Background: Bilastine (BLA) is a second-generation H1 antihistamine used to treat allergic rhinoconjunctivitis. Because of its limited solubility, it falls under class II of the Biopharmaceutics Classification System (BSC). The solid dispersion (SD) approach significantly improves the solubility and dissolution rate of insoluble medicines. Objective: To improve BLA solubility and dissolution rate by formulating a solid dispersion in the form of effervescent granules. Methods: To create BLA SDs, polyvinylpyrrolidone (PVP K30) and poloxamer 188 (PLX188) were mixed in various ratios (1:5, 1:10, and 1:15) using the kneading technique. All formulations were evaluated based on percent yield, drug content, and saturation solubility. The formulae with the greatest solubility enhancement were subjected to in vitro dissolution studies, Fourier transform infrared, and thermal analysis to study drug crystallinity and drug-polymer interactions. The best SD formula was made as effervescent granules using wet granulation and tested further. Results: The SD3 formula, which contained PVP K30 in a 1:15 ratio, had the highest solubility and release. In phosphate buffer (pH 6.8), over 88.43% of the BLA was released within the first 15 minutes. The optimum formula's effervescent granules demonstrated excellent flow qualities, a disintegration time of 87 seconds, an acceptable pH of 5.9, and 9.7 mg of BLA dissolved in the first 5 minutes. Conclusions: BLA dissolution can be improved via the solid dispersion technique, allowing for successful effervescent granule formulation.
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreNew Schiff base and their Mn(II),Co(II),Ni(II), Cu(II) and Hg(II) complexes formed by the condensation of O-phathaldehyde and ethylene diamine (2:1) to give ligand (L1) in the first step ,then the ligand (L1) with 2- aminophenol (1:2) to give ligand (L2) were prepared by classic addition through microwave method . These compounds (Ligands and complexes) have been diagnosed electronic spectra, FT-IR, 1H-&13C-NMR (only ligand), magnetic susceptibility, elemental microanalysis and molar conductance measurements. Analytical values displayed that all the complexes appeared (metal: ligand) (1:1) ratio with the six chelation. All the compounds appear a high activity versus four types of bacteria suc
... Show MoreThis work examines numerically the effects of particle size, particle thermal conductivity and inlet velocity of forced convection heat transfer in uniformly heated packed duct. Four packing material (Aluminum, Alumina, Glass and Nylon) with range of thermal conductivity (from200 W/m.K for Aluminum to 0.23 W/m.K for Nylon), four particle diameters (1, 3, 5 and 7 cm), inlet velocity ( 0.07, 0.19 and 0.32 m/s) and constant heat flux ( 1000, 2000 and 3000 W/ m 2) were investigated. Results showed that heat transfer (average Nusselt number Nuav) increased with increasing packing conductivity; inlet velocity and heat flux, but decreased with increasing particle size.Also, Aluminum average Nusselt number is about (0.85,2.
... Show MoreThe influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
... Show MoreBackground: Scientific education aims to be inclusive and to improve students learning achievements, through appropriate teaching and learning. Problem Based Learning (PBL) system, a student centered method, started in the second half of the previous century and is expanding progressively, organizes learning around problems and students learn about a subject through the experience of solving these problems.Objectives:To assess the opinions of undergraduate medical students regarding learning outcomes of PBL in small group teaching and to explore their views about the role of tutors and methods of evaluation. Type of the study: A cross-sectional study.Methods: This study was conducted in Kerbala Medical Colleges among second year students
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