Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome called coronavirus 2 (SARS-CoV-2). Due to its concerning rate of transmission and intensity, coronavirus was classified as a pandemic on March 11, 2020. With the continuous evolution of the viral genome and mutations that may alter infectivity, disease severity or interactions with host immunity, SARS-CoV-2 has evolved into many variants: Alpha (B.1.1.7 lineage), Delta (B.1.617.2 lineage), Delta plus (B.1.617.2.1), Omicron (B.1.1.529 lineage) and other variants. Thus, this study aimed to find and provide database for local clinical characteristics of different variants of SARS-COV-2 and severity of infection with viral load compared with the wild type. A total of 247 nasal swabs were collected from COVID-19 positive patients between March 2021 to March 2022. Specimens were tested by using real time reverse transcriptase polymerase chain reaction rRT-PCR assay to confirm the infection after RNA extraction by specialized kits. Results showed Alpha, Delta, Delta plus and Omicron variants presence in local population at the same time of their global spread at high rates with different cases of severity. The finding showed increase in severity with Alpha 79/87 (90%), wild type 26/32 (81%) (with 3 mortality cases), Delta/ Delta plus 68/84 (80%) and Kappa only one case. Also, Alpha along with the wild type was more associated to severe and critical cases, while mild to moderate group appeared with Omicron variant (32/43 (74%)). In addition, there was an increase in the severity among older patients (>40) and in men more than the women. Results indicate that although the wild type was no less dangerous or severe than Alpha or other variants, but with continuous appearence of new variants led to its reduced prevalence. In conclusion, findings demonstrated that most of the severe and critical cases had infection with Alpha, wild type than Delta or Delta plus variants. Whereas mild to moderate cases occurred in Omicron variants.
Objective(s): The study aims at evaluating pregnancy-related health behaviors for pregnant women, and to identify the association between pregnancy-related health behaviors and their demographic characteristics of pregnant woman’s age, education, employment, residential area and monthly income.
Methodology: A descriptive study is carried out for the period from December 14th, 2020 to June 20th, 2021. This study was conducted through a non-probability (convenience) sample of 150 pregnant women attending, Abo Ghareeb primary health care sector in Abo Ghareeb spend. The sample has been collected by using the instrument to gather data and accomplish the study's objectives. A questionnaire is composed of (29) items and it is divided into
This study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of
... Show MoreThis research deals with the financial reporting for non-current assets impairment from the viewpoint of international accounting standards, particularly IAS 36 "Impairment of non-current assets." The research problems focus on the presence of internal and external indicators on impairment of non-current assets in many of companies listed in Iraqi stock exchange. So it is required to apply IAS 36 to reporting for the impairment loss of assets since this impairment impact certain financial indicators. These indicators help users in their decision-making and forecasting future financial situation and the ability of the company to achieve future profits or maintain current profits. The research aims to shedding lig
... Show MoreThis study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m
... Show MoreExperiments research is done to determine how saturated stiff clayey soil responds to a single impulsive load. Models made of saturated, stiff clay were investigated. To supply the single pulse energy, various falling weights from various heights were tested using the falling weight deflectometer (FWD). Dynamic effects can range from the major failure of a sensitive sensor or system to the apparent destruction of structures. This study examines the response of saturated stiff clay soil to a single impulsive load (vertical displacement at the soil surface below and beside the bearing plates). Such reactions consist of displacements, velocities, and accelerations caused by the impact occurring at the surface depth induced by the impact loads
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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