Electrochemical determination of chemical oxygen demand using Ti/TiO2 electrode.

To overcome the shortcomings of the conventional potassium dichromate method (PDM) for monitoring chemical oxygen demand (COD) of waters, many efforts have been made on developing quick and environment-friendly techniques. Among all alternatives, electrochemical (EC) techniques are very competitive due to their relatively simple devices and quickness. A number of electrodes have been fabricated to investigate electrochemical determination of COD. However, little work has been reported on Ti/TiO2 based electrode for this purpose. In the present work, Ti/Ti/TiO2 electrode was simply prepared by anodic oxidation of pure titanium. Aqueous solutions of potassium hydrogen phthalate and phenol were electrolyzed by chronocoulometry in a three-electrode system with Ti/Ti/TiO2 as working electrode (anode). Organic compounds were electrochemically oxidized on Ti/Ti/TiO2 electrode by hydroxyl radicals and the released electrons were recorded and transferred to currents. The electric currents were proportional to the COD values of the water samples being investigated. Based on data of COD values and corresponding currents, a linear regression equation was obtained for a certain kind of waste water. With the regression equation, current of an unknown water sample was transferred to its COD value. Conditions for the presented EC method were set up as cell voltage 2.0V v.s. SCE and pH 7.0. The linear range of COD was of about 25~530 mg/L. COD values of real waste water samples were measured by Ti/Ti/TiO2 electrode and the relative errors were all in the range of ±8% compared with data determined by conventional PDM. The electrochemicalmethodology was successfully applied to evaluate COD in waste water

Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

Background: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. Methodology: We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. Conclusions: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents

Surface-Enhanced Infrared Absorption of o-Nitroaniline on Nickel Nanoparticles Synthesized by Electrochemical Deposition

Nickel nanoparticles were electrochemically deposited on indium-tin oxide (ITO) coated glass plate in a modified Watt’s electrolyte. The surface-enhanced infrared absorption (SEIRA) effect of the nanoparticles was evaluated by attenuated total reflection spectroscopy (ATR-FTIR) using o-nitroaniline as a probe molecule. Electrodeposition parameters such as deposition time, pH value, and the type of surfactants were investigated. The morphology and the microstructure of the deposits were characterized by the field emission scanning electron microscope (FESEM) and the atomic force microscope (AFM), respectively. The results indicate that the optimum parameters were potential of 1.3 V, time of 30 s, and pH of 8.92 in the solution of 0.3756 mol/L diethanolamine, 0.1 mol/L nickel sulfate, 0.01 mol/L nickel chloride, and 0.05 mol/L boric acid. The FESEM observation shows that the morphology of nickel nanoparticles with best enhancement effect is spherical and narrowly distributed particles with the average size of 50 nm. SEIRA enhancement factor is about 68

Application exploration of MBSE in the development process of airborne electromechanical computer

With the development of multi electrified and intelligent aircraft system, the high integration, the system architecture and interface design of airborne electromechanical computer are becoming more and more complex, the development cycle cost is increasing, and the quality problems are becoming increasingly prominent. In view of the severe quality form of airborne electromechanical computer, a model-based system engineering method is proposed to solve complex problems in this paper, which describes the behavior process of system development in a model and standard graphical way. This paper realizes the localization of the MBSE in the development process of airborne electromechanical computer, which improves the quality by putting de verification link in front and can be used as a reference for other complex computer systems

Synthesis of graphene from dry ice in flames and its application in supercapacitors

We have synthesized graphene by reducing carbon dioxide in magnesium and calcium metal flames. The as-prepared graphene has been used as conductive additive to improve the electrical conduction of activated carbon-based supercapacitor electrodes. The graphene/activated carbon composite electrode showed an outstanding specific capacitance of 220 and 180 F g (1) at a current density of 0. 1 A g (1) in 6 M KOH electrolyte when using graphene obtained in magnesium and calcium flames, respectively. (C) 2013 Elsevier B.V. All rights reserved

Triangle Water Index (TWI): An Advanced Approach for More Accurate Detection and Delineation of Water Surfaces in Sentinel-2 Data

One of the most basic classification tasks in remote sensing is to distinguish between water bodies and other surface types. Although there are numerous techniques for extracting surface water from satellite imagery, there is still a need for research to more accurately identify water bodies with a view to efficient water maintenance in the future. Delineation accuracy is limited by varying amounts of suspended matter and different background land covers, especially those with low albedo. Therefore, the objective of this study was to develop an advanced index that improves the accuracy of extracting water bodies characterized by varying amounts of water constituents, especially in mountainous regions with highly rugged terrain, urban areas with cast shadows, and snow- and ice-covered areas. In this context, we propose a triangle water index (TWI) based on Sentinel-2 data. The principle of the TWI is that it first analyzes the reflectance values of water bodies in different wavelength bands to determine specific types. Then, triangles are constructed in a cartesian coordinate system according to the reflectance values of different water bodies in the respective wavelength bands. Finally, the TWI is achieved by using the triangle similarity theorem. We tested the accuracy and robustness of the TWI method using Sentinel-2 data of several water bodies in Mongolia, Canada, Sweden, the United States, and China and determined kappa coefficients and the overall precision. The performance of the classifier was compared with methods such as the normalized difference water index (NDWI), the modified normalized difference water index (MNDWI), the enhanced water index (EWI), the automated water extraction index (AWEI), and the land surface water index (LSWI). The classification accuracy of the TWI for all test sites is significantly higher than that of these indices that are commonly used classification methods. The overall precision of the TWI ranges between 95% and 97%. Moreover, the TWI is also effective in extracting flooded areas. Hence, the TWI can automatically extract different water bodies from Sentinel-2 data with high accuracy, which provides also a favorable analysis method for the study of droughts and flood disasters and for the general maintenance of water bodies in the future

Triangle Water Index (TWI): An Advanced Approach for More Accurate Detection and Delineation of Water Surfaces in Sentinel-2 Data

One of the most basic classification tasks in remote sensing is to distinguish between water bodies and other surface types. Although there are numerous techniques for extracting surface water from satellite imagery, there is still a need for research to more accurately identify water bodies with a view to efficient water maintenance in the future. Delineation accuracy is limited by varying amounts of suspended matter and different background land covers, especially those with low albedo. Therefore, the objective of this study was to develop an advanced index that improves the accuracy of extracting water bodies characterized by varying amounts of water constituents, especially in mountainous regions with highly rugged terrain, urban areas with cast shadows, and snow- and ice-covered areas. In this context, we propose a triangle water index (TWI) based on Sentinel-2 data. The principle of the TWI is that it first analyzes the reflectance values of water bodies in different wavelength bands to determine specific types. Then, triangles are constructed in a cartesian coordinate system according to the reflectance values of different water bodies in the respective wavelength bands. Finally, the TWI is achieved by using the triangle similarity theorem. We tested the accuracy and robustness of the TWI method using Sentinel-2 data of several water bodies in Mongolia, Canada, Sweden, the United States, and China and determined kappa coefficients and the overall precision. The performance of the classifier was compared with methods such as the normalized difference water index (NDWI), the modified normalized difference water index (MNDWI), the enhanced water index (EWI), the automated water extraction index (AWEI), and the land surface water index (LSWI). The classification accuracy of the TWI for all test sites is significantly higher than that of these indices that are commonly used classification methods. The overall precision of the TWI ranges between 95% and 97%. Moreover, the TWI is also effective in extracting flooded areas. Hence, the TWI can automatically extract different water bodies from Sentinel-2 data with high accuracy, which provides also a favorable analysis method for the study of droughts and flood disasters and for the general maintenance of water bodies in the future