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The analysis result demonstrates that the seismic isolation layer has effectively controlled the vibration of superstructure, which would contribute to the reduction of seismic hazard.
Although we did not proceed tremendous detailed calculation about the entire cost data, via analysis, we think the anticipated cost would, to some extent, increase by about 5%~10% due to input of early-days seismic isolation system.

The particle size of the silicon carbide and aluminum oxide matrices affected wear reduction, with normal temperature conditions resulting in a 25% reduction in wear.
These data suggest that increased surface roughness correlates with higher friction coefficients.
This reduction suggests that sliding on the surfaces likely occurs shortly after the initiation of the transition.
Specifically, the data show that a wider track is required for a given normal load or sliding speed.
The data indicate that the wear rate curves vary at different velocities.

In global manufacturing system, reduction of weight for automobile components is the main concern in automotive manufacturing industries.
Table 2: Results of 65Si7 Steel and Nano Composite Cart Spring Load Deflection Maximum Shear Stress Equivalent Stress Steel Composite Steel Composite Steel Composite 15536 2.202 4.678 58.300 51.533 116.055 102.899 19616 2.765 5.913 73.622 65.022 146.344 129.855 24510 3.467 7.335 92.033 81.211 183.022 162.377 29425 4.158 8.866 110.22 97.455 219.577 194.866 Conclusions The fabricated composite cart spring was undergone to the finite element modeling development with its static loading conditions using the orthotropic elasticity data through 3D modelling software ANSYS R16.0 and modeled by using the PTC developed software of Pro Engineer.

The reduction of section area is 87.57%.

However, some drawbacks of Artificial intelligence-based algorithms include extensive computation requirements, rule sets, knowledge bases for FLC-based systems, and massive data for training in the case of NN-based systems [3, 7, 14].
Table 1 illustrates the electrical data of the SPR-X22-370 solar panels used to model this study.
SPR-X22-370 solar panel electrical data Electrical Data SPR-X22-370 No.
These techniques make more sense to initialize the particles around the global maximum power point if data on their distance in the search range is available.
Thus, this effect is directly related to efficiency reduction.

Moreover, the analysis of variance (ANOVA), linear regression model and main effect plot have been used to analyze the DTO data. 2.
The cutting force data were stored on the computer.
The most important statistical data in the ANOVA table are P-values.
The linear regression model is carried out to analyze and predict experimental measurement data.
The results data were analyzed using analysis of variance (ANOVA), linear regression model and main effect plot for mean.

From the transmission data, the optical bandgap energy is extracted.
This tendency in grain sizes observed by SEM is consistent with that of crystallite sizes obtained from XRD data analysis.
From the data analysis, the Rrms values of surface roughness are found to be 3.88, 5.49, 7.97 and 9.56 ± 0.01 nm for the TiO2 films deposited at RT, 200, 300 and 400°C, respectively.
Eq. 2 gives the explicit expression of n: n=3-2Eg20Eg2012 (3) The obtained data showed that the linear refractive index of the films is found to increase from 2.24 to 2.28 with increasing the substrate temperatures from RT to 400°C, respectively.
Klapetek, Gwyddion: open-source software for SPM data analysis, Cent.

Nanoemulsions can encapsulate functional ingredients within their droplets, which can facilitate a reduction in chemical degradation [18].
Coupled with powerful approaches such as association genetic analysis, DNA sequencing data of the crop germplasm, including the cultivated crop gene pool and the wild relatives can potentially provide highly useful information about molecular markers associated with agronomically and economically important traits [35].
Gene sequence and mapping data mean little until we determine what those genes do-which is where protein arrays come in [43].
The bar code is nothing but an electronic data depicting several parameters such as date of production, place of packaging, prices etc. and reading this code requires an electronic data reader.
The keys are biodegradable sensors for temperature and other stored data containing the history of stored food for both physical and biological parameters.

At present, the operational data from 24 CWs for urban and rural sewage treatment are available (Table 2).
There are 8 full-scale CWs for industrial wastewater treatment available with operational data.
There are 10 full-scale CWs treating urban or agriculture runoff available for operation data (Table 5).
The average designed HLR and the removal efficiencies of organics and nutrients compared among different types of CWs and wastewater treated based on the collected data from the surveyed full-scale systems in China (a. comparing among different types of CWs; b. comparing among different types of wastewater treated) Conclusions In the last two decades, different types of CWs have been applied for the treatment of different types of wastewater in China.
Generally, the data collected from the full-scale systems shows that CWs have effectively reduced the concentration of organics and nutrients in different wastewater streams with low operational cost.

Introduction Magnetic nanomaterials, due to their high saturated magnetization, good biocompatibility, easy preparation, have been explored widely for various applications such as magnetic hyperthermia [1], antibacterial agent [2], magnetic immunoassay [3], magnetic data storage [4], recyclable catalysts [5], drug delivery [6], magnetic resonance imaging [7], biosensors [8,9], effluent processing [10,11], etc.
All the above data manifest that β-CD-P was unequivocally attached onto the surface of Fe3O4 NPs after surface encapsulation with β-CD-P.
Fig. 4 (a) Kinetic adsorption curve of MG on Fe3O4@β-CD-P NPs at pH 6 on 25 oC; insets show the photographs of MG solution at 2×10-5 mol/L before (left) and after (right) adsorption by Fe3O4@β-CD-P NPs, fitting of adsorption kinetic data with (b) Pseudo-first-order and (c) Pseudo-second-order model.
Langmuir (Eq. 5) and Freundlich (Eq. 6) models were then used to fit the experimental data of MG adsorption by Fe3O4@β-CD-P NPs at room temperature.
Additionally, the maximum adsorption capacity(qm)of Fe3O4@β-CD-P NPs for MG is 88.49 mg g-1 by calculation from the Langmuir equation (Eq. 5): (5) (6) Fig. 5(a) Adsorption isotherms of MG by Fe3O4@β-CD-P NPs at pH 6 on 25 oC, fitting of adsorption isotherm data by (b) Langmuir and (c) Freundlich models.