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The reduction of TOC might be due to the P. putida has used carbon as an energy source using their metabolic process throughout the microbiological process in order to degrade, break down or transform hazardous contaminants [12] in samples to less toxic or nontoxic forms.
This indicated by the reduction of nitrogen in the sample of B20.
Throughout the experiment, the sulfate was used by P.putida to perform its microbiological process and result in reduction of sulfate in the sample of B20.
In this study, the phosphate was possibly used by P. putida to perform its microbiological process and result in reduction of phosphate in the sample Fig. 6 Result of phosphate in 24 days Table 1 Summary of the physico-chemical results Parameter Sample Standard Reference Soil + B20 + P. putida (Day 0) Soil + B20 + P. putida (Day 24) pH 7.45 7.25 6-7.5 [14] Total organic carbon (%) 0.0332 0.030 0-0.05% [15] Total nitrogen (ppm) 34.17 6.05 5-15 ppm Sulfate (ppm) 21.52 18.00 5-20 ppm Phosphate (ppm) 1.29 0.275 0.5-0.9 ppm Moisture content (%) 44.11% 50.35% 40-60% [16] Conclusion Based on the obtained data it can be concluded that P. putida is an effective microorganism and suitable as oil-soil biodegradable agent.

With respect to hot working, the fracture mechanisms domains agree in general with what is observed; however, the data is insufficient to confirm it totally.
Complimentary data on 304 [77,294], 321 [23], 316 [294a], T1 [60] and 304 in tension [29].
Published 304W data under similar conditions have been added [186,187].
However, the data for FeCrNi12 at 1200°C, FeCrNi9 at 900°C and FeC6.5 at 650°C are for various compositions [30,278].
It is remarkable that so much of the data fall in the band between FeCrNi12 and FeCrNi9 despite the wide variations in phase shape, distribution and composition [276].

Based on the experimental data and regression analysis method, the mathematical model of the critical strain of Cr4 steel is constructed.
The critical strain model provides data support to predict the dynamic recrystallization during Cr4 heavy supporting roller hot forging process.
From the data of the table 1, it can be seen that at a certain strain rate, the peak strain decreases with the increase of deformation temperature.
Base on the thermo-simulation experiment data which listed in table 1, the constants,,can be calculated by the regression analysis method using the data analysis and graphing software OriginTM.
（3）Based on the experimental data and regression analysis method, the mathematical model of the critical strain of Cr4 steel is constructed.

A critical comparison between experimental data and results of a 3D CFD analysis of the combustor is discussed.
The results of numerical analysis are in good agreement with experimental data as concerns CO emissions, while overestimate NO production in the diffusive flame region at 50% load.
A critical comparison between experimental data and results of the CFD analysis of the combustor is discussed.
The detailed facility layout, the gas turbine control and monitoring system, the data transfer system and the diagnostic measurement equipments are described in [2].
Fig. 4, Gaseous emissions experimental measurements and CFD results at different loads Figure 4 summarizes the comparison between the experimental data and CFD results concerning the main gaseous species at the exhaust at the different loads.

The ductile to brittle transition temperature (DBTT) is shifted to higher temperatures with phosphorus additions accompanied by the reduction of the upper shelf energy (USE).
Steel Fe C Si Mn P S Ni Cr Cu 1 Balance 0.18 0.16 1.55 <.003 0.0014 0.64 0.16 0.03 2 Balance 0.18 0.15 0.53 <.003 0.0011 0.64 0.15 0.03 3 Balance 0.18 0.16 1.53 <.003 0.0011 0.63 0.15 0.30 4 Balance 0.18 0.16 1.52 0.33 0.0030 0.65 0.16 0.03 5 Balance 0.18 0.16 1.55 0.25 0.0034 0.65 0.16 0.30 The data were curve fit using a hyperbolic tangent function of the form: E= a + b tanh [C (T - d)] where E is the absorbed energy (J), a, b, c are constants, d = DBTT, a + b = USE, T is the temperature (K).

The alloys have been unidirectionally hot rolled to 80 % reductions at 800ºC and air cooled.
From the pole figure data, the complete orientation distribution function (ODF) plots have been calculated with triclinic sample symmetry [12].

The approach to total weight reduction has been a key issue for car manufacturers as they cope with more and more stringent requirements for fuel economy.
The cause of the mismatch with the experiment in the detailed sheet thickness of the analysis concerns correction of the die, which was not performed in the data used to make products. and the real ironing rate vs. the ironing rate in the analysis. 　　 　　 　　

The experimental electrochemical impedance data were fitted to the electrical equivalent circuit by CNLS Levenberg – Marquardt procedure using ZView – Scribner Associates Inc. software.
From chronoamperometric graphical data we can conclude the following aspects: - potential range in which the only process occurs in studied system is SO32- ions anodic oxidation depends on Na2SO3 concentration added in alkaline solution.
In order to describe the SO32- ions oxidation process, the experimental impedance data were fitted to the electrical equivalent circuit presented in Fig. 12, using a complex non-linear least squares (CNLS) procedure. .
Conclusions The results presented in this paper represent a full characterization of the electrochemical oxidation process of sodium sulphite in alkaline media on skeletal nickel based 6 layer platinum nanoparticles electrodes, correlating cyclic and linear voltammetry data, kinetics data of electrode process obtained from Tafel method and EIS with chronoamperometry, chronopotentiometry and chronocoulometry data.
In the studied potential range, the process is controlled by charge transfer step, as confirmed by EIS data.

In this work we have used NASGRO Version 3.0 models of AL2024-T351 fatigue crack growth due to its ability to capture data trend in all three regions of the da/dN-∆K curve [18].
The actual values of Reff seen at the StressWave TM cold expanded hole can be as low as -3.3 but data for such low R values is not available in AFGROW so the parameter Rlo is needed to ensure that the value of R used is never outside the NASGRO da/dN-∆K curve data set which only exists for 0.1 ≤ Reff< Rlo = - 0.3.
As can be seen from the data in Figure 2 good agreement with experimental fatigue life can be obtained when Rlo = - 0.3.
Firstly it can be noted that the agreement between the experimental data and the AFGROW prediction for the unexpanded hole is truly excellent.
Values of R in this case are all within the NASGRO data set so Rlo did not affect the outcome and was set at -0.3.

Under the control of interface program, the module can automatically execute and transmit data.
The second is how each basic module matched with the transmission scheme is automatically called and the relative data are automatically exchange.
The main functions of tolerance database maintenance modules are: editing the data of tolerance databases in order to meet the need of continuous renewal national standards.
The core codes are: for x=1 to jishu Ichuan(x)=val(txtfenpei(x-1).text) next x 2) Implement calls and transmit data step by step Sequential calls and data transmission program flow chart N-S [4] is in Figure 5.
Random module names and file names are generated in order to correctly call modules and transmit data.