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Hintergrund: Es ist davon auszugehen, dass in Deutschland ca. 300.000 Personen von ME/CFS, also dem chronischen Fatigue Syndrom (CFS) oder auch Myalgische Enzephalomyelitis (ME) betroffen sind [ref:1]. Darunter befinden sich ca. 40.000 Kinder und Jugendliche [ref:2]. Da ätiologisch [zum vollständigen Text gelangen Sie über die oben angegebene URL]

Objective: Obtaining a systematic medical history (MH) from a patient is a core competency in medical education and plays a vital role in the diagnosis of diseases. At the Faculty of Medicine at LMU Munich, students have their first course in MH taking during their second year. Due to the COVID-19 pandemic, the traditional bedside MH taking course had to be transformed into an online course (OC). Our objectives were to implement an online MH taking course, to evaluate its feasibility and to compare the evaluation results to a historic cohort that had undertaken the traditional bedside teaching course (BTC).Methods: 874 second-year students participated in the OC (BTC=827). After teaching the theoretical background via asynchronous online lectures, students participated in a practical exercise with fellow students using the video communication platform Zoom where they were able to practice taking a MH on the basis of fictitious, text-based patient cases. Students were then asked to evaluate the course through a standardized online survey with 31 questions on teaching quality and self-perceived learning success, which had also been used in previous years. The survey results were compared to the results of the historic cohort using the Mann-Whitney U test.Results: A total of n=162 students (18.5%) evaluated the OC. In the historic cohort, n=252 (30.5%) completed the survey. 85.3% of the OC respondents thought that the atmosphere during the practical exercise was productive and 83.0% greatly appreciated the flexibility in terms of time management. Moreover, they appreciated the online resources as well as having the opportunity to undertake a MH taking course during the COVID-19 pandemic. 27.7% of the respondents thought that traditional BTCs should be supplemented through more online activities in the future. With respect to the ability of independently taking a MH upon completion of the course, the OC was rated significantly lower relative to the BTC (mean OC=2.4, SD=±1.1 vs. mean BTC=1.9, SD=±1.1 (1=strongly agree; 5=strongly disagree); p

Several animal species are susceptible to SARS-CoV-2 infection, as documented by case reports and serological and in vivo infection studies. However, the susceptibility of many animal species remains unknown. Furthermore, the expression patterns of SARS-CoV-2 entry factors, such as the receptor angiotensin-converting enzyme 2 (ACE2), as well as transmembrane protease serine subtype 2 (TMPRSS2) and cathepsin L (CTSL), cellular proteases involved in SARS-CoV-2 spike protein activation, are largely unexplored in most species. Here, we generated primary cell cultures from the respiratory tract of domestic and wildlife animals to assess their susceptibility to SARS-CoV-2 infection. Additionally, the presence of ACE2, TMPRSS2 and CTSL within respiratory tract compartments was investigated in a range of animals, some with unknown susceptibility to SARS-CoV-2. Productive viral replication was observed in the nasal mucosa explants and precision-cut lung slices from dogs and hamsters, whereas culture models from ferrets and multiple ungulate species were non-permissive to infection. Overall, whereas TMPRSS2 and CTSL were equally expressed in the respiratory tract, the expression levels of ACE2 were more variable, suggesting that a restricted availability of ACE2 may contribute to reduced susceptibility. Summarized, the experimental infection of primary respiratory tract cell cultures, as well as an analysis of entry-factor distribution, enable screening for SARS-CoV-2 animal reservoirs.

The 2019 UNESCO recommendation on Open Educational Resources (OER) encourages member states to monitor policies and mechanisms in OER across the world. In higher education, there are many initiatives and policies around OER. This contribution gives insights into the current situation concerning OER policy documents that are of national or institutional relevance for public higher education institutions in Germany, Switzerland, and Austria. For each country, a different approach for identifying OER policy documents was chosen, dependent on the availability of documents and different dominant forms of documentation. Whereas digital documents available on the web were found as helpful sources for Germany, and performance agreements between the national ministry and individual universities were used for analysis in Austria, a survey amongst all universities was the chosen research approach in Switzerland to give an overview about potentially OER related policy documents. All these documents are now made available via the OER World Map. With this contribution, the authors also highlight the possibility of using the OER World Map as a powerful tool to collect and evaluate OER policy documents., Neumann, J., Schön, S., Bedenlier, S., Ebner, M., Edelsbrunner, S., Krüger, N., Lüthi-Esposito, G., Marín, V. I., Orr, D., Peters, L. N., Reimer, R. T. D., & Zawacki-Richter, O. (2022). Approaches to Monitor and Evaluate OER Policies in Higher Education - Tracing Developments in Germany, Austria, and Switzerland. Asian Journal of Distance Education, 17(1), 125-147. https://doi.org/10.5281/zenodo.6508522

Fragestellung/Zielsetzung: Im Rahmen der COVID-19 Pandemie wurde der Anamnesekurs für Medizinstudierende an der LMU München in Präsenzform ausgesetzt und durch ein virtuelles Format ersetzt. Im Folgenden soll das virtuelle Format evaluiert werden, sowie die Frage beantwortet werden, [zum vollständigen Text gelangen Sie über die oben angegebene URL]

In Argentina it is important to study the possible impact of the type of school management on the quality of schooling, due to the growing participation of the private sector in the local education system since the mid-20th century. The purpose of this article is to test the following hypothesis: the lower risk of school failure observed in the private sector responds mainly to the characteristics of its student population, rather than to the type of management. To this end, multilevel logistic regression models are estimated using data from the PISA 2009 survey. The results favour the initial hypothesis. Fil: Formichella, Maria Marta. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina Fil: Krüger, Natalia Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina

We present a temporal accumulation scheme which disambiguates different kinds of visual 3D descriptors within one coherent framework. The accumulation consists of a twofold process: First, by means of a Bayesian filtering outliers become eliminated and second, the precision of the extracted information becomes enhanced by means of an unscented Kalman filtering process. It is a particular property of our algorithm to be able to deal with different kinds of visual descriptors by the very same mechanism. We show quantitative and qualitative results.

We present a three–level architecture for detection and tracking of independently moving objects (IMOs) in sequences recorded from a moving vehicle. At the first stage, image pixels with an optical flow that is not entirely induced by the car’s motion are detected by combining dense optical flow, egomotion extracted from this optical flow, and dense stereo. These pixels are segmented and an attention mechanism is used to process them at finer resolution at the second level making use of sparse 2D and 3D edge descriptors. Based on the rich and precise information on the second level, the full rigid motion for the environment and for each IMO is computed. This motion information is then used for tracking, filtering and the building of a 3D model of the street structure as well as the IMO. This multi-level architecture allows us to combine the strength of both dense and sparse processing methods in terms of precision and computational complexity, and to dedicate more processing capacity to the important parts of the scene (the IMOs).

We present a three-level architecture for detection and tracking of independently moving objects (IMOs) in sequences recorded from a moving vehicle. At the first stage, image pixels with an optical flow that is not entirely induced by the car's motion are detected by combining dense optical flow, egomotion extracted from this optical flow, and dense stereo. These pixels are segmented and an attention mechanism is used to process them at finer resolution at the second level making use of sparse 2D and 3D edge descriptors. Based on the rich and precise information on the second level, the full rigid motion for the environment and for each IMO is computed. This motion information is then used for tracking, filtering and the building of a 3D model of the street structure as well as the IMO. This multi-level architecture allows us to combine the strength of both dense and sparse processing methods in terms of precision and computational complexity, and to dedicate more processing capacity to the important parts of the scene (the IMOs).

In this work, we address the problem of road interpretation for driver assistance based on an early cognitivevision system. The structure of a road and the relevant traffic are interpreted in terms of ego-motion estimationof the car, independently moving objects on the road, lane markers and large scale maps of the road. We makeuse of temporal and spatial disambiguation mechanisms to increase the reliability of visually extracted 2D and3D information. This information is then used to interpret the layout of the road by using lane markers that aredetected via Bayesian reasoning. We also estimate the ego-motion of the car which is used to create large scalemaps of the road and also to detect independently moving objects. Sample results for the presented algorithmsare shown on a stereo image sequence, that has been collected from a structured road.