Modular control of human movement during running: An open access data set

The human body is an outstandingly complex machine including around 1000 muscles and joints acting synergistically. Yet, the coordination of the enormous amount of degrees of freedom needed for movement is mastered by our one brain and spinal cord. The idea that some synergistic neural components of movement exist was already suggested at the beginning of the 20th century. Since then, it has been widely accepted that the central nervous system might simplify the production of movement by avoiding the control of each muscle individually. Instead, it might be controlling muscles in common patterns that have been called muscle synergies. Only with the advent of modern computational methods and hardware it has been possible to numerically extract synergies from electromyography (EMG) signals. However, typical experimental setups do not include a big number of individuals, with common sample sizes of 5 to 20 participants. With this study, we make publicly available a set of EMG activities recorded during treadmill running from the right lower limb of 135 healthy and young adults (78 males and 57 females). Moreover, we include in this open access data set the code used to extract synergies from EMG data using non-negative matrix factorization (NMF) and the relative outcomes. Muscle synergies, containing the time-invariant muscle weightings (motor modules) and the time-dependent activation coefficients (motor primitives), were extracted from 13 ipsilateral EMG activities using NMF. Four synergies were enough to describe as many gait cycle phases during running: weight acceptance, propulsion, early swing, and late swing. We foresee many possible applications of our data that we can summarize in three key points. First, it can be a prime source for broadening the representation of human motor control due to the big sample size. Second, it could serve as a benchmark for scientists from multiple disciplines such as musculoskeletal modeling, robotics, clinical neuroscience, sport science, etc. Third, the data set could be used both to train students or to support established scientists in the perfection of current muscle synergies extraction methods. All the data is available at Zenodo (doi: 10.5281/zenodo.1254380). © 2018 Frontiers Media S.A.All right reserved

Doing Gender Im Technisch-Naturwissen-Schaftlichen Bereich

Für die Lösung des Nachwuchsproblems in den Technikwissenschaften spielt die Gewinnung von Frauen eine zentrale Rolle. Die in der Expertise dargestellten Befunde verdeutlichen dreierlei: (1) In den Natur- und Technikwissenschaften "verliert" man Frauen sehr früh im Lebensverlauf. (2) Wie beim Durchlauf eines Trichters (leaking pipeline) verringert sich mit jeder Bildungs- und Karrierestufe die Anzahl von Frauen in diesen Fächern und Berufen. (3) Die Erhöhung des Interesses für Technikwissenschaften von Mädchen und Frauen ist nicht nur "ein Problem" für das Bildungssystem, sondern ganz wesentlich auch des Arbeitsmarktes. Die Befunde der Expertise zeigen, dass es unbedingt notwendig ist, jungen Frauen, die in technischen Berufen gut ausgebildet sind, eine höhere Chance als bisher zu geben, (a) ihren Beruf aus dem Bereich Mathematik, Informatik, Naturwissenschaften, Technik (im Folgenden kurz: MINT) auszuüben und (b) dies auch mit den gleichen Gratifikationen wie Männer. Diese Herausforderung muss - und zwar unabhängig von der Nachfrage nach neuem Personal in technischen Berufen - schnell gemeistert werden, wenn Wirtschaft und Politik ein ernst gemeintes Interesse an "Frauen in MINT-Berufen" besitzen

Cognitive Reappraisal, Emotional Expression and Mindfulness in Adaptation to Bereavement: A Longitudinal Study

Data for SPSS, Syntax for SPSS, Output for SPSS. Please note: this is a 3-wave survey dataset. Sociodemographic and loss characteristics are derived from the first wave (T0), main variables are assessed at the second wave (T1) and third wave (T2). Connected to the paper with the same title, published in Anxiety, Stress, & Coping (doi: 10.1080/10615806.2023.2165647) Abstract from the paper: Maladaptive emotion regulation strategies increase prolonged grief and depressive symptoms following bereavement. However, less is known about the role of adaptive emotion regulation strategies in adaptation to loss. Therefore, we examined the concurrent and longitudinal associations of three putative adaptive emotion regulation strategies (cognitive reappraisal, emotional expression, and mindfulness) with prolonged grief and depression symptoms. A two-wave longitudinal survey was conducted. A sample of 397 bereaved Dutch adults (89% female, mean age 53 years) completed validated questionnaires to assess trait cognitive reappraisal, emotional expression, mindfulness, and prolonged grief and depression symptoms at baseline (T1) and 344 participants completed symptom measures again six months later (T2). Results: Zero-order correlations demonstrated that mindfulness, cognitive reappraisal, and emotional expression relate negatively to T1 and T2 symptom levels. In multiple regression analyses, controlling for relevant background variables, all emotion regulation strategies related negatively to T1 prolonged grief and depression symptoms. In multiple regression analyses, controlling for T1 symptoms and background variables, mindfulness predicted lower T2 depression symptoms. Adaptive emotion regulation strategies relate negatively to post-loss psychopathology symptoms, yet only mindfulness longitudinally predicts lower depression symptoms. Dispositional mindfulness may be a protective factor in psychological adaptation to bereavement