Confronting the severe health threats and environmental impacts of Cr(Ⅵ) in aquatic environments demands innovative and effective remediation approaches. In this study, Graphene oxide(GO)-decorated poly(dimethyl amin...
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Confronting the severe health threats and environmental impacts of Cr(Ⅵ) in aquatic environments demands innovative and effective remediation approaches. In this study, Graphene oxide(GO)-decorated poly(dimethyl amino ethyl methacrylate)(PDMAEMA) brush nanocomposites(GOP1, GOP2, GOP3, and GOP4) were fabricated using atom transfer radical polymerization(ATRP) by the “graft from” *** resulting nanocomposites were utilized for removing Cr(Ⅵ) with good adsorption performance due to the electrostatic interaction of protonated nitrogen groups in the brush chains with negatively charged particles in the solution. The kinetic model of pseudo-second-order best represented the contaminants' adsorption characteristics. The Weber-Morris model further indicated that surface adsorption and intraparticle diffusion mechanisms primarily controlled the adsorption procedure. Additionally, the Langmuir and Temkin isotherm models were found to most accurately represent the adsorption characteristics of the pollutants on the nanocomposites, and GOP4 can achieve the maximum adsorption capacity of 164.4 mg·g^(-1). The adsorbents' capacity maintains above 85% after five cycles of adsorption-desorption. The nanocomposites in this study demonstrate promising potential for eliminating Cr(Ⅵ) from aqueous solutions.
The demand for efficient power management solutions in electronic devices has increased significantly, especially for microcontrollers operating in low-power modes. This article presents the design and implementation ...
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In this study, mesoporous materials MCM-41 and SBA-15 were prepared by template extraction using supercritical carbon dioxide (CO2). When using the supercritical CO2 method, the extraction ratio of the template agent ...
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This paper proposes a new methodology for sensitivity analysis evaluation, fast and with high precision of the electric potential distribution near the transmission lines (TL's). The TL is modeled by the finite el...
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Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in *** 17.9 million people die from CVDs annually,accounting fo...
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Prediction and diagnosis of cardiovascular diseases(CVDs)based,among other things,on medical examinations and patient symptoms are the biggest challenges in *** 17.9 million people die from CVDs annually,accounting for 31%of all deaths *** a timely prognosis and thorough consideration of the patient’s medical history and lifestyle,it is possible to predict CVDs and take preventive measures to eliminate or control this life-threatening *** this study,we used various patient datasets from a major hospital in the United States as prognostic factors for *** data was obtained by monitoring a total of 918 patients whose criteria for adults were 28-77 years *** this study,we present a data mining modeling approach to analyze the performance,classification accuracy and number of clusters on Cardiovascular Disease Prognostic datasets in unsupervised machine learning(ML)using the Orange data mining *** techniques are then used to classify the model parameters,such as k-nearest neighbors,support vector machine,random forest,artificial neural network(ANN),naïve bayes,logistic regression,stochastic gradient descent(SGD),and *** determine the number of clusters,various unsupervised ML clustering methods were used,such as k-means,hierarchical,and density-based spatial clustering of applications with noise *** results showed that the best model performance analysis and classification accuracy were SGD and ANN,both of which had a high score of 0.900 on Cardiovascular Disease Prognostic *** on the results of most clustering methods,such as k-means and hierarchical clustering,Cardiovascular Disease Prognostic datasets can be divided into two *** prognostic accuracy of CVD depends on the accuracy of the proposed model in determining the diagnostic *** more accurate the model,the better it can predict which patients are at risk for CVD.
Attention deficit hyperactivity disorder (ADHD) is one of the children’s most common neurodevelopmental conditions. ADHD diagnosis is based on evaluating inattention, hyperactivity, and impulsivity symptoms that inte...
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Vibration analysis is crucial for predictive maintenance of bearing systems, aiming to reduce costs and prevent failures. This paper investigates signal processing techniques such as FFTs and Hilbert Transforms for fa...
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This study proposes a conceptual design of green hydrogen production via proton exchange membrane electrolysis powered by a floating solar photovoltaic *** system contributes to industrial decarbonization in which hyd...
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This study proposes a conceptual design of green hydrogen production via proton exchange membrane electrolysis powered by a floating solar photovoltaic *** system contributes to industrial decarbonization in which hydrogen blending with natural gas is proposed as an approach to smooth the energy *** proposed design addresses the challenge of supplying a continuous flow-rate of green hydrogen,which is typically demanded by industrial end *** study particularly considers a realistic area required for the installation of a floating solar photovoltaic *** enable the green hydrogen production of 7.5 million standard cubic feet per day,the required structure includes the floating solar photovoltaic system and Li-ion batteries with the nominal capacities of 518.4 megawatts and 780.8 *** is equivalent to the requirement for 1524765 photovoltaic modules and 3718 Li-ion *** assessment confirms the technical viability of the proposed concept of green hydrogen production,transportation and *** the present commercialization is hindered by economics due to a high green hydrogen production cost of USD 26.95 per kg,this green hydrogen pathway is expected to be competitive with grey hydrogen produced via coal gasification and via natural gas steam reforming by 2043 and 2047,respectively.
Poverty is considered a serious global issue that must be immediately eradicated by Sustainable Development Goals (SDGs) 1, namely ending poverty anywhere and in any form. As a developing country, poverty is a complex...
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Artificial neural networks (ANNs) are intricate mathematical models, drawing inspiration from the biological nervous system, and offering intelligence alongside nonparametric capabilities. The efficacy of ANNs heavily...
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