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

Review of dohan eherenfest et al. (2009) on “classification of platelet concentrates: from pure platelet-rich plasma (p-prp) to leucocyte- and platelet-rich fibrin (l-prf)”

This classic discusses the original publication of Dohan Eherenfest et al. on "Classification of platelet concentrates: from pure platelet-rich plasma (P-PRP) to leucocyte- and platelet-rich fibrin (L-PRF)", in which the authors propose four categories of platelet concentrates depending on their leukocyte and fibrin content (P-PRP, leucocyte- and platelet-rich plasma (L-PRP), pure platelet-rich fibrin (P-PRF), and L-PRF) to group a "jungle" of products in which the term platelet-rich plasma (PRP) was used indistinctly. They were able to identify common factors such as: (1) the use of anticoagulant and immediate centrifugation of the blood after its collection, (2) most preparation techniques allowed platelet concentrate preparation within an hour, (3) the centrifugation aimed to separate the blood in layers that would allow the extraction of specific fractions, and (4) the product was activated with thrombin or calcium chloride. The reviewed manuscript has been listed among the most cited PRP articles in regenerative medicine, with more than 800 citations, driving the current scientific research and clinical practice by categorizing L-PRP and P-PRP (now, leukocyte-poor PRP). The classification has also opened the door to understanding intrinsic biological mechanisms between the platelets, leukocytes, fibrin, and growth factors, later considered for studying the proliferation and differentiation of cells in different tissues affected by PRP. Since the initial classification of platelet concentrates, several other classification systems have been proposed and published in the current literature, such as the PAW, Mishra, PLRA, DEPA, MARSPILL, etc. These classifications have identified important aspects of PRP that affect the biological composition and, ultimately, the indications and outcomes. To date, there is still a lack of standardization in sample preparation, cohort heterogeneity, and incomplete reporting of sample preparation utilized, leading to a lack of clarity and challenging researchers and clinicians

Minimal muscle damage after a marathon and no influence of beetroot juice on inflammation and recovery

This study examined whether beetroot juice (BTJ) would attenuate inflammation and muscle damage following a marathon. Using a double blind, independent group’s design, 34 runners (~16 previous marathons completed) consumed either BTJ or an isocaloric placebo (PLA) for 3 days following a marathon. Maximal isometric voluntary contractions (MIVC), countermovement jumps (CMJ), muscle soreness, serum cytokines, leucocytosis, creatine kinase (CK), high sensitivity C-reactive protein (hs-CRP) and aspartate aminotransferase (AST) were measured pre, post, and on the 2 days after the marathon. CMJ and MIVC were reduced after the marathon (P0.05). Muscle soreness was increased in the day after the marathon (BTJ; 45±48 vs. PLA; 46±39 mm) and had returned to baseline by day 2, irrespective of supplementation (P=0.694). Cytokines (Interleukin-6; IL-6, interleukin-8, tumour necrosis factor-α) were increased immediately post-marathon but apart from IL-6 had returned to baseline values by day 1 post. No interaction effects were evident for IL-6 (P=0.213). Leucocytes increased 1.7 fold after the race and remained elevated 2 days post, irrespective of supplement (P<0.0001). CK peaked at 1 day post marathon (BTJ: 965±967 & PLA: 1141±979 IU·L-1) and like AST and hs-CRP, was still elevated 2 days after the marathon (P<0.05); however, no group differences were present for these variables. Beetroot juice did not attenuate inflammation or reduce muscle damage following a marathon, possibly because most of these indices were not markedly different from baseline values in the days after the marathon

Untersuchungen zur Tauchschmierung schnellaufender Kegelradgetriebe

In an experimental study the performance of flood lubrication in bevel gear boxes has been characterized. At a peripheral velocity of 20-60 m/s the dependence of frictional loss, oil and gear temperatures on the operation parameters specific load, dripping depth, oil additices and oil supply conditions have been investigated. It is demonstrated that flood lubrication of bevel gears represents already at low dipping depth a lubrication method reliable in service as long as a balanced heat flow is maintained by forced cooling. A limiting peripheral velocity has not been detected in this study. (WEN)SIGLEAvailable from TIB Hannover: RN 8590(398) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

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