Background: Pneumonia is the common lower respiratory tract infection among pediatrics, especially under five; it is a common cause of under-five children morbidity and mortality. Objectives of study: To identify nurses' perceptions toward therapeutic strategies for children with pneumonia and to find the association between their perceptions and their demographic variables. Methods: A Convenient sample of 46 nurses in Baghdad city from three hospitals) Kadhimiya Hospital for Children, Central Teaching Hospital of Pediatrics, and Child Welfare Teaching Hospital) included in the study to identify their perceptions regarding pneumonia in children. Results: The results of the study present that most of the nurses' participants in the a

Isradipine belong to dihydropyridine (DHP) class of calcium channel blockers (CCBs). It is  used in the treatment of hypertension, angina pectoris, in addition to Parkinson disease. It goes under the BCS class II drug (low solubility-high permeability). The drug will experience extensive first-pass metabolism in liver, therefore, oral bio-availability will be approximately15 to 24 %.

 The aim of this study was to formulate and optimize a stable  nanoparticles of a highly hydrophobic drug, isradipine by anti-solvent microprecipitation Method to achieve the higher in vitro dissolution rate, so that it will be absorbed by intestinal lymphatic transport in order to avoid hepatic first-pass metabolism&nbs

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

Darifenacin hydrobromide is a selective ?₃ receptor antimuscarinic drug and it is used in the management of urinary frequency, urgency, and incontinence in detrusor instability. It slightly soluble in water, undergoes extensive hepatic first-pass metabolism and has short elimination half-life (3–4 hours). Therefore, It has low bioavailability (15.4 % - 18.6 %). Darifenacin hydrobromide loaded NLCs were formulated by emulsification sonication using different ratios of solid lipid to liquid lipid, different types of surfactants, and different concentration of surfactants. Formula sixteen was considered as an optimized formula based on its particle size, PDI, zeta potential and entrapment efficiency. Formula sixteen subjected t

     Intelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo