 .	進 溧士 . 水人 .	進 沂士 . 水人 .	薦舉 .	濰縣人 .


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

法规名称	条文号	所在页码	引用意义

	431,432,433	332	因果关系的判断标准

	435 (2)	348	因果关系的判断

	766C	178	对纯粹经济损失的赔偿限制

《美国合同法重述》（第二版）	353	251	违约责任与精神损害赔偿的关系

英国 1945 年过失相抵改革法		161	过失相抵

英国 1846 年致命事故法案		235	死者近亲属等的赔偿请求权

1994 年国际统一私法协会《国际商事合同通则》	7.4.2	251	完全赔偿

汉谟拉比法典	196,197	187 (注释 1)	对人身损害的同态复仇


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	$\chi^2$	d.f.	P

Juvenile males

CJS	102·55	32	 < 0·001

Transience	83·90	25	< 0·001

Trap-dependence	79·43	26	< 0·001

Combined	89·29	38	< 0·001

Adult males

CJS	131·89	39	 < 0·001

Transience	109·82	32	< 0·001

Trap-dependence	73·92	23	< 0·001

Combined	79·56	38	< 0·001

Juvenile females

CJS	102·00	37	< 0·001

Transience	33·59	30	0·298

Trap-dependence	93·61	31	< 0·001

Combined	-	-	-

Adult females

CJS	106·76	32	< 0·001

Transience	87·48	25	< 0·001

Trap-dependence	82·70	26	< 0·001

Combined	76·74	42	< 0·001


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Trait	Breed	No.	ADP:$O^c$	ATP synthesis $rate^d$

PM	R	PM	R

Cow's weaningweight deviations	Hereford	12	.10	.31	-.20	-.36

Angus	13	-.15	-.03	-.14	-.04

Brangus	8	-.41	-.44	-.51	-.54

Cow's maternal half-sibsweaning weight ratio	Hereford	12	.36	.60*	-.06	-.63*

Angus	13	-.22	-.25	-.31	-.17

Cow's progeny meanweaning weight ratio	Hereford	12	.13	-.03	-.13	-.14

Angus	12	-.79**	$.72^{* *}$	-.35	-.60*

Brangus	9	-.15	.21	-.23	.22

Cow's yearlingweight deviations	Hereford	10	-.07	.01	.21	.15

Angus	13	.10	.11	-.08	.01

Brangus	8	-.53	-.29	-.26	-.38

Cow's maternal half-sibyearling weight ratio	Hereford	11	.01	.17	.32	.15

Angus	12	-.21	-.06	-.07	-.08

Cow's progeny meanyearling weight ratio	Hereford	9	.32	.25	.14	-.13

Angus	11	-.49	-.30	-.25	-.25

Brangus	5	-.51	-.60	-.51	-.60

Cow's paternal half-sibsweaning weight ratio	Hereford	12	.19	.11	.63*	.23

Angus	13	-.50+	-.16	-.63*	.00

Cow's paternal half-sibsyearling weight ratio	Hereford	12	-.44	.25	.47	.17

Angus	13	-.52+	-.22	-.63*	.03


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	Before the introduction ofparental leave (reference year 1995)	After the introduction ofparental leave (reference year 1999)	Total

	N	% working0 hours -1996	% working0 hours -1997	% working0 hours -1998	N	% working0 hours -2000	% working0 hours -2001	% working0 hours -2002	N

Mothers of one child	357	29.1	34.2	31.0	447	14.4	20.0	21.9	834

Mothers of two children	115	26.1	29.6	26.1	125	10.9	16.3	16.3	240

Childless women	7119	4.0	6.8	8.5	8651	4.5	7.2	9.5	15770

Total	7593				9223				16816


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Sl.No. 	Description	Design value

1	Nominal Flow Rate	170 m^3/h

2	Nominal Operating Temperature	350 ℃

3	Maximum Sodium Temperaturepermissible	450 ℃

4	Shut-off Head	$9 kg/cm^2 at 360V ( L-L)$

5	Operation	Continuous

6	Mounting Position	Horizontal

7	Pump Duct Design Pressure	$10 kg/cm^2$

8	Line Voltage	360 V, 3 Phase

9	Frequency	50 Hz

10	Line Current	308 Amps

11	Power Factor	0.5 at rated condition

12	Efficiency (%)	19.3

13	Input Power	98 kW

14	Cooling	Forced Air Cooling

15	Number of Poles	6

16	Slot per pole phase	2

17	Maximum Stator Current Density	$3.67 Amp/mm^2$

18	Tooth Flux Density	0.61 T

19	Annular gap for sodium flow	10.5 mm

20	Operating Slip	0.42


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

compd	X = Y =Z = H	$X = CH_{3}$,Y = Z = H	X = Z =$CH_{3}$,Y = H	origin

$O_{3}$	34.8			expt

XCH=(Z)CY	14.5	8.5	2.1	expt

XCHOOO(Z)CY	0	-7	-14	theory

XCH=O	-27.1	-37.1		expt

XCHOO	38	23		theory

$OCH(X)O^{b}$	4	-11		theory

OCH(X)O(Y)C(Z)O	-50	-58	-68	theory


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Wood	 Drydensity$(g /dm^{3})$	Measurementcross sectionb × h($~~~mm^2$)	Condition dry	Condition wet

Moisturecontent(weight-%)	Cuttingdepth(mm)	Moisturecontent(weight-%)	Cuttingdepth(mm)

Oak	680	50 × 60	5.2	2.5	42	4.5

E. beech	680	60 × 60	6.5	2.5	61	4

Spruce	400	60 × 60	10.1	4	60	5


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Dependent variable	 Financial KIBS (t)	All other (non-KIBS) sectors (t)

Financial KIBS (t)	-		-

All other (non-KIBS) sectors (t)	0.130***	(0.050) 	-

Financial KIBS (t -1)	0.078***	(0.021)	0.027***	(0.007)

All other (non-KIBS) sectors (t -1)	0.181***	(0.046)	0.395***	(0.028)

Model 3: Non-financial KIBS versus all other (non-KIBS) sectors

Dependent variable	Non-financial KIBS(t)	All other (non-KIBS) sectors (t)

Non-financial KIBS (t)	-		-

All other (non-KIBS) sectors (t)	-1.133***	(0.350)	-

Non-financial KIBS (t - 1)	0.014	(0.012)	0.009***	(0.002)

All other (non-KIBS) sectors (t -1)	0.763***	(0.189)	0.391***	(0.028)


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Targetconcentration	Lab 1	Lab 2

Measuredconcentration	Variance components %	TotalSD	TotalRSD	Measuredconcentration	Variance components %	TotalSD	TotalRSD

Day	Extract	PCRReplicates	Day	Extract	PCRReplicates

0.05	0.05	0	87.8	12.2	0.02	36.5	0.09	29.8	64.0	6.5	0.10	119

0.10	0.11	0	95.0	5.0	0.06	57.5	0.20	54	4.5	41.6	0.13	63

0.25	0.31	0.5	79.5	20.0	0.15	47.3	0.43	0	79.0	21.0	0.24	56


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

 No ofAntennaelements	DR shape	Frequency(GHz)	Feed type	Axial ratiobandwidth	References

1	C-Shaped	5	strip	44%	[67]

1	Rectangular withInclined slits	5.2	Probe	210 MHz	[68]

1	Rotated StackedRectangular	9.8	Slot	6%	[69]

1	Cylindrical withalford loop	2.4	Probe 	7%	[70]

1	Rectangular withInclined slots	3.5	Probe	25%	[71]

1	Rectangular withdiagonal groove	1.5,2.4	Slot	6.3% and3.68%	[72]

1	Half Cylinder	6	Strip	27%	[73]

3	Elliptical	10	Dielectricimage line	5.3%	[74]

1	Rectangular,Fractal	5.5,5.9	Cross-slots	5.85%	[75]

1	Elliptical (Hybrid)	60	ModifiedSlot	10%	[76]

1	Cylinder	3.3	Helical tape	6.4%	[77]

1	Vertical Cross	4.7	Probe	6.8%	[78]


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

NiTi deposition in AJA ATC co-sputter tool

NiTi target power (W)	375

Ti target power (W)	250

Thickness (nm)	270

Deposition time (min.)	18 minutes @ 15 nm/min.

Dep. Temp (°C)	600

Argon flow (sccm)	60

Chamber Pressure (mTorr)	5

Table 2 SU8 2000.5 fabrication parameters

SU8 2000.5 fabrication (Micro Chem Corp.)

Material	SU8 2000.5

Spin Speed (rpm)	4,000

SU8 Thickness $(\mu m)$	1.0

Soft Bake	2 min. @ 95℃

Exposure	160 $mJ/cm^{2}$

Post Exposure Bake	4 min. @ 95℃

Develop	50 seconds in SU8 developer

Rinse	Fresh SU8 developer, IPA


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

Method	Material properties	Location A	Location B

MLS-MLPG1 [28]	Homogeneous	2.918	2.140

FGM	2.360	2.594

Graded FEM [57]	Homogeneous	2.908	2.137

FGM	2.369	2.601

RBF-MLPG1	Homogeneous	2.885	2.127

FGM	2.420	2.620

RBF-MLPG5	Homogeneous	2.901	2.131

FGM	2.403	2.607


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

	Philosophy (general)	Philosophy of science

1840		Whewell, Philosophy oSciences

1865	Mill, Examination of Sir William Hamilton'sPhilosophy

1866		Lange, History of Mat

1872		E. Dubois-Raymond,Knowledge

1873		Jevons, The Principles

1874		Kirchoff, Principles of

1877	Peirce, 'The Fixation of Belief'

1878	Peirce, 'How to Make Our Ideas Clear'Peirce, 'The Doctrine of Chances'

1881		Helmholtz, Popular Le

1883		Mach, The Science of

1885		Clifford, Commonsens

1892	Frege, 'On Sense and Reference'	Pearson, The Gramma

1893	Bradley, Appearance and RealityPeirce, Search for a Method (not completed)	Mach, Popular ScientificHertz, The Principles o

1894	Peirce, The Principles of Philosophy (notcompleted)


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

项 目	行次	 计 划 数	实 际 数

本年	本季	本期	累计

11.机械设备购修费	12

12. 生产房屋建设	13

13.职工宿舍建设	14

二、经费支出(养路事业费)	15

1. 行政管理费	16

2. 路政经费	17

3.征稽经费	18

4.	19

三、借款 工程 支出	20

	21

四、其他	22

支出 合计	23


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.


Question:
You are an AI specialized in recognizing and extracting table from images. Your mission is to analyze the table image and generate the result in HTML format using specified tags.
Output only the results without any other words and explanation.

SU-8-based	Silicon-based

	SSS	DSS		SSS	DSS

SU-8	$1700 \mathrm{~nm}$	$1700 \mathrm{~nm}$	$\mathrm{Si}_x\mathrm{~Ni}_y$	50 nm	50 nm

Au	60 nm	60 nm	Si	150 nm	150 nm

SU-8	4500 nm	$1700 \mathrm{~nm}$	$\mathrm{Si}_x\mathrm{~Ni}_y$	210nm	50 nm

$\varepsilon / \sigma_{\mathrm{s}}\left(10^{-5}\right)$	$4.7~\mathrm{m}~\mathrm{N}^{-1}$	$ 7.0\,\mathrm{m}\,\mathrm{N}^{-1} $	$\varepsilon / \sigma_{\mathrm{s}}\left(10^{-5}\right)$	$ 2.2 ~m~N^{-1} $	$3.3 \mathrm{~m} ~\mathrm{~N}^{-1}$