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.
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Abstract: Plastic pollution is a major issue of the current century. This waste is found in seas, freshwater, lakes, rivers, coastal areas, and soil. In this article, this article discusses the various sources of plastic pollution, including the manufacturing process of plastics and the addition of materials to improve their properties, as well as the use of single-use plastics that are not recyclable, in addition to burning and illegal waste disposal in the open. The impact on public health is through human exposure to toxins from plastics in the environment directly through inhaling dust and fumes, consuming contaminated food and drink, and skin contact. Indirectly, when marine creatures consume microplastics, they will find their way
... Show MoreIsatin is a heterocyclic molecule that belongs to one of the most important classes of organic compounds known as indolines. Isatin, isatin analogs, and their Schiff bases have recently attracted a lot of attention in medicinal chemistry. Isatin, itself, shows various biological activities such as antiviral, anticancer, antimicrobial, anti-inflammatory, analgesic, antioxidant, and anticonvulsant. Bis- Schiff bases containing isatin moiety have been known to possess a wide spectrum of pharmacological activities. This review offers up-to-date information on the most active isatin bis-Schiff bases, which would include anticancer, antimicrobial, antiviral, anticonvulsant, anti-inflammatory, and analgesic activities. These observations c
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Isatin is a heterocyclic molecule that belongs to one of the most important classes of organic compounds known as indolines. Isatin, isatin analogs, and their Schiff bases have recently attracted a lot of attention in medicinal chemistry. Isatin, itself, shows various biological activities such as antiviral, anticancer, antimicrobial, anti-inflammatory, analgesic, antioxidant, and anticonvulsant. Bis- Schiff bases containing isatin moiety have been known to possess a wide spectrum of pharmacological activities. This review offers up-to-date information on the most active isatin bis-Schiff bases, which would include anticancer, antimicrobial, antiviral, anticonvulsant, anti-inflammatory, and analgesic activities. These observations c
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Rivers Tigris and Euphrates, as well as the wetlands in southern Iraq and the Diyala River, were all included in the evaluation of earlier studies on the variety and factors impacting fish in Iraqi waters. Different studies documented different types, and the number of species recorded varied between the studies, which could be explained by the registration of some species, synonyms, differs from the registration of some species with synonymous names By mistake, as well as recording new species in times that followed some previous studies, Also, the difference in some factors, including the pollution of some waterways, leads to a difference in the existing species, so we find the presence of species that are tolerant of pollution. There are
... Show MoreTo date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
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