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Zhangjiakou rainfall data were analyzed for many years, the rainfall from April to October accounted for 94.10% of the rainfall throughout the year, the rainfall from May to October accounted for 87.48% of the rainfall throughout the year.
Seasonal reduction coefficient calculation often considers the comparison between the rainfall data in the months that daily temperature above 0℃ and the rainfall data throughout the year.
According to the actual monitoring data of many northern city, the water quality laws are roughly the same or similar, combined with shortage of water resources in Zhangjiakou, this paper suggests Zhangjiakou City initial abandon flow coefficient adopts 0.9.
According to the data, excluding the factors of seasonal reduction, rainwater runoff initial abandon and runoff coefficient, the average annual rainwater resources potential of this city is 8296.5 × 104 m³.
Through the analysis on the related data in study region, the calculation formulas of the storage tank capacity and annual rainwater collection are derived.

The simulated experiment shows the modeling data is fit to the field data.
And even through Gleeble press and other equipment, it is not easy to attain accurate data.
To get the resistance of deformation model using neural network technology from the field data is an attempt to solve this dilemma.
In the same time, is calculated with Eq.(9) based on the data in table 1.
A model is shown in Figure 2: Fig.2:The deformation resistance of Q235 between 1310～1360K with rolling speed 52.5m/s and reduction 35mm Compared the data in Fig.2 with available data [1], the difference is less than10 %.

When the input signal Vin = Vref, the output data is 128; Vin> Vref, the output data is greater than 128; otherwise the data is less than 128.
Data acquisition process is shown in Fig.5.
Fig.5 Schematic of data acquisition The data collection part consists of analog circuits and digital circuits.
A/D 1 continuously collects data without the external input signal.
Collect ADC data from channel 1 continuously and determine whether the value of the data acquisition and the standard signal amplitude value are consistent.

A loss of anaerobic ferric iron reduction ability has been observed in ferrous iron-grown A. ferrooxidans CCM 4253 after aerobic passaging on elemental sulfur.
The authors proposed that Fe3+ reduction is mediated by an indirect chemical reaction with H2S in the acidic medium.
The MASCOT 2.2 search engine (MatrixScience, UK) was used for processing the MS/MS data.
List of selected proteins repressed in A. ferrooxidans CCM 4253 cells unable to catalyse ferric iron reduction during anaerobic sulfur oxidation.
Hydrogenase is a membrane-bound, nickel-containing enzyme produced under anaerobic conditions that catalyses the H2-dependent reduction of quinone.

For percentage thickness reduction of 59.6%, minimum roughness 2.09μm, and maximum hardness 41.7 BHN, the confirmatory test showed values of 64.78 % thickness reduction, roughness of 2.14μm and hardness of 44.82 BHN that were in agreement with the predicted value.
Experiment parameters % Thickness reduction Roughness, Ra Hardness, BHN A B C D E 1 0.46 6.0 0.50 2000 2300 47.10 3.59 42.77 2 0.46 6.0 0.50 2000 2500 53.62 3.68 44.35 3 0.46 6.0 0.50 2000 2700 54.35 3.79 43.15 4 0.46 8.0 0.75 2500 2300 55.80 3.20 41.97 5 0.46 8.0 0.75 2500 2500 50.72 3.22 41.84 6 0.46 8.0 0.75 2500 2700 56.52 2.93 40.10 7 0.46 10.0 1.00 3000 2300 55.07 2.74 30.36 All values for the experiment varied between following ranges: 8-27 0.56-0.78 6-10 0.5-1 2000-3000 2000-2700 47.1-64.29 2.62- 7.65 32.84- 43.54 *Only first seven sample data shown in above table.
Besides, it provides an efficient solution to the uncertainty, multi-input and discrete data problem.
No Experiment parameters GRC GRG A B C D E % thickness reduction Roughness Hardness 1 0.46 6.0 0.50 2000 2300 0.4488 0.7001 0.8712 0.6734 2 0.46 6.0 0.50 2000 2500 0.5675 0.6881 1.00 0.7519 3 0.46 6.0 0.50 2000 2700 0.5847 0.6727 0.3463 0.5346 4 0.46 8.0 0.75 2500 2300 0.6224 0.7629 0.8179 0.7344 5 0.46 8.0 0.75 2500 2500 0.5078 0.7594 0.8100 0.6924 6 0.46 8.0 0.75 2500 2700 0.6431 0.8109 0.7156 0.7232 7 0.46 10.0 1.00 3000 2300 0.6029 0.3644 0.4333 0.4669 *Only first seven sample data shown in above table.
· Better ' % thickness reduction' is observed with increase in size of forming tool

Gather data on energy consumption, heat duty, reflux ratios, and operating conditions. 2.
Conduct a final energy analysis using the thermal and operational data from the EIDC system. 2.
The data collection and analysis involve four key steps: 1.
Feed data included temperature, pressure, composition, and flow rate, which are essential for simulation.
The software simulation provided the process flow diagrams and energy consumption data for the direct sequence. 3.

The displacement has been studied for three typical kinds of aluminum reduction cells (semi-graphitic, graphitic and graphitized) after 30 days start-up.
Clearly, in our country, the 350 ~ 400KA aluminum reduction cell has gradually become the mainstream, and the cell deformation increases with the higher amperage [4].
Researching the relation between the graphitization degree of the cathode materials and the cell deformation on the basis of the thermo-electric field analysis, this paper could provide the valuable data for the cell technical improvement and the development of the new cell.
Table 1 Properties of cathode materials used in the aluminum reduction cell Material Thermal expansion coefficient (10-6) Elastic modulus (GPa) Density (g/cm3) Thermal conductivity (W•m-1•K-1) Sodium expansion coefficient (10-6) M P M P M P 0.31(1.0%wt) 0.63(2.0%wt） 1.0(3.0%wt) 1.62(5.0%wt) semi-graphitic 2.8 3.5 8 6 1.56 36 30 graphitic 2.8 3.3 8 6 1.59 65 58 graphitized 2.5 3.0 7 5 1.62 110 105 Calculation of thermal field.
The displacement of the 350kA aluminum reduction cells with graphitized cathodes was measured from preheating to 30 days after startup by using mechanical displacement instrument.

The synthesis of Ag nanoparticles was carried out by chemical reduction of silver nitrate (AgNO3) with sodium borohydride (NaBH4).
Ag nanoparticles were previously prepared according to the chemical reduction method [20].
Crystallographic data obtained from Powder Diffraction File (PDF) are shown in table 1.
These results are in agreement with the previous XRD data.
The nature of the reduction reaction involves nucleation, growth and precipitation of Ag nanoparticles.

It was interpreted in terms of adsorption-coupled reduction mechanism.
At pH 1, the maximum loading capacity of Cr (VI) according to UV - spectrometer data is 3.37 molkg-1 and that according to ICPS data is 2.1 molkg -1.
At pH 2 also, the maximum capacity evaluated from UV- data is found to be 2.71 molkg -1 and that from ICPS is 2.1 molkg -1.
Because the reduction rate of Cr (VI) to Cr (III) reduction is faster at pH 1 as will be described later; the difference in maximum loading capaities evaluated from UV and ICPS measurement is greater at pH 1 compared to that at pH 2.
The removal mechanism of Cr (VI) was its adsorption followed by reduction i.e. adsorption-coupled reduction mechanism.

All the data were the average value of repeated tests for three times, SPSS20.0 was used to conduct data analysis, PhotoshopCS and Excel was used for the chart and diagrams.
Fig.2 showed with the increasing of the hydrolysis time, the reduction rate of α-lactalbumin antigen in three-groups hydrolates gradually increased.
Fig.3 showed that with the increasing of the hydrolysis time, the reduction rate of β-lactoglobulin antigen made by trypsin and flavourzyme gradually increased.During hydrolysis for the first forty minutes, the antigen of β-lactoglobulin reduced more quickly in several hydrolates, while forty minutes later, the reduction rate of β-lactoglobulin antigen became flat.
And after 40 minutes of trypsin hydrolysis, then flavourzyme was added, the reduction rate of β-lactoglobulin antigen increased more quickly.
After 60 minutes of hydrolysis, the β-lactoglobulin antigen reduction rate of three groups were 13%, 55%, 71% respectively.