Seasonal analysis of match load in professional soccer players: An observational cohort study of a Swiss U18, U21 and first team

The aim of this study was to quantify and compare various external match load measures in three age groups and leagues in male soccer (U18 in highest league of their age group vs U21 in fourth highest league vs first team in highest league). In this retrospective observational cohort study accelerations, decelerations, absolute and relative high-speed running as well as sprint distance, dynamic stress load, explosive distance, high intensity bursts total distance, high metabolic load (HML) distance, speed intensity, total distance, total time, and total loading were assessed in 416 individual player matches of 59 players. All these external load measures showed large inter-individual variability. At a group level, one-way ANOVAs or Kruskal–Wallis tests revealed statistically significant differences between the three teams for all measures analyzed (all p < 0.05), except accelerations. The first team displayed statistically significant higher dynamic stress load, explosive distance, HML distance, speed intensity, total distance and total loading compared to the two youth teams (all p < 0.05). The U18 featured statistically significant higher number of decelerations, absolute and relative high-speed running distance, high metabolic load distance, speed intensity, relative sprint distance, total distance, and total time than the U21, while for U21 higher dynamic stress load was observed than for U18 (all p < 0.05). Based on our data we conclude a routinely monitoring of match loads of different age groups and competitive settings to be required to 1) provide an indication of what players need to be prepared for, 2) track the athletic and match evolution, and 3) individually tailor training programs allowing players to fulfill the short- and long-term sport-specific requirements

Self-Supervised Learning for Monocular Depth Estimation from Aerial Imagery

Supervised learning based methods for monocular depth estimation usually require large amounts of extensively annotated training data. In the case of aerial imagery, this ground truth is particularly difficult to acquire. Therefore, in this paper, we present a method for self-supervised learning for monocular depth estimation from aerial imagery that does not require annotated training data. For this, we only use an image sequence from a single moving camera and learn to simultaneously estimate depth and pose information. By sharing the weights between pose and depth estimation, we achieve a relatively small model, which favors real-time application. We evaluate our approach on three diverse datasets and compare the results to conventional methods that estimate depth maps based on multi-view geometry. We achieve an accuracy {\delta}1.25 of up to 93.5 %. In addition, we have paid particular attention to the generalization of a trained model to unknown data and the self-improving capabilities of our approach. We conclude that, even though the results of monocular depth estimation are inferior to those achieved by conventional methods, they are well suited to provide a good initialization for methods that rely on image matching or to provide estimates in regions where image matching fails, e.g. occluded or texture-less regions

Self-Supervised Learning for Monocular Depth Estimation from Aerial Imagery

Supervised learning based methods for monocular depth estimation usually require large amounts of extensively annotated training data. In the case of aerial imagery, this ground truth is particularly difficult to acquire. Therefore, in this paper, we present a method for self-supervised learning for monocular depth estimation from aerial imagery that does not require annotated training data. For this, we only use an image sequence from a single moving camera and learn to simultaneously estimate depth and pose information. By sharing the weights between pose and depth estimation, we achieve a relatively small model, which favors real-time application. We evaluate our approach on three diverse datasets and compare the results to conventional methods that estimate depth maps based on multi-view geometry. We achieve an accuracy δ1:25 of up to 93.5 %. In addition, we have paid particular attention to the generalization of a trained model to unknown data and the self-improving capabilities of our approach. We conclude that, even though the results of monocular depth estimation are inferior to those achieved by conventional methods, they are well suited to provide a good initialization for methods that rely on image matching or to provide estimates in regions where image matching fails, e.g. occluded or texture-less regions

What do perform competence models? Educational drafts as basis for Dialogic Learning at the Gymnasium

"Kompetenzmodelle, die von Lehrkräften im täglichen Fremdsprachenunterricht verwendet werden, sollten von der natürlichen Komplexität menschlichen Sprachhandelns ausgehen und nicht (nur) auf einer segmentierenden Grammatikprogression basieren. Zudem sollten sie personale, soziale und fachliche Kompetenzen der Schülerinnen und Schüler gleichermaßen fördern". Die Autoren stellen zwei Kompetenzmodelle vor, "welche sich auf unterschiedliche Weise mit Schreibkompetenz in einer Fremdsprache befassen": 1. das Kompetenzmodell aus dem "Gemeinsamen europäischen Referenzrahmen für Sprachen" (GeR), 2. ein Kompetenzmodell, das auf dem Konzept Dialogischen Lernens basiert. (DIPF/Orig./Un)Competency models used by teachers of foreign languages for planning and assessing their courses should be based on the complexity of authentic human communication rather than grammatical progression alone. They should also support and integrate personal, social and demand-specific competencies of students. (DIPF/Orig.

ReS2tAC -- UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices

With the emergence of low-cost robotic systems, such as unmanned aerial vehicle, the importance of embedded high-performance image processing has increased. For a long time, FPGAs were the only processing hardware that were capable of high-performance computing, while at the same time preserving a low power consumption, essential for embedded systems. However, the recently increasing availability of embedded GPU-based systems, such as the NVIDIA Jetson series, comprised of an ARM CPU and a NVIDIA Tegra GPU, allows for massively parallel embedded computing on graphics hardware. With this in mind, we propose an approach for real-time embedded stereo processing on ARM and CUDA-enabled devices, which is based on the popular and widely used Semi-Global Matching algorithm. In this, we propose an optimization of the algorithm for embedded CUDA GPUs, by using massively parallel computing, as well as using the NEON intrinsics to optimize the algorithm for vectorized SIMD processing on embedded ARM CPUs. We have evaluated our approach with different configurations on two public stereo benchmark datasets to demonstrate that they can reach an error rate as low as 3.3%. Furthermore, our experiments show that the fastest configuration of our approach reaches up to 46 FPS on VGA image resolution. Finally, in a use-case specific qualitative evaluation, we have evaluated the power consumption of our approach and deployed it on the DJI Manifold 2-G attached to a DJI Matrix 210v2 RTK unmanned aerial vehicle (UAV), demonstrating its suitability for real-time stereo processing onboard a UAV

Overestimation of Maximal Aerobic Speed by the Université de Montréal Track Test and a 1500-m-Time Trial in Soccer

Introduction: Maximal aerobic speed (MAS), usually measured by cardiopulmonary exercise testing (CPET) on a treadmill, is gaining popularity in soccer to determine aerobic performance. Several field tests are used to estimate MAS, although, gold standard methods are still not clarified. Therefore, this work aims 1) to compare two different CPET based methods to assess MAS and 2) to investigate the convergent validity of two common field tests to estimate MAS in soccer. Methods: Thirteen trained male soccer players completed an CPET on a treadmill to determine two VO2-kinetic based definitions of MAS (MASPlateau = speed at onset of VO2-plateau = gold standard; MAS30s = first speed of 30-s-interval of VO2max), the Université de Montreal Track Test (UMTT; VUMTT = speed of the last stage), and a 1500-m-time trial (1500-m-TT; V1500m = average speed). MASPlateau, MAS30s, VUMTT, and V1500m were compared using ANOVA. Additionally, limits of agreement analysis (LoA), Pearson’s r, and ICC were calculated between tests. Results: MAS30s, VUMTT, and V1500m significantly overestimated MASPlateau by 0.99 km/h (ES = 1.61; p < 0.01), 1.61 km/h (ES = 2.03; p < 0.01) and 1.68 km/h (ES = 1.77; p < 0.01), respectively, with large LoA (-0.21 ≤ LoA≤3.55), however with large-to-very large correlations (0.65 ≤ r ≤ 0.87; p ≤ 0.02; 0.51 ≤ ICC≤ 0.85; p ≤ 0.03). Discussion: The overestimation and large LoA of MASPlateau by all estimates indicate that 1) a uniform definition of MAS is needed and 2) the UMTT and a 1500-m-TT seem questionable for estimating MAS for trained soccer players on an individual basis, while regression equations might be suitable on a team level. The results of the present work contribute to the clarification of acquisition of MAS in soccer

Comparison of Written and Spoken Instruction to Foster Coordination between Diagram and Equation in Undergraduate Physics Education

Visual–graphical representations are used to visualise information and are therefore key components of learning materials. An important type of convention-based representation in everyday contexts as well as in science, technology, engineering, and math (STEM) disciplines are vector field plots. Based on the cognitive theory of multimedia learning, we aim to optimize an instruction with symbolical-mathematical and visual-graphical representations in undergraduate physics education through spoken instruction combined with dynamic visual cues. For this purpose, we conduct a pre-post study with 38 natural science students who are divided into two groups and instructed via different modalities and with visual cues on the graphical interpretation of vector field plots. Afterward, the students rate their cognitive load. During the computer-based experiment, we record the participants’ eye movements. Our results indicate that students with spoken instruction perform better than students with written instruction. This suggests that the modality effect is also applicable to mathematical-symbolical and convention-based visual-graphical representations. The differences in visual strategies imply that spoken instruction might lead to increased effort in organising and integrating information. The finding of the modality effect with higher performance during spoken instruction could be explained by deeper cognitive processing of the material

Match-related physical performance in professional soccer: Position or player specific?

The purpose of this study was to examine to what extent the physical match performance of professional soccer players is both position and player specific. First, official match data from the 2019/20 German Bundesliga season was used to search for players that met the inclusion criteria of playing a minimum of four entire matches in at least two different playing positions. Overall, 25 players met the criteria prior to the COVID-19 induced break, playing a minimum of eight matches. Second, the physical match performance of these players was analyzed separately for each position they played. The following four parameters were captured: total distance, high-intensity distance, sprinting distance, and accelerations. Third, the 25 players’ physical match performance data was then compared to normative data for each position they played to understand whether players adapted their physical performance (position dependent), or maintained their performance regardless of which position they were assigned to (position independent). When switching the position, the change in physical match performance of the respective players could be explained by 44–58% through the normative positional data. Moreover, there existed large individual differences in the way players adapted or maintained their performance when acting in different positions. Coaches and practitioners should be aware that some professional soccer players will likely incur differences in the composition of physical match performance when switching positions and therefore should pay special consideration for such differences in the training and recovery process of these players

Exploring real-time functional magnetic resonance imaging neurofeedback in adolescents with disruptive behavior disorder and callous unemotional traits

Introduction: Adolescents with increased callous unemotional traits (CU traits) in the context of disruptive behavior disorder (DBD) show a persistent pattern of antisocial behavior with shallow affect and a lack of empathy or remorse. The amygdala and insula as regions commonly associated with emotion processing, empathy and arousal are implicated in DBD with high CU traits. While behavioral therapies for DBD provide significant but small effects, individualized treatments targeting the implicated brain regions are missing. Methods: In this explorative randomized controlled trial we randomly assigned twenty-seven adolescents with DBD to individualized real-time functional magnetic resonance neurofeedback (rtfMRI-NF) or behavioral treatment as usual (TAU). Visual feedback of either amygdala or insula activity was provided during rtfMRI-NF by gauges and included a simple and concurrent video run plus a transfer run. A linear mixed model (LMM) was applied to determine improvement of self-regulation. Specificity was assessed by correlating individual self-regulation improvement with clinical outcomes. Results: The rtfMRI-NF (n = 11) and TAU (n = 10) completers showed comparable and significant clinical improvement indicating neither superiority nor inferiority of rtfMRI-NF. The exploratory LMM revealed successful learning of self-regulation along the course of training for participants who received feedback from the amygdala. A significant exploratory correlation between individual target region activity in the simple run and clinical improvement was found for one dimension of DBD. Conclusions: This exploratory study demonstrated feasibility and suggests clinical efficacy of individualized rtfMRI-NF comparable to active TAU for adolescents with DBD and increased CU traits. Further studies are needed to confirm efficacy, specificity and to clarify underlying learning mechanisms