Copper is a cheaper alternative to various noble metals with a range of potential applications in the field of nanoscience and nanotechnology. However, copper nanoparticles have major limitations, which include rapid oxidation on exposure to air. Therefore, alternative pathways have been developed to synthesize metal nanoparticles in the presence of polymers and surfactants as stabilizers, and to form coatings on the surface of nanoparticles. These surfactants and polymeric ligands are made from petrochemicals which are non- renewable. As fossil resources are limited, finding renewable and biodegradable alternative is promising.The study aimed at preparing, characterizing and evaluating the antibacterial properties of copper nanoparticle

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction o

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction of (4% for AL

The rise of antibiotic-resistant bacteria necessitates the exploration of novel antimicrobial agents. Yttrium oxide nanoparticles (Y₂O₃) have shown potential due to their unique physicochemical properties and antibacterial activities against various pathogens. This study investigates the cytotoxic and antibacterial effects of Y₂O₃ nanoparticles against Serratia fonticuli and Citrobacter koseri, bacteria isolated from cholangitis patients. Bacterial strains were isolated from bile specimens and confirmed using standard microbiological techniques. The methods of X-ray diffraction (XRD), (SEM), and Frequency transform-infrared spectroscopic (FT-IR) were used to characterize YO₃ particles. Using a microdilution technique, the minimum

Jumping ability is a fundamental variable in many sports, as its execution requires an integration of muscular strength Q1 and certain biomechanical variables. This is particularly evident in gymnastics jumping events and jump shots in ball games, both of which rely on a high level of vertical resistance. Vertical resistance serves as an indicator of an athlete’s ability to overcome their body weight while counteracting gravitational force to achieve optimal performance. As such, it is considered one of the key factors in movements that demand explosive power and speed. The researchers believe that despite the significant relationship between vertical resistance, speed-strength of the arms and legs, and certain biomechanical varia

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

AlPO4 solid acid catalyst was prepared in order to use it in transesterification reaction of edible oil after supporting it with tungsten oxide. The maximum conversion of edible oil was obtained 78.78% at catalyst concentration (5gm.), temperature 70°Ϲ, 30/1 methanol/edible oil molar ratio, and time 5hr. The study of kinetics of the transesterification reaction of edible oil indicates that the reaction has an order of 3/2, while the value of activation energy for  transesterification reaction is 51.367 kJ/mole and frequency factor equal 26219.13(L/ mol.minute).