551 research outputs found

    Produzieren in Niedersachsen und Baden-WĂŒrttemberg : Konzeption und Ergebnisse aus der Pilotstudie zum Firmenpanel

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    "Vom Institut fĂŒr Quantitative Wirtschaftsforschung der UniversitĂ€t Hannover und dem Institut fĂŒr Angewandte Wirtschaftsforschung in TĂŒbingen wurde ein Konzept fĂŒr ein niedersĂ€chsisch/baden-wĂŒrttembergisches Firmenpanel entwickelt. Dieses Konzept wurde in einer Pilotstudie anhand der Befragung von 103 Betrieben des Verarbeitenden Gewerbes getestet. Ergebnis der Piloterhebung ist einerseits, daß die Betriebe generell zur Teilnahme an der geplanten Panelerhebung bereit sind und daß hier mit einer sehr guten DatenqualitĂ€t gerechnet werden kann. Andererseits sind der bisher angewandte Fragebogen und das Erhebungsverfahren, ein Mix aus persönlichem Interview und schriftlicher Befragung, noch nicht optimal im Hinblick auf eine möglichst hohe Ausschöpfung. Aus diesen GrĂŒnden wurde ein neues Konzept entwickelt, das in einem weiteren Testlauf ĂŒberprĂŒft werden soll." (Autorenreferat)Panel - Konzeption, Erhebungsmethode

    UnternehmensgrĂ¶ĂŸe und Entlohnung

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    "Der vorliegende Beitrag behandelt den fĂŒr mehrere LĂ€nder festgestellten empirischen Befund, daß große Firmen im allgemeinen höhere Löhne zahlen als kleine Firmen. Nach einer Diskussion der verschiedenen theoretischen Versuche, diese empirische Tatsache zu erklĂ€ren, werden die einzelnen theoretischen Argumente empirisch ĂŒberprĂŒft. Als Datengrundlage dienen die Individualdaten der ersten vier Wellen des Sozio-ökonomischen Panels. Methodisch werden Varianzanalysen, Korrelations- und Regressionsanalysen, einschließlich der SchĂ€tzung von Fixed-Effects und Random-Effects Modellen verwendet. Die empirische Analyse zeigt, daß erhebliche positive Effekte der FirmengrĂ¶ĂŸe auf die Entlohnung erhalten bleiben, auch wenn kontrolliert wird fĂŒr - die Qualifikation der Arbeitnehmer - die Unterschiede in den Arbeitsbedingungen - die Betriebszugehörigkeitsdauer und Fluktuation - die monetĂ€ren Zusatzleistungen von Firmen - die HeterogenitĂ€t der Arbeitnehmer - die Monopolmacht von Betrieben. Der Beitrag schließt mit einigen VorschlĂ€gen fĂŒr die weitere Forschung auf diesem Gebiet." (Autorenreferat)Lohnhöhe, UnternehmensgrĂ¶ĂŸe

    Liebe, Polyamorie und (kein) Sex

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    Polyamorie ist romantische Liebe, die sich auf mindestens zwei Personen bezieht oder beziehen kann. Eine solche Definition klingt leichter als sie es tatsĂ€chlich ist. Um eine genaue und adĂ€quate Analyse von Polyamorie zu leisten, muss, erstens, geklĂ€rt werden, was Liebe – die hier allein als romantische Liebe thematisiert wird – ĂŒberhaupt ist. Sie ist, so soll gezeigt werden, ein spezifisches dispositionales Emotionsmuster, das eine besonders starke Form der subjektiven Bedeutsamkeit konstituiert. Auf dem Hintergrund dieses VerstĂ€ndnisses von romantischer Liebe im Allgemeinen soll dann, zweitens, gezeigt werden, dass polyamore Liebe keine andere Form der Liebe ist als monoamore Liebe, sondern sich als romantische Liebe allein durch die divergierende Anzahl der Personen, die Gegenstand der Liebe sind, von monoamorer Liebe unterscheidet; besonderer Auszeichnungen wie verantwortlich oder konsensuell, wie sie in der Literatur gelĂ€ufig sind, bedarf eine so verstandene polyamore Liebe, um sie hinreichend zu definieren, also nicht. Beachtet man aber, dass es eine Sache ist, polyamore Liebe, verstanden als emotionales PhĂ€nomen, zu definieren, und eine durchaus ganz andere Sache, polyamore Beziehungen zu definieren, bleibt Raum fĂŒr die Frage, wann genau eine Beziehungskonstellation eigentlich polyamor ist, oder wann eine polyamore Person einfach nur mehrere Personen liebt, ohne dass die entstehende Beziehungskonstellation als solche aber polyamor wĂ€re. Schließlich soll, drittens, das VerhĂ€ltnis von Polyamorie und SexualitĂ€t beleuchtet werden. Auch wenn SexualitĂ€t fĂŒr gewöhnlich als eines der hervorstechenden Elemente der romantischen Liebe verstanden wird, gehört sie gar nicht notwendig zu ihr – und jedenfalls hĂ€tte die Behauptung, dass eine notwendige Beziehung zwischen Polyamorie und gelebter SexualitĂ€t besteht, begrifflich-normative Konsequenzen, die man wohl gar nicht haben will. Es wird gezeigt, warum es keine notwendige Beziehung zwischen Liebe und SexualitĂ€t gibt – weder zwischen monoamorer noch zwischen polyamorer Liebe und SexualitĂ€t. Auch asexuelle polyamore (romantische) Liebe ist somit möglich

    Effects of the vasodilating beta-blocker nebivolol on smoking-induced endothelial dysfunction in young healthy volunteers

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    André C Schmidt1, Burkhard Flick1, Elke Jahn2, Peter Bramlage31Charité – Universitätsmedizin Berlin, Institute for Clinical Pharmacology and Toxikology, Berlin, Germany; 2Berlin-Chemie AG, Clinical Research and Medical Information, Berlin, Germany; 3Institute for Clinical Pharmacology, Medical Faculty Carl Gustav Carus, TU Dresden, GermanyObjective: To assess the effect of nebivolol, a highly selective third generation β1-adrenoceptor antagonist with an endothelium-dependent vasodilatory action, on smoking-induced endothelial dysfunction.Research design and methods: This open-label study examined the effect of 14 daily doses of 5 mg nebivolol on forearm blood flow in 21 healthy, young, male, light smokers (≤5 cigarettes/day), measured by plethysmography on Days 1, 7, and 14. The primary endpoint was the difference in forearm blood flow after smoking one standard cigarette from baseline (Day 1) until treatment end on Day 14. Secondary outcomes included the difference in forearm blood flow between Day 1 and Day 7 compared with Day 14 before and after smoking, the effect of nebivolol on blood coagulation parameters, high-sensitive-C-reactive protein (hs-CRP), and the safety and tolerability of nebivolol.Results: Nebivolol for 14 days did not significantly affect forearm blood flow after smoking. On Day 7 of nebivolol treatment, forearm blood flow after smoking was significantly greater than blood flow before smoking (increase of 0.44 mL/min; p = 0.00656). Serum level of hs-CRP showed a marked decrease from Day 1 to Day 14. No changes in coagulation parameters were observed over the course of nebivolol treatment. Nebivolol was well tolerated throughout the study.Conclusions: The increase in forearm blood flow and the marked decrease in hs-CRP over 14 days of treatment suggest that nebivolol has a positive effect on endothelial function in light smokers, but larger studies are required to confirm these observations.Keywords: C-reactive protein, endothelial dysfunction, nebivolol, nitric oxide (NO), smokin

    A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts

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    Many algorithms use 3D accelerometer and/or gyroscope data from inertial measurement unit (IMU) sensors to detect gait events (i.e., initial and final foot contact). However, these algorithms often require knowledge about sensor orientation and use empirically derived thresholds. As align ment cannot always be controlled for in ambulatory assessments, methods are needed that require little knowledge on sensor location and orientation, e.g., a convolutional neural network-based deep learning model. Therefore, 157 participants from healthy and neurologically diseased cohorts walked 5 m distances at slow, preferred, and fast walking speed, while data were collected from IMUs on the left and right ankle and shank. Gait events were detected and stride parameters were extracted using a deep learning model and an optoelectronic motion capture (OMC) system for reference. The deep learning model consisted of convolutional layers using dilated convolutions, followed by two independent fully connected layers to predict whether a time step corresponded to the event of initial contact (IC) or final contact (FC), respectively. Results showed a high detection rate for both initial and final contacts across sensor locations (recall ≄ 92%, precision ≄ 97%). Time agreement was excellent as witnessed from the median time error (0.005 s) and corresponding inter-quartile range (0.020 s). The extracted stride-specific parameters were in good agreement with parameters derived from the OMC system (maximum mean difference 0.003 s and corresponding maximum limits of agreement (−0.049 s, 0.051 s) for a 95% confidence level). Thus, the deep learning approach was considered a valid approach for detecting gait events and extracting stride-specific parameters with little knowledge on exact IMU location and orientation in conditions with and without walking pathologies due to neurological diseases

    SuperMimic – Fitting peptide mimetics into protein structures

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    BACKGROUND: Various experimental techniques yield peptides that are biologically active but have unfavourable pharmacological properties. The design of structurally similar organic compounds, i.e. peptide mimetics, is a challenging field in medicinal chemistry. RESULTS: SuperMimic identifies compounds that mimic parts of a protein, or positions in proteins that are suitable for inserting mimetics. The application provides libraries that contain peptidomimetic building blocks on the one hand and protein structures on the other. The search for promising peptidomimetic linkers for a given peptide is based on the superposition of the peptide with several conformers of the mimetic. New synthetic elements or proteins can be imported and used for searching. CONCLUSION: We present a graphical user interface for finding peptide mimetics that can be inserted into a protein or for fitting small molecules into a protein. Using SuperMimic, promising locations in proteins for the insertion of mimetics can be found quickly and conveniently

    New tools for investigating astrocyte-to-neuron communication

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    Gray matter protoplasmic astrocytes extend very thin processes and establish close contacts with synapses. It has been suggested that the release of neuroactive gliotransmitters at the tripartite synapse contributes to information processing. However, the concept of calcium (Ca(2+))-dependent gliotransmitter release from astrocytes, and the release mechanisms are being debated. Studying astrocytes in their natural environment is challenging because: (i) astrocytes are electrically silent; (ii) astrocytes and neurons express an overlapping repertoire of transmembrane receptors; (iii) the size of astrocyte processes in contact with synapses are below the resolution of confocal and two-photon microscopes (iv) bulk-loading techniques using fluorescent Ca(2+) indicators lack cellular specificity. In this review, we will discuss some limitations of conventional methodologies and highlight the interest of novel tools and approaches for studying gliotransmission. Genetically encoded Ca(2+) indicators (GECIs), light-gated channels, and exogenous receptors are being developed to selectively read out and stimulate astrocyte activity. Our review discusses emerging perspectives on: (i) the complexity of astrocyte Ca(2+) signaling revealed by GECIs; (ii) new pharmacogenetic and optogenetic approaches to activate specific Ca(2+) signaling pathways in astrocytes; (iii) classical and new techniques to monitor vesicle fusion in cultured astrocytes; (iv) possible strategies to express specifically reporter genes in astrocytes

    A Deep Learning Approach for Gait Event Detection from a Single Shank-Worn IMU: Validation in Healthy and Neurological Cohorts

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    Many algorithms use 3D accelerometer and/or gyroscope data from inertial measurement unit (IMU) sensors to detect gait events (i.e., initial and final foot contact). However, these algorithms often require knowledge about sensor orientation and use empirically derived thresholds. As alignment cannot always be controlled for in ambulatory assessments, methods are needed that require little knowledge on sensor location and orientation, e.g., a convolutional neural network-based deep learning model. Therefore, 157 participants from healthy and neurologically diseased cohorts walked 5 m distances at slow, preferred, and fast walking speed, while data were collected from IMUs on the left and right ankle and shank. Gait events were detected and stride parameters were extracted using a deep learning model and an optoelectronic motion capture (OMC) system for reference. The deep learning model consisted of convolutional layers using dilated convolutions, followed by two independent fully connected layers to predict whether a time step corresponded to the event of initial contact (IC) or final contact (FC), respectively. Results showed a high detection rate for both initial and final contacts across sensor locations (recall ≄92%, precision ≄97%). Time agreement was excellent as witnessed from the median time error (0.005 s) and corresponding inter-quartile range (0.020 s). The extracted stride-specific parameters were in good agreement with parameters derived from the OMC system (maximum mean difference 0.003 s and corresponding maximum limits of agreement (-0.049 s, 0.051 s) for a 95% confidence level). Thus, the deep learning approach was considered a valid approach for detecting gait events and extracting stride-specific parameters with little knowledge on exact IMU location and orientation in conditions with and without walking pathologies due to neurological diseases
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