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.

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

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

The article describes the basic principles of modeling a dictionary article in the “Dictionary of the Language of Russian Folklore Lexicon epics” (M. A. Bobunova, A. T. Khrolenko). Among such principles are the principle of linguocentrism (representation of universal cognitions in strict observance of the traditions of lexicographic science), the principle of anthropocentrism (language learning as a means of human consciousness / subconsciousness), the principle of expansionism (attracting material from various knowledge bases), the principle of explanatory ("explanatory moment"), and fractal principle (synergistic potential of the presented material: nonlinearity and self-similarity; hierarchical organizati

This systematic review aimed to analyse available evidence to answer two focused questions about the efficacy of erythritol powder air‐polishing (EPAP) (i) as an adjunctive during active periodontal therapy (APT) and (ii) as an alternative to hand/ultrasonic instrumentation during supportive periodontal therapy (SPT). Additionally, microbiological outcomes and patient's comfort/perceptions were assessed as secondary outcomes.

     The outbreak of a current public health coronavirus 2019 disease is a causative agent of a serious acute respiratory syndrome and even death. COVID-19 has exposed to multi-suggested pharmaceutical agents to control this global disease. Baricitinib, a well-known antirheumatic agent, was one of them. This article reviews the likely pros and cons of baricitinib in attenuation of COVID-19 based on the mechanism of drug action as well as its pharmacokinetics. The inhibitory effect of baricitinib on receptor mediated endocytosis promoter, AKK1, and on JAK-STAT signaling pathway is benefacial in inhibition of both viral assembling and inflammation. Also, its pharmacokinetic has encouraged the physicians toward the drug