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The article deals with the study of the possibility of using AlB12--50 wt.% Al aluminium-matrix composite material electric spark (ES) coatings to protect titanium alloys during wear under fretting. Fundamental possibility of such coatings obtaining is estimated by theoretical calculation of Palatnik's criterion (1.22). Thermal conductivity coefficient and heat capacity of the composite were calculated or determined from an experiment. The coatings were deposited on ALIER-52 setup. Fretting corrosion tests were carried out on MFK-1 setup according to 'the coating--counterbody' system (counterbody--hardened Steel 45). Phase composition of the coating was studied with DRON-3M diffractometer and elemental x-ray spectrum analysis of the friction track surface was carried out using a JEOL JAMP9500F (SEM) microanalyzer equipped with an energy-dispersive x-ray microanalysis. The following phases namely TiB2, Ti aluminides, Ti, TiO, TiO2 and AlB10 were revealed by x-ray analysis in the coating. The absence of the AlB12 phase is noteworthy. It can be explained by thermal-oxidative destruction of aluminium dodecaboride under severe conditions of ES alloying (ESA). Regardless of the deposition mode, the wear of the sample with ES-coating is shown to be significantly less than that of the uncoated one. A conclusion is made about the prospect of using this electrode material for ESA of titanium alloys operating under fretting corrosion. [ABSTRACT FROM AUTHOR]

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Composite samples based on microcrystalline cellulose matrix incorporated with micro/nanoparticles of La0.7Sm0.3VO4 complex oxide were made by cool pressing procedure. Morphology, crystallinity and characteristic luminescence and dielectric properties of the composites were studied. Their morphology can be described as "ceramics-like" type, as it consists of cellulose plates and embedded oxide particles. Luminescence spectra of the composites covers the range of the whole visible light, 350-750 nm, and comprises both wide band and narrow lines, related with host and oxide luminescence, respectively. Temperature dependences of the dielectric permittivity of composites showed the impact of the oxide particles on the characteristics of the microcrystalline cellulose. An assumption was made that this influence can be affected via water molecules, hydroxyl groups or molecules of the ambient gases. Studied composites can be perspective luminescent materials for transformation of ultraviolet and violet radiation into green-red light. [ABSTRACT FROM AUTHOR]

Background: Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate characteristic sound changes caused by COVID-19 and can be used for diagnostics of this illness., Objective: The aim of the study is to develop 2 fast, remote computer-assisted diagnostic methods for specific acoustic phenomena associated with COVID-19 based on analysis of respiratory sounds., Methods: Fast Fourier transform (FFT) was applied for computer analysis of respiratory sound recordings produced by hospital doctors near the mouths of 14 patients with COVID-19 (aged 18-80 years) and 17 healthy volunteers (aged 5-48 years). Recordings for 30 patients and 26 healthy persons (aged 11-67 years, 34, 60%, women), who agreed to be tested at home, were made by the individuals themselves using a mobile telephone; the records were passed for analysis using WhatsApp. For hospitalized patients, the illness was diagnosed using a set of medical methods; for outpatients, polymerase chain reaction (PCR) was used. The sampling rate of the recordings was from 44 to 96 kHz. Unlike usual computer-assisted diagnostic methods for illnesses based on respiratory sound analysis, we proposed to test the high-frequency part of the FFT spectrum (2000-6000 Hz)., Results: Comparing the FFT spectra of the respiratory sounds of patients and volunteers, we developed 2 computer-assisted methods of COVID-19 diagnostics and determined numerical healthy-ill criteria. These criteria were independent of gender and age of the tested person., Conclusions: The 2 proposed computer-assisted diagnostic methods, based on the analysis of the respiratory sound FFT spectra of patients and volunteers, allow one to automatically diagnose specific acoustic phenomena associated with COVID-19 with sufficiently high diagnostic values. These methods can be applied to develop noninvasive screening self-testing kits for COVID-19., (©Gregory Furman, Evgeny Furman, Artem Charushin, Ekaterina Eirikh, Sergey Malinin, Valery Sheludko, Vladimir Sokolovsky, David Shtivelman. Originally published in JMIR Formative Research (https://formative.jmir.org), 19.07.2022.)

The aim of the study is to develop a method for detection of pathological respiratory sound, caused by bronchial asthma, with the aid of machine learning techniques., Materials and Methods: To build and train neural networks, we used the records of respiratory sounds of bronchial asthma patients at different stages of the disease (n=951) aged from several months to 47 years old and healthy volunteers (n=167). The sounds were recorded with calm breathing at four points: at the oral cavity, above the trachea, on the chest (second intercostal space on the right side), and at a point on the back., Results: The method developed for computer-aided detection of respiratory sounds allows to diagnose sounds typical for bronchial asthma in 89.4% of cases with 89.3% sensitivity and 86.0% specificity regardless of sex and age of the patients, stage of the disease, and the point of sound recording., Competing Interests: The authors have no conflicts of interest to declare.