Search Results (19,811)

This study evaluates the financial profitability and carbon sequestration in mixed native forests of the Roble-Raulí-Coigüe and evergreen types in the southern macrozone of Chile, integrating both ecosystem services into forest management decision-making. The Faustmann model and dynamic programming were applied to determine the optimal rotation periods and Land Expectation Value (LEV) under two scenarios: exclusive timber production and combined timber and carbon production. The results indicate that mixed forests consistently outperform monocultures in terms of profitability, especially in 25%–75% mix configurations and moderate densities (2000 trees/ha). The observed range of 25%–75% across different tree species is determined by the interplay of two critical factors: the average annual growth rate (AAGR) of biomass and the opportunity cost of the forest rotation. In fast-growing species, the upper limit (75%) reflects an optimisation towards early carbon sequestration, whilst in slow-growing species, the ratio shifts towards the lower limit (25%) to compensate for longer rotation periods and associated biotic risks. This range acts as an efficiency frontier that balances biological productivity with the stability of the accumulated carbon stock. The inclusion of the economic value of carbon increased the LEV and extended the optimal rotation periods, confirming the relevance of integrating ecosystem services into forest planning. These findings suggest that mixed native forests represent a competitive and sustainable alternative to monocultures, contributing to climate change mitigation and income diversification for forest owners. Full article

Subway-hub blocks are critical areas where the pressures of metropolitan populations and environmental quality are closely interconnected. This study constructs a “pressure–context–carrier–response” (PCRC) framework (F1–F7) to systematically reveal the correlations between built-environment characteristics and environmental performance. The results demonstrate that resource allocation (F7) and comprehensive response (F5) display notable “asymmetric differentiation”. The socio-economic environment (F2, F3) considerably influences the concentration of green-space resource allocations (F7) (p < 0.01), with affluent blocks demonstrating a clear advantage in resource distribution. The thermo-ecological composite response (F5), which includes NDVI and LST, demonstrates “statistical convergence” (p = 0.894) across various block types, indicating that resource inputs cannot be linearly transformed into environmental efficiency. This disconnection is ascribed to two physical limitations: firstly, the stochastic nature of spatial distribution (Global Moran’s I ≈ 0) restricts the scale effects of green spaces; secondly, the nonlinear limitations of the physical medium indicate that under conditions of high pressure load (F1) and elevated spatial capacity (F6), the regulatory effectiveness of greening demonstrates a significant diminishing marginal return effect. Therefore, intervention planning must shift from controlling macro-level indicators to optimising micro-level accuracy to address ecological performance constraints in densely populated metropolitan areas. Full article

Though the European Commission has repeatedly stated that the necessary energy transition in Europe should leave “no one behind”, this paper describes a building refurbishment case that has entailed economic hardships for the low-income families involved. The project is located in the area of P. D. Orcasitas in southern Madrid, led by a grassroots neighbours’ movement, comprising one hundred and seven housing blocks, containing more than 2000 dwellings. The main source of funding for the operation consists of subsidies granted by the Madrid City Council; however, Spanish legislation requires the state Agency of Tax Administration to classify these subsidies as capital gains derived from lucrative transfers. Based on the tax data of vulnerable beneficiaries, the conclusion is that the recipients have ended up returning part of the subsidies to the State through their Income Tax Return. In addition, the Spanish Social Security Institute requires the return of social benefits associated with non-contributory retirement pensions and the Minimum Living Income. Apart from tax accounting, regulations are revised to draw conclusions. Unlike most actuations of this kind, in this case the negative effects are obvious. Although intended to alleviate fuel poverty, the initiative has exacerbated vulnerability due to the impact of the imposed penalties on household income. In conclusion, unless preventive measures are implemented, the mandatory refurbishment of inefficient buildings may place an undue burden on vulnerable low-income occupants and hinder the effective implementation of energy-efficiency regulations. Full article

Although tourism is increasingly seen as a key component of sustainable regional development and economic diversification, its extraordinary expansion raises governance and environmental issues at the local level. The current study assesses the influencing factors of inbound tourism demand to Saudi Arabia, a strategic empirical study due to its rapid and ambitious transformation under Vision 2030. This national strategy is designed to cultivate diverse tourist destinations, including coastal eco-resorts, mountain nature escapes, and urban cultural hubs. The unique sustainability hurdles in each area make the Kingdom a prime location for analyzing the development of regional tourism. This research focuses on the vibrant interfaces among sustainable practices, logistical efficiency, perceptions of safety and uncertainty, and macroeconomic environments that shape the Kingdom’s competitiveness as a tourism region. The study draws several beneficial findings using balanced panel data of 16 origin countries during the period of 2009–2023 and is assessed using a dynamic panel Generalized Method of Moments model. The findings state extensive perseverance within tourism flows, such that past arrivals significantly enable simultaneous inflows. Inbound tourism is strongly and favourably influenced by destination-side factors, particularly logistical performance, human rights conditions, and Saudi Arabia’s socioeconomic prosperity. In a similar vein, the demand for outward travel is strongly reinforced by origin-country prosperity. But travel expenses attenuate, environmental pressures and political risk reduce arrivals, and relative prices and pandemic uncertainty play a negligible role. The findings highlight the need to upgrade the country’s logistics infrastructure, enhance rights protection and governance, integrate sustainable practices, and capitalise on prosperity to make Saudi Arabia a desirable travel destination by Vision 2030. A key contribution of this study is to demonstrate how infrastructure, environmental stewardship, and institutional quality shape a region’s tourism attractiveness. The study illustrates how sustainability must be incorporated into regional-specific strategies to balance economic goals with ecological and social imperatives, providing a framework for other countries interested in sustainable tourism. Full article

Foreign plastic objects (FPOs) in poultry products present significant food safety risks and cause economic losses for the industry. Conventional detection methods, including X-rays and color imaging, often struggle to identify small or low-density plastics. Hyperspectral imaging (HSI) offers both spatial and spectral information but suffers from high computational cost when applied for FPO identification in industrial environments. This study introduces a parameter-efficient and computationally efficient spatial–spectral transformer framework for pixel-level classification of FPOs on broiler meat using NIR-HSI (1000–1700 nm). The framework integrates three innovations: (1) center-focused linear attention (CFLA) to reduce computational complexity from $O\left(n^2\right)$ to $O\left(n\right)$; (2) patch-local mixed-axis 2D rotary position embedding to preserve geometric relationships within hyperspectral patches; and (3) low-rank factorized projection (LRP) matrices to reduce parameters by approximately 50% within projection weight matrices. The framework was trained and evaluated on a dataset of 52 chicken fillets, comprising 295,340 labeled target hyperspectral pixels from 12 common polymer types and 1 fillet class. The model achieved 99.39% overall accuracy, 99.57% average accuracy, and a 99.31 Kappa coefficient across 248,540 test pixels. Per-class precision, recall, and F1-score exceeded 98.05%, 98.59%, and 98.76%, respectively, across all classes. Efficiency analyses showed an 83% reduction in multiply–accumulate operations (MACs), a 22% reduction in trainable parameters, and a model size reduction from 1.72 MB to 1.35 MB relative to the baseline configuration. These gains also translated into practical inference benefits, with the final model achieving a throughput of 212,971.5 hyperspectral patch cubes/s and a 4.19× speedup over the baseline. These results demonstrate that the proposed framework combines strong classification performance with high efficiency, supporting high-throughput inference for real-time monitoring and enabling contamination source traceability and preventive quality control in industrial poultry processing. The approach provides a benchmark for applying transformer-based models to food safety inspection tasks. Full article

This study proposes a new approach for optimizing the penetration level of photovoltaic units (PVUs) to achieve both engineering and economic benefits in a standard distribution power system. The Mirage Search Optimization (MSO) and the Pied Kingfisher Optimizer (PKO) are applied to minimize the total active power loss (TRPL) in the IEEE 69-node system. Two cases are considered: Case 1, where PVUs inject only active power, and Case 2, where PVUs inject both active and reactive power. The results demonstrate that PKO outperforms MSO and several metaheuristic algorithms reported in the literature. In Case 2, the optimal PVU penetration level of 67.17% significantly reduces TRPL compared with Case 1. The effectiveness of this optimized penetration level is further evaluated by comparing it with four other penetration levels: 25%, 50%, 75%, and 100%. PKO is then used to optimize the 24 h energy cost considering load variation and dynamic PV generation during four months of the year, including December, September, June, and March, which are ordered by increasing solar radiation across seasons under Vietnam’s climatic conditions. The results show that although the 75% penetration level slightly reduces the energy purchasing cost compared with the optimal level, it requires higher power capacity. Therefore, the optimized penetration level of 67.17% provides a balanced solution for reducing power losses while maintaining economic efficiency. Full article

This paper addresses the optimal management of photovoltaic (PV) systems and distribution static synchronous compensators (D-STATCOMs) in modern electrical distribution networks. A mixed-integer nonlinear programming (MINLP) model is formulated which co-optimizes device placement, sizing, and multi-period dispatch to minimize the total annualized system costs while satisfying AC power flow and operational constraints. To solve this challenging problem, a decomposition methodology is proposed, wherein the binary location decisions for the PVs and D-STATCOMs are treated as predefined inputs, upon the basis of site selections commonly reported in the literature. With the integer variables fixed, the problem is reduced to a continuous nonlinear programming (NLP) subproblem for optimal capacity sizing and operational scheduling, which is solved using the interior point optimizer (IPOPT) via the Julia/JuMP environment. The core contribution of this work lies in its comprehensive demonstration of the economic superiority of variable reactive power injection over conventional fixed compensation schemes. Through numerical validation on standard 33- and 69-bus test systems, it is shown that a variable D-STATCOM operation yields substantial and consistent economic gains. Compared to optimized fixed-injection solutions, variable injection provides additional annual savings averaging USD 120,516 (33-bus feeder) and USD 125,620 (69-bus grid), corresponding to a further 3.4% reduction in total costs. These benefits prove robust across different device location sets identified by various metaheuristic algorithms, and they scale effectively to larger network topologies. The results demonstrate that transitioning to variable power injection is not merely an incremental improvement but a fundamental advancement for achieving techno-economic optimality in distribution system planning. The proposed methodology provides utilities with a computationally efficient framework for determining near-optimal PV and D-STATCOM management strategies by first fixing deployment locations based on established planning insights and then rigorously optimizing sizing and dispatch, in order to maximize economic returns while ensuring reliable network operation. Full article

Marek’s disease (MD), caused by pathogenic Marek’s disease virus serotype 1 (MDV-1), is one of the most important avian immunosuppressive and neoplastic diseases and has led to huge economic losses to the poultry industry worldwide. Rapid and accurate clinical diagnosis is of great significance for efficient control of the disease. Herein, we have established a multiplex PCR (mPCR) method to simply differentiate all of the three types of MDV, using five specific primers targeting to MDV-1 oncogene meq or MDV-2 and MDV-3/HVT gB genes. Simultaneously, it can detect any type of virulent or vaccine MDV strains in one PCR reaction, with amplicons of the short (S) and long (L)-meq of MDV-1 strains, and the gB of MDV-2 and HVT vaccine strains. Non-specific amplifications of avian leukosis virus (ALV), reticuloendotheliosis virus (REV), or fowl adenovirus virus 4 (FAdV-4) were not observed, indicating a good specificity of this method. A total of 522 clinical samples of tumor-bearing or suspected diseased birds collected from 30 poultry farms were detected. The results demonstrated that the newly developed mPCR method accurately detected and differentiated epidemic MDV-1 infections and vaccine strains, and provided nearly 100% consistency for detecting clinical wild-type infections compared with conventional PCR amplification of the meq gene. Collectively, our data has provided a highly efficient method for early differential diagnosis of MD clinical cases, virus identification and future evaluation of vaccination efficacy in healthy chicken flocks, which would be meaningful for efficient control of the disease. Full article

Monitoring oil pipelines is crucial for effective infrastructure management and maintenance, as it helps prevent threats such as vandalism and leaks that can lead to catastrophic events. Pipeline leaks pose significant environmental and economic risks; however, existing detection methods are often expensive, slow, or unreliable, limiting their effectiveness for real-time applications. This study proposes a lightweight thermal-imaging-based intelligent leak detection system that integrates Convolutional Neural Networks (CNN), Autoencoder (AE), and Knowledge Distillation (KD), suitable for deployment on edge devices. The proposed system addresses challenges associated with existing pipeline detection techniques, including large model sizes, high transmission latency, and excessive energy consumption. Thermal images of pipelines are captured and compressed using an autoencoder before being processed by a CNN model optimized through knowledge distillation. The model was trained and tested on a locally collected thermal image dataset and designed for deployment on edge devices such as Raspberry Pi to simulate edge computing scenarios. Experimental results demonstrate that the proposed CNN + KD + AE model achieved 98% accuracy, 98% precision, 98% recall, and an F1-score of 98%, outperforming baseline models such as MobileNetV2 (91%), InceptionV3 (84%), EfficientNet-Lite (81%), and ResNet (74%). Furthermore, the number of trainable parameters was significantly reduced to 1.18 million, with a compact model size of 4.51 MB. These findings confirm the system’s suitability for real-time leak detection in remote and resource-constrained environments, contributing to the development of cost-effective, scalable, and energy-efficient solutions for intelligent pipeline monitoring. Full article

Wastewater heat recovery has emerged as a vital strategy for building energy conservation, due to its significant potential and the inherent thermal stability of sewage as a heat source. Enhancing synergy between such waste heat and other clean energy sources is a key research focus. This study developed a solar-assisted sewage-source coupled heating system for a Chinese university dormitory and established a multiobjective optimization framework integrating economic, environmental, and energy efficiency indicators via a combined weighting approach of the Analytic Hierarchy Process and Entropy Weight Method. Optimization was conducted using the Hooke–Jeeves algorithm, Particle Swarm Optimization algorithm, and the Hooke–Jeeves–Particle Swarm Optimization hybrid algorithm (shorten as HJ–PSO), with subsequent comparative performance analysis. The HJ–PSO hybrid performed best: 24% lower operating costs, a 4.8-year shorter dynamic payback period, 26.35% fewer carbon dioxide emissions, 38.65% lower overall energy consumption, and an 11.18% higher system coefficient of performance. Supported by relevant policies, the system is low-carbon and economically viable, enabling grid peak shaving. This research provides theoretical and engineering references for renewable energy heating systems. Full article

Large-section tunnels produce a large amount of dust after drill-and-blast construction. If not removed in a timely manner, the dust will seriously endanger workers’ health. For the purpose of enhancing the working conditions within the tunnel during construction, this investigation employs an integrated methodology that combines computational simulations with on-site measurements. Drawing upon the principles of gas–solid two-phase flow theory, the coupled diffusion law of airflow and dust in large-section tunnels is investigated. A two-factor orthogonal experiment combined with economic analysis is employed to determine the optimal ventilation parameters for the forced ventilation system. The findings indicate that, when the initial ventilation configuration is applied, the airflow field is divided into three stages, and dust diffusion is primarily driven by airflow. The average dust concentration in the 1.6 m breathing zone at 600 s post-blasting is measured to be 36.8 mg/m³. While satisfying the ventilation demand stipulated for the tunnel, the optimal ventilation parameters are determined as an outlet air velocity of 18 m/s and a duct-to-face distance of 40 m. Under these conditions, the dust concentration is reduced to 1.5 mg/m³, representing a 95.9% improvement in dust removal efficiency. Additionally, the hourly electricity cost at 18 m/s is USD 4.39 lower than that at 20 m/s. This study provides valuable insights for optimizing forced ventilation parameters in large-section tunnels, significantly reducing pollutant levels while saving costs. Full article

Background: Stroke remains a significant health and economic challenge both globally and in the Czech Republic. Although a structured network of specialized stroke centres exists, comparative data on patient outcomes and healthcare costs across hospital types are still lacking in the Czech context. This study analyzed real-world administrative data to assess 90-day mortality and healthcare costs after ischemic stroke, categorized by intervention and provider type. Methods: Claims data from six Czech health insurance companies, covering approximately 44% of the population, were used for the years 2017–2020. Patients aged 18 and older with a primary diagnosis of ischemic stroke (ICD-10 code I63) were included. Interventions were categorized as thrombectomy, thrombolysis, or other treatment, and providers were classified as comprehensive stroke centres (CSCs), primary stroke centres (PSCs), secondary referral hospitals (SRHs), or others. Costs were calculated from the payer perspective using administrative claims data, and standardized 90-day mortality and effective cost per survivor (ECPS) were computed. Funnel plots were used to evaluate provider variability in outcomes and costs. The analysis included 23,568 patients (47% female; mean age 70.6). Results: Thrombectomy was associated with the highest mean costs (€13,385), the highest 90-day mortality (29.3%), and the highest ECPS (€18,880). Patients receiving other treatments had the lowest costs (€2725) and lower mortality (14.4%). CSCs recorded the highest average costs (€5087) and mortality (16.7%), while SRHs had the lowest costs (€2204) and mortality (13.7%). Funnel plots revealed greater variability in costs, mainly driven by primary hospitalization, while mortality rates showed less variation. Conclusions: These findings suggest that while stroke outcomes are relatively consistent across providers, costs differ, possibly reflecting efficiency differences and case-mix severity. The study is limited by the lack of clinical severity data, highlighting the need to link administrative data with clinical registries for more comprehensive future evaluations. Full article

This paper presents a technical and economic feasibility analysis of a microgrid based on an existing traction substation supplying a 3 kV DC railway network. The study is based on real 15-min electricity consumption measurements and applies an engineering-oriented methodology to assess the integration of distributed energy resources, including wind turbines, photovoltaic generation, and a battery energy storage system. The analysis focuses on component sizing, land-use constraints, and investment efficiency under conservative and transparent assumptions. The results demonstrate that traction substation-based microgrids are technically feasible under realistic environmental and spatial conditions. The conducted variant analysis reveals a clear trade-off between the number of installed wind turbines and the required photovoltaic installation area, highlighting the importance of generation redundancy and source diversification for infrastructure-critical applications. The energy storage system is designed as a reliability-oriented backup component, ensuring continuity of supply during primary power outages rather than serving as an optimization or arbitrage asset. From an economic perspective, the obtained investment efficiency indicators indicate that the proposed microgrid configuration can achieve acceptable performance for capital-intensive infrastructure assets, particularly when supported by appropriate financing conditions and policy instruments. Overall, the study confirms that traction substation-based microgrids constitute a viable solution for enhancing energy supply diversification, resilience, and decarbonization of railway power systems, while providing a transparent framework for early-stage decision-making. Full article

The progressive phase-out of coal-fired power plants in Portugal has significantly reduced the availability of fly ash (FA) as a supplementary cementitious material (SCM), reinforcing the need for sustainable alternatives. Waste glass powder (WGP), characterized by its high amorphous silica content, has emerged as a promising candidate; however, most studies focus on ultrafine particles or isolated performance indicators, lacking an integrated technical, environmental, and economic assessment. This study evaluates cement pastes incorporating 25% WGP (by volume) with different particle size distributions, including fineness levels comparable to cement and FA. Mechanical performance, grinding energy demand, carbon footprint, and cost were systematically analyzed. The results indicate that WGP is technically viable as an SCM, with a median particle size (D₅₀) of approximately 48 µm providing the most balanced performance. Although finer particles enhance pozzolanic reactivity, the associated increase in grinding energy and economic cost offsets these gains. The findings demonstrate that optimizing particle size, rather than maximizing fineness, enables a technically robust and industrially realistic use of WGP. This approach supports circular economic strategies and contributes to the decarbonization of the construction sector by identifying an efficient replacement pathway for FA under resource-scarcity conditions. Full article

This article integrates sustainability principles into a three-echelon supply chain for deteriorating items with imperfect quality, consisting of a single vendor, a third-party logistics enterprise (3PL), and a single buyer, with a focus on balancing economic efficiency with environmental responsibility. The vendor is assumed to operate an imperfect production system, resulting in products of imperfect quality. The 3PL undertakes all transportation activities, while the buyer conducts a quality inspection process to detect defective items, which is subject to Type-I and Type-II errors. Aside from that, the inventory model also assesses carbon emissions arising from various operational activities including energy usage during production, warehousing, and disposal processes, and fuel consumption in transportation, for which the above members of the supply chain are accountable. Afterward, carbon management policies such as a carbon tax and carbon cap-and-trade are considered to regulate total supply chain emissions. The objective is to minimize the joint expected total cost by simultaneously optimizing shipment frequencies and the replenishment cycle for the buyer within carbon emission constraints. An iterative solution procedure is developed to address the problem. A numerical example and sensitivity analysis are provided to demonstrate the model’s applicability and to explore the influence of critical parameters. Finally, the study presents managerial insights, along with conclusions and recommendations for future research directions. Full article