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

Introduction: The use of screw-retained hybrid arch bars (HABs) is a relatively recent development in the treatment of mandibular fractures. The purpose of this study is to compare the clinical outcome between HAB and the conventional Erich arch bar (EAB) in the closed treatment of mandibular fractures. Materials and methods: This study included 18 patients who were treated for mandibular fractures with maxillomandibular fixation (MMF), patients were randomly assigned into a control group (n = 10) in which EAB was used and study group (n = 8) in which HAB was used. The outcome variables were time required for application and removal, gingival inflammation scores, postoperative complications, and incidence of wire-stick injury or gloves perf

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized

The osseodensification (OD) drilling technique was suggested as an alveolar ridge expansion technique, so the aim of this prospective clinical study was to evaluate the amount of bone expansion obtained by the OD drilling technique and its effect on implant stability in patients with narrow alveolar ridges. The width of the alveolar ridge was measured at the crest before and after implant site preparation, whereas the implant stability was measured using Osstell Beacon implant stability quotient (ISQ). The ISQ values were recorded immediately postoperatively and after 16 weeks. Twenty-three patients were included; they received 40 implants. The mean (± standard deviation [SD]) amount of expansion was 1.29 (± 0.41) mm, and the difference b

oupling reaction of 4-aminoantipyrene with the (L-Histidine) gave the new bidentate azo ligand.The prepared ligand was identified by FT.IR, UV-Vis and HNMR spectroscopics technique. Treatment of the prepared ligand was done with the following metal ions (Ag+ ,Pb+2 ,Fe+3 ,Cr+3  ) in aqueous ethanol with a1:1 and 1:2  M:L ratio . The prepared complexes were characterized by using FT. IR and UV- VIS spectroscopic method as well as conductivity measurements. Their structures were suggested according to the results obtained.

Polyimides are widely used in high-temperature plastics, adhesives, dielectrics, photoresists, nonlinear optical materials, separation membrane materials, and Langmuir-Blodgett (LB) films. They are commonly regarded as the most heat-resistant polymers. This work involved the synthesis of a new bismaleimide homopolymer and copolymer by performing many steps. The synthesis of compound (1) (bis [4-(amino phenyl) Schiff base] tolidine) via condensation of o-tolidine with two moles of 4-aminoacetophenone. Secondly, compound (1) was combined with maleic anhydride to form compound (2) (4, 4ˉ-bis[4-(N-maleamic acid) phenyl Schiff base] toluidine). Thirdly, a dehydration reaction was carried out affording compound (3) (4,4ˉ-bis [4-(N-maleimidyl

Coupling reaction of m-and p- amino acetop henone and p-amino benzoic acid with (LHistidine) gave the new bidentate azo ligands (L1, L2 and L3). The prepared ligands were identified by FT-IR, UV-Vis, 1HNMR and GC- mass sp ectroscopic technique. Treatment of the prepared ligands with the following metal ions (CoII, NiII, CuII, ZnII, CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M (L)2 Cl2]. The prepared complexes were characterized by using flame atomic absorption, FT-IR, UV-Vis and 1HNMR spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the com