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The aim of this work is to investigate the CCSM technical barriers towards the reduction of the process costs and the commercial utilisation of its by-products.
An autosampler (Cetac ASX-520) and a concentric glass venture nebuliser (ThermoFisher Scientific) were used and the data processing was undertaken using a Plasmalab software (version 2.5.4, Thermo-Fisher Scientific, UK).
These data need to be confirmed by XRF analysis on a larger representative sample.
The production of high-strength concrete represents the most likely route for large volume consumption of micro-silica produced during the reduction of atmospheric greenhouse by CCSM.

The data obtained in this study were analyzed by using statistical software SPSS v. 11.5 and reported as means±SD.
Then the data obtained under different treatment groups were statistically compared.
But the reduction in area is very closed to 316L.
Table 1 Mechanical properties of biomedical nickel-free stainless steel with high nitrogen Material tensile strength (Rm/Mpa) yield strength (Rp/Mpa) coefficient of elongation (A/%) reduction in area (Z) Cr17Mn15Mo2N0.42wt% 1010 800 34.5 62.5 Cr17Mn15Mo2N0.54wt% 1020 855 29 63.5 Cr17Mn15Mo2N0.60wt% 1060 905 27.5 60 316L 480 177 40 60 Fig.1 Microstructure of biomedical nickel-free austenitic stainless steel with high nitrogen Cytotoxicity test.

Silica fume is a product produced from the reduction of high purity quartz with coal in electric arc furnaces in the manufacture of silicon or ferrosilicon alloys.
The result of this concrete showed that the optimum noise reduction coefficient was at the void ratio of 25% [16].
In each sample, 2 channels were used which were placed in half span and quarter spans, allowing different data variations to be obtained.
In addition, the rigidity of porous concrete blocks is also reviewed by using natural frequency testing data, which is calculated using a formula Fn=12πkm or k=4π2mFn2.

Smart Microgrid is used to accept the distributed new energy power generation, including small hydropower, and it can realize the optimal allocation of energy, improve the power quality and power consuming efficiency, so as to promote energy conservation and emission reduction.
For the constraints given by Formula (3), exterior penalty function method is introduced, to reckon the constraints into the objective function in the form of a penalty term of penalty function, with the value of penalty factor of 100, as shown in Formula (6): (6) Optimization results According to natural lighting data of the microgrid area, using Formula (1) to calculate the output of small-scale photovoltaic power stations as shown in Figure 2.
Typical daily load factor curve of the microgrid area According to the above model and data, using MATLAB to conduct optimal calculations, use MATPOWER flow calculation program and particle swarm optimization, and then the optimized active power output of four small hydropower stations will be obtained, as shown in Figure 4.
The comparison of line loss of the system before and after optimization is shown in Table 5; we can see that the system line losses have a significant reduction as well after optimization.

Porous and ultra-light GO gels were obtained, and RGO (reduced GO) gels were also prepared by reduction with glucose.
After exfoliation and reduction of GO-PVA, the regular stacks of GO were destroyed and the diffraction peak became disappeared.
Some kinetic parameters at 30 ºC, estimated from the experimental data and Eq. (1), are listed in Fig. 3.
The experimental data were applied by the isotherm models of Langmuir Eq. (3).

The data in FTIR spectroscopy is given by the transmittance versus the wavelength.
Permeate flux and salt rejection were calculated from the recorded data.
The appearance of the C=O band is due to the effect of carboxyl group, which indicates that the reduction modification by formic acid has occurred effectively.
These two criterions are important to promote better mass transfer and prevent liquid filling the pore of the membrane which can lead to fouling and reduction in the permeate flux [11].

The cyanide concentration was increased around 10mg/L, COD reduction was achieved in 3-4 days.
It is evident from the results that incremental shift in cyanide concentration reduction in the reactor performance for a short period.
Data on cyanide concentration in the feed and effluent and cyanide removal are presented in fig.3 the influent cyanide concentration is varied as 0, 5, 10 and 15mg/L, respectively, In phaseⅠ, the effluent cyanide concentration lower than 0.5mg/L with corresponding cyanide removal of 99%; In phaseⅡ, the effluent cyanide suddently increased to 2.34 mg/L with corresponding cyanide removal of 63.96%.
Increasing cyanide concentration from 5 to 10 and 15mg/L, respectively, resulted in slightly increased VFA concentration, the influent of VFA concentration was around 250mg/L; In phase Ⅱ, it appeared that the concentration of VFA increased from229.46mg/L to 698.85 mg/L as influent cyanide concentration of around 10mg/L; In phase Ⅲ, cyanide concentration of 5mg/L result immediately in VFA increased from 586.6 to 1500.28mg/L; the influent VFA was higher than 600mg/L in most of the cases with influent cyanide concentration of 5,10 and15mg/L, respectively, data suggest that increasing influent cyanide concentration affected the activity of methanogens as evidenced by the increase in VFA concentration.

Results and discussion The data in Fig. 1 show that the viscsity decreases to a certain limit with an increase of motion velocity of fuel layers.
The anomaly in the behavior of boiler fuels viscosity is its reduction after heat treatment or relevant mechanical action.
Eliot, Boiler fuel additives for pollution reduction and energy saving, Noyes Data Corp., 1978

Such reduction could be compensated by the increase of the manganese and nitrogen contents, to maintain the typical balanced microstructure of DSS, with about the same content of ferrite and austenite.
Indeed the reduction of the nickel and mainly of the molybdenum contents seems to avoid the precipitation of intermetallic phases, very detrimental for the toughness and corrosion resistance of conventional DSS.
Thus, in the temperature range above 800°C, there is a good agreement between our results, Thermocalc calculations, Lee evaluations and other experimental data on Fe-Cr-Mn system, all indicating that, for the composition of our steel, the formation of the σ-phase is not possible and the microstructure consist of α-ferrite and γaustenite only.
This is not confirmed by 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 200 400 600 800 1000 1200 1400 1600 THERMO-CALC (2007.05.16:13.48) : DATABASE:TCFE3 W(CR)=0.22, W(NI)=1E-2, W(MO)=5E-3, W(N)=2E-3, W(C)=3E-4, W(MN)=5E-2, P=1E5, N=1; 1 1:T-273.15,NP(BCC_A2#1) 2 2:T-273.15,NP(FCC_A1#1) 1 3 3:T-273.15,NP(LIQUID) 1 3 1 2 12 4 4:T-273.15,NP(HCP_A3#2) 1 2 4 5 5:T-273.15,NP(M23C6) 1 2 45 6 6:T-273.15,NP(SIGMA#2) 1 4 5 6 1 7 7:T-273.15,NP(FCC_A1#2) 45 6 18 8:T-273.15,NP(BCC_A2#2) 7 45 6 TEMPERATURE_CELSIUS Molar Fraction of Phase 2007-05-16 13:48:14.40 output by user Massimo from PELLIZZARIPC 2 1    L Cr2N  our results or by Lee evaluations [7] and other experimental data [8, 9].

This last classification is a combination of the analytical methods with real data of the building obtained experimentally (mechanical and dynamic information).
This experimental data is a valuable tool for the calibration (or updating) of the model, obtaining more reliable results towards the real seismic performance of the structure.
Results showed that the ultimate load capacity and ductility could be improved satisfactory depending on the prestressing level and the device, allowing with this the vulnerability reduction of the towers (seismic risk mitigation).
Even when SMAs combined with AFRP showed less stiff behavior compared to prestressing steel, results interesting to conclude that this combined device allowed less change (increment + and reduction -) of the prestressing force in the order of ± 5%, compared to prestressing steel with a change of ± 20%.