Background: The occurrence of seizures in bacterial meningitis is important, as it has been reported to increase the risk of complications; however, its frequency and predictors are not well studied yet. Objective: To assess the frequency, clinical, and biochemical predictors of seizures in children with acute bacterial meningitis. Method: A cross-sectional study recruited confirmed acute bacterial meningitis cases based on positive CSF culture and sensitivity among children aged 2 months to 15 years admitted to the Central Child Teaching Hospital emergency department in Iraq. Patients were divided into two groups based on seizure at presentation time. Demographic characteristics [age, gender, residence, duration of fever and disease, presenting complaints and antibiotic intake]; hematological [WBC, neutrophils] Lymphocyte, N/L ratio, packed cell volume, platelets, blood sugar, and cerebrospinal fluid (CSF) indices were compared between groups. Results: Seizures had a frequency of 18% among the 122 children and were significantly higher in younger cases with female predominance. By multivariate analysis and odds ratio (OR), predictors for seizure were as follows: CSF lymphocytes (OR=0.25, 95%CI=0.08–0.26), lethargy (OR=8.15, 95%CI=1.03-68.65), headache (OR=0.09, 95%CI=0.02-0.45), neck stiffness (OR=0.07, 95% CI=0.01-0.61) and poor feeding (OR=4.8, 95%CI=1.21–18.97). Conclusions: CSF lymphocytes reliably predicted seizure with good sensitivity and specificity of 75% and 73%. Lethargy and poor feeding had the highest odds as clinical predictors of seizures. Together, those results can help with risk stratification and allocate resources for high-risk cases to improve patient outcomes
Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
... Show MoreBiologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,
... Show MoreBiologically active natural compounds are molecules produced by plants or plant-related microbes, such as endophytes. Many of these metabolites have a wide range of antimicrobial activities and other pharmaceutical properties. This study aimed to evaluate (in vitro) the antifungal activities of the secondary metabolites obtained from Paecilomyces sp. against the pathogenic fungus Rhizoctonia solani. The endophytic fungus Paecilomyces was isolated from Moringa oleifera leaves and cultured on potato dextrose broth for the production of the fungal metabolites. The activity of Paecilomyces filtrate against the radial growth of Rhizoctonia solani was tested by mixing the filtrate with potato dextrose agar medium at concentrations of 15%,
... Show MoreBackground: Bone density is a major factor that affect mini implant primarily stability; no Iraqi studies have evaluated bone density related to mini-implant placement for orthodontic anchorage at age 13 -15 years. The present research aims to evaluate gender, side and site differences in the bone density at various orthodontic implant sites for the maxillary alveolar bone. Materials and methods: Twenty nine individuals (16 males and 13 females) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 21 points (9 points for each side and 3 points between the right and left central incisors) . Results: The results obtained showed that there ar
... Show MoreA newly developed analytical method was conducted for the determination of Ketotifen fumarate (KTF) in pharmaceuticals drugs via quenching of continuous fluorescence of 9(10H)-Acridone (ACD). The method was applied using flow injection system of a new homemade ISNAG fluorimeter with fluorescence measurements at ± 90◦ via 2×4 solar cell. The calibration graph was linear in the range of 1-45 mmol/L, with correlation coefficient r = 0.9762 and the limit of detection 29.785 µg/sample from the stepwise dilution for the minimum concentration in the linear dynamic ranged of the calibration graph. The method was successfully applied to the determination of Ketotifen fumarate in two different pharma
... Show MoreAl-Aziz's book was chosen as a subject for research as it is one of the important books in the Islamic world in general and the Shafi'i school in particular and its author Imam Abdul Karim bin Mohammed bin Abdul Karim Al-Rafi's, who in the doctrine of the jurisprudence has made prominent lines and left behind invaluable scientific treasures in the service of religion. Its importance is summarized as follows:
1. Being an explanation of the book (brief) of the argument of Islam Imam Ghazali (God's mercy), one of the five books adopted in Shafi'i jurisprudence.
2. His work is Imam Abu al-Qasim al-Rafii known for the brilliance of the investigation and the power of weighting in the doctrine.
3. It is considered an encyclopedia in Sh
Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us
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