Reliability and information content of tests with cardioleader in cyclic types of sports

Tests with cardioleader to control the physical, technical and tactical preparedness of athletes in cyclic types of sports are discussed. Ways of increasing the reliability and information content of the tests were studied

Piecewise smooth systems near a co-dimension 2 discontinuity manifold: can one say what should happen?

We consider a piecewise smooth system in the neighborhood of a co-dimension 2 discontinuity manifold $\Sigma$. Within the class of Filippov solutions, if $\Sigma$ is attractive, one should expect solution trajectories to slide on $\Sigma$. It is well known, however, that the classical Filippov convexification methodology is ambiguous on $\Sigma$. The situation is further complicated by the possibility that, regardless of how sliding on $\Sigma$ is taking place, during sliding motion a trajectory encounters so-called generic first order exit points, where $\Sigma$ ceases to be attractive. In this work, we attempt to understand what behavior one should expect of a solution trajectory near $\Sigma$ when $\Sigma$ is attractive, what to expect when $\Sigma$ ceases to be attractive (at least, at generic exit points), and finally we also contrast and compare the behavior of some regularizations proposed in the literature. Through analysis and experiments we will confirm some known facts, and provide some important insight: (i) when $\Sigma$ is attractive, a solution trajectory indeed does remain near $\Sigma$, viz. sliding on $\Sigma$ is an appropriate idealization (of course, in general, one cannot predict which sliding vector field should be selected); (ii) when $\Sigma$ loses attractivity (at first order exit conditions), a typical solution trajectory leaves a neighborhood of $\Sigma$; (iii) there is no obvious way to regularize the system so that the regularized trajectory will remain near $\Sigma$ as long as $\Sigma$ is attractive, and so that it will be leaving (a neighborhood of) $\Sigma$ when $\Sigma$ looses attractivity. We reach the above conclusions by considering exclusively the given piecewise smooth system, without superimposing any assumption on what kind of dynamics near $\Sigma$ (or sliding motion on $\Sigma$) should have been taking place.Comment: 19 figure

Sliding mode control of quantum systems

This paper proposes a new robust control method for quantum systems with uncertainties involving sliding mode control (SMC). Sliding mode control is a widely used approach in classical control theory and industrial applications. We show that SMC is also a useful method for robust control of quantum systems. In this paper, we define two specific classes of sliding modes (i.e., eigenstates and state subspaces) and propose two novel methods combining unitary control and periodic projective measurements for the design of quantum sliding mode control systems. Two examples including a two-level system and a three-level system are presented to demonstrate the proposed SMC method. One of main features of the proposed method is that the designed control laws can guarantee desired control performance in the presence of uncertainties in the system Hamiltonian. This sliding mode control approach provides a useful control theoretic tool for robust quantum information processing with uncertainties.Comment: 18 pages, 4 figure

CONSTRUCTION OF A DNA-MICROARRAY FOR DIFFERENTIATION BETWEEN THE MAIN AND NON-MAIN SUBSPECIES AND BIOVARS OF THE MAIN SUBSPECIES OF YERSINIA PESTIS

Objective of the study is to design the DNA-microarray for differentiation of Y. pestis strains of the main and non-main subspecies and biovars of the main subspecies. Materials and methods. Efficiency analysis for the devised means was conducted using 62 Y. pestis strains of various subspecies and biovars, isolated in the natural foci of Russia and neighboring countries. Results and conclusions. Selected have been the DNA-targets, probes and primers – calculated. Enhanced is the method of sub-specific and biovar differentiation of Y. pestis strains by means of DNA-microarray. DNA-chip with “Med24”, “glpD(-93)”, and “45” targets allows for prompt differentiation of the strains of the main and non-main subspecies and biovars of the main subspecies based on the presence and absence of fluorescent signal by the specific for the main subspecies and its biovars DNA-targets

ЭНЕРГОСИЛОВЫЕ УСЛОВИЯ ГИДРОМЕХАНИЧЕСКОГО ПРЕССОВАНИЯ КРУГЛЫХ ИЗДЕЛИЙ

One of the main widespread methods of metal forming is pressing characterized by a favorable plastic deformation pattern with the predominant effect of all-round compressive stresses. This allows deforming low-ductile materials and alloys with sufficiently high degrees of deformation. This paper studies plastic deformation conditions at hydro-mechanical pressing as one of pressing types. A distinctive feature of hydro-mechanical pressing as compared to other pressing types is the ability to control the movement of the billet and prevent its ejection at the final process stage. The study covers the conditions of hydro-mechanical pressing which combines the use of high-pressure working fluid and the mechanical impact of the tooling on the pressing die. Formulas for the components of the total hydro-mechanical pressing stress are derived to serve the basis for determination of the optimal process tool geometry. Taper angles of the hydro-mechanical pressing die are optimized depending on the main pressing process parameters. The dependency graphs are plotted for the ratio of pressing stress to the resistance of pressed material deformation as a result of drawing that confirmed the presence of optimum taper angles of pressing dies.Одним из основных широко распространенных способов обработки металлов давлением является прессование, для которого характерна благоприятная схема пластической деформации с преобладающим действием напряжений всестороннего сжатия, что позволяет деформировать малопластичные материалы и сплавы с достаточно большими степенями деформирования. В настоящей работе рассмотрены условия пластического деформирования при гидромеханическом прессовании, как одной из разновидностей процесса прессования. Его отличительной особенностью по сравнению с другими видами прессования является возможность контролировать движение заготовки и предотвращать ее «выстреливание» в конечной стадии процесса. В ходе исследований проведен анализ условий гидромеханического прессования, сочетающего применение рабочей жидкости высокого давления и механическое воздействие технологической оснастки на прессующую матрицу. Получены формулы составляющих общего напряжения гидромеханического прессования, на основании которых определена оптимальная геометрия технологического инструмента. Проведена оптимизация углов конусности матрицы для гидромеханического прессования в зависимости от основных технологических параметров процесса прессования. Построены зависимости отношения напряжения прессования к сопротивлению деформации прессуемого материала от вытяжки, которые подтвердили наличие оптимальных углов конусности прессовых матриц

Effects of Glyphosate-Based Herbicide on Primary Production and Physiological Fitness of the Macroalgae Ulva lactuca

The use of glyphosate-based herbicides (GBHs) worldwide has increased exponentially over the last two decades increasing the environmental risk to marine and coastal habitats. The present study investigated the effects of GBHs at environmentally relevant concentrations (0, 10, 50, 100, 250, and 500 µg·L −1 ) on the physiology and biochemistry (photosynthesis, pigment, and lipid composition, antioxidative systems and energy balance) of Ulva lactuca, a cosmopolitan marine macroalgae species. Although GBHs cause deleterious effects such as the inhibition of photosynthetic activity, particularly at 250 µg·L −1 , due to the impairment of the electron transport in the chloroplasts, these changes are almost completely reverted at the highest concentration (500 µg·L −1 ). This could be related to the induction of tolerance mechanisms at a certain threshold or tipping point. While no changes occurred in the energy balance, an increase in the pigment antheraxanthin is observed jointly with an increase in ascorbate peroxidase activity. These mechanisms might have contributed to protecting thylakoids against excess radiation and the increase in reactive oxygen species, associated with stress conditions, as no increase in lipid peroxidation products was observed. Furthermore, changes in the fatty acids profile, usually attributed to the induction of plant stress response mechanisms, demonstrated the high resilience of this macroalgae. Notably, the application of bio-optical tools in ecotoxicology, such as pulse amplitude modulated (PAM) fluorometry and laser-induced fluorescence (LIF), allowed separation of the control samples and those treated by GBHs in different concentrations with a high degree of accuracy, with PAM more accurate in identifying the different treatments.info:eu-repo/semantics/publishedVersio

Искусственный интеллект в медицине: современное состояние и основные направления развития интеллектуальной диагностики

The main difference between artificial intelligence (AI) systems and simple automated algorithms is the ability to learn, synthesize and conclude. The AI system is trained on a set of examples, including pictures, characteristics of patients with a certain disease, then it allows to generalize a lot of such examples and get some general functional dependence, which brings in line the patient data and a certain diagnosis. The system can be named intelligent if this synthetizing ability is realized. Although the AI systems are now becoming more understood and accepted by doctors, a deeper understanding of «how it works» is needed. The article provides a detailed review of the application of methods and models of artificial intelligence in the diagnostics of cancer based on the of multimodal instrumental data. The basic concepts of artificial intelligence and directions of its development are presented. From the point of view of data processing, the stages of development of AI systems are identical. The stages of intellectual processing of diagnostic data are considered in the paper. They include the acquisition and use of training databases of oncological diseases, pre-processing of images, segmentation to highlight the studied objects of diagnosis and classification of these objects to determine whether they are malignant or benign. One of the problems limiting the acceptance of AI systems development by the medical community is the imperfection of the explainability of the results obtained by intelligent systems. Authors pay attention to importance of the development of so-called explanatory intelligence, because its absence currently significantly inhibits the introduction and use of intelligent diagnostic systems in medicine. In addition, the purpose of the article is a way to develop the interaction between a radiologists and data scientists.Главное отличие систем искусственного интеллекта (ИИ) от простых автоматизированных алгоритмов заключается в способности к обучению, обобщению и выводу. Система ИИ обучается на множестве примеров, включая снимки, характеристики пациентов с определенным заболеванием, далее она позволяет обобщить множество таких примеров и получить некоторую общую функциональную зависимость, которая приводит в соответствие данные о пациенте и определенный диагноз. Интеллектуальной система становится при реализации этой обобщающей способности. Несмотря на то, что в настоящее время тематика ИИ становится более понимаемой и принимаемой врачами, необходимо более глубокое понимание «как это работает». В статье приводится детальный обзор применения методов и моделей искусственного интеллекта в диагностике онкологических заболеваний на основе данных мультимодальной лучевой диагностики. Даны основные понятия искусственного интеллекта и направления его использования. С точки зрения обработки данных этапы разработки систем ИИ идентичны. В статье рассмотрены этапы интеллектуальной обработки диагностических данных, которые включают создание и использование обучающих баз данных онкологических заболеваний, предварительную обработку снимков, сегментацию изображений для выделения исследуемых объектов диагностики и классификацию этих объектов для определения, являются ли они злокачественными или доброкачественными. Одной из проблем, ограничивающих принятие развития систем ИИ медицинским сообществом, является несовершенство объяснимости результатов, получаемых при помощи интеллектуальных систем. В статье затронуты важные вопросы разработки объяснительного интеллекта, отсутствие которого в настоящее время существенно тормозит внедрение и использование интеллектуальных систем диагностики в медицине. Кроме того, цель статьи — путь к развитию взаимодействия между врачом и специалистом по искусственному интеллекту

Fluoxetine induces photochemistry-derived oxidative stress on Ulva lactuca

Emerging pollutants impose a high degree of stress on marine ecosystems, compromising valuable resources, the planet and human health. Pharmaceutical residues often reach marine ecosystems, and their input is directly related to human activities. Fluoxetine is an antidepressant, and one of the most prescribed selective serotonin reuptake inhibitors globally and has been detected in aquatic ecosystems in concentrations up to 40 μg L−1 . The present study aims to evaluate the impact of fluoxetine ecotoxicity on the photochemistry, energy metabolism and enzyme activity of Ulva lactuca exposed to environmentally relevant concentrations (0.3, 0.6, 20, 40, and 80 μg L−1 ). Exogenous fluoxetine exposure induced negative impacts on U. lactuca photochemistry, namely on photosystem II antennae grouping and energy fluxes. These impacts included increased oxidative stress and elevated enzymatic activity of ascorbate peroxidase and glutathione reductase. Lipid content increased and the altered levels of key fatty acids such as hexadecadienoic (C16:2) and linoleic (C18:2) acids revealed strong correlations with fluoxetine concentrations tested. Multivariate analyses reinforced the oxidative stress and chlorophyll a fluorescence-derived traits as efficient biomarkers for future toxicology studies.info:eu-repo/semantics/publishedVersio