Urbanization led to significant changes in the properties of the land surface. That appends additional heat loads at the city, which threaten comfort and health of people. There is unclear understanding represent of the relationship between climate indicators and the features of the early virtual urban design. The research focused on simulation capability, and the affect in urban microclimate. It is assumed that the adoption of certain scenarios and strategies to mitigate the intensity of the UHI leads to the improvement of the local climate and reduce the impact of global warming. The aim is to show on the UHI methods simulation and the programs that supporting simulation and mitigate the effect UHI. UHI reviewed has been conducted the form of many studies, it resulted that all simulation methods were pass through the follow stages: modeling, Simulation and mitigation. Most of the literature reviewed shows that there are some key criteria that have been adopted as universal urban health coverage in cities, and that the first control component is city design.
The primary goal of root canal treatment (RCT) is to expel the presence of any necrotic or vital tissue, microbes and their byproducts from the canal space before press forward with the following steps of the RCT procedures. Although this is difficult to attain, various strives had been practiced by employing chemical and mechanical methods to eliminate as much microorganisms as possible and make the canal space valid for the obturation materials to be received. The aim of this review is to demonstrate some of what new remedies that could be used as root canal disinfectant by summarizing the recent studies regarding the efficacy of different natural products against the most persistence microbiota that could be responsible for most
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The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.
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This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.
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Some genetic factors are not only involved in some autoimmune diseases but also interfere with their treatment, Such as Crohn's disease (CD), Rheumatoid Arthritis (RA), ankylosing spondylitis (AS), and psoriasis (PS). Tumor Necrosis Factor (TNF) is a most important pro-inflammatory cytokine, which has been recognized as a main factor that participates in the pathogenesis and development of autoimmune disorders. Therefore, TNF could be a prospective target for treating these disorders, and many anti-TNF were developed to treat these disorders. Although the high efficacy of many anti-TNF biologic medications, the Patients' clinical responses to the autoimmune treatment showed significant heterogeneity. Two types of TNF receptor (TNFR); 1 an
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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The Migration is one of the important dynamic population movement phenomena in population studies because of its great impact in changing many demographic characteristics between the region of origin and arrival. And the multiplicity of forms and types according to the different reasons for it and the motives that prompted the population to move, as well as the currents and their size are also different according to the different causes, and here there are many types of migration, and many of them have been studied at the local and regional levels, and as long as the population is in a continuous dynamic movement, other types of migration are generated. (Al Douri, 2015, 230) &nbs
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