Search Results (273)

Global river water quality degradation severely impairs aquatic ecosystem stability and human health, highlighting the urgency of spatiotemporal analysis for management guidance. Based on 2014–2024 monitoring data from the Quzhou Section of Qiantang River Basin, this study adopted the Water Quality Index (WQI) and statistical methods (PCA, Mann–Kendall test) to explore the spatiotemporal characteristics of water quality across the basin. Results showed an overall mean WQI of 79.26 (classified as “Good”), with general stability, localized fluctuations, and a stable-then-declining trend, mirroring an imbalance between governance effects and emerging pollution pressures. It identifies a critical governance phase focused on securing the current good water quality and curbing the trend of further deterioration. Water quality exhibited distinct variations: upper reaches > lower reaches, tributaries > mainstreams, with priority required for the Wuxi River’s declining WQI and the Qu River’s persistently low WQI. TN, TP, and NH₃-N were identified as key factors coupled with land use patterns. A differentiated strategy prioritizing nitrogen control, synergizing phosphorus–oxygen management, and reducing organics is thus proposed. This study provides scientific references for water quality assessment and targeted aquatic ecological governance in the basin and similar river networks. Full article

Wireless Body Area Network (WBAN) is an emerging medical health monitoring technology. However, WBANs encounter critical challenges in balancing reliability, energy efficiency, and Quality of Service (QoS) requirements for life-critical medical data. The design of its Medium Access Control (MAC) protocol has challenges since dynamic body-shadowing effects and heterogeneous traffic patterns. In this paper, we propose the Nash Bargaining Rate-optimization MAC (NBR-MAC), a hybrid MAC protocol that integrates TDMA-based Guaranteed Time Slots (GTS) with CSMA/CA-based contention access. Unlike traditional schemes, we model the rate allocation as an Asymmetric Nash Bargaining Game, introducing a rigorous disagreement point to guarantee minimum service for critical nodes. The utility function is normalized to resolve dimensional inconsistencies, incorporating sensor priority, buffer status, and channel quality. The Nash Bargaining solution is derived after proving convexity and verifying the axioms. Superframe time slots are allocated based on sensor data priority. Simulation results demonstrate that the proposed protocol enhances transmission success ratio and throughput while reducing packet age and energy consumption under different load conditions. Full article

Smart control technologies that can manage the complexity of urban traffic while also reducing response times for emergency vehicles are necessary. This article proposes AETM (Adaptive and Equitable Traffic Management), an adaptive and equitable traffic management system that integrates contextual methods for handling emergencies with traffic light control based on reinforcement learning. The system uses Q-learning to optimize traffic light phases under normal traffic conditions and integrates a dedicated emergency vehicle module, which includes detection, dynamic rerouting and contextual preemption functions. The system adaptively optimizes traffic light phases under normal traffic conditions and integrates a specialized module for emergency vehicles, which ensures their detection, dynamic rerouting and contextual preemption. The priority level is evaluated through an auxiliary fuzzy mechanism, based on interpretable rules, which takes into account local conditions without influencing the learning process. The performance of the framework is evaluated in a microscopic simulation environment by comparing classical control, adaptive control, and the full AETM configuration. The results highlight significant reductions in travel times and stops for emergency vehicles while maintaining overall traffic stability. Full article

Sustainable tourism has become a priority as environmental pressures on the hospitality sector intensify. Despite increasing promotion of green hotels, a persistent gap remains between pro-environmental intentions and actual booking behavior. Prior applications of the Theory of Planned Behavior (TPB) largely focus on developed economies and offer limited insight into how digital platforms, organizational credibility, and information-seeking behavior shape green hotel decisions in emerging tourism markets. To address this gap, this study extends TPB by integrating social media marketing, environmental knowledge, organizational green practices awareness, self-image in environmental protection, and consumer information-seeking behavior. Survey data from 538 foreign tourists staying in hotels in Turkey were analyzed using Partial Least Squares Structural Equation Modeling. The findings indicate that awareness of organizational green practices is the strongest predictor of consumer attitude, followed by self-image, social media marketing, and environmental knowledge. Consumer attitude, subjective norms, and perceived behavioral control shape purchase intention, while purchase behavior is driven by intention, perceived behavioral control, and information-seeking behavior. Notably, information-seeking behavior exerts a direct and mediating effect on purchase behavior but does not moderate the intention–behavior relationship, indicating a post-intentional verification role. Full article

In recent decades, the burden of TB has been gradually declining; however, with the emergence of COVID-19 and ongoing political conflicts, including the war in Ukraine, the proper functioning of healthcare services and TB control programs has been jeopardized. Recently, research has emphasized the importance of hematological parameters associated with inflammation, which can be easily analyzed through routine blood tests. Combining these parameters may have predictive value for various diseases, including pulmonary tuberculosis and even help monitor the effectiveness of treatment. Since there is no single hematological or inflammatory biomarker that provides precise and dynamic information about the success or failure of treatment, identifying individual markers or sets of biomarkers with higher sensitivity and specificity is essential. This is particularly important since sputum culture conversion at two months remains insufficiently sensitive and microscopy conversion has limited sensitivity and specificity in detecting treatment failure. Also, the analysis of the impact of the standard directly observed treatment, short-course regimen on pathogenic mechanisms also focuses on how it influences the interaction between inflammation and oxidative tissue degradation, by measuring plasma levels of glutathione. Utilizing a combination of hematological, inflammatory, and antioxidant biomarkers offers significant insights into systemic inflammatory responses in pulmonary tuberculosis patients, both before commencing treatment and during the entire duration of antituberculosis therapy. Combining different inflammatory parameters into a multiple biomarker can significantly enhance the accuracy of predicting prognosis and response to antibiotic chemotherapy. Identifying an optimal combination of biomarkers with predictive value is crucial for assessing treatment response and evaluating the effectiveness of anti-TB medication. Rather than developing or testing a composite prediction model, this review summarizes reported performance metrics from individual studies and highlights priorities for future prospective validation of integrated biomarker panels. Full article

Bovine respiratory disease (BRD) remains one of the most consequential health and economic challenges in U.S. beef production, particularly within integrated systems where microbial, environmental, and management factors intersect. This review synthesizes contemporary epidemiological insights, emphasizing BRD’s multifactorial pathogenesis driven by dynamic host–pathogen–environment interactions involving agents such as Mannheimia haemolytica, Pasteurella multocida, and Mycoplasma bovis, alongside stressors from transportation, weaning, and commingling. BRD imposes annual losses exceeding two billion dollars through diminished feed efficiency, reduced carcass yield, increased treatment costs, and mortality. Despite progress in vaccination, biosecurity, and therapeutic interventions, BRD persists due to diagnostic subjectivity and limitations of traditional control measures. The review underscores emerging innovations, including precision livestock technologies, AI-enabled surveillance, and metabolomic biomarkers as transformative tools for early detection and targeted mitigation, while noting barriers related to cost, data harmonization, and scalability. The rising threat of antimicrobial resistance further highlights the need for stewardship frameworks that balance therapeutic effectiveness and public health priorities. Additionally, the paper analyzes policy and economic considerations, arguing for coordinated efforts among producers, veterinarians, researchers, and regulators. BRD is reframed as a systems-level challenge requiring integrated scientific, operational, and regulatory strategies to enhance resilience and sustainability across U.S. beef production. Full article

Research on road transport infrastructures is rapidly evolving as electrification, automation, and digital connectivity reshape how systems are designed, operated, and managed. This study presents a combined bibliometric, scientometric, and network analysis of 2755 publications published between 2021 and 2025 to map the intellectual structure, main contributors, and dominant technological themes shaping contemporary road transport research. Using data from the Web of Science Core Collection, co-occurrence mapping, thematic analysis, and collaboration networks were generated using Bibliometrix and VOSviewer. The results reveal strong growth in research output, with China, the United States, and Europe forming the core of high-impact publication and collaboration networks. Six bibliometric clusters were identified and consolidated into three overarching domains: road transport systems, emphasizing vehicle dynamics, control, and real-time computational frameworks; energy and efficiency-oriented mobility research, focusing on electrification, optimization, and infrastructure integration; and emerging digital technologies, including IoT, AI, and autonomous vehicles. The analysis highlights persistent research gaps related to interoperability, cybersecurity, large-scale deployment, and governance of intelligent transport infrastructures. Overall, the findings provide a data-driven overview of current research priorities and structural patterns shaping next-generation road transport systems. Full article

The growing incorporation of distributed energy resources (DER) in power distribution grids, although pivotal to the energy transition, increases operational variability and amplifies the exposure to disturbances that can compromise resilience and the continuity of service during contingencies. Addressing these challenges requires both a shift toward flexible distribution architectures and the adoption of advanced power electronics interfacing systems. In this setting, this paper proposes a resilience-oriented strategy for medium-voltage (MV) distribution systems and clustered hybrid AC/DC microgrids interfaced through solid-state transformers (SSTs). When a fault occurs along an MV feeder segment, the affected microgrids naturally transition to islanded operation. However, once their local generation and storage become insufficient to sustain autonomous operation, the proposed framework reconfigures the power routing within the cluster by activating an emergency low-voltage DC (LVDC) power path that bypasses the faulted MV section. This mechanism enables controlled power sharing between microgrids during prolonged MV outages, ensuring the supply of priority loads without oversizing SSTs or reinforcing existing infrastructure. Experimental validation on a reduced-scale SST prototype demonstrates stable grid-forming and grid-following operation. The reliability of the proposed scheme is supported by both steady-state and transient experimental results, confirming accurate voltage regulation, balanced sinusoidal waveforms, and low current tracking errors. All tests were conducted at a switching frequency of 50 kHz, highlighting the robustness of the proposed architecture under dynamic operation. Full article

Japan has largely achieved the “first half” of SDG 6—universal access to safe drinking water and sanitation—through decades of intensive investment in water supply and sewerage systems, implementation of the Total Pollutant Load Control System, and stringent regulation of industrial effluents. National indicators show that coverage of safely managed drinking water and sanitation services is nearly 99%, and domestic statistics report high compliance rates for BOD/COD-based environmental standards in rivers, lakes, and coastal waters. Conversely, the “second half” of SDG 6 reveals persistent gaps: ambient water quality (6.3.2) remains at 57% (2023 data), while water stress (6.4.2) is at approximately 21.6%. Furthermore, SDG 6.6.1 shows that 3% of water basins are experiencing rapid changes in surface water area (2020 data), with ecosystems increasingly threatened by hypoxia in enclosed bays and climate-induced vulnerabilities. Drawing on global comparisons, this review synthesizes Japan’s progress toward SDG 6, elucidates the structural drivers for remaining gaps, and proposes policy pathways for a nature-positive water future. Using national statistics (1970–2023) and the DPSIR framework, our analysis confirms that improvements in BOD/COD compliance plateaued around 2002, reinforcing concerns that point-source measures alone are insufficient to address diffuse pollution, groundwater nitrate contamination, and emerging contaminants like PFAS. We propose six strategic directions: (1) climate-resilient water systems leveraging groundwater; (2) smart infrastructure renewal; (3) advanced treatment for emerging contaminants; (4) basin-scale IWRM enhancing transboundary cooperation; (5) data transparency and citizen engagement; and (6) scaled nature-based solutions (NbS) integrated with green–gray infrastructure. The paper concludes by outlining priorities to close the gaps in SDG 6.3 and 6.6, advancing Japan toward a sustainable, nature-positive water cycle. Full article

With the rapid development of the Internet of Things (IOT), 5G, and modern power systems, demand-side loads are becoming increasingly observable and remotely controllable, which enables demand-side flexibility to participate more actively in grid dispatch and emergency support. Under extreme rainstorm conditions, however, component failure risk rises and the availability and dispatchability of demand-side flexibility can change rapidly. This paper proposes a risk-aware emergency regulation framework that translates rainstorm information into actionable multi-load aggregation decisions for urban power systems. First, demand-side resources are quantified using four response attributes, including response speed, response capacity, maximum response duration, and response reliability, to enable a consistent characterization of heterogeneous flexibility. Second, a backpropagation (BP) neural network is trained on long-term real-world meteorological observations and corresponding reliability outcomes to estimate regional- or line-level fault probabilities from four rainstorm drivers: wind speed, rainfall intensity, lightning warning level, and ambient temperature. The inferred probabilities are mapped onto the IEEE 30-bus benchmark to identify high-risk areas or lines and define spatial priorities for emergency response. Third, guided by these risk signals, a two-level coordination model is formulated for a load aggregator (LA) to schedule building air conditioning loads, distributed photovoltaics, and electric vehicles through incentive-based participation, and the resulting optimization problem is solved using an adaptive genetic algorithm. Case studies verify that the proposed strategy can coordinate heterogeneous resources to meet emergency regulation requirements and improve the aggregator–user economic trade-off compared with single-resource participation. The proposed method provides a practical pathway for risk-informed emergency regulation under rainstorm conditions. Full article

The emergence and spread of swine coronaviruses represent a growing challenge for both veterinary medicine and public health. These viruses exhibit high mutation rates, recombination potential, and the capacity for cross-species transmission. Among the most relevant pathogens are PEDV, TGEV, PRCV, PHEV, PDCoV, and SADS-CoV, which have caused significant outbreaks in swine production systems worldwide, with severe economic consequences. Recent evidence demonstrates coronavirus circulation in wild boar populations across Europe, including Italy, Spain, and Germany. Although wild boars are not confirmed as primary reservoirs, their ecological behavior and increasing overlap with domestic pigs raise concern over their potential role in maintaining viral circulation. Future research priorities should focus on developing a more integrated and coordinated system for the control of swine coronaviruses, including strengthened surveillance in both domestic pigs and wild boar populations, the use of molecular epidemiology techniques to identify emerging variants, and structured collaboration among veterinary, ecological, health, and regulatory sectors. Finally, investment is needed in the development of next-generation vaccines and diagnostic tools to address the considerable genetic variability of swine coronaviruses and to improve the prevention and early detection of and response to future epidemic threats. Full article

The Internet of Military Things (IoMT) relies on Long-Range Wide Area Networks (LoRaWAN) for low-power, long-range communication in critical applications like border security and soldier health monitoring. However, conventional priority-based flow control mechanisms, which rely on static classification thresholds, lack the adaptability to handle the nuanced, continuous nature of physiological data and dynamic network states. To overcome this rigidity, this paper introduces a novel, domain-adaptive Fuzzy Logic Flow Control (FFC) protocol specifically tailored for LoRaWAN-based IoMT. While employing established Mamdani inference, the FFC system innovatively fuses multi-parameter physiological data (body temperature, blood pressure, oxygen saturation, and heart rate) into a continuous Health Score, which is then mapped via a context-optimised sigmoid function to dynamic transmission intervals. This represents a novel application-layer semantic integration with LoRaWAN’s constrained MAC and PHY layers, enabling cross-layer flow optimisation without protocol modification. Simulation results confirm that FFC significantly enhances reliability and energy efficiency while reducing latency relative to traditional static priority architectures. Seamlessly integrated into the NS-3 LoRaWAN simulation framework, the FFC protocol demonstrates superior performance in IoMT communications. Simulation results confirm that FFC significantly enhances reliability and energy efficiency while reducing latency compared with traditional static priority-based architectures. It achieves this by prioritising high-priority health telemetry, proactively mitigating network congestion, and optimising energy utilisation, thereby offering a robust solution for emergent, health-critical scenarios in resource-constrained environments. Full article

The convergence of food insecurity, water scarcity, and environmental degradation has intensified the global search for sustainable agricultural models. Integrated Microalgal–Aquaponic Systems (IAMS) have emerged as a novel multi-trophic platform that unites aquaculture, hydroponics, and microalgal cultivation into a closed-loop framework for resource-efficient food production and water recovery. This critical review synthesizes empirical findings and engineering advancements published between 2008 and 2024, evaluating IAMS performance relative to traditional agriculture and recirculating aquaculture systems (RAS). Reported under controlled laboratory and pilot-scale conditions, IAMS have achieved nitrogen and phosphorus recovery efficiencies exceeding 95% while potentially reducing water consumption by up to 90% compared to conventional farming. The integration of microalgal photobioreactors enhances nutrient retention, may contribute to internal carbon capture, and enables the generation of diversified co-products, including biofertilizers and protein-rich aquafeeds. Nevertheless, significant barriers to commercial scalability persist, including the biological complexity of maintaining multi-trophic synchrony, high initial capital expenditure (CAPEX), and regulatory ambiguity regarding the safety of waste-derived algal biomass. Technical challenges such as photobioreactor upscaling, biofouling control, and energy optimization are critically discussed. Finally, the review evaluates the alignment of IAMS with UN Sustainable Development Goals 2, 6, and 13, and outlines future research priorities in techno-economic modeling, automation, and policy development to facilitate the transition of IAMS from pilot-scale innovations to viable industrial solutions. Full article

Phytoplankton sinking is a pivotal process within the biological carbon pump that drives the vertical transport of organic carbon in the ocean. Its rates and underlying mechanisms directly influence the efficiency of the global carbon cycle and the potential for long-term sequestration. This review synthesizes current knowledge of phytoplankton sinking, encompassing buoyancy regulation mechanisms, environmental and physiological controls, methodological approaches such as settling column (SETCOL), and comparative evidence from laboratory and field studies. The aim is to elucidate the regulatory processes governing sinking and to provide a foundation for improving ecological models and refining estimates of carbon export. Evidence demonstrates that sinking rates vary considerably among phytoplankton groups, with nutrient limitation and aggregation emerging as critical modulators of export efficiency. By integrating results from experimental and in situ research, this review identifies unresolved questions and highlights priority areas: (1) quantitative coupling between aggregation and carbon flux; (2) mechanistic understanding of group-specific sinking responses; (3) integration of novel technologies, including in situ imaging and high-resolution modeling with established methods; and (4) development of interdisciplinary frameworks. Overall, this review consolidates current knowledge and underscores phytoplankton sinking as a crucial yet insufficiently resolved process within the marine carbon cycle. Full article

Forests play a strategic role in global sustainability, and restoration is essential to meet ESG targets. Seedling quality strongly influences reforestation success, but standardized evaluation protocols are often lacking. This study aimed to identify and prioritize critical technical parameters of forest seedlings and determine the highest-priority factor affecting field performance. A total of 100 seedlings of Handroanthus impetiginosus and Sparattosperma leucanthum were evaluated using Quality Function Deployment (QFD), considering reforestation as the client to translate field performance requirements into nursery-level technical parameters. Seedling characteristics were compared to standards based on the literature and nursery best practices. QFD analysis revealed that stem thickness and integrity, absence of borers, well-developed and firm roots, and complete and healthy leaves were the most critical attributes. Hardiness, combining structural robustness, disease resistance, and vigor, emerged as the central factor. Observed non-conformities included disease (15%), stem bifurcations (10%), and substrate deficiencies (12%). These results demonstrate that QFD is an effective tool for systematically identifying and prioritizing seedling attributes. The study provides a structured approach for nursery evaluation and quality control, supporting informed decision-making to enhance the success of forest restoration projects. Full article