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There are original data for the design of spring supporting in the high-frequency vibration sieve for slime dewatering.
These data are shown in table 1.
Fig. 1 Structure of high-frequency vibration sieve Fig. 2 Structure of stranded wire helical spring Table 1 The original data for the spring design Name Install load Working load Working Stroke Vibration frequency Parameter 01000F �= 1800TF �= 10mm=δ 25nHz=ν Name Number of spring Material of spring Modulus of elasticity Allowable shear stress Parameter 4 60 2Si Mn 80000G MPa = [ ] 600MPa=τ Fuzzy Optimization Design Model The fuzzy optimization is a method that an optimum solution will be obtained fully considering various kinds of fuzzy quantity and fuzzy relations existed in design variables, objective function and constraint conditions in the conventional optimization design [2].
The relationship of penalty factors for two adjacent iterations is: 1 k k r cr −= , in which, c is the reduction coefficient of penalty factor, and its value is usually at the range of 0.1-0.7.

These abnormal fault bring on the reduction of production capacity.
Description the Problem about Lamp Assembling Line Operation time is the basic data for calculating line balance rate and prerequisites for find out the bottleneck workstation.
We can calculate the line balancing rate and balancing loss from the collected data in table 1.
The data of table 1 indicates that the main reason of leading to a low line balancing rate of production line is that operation time of the bottleneck workstation is different from operation time of other workstations greatly.

Analyzing data obtained for a few tens values of critical current density jC=IC/L2 of mesa-heterostructers with different dSRO  and dLSMO  thicknesses a distribution of jC on dSRO – dLSMO plane was obtained, shown in Fig.2.
It is seen that as dSRO  and dLSMO  thicknesses approach the coherence lengths of ferromagnets, the jC data demonstrate a maximum.
Data present critical current and Shapiro steps vs. normalized RF current x = IRF/wIC, where w = hfe/2eICRN is normalized frequency (h is a Planck’s constant, e – electron charge, RN – normal resistance.
Microwave measurements also confirm absence of pinholes in experimental samples because the presence of pinholes would result in a significant reduction of Shapiro steps heights from the ones expected in resistively shunted junction model.

We have previously proposed a stacked gate insulator consisting of thick AlON layer and thin SiO2 underlayer and demonstrated a significant reduction in gate leakage [1].
The data for the capacitor with SiO2 single (49.1 nm) dielectrics was also shown (black line).
The data for AlON/SiO2 capacitors with the same AlON thickness (blue, green, and red open symbols) were also well fit by linear line with an identical slope, indicating the positive charge with an areal density of 1.2´1012 cm-2 at SiO2/SiC interface, which is comparable to that estimated for the capacitor with SiO2 single dielectrics.
The data plot in Fig. 2 (open circles, triangles, and squares) are all well fitted by assuming the positive charges of 1.2´1012 cm-2 at SiO2/SiC interface, the negative charges of 1.1´1012 cm-2 at AlON/SiO2 interface, and AlON dielectric constant of 8.0 (Fig. 3).

The summary of input data for this calculatin is as in Table 1.
Input data used in the calculation of electronic states of CdTe.
Parameters Input data Latice Face centered cubic, FCC Latice constants a = b = c = 6.48 Å Latice angles α,β &γ 90° (α = β = γ) Cd atom position (0,0,0), number of points in the logarithmic radial mesh ( NPT) = 781, maffin-tin radius (RMT) = 2.35, R0 = 0.00001 Te atom Position (0.25,0.25,0.25), NPT = 781, RMT = 2.55, R0 = 0.00001 The k-points that we chose for this calculation was 1000 (10x10x10) and the separation energy of core and valence states was equal to -9.0 Ry.This was done to ensure that the charge will leak the atomic sphere.
Reduction in the value of band gap energy is probably due to the hybridisation of p and d orbitals in the upper most valence band with the d orbitals pushed upwards, making the band gap reduced.

Introduction The production of sewage sludge from wastewater treatment plants (WWTP) has been continuously increasing for many years in China, and it poses an increasing threat to environmental security[1]. sludge incineration has been improved to be an effective method for sludge treatment, because it is advantaged in reduction of sludge volume, complete destruction of pathogen and organic pollutants, and energy recovery[2-4].
“Database” provides all of basic data for model calculation, “Process Model Worksheet” is a simulator where process model calculation is conducted, and “Graphic Interface Worksheet” provides an easy-to-use graphical interfaces.
Table 1 only shows some key data for process model calculation.
Table 1 Key data for process model calculation Parameter Value Sludge handling capacity 220 t/d Moisture content of wet sludge 80 wt.% Volatile ratio of sludge solid 47.1 wt.% Higher calorific value of sludge (volatile basis) 22990.8 kJ/kg Volatile ratio of coal 60.7 wt.% Higher calorific value of coal (volatile basis) 33608.4 kJ/kg Heat loss of the paddle dryer 10% Heat loss of the fluidized bed 3% Table 2 “Solver” for process optimization Sub optimum() 1 Sheets(“process”).Activate 2 SolverReset 3 SolverOK SetCell:=Range(“objective”), MaxMinVal:=1, ByChange:=Range(“variables”) 4 SolverAdd CellRef:=Range(“constraints”), Relation:=3, FormulaText:=0# 5 SolverSolve UserFinish:=True 6 Beep End Sub Result from process model calculation Fig.3 shows the auxiliary fuel and total energy consumption of sludge drying-incineration system.

These are increased circulation time in body and stability, improved biocompatibility and solubility, decreased cytotoxicity and degradation by metabolic enzymes reduction or elimination of protein immunogenicity [3-5].
Our data, together with these early studies, suggest that PCLA can have good ability to increase body circulation time.
Supporting for our cell viability data, we also checked morphological changes of the MCF-7 breast cancer cells by phase contrast microscope.
Morphologies of MCF-7 breast cancer cells against concentration of CLA after treatment with CLA and PCLA. 0 20 40 60 80 100 120 0 25 50 75 100 150 200 300 Concentration (uM) Cel l Vi abi l i t y ( % of Control) PEG CLA PCLA Half-life o f P CLA 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0 121824303642485460 Time( hr) ABSAs in the results for the cell viability data, both CLA and PCLA promoted apoptosis with increasing concentrations although proliferation of MCF-7 breast cancer cells was clearly detected in control group, as shown in Fig.5.

It is well known that microwave irradiations lead to large reduction in reaction time, enhancement of yield, and high selectivity of reaction due to the non-thermal effect of microwaves [5].
Relevant characterization data were given in Table 1 and 2.
The analytical data of bisdithiobenzil nickel complexes Analysis Found (%) Analysis Calculation (%) Samples Formula C H S C H S 5a C28H20NiS4 61.38 3.51 22.87 61.89 3.71 23.60 5b C30H24NiO2S4 60.20 3.98 20.82 59.71 4.01 21.25 5c C32H28NiO4S4 57.73 4.52 19.01 57.92 4.25 19.33 Results and Discussion Table 2 shows the yield of bisdithiobenzil nickel complex dyes 5a-c synthesized at different reaction time and different amount of solvent for 3 h by the conventional thermal and microwave heating.
The yield of bisdithiobenzil nickel complexes synthesized by conventional thermal and microwave method Reaction condition Yield (%) Method Time (h) Amount of solvent (ml) 5a 5b 5c 0.5 50 5.5 25.3 38.0 Conventional 2.0 50 65.0 70.0 73.0 0.5 9 7.7 50.7 58.5 Microwave 0.5 50 4.1 25.9 48.5 Mellting point and visible absorption data for the bisdithiobenzil nickel complex dyes 5a-c are summarized in Table 3 and Fig. 1.

Introduction Biomass gasification is considered a key technology in reaching targets for renewable energy and CO2 emissions reduction [1], and the biomass-to-SNG technology is one of the most important applications of biomass energy.
In this paper, simulation of the Biomass-to-SNG process based on gasification technology via pressurized interconnected fluidized beds was carried out with Aspen Plus software, which would provide theoretic referencing data for the further experimental researches.
Simulating condition and input data The biomass sample was the rice straw from Jiangsu, China.
Table 1 Input data for process simulation Parameters Value Room temperature 20 oC Biomass flow rate of gasifier 7 kg/h Air inlet temperature 20 oC Excess air coefficient of combustor 1.5 Flue gas outlet temperature of combustor 150 oC Combustor temperature 750 – 1050 oC Gasifier temperature 650 – 950 oC Feed water inlet temperature 20 oC Methanation temperature 300 oC Methanation pressure 0.3 MPa Results and discussions The crude methane mixture from the methanation reactor was mainly composed of CH4, CO2, and little H2 and CO.

The factorization can be expressed as following: (1) wheredenotes amatrix and is the number of examples in the dataset, each column of which contains an n-dimensional observed data vector with non-negative values.
The rankof the factorization is usually chosen such that, and hence the compression or dimensionality reduction is achieved.
This results in a compressed version of the original data matrix.
In other words, each data vector is approximated by a linear combination of the columns of, weighted by the components of.