This paper reports the synthesis and use of a novel metal-organic framework (MOF), named Zr-BADS, within the thin-film nanocomposite (TFN) membranes for reverse osmosis (RO) applications. Two types of zirconium-based MOFs, Zr-BADS-1 and Zr-BADS-2, were synthesized via a solvothermal method using bicinchoninic acid disodium salt as a linker and either dimethylformamide or ethanol as solvent, respectively. TFN membranes were prepared by embedding these MOFs within the polyamide thin film supported by a polysulfone support sheet. The specific surface area of Zr-BADS-1 and Zr-BADS-2 was determined to be 396.1 and 278.6 m2/g, respectively, indicating significant surface area conducive to water permeation. Scanning electron microscopic analysis r

Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

A variety of single-engine driven files and inematics have been introduced to improve the clinical performance of NiTi rotary files. The purpose of this in vitro study was to measure and compare the incidence of dentinal defects after root canal preparation with different single file systems.

Used in the study especially calibrated Erwa to determine the number of neighborhood or the Alayoshi number of bacteria in the count modeling and casting method dishes in addition to using the drop method yielded significant results for a match between the methods used ..

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi