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Data were processed with the Microsoft Excel software and Origin8.0.
Actually, the Cu and Pb concentration in the shoots of R. acetosa was reduced from the maximum at the second stage to 4.00 mg/kg and 2.56 mg/kg at the fourth stage, representing a reduction of 69.9% and 73.6%, respectively.

Table 2 Variation of pH during the process of fermentation Material Group 1st day 2nd day 3rd day 4th day 5th day 6th day 7th day Calcium Sulfate 1-1 3.76 3.44 3.34 3.22 3.20 3.16 3.15 1-2 3.75 3.43 3.33 3.23 3.19 3.16 3.15 1-3 3.81 3.44 3.34 3.24 3.20 3.19 3.16 1-4 3.78 3.47 3.33 3.24 3.19 3.18 3.17 1-5 3.82 3.46 3.35 3.24 3.19 3.17 3.17 1-6 3.81 3.47 3.34 3.24 3.19 3.18 3.18 Lime 2-1 4.39 3.75 3.59 3.50 3.44 3.41 3.40 2-2 4.30 3.76 3.62 3.50 3.45 3.43 3.43 2-3 4.38 3.76 3.61 3.49 3.43 3.42 3.42 2-4 4.35 3.76 3.61 3.49 3.44 3.43 3.43 2-5 4.49 3.75 3.60 3.49 3.44 3.42 3.42 2-6 4.56 3.78 3.64 3.52 3.47 3.45 3.45 Gypsum 3-1 3.92 3.50 3.38 3.28 3.22 3.21 3.21 3-2 3.89 3.50 3.37 3.27 3.22 3.20 3.20 3-3 3.86 3.48 3.36 3.26 3.20 3.19 3.19 3-4 3.85 3.48 3.35 3.27 3.21 3.20 3.20 3-5 3.89 3.49 3.33 3.26 3.20 3.19 3.19 3-6 3.83 3.46 3.58 3.25 3.35 3.19 3.19 Variation of EC during the process of fermentation As was displayed in Table 3, the EC decreased with the reduction of Ca2+ concentration
The tested data showed that: EC of 2.0 ‰ Ca2+ Lime Group was 4.4% lower than the 2.0 ‰ Ca2+ Calcium Sulfate Group, and 8.2% lower than 2.0 ‰ Ca2+ Gypsum Group, respectively; EC of 1.6 ‰ Ca2+ Lime Group was 13.2% lower than the 1.6 ‰ Ca2+ Calcium Sulfate Group, and 7.9% lower than 1.6 ‰ Ca2+Gypsum Group, respectively; EC of 1.0 ‰ Ca2+ Lime Group was 6.7% lower than the 1.0 ‰ Ca2+ Calcium Sulfate Group, and 2.3% higher than the 1.0 ‰ Ca2+ Gypsum Group, respectively.

Figure. 1 a) with a 64-1 reduction box driving 1mm pitch ball screws (Automation Ltd., Oldham, UK) was used to drive the extruder for the paste.
So many data around the ratio (R/r)2 were tested to find out the optimal Vr and Vxy.

(Ps, because of difference from different scholars’ data source and calculation method, the result is slightly different.
It caused wetland large reduction in degradation and severe water shortage, for example, the quantity of annual water shortage in Qilihai wetland has reached 34.93 million cubic meters.

Strain Strain rate [s-1] Temperature [°C] Fracture 0.1 25 200 400 600 700 800 900 Fracture 1 25 200 400 600 700 800 900 The data recorded by the Aramis™ system includes also the normal anisotropy coefficient r, calculated at a strain equal to 0.1.
In Fig. 4a, the normal average anisotropy results are reported: the temperature increase from room temperature to 600°C causes a reduction of anisotropy, whereas, at temperatures higher than 600°C, the material acquires again its anisotropic characteristics.

The evaluation of the stress-strain data recorded during the displacement controlled loading sequences allowed the calculation of cycle-dependent stiffnesses measured under conditions comparable to quasi-static loads in a nearly linear elastic stress-strain area.
This offers the potential for a reduction of experimental test time since the fatigue behaviour of multidirectional lay-ups with different stacking sequences can be calculated based on the parameters of the single ply as long as they are made of the same material.

The TiNi sheets were produced by coldrolling with a thickness reduction of about 22%.
Three groups of data are selected to discuss among the experiment results.

(b) Single nanoelectrodes; (c) Multiple nanoelectrodes; (d) Gap design for size expansion; (e) Bridge design for size reduction.
The data and results obtained are based on the optical characterization by using high power microscopy as in fig.6.

The identification of A, m and n parameters was performed by Aurock using a semi-direct algorithm based optimisation procedure fitting a tensile test numerical model to experimental data provided by ENSAM Angers following test requirements from Airbus.
A second analysis introduces a Ti6Al4V martyr sheet in order to optimise the Ti-6Al-2Sn-4Zr-2Mo sheet geometry (cost reduction) and to minimise thinning at the end of SPF process. 3D Analysis for SPF Process Optimisation.

Principal coordinates (PCA) analysis with a Jaccard similarity matrix was used on binary data generated from T-RFLP profiles to obtain an ordination diagram.
Aerobic methane oxidizing bacteria in an oxidizing methane generated a series of intermediate: methanol, formaldehyde, formate, and methane oxidation intermediates, can be heterotrophic denitrifying bacteria use, as the electron donor of the nitrate reduction (aerobicoxidative coupling of methane denitrification AME-D), while consuming oxygen cause hypoxic environment [4, 16], so the methane oxidation to denitrification promote denitrification, and lower C / N ratio is good AME-Dprocess [16].