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All data were expressed as the mean value ± the standard deviation (SD) or the standard error of means (SEM) of the obtained data as indicated in all figures and tables.
When the microspheres were added after cell adhesion, they did not show a significant inhibitory effect on the functions of NHOst (data not shown).
Pre-coated PS, PE and alumina microspheres showed the potential to suppress functions of NHOst although some of these data did not show statistical differences against NHOst without microspheres.
It was observed that HAp microspheres have no potential to deposit calcium after a 1-week incubation without NHOst (data not shown).
As expected, added various microspheres affected NHOst in a similar manner but less than the pre-coated microspheres (data not shown).

To upload stacker’s access accomplishment condition and fault alarm data from optical communication to HMI; 4.
To resolve the instruction data given by HMI and command Stacker PLC finish various movements.
Different frames have different data head and length.
Parity check will be added to the end of each frame data.
When there is transmission error in data transmission, it will realize data retransmission.

Along the y-axis, data were processed making use of axial symmetry, then a fitted curve was acquired using least squares polynomial.
Data and fitted curve along y-axis, Fig. 19.
Data and fitted curve along z-axis, 2mm in diameter 2mm in diameter Fig. 20.
Data and fitted curve along y-axis, Fig. 21.
Data and fitted curve along z-axis, 1mm in diameter 1mm in diameter Contrasting the data acquired in the 2mm case between that in the 1mm case, it’s shown that bigger particles carry more charge, result in bigger data acquired in the 2mm case, however, the close similarity in form between the fitted curves demonstrates that spatial sensitivity is just related to the positions of the charged particle when the dimensions of the sensor are fixed.

Below are the given data: Material performance of the Steel N80, circum radius 177.8mm, wall thickness 10.36mm is shown in Table 1.
It can be seen from Fig.5 drawn according to the calculated data that uneven coefficient of stress increases linearly with ground stress ellipticity increase.
It can be seen from the calculated data that the perforation hole enormously reduces the ability of the casing to resist extrusion by external force.
Fig.6 drawn according to the calculated data suggest that equivalent stress of the perforation section of the casing increases along with the increase of external pressure.
It can be inferred from Figure7 drawn according to the calculated data that equivalent stress at the perforation section of the casing decreases dramatically.

At present, the absolute position sequence has been completed via human-computer interactions including region selection and direction identification, and the data out of the selected region haven't been used for calibration.
During calibration, it requires to calculate based on image data of calibration target at different poses.
Conduct curve fitting to experiment data by applying least square method to get the optimal approximate solution.
Draw a straight line, designated as L, passing point B and point D, and designate the lesser of center data of B and D as R, the searching radius.
Reduction Algorithm for 3D Scattered Points Cloud Data Based on Clustering PlaneFeature [J].

(1) Suppose X is a sampled data matrix, that is, , in which n is the number/frequency of measured sampling and m is the number of measured variables.
The load matrix P and Dλ can be obtained from equation (2) and T, representation data information link between the principal component scores matrix, can be obtained from euqation (3)
(1) (2) (3) (3) To reconstruct the data, several typical principal components are extracted to accounts for the major variability in the data with the expression as follows: , (4) (4) The cumulative distribution function is usually adopted to figure out the number of principal components by picking up those whose cumulative contribution percentage is above 85%
Flowchart of PCA, network identification and D-S fusion of measurement data Fig.4.
When the system goes stable, the data of the fault xi is sustituted to be analysized by PCAi(i＝0, 1) model and obtain the low dimension vector, which is then identified by classification network and standardized to obtain two groups recognition results.

Using the known data one can state that specific values of ohmic loss Idl. are 0,9 ÷ 1,3 W/kg and 0,21 ÷ 0,26 W/kg, accordingly for amorphous magnet materials and traditional cold-rolled electrotechnical steel.
That is why it is necessary to analyze TLEPE in AMT and TPT statically and dynamically that means in coordination with technical data and exploitation data, measures and computer experiments.
The table 1 contains technical data PT 10 kV for the statistic analysis.
The dynamic inference using computer experiments and exploitation data gives more detailed and almost exhaustive information for comparison of AMT and TPT.
The data of this change in marks and nominal power rating are represented in table 2.

Cutting temperature is sampled by data acquisition card Advantech PCI-1710.
After the temperature is sampled, the PC will handle the sampled data and create the input of fuzzy control system.
Data acquisition card PCI1714UL is applied to sample vibration and AE signal for further study.
The main modules include: human-machine interface, data acquisition, data filter, fuzzy control and output of control value.
AE sensor and two vibration sensors are applied to sample data for further study.

However, when physical properties depend on microstructural details (such as the spatial correlation of crystallite orientation, the shapes and dispersion of second phases, extremes of statistical distributions, or local anisotropies) such data reduction is often difficult or pointless [6,7].
The user starts with a digitized image of the microstructure and builds a data structure on top of it.
All the data plus any that can be inferred by the user is employed.
For OOF2, the microstructure is a data structure composed of image and property data[6].
Finally, for the OOF2 program, the microstructure has become a set of data consisting of images and properties.

It can give both positive and reverse simulations and can nearly solve all problems concerning equilibrium thermodynamics and chemical kinetics in the interaction system of water, air, rock and soil, including water soluble complexing, adsorption-desorption, ion exchange, surface complexation, dissolving-precipitation, oxidation-reduction and other chemical reactions.
ZHANG Congzhi et al. (2006), through the lab soil-column effluent experiment on Na+, K+, Ca2+, Mg2+, applied PHREEQC in the simulation of coupling ion exchange and complex reaction transport models of Na+, K+, Ca2+, Mg2+ with PHREEQC, also compared the results with those of the software CXTFIT, and the results showed that the experimental data and simulated results are in a consistent tendency, and the simulated results of PHREEQC were better [11]; ZHANG Congzhi et al. (2008) studied the single-component and multi-component solute transport through lab soil-column effluent experiment, and used CXTFIT and PHREEQC to simulate the coupling adsorption and ion exchange reaction.
Ray et al. (2002) once adopted the geochemical transport model PHREEQC to predict the diffusion transport of Pb2+ in the clay liner of 10cm thick, and compared the results with the experimental data of other scholars [14]; Cécile et al. (2004) used the PHREEQC to study transport rule of Zn2+ in the soil-column under the condition of different PH values and different acetate concentrations based on the lab soil-column experimental data when the component reactivity is low and when there is acetate, which turned out that the error between simulation results and experimental data is no less than 10% [15]; Laurent et al. (2004) studied the absorbability and desorption sequence of multi-component heavy metals Pb2+, Cd2+, Zn2+ based on the lab soil-column experimental data and static adsorption experimental data when there is carbonate, and used PHREEQC for simulation, in which the results complied with the experimental results [16]; Ludwig et al. (2005) confirmed the applicability of the chemical
Vojtĕch et al. (2004) adopted PHREEQC to simulate the desorption and adsorption abilities of Pb, Cu, Zn and As in metallurgy residues under the condition of different PH values and different ion strengths, and then compared the results with the experimental data, which showed that there is good matching between them [18]; Vojtěch et al. (2005) studied the sedimentation of heavy metals in the spraying treatment of aqueous solution used for exhaust gas in metal smelting, simulated the sedimentation of the chemical element Pb under different PH values as well as the different sedimentation status with PHREEQC, and the simulated results complied with the results obtained from the geochemical research [19]; Cheryl et al. (2005) adopted PHREEQC to simulate the effluent concentration of heavy metals Pb, Cd and Cr in the effluent fluid in municipal refuse landfill, and the simulated results matched well with the experimental data [20]; Stéphanie et al. (2005) studied the reactive transport process
Physical reactions include convection, dispersion, diffusion, compression, decay (radioactive pollutants), etc., while chemical reactions include water phase complexation, surface complexation, oxidation reduction, acid-base reaction precipitation, ion exchange, adsorption, and precipitation-dissolution, as well as degradation of organic matters, all of which will affect the solute transport in the soil.