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The number density of G.P. zones is defined as the volume fraction of G.P. zones divided by the average volume per one G.P. zone.
On the other hand, the tensile-stress-aged specimen reveals no significant change in the number density with t.
Fig. 1 Effect of free, compressive-stress and tensile-stress aging at 220°C on the number density of disk-shaped G.P. zones.
We selected the grains in which the stress axis was nearly perpendicular or parallel to (001)α or (100)α and (010)α of the Cu matrix, and determined the number density of G.P. zones on {001}α from TEM observations using the electron beam parallel to [110]α or [101]α and [011]α of the grains.
The number density was plotted as a function of the angle θ between the stress axis and the plane normal of the G.P. zones.

There appear to be a number of parallels between the M.D-process on stainless steels and Ni-base alloys.
δDG.B/L= The effective grain boundary diffusion coefficient of the Cr-atoms with L as a characteristic size of the structure, in this case L= δ.
(3) Grain boundary (G.B) diffusion data for Cr in Inconel 600 (73Ni-16Cr-9Fe) is available [23] and for Cr at 540°C, δDG.B=1,22×10-25m 3/s.
Sub-grain clusters are then broken off and are transformed to Ni-rich austenite by dissolution and oxidation of the Cr-carbides.
Kozma: Handbook of Grain and Interphase Boundary Diffusion Data, Ziegler press, Stuttgart, 1989

The nitridation products are fiber-like α-Si3N4 and rod-like β-Si3N4, which makes better mechanical behavior due to fiber reinforcement; a great deal of Fe3Si intermetallic compounds uniformly distribute in matrix, which is one of the products of Fe-Si nitridation and as a plastic phase forming in grain boundary optimizes the performance of products.
In order to farther improve properties of the material, a metallic plastic phase Fe3Si was introduced into the grain boundary of Si3N4-SiC composite.
Ferrosilicon powder content of all samples was respectively 6% wt, 9% wt, 12% wt and 15% wt, the corresponding sample number was 1 #, 2 #, 3 # and 4 #. 0 # was a blank sample without ferrosilicon.
Table 2 Composition of samples wt % Sample Number SiC Ferrosilicon Si3N4 additive 5-3 mm 3-1 mm 1.5-0 mm 50μm 74μm 50μm 83μm 0 10 35 20 24 0 8 3 1 10 35 20 18 6 8 3 2 10 35 20 15 9 8 3 3 10 35 20 12 12 8 3 4 10 35 20 9 15 8 3 Experimental Procedure.
The morphologies of a-Si3N4,b-Si3N4 are fiber-like and rod-like and the intermetallic compund Fe3Si distributes uniformly in grain boundary

The system was applied to a number of digital museums and achieved expectable effect.
Conclusions In order to solve the fine-grained access control in information system, the structure of the object studied the information system framework view layer and control layer based on this model and the custom tag technology.
AOP technology constructs an independent from the application logic, rapid deployment, scalable and extensible Java WEB fine-grained information system access control scheme.

With the rising of annealing temperature, the number of β-Nb phase increase while eutectic declines.
As an efficient method to refine grain and improve strength through shear deformation, equal channel angular pressing (ECAP) has been widely used in structural material.
Recent study indicates [2-3]: ECAP can both improve the mechanical property and shape memory effect of NiTi alloy by refine grain.

Han Ping has classified pests by the artificial neural network according to the voice signal of grain pest larva when they bite food in food pile, and the correct classification rate is 0.958.
Figure 3 is the training error result diagram when the node number is 11.
The number of hidden layer nodes has obvious influence on the network training in the neural network.
So the best node number is eleven.
Based on artificial neural network classification of grain pests.

Microbes from the soil at different depths were selectively determined for both culturable under aerobic condition for both their numbers by most probable number (MPN) method and morphological diversities on the culture plate and under light microscope.
After the soil samples were collected from the surface to a depth of 50 cm that had the conventional cultivation procedure for rice with four stages: before planting, during the seedling growing and rice grains harvested, there were lower numbers of cultivable heterotrophic species inferring tentative negative effects of the chemical pesticides on overall diversity of microorganisms in the soil.
More gram positive bacteria were detected than gram negative bacteria as shown in Table 1, their numbers were enumerated to be 92 + 1.9% and the numbers of these bacteria were more than those of fungi approximately 53 + 3.2 % (data not shown).
Their diversities were lower both species and numbers compared to those of the negative control without pesticide (data not shown).
It seemed that the paddy soil help numbers of bacteria remained in untreated soil for a whole depth.

Cold work caused the reduction of the number of surface cracks and disappearance of IGSCC.
The degree of grain boundary sensitization (DOS) was evaluated by means of double-loop electrochemical potentio-kinetic reactivation (EPR) method following the standard JIS G 0580, in a solution of 0.5M-H2SO4+0.01M-KSCN at 30°C.
With increasing cold work, the number of both TGSCC and IGSCC reduced.
A strong cold work, namely, large hardening may cause a screening effect through a formation of rather homogeneous distribution of dislocation and/or twin structures as a corrosive structure other than grain boundaries.
Cold work caused the reduction of the number of surface cracks and disappearance of IGSCC.

Introduction Nano-ZrO2 ceramics are promising materials for a large number of high-technology engineering applications due to their excellent properties such as high intensity, high strength and toughness and so on[1,2].
In the column "D", number "1" expresses no generator on work, and "2" x-direction generator on work , and "3" y-direction generator on work, and "4" x- and y-direction generators on work.
Table 1 The factor and level charts of test Factor Level A Working table speed (m/min) B Feed speed (mm/pass) C Depth of cut (µm) D On/off work of generator E Abrasive size (µm) 1 5 3 3 1 5 2 10 5 5 2 7 3 15 8 10 3 4 20 10 20 4 Table 2 The test data Factor Test number A Working table speed(m/ min） B Feed speed (mm/ pass) C Depth of cut (µm) D On/off work of generator E Abrasive size (µm） Ra (µm) 1 5 3 3 1 5 0.151 2 5 5 5 2 5 0.136 3 5 8 10 3 7 0.289 4 5 10 20 4 7 0.302 5 10 3 5 3 7 0.213 6 10 5 3 4 7 0.211 7 10 8 20 1 5 0.252 8 10 10 10 2 5 0.203 9 15 3 10 4 5 0.148 10 15 5 20 3 5 0.202 11 15 8 3 2 7 0.281 12 15 10 5 1 7 0.294 13 20 3 20 2 7 0.314 14 20 5 10 1 7 0.328 15 20 8 5 4 5 0.128 16 20 10 3 3 5 0.182 Table 3 Response table for means Level Working table speed Feed speed Depth of polishing On/off work of generator Abrasive
Remarkable Work table speed 3 0.0009913 0.0003304 3.74 0.218 Feed speed 3 0.0036943 0.0012314 13.95 0.068 * Depth of polish 3 0.0138752 0.0046251 52.41 0.019 ** On/off work of generator 3 0.0072523 0.0024174 27.39 0.035 ** Abrasive size 1 0.0430562 0.0430562 487.89 0.002 *** error 2 0.0001765 0.0000883 total 15 0.0690457 Table 5 The optimum of processing parameters in polishing of nano-ZrO2 ceramic factor A Working table speed (m/min) B Feed speed (mm/pass) C Depth of polishing (µm) D On/off work of generator E Abrasive size (µm) Optimal level 5 3 5 4 5 2015 105 0.28 0.24 0.20 10853 20 1053 4321 0.28 0.24 0.20 7 5 W orking table speed (m /m in） MMMM eeee aaaa nnnn ((((μμμμ mmmm )))) Feed speed （m m /pass） D epth of cut (μm ） O n/off w ork of generator A brasive size (μm ） Fig.1 Main effect plot for means From Table 4 and Fig.1, it can be seen that the influence of size of abrasive grains
Therefore, Ra and the relative constants were obtained 4.67 1 2 3 4 5 , 0.0565, 0.161, 0.172, 0.176, 1.42 K e α α α α α − = = = = = − = Substituting them into the Eq.(1), it was obtained 3 0.0565 0.161 0.172 0.176 1.42 9.37227 10 a w p R f a S W υ − − = × ⋅ ⋅ ⋅ ⋅ (4) Summary Trough Orthogonal test analysis, it can be drawn that in ultrasonic polishing nano-ZrO2 ceramics, the importance order about the influence of machining parameters on surface roughness is abrasive grains, depth of cut, on/off work of ultrasonic generator, feed speed, working table speed in turns.

Recycling scrap tires and industrial mineral aggregate have become the focus on various industries research; a large number of scrap tires arise at domestic every year and have a low recycling efficiency; Some were burned directly, which seriously pollutes the environment.
The fatigue test results of new material Test temperature (℃) Strain levels(με) Initial modulus(MPa) Terminate modulus(MPa) Accumulative total dissipation(MPa) Fatigue number of times(×105) 15 600 1345 672.5 ＞560 ＞1.400 17 600 984 492 ＞426 ＞1.701 To use the cumulative dissipated energy targets to evaluate the fatigue performance of stress absorbing layer mixture is reasonable for the trabecular four-point bending fatigue test at strain-controlled According to domestic research results[4]; the larger cumulative dissipated energy is, the better the fatigue performance is.
Materials parameter of pavements Structural layers Material name Thickness(cm) Modulus (Mpa) Poisson's ratio Density(cm/g) Damping Top layer Fine-grained type AC-13 18 1200 0.25 2400 0.9 Middle layer Medium-grained type AC-20 Under layer Coarse-grained type AC-25 Absorbing layer(no) Fly ash and rubber asphalt mixture 2 600 0.25 2400 0.9 Top base course Cement stabilization paving 58 1400 0.20 2300 0.8 Lower base course Cement lime-treated soil 0.23 Ground Compaction ground - 50 0.35 1800 0.4 Table 11.
Pavement structures of test sections Test section number I II Pavement structure combination Fine-grained type AC-13 (5cm) Cement concrete panel(22cm) Fly ash rubber asphalt stress absorbing layer(2cm) Fly ash rubber asphalt stress absorbing layer(2cm) Emulsified asphalt seal coat Emulsified asphalt seal coat The old concrete pavement and foundation The old concrete pavement and foundation Table 13.