Search Results (7,495)

Metropolitan service-placement optimization is computationally challenging under strict evaluation budgets and regulatory constraints. Existing approaches either neglect capacity constraints, producing infeasible solutions, or employ population-based metaheuristics requiring hundreds of evaluations—beyond typical municipal planning resources. We introduce a two-stage optimization framework combining Bayesian optimization with domain-informed heuristics to address this constrained, mixed discrete–continuous problem. Stage 1 optimizes continuous service area allocations via the Tree-structured Parzen Estimator with empirical gradient prioritization, reducing effective dimensionality from 81 services to 10–15 per iteration. Stage 2 converts allocations into discrete unit placements via efficiency-ranked bin packing, ensuring regulatory compliance. Evaluation across 35 benchmarks on Saint Petersburg, Russia (117–3060 decision variables), demonstrates that our method achieves 99.4% of the global optimum under a 50-evaluation budget, outperforming BIPOP-CMA-ES (98.4%), PURE-TPE (97.1%), and NSGA-II (96.5%). Optimized configurations improve equity (Gini coefficient of 0.318 → 0.241) while maintaining computational feasibility (2.7 h for 109-block districts). Open-source implementation supports reproducibility and facilitates adoption in metropolitan planning practice. Full article

Urban logistics serves as a cornerstone for efficient freight transport and sustainable city development, particularly in contexts challenged by congestion and environmental pressures. This research examines the restructuring of the urban logistics system in Sfax, Tunisia—an expanding industrial and economic center increasingly burdened by traffic congestion. Through a comprehensive analytical framework, the study identifies the primary determinants influencing freight transport operations and develops a phased policy roadmap to enhance logistical efficiency. Neural Network Modeling is employed to evaluate the effects of multiple transport-related variables on logistics performance, while Graph Theory is utilized to represent spatial and functional interconnections, facilitating the visualization of freight flows and supporting evidence-based decision-making. The results emphasize the crucial role of managing truck circulation within Sfax’s urban core. Accordingly, a three-phase reorganization plan is proposed to optimize freight mobility, alleviate congestion, and advance sustainable urban growth. The methodological approach and policy insights offer practical guidance applicable to other metropolitan areas facing similar logistical challenges. Full article

The effective remediation of cadmium (Cd) pollution continues to pose a significant challenge in environmental science. Bacteria-loaded biochar (BLBC), a composite material synthesized by immobilizing functional microorganisms onto biochar, has emerged as a promising adsorbent for Cd due to its ability to simultaneously facilitate adsorption and biodegradation. In this study, a manganese (Mn)-oxidizing bacterium (Priestia sp. Z-MLHA-1), isolated from a high-manganese mining area, was successfully used to prepare BLBC. The Cd(II) immobilization performance and underlying mechanisms were systematically investigated. The results showed that bacterial loading significantly optimized the pore structure of the biochar, increasing its specific surface area by 40% and enriching the diversity of surface functional groups. Adsorption experiments demonstrated a strong affinity of BLBC for Cd(II), with a maximum adsorption capacity of 44.17 mg/g. The adsorption behavior followed the Langmuir isotherm and pseudo-second-order kinetic models, indicating a monolayer process dominated by chemisorption. The primary immobilization mechanisms involved complexation with surface oxygen-containing functional groups (e.g., −COOH, −OH), ion exchange, and a synergistic effect between the biochar and the immobilized microorganisms. This material enables efficient Cd(II) removal under environmentally benign conditions, thereby providing a theoretical foundation and technical support for the development of green and sustainable remediation technologies for heavy metal-contaminated water. Full article

Potassium (K) is crucial for global maize (Zea mays L.) production, yet the issue of “high K fertilizer input but low utilization efficiency” in K-rich soils of Xinjiang remains underexplored. A three-year field experiment (2020, 2021, 2024) in Xinjiang evaluated the effects of reduced K application on maize growth, grain yield (GY), and K-use efficiency. Five treatments were tested: K100 (136.0 kg K₂O·ha⁻¹), K60 (83.5 kg K₂O·ha⁻¹), K40 (55.6 kg K₂O·ha⁻¹), K0 (no K), and CK (no fertilizer). The research shows that K60 significantly outperforms K100 in terms of physiological parameters (plant height + 2.7–34.7%, leaf area index (LAI) + 6.3–26.8%, dry matter + 22.0–28.8%); GY and thousand kernel weight (TKW) improved by 6.9–15.1% and 9.3–30.3%, respectively. The potassium fertilizer productivity (PFP_K) and potassium fertilizer agronomic efficiency (AE_K) increased by 78–112.3% and 176.4–2085% compared to the K100. During the three-year period, the maximum net income of K60 reached 28,206 CNY·ha⁻¹, which was 18.9–20.7% higher than that of K100. Regression analysis identified an optimal K rate of 82.2–85 kg·ha⁻¹ for maximum yield. Least squares structural equation mode (PLS-SEM) and correlation analyses revealed that moderate K reduction enhanced vegetative growth and optimized yield structure, indirectly boosting yield, thereby directly driving net income. Thus, reducing K input can achieve “lower input with higher efficiency”, offering a practical basis for optimizing K management in arid-region maize systems. Full article

Exploring the spatio-temporal evolution patterns of rapeseed production at the county level in Sichuan Province, China, and analyzing the influence of natural conditions and socioeconomic development based on regional spatial characteristics, can help guide the rational distribution of crop production and provide a reference for the high-quality and sustainable development of the local rapeseed industry. Based on panel data from 2001 to 2023, this study employs GIS spatial analysis to examine the spatio-temporal evolution of rapeseed production in Sichuan and applies a Geodetector model to identify factors influencing its spatial and temporal variations. The results reveal that rapeseed production in Sichuan is concentrated in three main production areas: the northeastern Sichuan region, the middle Sichuan hilly region, and the Chengdu Plain. The dynamic evolution exhibits a composite pattern characterized by the stability and expansion of core areas, alongside breakthroughs and growth in peripheral regions, with increased production observed across 134 counties. The spatial center of rapeseed production shows short-range fluctuations and distinct regional anchoring, oscillating among Santai County, Shehong City, and Daying County, tracing a “Z”-shaped trajectory. Over the 23-year period, the global Moran’s I index ranged from 0.464 to 0.558, indicating a significant spatial clustering trend in rapeseed output among adjacent counties. Local spatial autocorrelation patterns were predominantly H-H, L-L, and L-H clusters. Factor detection identifies labor force availability, fertilizer application intensity, and effective irrigated area as the most influential factors. Interaction detection results consistently exhibit a two-factor enhancement effect. To enhance the rapeseed industry’s performance and efficiency, it is recommended to stabilize production capacity in the three core production areas, leverage central regions to strengthen radiation to the surrounding counties, optimize resource allocation based on clustering patterns, and focus on improving key factors such as labor and irrigation, as well as their synergistic effects. Full article

This study aims to develop a methodology for implementing solar photovoltaic systems (SSFV) in Caribbean hotels. It begins with an analysis of building characteristics to design and size the SSFV, considering panel support structures, system layout, and grid integration. The methodology also evaluates economic and environmental impacts at both company and national levels. Machine learning analysis identified the variables (Degree Days (DG) and Hotel Days Occupied (HDO)) $HDO\times DG$ as key determinants of energy consumption, with a high coefficient of determination ($R^2$ = 0.97). Implementing a target energy-saving line achieved a 5.3% reduction (1028 kWh) relative to the baseline. Using a genetic algorithm to optimize the SSFV azimuth angle increased photovoltaic energy production by 14.75%, enhancing efficiency and installation area use. Economic assessments showed a challenging scenario for hotels, with a negative internal rate of return of −10%, a 17 year payback period, and a net present value of USD 20,000. However, on a national scale, significant annual savings of USD 225,990.8 from reduced fuel imports were projected. Additionally, carbon emissions reductions of 18,751.4 tons ($tC{O}_2$) were estimated. The findings highlight the feasibility and benefits of SSFV implementation, emphasizing its potential to improve energy efficiency, reduce costs, and enhance sustainability in the Caribbean hotel sector. Full article

Promoting demand-responsive transit (DRT) is crucial for developing sustainable and green transportation systems in urban areas, especially in light of decreasing transit ridership and increasingly varying demand. However, the effectiveness of such services hinges on their ability to efficiently match varying travel demand. This paper presents a data-driven framework for the joint optimization of customized bus routes and timetables, to enhance both service quality and operational sustainability. Our approach leverages large-scale taxi trip data to identify latent travel demand, applying a spatial–temporal clustering method to group trip requests and identify DRT stops by trip origin, destination, and direction. An adaptive large neighborhood search (ALNS) algorithm is improved to co-optimize passenger waiting times and bus operation costs, where an unbalanced penalty for early or late schedule deviations is developed to better reflect passengers’ discomfort. The framework’s performance is validated through a real-world case study, demonstrating its ability to generate efficient routes and schedules. The model manages to improve passenger experience and reduce operation costs. By creating a more appealing and efficient service, this model contributes directly to the goals of green transport in terms of reducing the total vehicle kilometers that are traveled, and demonstrating a viable, high-quality alternative to private car usage. This study offers a practical and robust tool for transit planners to design a next-generation DRT system that is both economically viable and environmentally sustainable. Full article

Transitional attack represents a pivotal tactic in modern firefighting, whose efficacy is profoundly contingent upon the impact characteristics of water streams and their subsequent distribution patterns. This study integrates computational fluid dynamics (CFD) simulations with experimental validation to develop a momentum decomposition model for jet impingement on a ceiling. The model analyzes the dominant mechanisms of tangential spread and normal rebound on water distribution and optimizes water application strategies. Theoretical analysis reveals that upon ceiling impact, the normal velocity component of the stream undergoes rapid attenuation, causing the flow to be predominantly governed by tangential diffusion. This phenomenon results in an asymmetrically elliptical ground distribution, characterized by a significant concentration of water volume at the terminus of the diffusion path, while wall boundaries induce further water accumulation. A comparative analysis of the stream impact process and water distribution demonstrates a high degree of concordance between experimental and simulation results, thereby substantiating the reliability of the proposed model. Numerical simulations demonstrate that an increased jet angle markedly improves both coverage area and flux density. Higher water pressure enhances jet kinetic energy, leading to improved distribution uniformity. Appropriately extending the horizontal projection distance of the water jet further contributes to broadening the effective coverage. The parametric combination of a 49° jet angle, water pressure of 0.2–0.25 MPa, and a relative horizontal distance of 1.5–2.0 m is identified as optimal for overall performance. This research provides a scientific foundation and practical operational guidelines for enhancing the efficiency and safety of the transitional attack methodology. Full article

In the Hetao Irrigation District of China, land consolidation to expand cultivated areas has disrupted the regional water–salt balance, increasing soil salinization risks. This study investigates the spatial optimization of cultivated land and salt-accumulating wasteland, using the SahysMod model to simulate soil water–salt dynamics and develop multi-scenario plans. The objective is to identify optimal strategies for regulating the dry drainage system and controlling salt accumulation by optimizing three key parameters: cultivated land-to-wasteland area ratio, elevation difference between cultivated land and wasteland, and spatial layout schemes. The results show that the SahysMod model accurately simulates soil water–salt interactions. Under the current scenario, the root zone ECe of cultivated land is projected to reach 6.16 dS·m⁻¹ by 2030, surpassing the salt tolerance threshold for sunflowers and threatening crop yield. The optimized scenario, which reduces the cultivated land-to-wasteland ratio from 14.41 to 12.97, increases wasteland area to 22.01 hm² and raises the elevation difference from 20 cm to 40 cm, significantly improving salt accumulation efficiency. By 2030, the ECe in the root zone decreases to 5.37 dS·m⁻¹, bringing soil conditions within the tolerance range for major crops in the region. Between 2021 and 2025, salt accumulation in cultivated land decreases dramatically from 19.08% to 5.60% under the optimized scenario, demonstrating effective early-stage salt control. However, from 2026 to 2030, the annual salt accumulation rate stabilizes at 24.88% (optimized) versus 25.20% (current), with a difference of only 0.32%. This finding reveals that while spatial optimization effectively mitigates short-term salt buildup, it has limited efficacy in preventing long-term salt accumulation. Spatial simulations suggest that a northern concentrated and southern patchwork wasteland layout enhances salt-accumulating capacity. These results demonstrate that spatial optimization of cultivated land and wasteland configuration alone is insufficient to fundamentally resolve soil salinization. Therefore, comprehensive measures, including drainage system improvements, soil amendments, and refined irrigation management, are necessary for sustainable salt management in arid irrigation regions. Full article

Applications for intelligent cooperative Unmanned Aerial Vehicle (UAV) swarms are rapidly expanding. Efficient and reliable communication is critical for realizing this swarm intelligence, especially in remote areas lacking infrastructure where ad hoc networking is a prevalent approach. However, in such long-distance scenarios, significant propagation delays pose a fundamental challenge to Medium Access Control (MAC) protocols like carrier sense multiple access with collision avoidance (CSMA/CA). This paper theoretically compares random backoff and p-persistent to determine the optimal strategy for these conditions. We present analytical models for both strategies. The model for random backoff reveals its optimal performance is dependent on network topology, making it ill-suited for dynamic swarms. In contrast, our model for p-persistent yields an optimal transmission probability that is independent of the network topology. Simulation results validate our models, showing p-persistent achieves significantly higher throughput (over 40% improvement in an 80-node swarm). We conclude that the topology-independent characteristic of p-persistent makes it a more feasible, more robust, and superior solution for long-distance, dynamic UAV swarm networks. Full article

This paper provides a review of three mainstream technical routes for producing hydrogen from offshore wind power: offshore distributed hydrogen production, offshore centralized hydrogen production, and onshore hydrogen production. Based on global engineering cases, we analyze the characteristics, application scenarios, and current development status of each route, paying particular attention to economic performance, system efficiency, and environmental adaptability. The main challenges identified include the limited adaptability of electrolysis technologies, high full-life-cycle costs, and persistent bottlenecks in storage and transportation. Building on these findings, we summarize technological development trends and propose future directions in areas such as electrolyzer innovation, system efficiency optimization, direct seawater utilization, storage and transport infrastructure. This review aims to provide a reference for advancing research, development, and large-scale applications of offshore wind-to-hydrogen technologies. Full article

Net ecosystem exchange (NEE) is a central metric for assessing carbon cycling, and its accurate quantification is critical for understanding terrestrial-atmosphere carbon exchange dynamics. However, in complex alpine regions, high-resolution NEE estimation remains challenging due to limited observations and heterogeneous surface processes. To address this, we developed a multimodal feature fusion model (Multimodal-CNN-Attention-RF, MMCA-RF) that integrates convolutional neural networks (CNN) and random forest (RF) for NEE estimation in the Babao River Basin on the northeastern Tibetan Plateau. The model incorporates a cross-modal attention mechanism to dynamically optimize feature interactions, thereby better capturing the spatially heterogeneous responses of vegetation to environmental drivers. Results demonstrate that MMCA-RF exhibits strong stability and generalization, with R² values of 0.89 (training) and 0.85 (testing). Based on model outputs, the Babao River Basin acted as a carbon sink during 2017–2023, with a mean annual NEE of −100.86 gC m⁻² yr⁻¹. Spatially, NEE showed pronounced heterogeneity, while seasonal variation followed a unimodal pattern. Among vegetation types, grasslands contributed the largest total carbon sink, whereas open woodlands showed the highest sequestration efficiency per unit area. Driver analysis identified temperature as the dominant control on NEE spatial variation, with interactions between temperature, precipitation, and topography further enhancing heterogeneity. This study provides a high-accuracy modeling approach for monitoring carbon cycling in alpine ecosystems and offers insights into the stability of regional carbon pools under climate change. Full article

In the rapid development of rural tourism, multiple disturbances, such as capital reorganization, uneven resource distribution, and the marginalization of farmers as the main body, have emerged. This has led to the dual challenges of increased vulnerability and insufficient resilience of farmers’ livelihood systems in the face of risk shocks. Based on survey data of the “Agri-Tourism–Commerce–Culture Integration” demonstration zone in China, this study integrates the Pressure–State–Response model into the analysis of livelihood resilience and constructs a “vulnerability–adaptability–recuperability” tri-dimensional framework. Through methods such as the entropy weight method, the synthetical index method, grey relational degree analysis, and the obstacle degree model, this study measures the levels of different livelihood types of farmers in each dimension of livelihood resilience and their influencing factors. The research findings indicate that the overall livelihood resilience of farmers in the study area was at a medium level, with vulnerability making the most significant contribution, reflecting that the current livelihood system is dominated by risk resistance. Different types of farmers exhibit heterogeneity in resilience, with tourism-oriented farmers showing the highest resilience and agriculture-oriented farmers the lowest. However, tourism-oriented farmers also display the most prominent vulnerability, revealing the tension between short-term efficiency enhancement and long-term risk diversification in single livelihood strategies. Key factor analysis reveals that vulnerability correlates most strongly with livelihood resilience. The most correlated indicators are the price increase rate, proportion of migrant workers, and neighborhood trust in the vulnerability, adaptability, and recuperability dimensions. Diagnosis of obstacle factors reveal that loan accessibility, land resource dependency, and agricultural risk perception rank as the top three common obstacles, with tourism-driven farmers exhibiting higher obstacle degrees than other farmer categories. These findings not only validate the empowering effect of rural tourism on farmers’ livelihoods but also reveal the different livelihood strategies chosen by various farmers. Based on the results, this study proposes policy recommendations of “common optimization + individual adaptation” to enhance farmers’ livelihood resilience. This is conducive to transforming external support into farmers’ endogenous resilience capabilities and provides a useful reference for achieving the deep integration of rural tourism and farmers’ livelihood systems. Full article

The packaging sector is undergoing a significant transformation driven by increasing environmental challenges and new European regulatory frameworks. The Packaging and Packaging Waste Regulation (PPWR), following the European Green Deal and Circular Economy Action Plan, introduces five strategic priorities: waste prevention, recyclability, recycled content, compostable materials, and reusable systems. This framework aims to systematically review the current state of academic research in relation to these five intervention areas, assessing the extent to which the scientific literature supports the regulation’s circular economy objectives. The PPWR sets guidelines for key aspects such as packaging treatment, recycling targets, Extended Producer Responsibility (EPR) and material optimization. These aspects are strongly linked to market dynamics, driving innovation and new developments in packaging design. This study aims to provide a comprehensive overview of the industry’s evolution, with a focus on the crucial role of the circular economy in addressing the persistent issue of packaging waste. By conducting a systematic literature review using the PRISMA method, the research explores the relationship between the regulation’s structural design and the European Commission’s priority areas. The results reveal that waste prevention and reusability are the most researched areas, particularly concerning environmental assessments and regulatory tools like EPR. Additionally, while recyclability has been studied from technical and environmental perspectives, there is still a lack of research on how it connects with supply chain and material market trends. Strengthening these connections could significantly enhance recycling efficiency and improve the sustainability of packaging systems. Furthermore, financial incentives and policy strategies could play a key role in facilitating the transition to a circular economy. Addressing these gaps will foster a more integrated understanding of sustainable packaging solutions. Full article

With the irregular integration of small-capacity distributed generators (DG) and single-phase loads, rural low-voltage distribution transformers are faced with issues such as three-phase imbalance, light-heavy loading, and feeder terminal voltage excursions, impacting the safe and stable operation of the system. To address this issue, a coordinated control strategy based on direct power control (DPC) for low-voltage substation series-parallel coordination is proposed. A flexible interconnection topology for multi-substation series-parallel coordination is designed to achieve coordinated optimization of alternating current–direct current (AC-DC) power quality. Addressing the three-phase imbalance, light-heavy loading, and feeder terminal voltage excursions in rural low-voltage distribution transformers, a series-parallel coordinated optimization control strategy is proposed. This strategy incorporates a DC bus voltage control strategy based on sequence-separated power compensation and a closed-loop control strategy based on phase-separated power compensation, effectively addressing three-phase imbalances and load balancing in each power distribution areas. Furthermore, a series-connected phase compensation control strategy based on DPC is proposed, efficiently mitigating feeder terminal voltage excursions. A corresponding circuit model is established using Matlab/Simulink, and simulation results validate the effectiveness of the proposed strategy. Full article