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Reduction of BAP concentration through dilution of CTP with a polymer suppressed carcinogenicity [4].
The results showed a substantial reduction of the BAP content in CTP when polyetherols of varying molecular weight were reacted with BAP.
Zielinski et al. [7] studied the effect of poly(ethylene terephthalate) (PET) process waste product on the reduction of BAP content in CTP.
Wavelength scanning method was taken to measure, the wavelength range was set between 200 nm ~ 400 nm, wavelength interval was set as 0.1 nm and wavelength-absorbance data was saved in the computer.

Consequently, the high concentration of CO2 stream produced by the oxy-fuel combustion, leads to a considerable cost reduction for CO2 separation and compression [4].
In addition, due to the high concentrated and pressurized CO2 rich stream, Pressurized Oxy-Fuel Combustion results in considerable CO2-compression costs reduction.
Further benefits are the reduced need heat exchange surfaces, and equipment volumes, which immediately turn in an overall plant cost reduction.
A wide amount of AFT data are available in literature, but lots of this studies are not reliable for the prediction of slag behaviour in the ISOTHERM process since results were obtained under firing atmospheres fairly different from the actual processing conditions typical of an oxy-combustion reactor.

To obtain the necessary information about the components of the cutting forces, a universal strain-gage dynamometer UDM-600, equipped with interface and software for processing the experimental data was used.
These features include: ● High level of contact (especially normal) stresses generated on the rake surface of carbide tool due to intensive reduction of the length of contact area and significantly less intense reduction of normal loads acting on the rake face; ● Concentration of thermal stresses on the contact areas of the rake and flank surfaces of the tool that arises because of extremely low thermal conductivity of solid carbide and high coefficient of its thermal expansion; ● Virtually complete absence of stagnant zone of material to be machined and, if any, generation of a knob that performs the functions to protect contact areas from wear.
Chemical composition of wear-resistant layer of MCC (system Ti-TiN-TiCrAlN) Experimental data on the evaluation of the crystal chemical properties of the developed MCCs reveals the following.
The analysis of the data reveals the following.
Dependence of wear HBmax of carbide mills of cutting time of titanium alloy WT9 with ap=1.0 mm, ft =0.05 mm/tooth; v = 157 m/min: 1  WRC-15; 2  WRC-15-ZrN (arc-PVD); 3-  WRC-15-ZrCrAlN (arc-PVD); 4  WRC -15-Zr-ZrN-ZrCrAlN (FCVAD) These data find out that during machining by mills without coatings, length of cutting path and volume of removed material are low, and machining with high and medium cutting speeds is possible.

Reductions of 20 pct., 30 pct., 40 pct., and 50 pct., were achieved using a ~5 pct. reduction per pass without observable damage to the starting material.
The stress and strain measurements, parallel to the load line, and resultant mechanical properties of (i) strength (yield strength and ultimate tensile strength), and (ii) ductility quantified by strain-to-failure were determined by analyzing the load and strain data acquired during testing using Bluehill software.
For purpose of reference and to facilitate comparison the conventional AA 5083 in both the O and H131 tempers (before and after annealing), these data are also included.
The test data reveals a rapid loss of ductility of the conventional AA 5083, and a similar rate of increase of the ultimate tensile strength.
Table 1: Nominal chemical composition of aluminum alloy 5083 (in weight percent) Cr Cu Fe Mg Mn Si Ti Zn Aluminum 0.20 0.1 0.4 4.4 0.5 0.4 0.15 0.25 Balance Table 2: Mechanical properties, grain size and dislocation density data for cryomilled, UFG plate and conventional AA 5083.

To single frequency vibration acceleration at collected experimental data is analyzed, then based on the experiment selected the sensitivity of acceleration sensor, charge amplifier and output gain and filtering the gain of amplifier circuit, and finally determine the acceleration deviation E actual theory domain for (0.8 V, 0.8 V).
Test results When air spring initial height is 9.5 inches, Corresponding reform of the experimental data processing can be controlled before and after single frequency excitation, vertical acceleration root mean square value of sprung mass and the peak vertical acceleration of sprung mass, as shown in table 1.
Table 1 Comparison of experimental results under single frequency excitation Peak value of sprung mass acceleration in vertical vibration(m/s2) frequency 1.5Hz 4Hz 6Hz 7Hz 8Hz Control before 0.8052 0.3204 0.3395 0.3969 0.4323 Control later 0.6169 0.1984 0.3410 0.2513 0.3348 Can be seen from table 1, in the 1.5 Hz silent resonance and 4 ~ 8 Hz vibration frequency range, through the air spring after the electronic control unit to control the vertical acceleration of sprung mass has a different degree before the control is reduced, to facilitate control of vibration reduction effect is superior to exert control.

In this situation, standard times are determined: o by rate-clerks or technologists basing on their experience; o on the basis of survey data on actual use of work day when performing analogous operations of jobs; o for the entire job or operation not dividing it into elements.
The experience-based – statistic technique does not take into account the labour-intensity reduction reserves at the workplace wherewith the obtained standard times allow for deficiencies in the work process technology, organization of work and production thus not stimulating increase in productivity.
The collected data have been summarized and organized for further processing.

The Poisson’s equation may be solved by different mathematical methods: minimization of a certain specially selected functional [4]; assignment of boundary conditions by three directions; reduction of equation (1) to solving three one-dimensional differential equations.
Preference should be given to the grid regular topology and elements in the form of hexahedrons. 3D geo-seepage model is calibrated basing on the field observations data (read-outs of piezometers, drainage flows, etc.).
The updated seepage coefficients of separate geological features and grout curtain are computed basing on the obtained data (Fig. 2).

Orientation on the system of equations solution (2) without its reduction to the equation of type (1), that allows to avoid the assumption 𝜇𝑑 = 𝑐𝑜𝑛𝑠𝑡; 2.
Values E1, H1 derived at previous stages of calculations are used as initial data under calculation of the field in the next layer Δ𝜌2 and so on.
The results of the theoretical researches are confirmed by the experimental data and by practical realization of the obtained results.

Data for SiO2, Al2O3, TiO2, Fe2O3, CaO, Na2O, K2O and MgO were taken from FESEM results.
Data for SiO2, Al2O3, TiO2, Fe2O3, CaO, Na2O, K2O and MgO were used for the prediction.
However, EFB ratio is usually limited to 20% in coal:EFB blends to avoid further reduction of energy value.

Introduction After nearly a century with the internal combustion engine dominating the personal transportation sector, it now appears that the alternative fuel vehicle is on the verge of experiencing rapid growth in both developed and developing vehicle markets(see table1). [1-2] The rapid growth of vehicles has resulted in continuing growth in China’s oil demand. since 2009, China's automobile production and sales has been ranked first in the world, data prediction of the NDRC Energy Research Institute shows that the number of China's automobile on the road will reach 1.5 billion by 2020, the rapid growth of automobile will result in oil consumption exceeding 2.5 billion tons, accounting for the country's total oil demand in 57%, will further aggravate the carbon emissions and environmental problems, increasing difficulty of realization of China's carbon emission reduction targets [3].
This study invited 10 experts to give evaluation to index layers, through data processing, the two evaluation matrixes are: ; Evaluation vector Use following equation calculating the evaluation vector: (3) Evaluation vector and can present the index layers risk levels respectively.