The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when diagnosing a tissue sample. Small, unnoticeable changes in pixel density may indicate the beginning of cancer or tear tissue in the early stages. These details even expert pathologists might miss. Artificial intelligence (A.I.) and D.L. revolutionized radiology by enhancing efficiency and accuracy of both interpretative and non-interpretive jobs. When you look at AI applications, you should think about how they might work. Convolutional Neural Network (C.N.N.) is a part of D.L. that can be used to diagnose knee problems. There are existing algorithms that can detect and categorize cartilage lesions, meniscus tears on M.R.I., offer an automated quantitative evaluation of healing, and forecast who is most likely to have recurring meniscus tears based on radiographs.
Abstract: Persian literature, after the spread of Islam in Pars, received a lot of influence from the subtle and rhetorical details of the Holy Quran. This effect is more in poetry than in prose because the weights of Persian poetry are closer to the melody of the Qur'an and its weights.The effectiveness of most of the prose works is only in the Quranic themes and words. Persian poetry that has benefited from various sciences of rhetoric, including semantics, eloquence and rhetoric. The degree and manner of influence of each of the didactic, lyrical, epic and travelogue literary types is different from the rhetorical points of the Quran. The instructions under educational literature have benefited the least from Quranic rhetoric. The max
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By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy
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There is a real problem when adding micro elements to the soil as a result of fixation, sedimentation, washing or toxicity, and thus economic loss. The plant needs micro elements in very small quantities that do not burn the leaves or cause poisoning to plants, including iron, zinc and boron, as they are essential elements for growth and completing the plant's life cycle, and increase the plant's resistance to diseases and insects, activate enzymes, and form the chlorophyll molecule, in addition to their role in oxidation and reduction processes and vital processes. The use of fertilizers with their modern technology has made the process of activating seeds or foliar nutrition a matter of interest to researchers as a complementary process t
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Over the past ten years, tumor markers have played an increasingly important role in clinicaloncology. This trend is expected to continue as technology advances and our knowledge of thehuman body and disease processes grows. In the treatment of cancer, tumor markers are widelyused for a variety of purposes, including screening, selecting a management strategy,determining the prognosis, and post-therapy follow-up. A comprehensive of the fundamentalsof pathophysiology and identification strategies for each specific malignancy is necessary fortheir prudent application in clinical practice. Oncology's use of cancer biomarkers hastransformed the way that cancer is treated, and led to notable improvements in patient outcomesand cancer tre
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hemorrhagic fever (VHF), one of which is Filoviridae. The Filoviridae family includes the Ebola virus , is responsible for the current VHF outbreak in West Africa. Viral hemorrhagic fevers (VHFs) occur in various regions around the world, yet traditional diagnostic testing for these diseases has typically been conducted in major reference laboratories located in Europe and the United States. In this review, we explore the current understanding of the mechanisms driving the pathogenesis of viral hemorrhagic fevers (VHFs) and examine the progress in developing preventive and therapeutic strategies for these infections.
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Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.
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The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed
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