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Ecological risk assessment of potentially toxic elements (PTEs) in agricultural soil, vegetables and fruits with respect to distance gradient in proximity to lead-acid battery industry

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Environmental Nanotechnology, Monitoring and management 2024年 21卷

作者： Lima, Fatema Akter Bhattacharjee, Shovon Jahangir Sarker, Md. Salam, Mohammed Abdus Department of Environmental Science and Disaster Management Noakhali Science and Technology University Noakhali 3814 Bangladesh Biosecurity Program Kirby Institute University of New South Wales (UNSW Sydney) Kensington 2052 NSW Australia Mechanical and Manufacturing Engineering University of New South Wales (UNSW Sydney) Kensington 2052 NSW Australia Department of Fisheries and Marine Science Noakhali Science and Technology University Noakhali 3814 Bangladesh

Lead-acid battery industries in Bangladesh have proliferated in urban areas, leading to the release of significant amounts of potentially toxic elements (PTEs) and metalloids into the environment. This study aimed to assess the spatial distribution, sources, contamination status, and ecological risks in agricultural soils, vegetables, and fruits near these industries. Soil samples were collected from four sites at varying distances (0 m, 100 m, 250 m, and 500 m) around three lead-acid battery industries (AA, AB, and AC) in Dhaka and Gazipur Districts during June-July 2020. The concentrations of the Pb, As, Cd and Zn in agricultural soils were ranged between 8.40–116.61, 8.99–28.21, 0.03–1.28, and 25.38–68.72 mg/kg, respectively. The concentrations of Pb, As, and Cd were found to be considerably higher than background levels across all industries, with a gradual decrease in PTE concentrations from 0 m to 500 m. The contamination factor indicated high to moderate contamination in agricultural soils by As, Cd, and Pb, and low contamination by Zn. pollution load index, modified contamination degree, and nemerow comprehensive index revealed varying pollution levels in the vicinity of the industries, with AA and AB showing higher pollution compared to AC. The individual risk factors demonstrated significant risks associated with Cd and As exposure, while Pb and Zn posed lower risks. The potential ecological risk index indicated considerable ecological risk for AA (risk index = 192.41), moderate risk for AB (risk index = 111.80), AC (risk index = 65.08), respectively. Correlation and principal component analysis revealed strong positive associations (p < 0.01) among the chemical parameters and potentially toxic elements in soils, and demonstrated the lead-acid battery industry as the primary contamination source in the studied areas. There were strong positive relationships (p < 0.01) existed between As, Cd, and Zn in soils and vegetables;while a strong negative associatio

关键词： Hazardous materials Lead-acid battery Potentially toxic elements (PTEs) Risk assessment Soil contamination Vegetables and fruits

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha D Bhandarkar Aruna Sri Rongali Mohamed Dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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Perceived Risk and Reward Factors on Residential Solar Pv Adoption in the Philippines an Integration of Utaut, Tpb and Tam

SSRN

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SSRN 2024年

作者： Ragragio, Titus James Reynon Borres, Rianina D. Persada, Satria Fadil Young, Michael Nayat Ong, Ardvin Kester S. Prasetyo, Yogi Tri Nadlifatin, Reny Zulvia, Ferani Eva School of Industrial Engineering and Engineering Management Mapua University 658 Muralla St. Intramuros Manila1002 Philippines Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Malang65154 Indonesia International Bachelor Program in Engineering Yuan Ze University 135 Yuan-Tung Road Chung-Li32003 Taiwan Department of Industrial Engineering and Management Yuan Ze University 135 Yuan-Tung Road Chung-Li32003 Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia National Taiwan University of Science and Technology No.43 Keelung Rd. Sec.4 Da'an Dist. Taipei City106335 Taiwan

This study delves into the perception of homeowners in the Philippines regarding the utilization of Residential Rooftop Solar Photovoltaic Systems (RSPVS), focusing on their intention to adopt this renewable energy technology. The research is driven by the advantageous conditions in the Philippines, including high irradiance levels, supportive solar PV policies, and decreasing system costs. Understanding prosumers' (producers and consumers) perspectives is crucial to accelerating the adoption of RSPVS, which can significantly contribute to decentralizing and greening the electrical production landscape in the country. Building on previous studies, which highlight a keen interest in solar technology among homeowners but cite high installation costs and a lack of understanding as major barriers, this research aims to shed light on the factors influencing prosumers' intentions to use RSPVS. Employing a theoretical framework combining the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), Unified Theory of Acceptance and Use of Technology (UTAUT), and integrating Technophilia and Perceived Risk as supplementary constructs, this study seeks to uncover the drivers and inhibitors of RSPVS adoption. The study employs an online questionnaire distributed in key cities where Residential RSPVS is available, with a sample size of 239 respondents. The data collected are analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships between variables and to test the hypothesized model. The results indicate that factors such as Technophilia, Price Value, and Social Influence are significant determinants of prosumers' intent to adopt RSPVS. Notably, Technophilia, reflecting enthusiasm for new technology, emerged as a key factor, suggesting that prosumers are motivated by the allure of solar energy. Additionally, the study found that Perceived Risk was not a significant inhibitor, indicating a high level of confidence and tr

关键词： Solar energy

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Constructing a Minimized Connected Dominating Set Based on the Decentralized Nomination Algorithm in Mobile Ad Hoc Networks

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SSRN 2023年

作者： Hsieh, Hui-Ching Chiang, Mao-Lun Lin, Tzu-Ling Liao, Lu-Wen Chen, Ze-Yu Department of New Media Communication Hsing Wu University New Taipei City Taiwan Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung City Taiwan Department of Business Management National Taichung University of Science and Technology Taichung404336 Taiwan Department of Intelligent Production Engineering National Taichung University of Science and Technology Taiwan Department of Information and Communication Engineering Chaoyang University of Technology Taichung City Taiwan

Inspired by the backbone architecture of wired networks, in this study, we applied the concept of a virtual backbone to the routing scheme in a mobile ad hoc network (MANET) to develop an effective routing method. Using connected dominating set (CDS)-based methods to construct a virtual backbone network can effectively improve routing performance in a MANET. The CDS virtual backbone network we developed in the present study can respond quickly and identify routing paths through these CDS members as the network topology changes. Meanwhile, the nodes that are not CDS members can enter the power-saving mode to minimize unnecessary power consumption. Wireless nodes in a MANET can move freely within the network;therefore, CDS virtual backbones are easy to deconstruct. Researchers have developed centralized and decentralized CDS algorithms to reconstruct network topologies. When previously developed centralized CDS algorithms are applied, the system requires the information of all nodes in the network to reconstruct the virtual backbone. Therefore, the information exchange costs of such algorithms before refactoring are high. By contrast, decentralized CDS algorithms can use local information to reconstruct virtual backbones quickly. Yet, decentralized algorithms produce larger CDSs than centralized algorithms. To improve upon the performance of previously developed decentralized algorithms, we developed and herein present a new decentralized CDS algorithm called APP-CDS that can quickly construct a virtual backbone with the smallest possible CDS for use in MANET environments. © 2023, The Authors. All rights reserved.

关键词： Routing algorithms

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Automatic Assessment and Prediction of the Resilience of Utility Poles Using Unmanned Aerial Vehicles and Computer Vision Techniques

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International Journal of Disaster Risk science 2020年第1期11卷 119-132页

作者： Md Morshedul Alam Zanbo Zhu Berna Eren Tokgoz Jing Zhang Seokyon Hwang Department of Industrial Engineering University of LouisvilleLouisvilleKY 40292USA Department of Computer Science Lamar UniversityBeaumontTX 77710USA Department of Industrial Engineering Lamar UniversityBeaumontTX 77710USA Construction Management Program Lamar UniversityBeaumontTX 77710USA

The utility poles of electric power distribution lines are very vulnerable to many natural hazards, while power outages due to pole failures can lead to adverse economic and social consequences. Utility companies,therefore, need to monitor the conditions of poles regularly and predict their future conditions accurately and promptly to operate the distribution system continuously and *** article presents a novel pole monitoring method that uses state-of-the-art deep learning and computer vision methods to meet the need. The proposed method automatically captures the current pole inclination angles using an unmanned aerial vehicle. The method calculates the bending moment exerted on the poles due to wind and gravitational forces, as well as cable weight, to compare it with the moment of rupture. The method also includes a machine learning-based model that is built by using a support vector machine to predict the resilience conditions of a pole after a wind event in a faster manner. The three modules of the proposed method are effective tools to classify pole conditions and are expected to enable utility companies to increase the resilience of their systems.

关键词： Angular deflection Machine learning Support vector machine Texas Utility pole resilience

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LayOut Loud: An AI-Powered Augmented Reality and Mobile Application for Room Interior Design and Layout Optimization

LayOut Loud: An AI-Powered Augmented Reality and Mobile Appl...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： John Raphael G. Cuevas John Kenneth R. Rili Anny Neolicia G. Santillan Vivien A. Agustin Mary Grace N. Gonzales Criselle J. Centeno Richard C. Regala Department of Information Technology College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Computer Science Associate Dean of College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Information Technology Faculty of College of Engineering and Technology Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Information Technology Director of Graduate Program of College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines Department of Computer Science Computer Lab Administrator of College of Engineering and Technology Pamantasan ng Lungsod ng Maynila Manila Philippines

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

LayOut Loud is an AI-powered augmented reality (AR) and mobile application designed to revolutionize room interior design by offering tailored, real-time solutions for layout optimization. The primary objective of this tool is to design AI-powered features that analyze user-provided room dimensions, furniture types, and style preferences. By leveraging advanced algorithms, LayOut Loud generates personalized design suggestions that cater to the individual needs and aesthetic tastes of users, ensuring that each interior design experience is customized and unique. A key goal of the application is to enhance user experience and decision-making through a clustering algorithm. This algorithm categorizes furniture pieces based on their suitability and appearance in living spaces, streamlining the selection process for users. By enabling the visualization of these items in a 3D model, users can make informed decisions about their interior design choices, ensuring that each piece contributes to the overall aesthetic and functional harmony of the space. Additionally, LayOut Loud focuses on improving its AR capabilities by allowing users to capture their room layouts and view virtual furniture arrangements in real time. This feature provides practical, interactive design solutions, empowering users to experiment with different configurations and instantly see how potential changes would appear in their actual living environments. Ultimately, LayOut Loud offers a user-friendly, immersive platform that transforms the way individuals approach interior design.

关键词： Solid modeling Three-dimensional displays Layout Decision making Clustering algorithms Real-time systems User experience Mobile applications Augmented reality Optimization

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Occurrence and fate of pharmaceutical pollutants in wastewater: Insights on ecotoxicity, health risk, and state–of–the-art removal

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Chemosphere 2024年 354卷 141678页

作者： Nguyen, Minh-Ky Lin, Chitsan Bui, Xuan-Thanh Rakib, Md. Refat Jahan Nguyen, Hoang-Lam Truong, Quoc-Minh Hoang, Hong-Giang Tran, Huu-Tuan Malafaia, Guilherme Idris, Abubakr M. Faculty of Environment and Natural Resources Nong Lam University Hamlet 6 Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam 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 Linh Trung Ward Thu Duc City Ho Chi Minh City700000 Viet Nam Ho Chi Minh City700000 Viet Nam Department of Environmental Science and Management North South University Dhaka Bashundhara1229 Bangladesh Department of Civil Engineering McGill University Montreal Canada Faculty of Management Science Thu Dau Mot University Binh Duong 75000 Viet Nam Faculty of Medicine Dong Nai Technology University Dong Nai Bien Hoa76100 Viet Nam Laboratory of Ecology and Environmental Management Science and Technology Advanced Institute Van Lang University Ho Chi Minh City700000 Viet Nam Faculty of Applied Technology School of Engineering and Technology Van Lang University Ho Chi Minh City700000 Viet Nam Post-Graduation Program in Ecology Conservation and Biodiversity Federal University of Uberlândia MG Uberlândia Brazil Post-Graduation Program in Biotechnology and Biodiversity Federal University of Goiás GO Goiânia Brazil Post-Graduation Program in Conservation of Cerrado Natural Resources Goiano Federal Institute GO Urutaí Brazil Department of Chemistry College of Science King Khalid University Abha62529 Saudi Arabia King Khalid University Abha62529 Saudi Arabia

Pharmaceutical active compound (PhAC) residues are considered an emerging micropollutant that enters the aquatic environment and causes harmful ecotoxicity. The significant sources of PhACs in the environment include the pharmaceutical industry, hospital streams, and agricultural wastes (animal husbandry). Recent investigations demonstrated that wastewater treatment plants (WWTPs) are an important source of PhACs discharging ecosystems. Several commonly reported that PhACs are detected in a range level from ng L−1 to μg L−1 concentration in WWTP effluents. These compounds can have acute and chronic adverse impacts on natural wildlife, including flora and fauna. The approaches for PhAC removals in WWTPs include bioremediation, adsorption (e.g., biochar, chitosan, and graphene), and advanced oxidation processes (AOPs). Overall, adsorption and AOPs can effectively remove PhACs from wastewater aided by oxidizing radicals. Heterogeneous photocatalysis has also proved to be a sustainable solution. Bioremediation approaches such as membrane bioreactors (MBRs), constructed wetlands (CWs), and microalgal-based systems were applied to minimize pharmaceutical pollution. Noteworthy, applying MBRs has illustrated high removal efficiencies of up to 99%, promising prospective future. However, WWTPs should be combined with advanced solutions, e.g., AOPs/photodegradation, microalgae–bacteria consortia, etc., to treat and minimize their accumulation. More effective and novel technologies (e.g., new generation bioremediation) for PhAC degradation must be investigated and specially designed for a low-cost and full-scale. Investigating green and eco-friendly PhACs with advantages, e.g., low persistence, no bioaccumulation, less or non-toxicity, and environmentally friendly, is also necessary. © 2024 Elsevier Ltd

关键词： Microalgae

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FincGAN: A Gan Framework of Imbalanced Node Classification on Heterogeneous Graph Neural Network

FincGAN: A Gan Framework of Imbalanced Node Classification o...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hung Chun Hsu Ting-Le Lin Bo-Jun Wu Ming-Yi Hong Che Lin Chih-Yu Wang Graduate Program of Data Science National Taiwan University and Academia Sinica Taiwan Department of Accounting and Statistics National ChengChi University Taiwan Department of Risk Management and Insurance National ChengChi University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Research Center for Information Technology Innovation Academia Sinica Taiwan

Graph Neural Networks (GNNs) frequently face class imbalance issues, especially in heterogeneous graphs. Existing GNNs often assume balanced class sizes, which isn’t true in many cases. Applying them directly to imbalanced data can lead to sub-optimal performance. Traditional oversampling methods, while effective, risk overfitting and face difficulties in reintegrating synthetic samples into the original graph. In this study, we introduce Framework of Imbalanced Node Classification on heterogeneous graph neural network with GAN (FincGAN), a new framework that utilizes oversampling techniques to address class imbalance in heterogeneous graphs. Instead of duplicating existing samples, FincGAN employs a Generative Adversarial Network (GAN) to create synthetic samples and uses deep learning-based edge generators to connect them back to the original graph. Our evaluations on spam user detection in the Amazon and Yelp Review datasets show that FincGAN outperforms baseline models in all essential metrics, including F-score and AUC-PRC score, showing its effectiveness in addressing class imbalance.

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Enhancing Blockchain Scalability: Innovative Solutions for Optimized Performance in Decentralized Networks

Enhancing Blockchain Scalability: Innovative Solutions for O...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Akanksha Srivastav Sheenu Agarwal Arpit Jain Shikha Tayal Shalu Jain Khemraj Sharma Tula’s institute Dehradun U.K. India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun U.K. India Department of Computer Science & Engineering Koneru Lakshamaiah Education Foundation Vadessahwaram A.P. India Department of Computer Science & Engineering Tula’s Institute Dehradun Uttarakhand India Maharaja Agrasen Himalayan Garhwal University Pauri Garhwal Uttarakhand Department: Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi R.O.C

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

A substantial number of people are presently making use of decentralised cryptocurrencies that are built on blockchain technology. These crypto currencies have garnered a lot of interest over the course of the last few years and are currently being used by their users. Being the first use of blockchain technology, Bitcoin has been a resounding success, which drives further research and improvement in the sector concerned with blockchain technology. Bitcoin was the first usage of blockchain technology. Bitcoin, on the other hand, is susceptible to significant performance issues due to the fact that it has a high transaction latency and a limited throughput. The operations of the cryptocurrency are considerably impacted as a result of these concerns. As a result of the fact that other cryptocurrencies that rely on proof-of-work also carry over its deficiencies, there has been an increase in the number of concerns about the scalability of blockchain technology. The fact that this is the case makes scaling blockchain technology more challenging. All during the course of this investigation, an effort is made to analyse and classify the various scaling mechanisms that are now being used for blockchains. In addition to this, we are going to look at a variety of various approaches and present a list of possible solutions to the issue of scalability that the blockchain technology is now dealing.

关键词： Hands Computers Distributed ledger Scalability Bitcoin Throughput Proof of Work Fabrics Blockchains Informatics

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Assessing long-term morphological changes in the Vietnamese Mekong Delta 12th

Assessing long-term morphological changes in the Vietnamese ...

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12th International Conference on Fluvial Hydraulics, River Flow 2024

作者： Ahmed, M.F. Binh, D.V. Nguyen, B.Q. Kantoush, S. Sumi, T. Doan, N.L.P. Tuan, L.A. Nguyen, N.T. Vuong, N.D. Vu, H.T. Thang, H.N. Quyen, L.V. Water Resources Research Center Disaster Prevention Research Institute Kyoto University Kyoto Uji-shi Japan Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat Town Viet Nam University of Danang- University of Science and Technology Nguyen Luong Bang Danang Viet Nam Research Institute for Climate Change Can Tho University Ninh Kieu District Can Tho City Viet Nam Southern Institute for Water Resources Planning Ho Chi Minh City Viet Nam Faculty of Civil Engineering Technische Universität Dresden Germany Faculty of Fisheries University of Agriculture and Forestry Hue University Hue City Viet Nam

ISBN: (纸本)9781032757216

The Vietnamese Mekong Delta (VMD) has experienced significant morpho logical changes over decades, resulting in profound socioeconomic and environmental conse quences. This study investigated the VMD’s spatial and temporal morphological alterations from 1998 to 2020, utilizing four bathymetric datasets and remote sensing techniques. The ana lysis revealed that the average annual riverbed incision rate in the Tien and Hau Rivers dimin ished from-0.19 m/year (1998–2005) to-0.11 m/year (2005–2017) and further dropped to-0.10 m/year (2017–2020). The upper reaches of the Tien and Hau Rivers exhibited pronounce deepening over the three periods, whereas their lower reaches witnessed a converse trend. Add itionally, the study unveiled the average annual riverbank migration rate along the VMD, ran ging from 5 m/year to-5 m/year during the same examined periods. Notably, the dynamic processes of erosion and deposition intensified between 2017 and 2020. This research aims to provide crucial insights for refining sediment management strategies in the VMD. © 2025 The Author(s).

关键词： Miocene

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