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Data analysis.
Statistical analysis of the data was performed with Duncan’s method at 5% level, using the Version 16.0 of the SPSS software package.
Table 2 Effect of ammonium and nitrate ratio on Vc content (mg·100g-1 FW) of Chinese kale NH4+:NO3- Zhonghua Lvbao Zhongchihua Leaf Stalk Leaf Stalk Leaf Stalk 0:100 61.3±1.8 a 75.2±2.2 a 62.4±1.1 a 102.8±3.4 a 35.2±1.3 a 52.6±1.2 a 25:75 52.8±1.4 ab 75.5±1.7 a 63.5±1.1 a 83.7±0.9 b 30.9±1.5 ab 51.5±2.8 ab 50:50 43.4±6.2 bc 65.4±1.5 b 44.7±3.3 b 74.8±1.3 c 25.8±0.9 c 45.6±2.7 bc 75:25 33.8±1.7 c 64.4±2.8 b 43.5±2.3 b 70.4±0.9 c 28.3±1.7 bc 38.9±0.6 c Note: Data in the table were average ± standard error (n=3), and different letters in the same row indicated significant difference at 5 % level (Duncan’s method).
Table 5 Effect of ammonium and nitrate ratio on soluble protein content (mg·g-1 FW) of Chinese kale NH4+:NO3- Zhonghua Lvbao Zhongchihua Leaf Stalk Leaf Stalk Leaf Stalk 0:100 12.01±0.13 b 1.30±0.07 c 9.65±0.05 d 2.13±0.22 b 6.12±0.12 c 0.61±0.11 c 25:75 14.74±0.11 a 2.29±0.15 b 11.56±0.10 c 2.84±0.10 a 6.87±0.13 b 1.23±0.10 b 50:50 12.39±0.21 b 3.82±0.02 a 12.86±0.07 b 3.04±0.28 a 7.51±0.13 a 1.65±0.12 a 75:25 12.35±0.73 b 2.57±0.09 b 14.04±0.15 a 3.47±0.12 a 7.29±0.21 a 1.94±0.08 a Discussion The result showed that 50% and 75% enhancement of ammonium treatments significantly reduced Vc content, while the reduction was not significant for 25% ammonium enhancement treatment, compared with complete nitrate treatment.

Observations and force measurements on plant surfaces with fine roughness have demonstrated a strong reduction in the adhesive force exerted on insects [8].
Here we chose totally 20 female drosophilas to collect their adhesive force data.
Results and discussion The adhesive force data tested on the different friction plates was shown in Fig. 5.
Conclusion The self-designed lever-like testing equipment was invented to successfully test accurate adhesive force data.

From the data of Fig. 3b, the applied stress can be derived from the applied bending force and this can be plotted against the amount of flattening.
This is a reduction due to the softening process.
Firstly, it can be seen that the data points exhibit a bi-modal behavior.
The mechanical characterization data presented result from the complex interplay of heat transfer, cellular transformation, and viscoelastic mechanisms as verified by other investigators.

One formula describing the relationship under various conditions was proposed based on the experimental data, which would be helpful for the operation of PID in practice.
The reason for this phenomenon was that large volumetric flow rate led to large workload and reduction of the screening efficiency.
Based on the experimental data, the regression analysis could be easily got using SAS.
Fig. 4 Fitting results based on dimensional analysis when viscosity is 35 mPa·s As shown in Fig. 4 and 5, the curves fit well with the experimental data and the trend is that the loss rates of steel particle increase with the increasing volumetric flow rate, viscosity and steel particle ratio.

Statistical Analysis The distribution of the data was calculated by the Kolmoforov-Smith test and the variables were analyzed using One-way ANOVA.
Chemical Properties Wire Composition The amounts of elements of commercial orthodontic wire were the same as in Brantley’s study and SUS 304H (Table 3) was compared with the data sheet [9-10] as SUS 304H stainless steel type.
[5] Siriwat Chamnunphol, Influence of reduction ratio of cross sectional area in drawing stainless steel wire for orthodontic use, 2008
Sanmayer Steel Company [10] Product data sheet 304/304L STAINLESS STEEL AK Steel Corporation 2007 [11] Bela leffler.

Navid et al [3] asserted that dynamic loads such as impact and drilling process caused significant reductions in the composites stiffness and strength.
Once all the data have been measured, the volume fraction was calculated using Eq.1.
Tensile stress-strain curves for woven and stitch bi-axial composites Flexural properties The average flexural properties data for woven and bi-axial composites are depicted in Table 3.
Flexible properties for different batch of GFRP specimens Sample Woven Fiber Bi-axial (±45°) Fiber Ultimate Flexural Strength (MPa) Flexural Modulus (GPa) Ultimate Flexural Strength (MPa) Flexural Modulus (GPa) 1 304.64 21.25 168.80 11.79 2 341.64 20.07 130.09 10.61 3 312.58 19.68 128.60 10.36 4 320.17 21.15 120.26 8.73 5 311.88 19.80 104.51 7.85 Mean 318.18 (±12.72) 20.39 (±0.67) 130.45 (±21.22) 9.87 (±1.40) Residual tensile properties The average residual tensile strength data for woven and bi-axial for both types of drill are shown in Table 4.

Table 1 Input data considered in Helical Gear design Parameters Values for Helical Gear Pair Density of the material : 40Ni2Cr1Mo 28 8.836×106 kg/mm3 Allowable bending stress / crushing stress 400 N/mm2 / 1100 N/mm2 Young’s modulus of the material 2.15x105 N/mm2 Co-efficient of friction 0.08 Ratio between thickness and center distance (ψ) & Ratio between the thickness and module (ψm) 0.3 / 10 Design constraints are to be considered for the design of above helical gear are, crushing stress, bending stress, center distance, normal module, gear ratio and number teeth on pinion represented in Eq. 8, Eq. 9, Eq. 10, Eq. 11, Eq. 12 and Eq. 13.
Results and Discussion The complete optimization problem of helical gear pair have been formulated in terms of design variables and the optimum values of the objective functions for Power, Weight, Efficiency and Center distance and the design variables (m, b, z and P) influencing the objective functions are obtained with respect to the minimum COF value by implementing the input data provided in Table 1.
Weight reduction reduces the amount of material consumed while manufacturing the component.
[10] PSG College of Technology: Design Data Book, (Kalaikathir Achchagam, Coimbatore, 2008) [11] Baskar N, Asokan P, Saravanan R and Prabhakaran G: International Journal of Advanced Manufacturing Technology Vol.25 (2005), p. 1078-1088

The data was collected by TDS602 static data acquisition instrument.
The steel plate with 20mm thick and 100mm wide was processed into the fixture as shown in Fig. 3, the inner size of the fixture is 100mm×400mm×400mm, the aerated concrete block was stuck by the upper part and bottom part of the fixture, the two parts of the fixture was hinge jointed by steel bar of 10mm diameter at the corner, the bottom part of the fixture was welded on the base, the upper part of the fixture was constrained by steel bar, the organization with horizontal free movement was formed, the horizontal load apply point and displacement data collect point was set on the two upper corner of the fixture [6].
Zhang, Research on the seismic mechanism of triple fortification lines and the method of displacement-based damage-reduction control design for the improved MRSS, Beijing Jiaotong university, (2009) 55-71

A reliable and reproduce characteristic fingerprint of coffee flavor was established [4] and a group data of retention time (RT) of coffee flavor were obtained based on this method.
Experimental section Data preparation.The experimental values for the retention time of coffee flavor compounds are taken from the literature [4].
The data set is randomly separated into a training set of 36 compounds and a test set of 16 compounds.
After the heuristic reduction, the pool of descriptors is reduced to 160.

This results in reduction of insulator contamination resistance lead to the development of leakage current.
Generally, this capacitance value is about 1 – 8 µF -Then input the data in Fig. 5.
Table 1 Data from TINA simulation A B String efficiency = 66.92 C string efficiency = 58.45 D String efficiency = 53.71 E F String efficiency = 90.42 G String efficiency = 87.03 H String efficiency = 78.35 Table 2 Data from sphere gap measurement method A B String efficiency = 69.12 C String efficiency = 62.67 D String efficiency = 57.04 E F String efficiency = 76.36 G String efficiency = 66.69 H String efficiency = 59.76 A: Figure of clean insulator/string without guard ring condition.