Recent reports of new pollution issues brought on by the presence of medications in the aquatic environment have sparked a great deal of interest in studies aiming at analyzing and mitigating the associated environmental risks, as well as the extent of this contamination. The main sources of pharmaceutical contaminants in natural lakes and rivers include clinic sewage, pharmaceutical production wastewater, and sewage from residences that have been contaminated by drug users' excretions. In evaluating the health of rivers, pharmaceutical pollutants have been identified as one of the emerging pollutants. The previous studies showed that the contaminants in pharmaceuticals that are widely used are non-steroidal anti-inflammatory drugs, antibiotics, antiretrovirals, and anticancer drugs. Additionally, this review demonstrated the use of analytical techniques to examine these contaminants in various kinds of River water. Due to their extremely low concentrations in the aqueous environment (about in the range of ng/L to g/L), it is necessary to apply a technique for highly sensitive and selective multicomponent simultaneous analysis to identify and quantify these products. This analytical technique provides a flexible and reliable means to identify and evaluate pharmaceutical contaminants in river water samples by combining solid phase extraction and hyphenated mass spectrometric techniques. SPE-LC/MS/MS is the main method for estimating the level of pollution.
This research aims to identify how organizational compatibility, which represents the independent variable, affects higher performance, which is considered a dependent variable, given the importance of these variables in industrial organizations and their clear impact on their stability, survival, and growth in the light of changing environmental challenges. Where the practical research problem was represented by the weakness of awareness of the importance toward organizational compatibility and its dimensions (organizational loyalty, organizational similarity, affiliation or membership, compatibility with goals, and compatibility with values), which is meant by the individual's compatibility with the organization in which he/she w
... Show MoreThe financial crises that occurred in South East Asia and America, and the discovery of the financial and administrative corruption that affected these companies, which led to the crisis. Since then, organizations and institutions interested in accounting have begun new ways to further rationalize the management of these companies. Hence the concept of governance, which means good governance. Al-Susiya confirmed its adoption of the financial reporting standards and adopted internal and external auditing for the purpose of increasing the reliability and credibility of the financial and reports that increase the confidence of investors in making their investment decisions in the financial markets The study dealt with the contributi
... Show MoreTelevision contributes children the acquisition of knowledge, moral and social values through programs that are offered to them and the extent of the focus on the effective aspects of life in the age of the target stage. The subject of this research aims to know the children programs in Libya television through a comprehensive analytical study of the program entitled “zihur al-hayat” within the broadcast season from April 1, 2004 to June 30, 2004. It also focuses on trying to identify the Libyan television policy in broadcast educational content through the children's programs in the prevailing political and social conditions during the period of study as well as knowing the opinions of the children's sample under study in Al-Baidhaa
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show MoreChemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi
... Show MoreFibromuscular dysplasia (FMD) is a noninflammatory and nonatherosclerotic arteriopathy that is characterized by irregular cellular proliferation and deformed construction of the arterial wall that causes segmentation, constriction, or aneurysm in the intermediate-sized arteries. The incidence of FMD is 0.42–3.4%, and the unilateral occurrence is even rarer. Herein, we report a rare case of a localized extracranial carotid unilateral FMD associated with recurrent transient ischemic attacks (TIAs) treated by extracranial-intracranial bypass for indirect revascularization. The specific localization of the disease rendered our case unique.
The objective of this review was to describe the COVID-19 complications after recovery.
The researchers systematically reviewed studies that reported post-COVID-19 complications from three databases: PubMed, Google Scholar and the World Health Organization (WHO) COVID-19 database. The search was conducted between 21 November 2020 and 14 January 2021. Inclusion criteria were articles written in English, with primary data, reporting complications of COVID-19 after full
Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab
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