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Moreover, the coordination number of the nearest neighbor atoms, the average distance between the absorption atom and the backscattering atoms, the amplitude reduction factor etc can be determined by EXAFS.
The high-temperature insitu EXAFS spectra of Se K-edge were fitted with the following EXAFS function [28-32] where j refers to the jth coordination shell, Nj is the coordination number of the jth shell, S02 is the amplitude reduction factor, Fj(k) is the element-specific backscattering amplitude, Rj is the average distance between the absorbing atom and the backscattering atoms in the jth shell, λ(k) is the mean free path length of photoelectron, σj2 is the Debye-Waller factor, and fjl(k) is the phase shift experienced by the photoelectron in the scattering process.
Firstly, the post-edge background was removed by using a derivative method. [28] Then the data were normalized in order to eliminate the influence of different thickness.

Despite the importance of HE in these high strength steels, there exists for example almost no data on the impact of hydrogen on TRIP steels.
For higher reductions, the low temperature peak appeared to shift to slightly higher temperatures.
Therefore, this peak should not be correlated to the reduction in retained austenite fraction during deformation but other features related to the cold deformation process might play a role.

It consisted of a setup for fixturing the TFML, a 3-component piezoelectric dynamometer (type 9119AA2 from Kistler™) connected to a charge amplifier (LabAmp 5167A from Kistler™), and a personal computer for data acquisition and elaboration via the DynoWare™ software.
On the contrary, the thrust force reduction using the spur drill bit rather than the twist one is not significant (-5% on average).
However, the spur geometry allowed for a reduction in the elastic inflection of the TFML under the drill point load when exiting the workpiece, which is known to be the main delamination cause in such workpieces [14].

The average particle size data indicate that increasing the hydrogen peroxide concentration from 3% to 6% resulted to reduction of the average particle size of the oxidized starch nanocrystals.
At lower hydrogen peroxide concentration (3%), there is around 30% reduction in size when the reaction time is extended from 1 hour to 5 hours.

70 0.9 Table2 Range analysis of the orthogonal test Factors Average A B C D E F G H NiSO4 •6H2O FeSO4 •7H2O NaH2PO2 •H2O C6H8O6 C6H8O7 •H2O H3PO3 T pH 29.33 28.11 27.33 27.44 28.56 28.11 29.89 25.67 26.78 28.67 28.89 30.00 27.56 28.78 28.22 26.78 28.44 27.78 28.33 27.11 28.44 27.67 26.44 32.11 2.56 0.89 1.56 2.89 1.00 1.11 3.44 6.44 SE dB 64.63 62.67 61.03 61.91 61.64 62.53 61.70 64.71 62.02 63.87 64.57 61.88 63.28 63.83 63.77 64.36 61.22 61.34 62.28 64.09 62.96 61.51 62.41 58.81 3.41 2.52 3.53 2.21 1.63 2.32 2.07 5.90 Note: ① means the average value of the summation of corresponding evaluation criteria when one influencing factor at the same level; ②is the range of the average value of corresponding evaluation criteria when one influencing factor at different levels: , =1, 2, 3, and . 3.1.1 Range analysis In order to evaluate the influences of the above factors on properties of the amorphous Ni-Fe-P alloy fabric, range analysis was performed for experimental data
In the process of electrical deposition, because the reduction potential of Fe2+ was lower than that of Ni2+, Ni2+ preferentially deposited, while Fe2+ participated in electrochemical reaction in the form of anomalous codeposition.
Figure 1 Effects of Fe2+/ (Fe2++Ni2+) value on coating (a) ohms per square and weight gain rate; (b) shielding effectiveness 3.2.2 Effects of the concentrations of NaH2PO2•H2O NaH2PO2•H2O, as the reducing agent, showed certain catalytic action on the reduction of to Ni.

However, the excessive use of fossil fuels for power has resulted in many negative consequences, such as environmental pollution, reduction in energy reserves in the world, and so on.
And that, fuel cells have the ability to fulfill most of the global power reduction needs while meeting the efficacy and environmental expectations.
(6) Where Cdl is the double layer capacitance Ract is the activation resistance, and the ηact is cathode activation drop. ζ1, ζ2, ζ3, ζ4 are the model coefficient, whose values are defined based on experimental data fitting.

With the development of society, people are becoming more concerned about environment protection, energy saving and pollution reduction.
With the data of time and temperature, fit the time temperature curve and obtain the curve function of high accuracy, then programmed to calculate integration.
While the concentration is 7%, super cooling degree raises to 4℃ which will affect the timely release and utilization of heat and cause the reduction of storage capacity.

As total strain amplitude increases, the fatigue life is reduced obviously, but the reduction extent depends on the temperature.
The measured data fit well with Coffin-Manson's liner relationship.
At that moment lamellar interfaces cannot play the role of hindering the crack propagation any more, resulting in drastic reduction of LCF life.

The Spring Festival shift correction method of forecasting the flow chart as shown in Fig.1 shows: January and February data correction Predict monthly coefficient The annual total load Forecast years, each month the load January and February data reduction Fig.1 The forecasting flow graph of Spring Festival shift correction method The flow chart includes a variety calculation model: 1.
Correct data for January, February.
Prediction mathematical model adopts basic data trend extrapolation techniques. 3.
The algorithm can't complete forecast, can be used as the data and trend forecasting method of data pretreatment optimization tools, increase the prediction precision.
This kind of method for special occasions forecast, some need specialized data.

Assuming there are k failure data and n-k censored data in the n samples.
Analysis of Survival Data, London: Chapman & Hall, 1984
Lawless, Statistical Models and Methods for Lifetime Data[J], New York: John Wiley and Sons Inc., 1982
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Weibull regression models for reliability data[J].