The research aims to clarify the role of the main variable represented by the four dimensions of entrepreneurial behavior (creative, risk-taking, seizing opportunities, proactivity), in Reducing the dependent variable of organizational anomie with the dimensions (Organizational Normlessness, Organizational Cynicism, Organizational Valuelessness).

The experimental, analytical method was adopted in the completion of the research, and an intentional sample of (162) individuals in the administrative levels (higher and middle) in the factory was taken. The questionnaire was also adopted as the main tool, which

Diarrhea is a real disease in childhood which could cause death. Therefore, this study was conducted to isolate Salmonella from 350 stool samples taken from children under five years in age, suffering from diarrhea during the period from March 2019 to March 2020 in Tikrit city / Iraq. The results showed the possibility to isolate ten isolates of Salmonella enterica subsp. Enterica, an infection rate, represents 2.875% of the total rate of patients who suffer from diarrhea. The virulence genes were investigated for ten isolates of S. enterica subsp. enterica, the result is that all isolates possessed the genes stn, invA, lpfA with an appearance percentage of 100%, whi

One hundred isolates of Pseudomonas aeruginosa were obtained from patients admitted to Baghdad hospitals, Iraq during the period between May 2018 until July 2018. These isolates were distributed as 15 isolates from blood, 25 isolates from urinary tract infections, 10 isolates from sputum, 12 isolates from wounds, 15 isolates from ear infections, 15 isolates from bronchial wash of patients suffering from respiratory tract infections in addition to 8 isolates from cystic fibrosis patients. The isolates were initially identified by culturing on MacConkey agar, blood agar and P. aeruginosa agar then diagnosed by performing some morphological and biochemical tests. The second diagnosis was done by API 20E system followed by Vitek 2 compact syste

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV 2) or 2019 novel coronavirus (2019-nCoV) is quickly spreading to the rest of the world, from its origin in Wuhan, Hubei Province, China. And becoming a global pandemic that affects the world's most powerful countries. The goal of this review is to assist scientists, researchers, and others in responding to the current Coronavirus disease (covid-19) is a worldwide public health contingency state. This review discusses current evidence based on recently published studies which is related to the origin of the virus, epidemiology, transmission, diagnosis, treatment, and all studies in Iraq for the effect of covid-19 diseases, as well as provide a reference for future research

Abstract Background Hemoglobin A1c (HbA1c) is a widely used test for glycemic control. It is done for chronic kidney disease (CKD) patients. Renal disease is accompanied by thyroid abnormalities, which affect HbA1c, especially in those taking erythropoiesis-stimulating agents (ESAs). We aimed to find the effect of thyroid dysfunction on HbA1c in hemodialysis patients taking ESAs and those who do not. Materials and Method Fifty six patients were included in this study, which was done between September 2017 and June 2018, in Baghdad Teaching Hospital. Thyroid stimulating hormone, free T3, free T4 and HbA1c measurements were done. The patients were divided into 2 groups; those who took ESAs and those who did not, then they were subdivided into

Twenty four soil samples were collected from different sites in north sector of East Baghdad oil field, Iraq , and analyzed to assess the impact of urbanization and industrialization essential pollution. The soil samples were analyzed for heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) by using inductively coupled plasma–mass spectrometry (ICP-MS). Mean concentration of heavy metals in soil samples follows this pattern: Zn > Ni > Cr > Cu >Pb > As> Cd> Hg. The results show significant variations (lower and higher) in the concentrations of heavy metals compared with local and world studies, this variation is attributed to the natural anthropogenic sources. The pollution of studied soil was assessed using many soil

 Rheumatoid arthritis (RA) was a chronic inflammatory autoimmune disease for long-term that primarily affects small joints and leads to chronic inflammation in synovial. The aimed of the study to identify the relationships among some serological markers (antibodies to citrullinated protein/peptide antigens (ACPAs), anti-mutated citrullinated vimentin (anti-MCV), anti-carbamylated protein (Anti-Carp), anti- heterogeneous nuclear ribonucleoproteins (anti-hnRNP) and Glucose-6-phosphate isomerase (GPI)) and early diagnosis of RA. The study involved (60) Patients of newly diagnosis with RA that divided in to two subgroups (30 RF positive and 30 RF negative) groups and 30 subjects as healthy control group. The serological data from serum

      Systemic lupus erythematosus (SLE) is a multifactorial chronic autoimmune disease, with a wide spectrum of effect. The main feature of the disease is the production of a wide variety of autoantibodies as a result of immune tolerance loss. The work aims to evaluate the miRNA-146a gene polymorphism potential association with disease activity and chronicity changes in SLE patients. The study included 100 SLE patients and 50 matched controls. The systemic lupus erythematosus disease activity index (SLEDAI) was assessed. The single nucleotide polymorphism (SNP) of miR-146a gene (rs2910164) polymorphism was assayed by polymerase chain reaction (PCR) and sequencing technique in patients and control. 100 SLE pati

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the