Model singularly perturbed problems of the soil heat selection

Побудовано математичну модель двовимірного нестаціонарного процесу конвективно-дифузійного поширення тепла в трубці ґрунтового теплообмінника за умови превалювання конвективних його складових над дифузійними, яка дозволяє отримати розподіл температури теплоносія вздовж трубки теплообмінника та всередині самої трубки. Розвинуто числово-асимптотичний метод для розв’язання відповідної сингулярно збуреної задачі з умовою третього роду на бічній границі. Наведено результати комп’ютерних розрахунків, здійснено їх аналіз.In this paper we considered mathematical modeling of groundwater heat selection using the ground heat exchanger tubes, which has important applications for the solution of design problems of modern heating systems using renewable energy sources. We built a mathematical model of the two-dimensional unsteady convection - diffusion process of heat in a heat exchanger tube soil, under conditions of the prevalence of convective its components over diffusive ones. This let us get the temperature distribution of the coolant along the heat exchanger tubes and within the tube. Thus we assumed homogeneity of the soil structure, the lack of thermal resistance of the wall and ground heat exchanger pressure loss in the tube bends. This model allows to describe processes of heat transfer in both horizontal and vertical heat exchanger. We built asymptotic expansion of the solution of the corresponding singularly perturbed problem with the condition of the third kind on the side of the boundary (surface of the tube), in which the tube was describes the interaction of the heat exchanger with an array of the ground, which laid up. Application of the asymptotic method allowed to split a complex process into its component parts and stand-alone supplement to the convective component solution amendments on the exit from the tube and side adjustments that take into account the influence of ambient temperature. We performed a series of computer experiments on the results of which we can conclude that the effectiveness of screening low potential ground heat using heat exchanger through the soil for its further use for heating. The fact that the water content of the soil yield a greater increase in heat energy compared with dry sand and clay using horizontal heat exchangers was confirmed. Besides, it was confirmed that vertical heat exchanger is effective for all types of soil, but significant problem is the loss of heat accumulated in depth during the rise of the coolant in the heat exchanger tube through the upper cool layers of the soil

Стратегия развития химической промышленности

Розглянуто питання формування стратегії розвитку хімічної промисловості. Наведено статистичні дані стану її сьогодні. Запропоновано шляхи розвитку.The question of forming of strategy of development of chemical industry is considered. Statistical data over of the state of her are brought today. The ways of development are offered.Рассмотрены вопросы формирования стратегии развития химической промышленности. Приведены статистические данные состояния ее сегодня. Предложены пути развития

A wholistic approach to assessement of adaptation and resilience during spaceflight

Human performance within the context of extreme environments both terrestrially and in outer space continues to lead the frontier of new physiological discoveries, further enhancing the knowledge on limitations of human mind and body systems, the role and activity of adaptation mechanisms, as well as assessment and development of resilience strategies. The acquired knowledge informs the development of innovative prognostic, diagnostic and therapeutic medical tools and resources aboard the spacecraft and in terrestrial medical centres. Despite decades of research and space exploration, the prognostic and diagnostic capacity aboard the spacecraft remains limited and fragmented, while health assessments constitute of questionnaires and collection of nominal physiological parameters, both of which are analyzed retrospectively, upon return to Earth, unless there is an apparent onset of medical contingency which necessitates immediate therapeutic intervention. Even then, the use of the acquired physiological data is limited, as it is being down-sampled to manageable data tuples for clinical evaluation and interpretation. In prior research we proposed the use of a big-data analytics platform, Artemis, for real-time assessment of adaptation during spaceflight. The capability of Artemis to support acquisition, storage and analysis of large volumes of physiological, environmental and activity data presents a great prospect for enhanced medical capacity during long duration spaceflights and deep space exploration. As such, we would like to propose a framework of an extension of Artemis to further incorporate activity data and mental health evaluations, so as to develop a more wholistic approach to assessment of crew's well-being during spaceflight. The proposed extension would also enable investigation of the team dynamics and how interpersonal relationships influence individual's performance and well-being. From a biomedical monitoring perspective, utilization of Artemis would enable a meaningful use of the acquired physiological data and decrease the need for down-sampling of the data, thereby addressing the limitation of an enormous amount of data loss that persists with current data processing techniques. The proposed prototype will also provide a reliable on-site data warehouse, which would enable persistent, systematic and reliable storage of raw and derived analytics, as well as support the data transfer to the Mission control centres when the connection to do so is available. As such, it would support development of prognostic and diagnostic techniques for better prevention and management of medical contingencies aboard the spacecraft and improved medical autonomy of the crew

Spatio-temporal visualisation of big data analytics during spaceflight

Copyright © 2018 by the International Astronautical Federation (IAF). All rights reserved. Technological advancements continue to extend the capacity of clinical decision support aboard the spacecraft, while improve physiological monitoring practices, presenting new opportunities for clinical discovery and early detection monitoring. Preservation of health and performance of astronauts remains paramount for the success of the mission and safety of the entire crew. Increasing scientific evidence demonstrates effectiveness of the use of big data analytics to support provision of medical care in space, providing the necessary tools for development of an autonomous comprehensive clinical decision support system. In prior work, the big data analytics framework, known as the Artemis, was presented, demonstrating its capacity to analyse large volumes of physiological data streams, which could be effectively combined with other relevant clinical and environmental data. Preliminary studies focused on re-engineering of algorithms assessing adaption to enable them to run within an Online Analytics component of the Artemis platform, to assess the level of wellness and tolerance of adaptation mechanisms to the conditions of spaceflight, in real-time. Conventional data visualisation methods limited representation of data to 2-dimensional scatter graphs, which depicted the dynamicity of functional states, yet provided no task-specific or temporal detail, hindering the ability to understand the trajectory of changes that occur in response to changing physiological and environmental conditions. The ability of the Artemis platform to support real-time analytics has necessitated exploration of new data visualization techniques, to enable accurate representation of the functional state of the body, while depicting the trajectory of movement, signifying deviation from the norm and the risk of development of pathology. A spatio-temporal visualization technique for representation of big data analytics has been explored and demonstrates great potential to depict task-specific and time-specific dynamics of the functional health states, while improving the adaption knowledge for end-users, aiding interpretation of results. The use of spatio-temporal data visualization technique has been approbated during terrestrial simulation experiments and will be incorporated into an overarching Russian-Canadian space experiment “Cosmocard 2018†, focusing on modernization of software systems for use on the International Space Station

A sliding window real-time processing approach for analysis of heart rate variability during spaceflight

Copyright © 2019 by the International Astronautical Federation (IAF). All rights reserved. The paradigm of technological disruption continues to pave the way for innovative technology that has the capacity to acquire comprehensive real-time physiological and environmental data and present endless opportunities to study physiological processes and mechanisms, aid clinical discovery and advance the field of preventative and corrective medicine both on Earth and during spaceflight. Missions of increased distance and duration, as well as ad-hoc emergency situations that render the space crew to remain in space for long periods of time with reduced number of team members necessitate deployment of comprehensive clinical-decision support systems aboard the space station, to preserve and maintain the well-being of the crew, and ensure successful execution of mission objectives and safe return to Earth. In prior work, we presented the use of Artemis, big-data analytics platform for real-time analysis of adaption to conditions of spaceflight, to assess the levels of stress imposed on the human body and identify the state of well-being and any deviation from the norm that becomes apparent prior to onset of clinical symptoms. Conventional methods of adaption assessment were limited to 5-minute windows of data, which were historically averaged to a single hourly and daily value. The capability of Artemis to support analysis of high-frequency, high-volume and high-velocity data present new opportunities for analysis of heart rate variability during spaceflight. As such, we propose the use of a 5-minute sliding window-based analysis of heart rate variability for assessment of adaption during spaceflight. This method would support investigation of stressor-induced responses (i.e. physical load, task activity, environmental) to help identify the exact onset of the highest strain of regulatory mechanisms and assess activity of various components of the autonomic nervous system. In addition, 5-minute sliding window analysis would provide more insight into recovery processes during periods of inactivity or rest. This approach will be demonstrated with the use of data acquired from terrestrial simulation experiment “Luna-2015" and will be incorporated into future Space, Mars and Lunar missions, focusing on modernization of software systems for use on the International Space Station (ISS) and beyond

First record of the bivalve species Parvamussium fenestratum (Forbes, 1844) from the Middle Miocene of the Paratethys

This is the first Paratethyan record of a minute scallop species Parvamussium fenestratum (Forbes, 1844). The species was found in Middle Miocene (Upper Badenian) clayey deposits in the Surzha borehole, the Ukrainian Carpathian Foredeep Basin. Examination of other Parvamussium specimens stored in the Museum of the Earth in Warsaw and in the Hungarian Natural History Museum in Budapest revealed further Paratethyan records of Parvamussium fenestratum. These specimens, previously referred to Parvamussium felsineum (Foresti, 1893), were identified in the Middle Miocene faunas of Poland (Monastyrz and Długi Goraj, Roztocze Hills) and Hungary (Makkoshotyka, Tokaj Mts.). In the Mediterranean Neogene this extremely rare species has been reported from the Lower Miocene (uppermost Burdigalian) of Italy and from the Lower Pliocene (Zanclean) of Spain. Research on the Oligocene-Miocene succession in the Paratethys has shown representatives of Parvamussium Sacco, 1897 to be moderately abundant in clayey facies in different basins and the genus is regarded as biostratigraphically important. Data on the distribution of other Paratethyan and Neogene Mediterranean Parvamussium species viz., Parvamussium bronni (Mayer, 1861), P. duodecimlamellatum (Bronn, 1831), P. felsineum (Foresti, 1893) and P. miopliocenicum (Ruggieri, 1949) are reported. Finally, palaeobiological and palaeobiogeographical characteristics on the genus Parvamussium Sacco, 1897 the Early Cretaceous to Recent time span are described

Investigation of adaptation mechanisms during five-day dry immersion utilizing big-data analytics

© 2018 IEEE. Emerging technology continues to redefine the concept of health and human capacity to adapt to various extreme environments on Earth, as well as in space, while preserving performance and alleviating adverse effects on the human body. Technological advancements enable effective modeling of extreme environmental conditions in terrestrial facilities, demonstrating great potential for scientific discovery, modernization of available countermeasure systems and development of comprehensive software tools for clinical decision support. To date, a vast amount of knowledge has been accumulated on physiological deconditioning in response to spaceflight environment. The underlying conditions are often closely associated with maladaptation, supported by changes in heart rate variability parameters. However, existing methods do not support real-time data acquisition, processing and analytics, thereby limiting the usability of physiological data to inform clinical decision making and timely introduction of countermeasure systems. The proposed extension of Artemis, big data analytics platform and modernization of the wellness algorithm, demonstrate great potential to address limitations of existing methods, while significantly improve the provision of medical care in space or in terrestrial environments for individuals working and/or living under conditions of chronic stress. Current study demonstrates application of the proposed big-data analytics framework in a 5-day dry immersion experiment