The problem of the search (how to employ own aesthetic values sculpture prominent decorations doors in the holy shrines) as research aims to detect these formulas employed in relief sculpture in accordance with the aesthetic values of the decorations that add structure in the form of doors shrines dimensions of functional and aesthetic and expressive By selecting the general system configurations spaces for doors and select the components of the structural configurations decorative prominent types (geometric and floral and linear and composite) as well as identify the techniques adopted in the executive configurations doors at the level of raw materials and processors show. Find and define the beauty of decorative formations prominent of

Objective: The study the association of procalcitonin (PCT) and c-reactive protein (CRP) levels in COVID-19 patients and it's role as a guide in progress and management of those patients. Methodology: This cross-sectional study analyzed 200 CIOVID-19 patients in a single privet center in Baghdad, Iraq from January 1, 2021 to January 1, 2022. Demographic data like age, sex, and clinical symptoms were recorded. High sensitivity CRP and PCT in the serum were measured via dry fluorescence immunoassay (Lansionbio-China). Results: Out of 200 patients, 50 had moderate Covid and 150 had severe disease. Mean serum PCT levels was 0.039±0.05 ng/mL in the moderate group (range 0.011-0.067) and 0.43±0.21 ng/mL in the severe group (range 0.21

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

The pandemic of coronavirus disease 2019 (COVID-19), first reported in China, in December 2019 and since then the digestive tract involvement of  COVID-19 has been progressively described. In this review, I summed recent studies, which have addressed the pathophysiology of COVID-19-induced gastrointestinal symptoms, their prevalence, and bowel pathological and radiological findings of infected patients. The effects of gut microbiota on SARS-CoV-2 and the challenges of nutritional therapy of the infected patients are depicted.  Moreover, I provide a concise summary of the recommendations on the management of inflammatory bowel disease, colorectal cancer, and performing endoscopy in the COVID era. Finally, the COVID pancreatic re

The problem for the search to identify the role of loyal workers through (emotional loyalty, moral loyalty, continued loyalty) in enhancing the market share of the corporate center the human resource management strategies, namely (selection, training and development, and performance evaluation, and returns the system) for the parent company of cellular Allotsalat in Baghdad ,, and show the importance of research through the benefit to the company, through the importance of the search results, it draws the attention of decision-makers and those in charge of managing these human resources on the importance of those resources and work to develop them and keep them in order to increase their loyalty towards their organization and the

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

Background: The SARS-CoV-2 virus causes COVID-19, a respiratory syndrome. It causes inflammation and damages several organs in the body. miRNAs play a role in regulating the infection resulting from SARS-CoV-2. MicroRNA-155, a kind of microRNA linked to viral defences, can affect the immune responses during COVID-19. Objectives: Examination of the involvement of microRNA-155 in the development and severity of COVID-19, as well as finding the correlation between microRNA-155 and viral load (copies/mL) in severe cases of the disease. Materials and Method: A case-control research study was performed between October 2022 and June 2023. It included a cohort of 120 hospitalised individuals with severe cases of COVID-19, together with 115 individu

Background: COVID-19 is a disease that started in Wuhan/China in late 2019 and continued through 2020 worldwide. Scientists worldwide continue to research to find vaccines, treatments, and medication for this disease. Studies also conenue to find the pathogenicity and epidemiology mechanisms. Materials and Methods: In this work, we analyzed cases obtained from Alshifaa center in Baghdad/Iraq for 23/2/2020-31/5/2020 with total instances of 797, positive cases of 393, and death cases of 30. Results: Results showed that the highest infection cases were among people aged between 41-45. Also, it was found that males' number of cases was more than females. In contrast, death cases were significantly higher in males than females. It was not