Catalytic reduction is considered an effective approach for the reduction of toxic organic pollutants from the environment, but finding an active catalyst is still a big challenge. Herein, Ag decorated CeO2 catalyst was synthesized through polyol reduction method and applied for catalytic reduction (conversion) of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The Ag decorated CeO2 catalyst displayed an outstanding reduction activity with 99% conversion of 4-NP in 5 min with a 0.61 min−1 reaction rate (k). A number of structural characterization techniques were executed to investigate the influence of Ag on CeO2 and its effect on the catalytic conversion of 4-NP. The outstanding catalytic performances of the Ag-CeO2 catalyst can be assigne

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

   The economical and highly performed anode material is the critical factor affecting the efficiency of electro-oxidation toward organics. The present study aimed to detect the best conditions to prepare Mn-Co oxide composite anode for the electro-oxidation of phenol. Deposition of Mn-Co oxide onto graphite substrate was investigated at 25, 30, and 35 mA/cm² to detect the best conditions for deposition.  The structure and the crystal size of the Mn-Co oxide composite electrode were examined by using an X-Ray diffractometer (XRD), the morphological properties of the prepared electrode were studied by scanning electron microscopy (SEM) and Atomic force microscopy (AFM) techniques, and the chemical composition of the various

This paper presents the first data for bremsstrahlung buildup factor (BBUF) produced by the complete absorption of Y-91 beta particles in different materials via the Monte Carlo simulation method. The bremsstrahlung buildup factors were computed for different thicknesses of water, concrete, aluminum, tin and lead. A single relation between the bremsstrahlung buildup factor BBUF with both the atomic number Z and thickness X of the shielding material has been suggested.

The effect of 0.662MeV gamma radiation on the optical properties of the CdTe thin films was studied. 300nm thickness of CdTe samples were irradiated with doses (10, 20, 30,60krad) in room temperature. The absorption spectra for all the samples were recorded using UV- Visible spectrometer in order to calculate the energy gap, width of localized states and optical constants(refractive index, extinction coefficient, real and imaginary parts of dielectric constant). The optical energy gap was found to decrease from (1.53 to 1.48 eV), while the width of localized states increased from (1.34 to 1.49 eV) with the increasing of radiation dose. The behavior of energy gap with the irradiation dose makes the material a good candidate for dosimetry

In this study tungsten oxide and graphene oxide (GO-WO2.89) were successfully combined using the ultra-sonication method and embedded with polyphenylsulfone (PPSU) to prepare novel low-fouling membranes for ultrafiltration applications. The properties of the modified membranes and performance were investigated using Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), contact angle (CA), water permeation flux, and bovine serum albumin (BSA) rejection. It was found that the modified PPSU membrane fabricated from 0.1 wt.% of GO-WO2.89 possessed the best characteristics, with a 40.82° contact angle and 92.94% porosity. The permeation flux of the best membrane was the highest. The pure water permeation f

       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