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

Primary lymphangiectasia of the gastrointestinal tract

Intestinal lymphangiectasia is a very rare pathology, characterized by the presence of enlarged lymphatic vessels in all layers of the intestinal wall and in the mesentery. As a result, "lymphatic lakes" are formed, through which lymph exudates into the lumen of the intestine. The main manifestation is hypoproteinemic edema. Diagnosis of the disease is based on laboratory-instrumental methods of investigation, including by determining in the stool α-1 antitrypsin as a screening test. Treatment includes: a diet rich in calcium, trace elements, be sure to use medicinal foods enriched with medium chain triglycerides, substitution and symptomatic therapy

HI study of the environment around ESO 243-49, the host galaxy of an intermediate mass black hole

The lenticular galaxy ESO 243-49 hosts the ultraluminous X-ray source HLX-1, the best candidate intermediate mass black hole (IMBH) currently known. The environments of IMBHs remain unknown, however the proposed candidates include the nuclei of dwarf galaxies or globular clusters. Evidence at optical wavelengths points at HLX-1 being the remnant of an accreted dwarf galaxy. Here we report the Australia Telescope Compact Array radio observations of HI emission in and around ESO 243-49 searching for signatures of a recent merger event. No HI line emission is detected in ESO 243-49 with a 5$\sigma$ upper limit on the HI gas mass of a few $10^8 M_{\odot}$. A likely reason for this non-detection is the cluster environment depleting ESO 243-49's HI gas reservoir. The upper limit is consistent with an interpretation of HLX-1 as a dwarf satellite of ESO 243-49, however more sensitive observations are required for a detection. We detect ~$5 \times 10^8 M_{\odot}$ of HI gas in the peculiar spiral galaxy AM 0108-462, located at a projected distance of ~170 kpc from ESO 243-49. This amount of HI gas is ~10 times less than in spiral galaxies with similar optical and near-infrared properties in the field, strengthening the conclusion that the cluster environment indeed depletes the HI gas reservoir of these two galaxies. Here we also report observations of AM 0108-462 in several optical and near-infrared bands using the Magellan 6.5 m telescopes, and archival X-ray and ultraviolet observations with XMM-Newton and Swift. These data combined with the HI line data suggest it is likely that AM 0108-462 is experiencing a merger event.Comment: 12 pages, 9 figures, accepted for publication in MNRA

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

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

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

Connecting X-ray absorption and 21 cm neutral hydrogen absorption in obscured radio AGN

Many radio galaxies show the presence of dense and dusty gas near the active nucleus. This can be traced by both 21 cm H I absorption and soft X-ray absorption, offering new insight into the physical nature of the circumnuclear medium of these distant galaxies. To better understand this relationship, we investigate soft X-ray absorption as an indicator for the detection of associated H I absorption, as part of preparation for the First Large Absorption Survey in H I to be undertaken with the Australian Square Kilometre Array Pathfinder (ASKAP). We present the results of our pilot study using the Boolardy Engineering Test Array, a precursor to ASKAP, to search for new absorption detections in radio sources brighter than 1 Jy that also feature soft X-ray absorption. Based on this pilot survey, we detected H I absorption towards the radio source PKS 1657−298 at a redshift of z = 0.42. This source also features the highest X-ray absorption ratio of our pilot sample by a factor of 3, which is consistent with our general findings that X-ray absorption predicates the presence of dense neutral gas. By comparing the X-ray properties of active galactic nuclei with and without detection of H I absorption at radio wavelengths, we find that X-ray hardness ratio and H I absorption optical depth are correlated at a statistical significance of 4.71σ. We conclude by considering the impact of these findings on future radio and X-ray absorption studies

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)

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