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26 pages, 1398 KiB  
Article
Research on Consumer Behavior-Driven Collaborative Mechanism of Green Supply Chain and Its Performance Optimization
by Wenbin Cao and Yuansiying Ge
Sustainability 2025, 17(17), 7601; https://doi.org/10.3390/su17177601 - 22 Aug 2025
Abstract
As a crucial vehicle for advancing the transition to a green low-carbon economy, the green supply chain plays a pivotal role in alleviating pollution pressures and facilitating the green transformation of products. Existing studies mainly focus on static optimization and cost coordination in [...] Read more.
As a crucial vehicle for advancing the transition to a green low-carbon economy, the green supply chain plays a pivotal role in alleviating pollution pressures and facilitating the green transformation of products. Existing studies mainly focus on static optimization and cost coordination in green supply chains, with limited attention to the dynamic impact of consumer behavior on green production and channel coordination. Based on consumer green preferences and the evolution of reference prices, we developed a differential game model for a two-tier green supply chain composed of a manufacturer and a retailer. The model incorporates green goodwill and consumer memory variables to capture the dynamic interaction among product greenness, sales effort, and consumer perception. By comparing the dynamic optimal response paths under integrated and non-integrated strategies, the study analyzes how reference price effects and goodwill accumulation influence decision-making and system performance. The results show that the stable reference price of green products is significantly higher than the actual selling price. When consumer environmental awareness is strong, cooperative strategies can markedly improve both green performance and supply chain profits, offering potential for Pareto improvement. This research enhances behavior-oriented modeling in green supply chains and provides theoretical and empirical support for designing collaboration mechanisms in green product promotion. Full article
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26 pages, 1829 KiB  
Article
Green and Efficient Technology Investment Strategies for a Contract Farming Supply Chain Under the CVaR Criterion
by Yuying Li and Wenbin Cao
Sustainability 2025, 17(17), 7600; https://doi.org/10.3390/su17177600 - 22 Aug 2025
Abstract
Synergizing soil quality improvement and greening for increased yields are essential to ensuring grain security and developing sustainable agriculture, which has become a key issue in agricultural cultivation. This study considers a contract farming supply chain composed of a risk-averse farmer and a [...] Read more.
Synergizing soil quality improvement and greening for increased yields are essential to ensuring grain security and developing sustainable agriculture, which has become a key issue in agricultural cultivation. This study considers a contract farming supply chain composed of a risk-averse farmer and a risk-neutral firm making green and efficient technology (GET) investments, which refers to the use of technology monitoring to achieve fertilizer reduction and yield increases with yield uncertainty. Based on the CvaR (Conditional value at Risk) criterion, the Stackelberg game method is applied to construct a two-level supply chain model and analyze different cooperation mechanisms. The results show that when the wholesale price is moderate, both sides will choose the cooperative mechanism of cost sharing to invest in technology; the uncertainty of yield and the degree of risk aversion have a negative impact on the agricultural inputs and GET investment, and when yield fluctuates greatly, the farmer invests in GET to make higher utility but lowers profits for the firm and supply chain. This study provides a theoretical basis for GET investment decisions in agricultural supply chains under yield uncertainty and has important practical value for promoting sustainable agricultural development and optimizing supply chain cooperation mechanisms. Full article
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24 pages, 3252 KiB  
Article
Research on Composite Strengthening Methods for External Walls of Box-Shaped Bridge Piers Subjected to Peripheral Ice–Water Pressure
by Xi Li, Yiwei Yu, Jun Ma and Hang Sun
Buildings 2025, 15(17), 2993; https://doi.org/10.3390/buildings15172993 - 22 Aug 2025
Abstract
To address concrete cracking in submerged box-shaped hollow thin-walled piers under static ice and hydrostatic pressure, this study proposes a composite strengthening method employing externally bonded steel plates coupled with concrete infill blocks. Based on mechanical theoretical derivation, the strengthened structure is simplified [...] Read more.
To address concrete cracking in submerged box-shaped hollow thin-walled piers under static ice and hydrostatic pressure, this study proposes a composite strengthening method employing externally bonded steel plates coupled with concrete infill blocks. Based on mechanical theoretical derivation, the strengthened structure is simplified as a cooperative system comprising compression–truss and suspended-cable mechanisms. Key design parameters—including steel plate span, thickness, infill block height, and plate corner configuration—are optimized using a genetic algorithm. The optimization objective minimizes strengthening cost, subject to constraints of concrete crack resistance, steel plate strength, and deformation control, ultimately determining the numerically optimal composite strengthening solution. Validation through planar finite element models demonstrates that: (1) the proposed system effectively suppresses cracking in the original structure; (2) peak stresses in the steel plates remain below the yield strength of Q345 steel; and (3) the theoretical design is reasonable and effective, which can solve the cracking problem of the wading-tank hollow thin-walled pier under the action of surrounding load. Full article
(This article belongs to the Section Building Structures)
22 pages, 2971 KiB  
Article
Cooperative Schemes for Joint Latency and Energy Consumption Minimization in UAV-MEC Networks
by Ming Cheng, Saifei He, Yijin Pan, Min Lin and Wei-Ping Zhu
Sensors 2025, 25(17), 5234; https://doi.org/10.3390/s25175234 - 22 Aug 2025
Abstract
The Internet of Things (IoT) has promoted emerging applications that require massive device collaboration, heavy computation, and stringent latency. Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) systems can provide flexible services for user devices (UDs) with wide coverage. The optimization of both [...] Read more.
The Internet of Things (IoT) has promoted emerging applications that require massive device collaboration, heavy computation, and stringent latency. Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) systems can provide flexible services for user devices (UDs) with wide coverage. The optimization of both latency and energy consumption remains a critical yet challenging task due to the inherent trade-off between them. Joint association, offloading, and computing resource allocation are essential to achieving satisfying system performance. However, these processes are difficult due to the highly dynamic environment and the exponentially increasing complexity of large-scale networks. To address these challenges, we introduce a carefully designed cost function to balance the latency and the energy consumption, formulate the joint problem into a partially observable Markov decision process, and propose two multi-agent deep-reinforcement-learning-based schemes to tackle the long-term problem. Specifically, the multi-agent proximal policy optimization (MAPPO)-based scheme uses centralized learning and decentralized execution, while the closed-form enhanced multi-armed bandit (CF-MAB)-based scheme decouples association from offloading and computing resource allocation. In both schemes, UDs act as independent agents that learn from environmental interactions and historic decisions, make decision to maximize its individual reward function, and achieve implicit collaboration through the reward mechanism. The numerical results validate the effectiveness and show the superiority of our proposed schemes. The MAPPO-based scheme enables collaborative agent decisions for high performance in complex dynamic environments, while the CF-MAB-based scheme supports independent rapid response decisions. Full article
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17 pages, 1153 KiB  
Article
Real-World Systemic Treatment Patterns, Survival Outcomes, and Prognostic Factors in Advanced Hepatocellular Carcinoma: A 15-Year Experience from a Low-Resource Setting
by Jirapat Wonglhow, Chirawadee Sathitruangsak, Patrapim Sunpaweravong, Panu Wetwittayakhlang and Arunee Dechaphunkul
Cancers 2025, 17(17), 2729; https://doi.org/10.3390/cancers17172729 - 22 Aug 2025
Abstract
Background: The treatment landscape for advanced hepatocellular carcinoma (HCC) has evolved significantly recently; however, access to novel agents remains limited because of high costs. This study aimed to evaluate the systemic treatment patterns and survival outcomes for advanced HCC across different systemic treatment [...] Read more.
Background: The treatment landscape for advanced hepatocellular carcinoma (HCC) has evolved significantly recently; however, access to novel agents remains limited because of high costs. This study aimed to evaluate the systemic treatment patterns and survival outcomes for advanced HCC across different systemic treatment sequences under real-world resource constraints. Methods: This retrospective study was conducted at a tertiary center in Southern Thailand. The medical records of patients (n = 330) with advanced HCC treated with systemic therapy between 2010 and 2024 were reviewed. Outcomes included overall survival (OS), progression-free survival (PFS), and objective response rate (ORR). Prognostic factors for OS were investigated. Results: First-line therapies included tyrosine kinase inhibitor (TKI; 69.7%), chemotherapy (23.3%), immunotherapy (IO)/targeted therapy (3.6%), dual IO (1.8%), and IO monotherapy (1.5%). The median OS, PFS, and ORR for each cohort were 7.2, 5.2, 10.9, 8.5, and 8.6 months; 3.94, 3.22, 3.48, 6.19, and 2.69 months; and 9.6%, 10.4%, 16.7%, 0%, and 20.0%, respectively. OS improved with increasing lines of therapy (4.5, 12.2, 19.4, and 40.7 months for one to four lines, respectively). Portal vein tumor thrombus, ascites, elevated bilirubin level, high alpha-fetoprotein level, and poor Eastern Cooperative Oncology Group performance status were associated with poor prognosis; multiple treatment lines and overweight status were associated with improved OS. Conclusions: In this large real-world cohort, TKIs remained the mainstay effective treatment option because of limited access to IO-based regimens. Sequential systemic therapy significantly improved survival, emphasizing the importance of preserving treatment eligibility and multidisciplinary team involvement. Chemotherapy could be considered a viable option in resource-limited settings. Full article
(This article belongs to the Special Issue Hepatocellular Carcinoma Progression and Metastasis)
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17 pages, 3907 KiB  
Article
Motion Intention Prediction for Lumbar Exoskeletons Based on Attention-Enhanced sEMG Inference
by Mingming Wang, Linsen Xu, Zhihuan Wang, Qi Zhu and Tao Wu
Biomimetics 2025, 10(9), 556; https://doi.org/10.3390/biomimetics10090556 - 22 Aug 2025
Abstract
Exoskeleton robots function as augmentation systems that establish mechanical couplings with the human body, substantially enhancing the wearer’s biomechanical capabilities through assistive torques. We introduce a lumbar spine-assisted exoskeleton design based on Variable-Stiffness Pneumatic Artificial Muscles (VSPAM) and develop a dynamic adaptation mechanism [...] Read more.
Exoskeleton robots function as augmentation systems that establish mechanical couplings with the human body, substantially enhancing the wearer’s biomechanical capabilities through assistive torques. We introduce a lumbar spine-assisted exoskeleton design based on Variable-Stiffness Pneumatic Artificial Muscles (VSPAM) and develop a dynamic adaptation mechanism bridging the pneumatic drive module with human kinematic intent to facilitate human–robot cooperative control. For kinematic intent resolution, we propose a multimodal fusion architecture integrating the VGG16 convolutional network with Long Short-Term Memory (LSTM) networks. By incorporating self-attention mechanisms, we construct a fine-grained relational inference module that leverages multi-head attention weight matrices to capture global spatio-temporal feature dependencies, overcoming local feature constraints inherent in traditional algorithms. We further employ cross-attention mechanisms to achieve deep fusion of visual and kinematic features, establishing aligned intermodal correspondence to mitigate unimodal perception limitations. Experimental validation demonstrates 96.1% ± 1.2% motion classification accuracy, offering a novel technical solution for rehabilitation robotics and industrial assistance. Full article
(This article belongs to the Special Issue Advanced Service Robots: Exoskeleton Robots 2025)
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9 pages, 662 KiB  
Article
Regional Medical Collaboration May Lead to Early Detection of Interstitial Lung Disease
by Yoshiaki Zaizen, Masaki Tominaga, Goushi Matama, Yutaka Ichikawa, Rumi Gohara, Junichiro Hiyama, Souichiro Ide, Tomoko Kamimura, Masaharu Kinoshita, Yasuhiko Kitasato, Takeharu Koga, Yousuke Miyagawa, Hideo Ogino, Rumi Sato, Yoshiko Sueyasu, Kazuhiko Yamada and Tomoaki Hoshino
J. Clin. Med. 2025, 14(17), 5923; https://doi.org/10.3390/jcm14175923 - 22 Aug 2025
Abstract
Background: Establishing a highly accurate regional medical collaboration (RMC) system for interstitial lung disease (ILD) may facilitate early disease detection, improve patient satisfaction, and enhance advanced-stage care. Methods: We investigated whether the lung conditions in patients cared for by our RMC [...] Read more.
Background: Establishing a highly accurate regional medical collaboration (RMC) system for interstitial lung disease (ILD) may facilitate early disease detection, improve patient satisfaction, and enhance advanced-stage care. Methods: We investigated whether the lung conditions in patients cared for by our RMC system for ILD were detected earlier than those with usual care. Additionally, we investigated patients’ preferences regarding its use. Result: The time from respiratory symptoms onset to hospital referral did not differ significantly between patients cared for by the system and those with usual care. However, the number of patients referred to our hospital for suspected ILD before the onset of symptoms was significantly higher from the participating institutions than from other institutions (44.1% vs. 24.6%, p = 0.025). Additionally, 66.0% of patients preferred the medical care with the system. Conclusions: Establishing an RMC system for ILD may lead to earlier disease detection and contribute to improvement in medical care delivery to patients. Full article
(This article belongs to the Section Respiratory Medicine)
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23 pages, 909 KiB  
Article
Enhancing Marine Environmental Protection Enforcement in Taiwan: Legal and Policy Reforms in the Context of International Conventions
by Shu-Hong Lin and Yu-Cheng Wang
Laws 2025, 14(5), 60; https://doi.org/10.3390/laws14050060 - 22 Aug 2025
Abstract
The Marine Pollution Control Act (MPCA) in Taiwan aims to align with international conventions such as the United Nations Convention on the Law of the Sea (UNCLOS), the International Convention for the Prevention of Pollution from Ships (MARPOL), the International Convention on Civil [...] Read more.
The Marine Pollution Control Act (MPCA) in Taiwan aims to align with international conventions such as the United Nations Convention on the Law of the Sea (UNCLOS), the International Convention for the Prevention of Pollution from Ships (MARPOL), the International Convention on Civil Liability for Oil Pollution Damage (CLC), the International Oil Pollution Compensation Funds (FUNDs), and the International Convention for the Control and Management of Ships’ Ballast Water and Sediments (BWM). However, Taiwan’s particular international status prevents formal participation in these treaties. This study evaluates Taiwan’s legal and institutional frameworks on ship emission control, pollution liability and compensation, and interagency coordination, identifying key gaps compared with global standards. By analyzing Japan’s and South Korea’s best practices in port management, cross-border pollution prevention, and vessel monitoring, this study proposes legal and policy reforms that are tailored to Taiwan. Recommendations include strengthening liability mechanisms, enhancing interagency collaboration, monitoring vessels, and fostering regional cooperation. Our findings suggest that these reforms will improve Taiwan’s marine environmental governance and contribute to regional and global ocean sustainability. Full article
(This article belongs to the Section Environmental Law Issues)
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26 pages, 6324 KiB  
Article
A Multi-UAV Distributed Collaborative Search Algorithm Based on Maximum Entropy Mechanism
by Siyuan Cui, Hao Li, Xiangyu Fan, Lei Ni and Jiahang Hou
Drones 2025, 9(8), 592; https://doi.org/10.3390/drones9080592 - 21 Aug 2025
Abstract
This paper addresses the core issues of slow coverage rate growth and high repeated detection rates in multi-UAV cooperative search operations within unknown areas. A distributed cooperative search algorithm based on the maximum entropy mechanism is proposed to resolve these challenges. It innovatively [...] Read more.
This paper addresses the core issues of slow coverage rate growth and high repeated detection rates in multi-UAV cooperative search operations within unknown areas. A distributed cooperative search algorithm based on the maximum entropy mechanism is proposed to resolve these challenges. It innovatively integrates the entropy gradient decision framework with DMPC-OODA (Distributed Model Predictive Control-Observe, Orient, Decide, Act) rolling optimization: environmental uncertainty is quantified through an exponential decay entropy model to drive UAVs to migrate toward high-entropy regions; element-wise product operations are employed to efficiently update environmental maps; and a dynamic weight function is designed to adaptively adjust the weights of coverage gain and entropy gain, thereby balancing “rapid coverage” and “accurate exploration”. Through multiple independent repeated experiments, the algorithm demonstrates significant improvements in coverage efficiency—by 6.95%, 12.22%, and 59.49%, respectively—compared with the Search Intent Interaction (SII) mode, non-entropy mode, and random mode, which effectively enhances resource utilization. Full article
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34 pages, 1278 KiB  
Article
The Coordination of Monetary and Local Government Fiscal Policies and Local Fiscal Sustainability in China
by Hanlin Xia and Lin Zhang
Sustainability 2025, 17(16), 7555; https://doi.org/10.3390/su17167555 - 21 Aug 2025
Abstract
The growing importance of local governments, alongside the swift development of their bond markets, provides a novel framework for examining the coordination of monetary and local government fiscal policies in China. This investigation contributes a new viewpoint on local fiscal sustainability by emphasizing [...] Read more.
The growing importance of local governments, alongside the swift development of their bond markets, provides a novel framework for examining the coordination of monetary and local government fiscal policies in China. This investigation contributes a new viewpoint on local fiscal sustainability by emphasizing the role of policy coordination. Empirical evidence derived from regression models and proxy structural vector autoregression (Proxy SVAR) analyses conducted in this study substantiates the presence of coordination between monetary and local government fiscal policies in China; nevertheless, such coordination may pose risks to long-term local fiscal sustainability. Drawing on empirical data, this study utilizes a dynamic stochastic general equilibrium (DSGE) model that integrates key features characteristic of the Chinese economy to investigate the coordination of monetary and local government fiscal policies, as well as the effects of this coordination on local fiscal sustainability. The results derived from the baseline model indicate that although monetary and local fiscal policies in China are coordinated, such coordination facilitates the accumulation of local government debt, which ultimately compromises long-term local fiscal sustainability. Furthermore, the baseline model is extended and examined through multiple analytical approaches. When local government competition is introduced, monetary policy and local government fiscal policy become disconnected, which undermines local fiscal sustainability. Conversely, when local government cooperation is introduced, monetary policy and local government fiscal policy become more coordinated, which in turn improves local fiscal sustainability. Moreover, a higher steady-state debt level among local governments promotes greater coordination between monetary and fiscal policies, resulting in stronger fiscal sustainability. However, the imposition of debt constraints on local governments diminishes this coordination and adversely affects local fiscal sustainability. Additionally, in the absence of local financial friction, monetary and local fiscal policies exhibit increased coordination; however, this may potentially undermine long-term local fiscal sustainability. It is therefore imperative for the central government of China to prioritize the harmonization of monetary and local fiscal policies and to consider their implications for local fiscal sustainability, while simultaneously encouraging intergovernmental cooperation and the establishment of an integrated large-scale market. Full article
(This article belongs to the Special Issue Regional Economics, Policies and Sustainable Development)
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31 pages, 1463 KiB  
Review
Nuclear Energy as a Strategic Resource: A Historical and Technological Review
by Héctor Quiroga-Barriga, Fabricio Nápoles-Rivera, César Ramírez-Márquez and José María Ponce-Ortega
Processes 2025, 13(8), 2654; https://doi.org/10.3390/pr13082654 - 21 Aug 2025
Abstract
Nuclear energy has undergone a significant transformation over the past decades, driven by technological innovation, shifting safety priorities, and the urgent need to mitigate climate change. This study presents a comprehensive review of the historical evolution, current developments, and future prospects of nuclear [...] Read more.
Nuclear energy has undergone a significant transformation over the past decades, driven by technological innovation, shifting safety priorities, and the urgent need to mitigate climate change. This study presents a comprehensive review of the historical evolution, current developments, and future prospects of nuclear energy as a strategic low-carbon resource. A structured literature review was conducted following Kitchenham’s methodology, covering peer-reviewed articles and institutional reports from 2000 to 2025. Key advances examined include the deployment of Small Modular Reactors, Generation IV technologies, and fusion systems, along with progress in safety protocols, waste management, and regulatory frameworks. Comparative environmental data confirm nuclear power’s low life-cycle CO2 emissions and high energy density relative to other generation sources. However, major challenges remain, including high capital costs, long construction times, complex waste disposal, and issues of public acceptance. The analysis underscores that nuclear energy, while not a standalone solution, is a critical component of a diversified and sustainable energy mix. Its successful integration will depend on adaptive governance, international cooperation, and enhanced social engagement. Overall, the findings support the role of nuclear energy in achieving global decarbonization targets, provided that safety, equity, and environmental responsibility are upheld. Full article
(This article belongs to the Section Energy Systems)
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16 pages, 9200 KiB  
Article
Construction of Donor–Acceptor Heterojunctions via Microphase Separation of Discotic Liquid Crystals with Ambipolar Transport
by Heng Liu, Mingsi Xie, Yaohong Liu, Gaojun Jia, Ruijuan Liao, Ao Zhang, Yi Fang, Xiaoli Song, Chunxiu Zhang and Haifeng Yu
Molecules 2025, 30(16), 3441; https://doi.org/10.3390/molecules30163441 - 21 Aug 2025
Abstract
A series of novel discotic liquid crystalline donor–acceptor hybrid heterojunctions were prepared by blending the triphenylene derivative (T5E36) as donor and perylene tetracarboxylic esters as acceptor. Mesophases of blends were characterized by using polarized optical microscopy, differential scanning calorimetry, and X-ray diffraction. Results [...] Read more.
A series of novel discotic liquid crystalline donor–acceptor hybrid heterojunctions were prepared by blending the triphenylene derivative (T5E36) as donor and perylene tetracarboxylic esters as acceptor. Mesophases of blends were characterized by using polarized optical microscopy, differential scanning calorimetry, and X-ray diffraction. Results suggest that all the blends formed liquid crystalline phases, where both compounds in the blends self-assembled separately into columns yet cooperatively contributed to the overall hexagonal or tetragonal columnar mesophase structure. The charge carrier mobilities were characterized using a time-of-flight technique. The phase-separated columnar nanostructures of the donor and acceptor components play an important role in the formation of molecular heterojunctions exhibiting highly efficient ambipolar charge transport, with mobilities on the order of 10−3 cm2 V−1 s−1. These blends with ambipolar transport properties have great potential for application in non-fullerene organic solar cells, particularly in bulk heterojunction architectures. Full article
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20 pages, 3960 KiB  
Article
Laboratory-Scale Biochar-Aerated Constructed Wetlands for Low C/N Wastewater: Standardization and Legal Cooperation from a Watershed Restoration Perspective
by Mengbing Li, Sili Tan, Jiajun Huang, Qianhui Chen and Guanlong Yu
Water 2025, 17(16), 2482; https://doi.org/10.3390/w17162482 - 21 Aug 2025
Abstract
To address the problems of eutrophication exacerbation in water bodies caused by low carbon-to-nitrogen ratio (C/N) wastewater and the limited nitrogen removal efficiency of conventional constructed wetlands, this study proposes the use of biochar (Corncob biochar YBC, Walnut shell biochar HBC, and [...] Read more.
To address the problems of eutrophication exacerbation in water bodies caused by low carbon-to-nitrogen ratio (C/N) wastewater and the limited nitrogen removal efficiency of conventional constructed wetlands, this study proposes the use of biochar (Corncob biochar YBC, Walnut shell biochar HBC, and Manure biochar FBC) coupled with intermittent aeration technology to enhance nitrogen removal in constructed wetlands. Through the construction of vertical flow wetland systems, hydraulic retention time (HRT = 1–3 d) and influent C/N ratios (1, 3, 5) were regulated, before being combined with material characterization (FTIR/XPS) and microbial analysis (16S rRNA) to reveal the synergistic nitrogen removal mechanisms. HBC achieved efficient NH4+-N adsorption (32.44 mg/L, Langmuir R2 = 0.990) through its high porosity (containing Si-O bonds) and acidic functional groups. Under optimal operating conditions (HRT = 3 d, C/N = 5), the CW-HBC system achieved removal efficiencies of 97.8%, 98.8%, and 79.6% for NH4+-N, TN, and COD, respectively. The addition of biochar shifted the dominant bacterial phylum toward Actinobacteriota (29.79%), with its slow-release carbon source (TOC = 18.5 mg/g) alleviating carbon limitation. Mechanistically, HBC synergistically optimized nitrogen removal pathways through “adsorption-biofilm (bacterial enrichment)-microzone oxygen regulation (pore oxygen gradient).” Based on technical validation, a dual-track institutionalization pathway of “standards-legislation” is proposed: incorporating biochar physicochemical parameters and aeration strategies into multi-level water environment technical standards; converting common mechanisms (such as Si-O adsorption) into legal requirements through legislative amendments; and innovating legislative techniques to balance precision and universality. This study provides an efficient technical solution for low C/N wastewater treatment while constructing an innovative framework for the synergy between technical specifications and legislation, supporting the improvement of watershed ecological restoration systems. Full article
(This article belongs to the Section Wastewater Treatment and Reuse)
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26 pages, 2389 KiB  
Article
Application of a Heuristic Model (PSO—Particle Swarm Optimization) for Optimizing Surface Water Allocation in the Machángara River Basin, Ecuador
by Jaime Veintimilla-Reyes, Berenice Guerrero, Daniel Maldonado-Segarra and Raúl Ortíz-Gaona
Water 2025, 17(16), 2481; https://doi.org/10.3390/w17162481 - 21 Aug 2025
Abstract
Efficient surface water allocation in reservoir-equipped basins is essential for balancing competing demands within the Water–Energy–Food (WEF) nexus. This study investigated the applicability of Particle Swarm Optimization (PSO) for optimizing water distribution in the Machángara River Basin, Ecuador; a complex, constraint-rich hydrological system. [...] Read more.
Efficient surface water allocation in reservoir-equipped basins is essential for balancing competing demands within the Water–Energy–Food (WEF) nexus. This study investigated the applicability of Particle Swarm Optimization (PSO) for optimizing water distribution in the Machángara River Basin, Ecuador; a complex, constraint-rich hydrological system. Implemented via the Pymoo package in Python, the PSO model was evaluated across calibration, validation, and execution phases, and benchmarked against exact methods, including Linear Programming (LP) and Mixed Integer Linear Programming (MILP). The results revealed that standard PSO struggled to satisfy equality constraints and yielded suboptimal solutions, with elevated penalty costs. Despite incorporating MILP-inspired encoding and repair functions, the algorithm failed to identify feasible solutions that met operational requirements. The execution phase, which includes reservoir construction decisions, resulted in a total penalty exceeding EUR 164.95 billion, with no improvement observed from adding reservoirs. Comparative analysis confirmed that LP and MILP outperformed PSO in constraint compliance and penalty minimization. Nonetheless, the study contributes a reproducible implementation framework and a comprehensive benchmarking strategy, including synthetic test functions, performance metrics, and diagnostic visualizations. These tools can facilitate systematic evaluation of PSO’s behavior in high-dimensional, nonlinear environments and provide a foundation for future hybrid or adaptive heuristic models. The findings underscore the limitations of standard PSO in hydrological optimization but also highlight its potential when enhanced through hybridization. Future research should explore PSO variants that integrate exact solvers, adaptive control mechanisms, or cooperative search strategies to improve feasibility and convergence. This work advances the methodological understanding of metaheuristics in environmental resource management and supports the development of robust optimization tools under the WEF-nexus paradigm. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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36 pages, 3129 KiB  
Article
Spatiotemporal Meta-Reinforcement Learning for Multi-USV Adversarial Games Using a Hybrid GAT-Transformer
by Yang Xiong, Shangwen Wang, Hongjun Tian, Guijie Liu, Zihao Shan, Yijie Yin, Jun Tao, Haonan Ye and Ying Tang
J. Mar. Sci. Eng. 2025, 13(8), 1593; https://doi.org/10.3390/jmse13081593 - 20 Aug 2025
Abstract
Coordinating Multi-Unmanned Surface Vehicle (USV) swarms in complex, adversarial maritime environments is a significant challenge, as existing multi-agent reinforcement learning (MARL) methods often fail to capture intricate spatiotemporal dependencies, leading to suboptimal policies. To address this, we propose Adv-TransAC, a novel Spatio-Temporal Meta-Reinforcement [...] Read more.
Coordinating Multi-Unmanned Surface Vehicle (USV) swarms in complex, adversarial maritime environments is a significant challenge, as existing multi-agent reinforcement learning (MARL) methods often fail to capture intricate spatiotemporal dependencies, leading to suboptimal policies. To address this, we propose Adv-TransAC, a novel Spatio-Temporal Meta-Reinforcement Learning framework. Its core innovation is a hybrid GAT-transformer architecture that decouples spatial and temporal reasoning: a Graph Attention Network (GAT) models instantaneous tactical formations, while a transformer analyzes their temporal evolution to infer intent. This is combined with an adversarial meta-learning mechanism to enable rapid adaptation to opponent tactics. In high-fidelity escort and defense simulations, Adv-TransAC significantly outperforms state-of-the-art MARL baselines in task success rate and policy robustness. The learned policies demonstrate the emergence of complex cooperative behaviors, such as intelligent risk-aware coordination and proactive interception maneuvers. The framework’s practicality is further validated by a communication-efficient federated optimization architecture. By effectively modeling spatiotemporal dynamics and enabling rapid adaptation, Adv-TransAC provides a powerful solution that moves beyond reactive decision-making, establishing a strong foundation for next-generation, intelligent maritime platforms. Full article
(This article belongs to the Special Issue Advanced Control Strategies for Autonomous Maritime Systems)
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