Objective: The study aimed to 1) measure the prevalence of depression and anxiety among Iraqi pharmacy and medical students at a number of universities in Baghdad using Hospital Anxiety and Depression Scale (HADS) and 2) investigate the association between various sociodemographic factors and students’ HADS scores. Methods: This study was based on a cross-sectional descriptive design in four universities in Baghdad, Iraq. Depression and anxiety were screened using an Arabic version of the HADS. An online survey was administered via Qualtrics to convenience samples of students at four colleges of pharmacy and a college of medicine between March and June 2018. Multiple linear regression was used to identify factors associated

The aim of the research is to identify the relationship between health anxiety associated with Coronavirus (Covid 19) and its relationship to health behavior among Baghdad University employees, as well as to identify the differences in health anxiety and health behavior according to the variables (gender, occupation, and age). To achieve the objectives of the research, a scale was designed to measure the health anxiety in addition to the adoption of the health behavior scale prepared by (Renner & Schwarzer, 2005). The two scales were applied to a sample of (277) academics and (206) employees, while the number of students was (667). The sample was chosen by electronic application from a number of colleges at Al-Jadiriyah Complex. Afte

Vaccination is a vital cornerstone of public health, which has saved countless lives throughout history. Therefore, achieving high vaccination uptake rates is essential for successful vaccination programs. Unfortunately, vaccine uptake has been hindered by deferent factors and challenges. The objective of this study is to assess COVID-19 vaccine uptake and associated factors among the general population.

The problem of the paper focused on the role of the learning organization in the crisis management strategy, and the extent of the actual interest in both the learning organization and the crisis management and aimed at diagnosing and analyzing that and surrounding questions. The Statistical Package for the Social Sciences (SPSS) program was used to calculate the results and the correlation coefficient between the two main variables. The methodology was descriptive and analytical. The case study was followed by a questionnaire that was distributed to a sample of 31 teachers. The paper adopted a seven-dimensional model of systemic thinking that encourages questioning, empowerment, provision of advanced technologies, and strategic lea

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Biomarkers such as Interleukin-6 (IL-6), Procalcitonin (PCT), C-reactive protein (CRP) and Neutrophil-Lymphocyte Ratio (NLR) have a role in the pathogenesis of severe coronavirus disease 2019 (COVID-19). The aim of this study was to explore the differences between serum levels of such biomarkers in severe and non-severe COVID-19 cases and compare them with normal people and to evaluate the sociodemographic variables and chronic diseases effect on the severity of COVID-19. The study included 160 subjects, divided into two groups, a case group of 80 patients, and a control group of 80 normal persons. The case group was divided into two subgroups: 40 severe COVID-19 patients and 40 patients with non-severe disease. Blood IL-6 was asses