Nanofiltration (NF) ceramic membrane have found increasing applications particularly in wastewater and water treatment. In order to estimate and optimize the performance of NF membranes, the membrane should be characterized correctly in terms of their basic parameters such as effective pore radius (r_p) and equivalent effective thickness as well as effective surface charge ( ), the effective charge density ( ) and Donnan potential ( ). The impact of electrokinetic (zeta) potential on the membrane surface charge density, effective membrane charge density and Donnan potential at two different concentrations of the reference solutions 0.001, 0.01 M sodium chloride at various pH values from 3 to 9, and effective po

Traditional volumetric asphalt mix design methods do not directly evaluate cracking and rutting resistance, which may result in mixtures with inadequate field performance despite satisfying conventional volumetric requirements. Balanced Mix Design (BMD) has been introduced to address this limitation by incorporating performance testing. However, it remains unclear whether additive modification alone can recover mixtures that do not satisfy BMD criteria, or whether volumetric redesign (binder content optimization) is necessary. Therefore, this study investigated the effectiveness of additive modification before and after BMD redesign using IDEAL-CT and IDEAL-RT performance indices. Three additive systems were evaluated: SBS polymer,

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The residual limb within the prosthesis, is often subjected to tensile or fatigue stress with varying temperatures. The fatigue stress and temperatures difference which faced by amputee during his daily activities will produces an environmental media for growth of fungi and bacteria in addition to the damage that occurs in the prosthesis which minimizingthe life of the prosthetic limb and causing disconfirm feeling for the amputee.

In this paper, a mechanical and thermal properties of composite materials prosthetic socket made of different lamination for perlon/fiber glass/perlon, are calculated by using tesile test device under varying temperatures ( from 20oC to 60oC), also in this paper a device for measuring rotational bendin

A modern, rapid RP-HPLC-UV method was developed and validated in compliance with FDA and EMA guidelines for simultaneous quantification of 15 βlactam antibiotics) Ampicillin, Amoxicillin, cephalexin, cefotaxime, cefoxitin, cefamandole, cephalothin, piperacillin, penicillin, oxacillin, cloxacillin, nafcillin Carbenicillin, Mezlocillin and Dicloxacillin) in pharmaceutical formulations and pure forms. The method employs Column NEUCLEODUR C-18 (4.0 mm x 100 mm, 5µm particle size), at a temperature of thirty degrees Celsius, and the mobile phase was acetonitrile and KH2PO4 using gradient elution with a total separation time of 13 minutes, a flow rate of 1.3 ml/min, at = pH 4.5 for the buffer solution and the λ max was 220 nm. The met

The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled