In this research, titanium dioxide nanoparticles (TiO₂ NPs) were prepared through the sol-gel process at an acidic medium (pH3).TiO₂ nanoparticles were prepared from titanium trichloride (TiCl₃) as a precursor with Ammonium hydroxide (NH₄OH) with 1:3 ratio at 50 °C. The resulting gel was dried at 70 °C to obtain the Nanocrystalline powder. The powder from the drying process was treated thermally at temperatures 500 °C and 700 °C. The crystalline structure, surface morphology, and particle size were studied by using X-ray diffraction (XRD), Atomic Force Microscopy (AFM), and Scanning Electron Microscope (SEM). The results showed (anatase) phase of titanium dioxide with the average grain size

Denture cleansing is an essential step that can stop cross‑contamination and adds to the health of the patient, denture durability, and the general quality of life. A disinfection technique must be practical and devoid of damaging effects on the material's properties used to construct the denture base. The main aim of this study is to evaluate the effect of three concentrations of electrolyzed water denture cleanser on heat cure acrylic and polyamide after immersion in electrolyzed water. The evaluation is based on their efficacy on surface hardness, wettability, and color stability compared with one submerged in distilled water as a control group. The method consists of eighty samples of heat-cured acrylic and polyamide material.

The efficient behavior of a low-concentrating photovoltaic-thermal system with a micro-jet channel (LCPV/T-JET) and booster mirror reflector is experimentally evaluated here. Micro-jets promote the thermal management of PV solar cells by implementing jet water as active cooling, which is still in the early stages of development. The booster mirror reflector concentrates solar irradiance into solar cells and improves the thermal, electrical, and combined efficiencies of the LCPV/T-JET system. The LCPV/T-JET system was tested under ambient weather conditions in the city of Bangi, Selangor, Malaysia, and all data was recorded between 10:00 a.m. and 4:00 p.m. Parametric studies were conducted to compare the performance of the LCPV/T-JET system

The behavior corrosion inhibition of aluminum alloy (Al6061) in acidic (0.1 M HCl) and saline (3.5% NaCl) solutions was investigated in the absence and the presence of expired diclofenac sodium drug (DSD) as a corrosion inhibitor. The influence of temperature and was studied using electrochemical techniques. In addition, scanning electron microscopy (SEM) was used to study the surface morphology. The results showed that DSD acted as a powerful inhibitor in acidic solutions, while a moderate influence was observed with saline one. Maximum inhibition efficiency was 99.99 and 83.32% in acidic and saline solutions at 150 ppm of DSD, respectively. Corrosion current density that obtained using electrochemical technique was increased with temperat

This work involves separating and studying the aminoacylase-1 (ACY1) of amniotic fluid from healthy pregnant, mainly one peak with higher activity has been isolated by DEAE-Cellulose ion exchange from the proteinous supernatant produced by deposition of proteins using ammonium sulfate  (65%) after dialysis. The purification folds reaching to 19 folds also gave one protein peak when injected into the gel filtration column, a high ACY1 purity was obtained, with 38 folds of purification. It was found that the molecular weight of the isolated ACY1 was up to 46698 Dalton when using gel chromatography technique.The effect of ACY1 isolate was studied on rats with oxidative stress caused by lead acetate(LA) at 40 mg / kg body weight and compare

Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, and seven

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

Although renewable energy systems have become an interesting global issue, it is not continuous either daily or seasonally. Latent heat energy storage (LHES) is one of the suitable solutions for this problem. LHES becomes a basic element in renewable energy systems. LHES compensate for the energy lack when these systems are at low production conditions. The present work considered a shell and tube LHES for numerical investigation of the tube rotation influence on the melting process. The simulation and calculations were carried out using ANSYS Fluent software. Paraffin wax represents the phase change material (PCM) in this work, while water was selected to be the heat transfer fluid (HTF). The calculations were carried o

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea