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Also, the increase of the chamfer angle has a small influence on the maximum contact pressures, although that could be also dependent on the reduction of the polyethylene thickness.
In accordance with Wolff’s law, the reduction of the mechanical stimuli of the bone relative to the natural situation causes bone to adapt itself by reducing its mass in a process of resorption around the implant leading to micro-motions and subsequent implant loosening [5].
There is still not enough data to support the hypothesis that the mechanical properties of the liner material influences periprosthetic bone remodeling [6].
The loading data used in the simulation, such as the magnitude and orientation of the resultant force, were taken from Bergman’s data, whose study was based on the maximum dynamic hip joint force applied to an instrumented prosthesis on the femoral head [7].
Also, the increase of the chamfer angle has a small influence on the maximum contact pressures, although that could be also dependent on the reduction of the polyethylene thickness.

Comparing the calculation result and the actual data, the precision of the rolling force calculation is high.
(4) inoutin hhhr /)( −= (5) Rolling forces in elastic deformation zones: )()( 1 3 2 2 out in m out in out m out e in ee hhRWk hh h k E FFF −'− − − =+= ξ ν (6) Where: p F is the rolling force of plastic deformation zone, e F is the rolling force of elastic deformation zones. in e F is the rolling force of elastic entry deformation zone, out e F is the rolling force of elastic recovery deformation zone, mk is the average deformation resistance. int is the back tension, outt is the front tension, α is the influence coefficient of back tension, β is the influence coefficient of front tension, W is the strip width, R ' is the roll flatten radius, inh is the entry thickness, outh is the delivery thickness, r is the reduction
( )       ∆⋅ − +=' eqhW F E RR π ν 2116 1 (7) Where equivalent reduction: ( )ine p out e eq hhhh ∆+∆+∆=∆ (8) ( )outout out out e tkh E h − − =∆ 2 1 ν (9) ( )outoutout out in in e p tkh E hhhh − − +−=∆+∆ 2 1 ν (10) Where R ' is the roll flatten radius, R is the original roll radius, F is the rolling force.
The calculation results are compared with the actual data as shown in Table 1.
Table 1: Model calculation data and actual data comparing table Stand No. 1 2 3 4 5 Work roll radius[mm] 272.0 238.2 239.7 264.0 249.7 Deformation resistance [MPa] 474.51 653.48 759.77 827.41 880.36 Friction coefficient [-] 0.0996 0.0388 0.0304 0.0266 0.0223 Roll flatten radius [mm] 341.2 294.1 346.4 495.8 588.7 Model calculation data Rolling force [kN] 7927.6 7199.9 6829.3 7732.7 8137.1 Deformation resistance [MPa] 466.07 640.22 757.11 865.27 894.23 Friction coefficient [-] 0.0946 0.0359 0.0300 0.0310 0.0234 Roll flatten radius [mm] 341.7 295.0 346.8 495.3 588.8 Actual data Rolling force [kN] 7898.0 7009.6 6804.5 8179.8 8533.5 Set R' to the original roll radius Calculate rolling force F with Eq. 1 Calculate roll flatten radius R' with Eq. 7 mineRR ≤−' Set RR '= Start End Yes No Set RR =' Fig.2.

PCBP can be used in prediction or data mining more efficiently than FCBP.
So, if we can remove these unnecessary connections from the network, then training times would be greatly reduced, it is especially important for data mining, without faster training time, data mining using neural network is mission impossible.
To our best knowledge, most reduction methods have been done during training networks[6-7].
In the following experiments, we use the data set to train FCBP and PCBP.
When PCBP is applied in data recognition or other fields, like data mining, it learns faster than FCBP does, especially trained with a huge amount of sample data.

The experimental results show that the most important factors in nanogap reduction were the metal type and the initial nanogap.
The reduction of nanogaps after the lithography process, as discussed earlier, is a SB quality characteristic.
The SNRs (signal to noise ratios), which condense multiple data points in a trial, depending on the characteristic that is being evaluated.
The confirmation result is -29.73 (dB) that the optimizations of the lithograph process nanogaps reduction is achieved.
The nanogaps reduction via metal layer expansion technique for nanogaps fabrication is established.

Phase identification of the metal - oxide composite powders after drying and calcination was determined from X-ray diffractometry data (XRD) (Model JDX-3500, JEOL, Tokyo, Japan).
Subsequent sonochemical reduction of Pt or Pd ions was applied.
The particle size analysis (LPSA) data for the aqueous suspensions of the 3mol% yttria-stabilized zirconia powder impregnated with 5 wt% of platinum and 5 wt% of palladium respectively are shown in Fig. 2.
The sonochemical reduction of the platinum (or palladium) compounds was applied.
That is clear proof of the completion of platinum or palladium reduction.

As shown in Fig. 4a, the simulation results obtained from the YU model show the best agreement with experimental data compared to those obtained by IH and LK models.
To evaluate reduction of Young’s modulus during plastic deformation, loading-unloading test was carried out with the same equipment as the cyclic tension-compression test.
The chord modulus was determined from the experiments and following exponential equation [7] was utilized to describe Young’s modulus reduction during plastic deformation
(1) The parameters of the exponential equation are listed in Table 2 and obtained results are indicated in Fig. 4d where solid line is the fitted results with the exponential equation and the symbols are experimental data.
As shown in Fig. 8, there was no significant effect of the reduction of Young’s modulus on springback prediction.

Checking grey cloth → Arranging by slack management → Sewing seam side → Initial setting → Sewing bound edge → Dyeing →Reduction cleaning → Dewatering and Drying → Second setting → Reduction cleaning → Dewatering and Drying for finished product→ Testing the finished product → Packaging and storage 2.2.1 Initial setting: German Babu Kirk stereotyping machine was used.
Fig 1: Greece SCLAVOS process data 2.2.3 Dyeing (Include Reduction cleaning): Greece SCLAVOS automatic high temperature-pressure double soft flow dyeing machine was used.
Table1:Dyeing process Table2:Reduction cleaning process WW disperse dyestuff (o.w.f) X% Processing time RAP-CN levelling agent 0.2 g/l 20min/130℃ Ice HAC 0.5 g/l NaAC 0.2 g/l Ciba Refining oil C 2 g/l Sodium hydrosulfite 3 g/l Processing time Liquid Soda 4 g/l 20min/90℃ Sodium carbonate 2 g/l OLS Reduction cleaning agent 2 g/l DAM Disperse agent 2 g/l 20min/80℃ Fig2: Dyeing diagram of curve Fig 3: Reduction cleaning diagram of curve 2.2.4 Second setting: German Babu Kirk stereotyping machine was used in this step.
Recipe and color fastness for final production (result in white dyes combination was shown in the following table3) Table3: Recipe and color fastness for final production Recipe Item Result Bright red (o.w.f) Bright black(o.w.f) Brown (o.w.f) Dark Blue (o.w.f) WW-BFS Bright red 2% WW-DS Ruby 2% W-6GS Yellow 0.06% WW-DS Ruby 0.7% WW-KSN Black 4.5% W-6GS Yellow 1.4% WW-3BS Ruby 1.38% WW-GS Blue 1.3% W-6GS Yellow 0.14% WW-3BS Ruby 0.46% WW-GS Blue 5% washing color fastness acetate fiber 4-5 4-5 4 4-5 cotton 4-5 4-5 4-5 4-5 nylon 4-5 4-5 4-5 4-5 polyester 4-5 4-5 4-5 4-5 acrylic fibers 4-5 4-5 4-5 4-5 wool 4-5 4-5 4-5 4-5 white dyes combination fastness Off white 4-5 4-5 4-5 4-5 fine white 4-5 4-5 4 4-5 floating color fastness colorless；4-5 colorless；4-5 slightest；4 slightest；4-5 rubbing fastness Dry 4-5 4-5 4-5 4-5 Wet 4-5 4-5 4-5 4-5 Analyzing the data from the above table, we can see that by using WW disperse dyestuff, process flow B and RC4 Reduction cleaning

Data analysis shows a significant decrease in all pollutant parameters after 24 hours of retention time.
The following are the formulas used for data analysis; Pollutants Removal Efficiency.
Based on the data above, it can be concluded that the initial wastewater quality from Samudera Raya restaurant does not meet the standard.
The COD reduction of 95.01% is obtained after 12 days of retention time.
Efficiency based on wastewater pollutant level reduction Time (hr) BOD TSS Oil & Grease COD Efficiency Efficiency Efficiency Efficiency (%) (%) (%) (%) 24 98,69 97,58 99,5 94,6 48 99,01 99,25 99,82 96,72 72 99,8 99,25 99,64 95,87 Data analysis shows a significant decrease in all pollutant parameters after 24 hours of retention time.

The Sulfur Dioxide atmospheric environmental capacity of Chengdu urban agglomeration was calculated by using this model so as to provide basic data for the total capacity control of Chengdu urban agglomeration.
Therefore, in the present study, we have collected the meteorological data of the recent three years measured by all the meteorological stations in the urban agglomeration.
The calculation method of yield reduction rate of crops is described bellow.
According to the acid rain monitoring data [20] in the recent 5 years of five cities of Chengdu urban agglomeration, in the rain, [SO4]2-∕[NO3]- =5.4, which indicates that the sulfuric acid type acid rain is dominant in this area.
Therefore, in economically developed areas, the multi source mode – double objective optimized method can be used to calculate the atmospheric environmental capacity, while in economically developing areas, the multi source mode - linear optimized method can be used to calculate the atmospheric environmental capacity which will be used as the basic data for total capacity control.

This paper uses IEEE36 node example, based on typical data, using MATPOWER software, calculating the low-carbon comprehensive benefits of wind power on a typical day, the results show that, compared with the traditional grid, wind power has great low-carbon and economic advantages.
From the economy of CO2 emission reduction, wind power has some benefit through carbon trading mechanism.
Based on the model and typical data, his article analyzes the emission reductions and economic benefits and low-carbon comprehensive benefits of wind power.
Estimation of Life-cycle Emission Reduction Benefits for Wind Power Project Based on Interval number Theory[J].
An Energy Saving and Emission Reduction Based Bidding Transaction Mode Under Carbon Trading Mechanism[J].