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The addition of acetonitrile into electrolyte results in the change in the morphology of the coating surface, a significant reduction in the manganese content and, as a consequence, practical loss of activity in the oxidation of CO in CO2 and a reduction in the photocatalytic activity in the decomposition of methylene blue.
The data on morphology and element composition of the surface were obtained using an S-5500 scanning electron microscope (Hitachi, Japan) with the system for energy-dispersive X-ray spectral microanalysis.
Table shows the data on element composition of formed in electrolytes with and without addition of acetonitrile.
According to elemental analysis data, the regions containing nanostructures include at.%, 11.2 Mn, 18.5 Ti, 56.2 O, 14.1 C, neighboring regions are depleted of manganese and contain at. %, 6.3 Mn, 26.3 Ti, 58.6 O, 7.8 C, 1.1 Na.
The addition of acetonitrile to the electrolyte leads to a change in the morphology of the coating surface, a significant reduction in the manganese content and, as a consequence, practical loss of activity in the oxidation of CO and a reduction in the photocatalytic activity in the decomposition of methylene blue.

The obtained data were compared to the measurements of a pure cement reference paste.
The samples were subjected to various curing conditions and the obtained results were compared with the data measured on reference pure cement paste samples.
In order to acquire reliable data, six specimens representing each batch were tested.
The results obtained by the measurements on the submerged samples are in agreement with already published data [5, 7].
On the other hand, the results obtained in the case of samples exposed to air are unique, since no similar data have been found in the available literature.

In order to reduce calculation and data storing, the dimensionality reduction methods are taken as excellent choice.
PCA can eliminate the second-order correlation between data and keep up most information of the raw data.
We also test PCA plus SVM approach using standard benchmark data sets.
The data sets were obtained from UCI machine learning repository [12].
Here we select the data set with low dimensions, which means the is usually no singular.

If the LCF data is to be used to directly assess the life of a component, the crack size at the point of initiation must be known and compared to the dimensions of the critical location in the component.
If the definition of initiation results in large crack sizes before the load drop criterion is used, the data may give un-conservative life predictions for e.g. thin-walled components.
A better model response with respect to experimental data could probably be obtained by using a threshold effect in the kinematic hardening, cf. [7] or by using a Ohno-Wang type of model, e.g. cf. [8], [9].
This data agrees well with the FE-results from both elastic and elastic-plastic analyses, and is still not affected by the applied Rϵ.
This was shown to give good results, but require experimental data of sufficient quality.

While if the metal surface is negatively connected as the cathode, the reduction reaction is induced on the interface where the electrolyte is usually reduced.
In region II, the current keeps increasing along with the formation of hydrogen bubbles on the metal surfaces as the reduction reaction occurs [14].
The sampling rate for data acquisition was 10Hz at the beginning.
And the effects of pores and cross-hatch (grooves) on the reduction of friction are compared in the following section.
Wiklund, et al., Oil pockets and surface topography: mechanism of friction reduction, XI international colloquium on surfaces.

This kind of models needed a huge amount of data.
It also needed a lot of data.
Empirical analysis Based on the models, empirical data should be collected and analyzed.
According to the models and data, the Carbon emission table was compiled in table 2 and table 3.
By analyzing the driving force of carbon emission, this paper provided more intuitive and effective data support for making policies and measures of carbon emission reduction.

The properties analyzed are based on the data obtained from the steady state profiles from the simulations.
The electronic density of states was obtained from the output data obtained during the simulation.
The average bond length change data as a function of temperature change is not available in literature.
The trend for SiC matches with that by Fahrenholtz et al. [10] It is important to note that SiC data, here, is for the single crystal and Fahrenholtz et al. [10] data is for SiC phase in a composite.
Straining in both cases of SiC and ZrB2 leads to reduction in phonon frequencies relative to 0% strain resulting in reduction of phonon thermal conductance with increase in straining.

Finally, SVM was used to classify the GEP data set.
Neighborhood Rough Setis a method based on classical rough set, it can directly process continuous data [3,4].Therefore, information are not loss before reduction, making the attribute subsets have stronger classification capacity.
RS don’t need any prior information and can only rely on internal information of data themselves to discover tacit knowledge within them, reveal potential rules and effectively process incomplete and inaccurate data.
Neighborhood rough setthat was brought up by Qinghua Hu is a improved method that develops from t classical rough set and can directly process continuous data[3,4].It needn't discretize continuous data in advance, and can be directly used for problems of knowledge reduction etc.
We experimentized in MLLLeukemia data set to vertify our method.

In each case, the specimens were compressed to half their original height and the load-displacement data was recorded.
Plates will separate along the bonding face at reduction ratios of 2%, 4%, 6%, 8% and 10%, as shown in Fig.5 b).
Though it is noted that dissimilar metals and alloys can be joined by hot rolling at a large reduction ratio, the reduction ratios in the experiments were too small to create a strong bonding between the Al alloy plate and the Mg alloy plate.
Fig. 5 Separation of laminated composites at different reduction ratio: a) 1% and b) 2%.
The maximum strain at different positions increases with the reduction ration, λ.

Sand levee stability is influenced by the strength reduction degree of liquefaction soil layer, so this paper makes a further analysis and calculation about slide safety factor and risk probability under different reduction factors, as shown in fig3~ fig 4.
From the figure 3, we can find that safety factor reduced with decrease of soil strength reduction factor.
It is more sensitive when reduction factor is less than 0.6.
The probability of landslide changes with liquefaction soil strength reduction factor in Figure 4 demonstrates that when reduction factor decreases in range 1~5, landslide probability will have a large rangeability; When strength reduction factor is less than 0.5, failure probability almost tend to 100%.
Taking a segment levee of Minjiang (Fuzhou) downstream for a case study, the analysis data indicate the earthquake landslide risk of which is below 7 degrees.