Abstract Bilastine, a second-generation antihistamine, is commonly prescribed for managing allergic rhinoconjunctivitis and urticaria due to its prolonged action. However, its therapeutic potential is constrained by poor water solubility and low oral bioavailability. This study aimed to enhance bilastine dissolution and patient compliance by formulating a nanosuspension-based orodispersible film (ODF). An anti-solvent precipitation method was employed to produce nanosuspension using different hydrophilic stabilizers (Soluplus®, Poloxamer 188, and PEG 6000). The influence of formulation parameters, such as the stabilizer ratio, the anti-solvent ratio, stirring speed, and the stabilizer type, on particle size and polydispersity index (PDI)

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Heat transfer process and fluid flow in a solar chimney used for natural ventilation are investigated numerically and experimentally her in. Solar chimney was designed, manufactured and tested by selecting different positions of air entrance namely: bottom entrance, side entrance, and both side and bottom entrances. The effect of integrating the chimney with paraffin (phase change material) on its thermal behavior has been also investigated. CFD analysis based on finite volume method is used to predict the thermal performance, and fluid flow in two-dimensional solar chimney under unsteady state condition, to identify the effect of different parameters such as solar radiation, and inclination angle. Experimental results show that a solar chi

Most dinoflagellate had a resting cyst in their life cycle.  This cyst was developed in unfavorable environmental condition. The conventional method for identifying dinoflagellate cyst in natural sediment requires morphological observation, isolating, germinating and cultivating the cysts.  PCR is a highly sensitive method for detecting dinoflagellate cyst in the sediment.  The aim of this study is to examine whether CO1 primer could detect DNA of multispecies dinoflagellate cysts in the sediment from our sampling sites. Dinoflagellate cyst DNA was extracted from 16 sediment samples. PCR method using COI primer was running. The sequencing of dinoflagellate cyst DNA was using BLAST. Results showed that there were two clades of dinoflag

Item Difficulty and Item Discrimination Coefficient for School and College Ability Tests (SCAT) Advanced Form in Classical Test Theory (CTT) and Item Response Theory (IRT) and the Correlation among Them Mohammad moqasqas Haifa T. Albokai Assistant Professor of Measurement and Evaluation Associate Professor of Measurement and Evaluation College of Education, Taibah University The aim of this study was to study the item difficulty and item discrimination of the SCAT (advance form) with CTT, and IRT, and to study the correlation among them. To do this, the researchers used the data of their previous study, which conducted in (2011). It consisted of (3943) subject. Then, they used two-statistical programs (TAP, Bilog-MG-3) to obtain the item