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16 pages, 5546 KiB  
Article
Modification of Vegetation Structure and Composition to Reduce Wildfire Risk on a High Voltage Transmission Line
by Tom Lewis, Stephen Martin and Joel James
Fire 2025, 8(8), 309; https://doi.org/10.3390/fire8080309 - 5 Aug 2025
Abstract
The Mapleton Falls National Park transmission line corridor in Queensland, Australia, has received a number of vegetation management treatments over the last decade to maintain and protect the infrastructure and to ensure continuous electricity supply. Recent treatments have included ‘mega-mulching’ (mechanical mastication of [...] Read more.
The Mapleton Falls National Park transmission line corridor in Queensland, Australia, has received a number of vegetation management treatments over the last decade to maintain and protect the infrastructure and to ensure continuous electricity supply. Recent treatments have included ‘mega-mulching’ (mechanical mastication of vegetation to a mulch layer) in 2020 and targeted herbicide treatment of woody vegetation, with the aim of reducing vegetation height by encouraging a native herbaceous groundcover beneath the transmission lines. We measured vegetation structure (cover and height) and composition (species presence in 15 × 2 m plots), at 12 transects, 90 m in length on the transmission line corridor, to determine if management goals were being achieved and to determine how the vegetation and fire hazard (based on the overall fuel hazard assessment method) varied among the treated corridor, the forest edge environment, and the natural forest. The results showed that vegetation structure and composition in the treated zones had been modified to a state where herbaceous plant species were dominant; there was a significantly (p < 0.05) higher native grass cover and cover of herbs, sedges, and ferns in the treated zones, and a lower cover of trees and tall woody plants (>1 m in height) in these areas. For example, mean native grass cover and the cover of herbs and sedges in the treated areas was 10.2 and 2.8 times higher, respectively, than in the natural forest. The changes in the vegetation structure (particularly removal of tall woody vegetation) resulted in a lower overall fuel hazard in the treated zones, relative to the edge zones and natural forest. The overall fuel hazard was classified as ‘high’ in 83% of the transects in the treated areas, but it was classified as ‘extreme’ in 75% of the transects in the adjacent forest zone. Importantly, there were few introduced species recorded. The results suggest that fuel management has been successful in reducing wildfire risk in the transmission corridor. Temporal monitoring is recommended to determine the frequency of ongoing fuel management. Full article
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18 pages, 3140 KiB  
Article
Spatial and Temporal Distribution of Conversational and Emerging Pollutants in Fecal Sludge from Rural Toilets, China
by Lin Lin, Yilin Shen, Guoji Ding, Shakib Alghashm, Seinn Lei Aye and Xiaowei Li
Sustainability 2025, 17(15), 7088; https://doi.org/10.3390/su17157088 - 5 Aug 2025
Abstract
Effective management of fecal pollutants in rural sanitation is crucial for environmental health and public safety, especially in developing regions. In this study, temporal and regional variations in nutrient elements, heavy metals, pathogenic microorganisms (PMs), and antibiotic resistance genes (ARGs) of fecal samples [...] Read more.
Effective management of fecal pollutants in rural sanitation is crucial for environmental health and public safety, especially in developing regions. In this study, temporal and regional variations in nutrient elements, heavy metals, pathogenic microorganisms (PMs), and antibiotic resistance genes (ARGs) of fecal samples from rural toilets in China were investigated. The moisture contents of the fecal samples average 92.7%, decreasing seasonally from 97.4% in summer to 90.6% in winter. The samples’ pH values range from 6.5 to 7.5, with a slight decrease in winter (6.8), while their electrical conductivity varies from 128.1 to 2150 μs/cm, influenced by regional diets. Chromium (9.0–49.7 mg/kg) and copper (31.9–784.4 mg/kg) levels vary regionally, with higher concentrations in Anhui and Guangxi Provinces due to dietary and industrial factors. Zinc contents range from 108.5 to 1648.9 mg/kg, with higher levels in autumn and winter, resulting from agricultural practices and Zn-containing fungicides, posing potential health and phytotoxicity risks. Seasonal and regional variations in PMs and ARGs were observed. Guangxi Province shows the high PM diversity in summer samples, while Jiangsu Province exhibits the high ARGs types in autumn samples. These findings highlight the need for improved waste management and sanitation solutions in rural areas to mitigate environmental risks and protect public health. Continued research in these regions is essential to inform effective sanitation strategies. Full article
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51 pages, 4099 KiB  
Review
Artificial Intelligence and Digital Twin Technologies for Intelligent Lithium-Ion Battery Management Systems: A Comprehensive Review of State Estimation, Lifecycle Optimization, and Cloud-Edge Integration
by Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou and Khay See
Batteries 2025, 11(8), 298; https://doi.org/10.3390/batteries11080298 - 5 Aug 2025
Abstract
The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery [...] Read more.
The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article
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22 pages, 3217 KiB  
Article
A Deep Reinforcement Learning Approach for Energy Management in Low Earth Orbit Satellite Electrical Power Systems
by Silvio Baccari, Elisa Mostacciuolo, Massimo Tipaldi and Valerio Mariani
Electronics 2025, 14(15), 3110; https://doi.org/10.3390/electronics14153110 - 5 Aug 2025
Abstract
Effective energy management in Low Earth Orbit satellites is critical, as inefficient energy management can significantly affect mission objectives. The dynamic and harsh space environment further complicates the development of effective energy management strategies. To address these challenges, we propose a Deep Reinforcement [...] Read more.
Effective energy management in Low Earth Orbit satellites is critical, as inefficient energy management can significantly affect mission objectives. The dynamic and harsh space environment further complicates the development of effective energy management strategies. To address these challenges, we propose a Deep Reinforcement Learning approach using Deep-Q Network to develop an adaptive energy management framework for Low Earth Orbit satellites. Compared to traditional techniques, the proposed solution autonomously learns from environmental interaction, offering robustness to uncertainty and online adaptability. It adjusts to changing conditions without manual retraining, making it well-suited for handling modeling uncertainties and non-stationary dynamics typical of space operations. Training is conducted using a realistic satellite electric power system model with accurate component parameters and single-orbit power profiles derived from real space missions. Numerical simulations validate the controller performance across diverse scenarios, including multi-orbit settings, demonstrating superior adaptability and efficiency compared to conventional Maximum Power Point Tracking methods. Full article
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17 pages, 909 KiB  
Review
Potential of Natural Esters as Immersion Coolant in Electric Vehicles
by Raj Shah, Cindy Huang, Gobinda Karmakar, Sevim Z. Erhan, Majher I. Sarker and Brajendra K. Sharma
Energies 2025, 18(15), 4145; https://doi.org/10.3390/en18154145 - 5 Aug 2025
Abstract
As the popularity of electric vehicles (EVs) continues to increase, the need for effective and efficient driveline lubricants and dielectric coolants has become crucial. Commercially used mineral oils or synthetic ester-based coolants, despite performing satisfactorily, are not environmentally friendly. The fatty esters of [...] Read more.
As the popularity of electric vehicles (EVs) continues to increase, the need for effective and efficient driveline lubricants and dielectric coolants has become crucial. Commercially used mineral oils or synthetic ester-based coolants, despite performing satisfactorily, are not environmentally friendly. The fatty esters of vegetable oils, after overcoming their shortcomings (like poor oxidative stability, higher viscosity, and pour point) through chemical modification, have recently been used as potential dielectric coolants in transformers. The benefits of natural esters, including a higher flash point, breakdown voltage, dielectric character, thermal conductivity, and most importantly, readily biodegradable nature, have made them a suitable and sustainable substitute for traditional coolants in electric transformers. Based on their excellent performance in transformers, research on their application as dielectric immersion coolants in modern EVs has been emerging in recent years. This review primarily highlights the beneficial aspects of natural esters performing dual functions—cooling as well as lubricating, which is necessary for “wet” e-motors in EVs—through a comparative study with the commercially used mineral and synthetic coolants. The adoption of natural fatty esters of vegetable oils as an immersion cooling fluid is a significant sustainable step for the battery thermal management system (BTMS) of modern EVs considering environmental safety protocols. Continued research and development are necessary to overcome the ongoing challenges and optimize esters for widespread use in the rapidly expanding electric vehicle market. Full article
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23 pages, 5135 KiB  
Article
Strategic Multi-Stage Optimization for Asset Investment in Electricity Distribution Networks Under Load Forecasting Uncertainties
by Clainer Bravin Donadel
Eng 2025, 6(8), 186; https://doi.org/10.3390/eng6080186 - 5 Aug 2025
Abstract
Electricity distribution systems face increasing challenges due to demand growth, regulatory requirements, and the integration of distributed generation. In this context, distribution companies must make strategic and well-supported investment decisions, particularly in asset reinforcement actions such as reconductoring. This paper presents a multi-stage [...] Read more.
Electricity distribution systems face increasing challenges due to demand growth, regulatory requirements, and the integration of distributed generation. In this context, distribution companies must make strategic and well-supported investment decisions, particularly in asset reinforcement actions such as reconductoring. This paper presents a multi-stage methodology to optimize reconductoring investments under load forecasting uncertainties. The approach combines a decomposition strategy with Monte Carlo simulation to capture demand variability. By discretizing a lognormal probability density function and selecting the largest loads in the network, the methodology balances computational feasibility with modeling accuracy. The optimization model employs exhaustive search techniques independently for each network branch, ensuring precise and consistent investment decisions. Tests conducted on the IEEE 123-bus feeder consider both operational and regulatory constraints from the Brazilian context. Results show that uncertainty-aware planning leads to a narrow investment range—between USD 55,108 and USD 66,504—highlighting the necessity of reconductoring regardless of demand scenarios. A comparative analysis of representative cases reveals consistent interventions, changes in conductor selection, and schedule adjustments based on load conditions. The proposed methodology enables flexible, cost-effective, and regulation-compliant investment planning, offering valuable insights for utilities seeking to enhance network reliability and performance while managing demand uncertainties. Full article
(This article belongs to the Section Electrical and Electronic Engineering)
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18 pages, 7363 KiB  
Article
Agronomic Evaluation of Compost Formulations Based on Mining Tailings and Microbial Mats from Geothermal Sources
by María Jesús Puy-Alquiza, Miren Yosune Miranda Puy, Raúl Miranda-Avilés, Pooja Vinod Kshirsagar and Cristina Daniela Moncada Sanchez
Recycling 2025, 10(4), 156; https://doi.org/10.3390/recycling10040156 - 5 Aug 2025
Abstract
This study, conducted in Mexico, evaluates the agricultural potential of three compost formulations BFS1, BFS2, and BFS3 produced from mining tailings and thermophilic microbial mats and collected from geothermal environments. The physicochemical characterization included pH, electrical conductivity (EC), macronutrients (N, P, K, Ca, [...] Read more.
This study, conducted in Mexico, evaluates the agricultural potential of three compost formulations BFS1, BFS2, and BFS3 produced from mining tailings and thermophilic microbial mats and collected from geothermal environments. The physicochemical characterization included pH, electrical conductivity (EC), macronutrients (N, P, K, Ca, Mg, and S), micronutrients (Fe, Zn, B, Cu, Mn, Mo, and Ni), organic matter (OM), and the carbon-to-nitrogen (C/N) ratio. All composts exhibited neutral pH values (7.38–7.52), high OM content (38.5–48.4%), and optimal C/N ratios (10.5–13.9), indicating maturity and chemical stability. Nitrogen ranged from 19 to 21 kg·t−1, while potassium and calcium were present in concentrations beneficial for crop development. However, EC values (3.43–3.66 dS/m) and boron levels (>160 ppm) were moderately high, requiring caution in saline soils or with boron-sensitive crops. A semi-quantitative Compost Quality Index (CQI) ranked BFS3 highest due to elevated OM and potassium content, followed by BFS1. BFS2, while rich in nitrogen, scored lower due to excessive boron. One-way ANOVA revealed no significant difference in nitrogen (p > 0.05), but it did reveal significant differences in potassium (p < 0.01) and boron (p < 0.001) among formulations. These results confirm the potential of mining tailings—microbial mat composts are low-cost, nutrient-rich biofertilizers. They are suitable for field crops or as components in nursery substrates, particularly when EC and boron are managed through dilution. This study promotes the circular reuse of geothermal and industrial residues and contributes to sustainable soil restoration practices in mining-affected regions through innovative composting strategies. Full article
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11 pages, 1342 KiB  
Review
Review of Neurostimulation Therapies for Obstructive Sleep Apnea: Hypoglossal Nerve Stimulation and Beyond
by Patrícia dos Santos Cé, Maria Eduarda Schiestl Melo, Alan Alves Machado, Sarah Eden Ridge and Thomaz Fleury Curado
J. Clin. Med. 2025, 14(15), 5494; https://doi.org/10.3390/jcm14155494 - 4 Aug 2025
Abstract
Obstructive sleep apnea (OSA) is a sleep-related respiratory disorder characterized by partial or complete obstruction of the upper airway, typically resulting in a decrease in arterial oxygen saturation and repeated awakenings from sleep. It is the most common sleep-related respiratory disorder, affecting 9% [...] Read more.
Obstructive sleep apnea (OSA) is a sleep-related respiratory disorder characterized by partial or complete obstruction of the upper airway, typically resulting in a decrease in arterial oxygen saturation and repeated awakenings from sleep. It is the most common sleep-related respiratory disorder, affecting 9% to 38% of adults. OSA is associated with loss of tone, improper contraction of the tongue, and pharyngeal dilator muscles of the upper airway during sleep. The gold-standard treatment for moderate-to-severe OSA is continuous positive airway pressure (CPAP). However, many patients have poor long-term compliance with CPAP. Stimulation of the upper airway with electrical activation of the hypoglossal nerve has emerged as a promising treatment for patients with moderate-to-severe OSA who have failed CPAP therapy. Objectives: The present paper aims to review the literature regarding neurostimulation for the treatment of OSA. Conclusions: Hypoglossal nerve stimulation (HNS) has shown favorable success and low morbidity in the management of moderate-to-severe OSA. Full article
(This article belongs to the Special Issue Airway Management: From Basic Techniques to Innovative Technologies)
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33 pages, 3972 KiB  
Article
A Review and Case of Study of Cooling Methods: Integrating Modeling, Simulation, and Thermal Analysis for a Model Based on a Commercial Electric Permanent Magnet Synchronous Motor
by Henrry Gabriel Usca-Gomez, David Sebastian Puma-Benavides, Victor Danilo Zambrano-Leon, Ramón Castillo-Díaz, Milton Israel Quinga-Morales, Javier Milton Solís-Santamaria and Edilberto Antonio Llanes-Cedeño
World Electr. Veh. J. 2025, 16(8), 437; https://doi.org/10.3390/wevj16080437 - 4 Aug 2025
Abstract
The efficiency of electric motors is highly dependent on their operating temperature, with lower temperatures contributing to enhanced performance, reliability, and extended service life. This study presents a comprehensive review of state-of-the-art cooling technologies and evaluates their impact on the thermal behavior of [...] Read more.
The efficiency of electric motors is highly dependent on their operating temperature, with lower temperatures contributing to enhanced performance, reliability, and extended service life. This study presents a comprehensive review of state-of-the-art cooling technologies and evaluates their impact on the thermal behavior of a commercial motor–generator system in high-demand applications. A baseline model of a permanent magnet synchronous motor (PMSM) was developed using MotorCAD 2023® software, which was supported by reverse engineering techniques to accurately replicate the motor’s physical and thermal characteristics. Subsequently, multiple cooling strategies were simulated under consistent operating conditions to assess their effectiveness. These strategies include conventional axial water jackets as well as advanced oil-based methods such as shaft cooling and direct oil spray to the windings. The integration of these systems in hybrid configurations was also explored to maximize thermal efficiency. Simulation results reveal that hybrid cooling significantly reduces the temperature of critical components such as stator windings and permanent magnets. This reduction in thermal stress improves current efficiency, power output, and torque capacity, enabling reliable motor operation across a broader range of speeds and under sustained high-load conditions. The findings highlight the effectiveness of hybrid cooling systems in optimizing both thermal management and operational performance of electric machines. Full article
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50 pages, 9033 KiB  
Article
Heat Pipe Integrated Cooling System of 4680 Lithium–Ion Battery for Electric Vehicles
by Yong-Jun Lee, Tae-Gue Park, Chan-Ho Park, Su-Jong Kim, Ji-Su Lee and Seok-Ho Rhi
Energies 2025, 18(15), 4132; https://doi.org/10.3390/en18154132 - 4 Aug 2025
Abstract
This study investigates a novel heat pipe integrated cooling system designed for thermal management of Tesla’s 4680 cylindrical lithium–ion batteries in electric vehicles (EVs). Through a comprehensive approach combining experimental analysis, 1-D AMESim simulations, and 3-D Computational Fluid Dynamics (CFD) modeling, the thermal [...] Read more.
This study investigates a novel heat pipe integrated cooling system designed for thermal management of Tesla’s 4680 cylindrical lithium–ion batteries in electric vehicles (EVs). Through a comprehensive approach combining experimental analysis, 1-D AMESim simulations, and 3-D Computational Fluid Dynamics (CFD) modeling, the thermal performance of various wick structures and working fluid filling ratios was evaluated. The experimental setup utilized a triangular prism chamber housing three surrogate heater blocks to replicate the heat generation of 4680 cells under 1C, 2C, and 3C discharge rates. Results demonstrated that a blended fabric wick with a crown-shaped design (Wick 5) at a 30–40% filling ratio achieved the lowest maximum temperature (Tmax of 47.0°C), minimal surface temperature deviation (ΔTsurface of 2.8°C), and optimal thermal resistance (Rth of 0.27°C/W) under 85 W heat input. CFD simulations validated experimental findings, confirming stable evaporation–condensation circulation at a 40% filling ratio, while identifying thermal limits at high heat loads (155 W). The proposed hybrid battery thermal management system (BTMS) offers significant potential for enhancing the performance and safety of high-energy density EV batteries. This research provides a foundation for optimizing thermal management in next-generation electric vehicles. Full article
(This article belongs to the Special Issue Optimized Energy Management Technology for Electric Vehicle)
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17 pages, 6882 KiB  
Article
Development and Evaluation of a Solar Milk Pasteurizer for the Savanna Ecological Zones of West Africa
by Iddrisu Ibrahim, Paul Tengey, Kelci Mikayla Lawrence, Joseph Atia Ayariga, Fortune Akabanda, Grace Yawa Aduve, Junhuan Xu, Robertson K. Boakai, Olufemi S. Ajayi and James Owusu-Kwarteng
Solar 2025, 5(3), 38; https://doi.org/10.3390/solar5030038 - 4 Aug 2025
Abstract
In many developing African countries, milk safety is often managed through traditional methods such as fermentation or boiling over firewood. While these approaches reduce some microbial risks, they present critical limitations. Firewood dependency contributes to deforestation, depletion of agricultural residues, and loss of [...] Read more.
In many developing African countries, milk safety is often managed through traditional methods such as fermentation or boiling over firewood. While these approaches reduce some microbial risks, they present critical limitations. Firewood dependency contributes to deforestation, depletion of agricultural residues, and loss of soil fertility, which, in turn, compromise environmental health and food security. Solar pasteurization provides a reliable and sustainable method for thermally inactivating pathogenic microorganisms in milk and other perishable foods at sub-boiling temperatures, preserving its nutritional quality. This study aimed to evaluate the thermal and microbial performance of a low-cost solar milk pasteurization system, hypothesized to effectively reduce microbial contaminants and retain milk quality under natural sunlight. The system was constructed using locally available materials and tailored to the climatic conditions of the Savanna ecological zone in West Africa. A flat-plate glass solar collector was integrated with a 0.15 cm thick stainless steel cylindrical milk vat, featuring a 2.2 cm hot water jacket and 0.5 cm thick aluminum foil insulation. The system was tested in Navrongo, Ghana, under ambient temperatures ranging from 30 °C to 43 °C. The pasteurizer successfully processed up to 8 L of milk per batch, achieving a maximum milk temperature of 74 °C by 14:00 GMT. Microbial analysis revealed a significant reduction in bacterial load, from 6.6 × 106 CFU/mL to 1.0 × 102 CFU/mL, with complete elimination of coliforms. These results confirmed the device’s effectiveness in achieving safe pasteurization levels. The findings demonstrate that this locally built solar pasteurization system is a viable and cost-effective solution for improving milk safety in arid, electricity-limited regions. Its potential scalability also opens avenues for rural entrepreneurship in solar-powered food and water treatment technologies. Full article
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21 pages, 3085 KiB  
Article
Poultry Manure-Derived Biochar Synthesis, Characterization, and Valorization in Agriculture: Effect of Pyrolysis Temperature and Metal-Salt Modification
by Samar Hadroug, Leila El-Bassi, Salah Jellali, Ahmed Amine Azzaz, Mejdi Jeguirim, Helmi Hamdi, James J. Leahy, Amine Aymen Assadi and Witold Kwapinski
Soil Syst. 2025, 9(3), 85; https://doi.org/10.3390/soilsystems9030085 (registering DOI) - 4 Aug 2025
Abstract
In the present work, six biochars were produced from the pyrolysis of poultry manure at 400 °C and 600 °C (PM-B-400 and PM-B-600), and their post-modification with, respectively, iron chloride (PM-B-400-Fe and PM-B-600-Fe) and potassium permanganate (PM-B-400-Mn and PM-B-600-Mn). First, these biochars were [...] Read more.
In the present work, six biochars were produced from the pyrolysis of poultry manure at 400 °C and 600 °C (PM-B-400 and PM-B-600), and their post-modification with, respectively, iron chloride (PM-B-400-Fe and PM-B-600-Fe) and potassium permanganate (PM-B-400-Mn and PM-B-600-Mn). First, these biochars were deeply characterized through the assessment of their particle size distribution, pH, electrical conductivity, pH at point-zero charge, mineral composition, morphological structure, and surface functionality and crystallinity, and then valorized as biofertilizer to grow spring barley at pot-scale for 40 days. Characterization results showed that Fe- and Mn-based nanoparticles were successfully loaded onto the surface of the post-modified biochars, which significantly enhanced their structural and surface chemical properties. Moreover, compared to the control treatment, both raw and post-modified biochars significantly improved the growth parameters of spring barley plants (shoot and root length, biomass weight, and nutrient content). The highest biomass production was obtained for the treatment with PM-B-400-Fe, owing to its enhanced physico-chemical properties and its higher ability in releasing nutrients and immobilizing heavy metals. These results highlight the potential use of Fe-modified poultry manure-derived biochar produced at low temperatures as a sustainable biofertilizer for soil enhancement and crop yield improvement, while addressing manure management issues. Full article
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17 pages, 3816 KiB  
Article
Charging Station Siting and Capacity Determination Based on a Generalized Least-Cost Model of Traffic Distribution
by Mingzhao Ma, Feng Wang, Lirong Xiong, Yuhonghao Wang and Wenxin Li
Algorithms 2025, 18(8), 479; https://doi.org/10.3390/a18080479 - 4 Aug 2025
Abstract
With the popularization of electric vehicles and the continuous expansion of the electric vehicle market, the construction and management of charging facilities for electric vehicles have become important issues in research and practice. In some remote areas, the charging stations are idle due [...] Read more.
With the popularization of electric vehicles and the continuous expansion of the electric vehicle market, the construction and management of charging facilities for electric vehicles have become important issues in research and practice. In some remote areas, the charging stations are idle due to low traffic flow, resulting in a waste of resources. Areas with high traffic flow may have fewer charging stations, resulting in long queues and road congestion. The purpose of this study is to optimize the location of charging stations and the number of charging piles in the stations based on the distribution of traffic flow, and to construct a bi-level programming model by analyzing the distribution of traffic flow. The upper-level planning model is the user-balanced flow allocation model, which is solved to obtain the optimal traffic flow allocation of the road network, and the output of the upper-level planning model is used as the input of the lower-layer model. The lower-level planning model is a generalized minimum cost model with driving time, charging waiting time, charging time, and the cost of electricity consumed to reach the destination of the trip as objective functions. In this study, an empirical simulation is conducted on the road network of Hefei City, Anhui Province, utilizing three algorithms—GA, GWO, and PSO—for optimization and sensitivity analysis. The optimized results are compared with the existing charging station deployment scheme in the road network to demonstrate the effectiveness of the proposed methodology. Full article
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23 pages, 4451 KiB  
Article
Energy Management and Power Distribution for Battery/Ultracapacitor Hybrid Energy Storage System in Electric Vehicles with Regenerative Braking Control
by Abdelsalam A. Ahmed, Young Il Lee, Saleh Al Dawsari, Ahmed A. Zaki Diab and Abdelsalam A. Ezzat
Math. Comput. Appl. 2025, 30(4), 82; https://doi.org/10.3390/mca30040082 (registering DOI) - 3 Aug 2025
Viewed by 42
Abstract
This paper presents an advanced energy management system (EMS) for optimizing power distribution in a battery/ultracapacitor (UC) hybrid energy storage system (HESS) for electric vehicles (EVs). The proposed EMS accounts for all energy flow scenarios within a practical driving cycle. A regenerative braking [...] Read more.
This paper presents an advanced energy management system (EMS) for optimizing power distribution in a battery/ultracapacitor (UC) hybrid energy storage system (HESS) for electric vehicles (EVs). The proposed EMS accounts for all energy flow scenarios within a practical driving cycle. A regenerative braking control strategy is developed to maximize kinetic energy recovery using an induction motor, efficiently distributing the recovered energy between the UC and battery. Additionally, a power flow management approach is introduced for both motoring (discharge) and braking (charge) operations via bidirectional buck–boost DC-DC converters. In discharge mode, an optimal distribution factor is dynamically adjusted to balance power delivery between the battery and UC, maximizing efficiency. During charging, a DC link voltage control mechanism prioritizes UC charging over the battery, reducing stress and enhancing energy recovery efficiency. The proposed EMS is validated through simulations and experiments, demonstrating significant improvements in vehicle acceleration, energy efficiency, and battery lifespan. Full article
(This article belongs to the Special Issue Applied Optimization in Automatic Control and Systems Engineering)
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21 pages, 26631 KiB  
Technical Note
Induced Polarization Imaging: A Geophysical Tool for the Identification of Unmarked Graves
by Matthias Steiner and Adrián Flores Orozco
Remote Sens. 2025, 17(15), 2687; https://doi.org/10.3390/rs17152687 - 3 Aug 2025
Viewed by 55
Abstract
The identification of unmarked graves is important in archaeology, forensics, and cemetery management, but invasive methods are often restricted due to ethical or cultural concerns. This necessitates the use of non-invasive geophysical techniques. Our study demonstrates the potential of induced polarization (IP) imaging [...] Read more.
The identification of unmarked graves is important in archaeology, forensics, and cemetery management, but invasive methods are often restricted due to ethical or cultural concerns. This necessitates the use of non-invasive geophysical techniques. Our study demonstrates the potential of induced polarization (IP) imaging as a non-invasive remote sensing technique specifically suited for detecting and characterizing unmarked graves. IP leverages changes in the electrical properties of soil and pore water, influenced by the accumulation of organic matter from decomposition processes. Measurements were conducted at an inactive cemetery using non-invasive textile electrodes to map a documented grave from the early 1990s, with a survey design optimized for high spatial resolution. The results reveal a distinct polarizable anomaly at a 0.75–1.0 m depth with phase shifts exceeding 12 mrad, attributed to organic carbon from wooden burial boxes, and a plume-shaped conductive anomaly indicating the migration of dissolved organic matter. While electrical conductivity alone yielded diffuse grave boundaries, the polarization response sharply delineated the grave, aligning with photographic documentation. These findings underscore the value of IP imaging as a non-invasive, data-driven approach for the accurate localization and characterization of graves. The methodology presented here offers a promising new tool for archaeological prospection and forensic search operations, expanding the geophysical toolkit available for remote sensing in culturally and legally sensitive contexts. Full article
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