In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Nanoparticles of Pb_1-xCd_xS within the composition of 0≤x≤1 were prepared from the reaction of aqueous solution of cadmium acetate, lead acetate, thiourea, and NaOH by chemical co-precipitation. The prepared samples were characterized by UV-Vis spectroscopy(in the range 300-1100nm) to study the optical properties, AFM and SEM to check the surface morphology(Roughness average and shape) and the particle size. XRD technique was used to determine the crystalline structure, XRD technique was used to determine the purity of the phase and the crystalline structure, The crystalline size average of the nanoparticles have been found to be 20.7, 15.48, 11.9, 11.8, and 13.65 nm for PbS, Pb_0.75Cd_0.25S,

Nimodipine (NMD) is a dihydropyridine calcium channel blocker useful for the prevention and treatment of delayed ischemic effects. It belongs to class ? drugs, which is characterized by low solubility and high permeability. This research aimed to prepare Nimodipine nanoparticles (NMD NPs) for the enhancement of solubility and dissolution rate. The formulation of nanoparticles was done by the solvent anti-solvent technique using either magnetic stirrer or bath sonicator for maintaining the motion of the antisolvent phase. Five different stabilizers were used to prepare NMD NPs( TPGS, Soluplus®, HPMC E5, PVP K90, and poloxamer 407). The selected formula F2, in which  Soluplus 

has been utilized as a stabilizer, has a par

Nanotechnology has shown a lot of promise in the oil and gas sectors, including nanoparticle-based drilling fluids. This paper aims to explore and assess the influence of various nanoparticles on the performance of drilling fluids to make the drilling operation smooth, cost effective and efficient. In order to achieve this aim, we exam the effect of Multi Wall Carbon Nanotube and Silicon Oxide Nanoparticles as Nanomaterial to prepare drilling fluids samples.

Anew method for mixing of drilling fluids samples using Ultra sonic path principle will be explained. Our result was drilling fluids with nano materials have high degree of stability.

   The results of using Multiwall Carbon Nanotube and Silicon Oxide show t

The MTX was converted to MTX  nanoparticles  by the modified method based on changing the pH gradually . For the first time MTX NPs+Meropenem complex were prepared and evaluated as a potential tool to overcome antimicrobial resistance and to improve pharmacokinetics of the drug, the results showed that the antibacterial activity of complex (MTX NPs plus MEM) has increased (from 1( µg/ml) to >0.5( µg/ml) for p1 , from 2( µg/ml) to 1( µg/ml) for p10 and from 8( µg/ml) to 4( µg/ml) for p48).

Cilnidipine is a dihydropyridine calcium channel blocker used to improve the neurological outcome following subarachnoid hemorrhage. It belongs to BCS class II drugs that have a low oral bioavailability of 13%, thus preparation as nanoparticles would be expected to improve bioavailability. The aim of the study is to prepare Cilnidipine as nanoparticles using different carriers and co-carriers, concentrations, and types. Cilnidipine nanoparticles were prepared by a solvent anti-solvent method using different carriers (Soluplus®, Poloxamer 188, PVA cold) with co-stabilizers (PEG200, glycerol) at different ratios. Based on the obtained results, formula N4, which included Soloplus in a 5:5:1.19 weight ratio of drug to

Palladium nanoparticles are produced by Polyol method. The characterization of the Pd nanoparticle has been conducted by various techniques such as SEM and AFM. The results of Pd powder showed that the particle size is directly proportional to the temperature and the reaction time. The optimum conditions for obtaining minimum nanoparticles size are 45 oC reaction temperature and 60 min reaction time and the smaller particle size achieved is equal to 25 nm. The optical limiting of smaller size nanoparticles has been studied. The palladium nanoparticles appear to be attractive candidates for optical limiting applications.

Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bel