Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

Liquid electrodes of domperidone maleate (DOMP) imprinted polymer were synthesis based on precipitation polymerization mechanism. The molecularly imprinted (MIP) and non-imprinted (NIP) polymers were synthesized using DOMP as a template. By methyl methacrylate (MMA) as monomer, N,Nmethylenebisacrylamide (NMAA) and ethylene glycol dimethacrylate (EGDMA) as cross-linkers and benzoyl peroxide (BP) as an initiator. The molecularly imprinted membranes were synthesis using acetophenone (APH), di-butyl sabacate (DBS), Di octylphthalate (DOPH) and triolyl phosphate (TP)as plasticizers in PVC matrix. The slopes and limit of detection of l

ي لا ماق ثحبلا فادهأ قيقحتلو ثحبلا ةنيعل نايبتسا ءارجاو فراصملل ةيلاملا مئاوقلا ليلحتب ثحاب اهمهأ ناك تاجاتنتسا ىلإ ثحابلا لصوت دقو لإ صاخ معد دوجو مدع نم ةيفرصملا رطاخملا ةراد ةروصب اهدوجو مدعو فراصملل ةماعلا تارادلاا يف اهدوجو رصتقي ثيح ،ايلعلا تاهجلا لبق نم ديزي امم ،عورفلا يف ةلاعف مدع ةجيتن عورفلا نم ةدلوتملاو فراصملا اههجاوت يتلا رطاخملا اهمهأ ناك تايصوت ىلإ ثحابلا لصوت دقو امك ،ةيفرصملا تلاماعم

Research is aimed at defining the risks that the sales activity of the General Company for Leather Industries about a special, then diagnose these risks, through a set of indicators, which indicate its existence and try to overcome them, and minimizing the negative effects on those activities.

The research found some conclusions, which emphasizes that the General Company for Leather Industries, suffer from a lack of profit, and a large decrease in sales; a result of absence of demand on its products and rising cost of the expenses to income ratio of, which was reflected in the cost per unit produced. Also the conclusions shown that the number of sales outlets for the company to cover the geographical area is not enough, in spite