Neutron radiography for visualization of liquid metal processes: Bubbly flow for CO2 free production of Hydrogen and solidification processes in em field

The paper describes the results of two experimental investigations aimed to extend the abilities of a neutron radiography to visualize two-phase processes in the electromagnetically (EM) driven melt flow. In the first experiment the Argon bubbly flow in the molten Gallium - a simulation of the CO2 free production of Hydrogen process - was investigated and visualized. Abilities of EM stirring for control on the bubbles residence time in the melt were tested. The second experiment was directed to visualization of a solidification front formation under the influence of EM field. On the basis of the neutron shadow pictures the form of growing ingot, influenced by turbulent flows, was considered. In the both cases rotating permanent magnets were agitating the melt flow. The experimental results have shown that the neutron radiography can be successfully employed for obtaining the visual information about the described processes.LIMTEC

Author as a corporal subject of a. Huxley’s works

The relevance of the problem studied in the article is conditioned by the fact that A. Huxley’s works are regarded in the context of the modern theory of mimesis for the first time. The aim of the article is to analyze the author’s problem as a corporal subject of Huxley’s works in the context of the modern theory of mimesis. The leading method for studying this problem is the analytical anthropology of literature which allows describing mimetic features and the author’s image as a corporal subject of Huxley’s works. The main attention in the article is paid to the artistically embodied forms of the author’s corporality. The article may be useful for philologists, philosophers, for developing courses and seminars on the history of the English literature, and also within courses on the anthropology of literature. © 2016 Falaleeva et al

A Comparison of Photometric Redshift Techniques for Large Radio Surveys

Future radio surveys will generate catalogs of tens of millions of radio sources, for which redshift estimates will be essential to achieve many of the science goals. However, spectroscopic data will be available for only a small fraction of these sources, and in most cases even the optical and infrared photometry will be of limited quality. Furthermore, radio sources tend to be at higher redshift than most optical sources (most radio surveys have a median redshift greater than 1) and so a significant fraction of radio sources hosts differ from those for which most photometric redshift templates are designed. We therefore need to develop new techniques for estimating the redshifts of radio sources. As a starting point in this process, we evaluate a number of machine-learning techniques for estimating redshift, together with a conventional template-fitting technique. We pay special attention to how the performance is affected by the incompleteness of the training sample and by sparseness of the parameter space or by limited availability of ancillary multiwavelength data. As expected, we find that the quality of the photometric-redshift degrades as the quality of the photometry decreases, but that even with the limited quality of photometry available for all-sky-surveys, useful redshift information is available for the majority of sources, particularly at low redshift. We find that a template-fitting technique performs best in the presence of high-quality and almost complete multi-band photometry, especially if radio sources that are also X-ray emitting are treated separately, using specific templates and priors. When we reduced the quality of photometry to match that available for the EMU all-sky radio survey, the quality of the template-fitting degraded and became comparable to some of the machine-learning methods. Machine learning techniques currently perform better at low redshift than at high redshift, because of incompleteness of the currently available training data at high redshifts

Liquid metals for solar power systems

The use of liquid metals in solar power systems is not new. The receiver tests with liquid sodium in the 1980s at the Plataforma Solar de Almería (PSA) already proved the feasibility of liquid metals as heat transfer fluid. Despite the high efficiency achieved with that receiver, further investigation of liquid metals in solar power systems was stopped due to a sodium spray fire. Recently, the topic has become interesting again and the gained experience during the last 30 years of liquid metals handling is applied to the concentrated solar power community. In this paper, recent activities of the Helmholtz Alliance LIMTECH concerning liquid metals for solar power systems are presented. In addition to the components and system simulations also the experimental setup and results are included

A comparison of photometric redshift techniques for large radio surveys

Future radio surveys will generate catalogs of tens of millions of radio sources, for which redshift estimates will be essential to achieve many of the science goals. However, spectroscopic data will be available for only a small fraction of these sources, and in most cases even the optical and infrared photometry will be of limited quality. Furthermore, radio sources tend to be at higher redshift than most optical sources (most radio surveys have a median redshift greater than 1) and so a significant fraction of radio sources hosts differ from those for which most photometric redshift templates are designed. We therefore need to develop new techniques for estimating the redshifts of radio sources. As a starting point in this process, we evaluate a number of machine-learning techniques for estimating redshift, together with a conventional template-fitting technique. We pay special attention to how the performance is affected by the incompleteness of the training sample and by sparseness of the parameter space or by limited availability of ancillary multiwavelength data. As expected, we find that the quality of the photometric-redshift degrades as the quality of the photometry decreases, but that even with the limited quality of photometry available for all-sky-surveys, useful redshift information is available for the majority of sources, particularly at low redshift. We find that a template-fitting technique performs best in the presence of high-quality and almost complete multi-band photometry, especially if radio sources that are also X-ray emitting are treated separately, using specific templates and priors. When we reduced the quality of photometry to match that available for the EMU all-sky radio survey, the quality of the template-fitting degraded and became comparable to some of the machine-learning methods. Machine learning techniques currently perform better at low redshift than at high redshift, because of incompleteness of the currently available training data at high redshifts

Comparison of REMS, NEWS, qSOFA and SIRS criteria scales for sepsis prediction in patients with diagnosis “SARS-CoV-2, virus unidentified”: a retrospective observational study

Background. Despite ample research on the coronavirus infection sequence and therapy, the incidence of adverse outcomes remains very high. Sepsis stands among the major factors greatly complicating treatment and increasing the risk of death. A timely identification of highrisk sepsis patients is a cornerstone of effective sepsis prevention.Objectives. A comparative prognostic power assessment between the quick Sequential Organ Failure Assessment (qSOFA) scale, National Early Warning Score (NEWS), Initial Prehospital Rapid Emergency Medicine Score (REMS) and the Systemic Inflammatory Response Syndrome (SIRS) criteria for sepsis detection in anaesthetic intensive care patients with a diagnosis: SARS-CoV-2, virus unidentified.Methods. A retrospective observational study included 166 patients over 18-year age with unconfirmed infection (ICD-10 code U07.2). The qSOFA, NEWS, REMS and SIRS point estimates were obtained from each patient. The patients were retrospectively divided in two cohorts by sepsis presence (Sepsis-3 criteria) to determine the express scales power in evaluating the risk of sepsis (estimated as area under ROC curve, AUROC).Results. Data on 102 patients were included in the final analysis. Fifty-eight (57%) patients were terminal, and 55 (54%) developed sepsis. The estimates are as follows: NEWS — AUROC 0.848 [95% confidence interval (CI) 0.764–0.912], sensitivity 76.36% [95% CI 63.0–86.8], specificity 82.98% [95% CI 69.2–92.4], optimal cut-off threshold >5 points; qSOFA — AUROC 0.700 [95% CI 0.602–0.787], sensitivity 76.36% [95% CI 63.0–86.8], specificity 61.70% [95% CI 46.4–75.5], optimal cut-off threshold >0 points; REMS — AUROC 0.739 [95% CI 0.643–0.821], sensitivity 69.09% [95% CI 55.2–80.9], specificity 65.96% [95% CI 50.7–79.1], optimal cut-off threshold >5 points; SIRS criteria — AUROC 0.723 [95% CI 0.626–0.807], sensitivity 98.18% [95% CI 90.3–100.0], specificity 31.91% [95% CI 19.1–47.1], optimal cut-off threshold >0 points.Conclusion. The NEWS scale revealed a good prognostic power to estimate the risk of sepsis in patients with suspected COVID-19 disease. The qSOFA, REMS scales and SIRS criteria possess a good calibration capacity, albeit insufficient resolution, which limits their prognostic value

ВЛИЯНИЕ ФУНКЦИОНАЛЬНОГО СОСТОЯНИЯ ПАЦИЕНТОВ ПОЖИЛОГО И СТАРЧЕСКОГО ВОЗРАСТА НА ЧАСТОТУ ИНТРАОПЕРАЦИОННЫХ КРИТИЧЕСКИХ ИНЦИДЕНТОВ

The correlation between the age and wakefulness level evaluated as per the value of constant potential and  frequency of critical incidence occurrence has been investigated in 160 patients who had planned surgery with combined anesthesia due to the colon tumor. The latter depended on the age, it was the lowest in the high level of wakefulness and it was high in the low level of wakefulness regardless of the age. У 160 пациентов, планово оперированных в условиях сочетанной анестезии по поводу опухолей толстой кишки, изучена связь возраста и уровня бодрствования, оценённого по величине постоянного потенциала, с частотой развития критических инцидентов. Последняя зависела от возраста, была наименьшей при высоком уровне бодрствования, а при низком уровне бодрствования оказалась высокой независимо от возраста

ВНУТРИЧЕРЕПНОЕ ДАВЛЕНИЕ В УСЛОВИЯХ ВЫСОКООБЪЕМНОЙ ГЕМОФИЛЬТРАЦИИ ПРИ ТЯЖЕЛОМ СЕПСИСЕ

Objective: to define the prognostic value of intracranial pressure (ICP) changes in highvolume hemofiltration (HVHF) in patients with severe sepsis and normal preperfusion ICP.Subjects and methods. A retrospective study was conducted in 50 patients (a total of 134 sessions) with severe sepsis and normal baseline ICP who received ther apy using HVHF for extrarenal indications. Based on ICP changes before and after HVHF, the investigators identified 2 groups: 1) no ICP changes (n=81); 2) elevated ICP (n=53).Conclusion. HVHF is ineffective when the normal preperfusion ICP is increased in patients with severe sepsis who have a concurrence of an arteriovenous carbon dioxide difference of more than 8 mm Hg and a Glasgow coma score of less than 10.Цель исследования. Определить прогностическое значение динамики ВЧД в условиях ВОГФ у больных с тяжелым сепсисом и нормальным предперфузионным уровнем внутричерепного давления. Материал и методы. Проведено ретроспективное исследование 50 больных (всего 134 процедуры) с тяжелым сепсисом и нормальным уровнем внутричерепного давления (ВЧД) по данным измерения давления в центральной вене сетчатки, которым проводили высокообъемную гемофильтрацию (ВОГФ) по внепочечным показаниям. На основании динамики ВЧД до и после ВОГФ выделено 2 группы: 1я (n=81) — с отсутствием динамики ВЧД; 2я (n=53) — с повышением ВЧД.Заключение. ВОГФ не эффективна в случае увеличения предперфузионно нормального ВЧД у пациентов с тяжелым сепсисом, имеющих сочетание артериовенозной разницы напряжения углекислого газа более 8 мм рт. ст. и уровня по шкале ком Глазго менее 10 баллов

A Comparison of Photometric Redshift Techniques for Large Radio Surveys

Future radio surveys will generate catalogs of tens of millions of radio sources, for which redshift estimates will be essential to achieve many of the science goals. However, spectroscopic data will be available for only a small fraction of these sources, and in most cases even the optical and infrared photometry will be of limited quality. Furthermore, radio sources tend to be at higher redshift than most optical sources (most radio surveys have a median redshift greater than 1) and so a significant fraction of radio sources hosts differ from those for which most photometric redshift templates are designed. We therefore need to develop new techniques for estimating the redshifts of radio sources. As a starting point in this process, we evaluate a number of machine-learning techniques for estimating redshift, together with a conventional template-fitting technique. We pay special attention to how the performance is affected by the incompleteness of the training sample and by sparseness of the parameter space or by limited availability of ancillary multiwavelength data. As expected, we find that the quality of the photometric-redshift degrades as the quality of the photometry decreases, but that even with the limited quality of photometry available for all-sky-surveys, useful redshift information is available for the majority of sources, particularly at low redshift. We find that a template-fitting technique performs best in the presence of high-quality and almost complete multi-band photometry, especially if radio sources that are also X-ray emitting are treated separately, using specific templates and priors. When we reduced the quality of photometry to match that available for the EMU all-sky radio survey, the quality of the template-fitting degraded and became comparable to some of the machine-learning methods. Machine learning techniques currently perform better at low redshift than at high redshift, because of incompleteness of the currently available training data at high redshifts

Модель прогнозирования послеоперационной пневмонии в абдоминальной хирургии: результаты наблюдательного многоцентрового исследования

АКТУАЛЬНОСТЬ: Ведущее место в структуре послеоперационных осложнений занимает послеоперационная пневмония. Учитывая распространенность послеоперационной пневмонии и рост числа хирургических процедур, прогнозирование ее развития является актуальной задачей, позволяющей принять меры по снижению частоты ее возникновения, путем оптимизации периоперационного периода. Несмотря на свою ценность, существующие шкалы прогнозирования послеоперационной пневмонии не обеспечивают отечественных специалистов надежным и постоянным методом, с помощью которого можно стратифицировать риск развития послеоперационной пневмонии в нашей популяции. ЦЕЛЬ ИССЛЕДОВАНИЯ: разработка модели прогнозирования послеоперационной пневмонии на основе выявления факторов риска ее развития. МАТЕРИАЛЫ И МЕТОДЫ: Многоцентровое проспективное исследование, 6844 пациента старше 18 лет, подвергающиеся плановым оперативным вмешательствам на органах брюшной полости. Оценивали 30-дневную летальность и послеоперационную пневмонию. На первом этапе исследования проводилось сравнение между группой с пневмонией и группой без пневмонии исходных данных пациентов, а также факторов, связанных с операцией и анестезией. На втором этапе исследования проводился логистический регрессионный анализ для оценки вклада факторов в развитие послеоперационной пневмонии. На третьем этапе исследования выполнялось построение модели прогнозирования послеоперационной пневмонии по данным многомерного логистического регрессионного анализа. На заключительном этапе производилось сравнение полученной модели с моделями прогнозирования других авторов, встречающихся в мировой литературе. РЕЗУЛЬТАТЫ: Пневмония выявлена у 53 пациентов (0,77 %). Летальный исход наблюдался у 39 пациентов: у пациентов с пневмонией в 15 случаях (28,3 %), а без пневмонии — в 24 случаях (0,4 %). Ретроспективно с учетом полученной модели к группе высокого риска развития пневмонии были отнесены 933 пациента, частота развития пневмонии составляла 4,5 %. В группе низкого риска развития пневмонии — 5911 пациентов, частота развития пневмонии составляла 0,19 %. ВЫВОДЫ: Выявлены восемь независимых переменных, связанных с послеоперационной пневмонией: длительность операции, курение, полная функциональная зависимость, периоперационная анемия, требующая применения препаратов железа, интраоперационное применение вазопрессоров, III функциональный класс по классификации Американского общества анестезиологов, применение бронходилатирующих препаратов по поводу хронической обструктивной болезни легких, высокий операционный риск. Модель прогнозирования послеоперационной пневмонии имеет отличную прогностическую значимость (AUROC = 0,904)