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Assessment and optimization of As(V) adsorption on hydrogel composite integrating chitosan-polyvinyl alcohol and Fe3O4 nanoparticles and evaluation of their regeneration and reusable capabilities in aqueous media

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Science of the Total Environment 2023年 855卷 158877页

作者： Weerasundara, Lakshika Ok, Yong Sik Kumarathilaka, Prasanna Marchuk, Alla Bundschuh, Jochen School of Civil Engineering and Surveying Faculty of Health Engineering and Sciences University of Southern Queensland West Street ToowoombaQLD4350 Australia Korea Biochar Research Centre & Division of Environmental Sciences and Ecological Engineering Korea University Seoul Korea Republic of Institute for Life Sciences and the Environment University of Southern Queensland West Street ToowoombaQLD4350 Australia Doctoral Program in Science Technology Environment and Mathematics Department of Earth and Environmental Sciences National Chung Cheng University 168 University Rd. Min-Hsiung Chiayi County62102 Taiwan

A modified chitosan-polyvinyl alcohol (PVA) hydrogel was developed by incorporating Fe3O4 nanoparticles. Four chitosan-Fe3O4 (ChFe) hydrogel types were developed based on chitosan:Fe3O4 ratio as 1:0, 1:1, 1:0.5 and 1:0.25. Batch sorption experiments were conducted with different pH, dosage, kinetics, and isotherms. The exhausted ChFe hydrogels were evaluated for their regeneration and reuse capability with different acids and bases. The best hydrogel for arsenic (V) [As(V)] adsorption was 1:0.5 ratio ChFe hydrogel. The highest As(V) adsorption (89 %) was at pH 4 and the adsorption capacity gradually decreased with increasing solution pH. Within the pH 4–6 range, the hydrogel surface became positively charged due to protonation of –NH2 and –OH groups in the polymer chain and the positive surface attracted H2AsO4− and HAsO42− oxyanions. The experimental kinetic data was well-fitted to the Elovich model (R2 of 0.99) while the Freundlich isotherm model best described the isotherm data (R2 of 0.97). The models predicted chemisorption mechanisms on ChFe hydrogel composites. Electrostatic attractions with –NH3+ and –OH2+, ligand-exchange inner-sphere complexes formation and bidentate corner-sharing (2C) and bidentate edge-sharing (2E) trimetric surface complexes formation have been proposed as the adsorption mechanism of As(V) into ChFe hydrogel. 0.1 M CH3COOH showed the best regeneration pattern with 75, 96, 81, 53 and 43 % of 1st, 2nd, 3rd, 4th and 5th adsorption respectively. Because of this re-usable capability, the As(V) adsorption capacity is not a single value from one adsorption cycle, but a cumulative value of several adsorption cycles and it was 17.39 mg/g for five adsorption cycles. Open for regeneration and reuse, no post-treatment is needed for adsorbent-water separation, allow applications of the ChFe hydrogel composite in a wide range of applications such as water filtration and purification systems. The modification with ChFe further expands the application

关键词： Nanoparticles

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Application of vetiver grass (Vetiveria Zizanioides L.) for organic matter removal from contaminated surface water

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Bioresource technology Reports 2023年 22卷

作者： Nguyen, Minh Ky Hung, Nguyen Tri Quang Nguyen, Cong Manh Lin, Chitsan Nguyen, Tuan Anh Nguyen, Hoang-Lam Ph.D. Program in Maritime Science and Technology National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Faculty of Environment and Natural Resources Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc Dist. Ho Chi Minh City700000 Viet Nam Research Institute for Biotechnology and Environment Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc Dist. Ho Chi Minh City700000 Viet Nam Department of Civil Engineering McGill University Montreal Canada

This study presents the vertical flow constructed wetlands (VFCWs) as a green solution for organic matter removal in contaminated surface water – a case study in Vietnam. The experiments were conducted with hydraulic loading rates (HLRs) of 500 mL/m2/min (T1), 1000 mL/m2/min (T2), and 1500 mL/m2/min (T3) using Vetiver grass (V) and Control (C). The findings indicated that Vetiver grass (Vetiveria Zizanioides L.) based-VFCWs model achieves a removal efficiency of 90 % for biochemical oxygen demand (BOD5) and >80 % for chemical oxygen demand (COD). This could explain the significant contribution of aquatic plants to the VFCWs based on vertical flow characteristics. Analysis of variance showed that HLRs significantly influence the treatment efficiency of BOD5 and COD (P © 2023 Elsevier Ltd

关键词： Irrigation

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Microalgae: A potential bioagent for treatment of emerging contaminants from domestic wastewater

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Chemosphere 2024年 351卷 141245页

作者： Mehariya, Sanjeet Das, Probir Thaher, Mahmoud Ibrahim Abdul Quadir, Mohammed Khan, Shoyeb Sayadi, Sami Hawari, Alaa H. Verma, Pradeep Bhatia, Shashi Kant Karthikeyan, Obulisamy Parthiba Zuorro, Antonio Al-Jabri, Hareb Algal Technology Program Center for Sustainable Development College of Arts and Sciences Qatar University Doha 2713 Qatar Department of Civil and Environmental Engineering College of Engineering Qatar University Doha 2713 Qatar Bioprocess and Bioenergy Laboratory Department of Microbiology Central University of Rajasthan Ajmer India Department of Biological Engineering College of Engineering Konkuk University Seoul 05029 South Korea Austin Elements Inc. 4315 South Dr Houston 77053 TX United States Sapienza University of Rome Rome 00184 Italy Department of Biological and Environmental Sciences College of Arts and Sciences Qatar University Doha 2713 Qatar

Water crisis around the world leads to a growing interest in emerging contaminants (ECs) that can affect human health and the environment. Research showed that thousands of compounds from domestic consumers, such as endocrine disrupting chemicals (EDCs), personal care products (PCPs), and pharmaceuticals active compounds (PhAcs), could be found in wastewater in concentration mostly from ng L⁻¹ to μg L⁻¹. However, generally, wastewater treatment plants (WWTPs) are not designed to remove these ECs from wastewater to their discharge levels. Scientists are looking for economically feasible biotreatment options enabling the complete removal of ECs before discharge. Microalgae cultivation in domestic wastewater is likely a feasible approach for removing emerging contaminants and simultaneously removing any residual organic nutrients. Microalgal growth rate and contaminants removal efficiency could be affected by various factors, including light intensity, CO₂ addition, presence of different nutrients, etc., and these parameters could greatly help make microalgae treatment more efficient. Furthermore, the algal biomass harvests could be repurposed to produce various bulk chemicals such as sustainable aviation fuel, biofuel, bioplastic, and biochar;this could significantly enhance the economic viability. Therefore, this review summarizes the microalgae-based bioprocess and their mechanisms for removing different ECs from different wastewaters and highlights the different strategies to improve the ECs removal efficiency. Furthermore, this review shows the role of different ECs in biomass profile and the relevance of using ECs-treated microalgae biomass to produce green products, as well as highlights the challenges and future research recommendations. © 2024 The Authors

关键词： Emerging contaminant Green products Microalgae Sustainable aviation fuel Wastewater

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Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity

arXiv

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arXiv 2025年

作者： Najjar, Ayat A. Ashqar, Huthaifa I. Darwish, Omar A. Hammad, Eman Faculty of Modern Science Arab American University 13 Zababdeh P.O Box 240 Jenin Palestine Civil Engineering Department Arab American University 13 Zababdeh P.O Box 240 Jenin Palestine Artificial Intelligence Program Fu Foundation School of Engineering and Applied Science Columbia University 500 W 120th St New YorkNY10027 United States Information Security and Applied Computing Eastern Michigan University 900 Oakwood St YpsilantiMI48197 United States iSTAR Lab Engineering Technology & Industrial Distribution Texas A&M University 400 Bizzell St College StationTX77840 United States

This study seeks to enhance academic integrity by providing tools to detect AI-generated content in student work using advanced technologies. The findings promote transparency and accountability, helping educators maintain ethical standards and supporting the responsible integration of AI in education. A key contribution of this work is the generation of the CyberHumanAI dataset, which has 1000 observations, 500 of which are written by humans and the other 500 produced by ChatGPT. We evaluate various machine learning (ML) and deep learning (DL) algorithms on the CyberHumanAI dataset comparing human-written and AI-generated content from Large Language Models (LLMs) (i.e., ChatGPT). Results demonstrate that traditional ML algorithms, specifically XGBoost and Random Forest, achieve high performance (83% and 81% accuracies respectively). Results also show that classifying shorter content seems to be more challenging than classifying longer content. Further, using Explainable Artificial Intelligence (XAI) we identify discriminative features influencing the ML model's predictions, where human-written content tends to use a practical language (e.g., use and allow). Meanwhile AI-generated text is characterized by more abstract and formal terms (e.g., realm and employ). Finally, a comparative analysis with GPTZero show that our narrowly focused, simple, and fine-tuned model can outperform generalized systems like GPTZero. The proposed model achieved approximately 77.5% accuracy compared to GPTZero's 48.5% accuracy when tasked to classify Pure AI, Pure Human, and mixed class. GPTZero showed a tendency to classify challenging and small-content cases as either mixed or unrecognized while our proposed model showed a more balanced performance across the three classes. © 2025, CC BY.

关键词： Adversarial machine learning

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Study of soil structure interaction on basement wall with variants in distance and depth of the basement on soil class SE 2

Study of soil structure interaction on basement wall with va...

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2nd Joint International Conference on Emerging Computing technology and Sports, JICETS 2019

作者： Saragi, Yetty Irsyam, Masyhur Roesyanto Hendriyawan University of Hkbp Nommensen Sutomo Street No.4A Medan20234 Indonesia Post Graduate Program Civil Engineering Departement University of Sumatera Utara Medan-North Sumatera20155 Indonesia Institute of Technology Bandung Ganesha 10 Bandung West-Java40135 Indonesia Civil Engineering Departement University of Sumatera Utara Medan North-Sumatera20155 Indonesia

The function of the basement is to carry the weight of the upper structure into the soil and to resist lateral loads around the basement wall. One aspect of geotechnical engineering that often a problem in basement wall planning is the determination of lateral ground pressure in the basement wall due to earthquake which must be held by the basement wall. In this study, an analysis of the effects of local soil conditions due to dynamic loads is done through analysis of soil-structure interaction. The analysis is done by modeling the local soil with variations in basement depth and the adjacent basement distance to get the lateral pressure distribution due to dynamic load. The analyzed soil conditions are considered homogeneous at land sites SE (soft soil) with the dynamic load input from earthquake loads uses a 10% probability of exceedance in 50 years (500 years). The most influential parameter for soil displacement is the distance of the basement and then the depth of the basement. The most influential parameter on lateral forces is the depth of the basement followed by the distance of the basement. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Dynamic loads

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Actuation Strategy of a Virtual Skydiver Derived by Reinforcement Learning

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IFAC-PapersOnLine 2020年第2期53卷 1569-1574页

作者： Anna Clarke Per-Olof Gutman Technion Autonomous Systems Program Technion - Israel Institute of Technology Haifa 32000 Israel Faculty of Civil and Environmental Engineering Technion – Israel Institute of Technology Haifa 32000 Israel

An innovative approach of training motor skills involved in human body flight is proposed. Body flight is the art of maneuvering during the free fall stage of skydiving. The key idea is gradually constructing the movement patterns which are the combinations of body degrees-of-freedom that are activated synchronously and proportionally as a single unit, and turning this process into a coaching strategy. The proposed method is iterative: at each skill level an optimal movement pattern is constructed from the basic elements of the current movement repertoire. The free-fall maneuvers of each learning stage can be executed using any one of the basic elements. The construction has two stages: 1. tracking the desired maneuver while the body is actuated by each one of the basic patterns; 2. finding an optimal combination of these patterns to form a new way of body actuation. This hierarchical design resolves stage 2 by Reinforcement Learning with pure exploration and a minimal number of episodes. The method was tested in a Skydiver Simulator and resulted in deriving a movement pattern that showed a superior performance of the studied maneuver. The states and the reward of the Reinforcement Learning algorithm were converted into motor learning aids.

关键词： autonomous systems simulators multiple degrees-of-freedom reinforcement learning

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Hull/Mooring/Riser coupled analysis of a turret-moored FPSO 6000FT: Comparison between polyester and buoys-steel mooring lines 11

Hull/Mooring/Riser coupled analysis of a turret-moored FPSO ...

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SNAME 11th Offshore Symposium - Opportunities and Challenges: technology for the Gulf of Mexico and Beyond

作者： Tahar, Arcandra Nurtjahyo, Prahoro Kim, Joseph M.H. Offshore Technology Research Center Department of Civil Engineering Ocean Engineering Program Texas A&M University United States

Hull/mooring/riser coupled dynamic analyses of a tanker-based turret-moored FPSO (Floating Production Storage and Offloading) designed for 6000-ft water depth are conducted in the time domain. Two types of mooring systems (12 chain-polyester-chain mooring lines, called FPSO 6000ft - polyester, and 12 chain-spring buoys-jacketed spiral strand-ground chain mooring lines, called FPSO 6000ft - buoy) and 13 steel catenary risers are included as slender members. The numerical simulations were conducted for 100-yr Hurricane condition with nonparallel wind, wave, and current. The performance of those two mooring systems is compared and the differences are analyzed. The comparison shows that under the same environmental condition, the taut polyester lines give better motion characteristics of hull than slack steel lines with buoy. © SNAME 2019.

关键词： Floating production storage and offloading

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Seasonal Influence on Pollution Index and Risk of Multiple Compositions of Microplastics in an Urban River

SSRN

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SSRN 2022年

作者： Huang, Chi-Wei Li, Yi-Lin Lin, Chitsan Bui, Xuan-Thanh Vo, Thi-Dieu-Hien Ngo, Huu Hao Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan Ph.D. Program in Maritime Science and Technology College of Maritime National Kaohsiung University of Science and Technology Kaohsiung81157 Taiwan 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam Linh Trung ward Ho Chi Minh City700000 Viet Nam Faculty of Environmental and Food Engineering Nguyen Tat Thanh University Ho Chi Minh City Viet Nam School of Civil and Environmental Engineering University of Technology Sydney SydneyNWS 2007 Australia

The emerging contaminant microplastics (MPs) are getting worldwide attention for their ubiquitous occurrence and potential risk in the environment. However, the seasonal influence on freshwater MP pollution remains poorly understood. To better understand and evaluate the riverine MPs in different seasons, this study conducted the risk assessment of MPs in an urban river, Houjin River, during the different seasons. The present study found that the MPs was more abundant in the dry season compared with wet seaon. Similarly, the mixture of different MPs polymers was more diverse in the dry season. The related pollution indexes such as the contamination factor (CF) and pollution load index (PLI) showed that the majority of the water samples in Houjin River was heavily polluted and higher in the dry season. The higher risk quotient (RQ) of MPs in the dry season was also observed. To sum up, the results of this study indicate the seasonal effects on the pollution and risk of multiple compositions of MPs in the urban river, suggesting higher impacts of riverine MPs pollution in the dry season, as well as the potential increase of MPs may lead to health risk in the future. © 2022, The Authors. All rights reserved.

关键词： Risk assessment

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Predicting the insulating paper state of the power transformer based on XGBoost/LightGBM models

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Scientific Reports 2025年第1期15卷 1-16页

作者： Ghoneim, Sherif S. M. Baz, Mohammed Alzaed, Ali Zewdie, Yohannes Tesfaye Department of Electrical Engineering College of Engineering Taif University Taif 21944 Saudi Arabia Department of Computer Engineering College of Computers and Information Technology Taif University Taif 21944 Saudi Arabia Architectural Engineering Program - Civil Engineering Department Faculty of Engineering Taif University Taif 21944 Saudi Arabia Department of Electrical and Computer Engineering Faculty of Technology Debre Markos University P. BOX 269 Debre Markos Ethiopia

Power transformer plays a crucial role in the power networks. Most of the transformer malfunctions was due to failure in the insulating systems. The utilities keen on the contentious operation of the power network, so early detection of the transformer faults avoiding the undesirable outage of the transformer from the service. The insulating paper state is an indication to the transformer health and aging of it may lead to failure of the transformer, so some periodic and routine test must be performed on the insulting oil to get information about the insulating paper condition. The value of the degree of polymerization (DP) is a key of the insulating paper state. Various recommended tests such as the dissolved gases (DGA), breakdown voltage (BDV), oil interfacial tension (IF), oil acidity (ACI), moisture content (MC), oil color (OC), dielectric loss (Tan δ), and furans concentration specifically (2-furfuraldehyde (2-FAL)) were carried out to correlate between these variables and the DP and then to the insulating oil state. The collected data from these tests were used to supply XGBoost/LightGBM to build artificial intelligence model to predict the insulating paper state. The results indicated that the great ability of the proposed model to predict the insulating state with high accuracy. Of these various configurations for these two classification models, one achieved perfect prediction accuracy (100%) of the insulating paper state prediction accuracy. The other configurations showed accuracy values from 1.0 down to 0.955. © The Author(s) 2025.

关键词： Dissolved gas analysis Furnic compounds Insulating oil Insulating paper Power transformer XGBoost/LightGBM

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Analysis of the association between image resolution and landscape metrics using multi-sensor LULC maps

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Planning Outlook Series 1 2024年第10期67卷

作者： Beril Varol Szilard Szabo Raziye Hale Topaloğlu Gül Aslı Aksu Elif Sertel a Graduate Program of Geomatics Engineering Istanbul Technical University Graduate School of Science Engineering and Technology Istanbul Turkiye b Department of Physical Geography and Geoinformatics Faculty of Science and Technology University of Debrecen Debrecen Hungary c Faculty of Civil Engineering Department of Geomatics Yildiz Technical University Istanbul Turkiye d Faculty of Engineering and Architecture Department of Landscape Architecture Kastamonu University Kastamonu Turkiye e Faculty of Civil Engineering Department of Geomatics Engineering Istanbul Technical University Istanbul Turkiye

This study aims to investigate the changes in landscape metrics with varying spatial resolution from Sentinel-2 (10 m), SPOT 7 (1.5 m), Pleaides (0.5 m), and Worldview-4 (0.3 m) images. We implemented Geographic Object-Based Image Analysis (GEOBIA) techniques to all images to identify 21 land use and land cover (LULC) classes, which were then used to calculate several landscape metrics. We performed the Welch hypothesis testing on the class-level landscape metrics and applied Standardized Principal Component Analysis (PCA) with the correlation matrix to reveal the multivariate pattern of landscape metrics. Our results showed that 10 m and even the 1.5 m spatial resolutions cannot guarantee the identification of all LULC classes, and class areas change with varying spatial resolution (sometimes with 200% differences). Sentinel-2 images have some limitations, specifically from the landscape ecological planning perspective; on the other hand, Pleaides and Worldview-4 seem good alternatives to understand habitats’ viability and landscape isolation/connectivity.

关键词： GEOBIA land use/land cover (LULC) mapping landscape pattern urban habitats spatial resolution

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