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This effect is not attributed to a better efficiency of the oxide scales but rather to the reduction of the niobium solid solution fraction with tin additions.
The crystal structure of each compound was identified by matching the characteristic XRD peaks against JCPDS data.
The addition of tin has also several effects on the compositions of the MASC constitutive phases: - First, EPMA data (Figure 2) shows that tin additions modify the solubility of the other elements within the (Nb,Ti)ss.

The Eu 3+ ions are incorporated into the garnet phase, as is suggested by the lattice parameter value being larger than that in literature data (homogeneous strain).
Dots are experimental data points; full lines are result of the fit.
The data presented in Table 1 also show that the average crystallite size increases while the lattice disorder apparently passes through a maximum for intermediate thermal treatments and then decreases.
From the reduction of the cubic garnet lattice parameter caused by an increase of the thermal treatment, it has been inferred that the mechanism of segregation of the Eu atoms from the YAG matrix is probably because of the effects of immiscibility.

Such procedure may yield very different results depending on the hardening law fitted to the experimental data.
Since the pre-necking data is readily available from a standard tensile test, the usual way to estimate the post-necking hardening behaviour is by fitting a hardening law to the experimental data (which is available before the point of maximum uniform elongation).
On the left side of this figure the results are shown for the material data obtained by the extrapolation method (EM).
Unlike the material behaviour obtained through inverse modelling and the PNTE, the hardening laws are not forced to match experimental data at higher plastic strains since they are fitted to the available pre-necking data.
The most obvious discrepancies with the experimental data are situated in the ring groove of the die and the interlock region.

In this paper, we propose a novel approach for prolonging the lifetime of the wireless sensor network by minimizing the consumed nodes energy due to the data routing, in order to continue to provide measurement functions or data routing.
Transmitting data to the sink is achieved based on a broadcast of a hello_sink message; 2.
After choosing the routing path, the source node starts sending data packet by packet.
Data transfer details between the nodes S and D.
Data transfer details between the nodes S and D for each path.

Table 2 Test Results of fabric property Sample number Test Index Drape coefficient (%) Specular Gloss (%) Gas Permeability (L/m2·s) Immediate elastic (%) Delay elastic (%) 1 62.64 2.12 439.8 127 136 2 62.37 1.90 457.9 134 146 3 59.19 1.86 475.1 143 153 4 56.31 1.81 486.3 159 166 5 52.50 1.61 533.0 163 168 6 45.46 1.71 1396.0 151 165 According to the measured data in Table 2, based on unitary linear regression principle [2], the SPSS (statistical software) was used to make linear regression analysis of the relationship between fabric properties and filament number of samples 1 to 5.
Table 3 Linear regression equation form of fabric performance and filament number Performance Regression equation Pearson coefficient Drapability y=-0.0846x+64.489 0.9664 Gloss y=-0.0033x+2.0927 0.8250 Gas Permeability y=0.6855x+430.71 0.9376 Immediate elastic y=0.2970x+124.53 0.9020 Delay elastic y=0.2493x+136.45 0.8447 From the regression equation in Table 3 and comparison of the performance of sample 6 in Table 2, we can see that: •When dpf of FDY polyesters ≤ 0.2467dtex, the silk-like drape effect could be obtained; •When dpf of FDY polyesters≤ 0.4784dtex, the silk-like luster could be available; •When dpf of FDY polyesters≤ 0.0272dtex, the silk-like permeability could be got, and at present to get such a fineness of filament need not only high technology, but also higher costs, so a reasonable choice of dpf and caustic reduction processing were used to improve the permeability of fabrics in the design of the fabric; •When dpf of FDY polyesters≤ 0.6235dtex, the silk-like immediate

Introduction Along with the concept of sustainable transportation put forward, energy saving and emissions reduction in railway system are receiving more and more attention [1].
The line data [5] is depicted in Fig.1, distance is 4500m，upper slope is 1‰, distance is 9000m, lower slop is -1‰, distance is 4500m, slope is 1‰ upper, distance is 1600m.

Introduction Many structures may not be subjected to strong earthquake in the using period, many well-detailed structures possess significant reserve strength and capacity to dissipate energy, seismic load of structure is larger than designed seismic load, it is uneconomic to design complete elastic structure subjected to the stronger seismic load. [1]In advanced seismic design, structure subjected to strong seismic force are allowed to plastic and taken advantage of the fact that the structures possess ductility, dissipate energy and overstrength, design seismic load of fortification earthquake is permitted a reduction by seismic response modification factor (R) and seismic response is computed by elastic analysis, structure displacement of elastic analysis is magnified by displacement amplification factor (Cd) to estimate the max elsto-plastic displacement.
The enclosure area of capability curve and polygon line is assumed as A0, Ke is the initialization stiffness from the elastic data of capability curve; Ke （4）（5）（6） (3) Capability Spectrum Method.

Due to the effect of wool anti-felting is not satisfied by using protease alone, to enhance the reaction between protease and wool and improve wool anti-shrink effect, various oxidation pretreatment and reduction pretreatment are adopted [2].
Going through the data [3] and experiments, the main influence factors of oxidation pretreatment effect were found, which were pH value, concentration of hydrogen peroxide, processing temperature and time.

The specimens were prepared by casting into rod ingots and then drawn into wires with a diameter of 1mm and a sectional reduction of 90%.
All data procssing was conducted by the use of Origial 7.0.

Comparison of mineralogical composition of all samples before bioleaching and after bioleaching (data not shown) showed destruction and release of smectite, kaolinite, illite and goethite.
The results of the bioleaching serve as a starting point for improvement in microbial fermentation techniques by the application of chelators during speeding up of reduction and dissolution of iron from non-metallics.