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The x-ray diffraction (XRD) data show that the reduction annealing process decreases c-axis length indicating successful removal of the excess oxygen.
Moreover, some studies claimed that the O(3) can be eliminated through the “modified” reduction annealing process [11–13].
Fig. 1 also describes that there are peaks that shift to a higher diffraction angle after the reduction annealing.
Similarly, the reduction annealing also provides an effect on the R distance.
Baqiya et al., ‘Ce-Doping and Reduction Annealing Effects on Magnetic Properties of Pr2-xCexCuO4 Nanoparticles’, J.

Introduction Since the beginning of Ti alloy production in the late 1940's, Ti sponge has been produced by either the Kroll (magnesium reduction) or Hunter (sodium reduction) processes [1].
The inspection data clearly reveal the handling defects (~50µm in size, identified by arrows) against the almost zero background noise levels.
Tensile data from this material, Figure 3b, showed a 0.2% yield strength of 1035MPa, an ultimate tensile strength of 1170 MPa and a plastic elongation to failure of 7 percent, while the modulus was about 117GPa.
Highcycle fatigue (HCF) data obtained from this material is shown in Figure 3c, where it is compared to identically tested AMS 4921 Grade 4 CP Ti bar, and literature Ti-64 data [5].
The data show meltless Ti-0.9B material has a runout stress (10 7 cycles) 275 MPa greater than CP Ti, and 240MPa greater than Ti-64 bar.

Figure 1 a) Schematic of PPT experimental set-up and b) thermal decay data of surface temperature after heating over defect and non-defect areas In PPT the surface IR data is processed into phase data by using a FFT.
The current work focusses on optimising the processing of the IR thermal data into the FFT phase data to maximise the contrast between defective and non-defective regions and to ensure the repeatability of such data.
All data was collected at a frame rate of 383 Hz in order to allow maximum sampling of the decay period with enough data for analysis.
From this point the camera manufacturer’s software was used to process the thermal data into phase data.
Figure 3 Flow diagram illustrating data processing routine from thermal IR data to PPT phase data Datum location for FFT.

The latter includes two methods: sensitivity extraction and data mining methods to select attributes.
Attribute reduction makes the amount of data of the diagnosis decreased, and the purpose of shortening diagnosis time is achieved.
The algorithm uses the data points as potential cluster center and calculates the mountain function value of each data point according to calculating the distance between the data points, and determines the number of clusters and cluster centers.
Therefore, there is a characteristic parameter for each type of fault patterns. 2.2 Attribute Selection Methods in Data Mining In the real world, a large database or data warehouse data is very large, attribute selection needs to be used and process data in data mining.
Thus the attribute selection method can be selected for bearing fault diagnosis feature extraction in data mining.

Existence of a novel Hg2+ -reducing enzyme system, in which mercury resistant aa3-type cytochrome c oxidase catalyzes the reduction of Hg2+ with reduced mammalian cytochrome c or Fe 2+ as an electron donor to give Hg0, has been shown in iron-grown MON-1 cells.
There has been no reports on the mechanism of Hg2+ reduction by sulfur-grown A. ferrooxidans cells.
There has been no reports on Hg2+ reduction in sulfur-grown A. ferrooxidans cells.
The strain was able to grow on 1% sulfur medium (pH 2.5) with 10 µM of HgCl2 and with 0.2 µM of phenylmercury acetate (PMA) (data not shown). 3 Activities of Hg 0 volatilization from HgCl2 and PMA and MMC.
In contrast, the activity was completely inhibited by 1 mM of NaCN (data not shown).

The crack-closure concept has not yet been able to correlate data in the threshold regime, either from load-reduction tests at constant R or constant Kmax tests.
Fig. 1 FCG rate data at low and high stress ratio for load-reduction Fig. 2 FCG rate data for a constant Kmax and different stress ratio Fig. 2 shows a comparison of test data generated at R = 0.1 and 0.7 using the load reduction method.
However, the load-reduction test method has been shown to produce higher thresholds and lower rates in the near-threshold regime than steady state constant-amplitude data on a wide variety of materials.
Thus, the load-reduction test method does not, in general, produce constant-amplitude FCG data.
The constant R test results at 0.95 agreed well with the DKeff-rate data, while the R = 0.9 data agreed well with constant Kmax test data in the low-rate regime.

China ahanren888@163.com,bxuqiangf22@126.com,c75722279@qq.com Keywords: sheet metal forming; strain analysis; thickness reduction rate; forming limited diagram Abstract.
Then, （7） Here, is thickness reduction rate.
The average thickness reduction rate in each portion is used in correction same area method come from finite element analysis for the workpiece.
The average thickness reduction rate in each portion is taken into account in the strain calculation.
We can obtain the average thickness reduction rate in each portion through finite element analysis or experiments. 3) The data on strain obtained from the deep drawing forming experiment show that the strain curve from correction same area method is close to the experimental strain curve.

Nanjing Jiangsu China 210000 a E-mail:hh4166@sian.com b E-mail:tq19880626@yahoo.com.cn Key words: Yunnan; carbon emission; low carbon economy; influence factors Abstract:The paper uses a large amount of data uncertainty analysis of a the Yunnan "12th Five-Year" period of low-carbon development, pointed out that economic development, eliminate backward production capacity, energy consumption and energy saving will be contradictions, and the main problem of the reality of low-carbon development in Yunnan.
According to the GDP and carbon emissions data from 2005 to 2010 in Yunnan province, using the method of regression analysis, analysis the relationship between the carbon emissions and GDP in Yunnan province , and to predict the " 12th Five-Year Plan" GDP carbon emissions and its trend.
estimates Years GDP (billion) Carbon emissions (tons) Carbon emission intensity (tons / million) 2005 3461.73 11033.71 3.19 2006 3988.14 12633.91 3.17 2007 4772.52 13714.67 2.87 2008 5692.12 13813.07 2.43 2009 6169.75 15267.3 2.47 2010 7224.18 16183.33 2.24 2011 8750.95 18217.09 2.08 2012 9808.36 19546.89 1.99 2013 10993.53 21037.36 1.91 2014 12321.92 22707.95 1.84 2015 13810.82 24580.39 1.78 Energy-saving emission reduction target to calculate in the period of " Twelfth Five-Year Plan" in Yunnan Using the regression model, on the basis of data in " 2011 in Yunnan statistical yearbook ", put the GDP gross, the unit GDP energy consumption reduction rate and energy consumption of 2010 in Yunnan to the formula, obtained energy saving and emission reduction predictive value during "Twelfth Five Years Plan" ( see Table 4 ).
Table 4 Yunnan Province during the "12th Five-Year" energy-saving emission reduction estimates Index In 2010 In 2015 GDP（One hundred million yuan） 7224.18 13810.
The uncertainty about the lack of long-term mechanism of energy-saving emission reduction “Eleven five”period, China's energy saving and emission reduction for pollutant discharge standard uncertainty, especially to ensure energy-saving emission reduction economic policy flaw, caused the " 12th Five-Year Plan" energy-saving emission reduction difficult.

Carbon emission data of associated materials are obtained from PaLATE database.
The Life Cycle Cost Saving (LCCS)i% and the Life Cycle Carbon Reduction (LCCR)i%, expressed by Eq. (1) and Eq. (2) represent the percentage reduction of cost and carbon footprint while using mixture with i% of RAP rather than that of virgin mixture (0% of RAP added).
The database of PaLATE also includes carbon emission data for recycled materials and on-site recycling processes, which are not provided by other LCA tools.
The compositions of mixtures with different RAP contents (see Table 2) are calculated by an equation provided by Federal Highway Administration, Eq. (11), associated with the density data in the PaLATE.
For 40% RAP mixture, the reduction of carbon footprint is almost 30%.

To support employees in technology- and process-oriented domains, AMAG data scientists develop analytical tools for data exploration and data analysis.
High quality data and pre-processing is key to a representative, reliable data analysis result.
To ensure data is correct we strive to make data representative: It must capture the absolute maximum of information and accuracy it possibly can.
Consistency of industrial data also varies strongly.
It can be updated easily when new data is available.