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4th International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics, ICA-SYMP 2025

作者： Laosunthara, Ampan Thongthip, Ratchaneekorn Krutphong, Kodchakorn School of Environment and Society Institute of Science Tokyo Tokyo Japan Disaster Preparedness Mitigation and Management Department of Civil & Infrastructure Engineering Pathumthani Thailand Environmental Engineering and Disaster Management Program Mahidol University Kanchanaburi Thailand

ISBN: (纸本)9798331505400

This study compares the disaster management laws of Thailand and Japan. The research reveals significant differences in legislative approaches, reflecting each country's unique historical, and governance contexts. Japan's law demonstrates a more comprehensive approach to the disaster management cycle and stakeholder involvement, with integrated financial provisions. Thailand's law emphasizes organizational aspects. Both prioritize response measures but show potential gaps in addressing preparedness and mitigation phases. The study identifies areas for further investigation, including financial measures, and international cooperation approaches. This comparative analysis offers valuable insights into both countries' ongoing development of disaster management systems and highlights potential areas for mutual learning and improvement in disaster risk reduction strategies. Creating resilience in the society through the core of the government working and stakeholders' given authorities. © 2025 IEEE.

关键词： disaster prevention

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Navigating Legal Frameworks for National Resilience: A Comparative Analysis of Key disaster management Laws in Thailand and Japan

Navigating Legal Frameworks for National Resilience: A Compa...

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First International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)

作者： Ampan Laosunthara Ratchaneekorn Thongthip Kodchakorn Krutphong School of Environment and Society Institute of Science Tokyo Tokyo Japan Department of Civil & Infrastructure Engineering Disaster Preparedness Mitigation and Management School of Engineering and Technology Asian Institute of Technology (AIT) Pathumthani Thailand Environmental Engineering and Disaster Management Program Mahidol University Kanchanaburi Thailand

ISBN: (数字)9798331505400

ISBN: (纸本)9798331505417

关键词： Phase measurement Law Prevention and mitigation disasters Area measurement Legislation Frequency measurement Stakeholders Robots Resilience

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Strength and Permeability of Thermally Consolidated Soft Ground

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Geotechnical and Geological engineering 2025年第5期43卷 1-24页

作者： Srisakul, Watchara Chub-uppakarn, Tanan Chompoorat, Thanakorn Department of Engineering Technology Faculty of Engineering and Technology Rajamangala University of Technology Srivijaya Trang92150 Thailand Department of Civil and Environmental Engineering Faculty of Engineering Prince of Songkla University Songkhla90110 Thailand Southern Natural Disaster Research Center Prince of Songkla University Songkhla90110 Thailand Civil Engineering Program School of Engineering University of Phayao Phayao56000 Thailand

This study investigates the effects of thermal treatment on the mechanical behavior of highly compressible Pak Phanang clay, a soft soil with low strength that typically requires advanced ground improvement methods. Heating is considered a promising technique for enhancing foundation stability, particularly for critical infrastructure. The research focuses on the thermo-mechanical behavior of the clay, emphasizing consolidation and solidification processes that influence load-bearing capacity. Isotropically consolidated undrained triaxial tests were conducted at temperatures of 30 °C, 40 °C, 50 °C, and 60 °C with over-consolidation ratios (OCR) of 1, 2, 4, and 8. The results showed that increasing temperature significantly enhanced both peak deviator stress (qu) and the secant Young’s modulus (E50), with a strong linear correlation: E50=108.70×qu. Dry density increased and organic matter content slightly decreased under thermal treatment, particularly in normally consolidated clay. Excess pore water pressure (EPWP) increased linearly with temperature across all OCR values. Consolidation volume change also increased with temperature but decreased as OCR rose. The coefficient of consolidation (Cv) improved with temperature, leading to faster consolidation, especially in normally consolidated specimens. The coefficient of permeability (k) increased with temperature but declined with higher OCR, with k rising by 14.6%–24.2% from 30 °C to 60 °C in normally consolidated samples. Predictive models for qu and k based on temperature and OCR demonstrated high accuracy. Overall, the findings provide a reliable understanding of the thermal–mechanical response of this clay type, supporting its application in temperature-assisted ground improvement. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Shear strength

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Optimizing waste pre-collection model in Indonesian communities: comparing drop-off and door-to-door models through social cost–benefit analysis

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Journal of Material Cycles and Waste management 2025年 1-17页

作者： Miftahadi, Machmuddin Fitra Hibino, Kohei Rachman, Indriyani Matsumoto, Toru Graduate Program in Environmental System Graduate School of Environmental Engineering The University of Kitakyushu Kitakyushu808-0135 Japan Kitakyushu Urban Centre Institute for Global Environmental Strategies Kitakyushu805-0062 Japan Department of Natural Science Education School of Postgraduate Studies Universitas Pakuan Kota Bogor16143 Indonesia Research Center for Urban Energy Management Institute of Environmental Science and Technology The University of Kitakyushu Kitakyushu808-0135 Japan

Indonesia lacks an established waste pre-collection system resulting 90% waste ending up in open-dumping site. This study identifies a 35-m radius per drop-off points as the most optimal model. The City of South Tangerang, on 21 residential areas with a population of 63,157, being examine. Utilizing ArcGIS Pro and Python scripting, 12 scenarios were developed, model drop-off radii of 15–45 m and household limits of 4–32 per drop-off point, including combined models. Spatial clustering KD-Tree algorithm and Proximity-based Routing were employed to determine collection placements and walking distances. Heatmap and ANOVA tests evaluated conformity with residential characteristics. Model then organized into eight frequency schemes, utilizing motorcart and handcart systems with 4-day and 2-day pickup schedules for waste bank and in-house compost programs. This optimized model reduces collection time by up to 81% and costs by 50% compared to traditional door-to-door systems, achieving cost reductions of $30–$38 USD per ton and lowering CO₂ emissions. The discussion covers opportunity costs and occupational risk. This approach supports Indonesia’s waste reduction targets and offers policy alignment for urban waste management. © The Author(s), under exclusive licence to Springer Nature Japan KK, part of Springer Nature 2025.

关键词： Python

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A modeling framework for assessing the future changes in the occurrence of extreme rain-induced landslides

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Gondwana Research 2025年 143卷 52-63页

作者： Zhang, Xinlong Lin, Qigen Lok, Manhoi Huang, Taosheng Yu, Xuan Wang, Weiping Shen, Ping State Key Laboratory of Internet of Things for Smart City and Department of Civil and Environmental Engineering University of Macau Macao SAR China Institute for Disaster Risk Management School of Geographical Sciences Nanjing University of Information Science & Technology Nanjing China Department of Civil and Environmental Engineering University of Macau Macao SAR China Center for Water Resources and Environment School of Civil Engineering Sun Yat-sen University Guangzhou China School of National Safety and Emergency Management Beijing Normal University Zhuhai China Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance Beijing Normal University Zhuhai China

Landslides triggered by extreme rainfall pose a serious threat to lives and livelihoods under climate change. However, the influence of climate change on the frequency and intensity of extreme rainfall and the resulting landslide hazard remains insufficiently investigated. Here we develop a novel framework to assess how future changes in extreme rainfall affect landslide occurrence, using a comprehensive dataset of landslide events in Guangdong province, China. We apply the XGBoost machine learning algorithm with a correction by feature interaction constraints to model landslide hazards based on various predisposing and triggering factors. We use a new extreme rainfall correction method to account for the global climate model-projected changes in rainfall patterns under different emission scenarios, based on which we perform a multi-model ensemble analysis to reduce the uncertainty of climate projections. We find that regions with high landslide probability are strongly associated with intense rainfall events, especially in steep and erodible river valleys. Our projections show that under a high-emission scenario, extreme rainfall events and landslide hazards will increase substantially in Guangdong, highlighting the urgency of adaptation of climate change and risk management. Our framework provides a valuable tool for understanding the interactions between climate change, extreme rainfall, and landslide occurrence, and for developing effective mitigation strategies. © 2025 International Association for Gondwana Research

关键词： Climate change Extreme rainfall Machine Learning Rain-induced landslides

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Effects of Nitrogen Fertilizer Types on the Uptake and Translocation of PFAS and Metabolomic Activities of Hydroponically Cultivated Lettuce (Lactuca sativa)

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Journal of Agricultural and Food Chemistry 2025年第18期73卷 10907-10913页

作者： Adu, Olatunbosun Duza, Syeda Sharmin Sharma, Virender K. Ma, Xingmao Department of Water Management and Hydrological Science Texas A&M University College StationTX77843 United States Program for the Environment and Sustainability Department of Environmental and Occupational Health School of Public Health Texas A&M University 212 Adriance Lab Rd. 1266 TAMU College StationTX77843 United States Department of Chemical Environmental and Materials Engineering University of Miami Coral GablesFL33146 United States Department of Civil and Environmental Engineering Texas A&M University College StationTX77843 United States

Increasing evidence is showing that per- and polyfluoroalkyl substance (PFAS) replacing compounds are not as safe as they were assumed. This study investigated the plant uptake of two most prevalent PFAS, perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic (PFOS) and their replacing compounds, hexafluoropropylene oxide dimer acid (HFPO-DA or GenX) and 6:2 chlorinated polyfluoroalkyl ether sulfonates (Cl-PFESAs) (6:2 Cl-PFAES) by hydroponically grown lettuce in the presence of different nitrogen fertilizers including ammonium sulfate ((NH4)2SO4), potassium nitrate (KNO3), and urea in a growth chamber. Interestingly, (NH4)2SO4 significantly increased GenX uptake in lettuce shoots by ∼108% and KNO3 increased the uptake of PFOS and 6:2 Cl-PFAES by 267% and 395%, respectively, suggesting that the nitrogen fertilizer type has a marked impact on the plant uptake of PFAS and that this impact was PFAS-dependent. Our results also showed that (NH4)2SO4 generally resulted in higher PFAS root to shoot transfer than the other two types of nitrogen fertilizers. Metabolomic analysis revealed that amino acids, nucleotides, and antioxidants are the major metabolites that were either significantly increased or decreased in the lettuce shoots. These results showed that nitrogen fertilization management can have a significant impact on PFAS plant uptake and transport, and the impact depends on the types of nitrogen fertilizer and PFAS compounds. © 2025 The Authors. Published by American Chemical Society.

关键词： Urea fertilizers

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Current advances in bioethanol synthesis from lignocellulosic biomass: sustainable methods, technological developments, and challenges

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Journal of Umm Al-Qura University for Applied Sciences 2025年 1-18页

作者： Novia, Novia Melwita, Elda Jannah, Asyeni Miftahul Selpiana, Selpiana Yandriani, Yandriani Afrah, Bazlina Dawami Rendana, Muhammad Department of Chemical Engineering Faculty of Engineering Universitas Sriwijaya Jl. Raya Palembang-Prabumulih KM 32 Inderalaya Sumatera Selatan Ogan Ilir 30662 Indonesia Master Program of Environmental Management Graduate School Universitas Sriwijaya Jl. Padang Selasa 524 Bukit Besar Sumatera Selatan Palembang 30139 Indonesia Doctoral Program Faculty of Engineering Universitas Sriwijaya South Sumatra Palembang 30139 Indonesia

Bioethanol production from lignocellulosic biomass has become an economical and environmentally friendly substitute to current petroleum-based fuels. This is due to its ability to decrease carbon dioxide emissions and make use of plentiful natural resources. Current advances in this area concentrate on improving the effectiveness and expandability of the conversion procedures by using inventive pretreatment approaches, enhanced enzyme compositions, and refined fermentation technologies. Consolidated bioprocessing (CBP) and utilizing genetically modified microbes have expedited the decomposition of intricate biomass complexes and enhanced overall productivity. Furthermore, process intensification developments, such as the adoption of hybrid reactors and continuous production systems, have considerably decreased production expenses and energy usage. Nevertheless, there are still obstacles to overcome, including the raw materials inconsistency, the demand for efficient recovery and purifying techniques, and the financial viability of extensive processes. This study examines the latest developments in bioethanol production from lignocellulosic biomass. It focuses on ecological approaches, technical advancements, and the main obstacles that need to be overcome to exploit its promise as a biofuel fully. This review primarily focused on outcomes documented in the last five years from 2019 to 2024. The first segment of this work focuses on the second-generation bioethanol production process, which includes: the properties and composition of lignocellulosic biomass, pretreatment, enzymatic saccharification, and fermentation. The subsequent portion of this paper examines a techno-economic analysis, the obstacles and the prospective technology outlook. It finishes by discussing findings from research fields that haven't been investigated yet, besides the obstacles faced in bioethanol manufacturing methods. © The Author(s) 2025.

关键词： Bioethanol Enzymatic hydrolysis Fermentation Lignocellulosic biomass Pretreatment

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Statistical trend characteristics of rainfall over Kerala, India evaluated through analysing modern era retrospective analysis for research and applications (MERRA-2) reanalysis data

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Bulletin of Atmospheric Science and Technology 2025年第1期6卷 1-38页

作者： Modon Valappil, Ninu Krishnan de Oliveira Júnior, José Francisco Mendes, David Jamjareegulgarn, Punyawi Hamza, Vijith Environmental Technology Division School of Industrial Technology Universiti Sains Malaysia Pulau Pinang 11800 Malaysia Laboratory of Applied Meteorology and Environment (LAMMA) Institute of Atmospheric Sciences (ICAT) Federal University of Alagoas (UFAL) LourivalMeloMota avenue S/N Alagoas Tabuleiro dos Martins Maceió CEP: 57072-970 Brazil Post-Graduate Program in Aerospace Engineering – PPGEA Federal University of Rio Grande do Norte – UFRN Campus Universitário Lagoa Nova RN Natal Brazil Prince of Chumphon Campus King Mongkut’s Institute of Technology Ladkrabang Chumphon 86160 Thailand Kerala State Disaster Management Authority Kerala Thiruvananthapuram 695033 India

Statistical trends of rainfall (annual and seasonal rainfalls) in Kerala, India were characterised using the 44-years (1980–2023) data of Modern-Era Retrospective Analysis for Research and Applications (MERRA) version 2. Monthly rainfall data were collected from the selected fifty locations which represent the state as a whole, and the collected data were then categorised into annual as well as seasonal (winter, summer, monsoon and post-monsoon) datasets based on the classification proposed by Indian Meteorological Organisation (IMD). Lag-1 autocorrelation, modified Mann Kendall (mMK), Pettitt test and Theil-Sen’s slope methods were used to determine the statistical characteristics of rainfalls in Kerala. Mean rainfalls were 3124 mm, 66 mm, 527 mm, 1667 mm and 862 mm, respectively, for annual, winter, summer, monsoon and post-monsoon periods. mMK based statistical trend analysis revealed an overall decreasing trend characteristics in annual (-0.54 mm.y⁻¹), monsoon (-1.20 mm.y⁻¹), and post-monsoon (-0.93 mm.y⁻¹) seasons whereas winter and summer rainfalls showed an increasing trend (0.67 mm.y⁻¹ and 3.40 mm.y⁻¹, respectively) for the state as a single unit. Pettitt test indicated four dominant periods of change in rainfall characteristics in the study area that spanned over the decades of 1980, 1990, 2000 and 2010, in which major changes in annual and seasonal rainfalls were occurred during 1990’s, 2000’s and 2010’s. Theil-Sen’s slope-based estimation of rate of change in rainfall showed an average variation of -4.33 mm.y⁻¹, 0.17 mm.y⁻¹, 6.27 mm.y⁻¹, -6.54 mm.y⁻¹ and − 3.28 mm.y⁻¹ for annual, winter, summer, monsoon and post-monsoon seasons, respectively. Though the winter and summer rainfalls showed an increase in its rate during the period of analysis, annual rainfall showed an overall reduction in the amount of rainfall received in the state. The study ulti

关键词： MERRA-2 Modified Mann Kendall Period of change Rainfall variation Spatial statistics

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Using electric vehicles to power houses or travel during blackouts triggered by natural hazards: A choice experiment in Japan

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Energy and Buildings 2025年 342卷

作者： Yamazaki, Shota Kotani, Hitomu Nakano, Kazuyoshi Matsushima, Kakuya Department of Urban Management of Engineering Kyoto University Kyoto Japan Department of Civil and Environmental Engineering School of Environment and Society Institute of Science Tokyo Tokyo Japan Socio-Economic Research Center Central Research Institute of Electric Power Industry Tokyo Japan Disaster Prevention Research Institute Kyoto University Kyoto Japan

Electric vehicles (EVs) can power houses during large-scale blackouts caused by natural hazards. However, during natural hazard-related disasters, EVs are essential for transportation to obtain supplies and for other purposes. This study focuses on the conflict between powering houses with EVs and using them for transportation during natural hazard-triggered blackouts. We assessed the conditions under which the choice between using EVs for powering houses or traveling varied. In particular, we conducted a choice experiment with EV-owning households in Japan, using a questionnaire based on the stated preference approach. The respondents were presented with a hypothetical scenario immediately after a blackout caused by an earthquake. They were asked whether, in the case of a blackout, they would prefer to use their EVs for traveling or powering their houses while considering the season, time of the day, weather, and EV battery level. We considered two travel destinations: 1) shopping centers (to obtain supplies) and 2) public charging stations (to recharge EVs). Based on responses of 300 individuals (150 individuals for each destination), we used discrete choice models to identify the blackout conditions and household characteristics that could influence the choice. Overall, individuals preferred using EVs for powering houses rather than for traveling to each destination;however, this tendency varied by conditions and characteristics (e.g., stronger on rainy days, but weaker in spring or fall, or among households with people requiring care). Based on the results, we suggested measures to enable the use of power at home while achieving the purpose of traveling. © 2025 The Author(s)

关键词： Travel time

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Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

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Journal of Computing in Civil engineering 2025年第4期39卷

作者： Luo, Linchao Cheng, Chih-Shen Mobley, William Novoselac, Atila Lieberknecht, Katherine Leite, Fernanda Civil Engineering and Project Management Program Dept. of Civil Architectural Environmental Engineering Univ. of Texas at Austin AustinTX78712 United States Texas Advanced Computing Center Univ. of Texas at Austin AustinTX78712 United States Robert and Francis Stark Centennial Fellowship in Engineering Dept. of Civil Architectural Environmental Engineering Univ. of Texas at Austin AustinTX78712 United States School of Architecture Univ. of Texas at Austin AustinTX78712 United States Cockrell School of Engineering Joe J. King in Civil Architectural Environmental Engineering Univ. of Texas at Austin AustinTX78712 United States

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S-BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-D

关键词： Binary codes

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