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Traditional spacecraft attitude control often relies heavily on the dimension and mass information of the spacecraft. In active debris removal scenarios, these characteristics cannot be known beforehand because the debris can take any shape or mass. Additionally, it is not possible to measure the mass of the combined system of satellite and debris object in orbit. Therefore, it is crucial to develop an adaptive satellite attitude control that can extract mass information about the satellite system from other measurements. The authors propose using deep reinforcement learning (DRL) algorithms, employing stacked observations to handle widely varying masses. The satellite is simulated in Basilisk software, and the control performance is assessed using Monte Carlo simulations. The results demonstrate the benefits of DRL with stacked observations compared to a classical proportional–integral–derivative (PID) controller for the spacecraft attitude control. The algorithm is able to adapt, especially in scenarios with changing physical properties.

In 1909 Egon Wellesz published the article “Renaissance und Barock” in which he applied the term “Baroque,” which originated in art history, to music. With this he introduced the name for this music-historical epoch to musicology at least ten years before Curt Sachs, whose essay “Barockmusik” (1919) is still commonly referred to as the first mentioning of “Baroque Music.” Wellesz was one of the first musicologists to systematically deal with the music of the seventeenth and eighteenth centuries, in his case with a particular emphasis on Vienna. In his work he contributed significantly to defining the Baroque era as an independent music-historical stye period and thus made a valuable contribution to the early history of the discipline of musicology. This article will attempt to reconstruct Welleszʼs general understanding of the Baroque period, its temporal delineation, as well as his demarcation of a distinctly “Austrian” or “Viennese” Baroque tradition. In Wellesz’s writings it becomes clear that his methods and terminology derived not only from his teacher Guido Adler, but also adopted aspects of contemporary art-historical approaches.

Der Kunstwert von ‚reiner‘ Musik—Musik ohne Programm, Überschrift und Text—geriet mit dem Niedergang des mimetischen Kunstprinzips im späten 18. und frühen 19. Jahrhundert zum Problem (nicht nur) der idealistischen Musikästhetik. Kants Kritik der Urteilskraft (1790), die auf kommende Ästhetiker_innen besonders nachhaltig wirkte, zog sogar den Status der Musik als Kunst generell in Frage und formulierte ein Dilemma, das mit innovativen Ansätzen überwunden werden musste. Im Hinblick auf dieses Dilemma setzt mein Artikel die Ästhetik der ‚absoluten Tonkunst‘ von Eduard Hanslick und die Idee des ‚reinmenschlichen‘ Gesamtkunstwerks von Richard Wagner in direkten Dialog mit der idealistischen Musikästhetik. Wagners und Hanslicks Konzepte von ca. 1850 werden hierbei als Lösungsstrategien der idealistischen Problematik interpretiert und folglich gezeigt, dass Gesamtkunstwerk und musikalische Autonomie als ästhetische Positionen die gleiche Wurzel haben und als Seiten der gleichen Medaille gelesen werden können. Die beiden Autoren vereint trotz bekannter disparater Ansichten die von idealistischen Philosophen gestellte Diagnose, dass ‚reine‘ Musik semantisch mangelhaft sei und Gefühle, Begriffe und Gegenstände nicht zweifelsfrei ausdrücken könne. Ohne Eduard Hanslick und Richard Wagner als Idealisten aufzufassen oder ihre jeweilige Ästhetik gar auf den Deutschen Idealismus zu reduzieren, soll durch diese Arbeit gezeigt werden, dass sich die Antipoden unter diesem Gesichtspunkt näher waren, als meistens vermutet wird.Banner image: Eduard Hanslick and Richard Wagner. Silhouette by Otto Böhler. ÖNB, Bildarchiv Austria, Inventarnummer Pf 5786 : D (1) (https://www.bildarchivaustria.at/Pages/ImageDetail.aspx?p_iBildID=14690029).

Traditional spacecraft attitude control often relies heavily on the dimension and mass information of the spacecraft. In active debris removal scenarios, these characteristics cannot be known beforehand because the debris can take any shape or mass. Additionally, it is not possible to measure the mass of the combined system of satellite and debris object in orbit. Therefore, it is crucial to develop an adaptive satellite attitude control that can extract mass information about the satellite system from other measurements. The authors propose using deep reinforcement learning (DRL) algorithms, employing stacked observations to handle widely varying masses. The satellite is simulated in Basilisk software, and the control performance is assessed using Monte Carlo simulations. The results demonstrate the benefits of DRL with stacked observations compared to a classical proportional-integral-derivative (PID) controller for the spacecraft attitude control. The algorithm is able to adapt, especially in scenarios with changing physical properties. [ABSTRACT FROM AUTHOR]

Abstract Background The aims of this study are to determine (i) SARS-CoV-2 antibody positive employees in Austrian trauma hospitals and rehabilitation facilities, (ii) number of active virus carriers (symptomatic and asymptomatic) during the study, (iii) antibody decline in seropositive subjects over a period of around 6 months, (iv) the usefulness of rapid antibody tests for outpatient screening. Method A total of 3301 employees in 11 Austrian trauma hospitals and rehabilitation facilities of the Austrian Social Insurance for Occupational Risks (AUVA) participated in this open uncontrolled prospective cohort study. Rapid lateral flow tests, detecting a combination of IgM and IgM against SARS-CoV-2), two different types of CLIA (Diasorin, Roche), RT-PCR tests and serum neutralization tests (SNTs) were performed. The tests were conducted twice, with an interval of 42.4 ± 7.7 (Min = 30, Max = 64) days. Positive participants were re-tested with CLIA/SNT at a third time point after 188.0 ± 12.8 days. Results Only 27 out of 3301 participants (0.82%) had a positive antibody test at any time point during the study confirmed via neutralization test. Among positively tested participants in either test, 50.4% did not report any symptoms consistent with common manifestations of COVID-19 during the study period or within the preceding 6 weeks. In the group who tested positive during or prior to study inclusion the most common symptoms of an acute viral illness were rhinitis (21.9%), and loss of taste and olfactory sense (21.9%). Based on the neutralization test as the true condition, the rapid antibody test performed better on serum than whole blood as 84.6% instead of 65.4% could be detected correctly. Concerning both CLIA tests overall the Roche test detected 24 (sensitivity = 88.9%) and the Diasorin test 22 positive participants (sensitivity = 81.5%). In participants with a positive SNT result, a significant drop in neutralizing antibody titre from 31.8 ± 22.9 (Md = 32.0) at T1 to 26.1 ± 17.6 (Md = 21.3) at T2 to 21.4 ± 13.4 (Md = 16.0) at T3 (χ2 = 23.848, df = 2, p

Accurate calculations of the heat transfer and the resulting maximum wall temperature are essential for the optimal design of reliable and efficient regenerative cooling systems. However, predicting the heat transfer of supercritical methane flowing in cooling channels of a regeneratively cooled rocket combustor presents a significant challenge. High-fidelity CFD calculations provide sufficient accuracy but are computationally too expensive to be used within elaborate design optimization routines. In a previous work it has been shown that a surrogate model based on neural networks is able to predict the maximum wall temperature along straight cooling channels with convincing precision when trained with data from CFD simulations for simple cooling channel segments. In this paper, the methodology is extended to cooling channels with curvature. The predictions of the extended model are tested against CFD simulations with different boundary conditions for the representative LUMEN combustor contour with varying geometries and heat flux densities. The high accuracy of the extended model’s predictions, suggests that it will be a valuable tool for designing and analyzing regenerative cooling systems with greater efficiency and effectiveness.

Abstract SARS‐CoV‐2 may not only manifest as pneumonia (COVID‐19) but also in other organs, including the brain (neuro‐COVID). One of the cerebral complications of SARS‐CoV‐2 is ischemic stroke. Transitory ischemic attack (TIA) in a SARS‐CoV‐2 positive has not been reported. A 78‐year‐old poly‐morbid male (diabetes, hypertension, and coronary heart disease), admitted for COVID‐19, developed atrial flutter on hospital day (hd) 2. Anticoagulation with enoxaparin was started. On hd5, he experienced a TIA despite sufficient anticoagulation. The patient expired on hd28 due to multi‐organ failure from sepsis due to superinfection with staphylococcus aureus. Infection with SARS‐CoV‐2 may be complicated by atrial flutter. Atrial flutter may be complicated by TIA despite sufficient anticoagulation, suggesting that standard anticoagulation may be insufficient to meet SARS‐CoV‐2‐associated hypercoagulability syndrome. Forced anticoagulation and adequate antibiosis in poly‐morbid SARS‐CoV‐2‐infected patients with hypercoagulability and cytokine storm are warranted.