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, Typically, Co/SiO2 catalysts were prepared by impregnation of SiO2 with nitrate solution, followed by calcination and reduction, which formed larger cobalt particles.
The mean Co3O4 crystallite sizes were estimated from the XRD data using the Scherrer equation.
The H2 consumption was monitored with TCD using the reduction of CuO as the standard. 2.3 Catalytic experiments Catalysts were evaluated in a pressured fixed-bed reactor at 2 M Pa, 1200 h-1 with the H2/CO ratio of 2 after reduction at 673 K for 10 h.
As the catalysts were modified with ethylenediamine, a third peak appearing at around 600-800 oC originated from the reduction of cobalt-silica interaction species[7].
The reduction degrees of catalysts were calculated.

(4) Change of the basic mechanical properties of concrete during heating has usually accounted for by the temperature parameters: strength reduction coefficient gc,q and reduction coefficient deformation modulus bc,q: fc,q = fck × gc ; Ec,q = Ec × bc,q (5) Temperature relations are defines expressly for ultimate deformations and associated ultimate coefficient secant modulus, but, according to the test experience [8], this formula can be used without loss of accuracy of final results nc1,q = nc × gc,q , (6) then ec1, q = ec1 / bc,q
(7) Temperature relations of the strength reduction gc,q and initial modulus of concrete deformation bc,q , and also thermal strain can be set in a tabular, or an analytical form: ; ; (8) , (9) where: qc – the heating temperature of the concrete; 20 – initial temperature, °С; g, b, m, n, a, p, ea – experimental parameters (Tab. 1); 1000 – dimensional factor.
Temperature relations between strength reduction gc,q and initial strain module bc,q (а), the thermal strain (b) normal weight concrete on a siliceous aggregates Figure 3.
Changing the strength characteristics of reinforcement during heating is taken into account by using the temperature parameters: reduction coefficient of yield strength ksy,q and the reduction coefficient of the proportional limit ksp,q: , ; (16) where qs – the heating temperature of the reinforcement; 20 – initial temperature, °С; wy, wp, c, d – experimental parameters (table 2); 1000 – dimension factor.
A compilation of elevated temperature concrete material property data and information for use in assessments of nuclear power plant reinforced concrete structures (2010), Office of Nuclear Regulatory Research, 328 p

Before analysis, an pre-reduction of CuO phase to Cu0 was performed in a flow mixture of 5%H2-N2, raising the temperature at a heating rate of 10˚C/min from room temperature up to 290˚C.
Cu0 surface area, particle size and degree of sintering were calculated from N2O decomposition data [6].
Results and discussions Fig. 1 XRD patterns of Cu/ZnO catalysts before reduction: a CP Cu, b PM 60Cu-40Zn, c CP 60Cu-40Zn; and after reduction: c CP Cu, d PM 60Cu-40Zn, e CP 60Cu-40Zn.
XRD patterns of diversified copper catalysts before and after reduction are shown in Fig. 1.
Moreover, ZnO could hinder Cu0 from sintering for the migration, aggregation of Cu0 particles due to local overheating in the processes of reduction and reaction.

The oxide thickness was estimated from capacitance-voltage (C-V) data and a profile meter.
This is revealed from C-V data and thermally stimulated current measurements (TSC) on n-type reference capacitors.
Fig.3: C-V data of a N2O grown n-type MOS structure and wet oxide reference capacitor.
Fig. 4: Interface state density extracted from the C-V data in Fig. 3.
Fig. 7: Interface state density extracted from CV data of n-type MOS capacitors showing the effect of the RTP anneal.

The problem of radial distribution control for burden material as based on the data of radial gas distribution consists in the significant delay of control actions caused by stepwise formation of the proper structure of burden column as the determining factor for gas flow formation process.
This is supported by experimental data obtained from the researches of physical models of throat and on the operating blast furnaces by means of monitoring instruments for surface texture and column structure of burden.
The monitoring of burden surface was carried out on 24-hour basis according to two mutually perpendicular diameters of the throat with automated recording of the most useful data.
The information about the axes of point position for units 1 and 2 is provided by angular sensors 6, 7 and is transmitted to the computing unit 8, the latter determines the incompatibility level for axes of point of the units in the plane to provide its automatic minimization by means of monitoring system 3, it also determines and registers the position data for the checked burden surface.
The algorithm consists in automated search of maximum correlation conditions for two proper arrays of data from the scanners created for one or some geometric profiles of the burden surface.

The data used in this study is a topographical map scale of 1: 25,000, satellite imagery and Google Map TM 1996, 2002, 2007, 2011, and 2014, as well as secondary data from relevant agencies.
The collection of data is to get the data used as the basis for simulation modeling.
Data obtained from the previous studies and agencies.
Each of these sub-models must be calibrated and validated in advance with the existing data.
This model can be used to predict the condition of the land area changes for the next 20-30 years because this model is based on the data 20 years ago.

Orthogonal wavelet decomposition and wavelet noise reduction methods are used to separate shock component from test results.
A NI type data acquisition instrument, with PXI-4472 boards and PXI-6250 boards is used to measure acceleration and strain.
Fig. 3 Measured point arrangement Test Results And Data Analysis Method Time-domain results.
Typical time history of measured acceleration in the vertical direction is shown in Figure 4. the response before time 2.048s is just caused by the diesel engine operation and data frequency is complex.
Fig. 9 Shock acceleration response of point 3 Summary The shock test method of marine diesel engines to underwater explosion include measurement points arrangement, hardware configuration of the test system, data processing methods and so on.

And in recent years, along with the trends of a global energy saving and carbon reduction, the concept of producing green products with low-carbon, water saving, energy abating, pollution decreasing attributes has arisen.
The printing process is the textile printing via digital data processing through the scanners and digital imaging machines etc to input devices.
The samples adopt the color blocks drawn by the three primary colors and match with four different inks to print respectively on the fabrics in cotton, silk and polyester fiber, and then analyze data after being measured by spectrophotometer. 4.1 Comparison between nano ink and reactive ink digital printing applied to cotton fabrics Apply nano ink and reactive ink digital printing to cotton fabrics.
Collect pictures of theme image and transform them into design sketches, fabrics, data search, analysis, and then confirm the design.
Therefore, this study, primarily through the Nanotechnology with green environmental protection and reduction of carbon from Mimaki Engineering Co.

The system can provide for a safe and effective collection of the relevant data about sludge treatment and disposal.
Besides the above characteristics, the whole process chain managerial strategy of sludge treatment and disposal can collect the data for all aspects and stages and to meet the requirements of data reporting system.
As is shown in Figure 2, the data platform of sludge treatment and disposal collects the data from the WWTPs to the final disposal, including the amount of predicted sludge in WWTPs, sludge production, transportation, and disposal, etc.
The operating diagram of data platform of sludge treatment and disposal The data platform of sludge treatment and disposal is an effective system that can be used to manage and guide the planning, track the problem for short-term, and adjust the ability for long-term.
The data platform of sludge treatment and disposal collects the data from the WWTPs to the final disposal, including the amount of predicted sludge in WWTPs, sludge production, transportation, and disposal, etc.

The quantitative emission data for sub-sites or any selected area were used for more precise ranking, for differentiation between point and diffuse sources and also for the estimation of the metal load on the watershed.
By the elimination of any of the sources or by the reduction of their emission we can simulate the results of the remediation and predict its effect on the Toka-water.
The calculation of the Risk Quotient (RQ = PEC/PNEC = the ratio of the Predicted Environmental Concentration and the Predicted No Effect Concentration), predicting the contaminant concentration from measured data and comparing it to generic or site specific No Effect data, e.g. limit values or other environmental quality criteria.
From the results of the Soil Testing Triad, the most suitable remediation (risk reduction) method can be also selected and planned.
Reduction in the mobility of Cd and Zn was the most efficient with fly ashes A and B: 99-99,9 % in the water extract and 60-80 % in plant uptake.