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.     

On the Intracenter Relaxation of Shallow Antimony Donors in Strained Germanium

Semiconductors - Long-wavelength acoustic phonon-assisted relaxation rates for the excited 1s(T), 2p0, 2s, 3p0, 2p±, 4p0, and 3p± states of antimony donors in a germanium crystal are...     

Photovoltaic Power Supply Unit for the Basic Stations of Cellular Companies

The data on the use of solar photovoltaic plants (PVPs) for providing a reliable and guaranteed power supply to telecommunication systems and cellular communication systems in the conditions prevalent in Uzbekistan are given. The research-based structures developed by OOO MIR SOLAR and the selection of PVP elements ensuring their reliable operation are described. The main influencing factors are discussed, and the use of effective combinations of different types of panels (from monocrystalline and polycrystalline silicon) and a specially developed controller are considered.     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

Comparison of Sharp Interface to Variable Density Models in Pumping Optimisation of Coastal Aquifers

Water Resources Management - A number of models have been developed to simulate seawater intrusion in coastal aquifers, which differ in the accuracy level and computational demands, based on the...