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Precipitates with various sizes are homogeneously distributed in the grain as well as the grain boundaries.
It was suggested that the grain size could be controlled by the SPP size and volume fraction due to the interaction of the grain boundary with the SPPs in both binary alloys [9] and ternary alloys [12].
(a) (b) (c) Fig. 1 TEM microscopy and grain size of (a) Zr-1Nb; (b) Zr-1Nb-0.2Fe; (c) Zr-1Nb-0.4Fe alloys.
All the alloys tested in this study exhibited the transition behavior in the corrosion kinetics although the transition time and transition number were different depending on the alloy composition.
The grain sizes in the alloys were similar and the effect of grain size on corrosion was small, so the different corrosion behavior should be resulted from the different SPP characteristics.

Fig. 3 Two-dimensional element distribution of Nd impurity in Tb metal Table 3 Analytical date of Nd impurity by LA-ICP-MS in Tb metal Sample Number No. 1 No. 2 No. 3 No. 4 No. 5 No. 6 No. 7 Average relative intensity(IE/ITb×10-4) 5.77 5.76 5.7 5.74 5.76 5.76 5.78 Relative standard deviation (RSD) (%) 14.04 14.93 15.16 14.84 15.16 15.32 15.48 Average concentration(ppm) 3.49 2.39 2.26 2.51 2.54 2.54 2.37 Based on the binary phase diagram of Nd-Tb system [9], there is no inter-metallic compound formed in the rich-Tb region, and the melting point of Nd being 1024℃ is lower than the re-melting temperature, consequently, in the last phase transformation of the solidification, neodymium atom will be solidified in the crystalline grain or crystal boundary, and it is dispersed uniformly in the Tb metal, and average concentration of Nd is in the range of 2.26ppm~3.49ppm, and it tallies with the segregation degree data in the Table 4, and the segregation degree is about 15% for each sample
Fig. 4 Phase diagram of Nd-Tb system For the other rare earth elements, they are similar to Nd element, there is no intermetallic compound with Tb element [13], so that these rare earth impurities disperse in the crystal grains or enriched at grain boundary, and they are relatively uniform in the Tb metal from macroscopic view.
Table 4 Average concentration of rare earth impurities in Tb metal tested by LA-ICP-MS (ppm) Sample Number No. 1 No. 2 No. 3 No. 4 No. 5 No. 6 No. 7 La 14.23 11.22 10.99 11.62 11.64 11.65 11.11 Ce 2.24 2.09 2.08 2.11 2.11 2.11 2.09 Pr 1.14 1.11 1.1 1.11 1.11 1.11 1.1 Nd 3.49 2.39 2.26 2.51 2.54 2.54 2.37 Dy 5.91 5.22 5.11 5.25 5.3 5.27 5.18 Ho 0.8 0.72 0.71 0.73 0.74 0.73 0.71 Er 3.78 3.15 3.08 3.2 3.24 3.22 3.14 (2) High melting point impurity For the high melting point impurity, such as Ta, which is introduced in the distillation purification by using Ta sheet acting as a condenser, is distributed extremely non-uniform in the Tb metal, as seen in Fig. 5, the red color point notes the local concentration of Ta is very high.
Fig. 7 Two-dimensional element distribution of Al impurity in Tb metal Table 6 Analytical date of Al impurity by LA-ICP-MS in Tb metal Sample Number No. 1 No. 2 No. 3 No. 4 No. 5 No. 6 No. 7 Average relative intensity(IE/ITb×10-4) 21.91 22.51 22.52 22.85 22.86 22.82 22.14 Relative standard deviation (RSD) (%) 8.88 13.42 11.8 13.56 11.38 10.37 10.27 Average concentration(ppm) 11.31 9.46 9.27 9.95 9.87 9.95 9.09 Before the SSE process, the last phase transformation of Tb metal is solidification.
In the other hand, the atomic radius of Al and Tb is 0.143nm and 0.177nm respectively, the diameter ratio of two elements atom, δ(ΔrAl/rTb), is equal to 19.2%, so that the Al atom will be replace the Tb atomic position in the crystal lattice, and it is solid dissolved in the crystalline grain, or enrich at crystal boundary, when the temperature decrease lower than 845℃, very small amounts of AlTb2 precipitates could form in the crystalline grain and crystal boundary.

In this study, the correlation factor between these windows was calculated using the color number (the brightness) of each pixel.
The height in each point (z-direction) was given by the color number from 0 to 255 in the height image for three-dimensional analysis, while the numerical data in the two perpendicular directions (x- and y-directions) were given by the dimension in pixel.
The three-dimensional image reconstruction was carried out on the stage I fatigue fracture surface in a Cu-Be alloy (the grain diameter is about 2.4x10 -5 m) (Fig. 5).
SiC grains of a wide size range (from about 3.7x10 -7 to about 8.6x10 -5 m) as well as the residual Si phase were involved in the impact-fractured specimen of a commercial SiC (Norton NC-430) [9] (Fig. 8).
Relatively flat parts are probably formed by fracture along the interface between a large SiC grain and the residual Si phase, while the parts of complex geometry may be formed by fracture in the Si phase or along the interface between fine SiC grains and the Si phase.

The present investigation describes the results obtained in the preparation of a number of Cu-Zn ferrites, additionally doped with titanium, which were eventually used to design a very sensitive minithermostat and some magneto-thermal relays.
Grain size of ceramics seems to be the main factor that strongly influences the permeability.
Larger grains lead to higher permeabilities and some earlier studies have found a nearly linear dependence of initial permeability with grain size [6, 7, 10-12].
If the value of the initial permeability depends mainly of the grain size of polycrystalline ceramics the sharpness S is mainly due to the cation distribution on A and B sites of the lattice and this distribution depends on the cooling speed from the high sintering temperature to room temperature [16-22].
Disc shaped samples were also used to construct a number of magneto thermic relays as will be further shown.

For this purpose, a number of units and laboratory facilities are created in the Laboratory of layered composites and coatings [1]: 1.
Consequently, the temperature changes obviously cause local changes in the energy state in the volume of the metal resulting in emergence of active centers and appearance of various defects (vacancies, dislocations, etc.), i.e. the change in mechanical properties is due to increase in the number of defects and growth of their migration rate.
These processes result in grain refinement in the surface layer and increase in the number of defects in the material structure that migrate inside the grains and accumulate at their boundaries.
In the third area, the number of active centers on the surface and in the volume of the metal increases significantly with growth of temperature and time of action of the electric discharge plasma.
It is explained by an enhancement of shock-wave actions intensity leading to grain refinement in the surface layer and plasticity reduction of the metal as a whole, as indicated by the increase in ultimate tensile strength at 135 W/cm2.

The applications of PEF equipment to food processing, such as juice, grains products, milk, vegetables and so on have been reported (Table 3).
The factors of PEF treatment include pulse duration, pulse frequency, pulse width, pulse number and electric field strengths.
It can be inferred that PEF treatment will damage the structure of grain product.
Table 3 Application of different pulse parameters on food processing Classification Materials Pulse parameters Reference Grain product Corn starch Pulse frequency 1008 Hz , pulse duration 40 μs, the voltage were30, 40, and 50 kV cm-1 [8] Egg whites The maximum voltage 30 kV, pulse width 60 ps [11] Soy protein isolate Electric field were 22 and 25 kV/cm and pulse numbers of 30, 60, 90 and 120 [17] Vegetable Onion tissues A pulse width 100 μs, pulse frequency 1 Hz, electric field strengths 67 to 333 V/cm, pulses number 1 to 100 [9] White asparagus Voltage 15000 V, electric field strength 5 kV/cm, pulse number 20; frequency 2 Hz [19] Juice Peach Capacitor at 3 to10 μF, pulse width at 0.02 and 0.08 ms [21] Orange juice–milk Electric field strength 15–30 kV/cm, peak current was 11.2–22.4A, pulse duration 2.5μs, repetition rate 547 pps, number of chambers 6, flow rate 120 mL/min, pulses number of per chamber was 3.3, treatment time 50 μs [28] Fresh apple juice The flow rate was 15.75 ml/min

number of data samples for training.Generalized regression neural network (GRNN) has good approximation ability, classification ability, and its learning speed is superior to BP network.
R is the number of input vector elements, equal to the learning samples input vector dimension, and the weights are the transpose of input vector.
To construct the GRNN model, in this paper we set total power of agricultural machinery as the output factor of forecasting and choose four indexes as the influencing factors which are gross output value of farming, forestry, husbandry and fishing, total grain output, per capital income of the former's family and total crop planting area.
Normalization is to avoidthe great prediction error which caused by the order of magnitude difference between inputs and outputs, thus convert the data to the number in intervals of [0, 1].Generallyminimum and maximum method is used.
Extrapolation inspection.Extrapolation test is to compare the results of afterwards forecasting test set withpractical value, and can be represented by Relative Error, as shown in Eq.9 (9) In this paper the test data include gross output value of farming, forestry, husbandry and fishing, total grain output, per capital income of the farmer's family and total crop planting area of Guangxi in 2010.

The role of the Ti –sublayer on a sintered powder tungsten carbide substrate is not only limited by the adhesion improvement, but it is mainly used to neutralise the grain boundary microcracks on a surface.
In general, the surface covered by Ti layer appears to be smoother owing to the micro-cracks and grain boundaries fulfilling.
This test was done on a PCB (BTHL832HS (Cu:12/12 mm) 4 panels/stack) as a function of the hit count (a number of drilled holes) on the penetration rate.
Hit count corresponds the number of holes made by micro drills without coating (Nnc) and with ta-C coating (Nc).
Tests for the coated micro-drills demonstrate practically the same number of holes (Nc) varies in range from 32038 to 36916.

The observed impairment of cell attachment (decrease in number of focal adhesions) and the increase in number of apoptotic cells in our early studies after the certain mechanical surface treatment [2] were suggested to be a result of martensite emergence in the austenitic structure of NiTi alloys.
Thus, the grains, which transform to martensite during direct martensitic transformation in polycrystalline NiTi alloy, “shrink”, causing tension of the neighboring untransformed austenite grains.
The opposite process takes place during reverse martensitic transformation when the grains transformed to austenite expand causing their tension and compression in the surrounding untransformed martensitic grains.
These variations in cell size were accompanied by similar variations in number and area of FAs, which were minimal at the moderate stress level in comparison with the same characteristics at zero and the highest stress level.
While tensile stress increased, the average number and area of adhesions steadily decreased.

The 1980s saw dramatic growth in the number and kinds of measurements, including initial pulsed source studies at IPNS and commercial work at Harwell and Chalk River.
MacEwen measured grain interaction stresses in hexagonal Zircaloy [18] on the GPPD.
In fact, for pulsed sources, data from all peaks with d-spacings between about 0.5 Å and 5 Å are collected simultaneously so that a large number of peaks are present.
Another issue raised was the effect of texture on grain interaction stresses, an ongoing concern.
Today grain interaction and residual thermal microstresses are often studied at pulsed sources, and the role of texture is discussed at a number of talks at this meeting.