ملخص البحث: يعد اسلوب تدريب المقاومات المرنة واحد من اساليب تدريب القوة العضلية فهو النظام الذي يتم من خلاله استخدام تمرينات يتم ادائها ضد مقاومات متغيرة مثل الحبال المطاطية او اشرطة الساندو، ويمتاز هذا الاسلوب بتغير الشدة خلال اداء التمرين الواحد اي ان كلما تم مط الحبل المطاطي ازدادت مقاومته وبالتالي فان اللاعب يستخرج قوته اكثر كلما اقترب الى مركزية الحركة في التمرين وهذا هو جوهر الاختلاف بينه وبين استخد

A la fin du XVIIIe siècle, les penseurs français dont Rousseau et Saint-Pierre, commencent à mettre en question la civilisation européenne. Dans leurs œuvres les plus importantes, ces deux auteurs parlent de la société européenne d'une façon très banale. Ils font, par contre, une invitation à la Solitude et l'isolement dans la nature afin d'éviter la corruption de l'âme par la société mondaine. Ces écrivains-penseurs croient que la société peut gâter l'humanité de l'individu. Ils suggèrent à travers les images innocentes de leurs principaux personnages vivant dans la campagne, un monde idéal où il n'y a que pureté et chasteté.  Dans les deux œuvres que nous avons choisies (Paul et Virginie de Bernardin de

This research paper studies the use of an environmentally and not expensive method to degrade Orange G dye (OG) from the aqueous solution, where the extract of ficus leaves has been used to fabricate the green bimetallic iron/copper nanoparticles (G-Fe/Cu-NPs). The fabricated G‑Fe/Cu-NPs were characterized utilizing scanning electron microscopy, BET, atomic force microscopy, energy dispersive spectroscopy, Fourier-transform infrared spectroscopy and zeta potential. The rounded and shaped as like spherical nanoparticles were found for G-Fe/Cu‑NPs with the size ranged 32-59 nm and the surface area was 4.452 m²/g. Then the resultant nanoparticles were utilized as a Fenton-like oxidation catalyst. The degradation efficiency of

ي لا ماق ثحبلا فادهأ قيقحتلو ثحبلا ةنيعل نايبتسا ءارجاو فراصملل ةيلاملا مئاوقلا ليلحتب ثحاب اهمهأ ناك تاجاتنتسا ىلإ ثحابلا لصوت دقو لإ صاخ معد دوجو مدع نم ةيفرصملا رطاخملا ةراد ةروصب اهدوجو مدعو فراصملل ةماعلا تارادلاا يف اهدوجو رصتقي ثيح ،ايلعلا تاهجلا لبق نم ديزي امم ،عورفلا يف ةلاعف مدع ةجيتن عورفلا نم ةدلوتملاو فراصملا اههجاوت يتلا رطاخملا اهمهأ ناك تايصوت ىلإ ثحابلا لصوت دقو امك ،ةيفرصملا تلاماعم

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec