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It has shown that energy storage functionality can be added into the composites with no reduction in the short beam shear strength.
The addition of a thin capacitive film in the center of the composite will dilute the superior properties of the carbon fiber, but this reduction will be minor due to an interleave thickness of less than 3% of the total material thickness.
Additionally, the short beam shear strength will also be measured since this will be very sensitive to reductions caused by the polymer interleaf.
The numerical data, tabulated in Table 2, shows that on average the short beam shear strength is not reduced and is consistent with the manufacturer reported values.
It has been shown that while the breakdown strength remains low due to processing, energy storage functionality can be added with no reduction in the short beam shear or tensile strength of the composite.

Choice of High-Density Products In the data-centric enterprises of today there is a need for more processing, data, and connectivity in less floor space.
Pre-Connected Products As the importance and confidentiality of data center characteristics, usually the user does not want the workers take a long time in the normal operation of data center.
And we will implement these methods to optimize university’s data center.
[3] Carrie Higbie, Data Center E-Book, 2010, pp44-48
[6] High-density data center cabling technology, http://www.cabling-system.com/,2009, 8.19

However, the results of the experimental data fitted by Langmuir-Hinshelwood equation show that linear correlation coefficient is also less than 0.90.
Fig.4 shows the fitting results of experimental kinetic data for COD removal by pseudo-first-order kinetic model, pseudo-second-order kinetic model and liquid film diffusion model.
Fig. 4 Kinetic fits for COD removal As shown in Fig. 4a and 4b, the results of the pseudo-second-order kinetic model fitting for experimental data are better than the pseudo-first-order kinetic model.
Data, Vol. 55(2010), p.4614 [2] S.
Data, Vol.58(2013). p.2248 [26] X.

A step size of 0.1 mm was used for EBSD data collection.
Also rolling direction of the specimen was maintained parallel to the beam direction during EBSD data acquisition.
Further, increase of annealing time to 180s (a multiple of 3 x 45s) led to a rapid increase in the fraction of grains larger than sub-micron size, shown with green colour data points in Fig. 2(b).
Nearly 50% of grains were of very fine size (< 2mm) when numbers of annealing repetitions, as shown by black and red data points in Fig.4, were less.
Formation of dislocations or subgrain evolution are expected to influence the local orientation of the grains and to elucidate this, an inverse pole figure analysis of the EBSD data was carried out.

The direct consequences of desertification include dramatic increase in number of dust storms, decrease in the land’s ability to produce food, increased social costs, decline in the quantity and quality of fresh water, increased poverty and political instability, reduction in the land’s resilience, and decreased land productivity [2,3].
Data analysis Statistical analysis (ANOVA with least-significant-difference (LSD) tests, correlation analysis, regression analysis, path analysis and PCA) was carried out using the SPSS 13.0 software for Windows.
Therefore, some researchers have suggested that identifying a minimum data set could provide some sensitive, reliable, and meaningful information for soil quality assessment.
Unfortunately, which basic indicators should be included in this minimum data set and how many measurements are required are still being debated.
This multivariate statistical method results in a data reduction that aims to explain the majority of the variance in the data while reducing the number of variables to a few uncorrelated components.

This paper adopts additive model of LMDI method to do a decomposition analysis on factors of carbon emissions of industrial energy consumption from 2003 to 2012 in Nanning urban area, so that Nanning could scientifically establish industrial carbon emission reduction strategy and realize coordinate development between environment and economy.
Model and Data 2.1.
Data sources and processing Industrial energy consumption data sources 2004-2013 Statistic Yearbook of Nanning.
According to the "2006 IPCC National Greenhouse Gases List Handbook"[6], the carbon emission data in each industry have been accounted, and the specific calculation formula is as follows: . (13) In the formula: C means CO2 discharge amount of consumed energy, and i is type of energy.
Among them, data of emission factors of thermal power and electric power come from the 2012 statistics of IEA[9].

Figures 3 (a) and 3(b) show the T dependence of Kab (H || ab plane), Kc (H ||c axis) and nQ for the two As sites, together with the corresponding data for x = 0 and 0.049.
These data also suggest that Ni substitution up to 4.9% does not produce significant change in the density of states at the Fermi energy N(EF).
Figure 3(c) shows the temperature dependenc of Bint, together with the data for the 4.9%Ni-CaK1144 sample with TN = 52 K.
The Kc and Kab data for x = 0 and 0.049 are from Refs. [18] and [24], respectively.
The data for x = 0.049 are from Ref. [24].

The results of the data from this study will also be useful in the development of several technologies such as composite derived from Spent Coffee Ground (SCG) because the data presented will also involve violence from a type of coffee that is given a variety of heat treatments.
During the production process, moisture content data can be collected and analyzed to help producers create better production plans that will increase yield and economic benefits [23].
In Coffea Arabica sample 4, a decrease in humidity of 0.2% was found so that in this sample the final data of humidity obtained was 0.19%.
Canophera after 1 week sample hardness test results Next is the data on Canephora coffee beans that were treated with storage in an airtight room for 7 days after the roasting process.
The data shows that roasted Canephora beans generally had lower hardness than raw beans after storage.

The simulation procedure is confirmed and verified perfectly by experimental data.
The data acquired from the test are in the form of load versus displacement that, converted to nominal stress/strain curve.
The data are employed as input data in simulation procedure and also for validation model procedure.
The results are confirmed and validated well using experimental data.
a) b) Fig. 2 Average experimental result of compression test (a) reaction force-displacement (b) nominal stress/strain The average data was calculated from three tests results and used to determine the nominal stress/strain curve for hyperelastic region (Fig. 2 (b)).

The dilatometry test provides a hardness data according to cooling curves which are used to determine the material constants (K1~K5) of QFA and the time‒temperature‒property (TTP) diagram of boron steel.
Firstly, dilametory test was carried out by the dilatometer installed with air cooling system which results in the hardness data of boron steel according to various cooling rates of 0.2 to 100℃/s.
(2) where Δt is the time step used in cooling curve data acquisition.
In order to determine the material constants in the Eq. (1), experimentally measured hardnesses data are required for the various cooling curves.
Fig. 1 shows the hardness data of boron steel.