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Experimental details The material studied was made by direct reduction of extra pure quartz and carbon.
After tapping from the reduction furnace, the material was cooled down, etched and cleaned with DI water.
Compared to literature data, the EBIC contrast values of dislocations at 100K are quite high - we cannot exclude that in our measurements the dark spot visible in the map is due to more than one dislocation.
Summary In this work we reported a first study of solar grade silicon obtained directly by carbothermic reduction of very pure quartz and carbon.
The data and information obtained by these analysis are used for an optimisation of a solar cell process for this material which is currently in progress.

In this study, the method to quantify the effectiveness scale was suggested by selecting travel time saving, CO2 reduction, fuel savings and VMS information provision as benefit items for effect analysis on the national highway ITS project.
In particular, direct effects like travel time saving and operating cost reduction for users and operators as well as indirect effects like noise and air pollution reduction can be expected through ITS construction.
The economic evaluation is the method to analyze effectiveness and economic feasibility of project through economic indicators by quantifying costs and benefit items, and it evaluates economic feasibility by outputting the benefits considering characteristics of ITS by functions in future travel pattern after predicting traffic demand through basic analytical data for evaluation[6].
For benefit items generally used in ITS effect analysis, travel time saving, CO2 reduction, fuel saving and CMS information value benefits were selected.
In this study, the method to quantify the effectiveness scale was suggested by selecting travel time saving, CO2 reduction, fuel savings and VMS information provision as benefit items for effect analysis on the national highway ITS project.

The investment costs for reduction SO2 is CNY 600/t.
Forest Fire Case Analysis Because the data of real forest fire case in not sufficient, the case in this paper is a self-made forest fires case.
It was operated fully through self-made forest fire data and it provided an important basis for accurately measuring forest fire loss and correctly assessing forest fire prevention work.
At present, in our country only some serious or especially serious forest fire has field assessment survey, and the survey data have omission items.
The accuracy of forest fire loss data is directly related to loss assessment result accuracy.

As can be noticed by analyzing of the data presented on the fig. 2 during rolling in Variant I the average size of the austenite grain diameter was approximately 20 μm.
During rolling in Variant II the average size of the austenite grain diameter was approximately 15 μm (reduction by 25% than in traditional rolling process).
Unification on the cross section and reduction of the austenite grain size should causes uniform mechanical parameters and increase impact resistance.
Estimated, in industrial conditions data, confirmed good agreement of the theoretical model used to determination evaluation of microstructure during round bars rolling.
When analyzing the data presented on the Fig.5 it can be found that decrease of the average austenite grain size and unification the grain size on the cross section of rolled round bars causes during rolling with accelerated cooling (Variant II) causes increase of braking energy of the ø26 mm round bars in all range investigated temperatures.

Due to mandatory emission reduction and rising oil prices electric vehicles are about to be introduced in mass markets.
From the China automobile industry yearbooks and china statistical yearbooks, correlative data of automobile industry and china macro economy from 2004 to 2011 are collected.
Table 1 Scale value of EV industry 2015 2020 Eclectric vehicle industrial scale (number of EV vehicle) 1510000 9320000 Under Copenhagen commitment control, the EV scale of China in 2020 is better from 92340 to 102890 [5].Compare the scale data with Table 1, the EV scale in 2020 far more below the necessary number if the government policies stay the same.
The result does not comply with energy conservation and pollution reduction targets and is not conducive to the industrialization of EV industrial development.
The scale of EV in 2020 is 92340,000 which equal to data in Table 2, corresponding values of government policies is in Table 2.

Comparison between the predicted data and the measured ones shows that the higher the precision level is, the more accurate the model prediction will be.
Even though historical data is sparse and arbitrarily distributed, the method is feasible.
According to the above data, the model was established and the NO2 concentrations of the same months in 2012 had been predicted [4].
Through contrasting with the measured data in the else points, the predicted results are reasonable.
It can be seen from Fig. 1 that the pollution trends are basically the same, but the predicted and the measured data are not absolutely one-to-one correspondents.

Introduction As a natural capital,soil has not  been comprehensive cognized recently.With the development of city modernization and industrialization,human activities affect the evolution of soil resource function profoundly and lastingly,including the shift between soil  bearing function and soil production function,and the reduction of ecological regulation function from sealing soil etc..The transformation of soil functions, reduction or even specific function disappear, these has caused the unbalance of many areas’ soil function,and these factors has become the shackles of soil utilization value maximization, so in order to achieve the optimized use of soil resources we  must carry on scientific planning.
We can select a scientific econometric model to choose soil advantage  function or function group in specific region with the specific data,change the simple ideas to determine the optimal use  and value only on the basis of land productivity and geographical position.
Factor analysis model also can make some complicated and high correlative indexes into a functional groups according to the objective representation of data.
The empirical analysis 3.1 The data source.On the base of Zhengzhou soil species, soil database, agriculture and land use database, landform characteristics,56 sample points in the territory were selected and corresponding soil function parameters were extracted .
Then this paper obtain soil value data matrix by two methods of reference and measuring formula.

Through the tensile test, use ANSYS Workbench to simulate the process of tensile measurement and compare the experimental data.
It has such good advantages[1-4] as high strength, high hardness, high fatigue strength as well as low density, light weight, shock absorption and good noise reduction, etc.
Tensile Test Results and Analysis The Influence of Austempering Parameters on Tensile Strength and Elongation[5-7] According to the experimental data of tensile test (shown in Table 2), establish the graph of relations between the austenitizing time, austempering temperature and austempering time and the tensile strength and elongation in the Origin and analyze the change rule between them.
Analysis of the above experimental data shows that when the austempering parameters are respectively 900℃, 120min, 250℃ and 180min, the tensile strength is maximum (1467Mpa); when the tensile strength is minimum (787Mpa), the corresponding austempering parameters respectively are 900℃ and 120min, 400℃ and 180min.
That’s because cast iron is brittle material, the percentage of area reduction is small.

The production of advanced high strength steels (AHSS) has been rapidly expanding in recent years as these steels allow for considerable reduction in weight and enhancement of car safety due to the unique combination of high strength, toughness and formability.
Only the data pertinent to typical HSM finishing rolling temperatures are shown.
In Fig. 2, the data for typical X80 grade and 0.16 % C – 0.8 % Mn steel are also shown; the former grade is traditionally CR processed.
Rolling temperatures, speeds and pass reductions have to be adjusted to ensure full recrystallization between the passes but at the same time to prevent grain coarsening after the rolling passes.
Then in DRCR, to avoid this situation, DRX should be completed in each rolling pass that would in turn require large pass reductions practically unachievable because specifics of rolling geometry and high deformation resistance.

To be able to process the large amounts of data, both high demands on data quality and efficient algorithms for data processing and analysis are key.
This work deals with data preparation and analysis of production data in the manufacture of aluminum rolling ingots.
Preprocessing and Analysis Data Preparation.
As data sources, casting process data have already been discretized as described in the previous section.
Schreck, Visual Data Analysis of Production Quality Data for Aluminum Casting: HICSS (2021), 1530-1605