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Reduction by silicon If silicon is used as a reducer for barium reduction, the process of reduction progresses proportionally to the amount of reducer up to 0.06 kg (Fig. 3).
The degree of barium reduction amounts to 70%.
However, its reduction degree is 40–50 % only.
Reduction by silicon and aluminum To assess the possibility of combined reduction by silicon and aluminum the case for reduction of 1 kg ВаО and 0.2 kg Si followed by aluminum addition was calculated.
The data of calculation are shown in Figure 7.

This analytical model can explain almost all experimental data: oxidation-temperature dependence, oxidation-time dependence, and initial-Z1/2-concentration dependence of the defect reduction.
Based on these data, an analytical model of defect reduction is proposed.
Each symbol indicates the experimental data and each line indicates the calculated nI curve obtained from Eq. (1)-(3).
Each symbol indicates the experimental data and each line indicates the calculated nV curve.
Each symbol indicates the experimental data and each line indicates the calculated nV curve.

The α-MnO2-CNT curve shows a significant reduction current with a reduction peak at -0.2V (versus the standard calomel electrode, SCE) in an oxygen-saturated environment.
The reduction potential of α-MnO2-CNT shifted from -0.28 to -0.32 at 1600 rpm.
The four-electron transfer reaction occurs in the following order: 2+-* (i) *** (ii) *-* (iii) *+-2 (iv) The Koutecky-Levich (K-L) equation can be used to calculate the number of electrons (n) involved in the oxygen reduction reaction, as depicted in Figure 6. using the rotating disk electrode (RDE) data for various voltages.
The K-L equation is presented as follows: (1) (2) (3) The equation used to calculate the electron transfer number in RDE data for various voltages, shown in Figure 6. is given by the Koutecky-Levich (K-L) equation.
"Biomass-derived metal-free porous carbon electrocatalyst for efficient oxygen reduction reactions."

In cork stopper production SMED resulted in a 43% overall reduction in changeover time.
Step 1 was done together with step 6, and step 3 was done together with step 4, which resulted in a time reduction of 9.35 minutes.
Design and create a new bypass system to reduce the time required to bypass PVC, resulting in a reduction in work time.
Data was collected and timing was recorded for five instances after the improvements were made.
By analyzing the data and implementing a system to sustain positive outcomes, the standardized procedures and implementation methods that have proven effective are adopted as work standards by the management team and provide the standard documents for training the relevant personnel.

Analysis of Carbon emissions and countermeasure research in Guangzhou Chen Yu1,a, Jian-ping GE1.b,Li Li1.c 1School of humanities and economic management, China University of Geosciences, Beijing 100083 739120848a@qq.com,bgejianping@cugb.edu.cn,clilyght@126.com Keywords:Carbon emissions, emissions reduction policy, Guangzhou Abstract.This paper uses data Decade 2003-2012 "Guangzhou StatisticalChen Yu (1991), female, Master in public management／JianpingGe (1982), male, associate professor, research direction for the new energy economy and management.
Present situation of carbon emissions Calculation methods and data sources According to the method recommended by the 2006 IPCC national greenhouse gas listing guidelines, according to a 2003-2012 data of the total energy consumption in Guangzhou to estimate of Guangzhou’s carbon emissions, we can get the carbon emissions in Guangzhou.
This article adopted all kinds of energy coefficient of carbon emissions, provided by the national development and reform commission energy research institute, as the basis for the calculation, as it shown in table 1: Table 1.The coefficient of carbon emissions of all kinds of energy Kind Coal Oil Natural gas （ten thousand tons of carbon／ten thousand tons of standard coal） 0.7476 0.5825 0.4435 The data in this article is from the Guangzhou statistics yearbook (2003 to 2012), an the data of the sample ranges from 2003 to 2012 Carbon emissions According to relevant data and formula calculation, we can get the carbon emissions and growth rate in Guangzhou, as it showed in figure 1 and figure 2: Figure 1 2003～2012carbon emissions in Guangzhou Figure 2 2003～2012 growth rate of carbon emissions in Guangzhou From figure 1, we can see that in the period 2003 to 2012, the total amount of carbon emissions in Guangzhou showing an overall upward trend, rising year by year, from
Strategies for the reduction of carbon emissions in Guangzhou Improving energy efficiency is the core objective of the measures of greenhouse gas reduction.
Among them, improve energy efficiency and emission reduction measures is the main content and core objectives.

The application research on the data protection of the typical CNC machine Qiujun Wu1,a, Jianjun wang1,b 1HeBei institute of mechatronic technology, Xingtai, China 054048 awqj12san@126.com , bwabj2025@126.com Keywords: Machine data, data backup, data recovery Abstract.
Therefore, a good data backup solution is the most effective mean to solve the data fault.
Such as machine data, tool data, zero offsets, setting data, pitch compensation, part program and so on.
Data reduction is the reverse process of data backup.
FANUC data backup includes user data backup and PMC data backup.

This text studied the affection of the cold reduction ratio and annealing temperature to the high strength IF steel on microstructure and property, and assured the optimal process parameter which has supplied the theoretical guidance and reference data to the industry.
The A80 gradually reduce under 85% cold reduction ratio, and the A80 gradually increase under others cold reduction ratio.
The Ae gradually increase under 75% cold reduction ratio, and the Ae gradually reduces first increases again under others cold reduction ratio.
The A80 gradually reduce under 75% cold reduction ratio, and the A80 had no obvious change under others cold reduction ratio.
The Ae reduces first and increases again under 85% cold reduction ratio, and the Ae g had no obvious change under others cold reduction ratio.

Another one is based on the use of test data compression (TDC) techniques, which has been at the forefront of solutions to reduce test costs through reduction in tester storage and test application time[1~16].
A method called COMPACT is presented in [10], the key idea of COMPACT is to employ two data compression schemes, run-length coding for data with low activity and GZIP for data with high activity.
In the paper, we analyze the application condition of a compression algorithm for test data, and denote a test data compression method RLE-G, Run Length Encoding based on Golomb coding, that provide significant compression for pre-computed test sets and lead to considerable reduction in testing time, it has the excellent advantages of high compression ratio and low overhead.
As the original test data are stored on the ATE side, and the test data stored in memory of the ATE in compressed (encoded) form (TE).
Therefore, to reduce the data expansion and get highest compression efficiency, the analysis of the overall data coding results is needed.

They are specified in a veryhigh-dimensional tensor space and recognition methods operatingdirectly on this space suffer from the curse of dimensionality[3].Dimensionality reduction is commonly used to transform a high-dimensional data set to a low-dimensional subspace while retaining most of the underlying structure in the data [4].
In this paper, we use Kernel Principal Component Analysis (KPCA) for dimensionality reduction and feature extraction in railway tunnel deformation data analysis.
KPCA reduce dimensionality of original data.
The projected data could basically represent the original railway tunnel deformation data information, but its distribution in Eigen space is not compact.
Jain, "Incremental nonlinear dimensionality reduction by manifold learning," IEEE Trans.

Experiment apparatus and procedure The experiment data were obtained at the Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, DLUT.
Through the comparison of the grain coating permeability model and the pore filling permeability models with the experimental data, the results are better agreement with the pore filling mode that hydrate will form.
Similar to above, the experimental data are correlated using Masuda's permeability correlation [9], as Eq. (3).
Comparison between the experiment data and Masuda permeability model.
In the absence of experimental data, many numerical simulations have shown that the gas production rate is correlation with permeability of the hydrate zone [6, 9].