n-Hexane conversion enhancement was studied by adding TCE (Trichloro-ethylene) on feed stream using 0.3%Pt/HY zeolite catalyst. All experiments were achieved at atmospheric pressure and on a continuous laboratory unit with a fixed bed reactor at a temperature range 240-270◦C, LHSV 1-3h-1, H2/nC6 mole ratio 1-4.
By adding 435 ppm of TCE, 49.5 mole% conversion was achieved at LHSV 1h-1, temperature of 270ºC and H2/nC6 mole ratio of 4, while the conversion was 18.3 mol% on the same catalyst without adding TCE at the same conditions. The activation energy decreased from 98.18 for pure Pt/HY zeolite to 82.83 kJ/mole by adding TCE. Beside enhancement the activity, selectivity and product distribution enhanced by providing DMB (Dimethyl b

Cold atmospheric plasma (CAP) is used widely in medical and biological fields because of non-thermal effected. Direct application of plasma is preferred in medical functions, so, direct application of cold plasma has obtained by the floating electrode dielectric barrier discharge (FE-DBD) system. The purpose of this paper to review the effect of (CAP) on the reproductive hormones (testosterone, LH, E2, progesterone, for male rats. The study appeared that no significant effect on E2 and progesterone hormone for all time of exposure, besides this significant difference in LH hormone (P<0.05) at 15 sec, (P<0.0001) at 30, 90 sec and (P<0.001) at 60 sec of exposure to plasma. Added to that significant difference (P<0.01) at 15, 30, 60 sec and no

Films of CdSe have been prepared by evaporation technique with thickness 1µm. Doping with Cu was achieved using annealing under argon atmosphere . The Structure properties of these films are investigated by X-ray diffraction analysis. The effect of Cu doping on the orientation , relative intensity, grain size and the lattice constant has been studied. The pure CdSe films have been found consist of amorphous structure with very small peak at (002) plane. The films were polycrystalline for doped CdSe with (1&2wt%) Cu contents and with lattice constant (a=3.741,c=7.096)A°, and it has better crystallinty as the Cu contents increased to (3&5wt%) Cu. The reflections from [(002), (102). (110), (112), and (201)]planes are more prominen

: Cervical cancer representsone of the possibly preventable cancer. The study was designed to find the possible correlation of Tafazzin on the progression of cervical carcinoma. Two groups of paraffinized blocks were included. The study group of 30 cervical tumors as well as 15 biopsies of healthy cervical tissues. After sectioning on a positive charge, immunohistochemical application (IHC) was performed to detect Tafazzin expression. Nighnty percentage (27 out of 30) of the studies group showed positive overexpression as shown in with a significant association of the expression with cervical cancer with a significant association. There is a possible role of TAZ in hastening the development of cervical cancer through different mechanisms. F

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

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

   Real life scheduling problems require the decision maker to consider a number of criteria before arriving at any decision. In this paper, we consider the multi-criteria scheduling problem of n jobs on single machine to minimize a function of five criteria denoted by total completion times (∑), total tardiness (∑), total earliness (∑), maximum tardiness () and maximum earliness (). The single machine total tardiness problem and total earliness problem are already NP-hard, so the considered problem is strongly NP-hard.

We apply two local search algorithms (LSAs) descent method (DM) and simulated annealing method (SM) for the 1// (∑∑∑