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Silicon was synthesized from bamboo leaves by combustion followed by magnesiothermic reduction process.
SiO2 was reduced to Si by magnesiothermic reduction process.
Nevertheless, results from EDS data indicated that there was trace amount of magnesium in the product obtained, which came from magnesiothermic reduction process.
The XPS data in Fig. 4 declared that NrGO product has nitrogen atom embedded on graphene sheets due to the presence of C-N and C=N bonds.
In contrast, EDS data confirmed that there were silicon in NrGO/TiO2/Si 7:1:2 and NrGO/TiO2/Si 6:2:2.

When the data is analyzed, the gradient of load-strain is applied.
Equipment for wheelset the axle box measurement and save of data Title of Publication (to be inserted by the publisher) We measured and analyzed the data only in case of leading axle running.
Fig. 14 shows the measuring data according to the running distance.
Data according to the movement Fig. 15.
Speed and derailment coefficient distance The result data was shows speed and derailment coefficient by polynomial regression and gaussian(see Fig. 15) in case of the speed was over 224km/h.

This paper is focusing on the study of SRB growth using pressure sensor to measure the pressure changes in bacterial reactor [6].The whole experiment is divided into two parts, the first part is culture of SRB, and the second part is the data processing and analysis.
Diagram of sensor data acquisition Figure 7.
Temperature Compensation Circuit In the data acquisition module of the pressure sensor, in order to reduce error we take temperature compensation circuit for error.
Analysis of Experimental Results Through the test analysis, we get table 1 after data statistics.
The experimental results are consisting with computer data.

By quantifying the loss of mechanical performance, this study aims to provide essential data for optimizing the durability and reliability of critical infrastructure.
This strategy allows for (i) capturing real synergies between radiation, humidity, thermal cycles, and service loads; (ii) validating accelerated aging protocols using a field benchmark; and (iii) generating direct data for lifetime prediction models in optical and energy infrastructures.
This allows for a direct correlation between material degradation and actual operational performance in critical infrastructures, providing data of greater practical relevance for engineers and designers than mere laboratory simulation.
The observed ranges within the data (e.g., for UTS) also underline the variability inherent in field-aged samples, which can experience non-uniform exposure conditions.
Table 1 ([Insert Table 1 here, summarizing key TGA data like Tonset​, Tmax​, % residue for new and used samples]) summarizes the key thermal degradation parameters.

After the homogenization process, deformation process was performed on AlFeNiMg alloy by gradual reduction.
This condition can lead to the increase in mechanical properties, especially the strength or hardness of metal through crystal orientation. 20 μm a 20 μm b 20 μm c 20 μm d Fig. 2 Micrographs of AlFeNiMg alloy, (a) deformation at 30% reduction, (b) deformation at 53% reduction, (c) deformation at 65% reduction,(d) deformation at 88% reduction.
Based on data from reference [7 ], it is shown that the peak of FeAl3 phase is located at 2q angle at 22o, 24o, 25o, 26o, 27o, 40o, 42o, 43o, 45o, 47o, 50o, 64o, 67o, 69o, 73o, 75o, 76o, 78o, 82o, 86o, 90o and 93o.
After deformation the hardness values are 113 HV at 30% reduction, 135 HV at 53% reduction, 153 HV at 65% reduction and 165 HV at 88 % reduction.
[7] Anonymous, PDF Card, International Center For data Diffraction, 2008

Based on user behavior analysis, using the information of data warehouse will be a reasonable quantification of qualitative indicators, draw the user a variety of potential semantic behavior, and user clustering and dimension reduction, the establishment of a recommendation based on user behavior analysis model .
Data Mining.
Data Warehousing and Data Mining for Telecommunications[M]ARTECH HOUSE，1997
Principles of Data Mining [M].
Data Preprocessing and Dimension Optimization in Data Mining [J].

Conditions of Result Approach while using Airfoil's Measurement Data for Calculation of Wing's Lifting Force E.
Another possibility to take into account the non-linear section data in wing calculation is presented in research by Jacob 0.
The method combines numerical solution of lifting-line theory and a special approach to evaluating nonlinear section lift data.
So, the change in the plate's setting angle is determined by an iterative procedure from known sectional non-linear data.
In general, calculated sectional data can be used as well as the wind tunnel measurement data of aerodynamic coefficients of known airfoils

Introduction Aircraft drag reduction and environmental protection both are hotspot of current research, it’s an important part of the research that using wing tip devices to reduce drag of the wing.
The paper provided the aerodynamic benefit brought by winglets, in order to Indicate the important significance of winglet in energy saving and emission reduction, provide theoretical basis for airline decision-making.
Aerodynamic model The paper used CATIA to model surfaces According to the airfoil’s basic data, and then grid the model by using Fluent Pretreatment Software.
Fig.4 Mach number distribution on the upper surface of the wing added winglet(attack angleα=0) Fig.5 Maher number distribution on the upper surface of the original wing (attack angle α=0) The results are further processed such as shown in Table 3, the increase rate RL and drag reduction rate Rd defined as follows
[2]Tang Deng-bing, Qian Jia-xiang,in:The application and development of drag reduction device, edited by Journal of Nanjing University of Aeronautics & Astronautics,China (1994),in press

Based on a lot of inspected track irregularity data, the reference [2] proposed a set of general track spectra of Chinese main railway lines (ChinaRLS).
All the time series simulated track vertical profile irregularities are shown in Fig.3 by box and whisker plot, in which the height of every group represents the numerical range of the data, and the “boxes” represent the 25th through the 75th percentile and the horizontal line inside the box is the median value (or the 50th percentile).
According to Fig.5, the sequence of the rates of wheel load reduction of locomotive is the 200km/h of ChinaRLS < the 120km/h of ChinaRLS < the 160km/h of ChinaRLS < the 6th of AmericaRLS.
The sequence of rates of wheel load reduction of vehicle is the 200km/h of ChinaRLS < the 160km/h of ChinaRLS, while the values of the rates of wheel load reduction caused by the 120km/h and the 6th are 1, which are beyond the limits of derailment.
If those abnormal data are excluded, the order of size of the wheel-rail interaction forces of vehicle is similar to locomotive.

In the whole frequency range, the noise-reduction ability of transverse grooved concrete pavement is the worst.
Fig. 3 Noise testing results for concrete pavements with different texture It can be seen through the data in the graph: (1) The noise level of concrete pavement with the transverse spacing groove is the highest, whose noise level is higher than 2.6 to 4.3 db compared with the same longitudinal groove parameters of concrete pavement
For a frequency larger than 1600HZ, porous concrete pavement has stronger noise-reduction ability.
In the whole frequency range, the noise-reduction ability of transverse grooved concrete pavement is the worst
Cackler: Evaluation of U.S. and European Concrete Pavement Noise Reduction Methods[R].