ASSESSMENT OF ANAEROBIC POWER WITH ARM AND LEG WINGATE TESTS IN ATHLETES

The research was carried out with the aim of determining and assessing arm anaerobic power, leg anaerobic power and aerobic capacity in individuals with different branches of active sports. A total of 60 subjects engaged in active sports at Elite level in different branches participated in the study. These branches are; wrestling (group G, n:10), football (Group F, N = 10), bicycle (BI group, n = 10), boxing (BO group, n = 10), taekwondo (TA group, n = 10), and tennis (TE group, n = 10). The research was carried out in the performance Laboratory of Selçuk University School of Physical Education and Sports. For anaerobic measurements, two separate Monark branded Wingate ergometers for arm and leg were used. Shuttle run tests were performed for aerobic measurements. SPSS for Windows 15.0 package program was used in the calculation and assessment of the obtained data. The normality distribution of the measured parameters was determined by the Shapiro-Wilks test. One-way variance analysis (ANOVA) was used to determine the differences between sports branches. In determining the source of difference, the LCD and Dunnett's C were applied from Post-Hoc tests. Significance level was taken as 0.05 in this study. As a result of the leg Wingate ergometer test, the peak power values of wrestlers were found to be significantly different at p<0.05 level compared to those of football, boxing, taekwondo and tennis players. The results of arm Wingate ergometer test showed that the peak power values of the boxers and wrestlers were significantly different in p<0.05 compared to the athletes in other branches. When their MaxVO2 levels were examined, it was observed that the values of cyclists differ significantly in p<0.05 compared to the average of athletes in other branches except wrestlers.  Article visualizations

Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image while highlighting salient features useful for a specific task. This enables us to eliminate the necessity of using explicit external tissue/organ localisation modules when using convolutional neural networks (CNNs). AGs can be easily integrated into standard CNN models such as VGG or U-Net architectures with minimal computational overhead while increasing the model sensitivity and prediction accuracy. The proposed AG models are evaluated on a variety of tasks, including medical image classification and segmentation. For classification, we demonstrate the use case of AGs in scan plane detection for fetal ultrasound screening. We show that the proposed attention mechanism can provide efficient object localisation while improving the overall prediction performance by reducing false positives. For segmentation, the proposed architecture is evaluated on two large 3D CT abdominal datasets with manual annotations for multiple organs. Experimental results show that AG models consistently improve the prediction performance of the base architectures across different datasets and training sizes while preserving computational efficiency. Moreover, AGs guide the model activations to be focused around salient regions, which provides better insights into how model predictions are made. The source code for the proposed AG models is publicly available.Comment: Accepted for Medical Image Analysis (Special Issue on Medical Imaging with Deep Learning). arXiv admin note: substantial text overlap with arXiv:1804.03999, arXiv:1804.0533

Mindfulness en futbolistas masculinos: un estudio transversal

The present study aims to determine whether mindfulness shows a significant difference based on the male soccer players' amateur/ professional status, position, playing experience, history of receiving mentorship, psychological performance counselling or therapy from a sports psychologist, and status of performing mental training. The study was carried out with 233 adult male soccer players and the Mindfulness Inventory for Sport and Personal Information Form was applied to the participants. As a result of the study, it was found that professional soccer players had higher mindfulness levels compared to amateur soccer players. It was observed that mindfulness levels differed in favor of soccer players who received mentorship or psychological performance counselling, performed mental training and had more experience in sports. It was also observed that attackers had higher mindfulness levels compared to midfielders.El presente estudio tiene como objetivo determinar si la atención plena muestra una diferencia significativa en función del estado amateur / profesional de los jugadores de fútbol masculino, la posición, la experiencia de juego, el historial de recibir tutoría, asesoramiento o terapia de rendimiento psicológico de un psicólogo deportivo y el estado de realización de entrenamiento mental. El estudio se realizó con 233 jugadores de fútbol varones adultos y se aplicó a los participantes el Inventario de Mindfulness para el Deporte y el Formulario de Información Personal. Como resultado del estudio, se encontró que los jugadores de fútbol profesionales tenían niveles más altos de atención en comparación con los jugadores de fútbol aficionados. Se observó que los niveles de mindfulness difirieron a favor de los futbolistas que recibieron tutoría o asesoramiento psicológico de desempeño, realizaron entrenamiento mental y tenían más experiencia en deportes. También se observó que los atacantes tenían mayores niveles de atención en comparación con los mediocampistas.  

Phenolic components, antioxidant activity, and mineral analysis of Capparis spinosa L

In addition to being consumed as food, caper (Capparis spinosa L.) fruits are also used in folk medicine to treat inflammatory disorders, such as rheumatism. C. spinosa L. is rich in phenolic compounds, making it increasingly popular because of its components’ potential benefits to human health. We analyzed a number of individual phenolic compounds and investigated in vitro biological activities of C. spinosa L. Sixteen phenolic constituents were identified using reverse phase-high performance liquid chromatography (RP-HPLC). Total phenolic compounds (TPCs), ferric reducing antioxidant power (FRAP) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity were used as determinants of antioxidant capacity. C. spinosa L. exhibited strong antioxidant activity and contained high levels of antioxidant compounds. Gentisic, sinapic and benzoic acid were detected in C. spinosa L. No gallic acid, proto-catechuic acid, proto-catechuic aldehyde, chlorogenic acid, p-OH benzoic acid, vanillic acid, caffeic acid, syringic acid, vanillin, syringaldehyde, p-coumaric acid, ferulic acid or rosmarinic acid were identified. Iron and zinc were present at high levels in samples. C. spinosa L. appears to be a good source of antioxidants and minerals that might serve to protect health and combat several diseases.Key words: Antioxidant, capers, Capparis spinosa L., phenolics

DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks

In this paper, we propose DeepCut, a method to obtain pixelwise object segmentations given an image dataset labelled with bounding box annotations. It extends the approach of the well-known GrabCut method to include machine learning by training a neural network classifier from bounding box annotations. We formulate the problem as an energy minimisation problem over a densely-connected conditional random field and iteratively update the training targets to obtain pixelwise object segmentations. Additionally, we propose variants of the DeepCut method and compare those to a naive approach to CNN training under weak supervision. We test its applicability to solve brain and lung segmentation problems on a challenging fetal magnetic resonance dataset and obtain encouraging results in terms of accuracy

Cutaneous Metastasis of Pancreatic Carcinoma Seen in the Left Gluteal Region and Axilla

Pancreatic cancer is usually high-grade and metastatic when diagnosed. Skin metastasis is very rare and is usually found in the periumbilical area. Non-umbilical metastasis is extremely rare. Only 19 cases have been reported in the literature. Only one case in the buttock has been described: thus our case is the second one known. In this note, we present a cutaneous metastasis of a pancreatic cancer case that was admitted to the clinic with a mass each on the left buttock and in the left axilla, surgically treated for palliation. We include a review of the literature