Persistence of antibiotics in the aquatic environment has raised concerns regarding their potential influence on potable water quality and human health. This study analyzes the presence of antibiotics in potable water from two treatment plants in Baghdad City. The collected samples were separated using a solid-phase extraction method with hydrophilic-lipophilic balance (HLB) cartridge before being analyzed. The detected antibiotics in the raw and finished drinking water were analyzed and assessed using high-performance liquid chromatography (HPLC), with fluorometric detector and UV detector. The results confirmed that different antibiotics including fluoroquinolones andB-lactams were detected in the raw an

Background: The posterior slope of the articular eminence of completely edentulous patients compared to patients with maintained occlusion shows significant flattening. This study aimed to correlate between the flattening of the posterior slope of the articular eminence, with dental status, age, genders, on both sides using computed tomography. Materials and Methods: The sample of the present study was a total of 117 Iraqi subjects, who admitted to the maxillofacial department at Al-Sadr Teaching Hospital in Al-Najaf city. The examination was performed on CT scanner; the eminence inclination was measured in two methods using sagittal section. Results: Clinically, the inclination of articular eminence was higher in edentulous subjects than i

Background: Parvovirus B19 is a human pathogenic virus associated with a wide range of clinical conditions. During pregnancy congenital infection with parvovirus B19 can be associated with poor outcome, including miscarriage, fetal anemia and non-immune hydrops.  

Objective: The study aimed to determine the prevalenceof Parvovirus B19 DNA in pregnant women attending the Military hospital in Khartoum, demonstrating the association between the virus and poor pregnancy outcomes.

Subjects and methods: This study was a cross sectional study, testing pregnant Sudanese women whole blood samples (n= 97) for the presence of Parvovirus B1

Background: The surgical extraction of impacted third molar usually results in postoperative inflammation manifested as pain, facial swelling and trismus which may cause deterioration in the patient’s quality of life. Methods: This randomized controlled study included 56 patients indicated for surgical extraction of IMTM under local anesthesia. These patients were randomly assigned into two groups: a study group that included patients who received Tibrolin® postoperatively and a control group that did not. The predictor variable was whether to use SET or not. Pain measured by the pain numerical rating scale (NRS), facial swelling, and the degree of trismus were the outcome variables. The Arabic version of the Oral Health Impact P

Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi