Potentiometric sensors with plastized poly(vinyl chloride) membranes selective to penicillin antibiotics: Properties and applications

Potentiometric sensors with plasticized poly(vinyl chloride) membranes based on β-lactam–tetraalkylammonium ion associates sensitive to penicillin antibiotics are proposed. The physicochemical characteristics (solubility product constants and dissociation constants) of active membrane components and the electrode, transport, and selective properties of the membranes of liquidand solid-contact sensors have been studied. The quantitative characteristics of membrane transport (penetrability, ion flux, and transport rate) have been evaluated. The main charge carriers in the membranes and at the membrane/solution interface have been determined from the membrane transport characteristics. The potentiometric sensors are shown to be applicable to the determination of penicillin antibiotics in biological fluids (blood serum and oral fluid) from patients with urinary tract infection.     

Measuring equipment and test bench to control evolution of acoustic-deformation and heat fields induced in solids under failure by fluids

The authors have developed a procedure and a test bench for studying evolution of various nature physical fields in modeling geomedium fracture by fluids. The test bench performs synchronous recording of macro- and micro-deformation, heat and acoustic emission induced in physical models of geomedium under loading to discontinuity. The experimental procedure has been trialed. The analysis of the synchronized test data allows a conclusion on the existence of time–space relationship between different nature physical fields induced during failure of solids.     

Production technology for low-carbon,low-sulfur boron steel

A technology for slag formation in the ladle–furnace unit is considered; the slag is based on the CaO–SiO₂–MgO–Al₂O₃–B₂O₃ system. This technology permits both microalloying of the steel with boron (reduced from the oxide phase) and desulfurization of the steel. The resulting boron content in the steel is 0.001–0.008%; the sulfur content in low-alloy steel and pipe steel is low (0.004–0.010%); and the consumption of manganese ferroalloys is reduced to 0.5 kg/t for 08кп steel and 1.4 kg/t for 09Г2C steel. In addition, the proposed technology increases the strength of the rolled steel, without loss in its plasticity; and reduces the environmental impact thanks to the replacement of fluorspar by colemanite.     

基于状态空间法的电动机故障诊断和识别

电动机的初期故障信号一般较弱,不易辨别,而状态空间法在小信号的处理中灵敏度很高。为达到对电动机故障的诊断和识别,试图把状态空间法应用到对电动机的故障诊断中,先通过推导,从数学理论层面分析了状态空间法对于电动机故障信号的可辨别性,再使用Matlab软件搭建状态空间的辨别模型,把实验台测试的三组数据导入到模型中进行测试。测试的结果有力地证明了此方法的可行性,并能克服快速傅里叶变换(FFT)中数据采集量较大、分辨率不高的缺点。     

The Spatial LASSO With Applications to Unmixing Hyperspectral Biomedical Images

Hyperspectral imaging (HSI) is a spectroscopic method that uses densely sampled measurements along the electromagnetic spectrum to identify the unique molecular composition of an object. Traditionally HSI has been associated with remote sensing-type applications, but recently has found increased use in biomedicine, from investigations at the cellular to the tissue level. One of the main challenges in the analysis of HSI is estimating the proportions, also called abundance fractions of each of the molecular signatures. While there is great promise for HSI in the area of biomedicine, large variability in the measurements and artifacts related to the instrumentation has slow adoption into more widespread practice. In this article, we propose a novel regularization and variable selection method called the spatial LASSO (SPLASSO). The SPLASSO incorporates spatial information via a graph Laplacian-based penalty to help improve the model estimation process for multivariate response data. We show the strong performance of this approach on a benchmark HSI dataset with considerable improvement in predictive accuracy over the standard LASSO. Supplementary materials for this article are available online.