Search Results (546)

Faced with the access of a large number of devices, and for mobile vehicles with high speeds, some situations may be far from the communication range of the current edge node, resulting in a significant increase in communication latency and energy consumption. To ensure the effectiveness of task execution for mobile vehicles under high-speed conditions, this paper regards intelligent vehicles as edge nodes and establishes a dynamic offloading model in Vehicle-to-Vehicle (V2V) scenarios. A dynamic task offloading strategy based on optimal stopping theory is proposed to minimize the overall latency generated during the offloading process while ensuring the effectiveness of task execution. By analyzing the potential migration paths of tasks in V2V scenarios, we construct a dynamic migration model and design a migration benefit function, transforming the problem into an asset-selling problem in optimal stopping theory (OST). At the same time, it is proven that there exists an optimal stopping rule for the problem. Finally, the optimal migration threshold is determined by solving the optimal stopping rule through dynamic programming, guiding the task vehicle to choose the best target service vehicle. Comparisons between the proposed TMS-OST strategy and three other peer offloading strategies show that TMS-OST can significantly reduce the total offloading latency, select service vehicles with shorter distances using fewer detection attempts, guarantee service quality while lowering detection costs, and achieve high average offloading efficiency and average offloading distance efficiency. Full article

Background/Objectives: With the increasing global concern about diet-related diseases associated with the consumption of ultra-processed foods (UPFs), there is an urgent need for practical and standardized tools to evaluate and monitor UPF intake. This study aimed to adapt and validate the Nova-UPF screener, a brief, food-based questionnaire originally developed in Brazil, for use among Portuguese adults. Methods: The adaptation process relied on data from the Portuguese National Food, Nutrition and Physical Activity Survey (IAN-AF 2015–2016) and was refined using the DELPHI methodology. A validation study was carried out with a convenience sample of 304 adults through an electronic questionnaire. Dietary intake was evaluated using a 24 h dietary recall. Criterion validity was assessed by examining the relationship between the Nova-UPF score and the percentage of total energy intake (TEI) from UPFs, while construct validity was evaluated based on predefined hypotheses. Agreement between quintiles of Nova-UPF score and quintiles of UPF contribution to TEI was tested using the prevalence and bias-adjusted kappa (PABAK) index. Results: The final Portuguese version of the Nova-UPF screener includes 25 subgroups. The Nova-UPF score was positively associated with the percentage of UPF contribution to TEI (B = 6.224, p < 0.001). Participants in the highest quintiles of the Nova-UPF score had higher TEI but lower consumption of monounsaturated and polyunsaturated fats, potassium, and dietary fibre. There was a near-perfect agreement between quintile classifications of UPF and Nova-UPF score (PABAK = 0.86). Conclusions: The Portuguese Nova-UPF screener is a valid, simple, and quick tool for evaluating UPF consumption and dietary quality in adults. Full article

This study comparatively evaluated the performance of three industrial broiler carcass chilling methods—air chilling, combination chilling (air and water spraying), and the Thor Ice ice-slurry system—under commercial processing conditions. A total of 90 Ross 308 carcasses were analyzed (30 per method, in three repetitions). Air chilling and Thor Ice chilling were conducted for 1 h 45 min at 4000 birds/h, whereas combination chilling lasted 3 h at 7200 birds/h. For each carcass, initial and final temperature and weight were recorded to determine chilling loss. Significant differences were observed among the methods (p < 0.05). Combination chilling achieved the lowest final temperature (1.4 °C), while Thor Ice chilling resulted in the smallest chilling loss (−0.47%). The analysis of energy consumption revealed that air chilling had the highest electrical energy use (15,491.6 kWh/h), whereas the Thor Ice system had a lower energy demand (13,511.2 kWh/h). Combination chilling exhibited the highest water consumption (413.7 m³), reflecting the use of water spraying. Based on these findings, combination chilling was the most effective in reducing carcass temperature, while the Thor Ice system provided a technologically efficient alternative with minimal mass loss and reduced energy demand. Full article

This study addresses the fabrication challenges associated with producing diverse geometries for concrete dry connections, particularly regarding cost, time, and geometric limitations. The research investigates methods for fabricating precise, rebar-free dry connections in concrete, focusing on stamping and green-state computer numerical control (CNC) milling. These methods are evaluated using metrics such as dimensional accuracy, tool abrasion, and energy consumption. In the stamping process, a design of experiments (DOE) approach varied water content, concrete age, stamping load, and operational factors (vibration and formwork) across cone, truncated cone, truncated pyramid, and pyramid geometries. An optimal age range of 90 to 105 min, within a broader operational window of 90 to 120 min, was identified. Geometry-specific exceptions, such as approximately 68 min for the truncated cone and 130 min for the pyramid, were attributed to interactions between shape and age rather than deviations from general guidance. Within the tested parameters, water fraction primarily influenced lateral geometric error (diameter or width), while age most significantly affected vertical error. For green-state milling, both extrusion- and shotcrete-printed stock were machined at 90 min, 1 day, and 1 week. From 90 min to 1 week, the total milling energy increased on average by about 35%, and at one week end-face (head) passes caused substantially higher tool wear, with mean circumference losses of about 3.2 mm for head engagement and about 1.0 mm for side passes. Tool abrasion and energy demand increased with curing time, and extrusion required marginally more energy at equivalent ages. Milling was conducted in two engagement modes: side (flank) and end-face (head), which were evaluated separately. End-face engagement resulted in substantially greater tool abrasion than side passes, providing a clear explanation for tolerance drift in final joint geometries. Additionally, soil-based forming, which involves imprinting the stamp into soft, oil-treated fine sand to create a reversible mold, produced high-fidelity replicas with clean release for intricate patterns. This approach offers a practical alternative where friction and demolding constraints limit the effectiveness of direct stamping. Full article

This study addresses a critical gap in Energy-Efficient Permutation Flow Shop Scheduling (EPFSP) by integrating the often-overlooked time-accumulative equipment degradation inherent in practical manufacturing. This research formalizes and solves the EPFSP with machine deterioration (EPFSP-DEM), aiming to simultaneously minimize the makespan and total energy consumption. To achieve this objective, this study proposes a Diversity-Constrained Imperialist Competitive Algorithm (DCICA) featuring several novel mechanisms. In DCICA, a differentiated assimilation is developed to improve diversity of the population; a knowledge-guided revolution is designed to allocate computing resources efficiently; the convergence and diversity metrics are defined to evaluate the search quality on assimilation and revolution; a novel imperialist competition is also given to enhance information exchanges among empires and strengthen the search for some worse solutions. Finally, extensive experiments are conducted, and the results demonstrate that DCICA outperforms the existing algorithms in solving the investigated problem. Full article

The utilization of treated dredged sludge as a partial replacement for natural sand and gravel in construction projects offers a promising approach to reducing the exploitation of natural resources. The conventional vacuum preloading (VP) method, while widely used for soft soil improvement, is often associated with prolonged consolidation periods and high energy consumption in its later stages. Conversely, the electroosmosis (EO) technique is effective in enhancing drainage in low-permeability soft clays but is constrained by issues including anode corrosion, high operational costs, and uneven soil reinforcement. This study presents an experimental investigation into an alternating vacuum preloading and electroosmosis method for sludge treatment based on the underlying reinforcement theory. A series of laboratory model tests was conducted using a self-made vacuum–electroosmosis alternating test device. The reinforcement efficiency was assessed through the continuous monitoring of key performance indicators during the tests, including water discharge, surface settlement, electric current, electrode corrosion, and energy consumption. Post-test evaluations of the final soil shear strength and moisture content were also performed. The test results demonstrate that the alternating vacuum–electroosmosis yielded more significant improvement than their synchronous application. Specifically, the alternating vacuum–electroosmosis increased total water discharge by 46.1%, reduced final moisture content by 20.8%, and enhanced shear strength by 35.6% relative to the synchronous mode. Furthermore, an alternating VP-EO mode was found to be particularly advantageous during the electroosmosis phases, facilitating a more stable and sustained dewatering process. In contrast, the application of vacuum preloading alone resulted in inefficient performance during the later stages, coupled with relatively high energy consumption. Full article

Energy used in residential buildings accounts for more than 22% of total global energy consumption. Therefore, energy efficiency has become a crucial factor in design and planning processes. A courtyard can be considered one of the most important passive design strategies that contribute to reducing energy consumption. However, due to the spread of multi-story buildings all over the world, this significant strategy has been ignored, hence the emergence of the skycourt. Limited studies have investigated the influence of morphological indicators of skycourts on energy consumption and carbon emissions regarding a hot–humid climate, which presents a research gap. Thus, this research examines the effect of skycourts in reducing energy consumption through an applied study using the Design Builder simulation program for multi-story residential buildings in a hot–humid climate such as Port Said city. The results indicate that skycourt spaces contribute significantly to reducing air temperature by up to 3 °C in the hottest summers and contribute to reducing energy consumption by rates ranging between 8 and 10% annually and reducing carbon emissions. This reflects the role of the skycourt as one of the most important passive design strategies in the current era that can contribute to saving energy consumption in the building sector. Finally, a matrix is conducted to help select the appropriate replacement for the skycourt of multi-story residential buildings in hot–humid climates, which reflects the novelty of the research. The proposed investigations and matrix can contribute to providing well-being, sustainable communities, and overcoming climate change effects, hence reflecting sustainability and the Sustainable Development Goals (SDGs), especially goals three, eleven, and thirteen. Full article

With the rapid increase in plastic consumption, waste polypropylene (WPP) has become one of the major components of municipal solid waste, posing significant environmental and resource challenges. According to statistics, polypropylene accounts for approximately 19.1% of the total global plastic waste, posing significant environmental challenges. In recent years, the recycling and reuse of WPP in asphalt pavement materials have received increasing attention due to its excellent mechanical properties, thermal stability, and low cost. This review systematically summarizes the physicochemical properties and recycling technologies of WPP, including mechanical, chemical, and energy recovery routes. Furthermore, the modification mechanisms, preparation methods, and performance characteristics of WPP-modified asphalt binders and mixtures are comprehensively discussed, focusing on their high-temperature stability, compatibility, low-temperature cracking resistance, and anti-moisture damage. Research indicates that WPP modification significantly enhances high-temperature rutting resistance, and thermo-chemical modifiers have successfully enabled the application of WPP in warm-mix asphalt. This review uniquely integrates recent advances in thermo-mechanochemical upcycling with mixture-level performance, bridging molecular design and field application. However, critical challenges, including poor compatibility, insufficient storage stability, and the lack of a unified assessment for the high variability of WPP raw materials, still need to be addressed. Finally, this review primarily focuses on the recycling technologies of WPP, its modification mechanisms in asphalt binders, and the resulting impact on the pavement performance of WPP-modified mixtures. Full article

Production scheduling that involves distributed factories, machine maintenance, and resource constraints plays a crucial role in manufacturing. However, these realistic constraints have rarely been considered simultaneously in the hybrid flow shop (HFS). To address this issue, a distributed resource-constrained hybrid flow shop scheduling problem with machine breakdowns (DRCHFSP-MB) is studied. There are two optimization objectives, i.e., makespan and total energy consumption (TEC). To solve the strongly NP-hard problem, a mathematical model is established and a block–neighborhood-based multi-objective evolutionary algorithm (BNMOEA) is developed. In the proposed algorithm, an efficient hybrid initialization method is adopted to obtain high-quality individuals to participate in the evolutionary process of the population. Next, to enhance the search capability of the BNMOEA, three well-designed crossover operators are used in the global search. Then, the convergence of the proposed algorithm is improved by utilizing eight critical factory-based local search operators combined with block–neighborhood. Finally, the BNMOEA is compared with several of the most advanced multi-objective algorithms; the results indicate that the BNMOEA has an outstanding performance in solving DRCHFSP-MB. Full article

This paper presents a comprehensive economic comparison between renewable and fossil-fuel-based heating systems for a newly constructed residential building in Kraków, Poland, over the period 2022–2030. The analysis introduces the concept of Corrected Final Energy Consumption (CFEC) as a harmonized measure for comparing various energy sources and applies the Present Value of Total Lifecycle Cost (PVTLC) as an appropriate financial metric for non-commercial residential investments. Four heating options were examined: district heating system (DHS), gas boiler, air-to-water heat pump, and heat pump combined with photovoltaic (PV) panels. Based on real tariffs and standardized data from the Energy Performance Certificate (EPC), the DHS option demonstrated the lowest lifecycle cost, while the air-to-water heat pump—despite environmental advantages—proved the most expensive without substantial subsidies. Sensitivity analyses confirmed the strong influence of investment subsidies and fuel price fluctuations on the competitiveness of alternative systems. The findings highlight the methodological shortcomings of conventional annual-cost approaches and propose PVTLC as a more reliable decision-making tool for residential energy planning. The study also discusses regulatory, climatic, and behavioral factors affecting investment outcomes and emphasizes the need to integrate financial, environmental, and social criteria when evaluating household-level energy solutions. Full article

With the rapid advancement of battery technology, new energy hybrid tugboats have been progressively adopted. In order to align with the trend of electrifying tugboat fleets, a mixed-integer linear programming (MILP) model for the joint scheduling of new energy hybrid tugboats and berths has been established. The model incorporates the constraint imposed by the limited number of tugboat charging connectors. The objective is to minimize the total cost over the scheduling horizon, including ship waiting, delayed-departure costs, and the operating costs of both conventional diesel and hybrid tugboats. In light of the characteristics inherent to the problem, a hybrid solution approach combining CPLEX with a heuristic-enhanced whale optimization algorithm (WOA) is employed to solve the model. A case study was conducted using data on the energy consumption of tugboats at Xiamen Port. The effectiveness of the model and algorithm was then verified through a series of small-scale instance experiments. Finally, a comprehensive sensitivity analysis of key parameters is finally conducted, including the number of tugboat charging connectors, battery capacity, and charging rate. This analysis provides valuable guidance for port tugboat operations. Full article

Under the environment of globalized energy restructuring and achieving the goal of “peak carbon and carbon neutrality”, this paper proposes an optimal scheduling method based on the improved cosine algorithm for island microgrids, which relies on diesel generators, resulting in high carbon emissions and high operating costs. First, an optimal scheduling model for island microgrids is established with the objective of minimizing the system operating cost, which comprehensively considers the carbon emission penalty, power balance constraints, equipment operation constraints, and the volatility of renewable energy sources. Secondly, the traditional sine–cosine algorithm is improved by introducing an adaptive adjustment factor, elite retention strategy and chaotic mapping initialization population in order to solve its shortcomings of falling into local optimums and insufficient convergence accuracy when solving high-dimensional complex problems. Finally, the effectiveness of the proposed method is verified by simulation experiments. The results show that the method in this paper reduces the total system cost to 2994.2 yuan (6.5% lower than the baseline scenario), reduces the carbon emission to 968.8 kg (55.1% lower), and improves the wind and light consumption rate to 98.84%, which is an obvious advantage and provides a theoretical basis and technical support for the realization of the low-carbon and economic operation of island microgrids. Full article

The multi-microgrid integrated energy system (MM-IES) plays a vital role in enhancing energy utilization efficiency and promoting the coordinated consumption of renewable energy. However, the realization of low-carbon dispatch in MM-IES is hindered by multi-energy coupling and the need for distributed coordination under increasingly stringent carbon emission constraints. To address these issues, a distributed scheduling strategy that integrates demand response and green certificate trading mechanisms is proposed. Firstly, a low-carbon integrated energy microgrid (IEM) model integrating carbon capture and storage (CCS) and power-to-gas (P2G) technologies is proposed to improve the system’s low-carbon regulation capability and mitigate the impact of multi-energy coupling in MM-IES. This integration enhances the system’s low-carbon regulation capability. Secondly, to incentivize user participation in system optimization, a demand response mechanism and a tiered green certificate trading model are introduced. On this basis, an MM-IES low-carbon economic dispatch model is established with the goal of minimizing total operating costs, carbon trading costs, and green certificate trading costs. To further protect the privacy of each microgrid and achieve efficient coordination, distributed algorithms are used to solve the model. This method only requires exchanging boundary information to achieve collaborative optimization between microgrids. Finally, the simulation results indicate that the proposed strategy can effectively reduce system operating costs and carbon emissions. Furthermore, the effectiveness of demand response and green certificate trading in promoting low-carbon economic operation of multi microgrid systems is verified. Full article

Accurate forecasting of carbon emissions is not only essential for addressing the challenges of climate governance but also provides timely support for dynamic carbon quota adjustments and emergency emission reduction decisions. In this study, we take China’s daily carbon emission data from 2021 to 2024 as the research objects and propose a novel forecasting framework called STL-wLSTM-SVR based on seasonal-trend decomposition with Loess (STL), long short-term memory network (LSTM) and support vector regression (SVR). First, the original carbon emission sequence is decomposed via STL into seasonal, trend and residual components. Subsequently, LSTM is employed to predict the seasonal and trend components with hyper-parameters optimized by whale optimization algorithm (WOA), and SVR is used to predict the residual component with parameters optimized through grid search method. Then, the final results are obtained by accumulating the forecasted values of the three subsequences. The experimental results illustrate that the STL-wLSTM-SVR model achieved a high-precision forecast for China’s total daily carbon emissions (RMSE of 0.1129, MAPE of 0.28%, MAE of 0.0851) and demonstrated remarkable adaptability for five major sectors—from navigating the high volatility of ground transport (MAPE of 0.36%) to effectively handling the dramatic post-pandemic structural break in aviation (MAPE of 0.72%). These findings assess the effectiveness of the hybrid forecasting framework and provide a valuable methodological reference for similar prediction tasks, such as sector-specific pollutant emissions and regional energy consumption. Full article

The system analysis method is suitable for detecting the optimal pathways for regional sustainable (e.g., green, low carbon) socioeconomic development. This study develops an inexact fractional energy–output–water–carbon nexus system planning model to minimize total carbon emission intensity (CEI, total carbon emissions/total economic output) under a set of nexus constraints. Superior to related research, the model (i) proposes a CEI considering both sectoral intermediate use (indirect) and final use (direct); (ii) quantifies the dependencies among energy, output, water, and carbon; (iii) restricts water utilization for carbon emission mitigation; (iv) adopts diverse mitigation measures to achieve carbon neutrality; (v) handles correlative chance-constraints and crisp credibility-constraints. A case in Fujian province (in China) is conducted to verify its feasibility. Results disclose that the total CEI would fluctuate between 45.05 g/CNY and 47.67 g/CNY under uncertainties. The annual total energy and total output would, on average, increase by 0.58% and 2.82%, respectively. Eight mitigation measures would be adopted to reduce the final carbon emission into the air to 0 by 2060. Compared with 2025, using water for carbon emission mitigation would increase 17-fold by 2060. For inland regions, authorities should incorporate other unconventional water sources. In addition, the coefficients of embodied energy consumption and water utilization are the most critical parameters. Full article