VO2max changes in English futsal players after a 6-week period of specific small-sided games training

Futsal is a high-intensity, intermittent sport where accelerations and short sprints are performed at maximal or sub-maximal intensity. These efforts are interspersed by brief recovery periods, during 2 halves of 20 minutes stopping clock. Aerobic endurance inevitably plays a key role in the players’ performance. The aim of this study was to analyse the VO2 max progression and the agility (with and without ball) of English futsal players during a 6-week period of small-sided games practice. Two teams volunteered to participate in this study; an experimental group (EG), which performed a specialised small-sided training regime and a control group (CG) (normal training regime). VO2max was estimated from the results of the 20-metre Multi-Stage Fitness Test. The VO2max of the futsal players in the EG improved significantly (58.73±2.41 ml/kg/min vs. 60.11 ± 2.99 ml/kg/min, p=0.04). The same player's agility and agility with ball performance did not report any significant changes in either group. The results showed that periodisation, training sessions and methods based on small-sided games, which implied a change in the number of players, the size of the pitch and the task constraints, were adequate to increase aerobic endurance

ULTRA-HIGH PRECISION UAV-BASED LIDAR AND DENSE IMAGE MATCHING

This paper presents a study on the potential of ultra-high accurate UAV-based 3D data capture. It is motivated by a project aiming at the deformation monitoring of a ship lock and its surrounding. This study is part of a research and development project initiated by the German Federal Institute of Hydrology (BfG) in Koblenz in partnership with the Office of Development of Neckar River Heidelberg (ANH). For this first official presentation of the project, data from the first flight campaign will be analysed and presented. Despite the fact that monitoring aspects cannot be discussed before data from additional flight campaigns will be available later this year, our results from the first campaign highlight the potential of high-end UAV-based image and LiDAR sensors and their data fusion. So far, only techniques from engineering geodesy could fulfil the aspired accuracy demands in the range of millimetres. To the knowledge of the authors, this paper for the first time addresses such ultra-high accuracy applications by combing high precision UAV-based LiDAR and dense image matching. As the paper is written at an early stage of processing only preliminary results can be given here

USE AND OPTIMISATION OF PAID CROWDSOURCING FOR THE COLLECTION OF GEODATA

Crowdsourcing is a new technology and a new business model that will change the way in which we work in many fields in the future. Employers divide and source out their work to a huge number of anonymous workers on the Internet. The division and outsourcing is not a trivial process but requires the definition of complete new workflows – from the definition of subtasks, to the execution and quality control. A popular crowdsourcing project in the field of collection of geodata is OpenStreetMap, which is based on the work of unpaid volunteers. Crowdsourcing projects that are based on the work of unpaid volunteers need an active community, whose members are convinced about the importance of the project and who have fun to collaborate. This can only be realized for some tasks. In the field of geodata collection many other tasks exist, which can in principle be solved with crowdsourcing, but where it is difficult to find a sufficient large number of volunteers. Other incentives must be provided in these cases, which can be monetary payments

NEURAL NETWORKS FOR THE CLASSIFICATION OF BUILDING USE FROM STREET-VIEW IMAGERY

Within this paper we propose an end-to-end approach for classifying terrestrial images of building facades into five different utility classes (commercial, hybrid, residential, specialUse, underConstruction) by using Convolutional Neural Networks (CNNs). For our examples we use images provided by Google Street View. These images are automatically linked to a coarse city model, including the outlines of the buildings as well as their respective use classes. By these means an extensive dataset is available for training and evaluation of our Deep Learning pipeline. The paper describes the implemented end-to-end approach for classifying street-level images of building facades and discusses our experiments with various CNNs. In addition to the classification results, so-called Class Activation Maps (CAMs) are evaluated. These maps give further insights into decisive facade parts that are learned as features during the training process. Furthermore, they can be used for the generation of abstract presentations which facilitate the comprehension of semantic image content. The abstract representations are a result of the stippling method, an importance-based image rendering

Diastereoselective Spiroketalization: Stereocontrol Using An Iron(0) Tricarbonyl Diene Complex

It has been demonstrated that an element of planar chirality can influence the formation of an adjacent spiroketal stereocenter. Appropriately functionalized enantiomerically pure 1- and 2-sulfinyl 1,3-dien-5-ones and their corresponding iron(0) tricarbonyl complexes (7, 17) have been prepared, and the derived spiroketals (8, 18) are made in good to excellent diastereoselectivity. A preliminary exploration of the combined effects of planar and central chirality upon the diastereoselectivity revealed matched and mismatched combinations (14)

Loss-of-Function Mutations in ELMO2 Cause Intraosseous Vascular Malformation by Impeding RAC1 Signaling

Vascular malformations are non-neoplastic expansions of blood vessels that arise due to errors during angiogenesis. They are a heterogeneous group of sporadic or inherited vascular disorders characterized by localized lesions of arteriovenous, capillary, or lymphatic origin. Vascular malformations that occur inside bone tissue are rare. Herein, we report loss-of-function mutations in ELMO2 (which translates extracellular signals into cellular movements) that are causative for autosomal-recessive intraosseous vascular malformation (VMOS) in five different families. Individuals with VMOS suffer from life-threatening progressive expansion of the jaw, craniofacial, and other intramembranous bones caused by malformed blood vessels that lack a mature vascular smooth muscle layer. Analysis of primary fibroblasts from an affected individual showed that absence of ELMO2 correlated with a significant downregulation of binding partner DOCK1, resulting in deficient RAC1-dependent cell migration. Unexpectedly, elmo2-knockout zebrafish appeared phenotypically normal, suggesting that there might be human-specific ELMO2 requirements in bone vasculature homeostasis or genetic compensation by related genes. Comparative phylogenetic analysis indicated that elmo2 originated upon the appearance of intramembranous bones and the jaw in ancestral vertebrates, implying that elmo2 might have been involved in the evolution of these novel traits. The present findings highlight the necessity of ELMO2 for maintaining vascular integrity, specifically in intramembranous bones.WoSScopu