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Data getting Got the microarray data from Gene Expression Omnibus Web site (GEO database), accession number GSE1873.
The Just-RMA method was used to read microarray data into BRB-Arraytools.
All data base select Mus musculus genes as reference.
NCBI GEO: archive for high-throughput functional genomic data.
BRB ArrayTools Data Archive for Human Cancer Gene Expression: A Unique and Efficient Data Sharing Resource.

The material data for modeling kinematic hardening behavior were obtained by cyclic tension-compression tests, whilst the isotropic hardening and the yield surface parameters were acquired by simple uniaxial tension tests.
Material data identifying.
To assess the sensitivity of the simulation results to the material data, a parametric study was performed in the AutoForm R7® software on the user-defined variables.
The effect of 10-30% change in the Young’s reduction rate on the springback Fig. 8.
Besides that the Young’s reduction factor has approx. two times stronger effect than the Young’s reduction rate has, both of their impact is almost negligible, and the default parameters can be used safely for DP600.

Zinc Substituted Hydroxyapatite - A Comparison of Modelling and Experimental Data Helen Chappell1a, David Shepherd2b, Serena Best2c 1 Department of Earth Sciences, Downing Street, Cambridge, CB2 3EQ, U.K. 2 Department of Materials Science and Metallurgy, Pembroke Street, Cambridge, CB2 3QZ, U.K.
a hc263@cam.ac.uk, b dvs23@cam.ac.uk, csmb51@cam.ac.uk Keywords: Hydroxyapatite, Zinc, Density Functional Theory, X-ray fluoresecence spectroscopy, Rietveld analysis, Inductively Coupled Plasma Emission Spectrometry Abstract The effect of substitution of zinc into the hydroxyapatite lattice(ZnHA) was evaluated using experimental precipitation studies and with ab initio modelling data.
The aim of the study was to attempt to explain experimental results with data obtained from ab initio modelling in order to address the problem of low zinc uptake in the experimentally produced material.
This accounts for the reduction in the a-lattice parameter, from the phase-pure HA cell value of 9.488 Å, to 9.319 Å in cell 4.
We have also shown that the trends in lattice parameters, in particular the reduction of the a-parameter, are due to the movement of the hydroxyl ions away from the c-axis.

On the basis of X-ray diffraction data a new phase appears in the initial stage of MnO2 discharge when n*=0.6 [20].
According to other data, the homogeneity range narrows down to n*=0.5 [15].
According to chemical analysis data the reactions (5) and (4) are accompanied by a partial transfer of manganese ions to the contacting solution.
However, the analysis of the entire array of the obtained experimental data leads to the conclusion that the difference in electrochemical behavior between O and MA oxides has a different nature.
Comparing our results with the data presented in the literature one can conclude that mechanoactivated manganese dioxide reveals the electrochemical behavior similar to the behavior of γ-MnO2.

The present work aims to bring new data about the effect of alkali charge in co-precipitation preparation of Cu-Mn mixed oxide catalyst as WGSR for fuel cells.
Reduction peak of α presents the reduction of highly dispersed non-crystalline copper oxide strongly interacting with manganese oxide and that of smaller copper oxide particles weakly assisted with manganese oxide.
Reduction peak of β may be assigned to the reduction of surface copper oxide (crystalline) and subsurface Cu-Mn Solid solution (crystalline) which stronger interacted with surface oxygen vacancies.
Catalytic performance closely related to the (β+λ) reduction peak (Surface phase reduction peak and bulk phase reduction peaks closely combinated with oxygen vacancy of Cu-Mn solid solution) area.
The (β+λ) reduction peak area of catalyst become larger, catalyst had better low-temperature activity.

The selected structure also allows for flexible selection of the measuring channels, which are essential for system monitoring and data acquisition.
The adjustable parameters in this case are: · type of waveform · frequency table · number of repetitions of full periods Variables used for the implementation of the above mentioned controller were collected in a cluster representing data types [11] shown in Figure 3.
Classes of roads and their power spectral densities are defined in ISO 8608:1995 entitled: “Mechanical vibration – Road surface profiles – Reporting of measured data”.
Konieczny, Modified Clipped-LQR Method for Semi-Active Vibration Reduction Systems with Hysteresis, Diffusion and Defect Data-Solid State Data-Part B-Solid State Phenomena, 177, 10-22, 2011, Trans Tech Publ
Sibielak, Mathematical Model of a Shape Memory Alloy Spring Intended for Vibration Reduction Systems, Diffusion and Defect Data-Solid State Data-Part B-Solid State Phenomena, 177, 65, 2011, Trans Tech Publ

Measurement of Reduction in Surface Temperature.
The temperatures were monitored by thermocouples embedded in the concrete surfaces, and were recorded by a data logger at 1h interval, as shown Fig. 2 and Fig. 3 respectively.
Fig. 2 Geometry of embedded thermocouples Fig. 3 Geometry of data logger Accelerated Loading Test.
Typical meteorological weather data of summer times in Wuhan city, P.R.China were used in this research project.
The weather data on 08-August-2008 was selected for specific analysis.

Table 1 is all kinds of neuron corresponding space form data.
Feature extraction is the principle of simple calculation and separation between data of large data as sample characteristics.
And fuzzy logic can be a very good solves this problem, fuzzy logic classifier for overlap more characteristic data classification effect is very good.
Blurred logic classification implement is kind with graver overlapping data characteristic classification effect. 
The Elements of Statistical Learning: Data Mining, Inference and Prediction.

Figure 1 shows the pipeline segments later: Data Preparation Once the pipeline failure, many adverse consequences will appear.
When giving the following data, the uncertainty, integrity and simplicity of the data must be ensured.
Uncertainty is that the data noise must be less.
Knowledge discovery from data containing noise will affect the credibility of the knowledge.
Data noise will mask the true knowledge, and may influence the credibility of the final decision-making rules.

Data Stored in the Cloud Storage CRS code , the MDS erasure codes, is a code based on XOR erasure codes, whose encoding function is linear and the encoded data including data blocks and parity blocks.
The Encoded Data is Stored in the Cloud.
Then each data segment is coded by using CRS code.
For example, the data block D0 of the data segment 0 is stored in the slice 0, the data block D1 stored in the slice 1, so the data block D0 of the data segment 1 is stored in the slice 0, the data block D1 stored in the slice 1, and so on.
Research on redundant data storage based on DHT[D].