Magnetic plaster kiln dust (MPKD) was synthesized as a unique, low-cost composite reused of byproduct plaster kiln dust (PKD), which is considered a source of air pollution. The FESEM, EDS, XRD, FTIR, VSM, and BET tests were used to characterize the MPKD. The characterization revealed that the MPKD was nanotubes non-agglomerated and super-paramagnetic with a high specific surface area (102.7 m²/g). Compared with the specific area of other materials (composites), the MPKD could be considered a promising substance in the field of water/wastewater treatment.

Statement of the Problem. The use of orthodontic fixed appliances may adversely affect oral health leading to demineralizing lesions and the development of gingival problems. Aims of the Study. The study aimed to coat orthodontic archwires with chlorhexidine hexametaphosphate nanoparticles (CHX-HMP NPs) and to evaluate the elusion of CHX from CHX-HMP NPs. Materials and Methods. A solution of CHX-HMP nanoparticles with an overall concentration of 5 mM for both CHX and HMP was prepared, characterized (using atomic force microscope and Fourier transformation infrared spectroscopy), and used to coat orthodontic stainless steel (SSW) and NiTi archwires (NiTiW). The coated segments were characterized (using scanning electron microscopy

Ondansetron HCl (OND) is a potent antiemetic drug used for control of nausea and vomiting associated with cancer chemotherapy. It exhibits only 60 – 70 % of oral bioavailability due to first pass metabolism and has a relative short half-life of 3-5 hours. Poor bioavailability not only leads to the frequent dosing but also shows very poor patient adherence. Hence, in the present study an approach has been made to develop OND nanoparticles using eudragit^® RS100 and eudragit^® RL100 polymer to control release of OND for transdermal delivery and to improve patient compliance.

Six formulas of OND nanoparticles were prepared using nanoprecipitation technique. The particles sizes and zeta potential were measured

Polyaniline (PANI) has been prepared by the oxidation method in order to fabricate it with various concentrations of copper nanoparticles (CuNPs) which produced using the reduction method. Various techniques have characterized pure PANI and PANI doped CuNPs composites, such as fourier transform infrared spectroscopy (FT-IR), X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FE-SEM) and energy dispersive X-ray spectroscopy (EDS), which were provided important information about the structure and morphology of the fabricated polymer nanocomposites. The properties of dielectric permittivity (έ), dielectric loss (ἔ) and electrical conductivity (σ_AC) properties were studied at room temperature versus a range

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The research aimed to modeling a structural equation for tourist attraction factors in Asir Region. The research population is the people in the region, and a simple random sample of 332 individuals were selected. The factor analysis as a reliable statistical method in this phenomenon was used to modeling and testing the structural model of tourism, and analyzing the data by using SPSS and AMOS statistical computerized programs. The study reached a number of results, the most important of them are: the tourist attraction factors model consists of five factors which explain 69.3% of the total variance. These are: the provision of tourist services, social and historic factors, mountains, weather and natural parks. And the differenc