Objective: Carbamazepine is typically used for the treatment of seizure disorders and neuropathic pain. One of the major problems with this drug is its low solubility in water; therefore the objective of this study was to enhance the solubility of carbamazepine by complexation with cyclodextrin to be formulated as effervescent and dispersible granules.Methods: Solvent evaporation method was used to prepare, binary (Carbamazepine/β-cyclodextrin) complex and ternary (Carbamazepine/β-cyclodextrin/hydroxypropyl methyl cellulose (HPMC E5). The more soluble complex will be further formulated as unit dose effervescent and dispersible granules. The complexes were evaluated for their solubility, drug content, percentage practical yield and

Objective: To identify barriers to healthcare access, to assess the health literacy levels of the foreign-born Arabic speaking population in Iowa, USA and to measure their prevalence of seeking preventive healthcare services. Methods: A cross-sectional study of native Arabic speaking adults involved a focus group and an anonymous paper-based survey. The focus group and the Andersen Model were used to develop the survey questionnaire. The survey participants were customers at Arabic grocery stores, worshippers at the city mosque and patients at free University Clinic. Chi-square test was used to measure the relationship between the characteristics of survey participants and preventive healthcare services. Thematic analysis was

   Research aims at evaluating the quality of the teaching skills of math teachers in junior high / scientific branch  from their point of view.

The researchers prepared for this purpose a quality of teaching skills standards questionnaire, It consisted of 72 items distributed on four axis, The research sample was 200 teachers The researchers used statistical methods: the arithmetic mean, standard deviation, variance test, test Shiva  , The results showed a statistically significance difference Attributed to the qualification  variable  in the second  axis (Planning for teaching topics) And the absence of statistical difference function,

Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.

This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subj

In this work a chemical sensor was built by using Plane Wave Expansion (PWE) modeling technique by filling the core of 1550 hollow core photonic crystal fiber with chloroform that has different concentrations after being diluted with distilled water. The minimum photonic bandgap width is.0003 and .0005 rad/sec with 19 and 7 cells respectively and a concentration of chloroform that filled these two fibers is 75%.

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T