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The formation of deoxynivalenol and fusarium graminearum can be reduced in wheat grains by ZnO NPs without any damage to grain structure [10].
It was also reported that the application of ZnSO4 and ZnO NPs increased the Zn content in grains of wheat but within the grain ZnO NPs were not detected [18].
Significant findings were reported by the application of ZnO NPs on various crop plants in terms of germination of seed, growth of the seedling, contents of total sugar, protein and nitrogen, biomass, improvements in micronutrients and efficiency of photosynthesis in the number of crop plants like tomato, cucumber, spinach, mung and wheat [16, 17].

There are number of Pressure Tubes in PHWR Nuclear Plants wherein fuel is loaded and are called coolant channel assemblies.
MICRO EXAMINATION: Grain size and microstructure to be taken for information.
Grain size were observed were 5 to 7. 9.

A lot of information can be obtained by applying X-ray diffraction analysis to the determination and analysis of the order of clusters and atomic structures, such as: radial distribution function RDF, two-body correlation function PDF, atomic density, coordination number (N), structure factor S (Q), etc., these parameters can reflect the structural characteristics of the melt.
Density [8] is related to the coordination number and interatomic distance of the melt atoms, and the influence of temperature on the melt density varies with the change of the melt structure.
Solve calculation problems through random numbers or pseudo-random numbers.
The results showed that the microstructure of Al50Mg50 amorphous alloy Many different structure types are composed of short-range ordered structural units, among which the icosahedral basic atomic cluster is its main short-range ordered structural unit and it inhibits crystallization, and the number of atoms of the cluster shows a magic number sequence. 3.2 Domestic research progress Jiang J Z [15] carried out extended X-ray absorption fine structure measurement on the K edge of liquid Zn metal at different temperatures, and further confirmed the shrinkage behavior of the average atomic bond length in the first shell of the melt when heated.
The alloy metallographic structure observation and mechanical property test show that the structural transformation makes the grain size of the alloy solidified structure significantly refined and the grain morphology tends to be equiaxed; after heat treatment, the alloy yield strength increases by about 18%, and the surface Rockwell hardness increased by about 14%.

., has been successfully developed to conduct original statistic distribution analysis Figure 1 the Signal draw sketch for single discharge of spark spectrum The relation between intensity ratio of the single discharge of elements derived from each spot and contents of elements at corresponding position can be given by: Ri = Ia,i / Ir,i = K•Ci b R Where, Ri is intensity ratio of number i measurement; Iai and Iri are intensities of analytical and reference lines of number i measurement; Ci is element content of the position corresponding to number i discharge.
D=∑Dj / N Where, Dj is apparent density of the position corresponding to number j discharge; Ci is i element content of the position corresponding to number j discharge； This method can be used in the quantitative analysis of the porosity in the materials. 6.
The sensitivity of the signals is in ratio with grain size of the Inclusion.

Similarly, Fraenkel et al explored the grain drying velocity in the tail pipe of a Rijke-type combustor [4], and found that the oscillating flow gas with a pulsating frequency of 80 Hz and with pulsating amplitude of 1500 Pa can cut down the drying time by half.
Poh et al. adopted computational fluid dynamics to investigate the characteristics of heat transfer in pulsating flow with different Reynolds number (100-1000) and with different oscillating frequency (1-20 Hz) [6], results showed that the best oscillating frequency to enhance heat transfer is different under different Reynolds number.
This finding was supported by Ji et al.’s [7] and Velazquez et al.’s works [8-9], and was extrapolated to a Reynolds number of 10000 by Elshafei et al.’s work [10].
Several works presented the relationship between the heat transfer process inside a pipe and the Prandtl number and the oscillating frequency [11, 12, 13, 14], and developed suitable models to predict the heat transfer process, results showed that there are some proper ranges of Prandtl number and oscillating frequency to enhance heat transfer, otherwise the pulsating flow has no effects on the heat transfer or downgrade the heat transfer coefficient.

In this case, all competing flows have the same max traffic rate calculated as: Bandwidth/Number.
And Bandwidth denotes the client link capacity, Number is the number of storage servers in the cluster system.
We can see that our solution can prevent the Incast collapse when the number of server increases to 128 at least.
When the number of servers increases from 32 to 128, the goodput of our solution decreases slightly from 988Mbps to 878Mbps, while it decreases from 912Mbps to 784Mbps using High Timer solution.
A., Mueller, B.: Safe and effective fine-grained TCP retransmissions for datacenter communication.

Wang, Influence of coarse aggregates’ shape index and gradation in self-compacting concrete’s rheological behavior and working performance, Concrete, 1(2011): 75-80 , At the same time, a large number of admixtures used during the production have obvious economic, social and environment benefits, which has a very wide range of applications.
Therefore, preferable aggregate grading must satisfy the following three conditions: small porosity to decrease the cement content and ensure compactness; small total surface area to decrease water demand for moisting the surface of aggregate; a small number of fine grains to meet the requirement of concrete workability.
Table 2 Properties of SCC with different aggregate grading Test serial number Coarse aggregate strategy Slump//cm T500 /s Slump flow /cm Compression strength/MPa Splitting tensile strength/MPa 3d 28d 3d 28d S1 ZCS1 24 9 61 21.7 35.6 1.71 2.28 S2 ZCS2 24 9 62 20.9 34.8 1.61 2.14 S3 ZCS3 25 8 65 23.4 37.6 1.74 2.31 As seen in Table 3, the workability of SCC can be obviously improved by choosing the proper sand percentage under the same coarse aggregate grading.
Table3 Properties of SCC with different aggregate grading Test serial number Sand percentage/% Slump/cm T500/s Slump flow /cm Compression strength/MPa Splitting tensile strength/MPa 3d 28d 3d 28d S4 45 21 11 56 22.3 35.7 1.83 2.59 S5 47 22 11 57 20.8 34.5 1.72 2.46 S6 49 21 8 59 19.8 32.7 1.68 2.16 Different from the change of fluidity of concrete mixture, the strength index of SCC decreases with the increasing sand percentage.
Table 4 Properties of SCC with different shape index* Test serial number Shape index I Slump/cm T500/s Slump flow /cm Compression strength/MPa Splitting tensile strength/MPa 3d 28d 3d 28d S8 0.3712 21 11 56 20.15 34.47 168 2.48 S9 0.3959 22 11 57 20.69 34.78 1.71 2.47 S10 0.4316 24 7 62 21.56 35.50 1.82 2.55 S11 0.4403 21 8 59 23.03 36.65 1.91 2.63 *：shape index：I＝I=∑αi×pi，αi is sphericity distribution interval, pi is the probability ofαi to total region.

The macroscopic state of the system is determined by the occupation numbers ns.
Thus the partition function form (1) could be written as      11' ' ' ' ,' 1 = exp 2 s s s ss s s ss s s s s s ns Z i n W U D D                           . (3) The additional field variables  and  describe the attractive or repulsive nature of interaction, that allows taking into account the combination of states representing different combinations of occupation numbers.
For a practical case, one always has some number of B-type particles in the A-B binary system =Bs sNn (considering a canonical ensemble).
The number of realistic interactions, for which the inverse operator can be found analytically, is limited.
It should be emphasized that this equilibrium state defined by (11) is only valid for a space-limited systems with the boundaries (grain boundaries, external free boundaries, etc.).

Metal powders and pore inducers were blended together with diamond grains for sufficient time to guarantee a homogeneous distribution of the initial materials.
Quite a number of micro-cracks distribute on the surface of base metal of the porous wheel I as shown in Fig.7(a).
Coupled with the experimental results of the grinding forces and the surface topographies of the two wheels after a certain number of grinding passes, it is shown that wheel I exhibits better self-sharpening ability because high porosity within it provides more space for debris and make the diamond grits easy to emerge in the grinding process.
This is why quite a number of micro-cracks distribute on the matrix surface of the porous wheel I after it grinded for a period of time at a higher rotating speed and bigger depth of cut.
SEM observations revealed that quite a number of micro-cracks distribute on the matrix surface of the porous wheel I while much more serious erosion o and burning on the base metal was observed on the wheel II.

, based on the principle of multi-objective planning, According to the multi-grade standards, the evaluation index can translate into measurable evaluation scores through conversion function, and then an overall evaluation is obtained according to the evaluation objects , and judge the merits based on the final score, This method is used to evaluate the object with comparison, ordering, and rarely used for classification.We have a new try to apply it to grade the risk .Calculate the maximum and minimum efficiency coefficient for each classification. to determine the efficiency coefficient demarcation point, and make the classification more reasonable. the improved evaluation steps as follows: 2.1 Set the classification standard Classification standard is the max and min value of corresponding evaluation of some category, the max limit value is the max standard of one category, and the min value is the min standard. set evaluation standard vector is Y=(y1,y2,…,ym) , classification number
is m, and standard value number is m+1, classification standard value is kj(j=0,1,2,…,m+1) 2.2 Indentify standard coefficient of standard value Standard coefficient is the level coefficient of corresponding standard value, Objectively reflect the different levels of evaluation criteria value, it is used to calculate the index of the actual value corresponds to the standard value, the standard value for each category, there is a corresponding coefficient.
Standard coefficients is represented with number ranged between 0-1 , record as λj (j=1,2,…,m+1) .Calculate formulation as follows: For efficiency index that the larger value is the better: (1) For cost-type index that the smaller value is the better: (2) In the formulation, λj is the standard coefficient; kj is the standard value; xmax is the max index; xmin is the min index. 2.3 Determine the weight of each index Entropy method is used here.
Sites dominated by coarse-grained granite bedrock, interspersed with granitic porphyry vein-in the meantime, part of the tunnel under water-rich Sandy layers, construction risk is significant. 4.2 Standard coefficient of standard value of categories In the establishment of the index system for evaluation of surrounding rock stability, span, groundwater surroundings, construction management belong to the benefit indicators, that is,the higher the value, the lower the stability of the surrounding rock, the greater the risk of collapse in tunnel.
Table 4 Comparative results of surrounding rock number individual indicators total level actual Vp depth span groundwater surroundings management 1 0.0765 0.01456 0.05537 0.0551 0.045 0.02 0.26653 II II~III 2 0.20094 0.02136 0.05411 0.1121 0.03 0.022 0.44051 III III 3 0.26979 0.01728 0.0511 0.1406 0.105 0.02 0.60377 IV III~ IV 4 0.0306 0.01256 0.05537 0.0342 0.0075 0.028 0.16823 I I Conclusions 1.