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This enhancement might be closely related to the reduction of residual stress and slightly large grain, but its resistance was not affected by the anodic polarization behavior.
Some data showed that there is a similar effect of caustic concentration and temperature on the cracking of mild steel and Type 304 and 316 stainless steels [4].
The enhancement of the SCC resistance as shown in Fig. 1 and the reduction of susceptibility to SCC were not explained by these microstructural changes.
Variation of residual stress of anodic polarization curves of S32050 S32050 with thermal treatment By the experienced data [8] of nuclear power plants, it was reported that SCC problems were reduced largely as the grain size of Alloy 600 or Alloy 690 was increased.
This enhancement might be closely related to the reduction of residual stress and slightly large grain, but its resistance was not affected by the anodic polarization behavior.

The VS of treated specimens has a more significant reduction than EMC and WA when the heat treatment temperature is above 180℃.
Based on the testing data of mass and dimension for samples under different conditions, the moisture content (MC) and volume swelling (VS) can be calculated as an index of moisture performance and dimensional stability properties according to the formula below: (1) (2) where and are the weight and volume of specimens under different conditions, and are the weight and volume of oven-dried specimens.
This may be the main reason contributing to the reduction in water absorption of heat treated wood.
The VS of treated wood has a more significant reduction than EMC and WA when the heat treatment temperature is above 180℃.
Quality control of thermally modified timber: interrelationship between heat treatment intensities and CIE L*a*b* color data on homogenized wood samples.

On another matter, the decreasing intensity of ‒OH group at 3400 cm–1 region indicated ‒OH as reduction group to reduce Au(III) ions into Au(0).
Stereo-microscope was used to confirm the presence of Au on the adsorbent surface after adsorption-reduction process.
This data supports the previous data of adsorbent morphology after adsorption.
Ohto, K.Inoue, Polymerization of phenol derivatives by the reduction of gold ions to gold metal, React.
Sudiono, Adsorption kinetics of adsorption-reduction of Au(III) on humic acid from Rawa Pening peat soil, Pharmaciana 3 (2013) 15-22

The related data are shown as the following Table 1-3.
Table 1 Simulative Data about the Relationship between the Organization Centralization and Project Complexity Organization Centralization Time of Simulation The Implicit Workload Project Complexity Rework Coordination Waiting Total High 823.5d 22836.5 53409.1 32759.3 109004.9 0.757 Medium 800.2d 17798.7 51273.0 21061.4 90133.1 0.626 Low 760.0d 11010.7 45092.5 7409.0 63512.2 0.441 Table 2 Simulative Data about the Relationship between the Organization Normalization and Project Complexity Organization Normalization Time of Simulation The Implicit Workload Project Complexity Rework Coordination Waiting Total High 769.0d 11376.9 20234.5 9823.7 41435.1 0.288 Medium 800.2d 17798.7 51273.0 21061.4 90133.1 0.626 Low 1039.6d 36360.0 101252.2 25033.3 162645.5 1.129 Table 3 Simulative Data about the Relationship between the Degree of Organization Matrix form and Project Complexity Degree of Organization Matrix form Time of Simulation The Implicit Workload Project Complexity Rework Coordination
Besides the waiting workload has the most drastic reduction among the implicit workload while the rework workload and coordination workload have much less reduction.
The data are shown as the following Table 4-6.
Table 4 Simulative Data about the Relationship between Team Experience and Project Complexity Team Experience Time of Simulation The Implicit Workload Project Complexity Rework Coordination Waiting Total High 784.5d 17186.9 35834.6 18549.6 71571.1 0.497 Medium 800.2d 17798.7 51273.0 21061.4 90133.1 0.626 Low 834.4d 19222.1 72966.0 21160.0 113348.1 0.787 Table 5 Simulative Data about the Relationship between Functional Mistakes and Project Complexity Functional Mistakes Time of Simulation The Implicit Workload Project Complexity Rework Coordination Waiting Total 0.0 751.2d 6058.2 30515.7 1354.0 37927.9 0.263 0.1 800.2d 17798.7 51273.0 21061.4 90133.1 0.626 0.2 840.4d 27006.8 55351.8 38372.1 120730.7 0.838 Table 6 Simulative Data about the Relationship between Working Experience and Project Complexity Working Experience Time of Simulation The Implicit Workload Project Complexity Rework Coordination Waiting Total High 793.4d 17939.7 47174.0 15812.6 80926.3 0.562 Medium 800.2d 17798.7

Two main fibre effects were observed: a significant reduction of irreversible strains when the specimens were loaded and then heated and cooled and a different evolution in LITS passing from 200°C to 400°C, characterized by a significant reduction of the expected deformation.
In order to support high temperatures without loss of data acquisition, the displacements were measured with three LVDTs placed outside the oven and not subjected to high temperatures.
In general, a better prediction was achieved with the introduction of the reduction factor.
From the experimental results, one can notice that the curvature of the experimental LITS compliance (JLITS) curve is modified after 200°C (reduction of LITS growth rate).
· The curvature of the experimental LITS compliance (JLITS) curve is modified after 200°C (reduction of LITS growth rate) and this could be an effect introduced by steel fibres.

The developed chip serration model shows good agreement with experimental data.
Investigations into the causes of chatter and its subsequent avoidance or reduction is therefore of utmost importance.
Thus, a damping technique, for instance magnetic damping from tool side to dampen tool holder vibration, will reduce chatter and this reduction should show up in the chip serration.
The data acquisition system comprised an accelerometer (Kistler 50g), for vibration data acquisition; a Dewetron module, for signal conditioning; and a National Instruments DAQ card (model: PCI-6023E), for interfacing with the Dell workstation.
Fig. 4: Photograph of the magnet setup Fig. 3: 3-D Catia model of the special fixture Response Surface Model A 3 factors 5 levels simple CCD model was developed in RSM using DOE software to model chip serration frequency from empirical data.

The concentration data is collected by per second.
Fig. 2 Sensors regulating device unit Data Acquisition and Processing The acquisition of emission test data is the key to the whole test, and the experimental data to be recorded simultaneously with OEM-2100 include gas emissions data, GPS system detects road operational data, engine technology, operational parameter data.
By the compiled Visual Basic program, the text format data in Microsoft Excel will be converted data easy to read and statistical analysis, thus achieve the improvement and match of the data.
The GPS vehicle operating data were corresponded to the table through the time difference between the two instrument, using the latter second of speed data to reduce the previous second of speed data obtains acceleration data of every second in the vehicles operating.
By the above data processing, the initial test GPS and OEM-2100 real-time data can be obtained from the experiment, through the vehicle speed with the engine speed changes, and eventually to obtain emissions data and vehicle operation data database established after fitting.

The dynamical data fit very well with the pseudo-second-order kinetic model and the calculated adsorption capacities (23.98, 24.33 and 24.81 mg/g) were in good agreement with experiment results at 20℃, 30℃ and 40 ℃ for the 100 mg/L Cr(VI) solution.
The Freundlich model (R2 values were 0.9198-0.9871) fitted adsorption data better than the Langmuir model.
These results have shown that the experimental data do not well agree with the pseudo-first-order kinetic model.
In the present study, the equilibrium data of the adsorption of Cr(VI) onto the GPC at pH 4.0, 6.0 and 8.0 were fitted with the Langmuir equation and the Freundlich equation.
Conformation of the experimental data into Langmuir isotherm model with high R2 value indicates the homogeneous nature of the adsorbent surface.

Senanayake et al give new data for Fe(Ni,Co)OOH and limonitic ore [6].
The reduction process can not transform all of iron oxides to FeNi or Fe because it is lack of coal.
Forssberg; Effects of Mechanical Activation on the Reduction Behaviour of Hematite Concentrate; Int.
Dikeç; Reduction of iron ore pellets with domestic lignite coal in a rotary tube furnace; Int.
Pugaev; Reductive Acid Leaching of Laterite and Metal Oxides – A Review with New data for Fe(Ni,Co)OOH and a limonitic Ore; Hydrometallurgy; 2011; 110:13-32 [7] M.

Our country is not liable for legally binding emissions reduction of the task at present, but the government has taken measures to deal with the greenhouse effect.
Based on emission reduction requirements about carbon intensity and energy intensity in 12th Five-Year Plan about the case of urban agglomeration and survey data, combined with the optimization model in this article, the net carbon emissions of the urban agglomeration area is 1.90×107t in 2015 solved by LINGO software.
Carbon intensity of the urban agglomeration "core area" in the case in 2015 reduces by 40.00% compare with those in 2010, it is higher than the national requirements which set greenhouse gas emissions in 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission and the proposed carbon intensity decreased by 18.00% requirements in the twelfth five-year plan for the urban agglomeration in the case; at the same time, the optimization scheme (Table 2) reveals that carbon area of forest land, garden land, grassland have increased, improved the "core area" of carbon absorption ability, and the optimization plan of energy consumption is also meet the emission reduction targets which in 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission and the urban agglomeration plan, it have down 41.86%, by pay attention to the emission reduction of carbon intensity and energy consumption, the GDP of the actual area in "core area" will reach 63 million Yuan, which can accounts
Fig.  1 The proportion of different energy consumption in the case of urban agglomeration: (A) for 2015 and (B) for 2010 Conclusions Reducing carbon dioxide and other greenhouse gas emissions is an important goal to build a low carbon city group, using minimum net carbon emissions of the urban agglomeration area as the optimization objective, considering many factors such as carbon sources and carbon sinks, combines with a city group regional planning and using the energy consumption, carbon sink area of urban agglomeration in 2010 as the base period data, this paper predict the economic growth, energy consumption and land carbon sink area of urban agglomeration at the end of 12th Five-Year Plan.
This optimization model not only meets the greenhouse gas emission reduction requirements in 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission, but also completes the greenhouse gas emission reduction targets proposed by the urban agglomeration in 12th Five-Year Plan.