The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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.

This paper describes the development of a simple spectrophotometric determination of bismuth III with 4-(2-pyridylazo) resorcinol (PAR) in aqueous solution in the presence of cetypyridinium chloride surfactant at pH 5 which exhibits maximum absorption at 532 nm. Beer's law is obeyed over the range 5-200 µg/25 mL. i.e. 0.2-8 ppm with a molar absorptivity of 3×104 l.mol-1.cm-1 and Sandell's sensitivity index of 0.0069 µg.cm-2. The method has been applied successfully in the determination of Bi (III) in waters and veterinary preparation.

This study explored the development and qualities of the response of electrochemical properties of enrofloxacin-selective electrodes using precipitation based on producing phosphotungstic, after utilizing a matrix of polyvinyl chloride (PVC) and dibutyl phthalate or dibutyl phosphate as a plasticizer. The resulting membrane sensors were an enrofloxacin-phosphotungstic electrode (sensors 1) and an ENR-DOP-PTA electrode (sensors 2). Linear responses of (ENR-DBPH-PTA) and (ENR-DOP-PTA) within the concentration ranges of 2.1×10^-6-10^-1 and 3.0×10^-6-10^-2 mol. L^-1, respectively, for both sensors were observed. Slopes of 51.61±0.24 and 39.40± 0.16 mV/decade and pH ranges equal to 2.5-8.5

The New Schiff base ligand 4,4'-[(1,1'-Biphenyl)-4,4'-diyl,bis-(azo)-bis-[2-Salicylidene thiosemicarbazide](HL)(BASTSC)and its complexes with Co(II), Ni(II), and Cu(II) were prepared and characterized by elemental analysis, electronic, FTIR, magnetic susceptibility measurements. The analytical and spectral data showed, the stiochiometry of the complexes to be 1:1 (metal: ligand). FTIR spectral data showed that the ligand behaves as dibasic hexadentate molecule with (N, S, O) donor sequence towards metal ions. The octahedral geometry for Co(II), Ni(II), and Cu(II) complexes and non electrolyte behavior was suggested according to the analysis data.

          The objective of the present investigation was to enhance the solubility of practically insoluble mirtazapine by preparing nanosuspension, prepared by using solvent anti solvent technology. Mirtazapine is practically insoluble in water which act as antidepressant .It was prepared as nano particles in order to improve its solubility and dissolution rate. Twenty formulas were prepared and different stabilizing agents were used with different concentrations such as poly vinyl pyrrolidone (PVPK-90), poly vinyl alcohol (PVA), poloxamer 188 and poloxamer 407. The ratios of drug to stabilizers used to prepare the nanoparticles were 1: 1 and 1:2. The prepared nanoparticles were evaluated for