The aim of this study is to utilize the electromembrane extraction (EME) system as a manner for effective removal of zinc from aqueous solutions. A novel and distinctive electrochemical cell design was adopted consisting of two glass chambers, a supported liquid membrane (SLM) housing a polypropylene flat membrane infused with 1-octanol and a carrier. Two electrodes were used, a graphite as anode and a stainless steel as cathode. A comprehensive examination of several influential factors including the choice of carrier, the applied voltage magnitude, the initial pH of the donor solution, and the initial concentration of zinc was performed, all in a concerted effort to ascertain their respective impacts on the efficiency of zinc elimination. Two distinct carriers, namely tris(2-ethylhexyl) phosphate (TEHP) and bis(2-ethylhexyl) phosphate (DEHP) were evaluated, in a tandem with utilization of 1-octanol. The results revealed essential role played by the applied voltage in augmenting the rate of mass transfer of zinc across the membrane. The best operating conditions were utilized for 1-octanol enriched with 1.0 vol.% bis(2-ethylhexyl) phosphate as a carrier, applied voltage of 60 V, initial pH of 5, initial zinc concentration of 15 mg L-1, extraction duration of 6 hours, and stirring rate of 1000 rpm. Surprisingly, operating under these meticulously devised conditions culminated in the outstanding removal efficiency of 87.3 %. In comparison with no applied voltage, a substantial enhancement in removal efficiency was observed, transcending from a meager 36.67 % to an impressive 87.3 % at 60 V, suggesting thus a tremendous potential of EME as an efficacious technique for the elimination of heavy metals.
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
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreSmoking and central obesity have both been linked to periodontitis, but their combined relationship with periodontal disease may be influenced by demographic and behavioral factors. This cross-sectional study analyzed records of 420 adult dental patients attending the College of Dentistry at the University of Baghdad. Data included demographic characteristics, smoking status, periodontal clinical findings, body mass index (BMI), and waist-to-height ratio (WHtR). Periodontitis was defined according to the 2018 classification framework, and logistic regression models were used to examine the associations of smoking and obesity-related indicators with periodontitis. The overall prevalence of periodontitis was 36.4%. Participants with p
... Show MoreThe posterior regions of the jaws usually represent a significant risk for implant surgery. A non-valid assessment of the available bone height may lead to either perforation of the maxillary sinus floor or encroachment of the inferior alveolar nerve and consequently to implant failure. This study aimed to evaluate the reliability of surgeon’s decision in appraising the appropriate implant length, in respect to vital anatomical structures, using panoramic radiographs.
Only implants that are inserted in relation to the maxillary sinus (MS) or the mandibular canal (MC) were enrolled (firs
The compliance is considered
This study aimed to deduce the net atrioventricular compliance which is affected the trans mitral blood flow.
This study focuses on study group of 25 patients (15 males
The study objective was to summarize and evaluate the literature from the last decade about the cost of illness (COI) of diabetic retinopathy (DR) and diabetic macular edema (DME) through a systematic review.
Author conducted a search of the PubMed, and Google Scholar, electronic databases from January 2014 until July 2024, by identifying the following keywords ‘cost of illness,’ ‘economic burden,’ ‘diabetic retinopathy,’ and ‘diabetic m