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In the following content, three targets are used, such as: , and GDPI, to carry on the stable analysis by statistical data between 1978 and 2010 in Zhenjiang city, further studies the relation between the industrial structure adjustment and the economy growth in Zhenjiang city by the Grainger causality test.
Before carrying on the Grainger to test the model, we Firstly test the data stability using the ADF unit root.
Generally , , ,named as the first step difference of , named as the first step difference of , named as the first step difference of , we test the data stability using the ADF unit root to , , .
GDP) and statistical output value data about the primary industry, the secondary industry and the tertiary industry in “Zhengjiang Statistics Yearbook 2011" (2001-2010), the following estimate economy model may be obtained utilizing Eviews3.1 economical measurement software: (5) （13.09） （104.87） （61.15） (Note: the data in the parenthesis under the parameter is the one corresponding to the T-statistics data in the estimate model) It can be known from the results that (1) Looking from the growth elasticity of the contribution of the three industries to the economic growth, the primary industry, the secondary industry and the tertiary industry’s growth elasticity respectively are: 0.1033, 0.5872, 0.3158.
The global greenhouse gas emission reduction: the theoretical framework and solutions [J].

The bevel package showed about an 83% reduction in the mean number of flakes.
Figure 8: Overlay X (Left), Y (Right) data comparing POR and Bevel Clean The Ovelay data of the wafer splits on the X and Y axis were measured after the patterns were aligned and developed on the photolithography tool.
The split data indicates that the bevel clean split has a much smaller standard deviation at both the X and the Y axis.
“Middle of Line (MOL) Cleaning Challenges in Sub-20nm Node Device Manufacturing”, UCPSS (2016) [3] Aaron Eppler, “Controlling Uniformity At The Edge”, SEMICONDUCTOR ENGINEERING (2017) [4] KLA-TENCOR,” Criticality Of Wafer Edge Inspection And Metrology Data To All-Surface Defectivity Root Cause And Yield Analysis”, SEMICONDUCTOR ENGINEERING (2018)

Introduction By analyzing the movement rules of ocean current and the drift process of Ocean Bottom Seismometer(OBS’) launching underwater to establish the mathematical model of OBS’s water drifting process accurately; By analyzing the OBS’s force conditions in sea water (gravity, buoyancy and sea water resistance, etc) to establish the stress predicition model of OBS’s sinking coupled frame sole; By analyzing the coupling characteristics between OBS and undersea medium and contact surface feature, based on software ANSYS, to set up the finite element model of coupling frame; Combined the mathematical model of OBS’s drift process with the coupling frame’s finite element model, using modal analysis method to analyze the influence of OBS coupling frame on OBS settlement process to improve OBS coupling frame’s mechanical characteristics and solid bottom characteristics, and to reduce the OBS’s drifting distance caused by ocean currents, then to obtain more reliable OBS seismic data and
guarantee the reliability of later data processing.
Using a sphere Hertz's law[4], the collision time can be got from energy conservation , and use energy conservation ways to get an elastic body collision of time, and then use momentum theorem to get the corresponding relations between the pressure and reduction[5].
And then use the single factor analysis and comparison analysis to analyze various factors on the influence of the OBS settlement process, and further analyzes the effect of OBS sink coupling frame on the process of OBS settlement, and concludes that the heavy coupling model parameters for each frame OBS settlement process influence, and feedback the actual measurement data to the settlement frame model, so to improve the settlement frame model and reduce the OBS submarine drift caused of the ocean currents acquiring more reliable OBS seismic data.

Introduction With the rapid development of information technology, the application of high-dimensional data is wider, the number of high-dimensional data is also increasing, the dimensionality reduction of high-dimensional data is particularly more and more important .The main purpose of manifold learning is to restore the low-dimensional manifold structure from high-dimensional data.

Thus, by analyzing only data on the powder bulk density (packed density)it is not possible to make unique conclusion in order to choose the optimum processing time of the powder mixture in the PBM.
The data of the measurements are presented in the form of a histogram in fig. 2.
This fact is well consistent with numerous literature data on the treatment of powder mixtures in the PBM, and can be interpreted as the result of particle agglomeration.
Thus, using the data presented in Fig. 2, it is possible to make the following generalization: 1.
The additional comparison with data of Barkhausen noise measurement suggests that there are practically no metal particles in the composite coating.

The Ni-Cu-Mo electrodeposition process is accompanied by the hydrogenation side reaction, which leads to a certain error in the results after data processing.
Despite this, the error can still be ignored when the data obtained from the test with the total current are processed due to the addition of sodium dodecyl sulfate and other additives into the electrodeposition solution.
Based on the data collected from the single potential step curve of trisodium citrate at different concentrations, as shown in Fig. 2, the results were plotted and compared with the nucleation Models (1) and (2), as detailed in Figs. 3 and 4.
According to Figs. 3 and 4, the experimental data obtained without and with the addition of trisodium citrate are consistent with the theoretical value of transient nucleation before the current peaks (t/tm≤ 1).
(3) Based on the data of the i-t curve in Fig. 1, the im at each step potential can be determined, as shown in Tab. 1.

A nonlinear finite element model was established using ANSYS with right material parameters for prestressed concrete box girder with steel plate and concrete composite strengthening (SPCCS).A comparison was made between analysis results and function formula data, and results show that the numerical result s of nonlinear static analysis are in good agreement with the formula results.
Refer to Tab. 4 for some of the measured horizontal distribution data.
Here a comparative analysis is applied to the effects of above two different strengthening methods in load test, and refer to Tab. 5 for part of the test data.
Secondly, the rigidity, strength and horizontal loading distribution as well as dynamic performance of the bridge are evaluated with the numerical analysis results and load test data of the bridge.
All the data show that the strengthening is effective.

Introduction Since the dark current can lead to the reduction of the performance of the infrared detectors, what related with the dark current attracts a wide attentions[1-3].
(4) Results and data Table1 Parameters of the QDIPs
In this figure, the curves with ”*” and the circles represent the dark current values from the our models at the temperature 78K and 100K, respectively, the plot including circularities is the dark current data from the published data[15] at 78k.
Let these published data at 78K are compared with calculated values, it can be found that they have a good consistency, and the consistency show the right of the models.
Based the model, the calculated results of the dark current is given, and they are compared with the experimental data from published reports.

Experimental data are compared with calculations based on density functional theory using the generalized gradient approximation (GGA) for the positron annihilation.
Details of the experimental setup as well as the data treatment [5] were in many respects similar to the case study described in Ref. [6].
Results Fig.1 shows experimental raw data and calculations.
The fact that experimental data for Al-6at.
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Subsequently, the acquired data are processed and analyzed for determining the current state of the printer.
While in the first part, the configuration and start-up tasks of the system are carried out, in the second one, a sequential image acquisition and processing procedure to obtain data is done.
Merla, “Regions of interest selection and thermal imaging data analysis in sports and exercise science: A narrative review,” Physiol Meas, vol. 42, no. 8, 2021, doi: 10.1088/1361-6579/ac0fbd
Patino et al., “Fusion of Heterogenous Sensor Data in Border Surveillance,” Sensors, vol. 22, no. 19, pp. 1–17, 2022, doi: 10.3390/s22197351
Bartsokas, “Computer Vision and Pattern Recognition for the Analysis of 2D/3D Remote Sensing Data in Geoscience: A Survey,” Remote Sens (Basel), vol. 14, no. 23, 2022, doi: 10.3390/rs14236017