Brainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's

    Polycystic ovary syndrome (PCOS) is a heterogeneous disorder . PCOS affects 6–10% of women during their reproductive life. Patients with PCOS are in the high risk for coronary heart disease because of their abnormal lipid profile, insulin resistance and obesity. The present study aimed to shed a light on the contribution of  sialic acid, paraoxonase and immunoglobulin G as a clinical indicator in the pathogenesis of PCOS. Seventy five female patients with age range (16-38) years taken from Al-Sadder Teaching Hospital and AlZahrawi Hospital in Governorate of    Messan through the period from July 2013 to December 2013 and twenty five apparently health subject as a control group were

Systemic lupus erythematosus (SLE) is one of the autoimmune disorders, generated by a production of specific autoantibodies against self-antigens before the occurrence of clinical symptoms. The etiology of disease is still unknown, although there have been several infectious agents that have been associated with SLE development, especially in genetically predisposed individuals. Herpes simplex virus-I and -II (HSV-I and -II) and Toxoplasma gondiiare two infectious agents that have been suggested to be involved in SLE etiology. Accordingly, the present study assessed anti- HSV-I and -II and anti-T. gondii IgG and IgM antibodies by enzyme linked immunosorbent assay in sera of 64 SLE female patients and 32 healthy control women. The patients w

Derivational word formation process is one of the most substantial linguistic procedures that solves many problems in the translation of the language new vocabulary and helps to comprehend the smallest language component that not simply semantically and structurally explain the elements  of both Russian and Arabic but also enables translators to comprehend the derivational method procedures of both languages. It also reveals the structural aspects of translation equivalences, cognitive and semantic foundations of translation. The rapid development of languages and the appearance of a new vocabulary like ṭabaʿa "print → ṭābiʿat "printer", kataba "to write" → kātib → kātibat, rafaʿa "to raise" → rāfiʿat "a crane" d

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University