We have studied in this research litter (Taa) a morphological , sonic indicative and comparative study among four Semitic languages. They are Arabic , Hebrew, Syriac and Akkadian languages . We have divided the research into a number of pivots beginning with an entrance about the letter (Taa) in Semitic languages and the symbols which are used by these languages referring to . Then we have studied (Taa) from sonic side with letters phenomenon (b, g, k, p, t) the six in both Hebrew and Syriac languages . The letter (Taa) is formed one of them and the sonic change that is happening in articulation (Taa) according to sonic rules related to these letters in case of emphasis or in case of neglected (not emphasis). Then we have studied the pro

This study aims to predict the organic pollution produced from the presence of some polycyclic aromatic hydrocarbons (PAHs) and determination it's concentrations (µg/L , ppb) in Tigris river water by a collection twenty-seven water samples from a selected three stations with nine sampling sites and three depths of water (5 cm , 2 m and 4 m) each site for 4.6 km distance of a geographic studied area which is located between the ( Al-Senak and AL-Sarrafiah bridges ) at Baghdad city – Iraq on May, 2012. The geographic location was determined with a Global Positioning System (GPS) and Geographic Information System (GIS) software program. The concentrations of fourteen components (PAHs) were performed using the reverse phase

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.

Cilnidipine is a dihydropyridine class of calcium channel blockers, it is classified as a BCS class II drug, characterized by a low oral bioavailability of 13%. Consequently, the utilization of nanoparticle preparation is anticipated to enhance its bioavailability. The objective of the research is to integrate cilnidipine nanoparticles into oral films as a means of enhancing patient adherence. The optimal polymers for producing Cilnidipine films were PVA cold and or HPMC E5 at different concentrations using a casting technique with glycerol as a plasticizer. The Nano suspension-based preparation of Cilnidipine's oral film containing the combination of polymers exhibited a significant enhancement in vitro dissolution, with a percentage excee

Psoriasis is a long-lasting autoimmune disease that is characterized by swollen skin patches. Normally, these skin patches are dark, swollen, itchy and scaly. The single application of the innate TLR7/8 ligand Imiquimod (IMQ) in mice easily induces a dermatitis that closely resembles human psoriasis, critically dependent on the axis of IL-23/IL-17. Artemisia dracunculus prepared as an ointment and has been used topically to mice before imiquimod application. The results of the current study showed that A. dracunculus ointment can significantly reduce psoriasis area and severity index in (A. dracunculus ointment + imiquimod group as compared with both control group and (vehicle ointment + imiquimod) group.

Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.