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Recent progress in wind technology has led to cost reductions to cost levels comparable, in many cases, with conventional methods of electricity generation[1][2].
The IEC61400-1 standard definitions turbulence intensity is ratio of the wind speed standard deviation to the mean wind speed, determined from the same set of measured data samples of wind speed, and taken over a specified period of time [3].
These data are also essential to select the WECS in order to maximize efficiency and durability.
All these data are usually arranged in a histogram.
Based on the data above, the air density increases from 1.1kg/m3 and 1.225 kg/m3, which increased 11.4%, there are differences on different coordinate systems.

Furthermore, it delivers key input data for the nucleation and growth models required for precipitation simulations.
In order to evaluate the energy dissipation, diffusion mobility data are thus required.
For accurate reproduction by kinetic precipitation simulation using ME-Ni databases [9], the evaluated thermodynamic equilibrium solvus needs to be close to the experimental data.
Evaluations of γ´ solvi with ME-Ni lie close to experimental data for a large variety of alloy compositions and temperatures, as shown in Fig. 1.
Thermodynamic modeling, taking into account phase diagram data of stable phases as well as first-principles results of metastable structures [19], employed in kinetic precipitation simulations, adds the suggestion of stable S-phase.

Figure 3 shows the experimental data of the packing density, which was approximated by the relative density for the specimens fired at 1073K, after binder removal.
Calculation of the packing density by Eq. (1) with the data of ρm and ρc is also demonstrated in Fig. 3 for some values of H.
The values of H determined from the data are plotted in Fig. 4.
The obtained data on S and E is plotted in Fig.7 with error bars, where the values of b and c are listed in Table 1.
S and E for X=0.8 of Compact A at 1579K were omitted from the data because the error was too large to settle them.

Results and Discussions La:Ba:Cu (1:2:3) system: The X-ray data of the obtained product shows a new type of compound.
X-ray powder diffraction data was indexed using similar unit cell parameters.
As it was seen from the unidentified data there are lots of distortions.
In the IR data there was very weak bands of La-O around 500 cm-1 (Fig.3).
The other elements as expected were observed in the EDX data (Fig.5).

The Comparative Analysis of Energy Saving and Emission Reduction of Cogeneration and Separate Generation of Heat and Electricity Conditions of Comparison.If the annual heat and electricity generation of this project are produced respectively by cogeneration and separate generation of heat and electricity, according to the conditions and results in 2.4, the power generation efficiency of separate generation is 22.51%, the heating efficiency is 80%, and the annul operating time is 7000h.
Table 4 Coal consuption and pollutant emission of cogeneration and separate generation System Project Cogeneration Pure electricity generation Pure heating Standard coal onsumption [t] 114625 95495 20600 Coal saved by ogeneration [t] 1470 Annual SO2 emission [t] 201.74 168.7 36.256 Annual SO2emission reduced [t] 3.216 Annual NOX emission [t] 453.91 387.16 81.576 Annual NOX emission reduced [t] 14.826 Annual dust emission [t] 2.957 2.464 0.531 Annual dust emission reduced [t] 0.095 Analysis and Conclusions.According to data from the above table, we can conclude that congeneration can save 1470t standard coal compared to separate heat and electricity generation, and the energy saving effects are significant.
The following are data based on the practical operating conditions of straw power stations, which can be used to evaluate the economical benefits of cogeneration and pure electricity generation.
With the analysis of data of energy saving and emisison reducing of cogeneration under winter and summer working conditions, cogeneration has an advantage in aspects of theraml economy as well as energy saving and emission reducing compared to pure heating and pure electricity generation.
Area and Total Output of Corp Plantation of Jilin Province. data center of Chinese net work of grain, 2011-5-13 [2] Luo Jun.

For solid-state lighting applications, natural white light suitable for illumination from a single emitter layer is incredibly imperative, which makes the device structure less intricate and evades the problems of self-reduction and color variability that occur in multiple emitters [5].
The single-crystal X-ray diffraction data (SCXRD) were collected using a Rigaku Saturn 724 diffractometer on a rotating anode (Mo-Kα radiation, 0.71073 Å) at 170.01(10) K.
The detailed crystallographic data is shown in Tab. 1.
Tab. 1 Crystal data and structure refinement for TMGPbCl3 Empirical formula C5H14Cl3N3Pb Formula weight 429.73 Temperature/K 170.01(10) Crystal system orthorhombic Space group Pbca a/Å 7.8396(2) b/Å 18.6844(4) c/Å 32.3085(7) α/° 90 β/° 90 γ/° 90 Volume/Å3 4732.49(19) Z 8 Density (calc)/g·cm-3 2.413 Absorption coefficient/mm-1 14.896 F(000) 3168.0 Crystal size/mm3 0.3 × 0.25 × 0.1 Radiation MoKα (λ = 0.71073) 2Θ range for data collection/° 4.36 to 62.26 Index ranges -10 ≤ h ≤ 10, -27 ≤ k ≤ 19, -45 ≤ l ≤ 36 Reflections collected 29899 Independent reflections 6535[Rint = 0.0339, Rsigma = 0.0334] Data/restraints/parameters 6535/0/225 Goodness-of-fit on F2 1.043 Final R indexes [I>=2σ (I)] R1 = 0.0374, wR2 = 0.0827 Final R indexes [all data] R1 = 0.0585, wR2 = 0.0894 Largest diff. peak/hole/e Å-3 2.08/-1.85 Fig. 1 The synthesis and structure description of TMGPbCl3.

After 30 days of degradation the PGA nanofiber disappeared (data not shown).
The nanofibers disintegrated from 10 days and completely disappeared after 20 days (data now shown).
Broken nanofibers were observed after 25 days of degradation with and without cell culture (data not shown).
However, the nanofibers underneath the cell culture seemed to remain unaffected (data not shown).
PLGA degradation without cell culture was continued until 120 days when it broke into pieces (data not shown).

Fig.1 Filling with water movement of air bag structure experiment device Water movement of test monitoring devices In the experiment, TS-3 type of soil moisture movement parameters to be automatic acquisition system information, of filling structure model of different depth water potential, moisture content, conductivity, temperature, humidity and other parameters of the digital signal continuous monitoring, and by using the computer system to collect data.
Software is moisture movement monitoring control system, the main functions: parameter setting, data acquisition, and data display menu functions.
Water movement of test monitoring devices In the experiment, TS-3 type of soil moisture movement parameters to be automatic acquisition system information, of filling structure model of different depth water potential, moisture content, conductivity, temperature, humidity and other parameters of the digital signal continuous monitoring, and by using the computer system to collect data.
Software is moisture movement monitoring control system, the main functions: parameter setting, data acquisition, and data display menu functions.
Fig.3 The water potential curves of the soil-fly ash unsaturated zone The vertical distribution of the law The figure 4, filling structure with the water bag gas model in vertical direction of the reduction of has a distinct trend, soil and water potential of filling material with depth, the increase gradually reduced, but the attenuation rate by temperature, humidity and other factors, the change of the water there are some differences. 0 ~ 10 cm of surface soil of the influence of air flow are the most obvious, soil moisture be lost faster, the linear decrease water potential basic trend; 10 cm ~ 25 cm soil layer of the relative to the attenuation trend surface soil relatively slow, the water in 120 cmH2O keep within the scope of the following; 40 cm below and soil and filling layer material from the evaporation almost effect, but the pore water through the capillary tiny capillary channel supplies the upper of soil water, making the water almost no change.

The data collected from this technique were used to calculate the specific surface area (SBET), micropore surface area (Smicro), mesopore surface area (Smeso), micropore volume (Vmicro), mesopore volume (Vmeso), total pore volume (Vtotal) and average pore diameter (Dp) of the ACMs by using the standard methods [14].
The nitrogen adsorption-desorption isotherm data, shown in Figure 1, for the ACMs, exhibit a typical shape of curve for porous carbon material, which is in general an evident for evaluating the existence of micropores and mesopores in the material [15].
Nitrogen adsorption-desorption data for ACMs.
The CV data (not shown here) recorded at the scan rates from 1 to 100 mV/sec for all the ACMs cells were further analyzed by estimating the values of specific capacitance from these data using a standard procedure [16].
Rouquerol, et al., Reporting Physisorption Data for Gas / Solid System with Special Reference to the Determination of Surface Area and Porosity, Pure Appl.

Based on searching and read related domestic and foreign vatious database( mainly include Wangfa data resource system, Weipu China technology journal, SCI, EI Vilage, Elsevier, EBSCO, Cell Press etc.), we find that though there are some researches on the environmental management level evaluation index system, like Chen Yaobei, Wang Xueqin [1] according to the frame model theory “ driving force—state- response”, constructs the regional environment management index system frame from the angel of the environment management process, and put forward the level standard of regional environmental management evaluation model and environmental level of management evaluation index, and they take the Chongqing district as an example.
Factor analysis is done based on the survey data which optimization the evaluation index of regional industrial focus areas of ecological environment, and build a relatively complete evaluation index system of the regional industrial focus areas of ecological environment, the detail structure is as table 1.
Through a variety of measurement and calculation, comes the first level index weighting A, second level weighting Ai and some related data of membership rijk ( K=1, 2, 3, 4, 5) .
According to the data, we can get the following data, A=(0.31, 0.29, 0.40), A1=(0.23, 0.23, 0.27, 0.13, 0.14), A2=(0.05, 0.10, 0.10, 0.10, 0.05, 0.25, 0.05, 0.05, 0.15, 0.05, 0.05), A3=(0.11, 0.10, 0.09, 0.08, 0.12, 0.10, 0.14, 0.06, 0.10, 0.04, 0.06).
Third, continue to increase the supervision of the energy-saving reduction, improve the regional ecological environment management service ability, improve the management level of Hengyang lead and zinc industry environment, practically apply saving, low carbon economy and circular sustainable development mode to the production process of lead and zinc enterprises.