The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO₂ in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO₂ micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO₂ micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO₂ nanoparticle. GIC-contai

Abstract

In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G

Background: Self-medication is a practice or action taken by individuals for themselves in order to achieve and maintain health, as well as to avoid and protect against disease. The aim of this study is to evaluate the knowledge, attitudes, and practice of self-medication among medical students at Sudan International University.

Subjects & Methods: This was a prospective study that involved 288 out of 1000 students in the Faculty of Medicine at Sudan International University. Data were collected using a self-administered questionnaire from January to March 2022 to evaluate the self-medication knowledge, attitude, and practice among first, second, and third-ye

Background: The denture base inaccuracies during processing negatively influence the retention and stability of finished complete denture. The aims of this study were to evaluate teeth movement and palatal adaptation of autoclave cured denture bases and their relationship with palatal depths and investments. Materials and methods: A nightly maxillary complete dentures prepared, processed and organized to be tested as follows: 1. Processing methods: water bath and autoclave with both fast and slow cycles. 2. Palatal depth: shallow, medium and deep. 3. Investing medium: stone and silicone. For every finished denture, two measurements were done: first: teeth movement by attaching metallic reference screws on the right and left centrals, first

Developing smart city planning requires integrating various techniques, including geospatial techniques, building information models (BIM), information and communication technology (ICT), and artificial intelligence, for instance, three-dimensional (3D) building models, in enabling smart city applications. This study aims to comprehensively analyze the role and significance of geospatial techniques in smart city planning and implementation. The literature review encompasses (74) studies from diverse databases, examining relevant solutions and prototypes related to smart city planning. The focus highlights the requirements and preparation of geospatial techniques to support the transition to a smart city. The paper explores various aspects,

Diazotization reaction between 1-(2,4,6-Trihydroxy-phenyl)-ethanone and diazonium salts was carried out resulting in ligand 4-(3-Acetyl-2,4,6-trihydroxy-phenylazo)-N-(5-methyl-isoxazol-3-yl)-benzenesulfonamide, this in turn reacted with the next metal ions (V4+ , Cr3+ , Mn2+ and Cu2+) forming stable complexes with unique geometries such as (Octahedral for both Cr3+ , Mn2+ and Cu2+ ,squar pyramidal for V4+). The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible which proved the obtained geometries, fourier transfer proved the formation of azo group and and the coordination with metal ion through it. Pyrolysis (TGA & DSC) studies proved the coordination of water residues with me

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod