Search Results (1,443)

The escalating heatwave risks over the Tibetan Plateau (TP) highlight unresolved gaps in understanding multitype mechanisms and diurnal urban canopy heat island (UCHI) responses. Using Xining’s high-density observational network (2018–2023) and by employing comparative analysis (urban–rural, heatwave versus non-heatwave days) and composite analysis, we found: During the record-breaking July 2022 heatwave across the TP, Xining reached an extreme UCHI peak (z-score: 3.0). Critically asymmetric UCHI responses as daytime heatwaves amplify mean intensity by 0.35 °C via extreme value shifts, whereas nighttime events suppress it by 0.31 °C. Crucially, heatwaves induce negligible daytime UCHI modulation but drive comparable magnitude nighttime UCHI intensification (during daytime events) and reduction (during nighttime events), demonstrating type-dependent and diurnally asymmetric urban thermal sensitivities. Heatwaves driven by distinct synoptic patterns; daytime events are controlled by an anomaly anticyclone (cloudless, dry conditions), while nighttime events occur under plateau-north anticyclones (cloudy, humid conditions). These patterns fundamentally reshape heatwave–UCHI interactions through divergent mechanisms: Daytime/nighttime heatwaves amplify/suppress nocturnal UCHI through enhanced/reduced urban heat storage and accelerated/inhibited rural radiative cooling. Our case study demonstrates that although heatwaves generally amplify nocturnal UCHI, in dry regions, their synoptic drivers significantly modify this nighttime synergy. The nocturnal UCHI during heatwave is not only driven by humidity effects but also modulated by cloud cover-regulated rural radiative cooling and urban thermal storage. These findings establish a mechanistic framework for heatwaves–UCHI interactions and provide actionable insights for heat-resilient planning in high-altitude arid cities. Full article

The lion’s paw scallop (Nodipecten subnodosus) is a commercially valuable pectinid whose postharvest quality strongly depends on storage and handling conditions. This study investigated the combined effects of seasonality, postmortem time, and storage temperature on energy metabolism in the adductor muscle, focusing on metabolites associated with rigor mortis and freshness. Adult scallops (~10 cm shell height) were harvested in four seasons (spring, summer, autumn, winter), transported under commercial conditions for approximately 2 h, and stored at 0, 5, and 10 °C for 48 h. Muscle samples were collected every 8 h and analyzed for ATP, ADP, AMP, glycogen, arginine phosphate (Arg-P), and free arginine using HPLC and enzymatic assays. In addition, the adenylate energy charge (AEC) was determined in freshly harvested and post-transport specimens. Initial ATP concentrations ranged from 4.2 to 6.5 µmol/g, with higher levels in winter, while Arg-P varied from 3.1 to 4.8 µmol/g. Seasonality significantly influenced all metabolites except arginine, and transport markedly reduced ATP and AEC, particularly in spring and autumn. Storage at 0 °C resulted in rapid ATP depletion (<1.0 µmol/g within 12 h) and AMP accumulation (>3.0 µmol/g), indicating accelerated energy collapse. In contrast, scallops stored at 5 and 10 °C maintained ATP levels above 2.5 µmol/g for up to 24 h, delaying rigor mortis, reducing postmortem contraction, and preserving muscle texture and appearance. Overall, these findings demonstrate that moderate refrigeration represents a physiologically suitable and technologically advantageous strategy to optimize scallop postharvest handling, extend shelf life, and enhance product quality for the fresh seafood market. Full article

Accelerated oxidation experiments on Chinese 0# diesel fuel were performed with a self-designed aging reactor system. Five experimental conditions covering pressures ranging from atmospheric pressure to 0.8 MPa, temperatures ranging from room temperature (25 °C) to 80 °C, and their synergistic effects were adopted to simulate the long-term oxidation of diesel fuel. The extent of deterioration was evaluated based on the measurement of three key indicators, i.e., oxidation stability, wear scar diameter, and viscosity. Thermogravimetric analysis (TGA) tests were performed, and the measured thermogravimetric (TG) curves and derivative thermogravimetric (DTG) curves were used to evaluate the effects of reactor material, heating rate, bath gas, and reactive gas on the deterioration and vaporization processes of diesel fuel. Based on a comparison of the deterioration indicators of diesel fuel collected from the accelerated oxidation experiments and oil depots serving actual operating emergency diesel generators (EDGs), a rapid assessment method of real-time diesel deterioration was explored. Based on the experimental observations, the affecting mechanisms of the increases in temperature and oxygen partial pressure were discussed. Two test methods of accelerated oxidation, with the respective conditions of 0.8 MPa/80 °C and atmospheric pressure/80 °C, were proposed, which could effectively compress the time needed for long-term storage simulations (e.g., 200 h lab aging equals three years of actual operation). The optional temperature and pressure windows for acceleration oxidation were confirmed (40–80 °C/0.3–0.8 MPa). These results are valuable for the further understanding of the processes of deterioration and vaporization of diesel fuel. Full article

The influence of stress on gas sorption behavior and sorption-induced swelling in coal is critical for the success of CO₂-enhanced coalbed methane recovery (CO₂-ECBM) and geological carbon sequestration—a key strategy for mitigating climate change and promoting clean energy transitions. However, this influence remains insufficiently understood, largely due to experimental limitations (e.g., overreliance on powdered coal samples) and conflicting theoretical frameworks in existing studies. To address this gap, this study systematically investigates the effects of two distinct stress constraints—constant confining pressure and constant volume—on CO₂ adsorption capacity, adsorption kinetics, and associated swelling deformation of intact anthracite coal cores. An integrated experimental apparatus was custom-designed for this study, combining volumetric sorption measurement with high-resolution strain monitoring via the confining fluid displacement (CFD) method and the confining pressure response (CPR) method. This setup enables the quantification of CO₂–coal interactions under precisely controlled stress environments. Key findings reveal that stress conditions exert a regulatory role in shaping CO₂–coal behavior: constant confining pressure conditions enhance CO₂ adsorption capacity and sustain adsorption kinetics by accommodating matrix swelling, thereby preserving pore accessibility for continuous gas uptake. In contrast, constant volume constraints lead to rapid internal stress buildup, which inhibits further gas adsorption and accelerates the attainment of kinetic saturation. Sorption-induced swelling exhibits clear dependence on both pressure and constraint conditions. Elevated CO₂ pressure leads to increased strain, while constant confining pressure facilitates more gradual, sustained expansion. This is particularly evident at higher pressures, where adsorption-induced swelling prevails over mechanical constraints. These results help resolve key discrepancies in the existing literature by clarifying the dual role of stress in modulating both pore accessibility (for gas transport) and mechanical response (for matrix deformation). These insights provide essential guidance for optimizing CO₂ injection strategies and improving the long-term performance and sustainability of CO₂-ECBM and geological carbon storage projects, ultimately supporting global efforts in carbon emission reduction and sustainable energy resource utilization. Full article

Battery Electric Vehicles (BEVs) technology is rapidly emerging as the cornerstone of sustainable transportation, driven by advancements in battery technology, power electronics, and modern drivetrains. This paper presents a comprehensive review of current and next-generation BEV powertrain architectures, focusing on five key subsystems: battery energy storage system, electric propulsion motors, energy management systems, power electronic converters, and charging infrastructure. The review traces the evolution of battery technology from conventional lithium-ion to solid-state chemistries and highlights the critical role of battery management systems in ensuring optimal state of charge, health, and safety. Recent innovations by leading automakers are examined, showcasing advancements in cell formats, motor designs, and thermal management for enhanced range and performance. The role of power electronics and the integration of AI-driven strategies for vehicle control and vehicle-to-grid (V2G) are analyzed. Finally, the paper identifies ongoing research gaps in system integration, standardization, and advanced BMS solutions. This review provides a comprehensive roadmap for innovation, aiming to guide researchers and industry stakeholders in accelerating the adoption and sustainable advancement of BEV technologies. Full article

The temperature of the thermal energy storage unit is a critical parameter for the stable operation of seasonal borehole thermal energy storage (BTES) systems. However, existing temperature prediction models predominantly focus on estimating single-point temperatures or borehole wall temperatures, while lacking effective methods for calculating the average temperature of the storage unit. This limitation hinders accurate assessment of the thermal charging and discharging states. Furthermore, some models involve complex computations and exhibit low operational efficiency, failing to meet the practical engineering demands for rapid prediction and response. To address these challenges, this study first develops a thermal response model for the average temperature of the storage unit based on the finite line source theory and further proposes a simplified engineering algorithm for predicting the storage unit temperature. Subsequently, two-dimensional discrete convolution and Fast Fourier Transform (FFT) techniques are introduced to accelerate the solution of the storage unit temperature distribution. Finally, the model’s accuracy is validated against practical engineering cases. The results indicate that the single-point temperature engineering algorithm yields a maximum relative error of only 0.3%, while the average temperature exhibits a maximum relative error of 1.2%. After employing FFT, the computation time of both single-point and average temperature engineering algorithms over a 10-year simulation period is reduced by more than 90%. When using two-dimensional discrete convolution to calculate the temperature distribution of the storage unit, expanding the input layer from 200 × 200 to 400 × 400 and the convolution kernel from 25 × 25 to 51 × 51 reduces the time required for temperature superposition calculations to approximately 0.14–0.82% of the original time. This substantial improvement in computational efficiency is achieved without compromising accuracy. Full article

Oxidative reactions accelerate quality loss in emulsified meats. This study evaluated a clean-label strategy in goat meat pates by co-fortifying Portulaca oleracea powder 1% and honey 4%. Control and treatment batches were cooked to 72 °C and stored as opened packs at ≤6 °C for 10 days. Oxidative stability of lipid and protein was monitored by peroxide value (PV), TBARS, acid value, and baseline protein carbonyls; total antioxidant capacity was assessed by FRAP and DPPH; color was quantified in CIE Lab; fatty acids were profiled by GC-FID; and protein integrity was examined by SDS-PAGE. The treatment modestly increased α-linolenic acid (ALA) (1.2% vs. 0.8%) in the control and markedly enhanced antioxidant status (FRAP 10.5 ± 0.04 mg GAE/g vs. not detected; DPPH 33.02 ± 0.009% vs. 22.33 ± 0.007%; IC₅₀ 106.10 ± 10.01 vs. 138.25 ± 11.15 µg/mL). Across storage, PV showed a small, non-significant delay on day 10 (13.0 ± 0.9 vs. 14.0 ± 0.9 meq/kg), while secondary and hydrolytic indices were consistently lower (TBARS day 10: 1.91 ± 0.13 vs. 3.29 ± 0.23 mg MDA/kg; acid value day 10: 7.0 ± 0.5 vs. 8.5 ± 0.6 mg KOH/g). Protein carbonyls at baseline were comparable (99.19 vs. 95.73 nmol/mg). L* and b* remained similar before and after light exposure, with a modest, non-significant reduction in color stability and greater a* loss in the treatment. These results show that purslane–honey co-fortification nutritionally enriches pates and attenuates oxidative spoilage during refrigerated storage, with minor color trade-offs that merit process optimization. Full article

In this study, the impact of the electric motor size and the hybridization ratio of a Fuel Cell Electric Bus on its vehicle performance (i.e., gradeability and acceleration) and fuel consumption was investigated using the ADVISOR software. The investigation first involved a parametric analysis with different electric motor and fuel cell sizes for the dynamic performance metrics, specifically the 0–60 km/h vehicle acceleration and the maximum gradeability (%) at a constant speed of 20 km/h. The results revealed that the acceleration is most sensitive to fuel cell power. Regarding gradeability, a more complex relationship was observed: when the electric motor power was below 215 kW, gradeability remained consistently low regardless of the fuel cell size. However, for motors exceeding 215 kW, fuel cell power then became a significant influencing factor on the vehicle’s climbing capability. Subsequently, the analysis focused on the effect of the hybridization ratio, which represents the power balance between the fuel cell and the energy storage system, varied between 0 and 0.8. Results showed that increasing the hybridization ratio decreases gradeability and acceleration performance and increases total energy consumption. This trade-off is quantitatively illustrated by the results over the Central Business District (CBD) driving cycle. For instance, the pure battery-electric configuration (a hybridization ratio of 0), featuring a 296 kW battery system, recorded a gradeability of 12.4% and an acceleration time of 16.3 s, while consuming 28,916 kJ. At an intermediate hybridization ratio of 0.4 (composed of a 118.4 kW fuel cell and a 177.6 kW battery), performance remained high with a gradeability of 12.2% and an acceleration of 17.3 s, but the energy consumption increased to 43,128 kJ. Finally, in the fuel-cell-dominant configuration with a hybridization ratio of approximately 0.8 (a 236.8 kW fuel cell and a 59.2 kW battery), gradeability dropped to 8.4%, acceleration time deteriorated to 38.9 s, and total energy consumption increased further to 52,678 kJ over the CBD driving cycle. Full article

The acceleration of climate change and increasing weather-related disasters require more active utilization of renewable energy. To maximize the use of renewable energy, energy storage is an essential part. Liquid piston gas compressors have recently drawn attention because of their applicability to compressed air-based energy storage. Aqueous foam can be used to enhance the efficiency of liquid piston gas compression by boosting heat transfer. To validate the effectiveness of the combination of liquid piston and aqueous foam in a multi-stage compression system, which can contribute to higher efficiency, the present work performed experimental study at various pressure levels. Compressions were performed with and without aqueous foam at three different initial pressure levels of 1, 2, and 3 bars. For each cycle of compression, a pressure ratio of 2 was used, and the impact of pressure levels on compression efficiency was measured. With the use of foam, isothermal efficiencies of 91.4, 88.2, and 86.6% were observed at 1, 2, and 3 bar(s), which improved by 2.2, 2.1, and 1.3% compared to the baseline compressions. To identify the cause of the effectiveness variations, the volume changes in the foam at the different pressure levels were visually compared. In higher-pressure tests, a significant reduction in the foam amount was observed, and this change may contribute to the decreased effectiveness of the technique. Full article

Background/Objectives: Encouraged by the traditional use of Cotinus coggygria Scop. (European smoketree) for its anti-inflammatory and antioxidant properties, and considering the limitations of current therapies for recurrent aphthous stomatitis (RAS), we aimed to develop and evaluate a mucoadhesive oral gel containing C. coggygria stem bark extract. Methods: A thermosensitive gel was formulated using Carbopol^® 974P NF and poloxamer 407, enriched with 5% C. coggygria extract (CC gel), and characterized for its organoleptic properties, pH, electrical conductivity, and storage stability over six months. Therapeutic efficacy was assessed in a Wistar albino rat model of chemically induced oral ulcers. Animals were divided into three groups: untreated controls (CTRL), rats treated with gel base (GB), and those treated with CC gel over a 10-day period. Healing progression was monitored macroscopically (ulcer size reduction), biochemically (oxidative stress markers in plasma and tissue), and histologically. Results: The CC gel demonstrated satisfactory physicochemical stability and mucosal compatibility. Moreover, it significantly accelerated ulcer contraction and achieved complete re-epithelialization by day 6. Biochemical analyses revealed reduced TBARS and increased SOD, CAT, and GSH levels in ulcer tissue, indicating enhanced local antioxidant defense. Histological evaluation confirmed early resolution of inflammation, pronounced fibroblast activity, capillary proliferation, and full epithelial regeneration in the CC group, in contrast to delayed healing and persistent inflammatory infiltration in the GB and CTRL groups. Conclusions: These findings indicate that the CC gel has potential as a natural, topical formulation with antioxidant and regenerative properties for RAS, although further studies, including clinical evaluation, are required to confirm its overall efficacy and long-term safety. Full article

Postharvest shiitake mushrooms (Lentinus edodes) often undergo browning under low-temperature, high-humidity storage conditions, which significantly reduces their commercial value and constrains industry development. However, the molecular mechanisms regulating this process remain unclear. In this study, we used ‘Nongxiang No. 1’ as the experimental material and observed that during storage, the L* value of caps and stipes decreased continuously, shifting from light brown to dark brown-black. Concurrently, the relative electrical conductivity increased by approximately 3.07-fold, and the membrane lipid peroxidation product malondialdehyde (MDA) content increased by approximately 7.9-fold. Superoxide dismutase (SOD) activity initially increased then declined, indicating that elevated membrane permeability accelerates senescence. Peroxidase (POD) activity exhibited a significant upward then downward trend and improved 75.83% at day 22 of postharvest storage, with LEHP1, LEHP2, and LEHP3 gene expression patterns closely aligning with these changes. Specifically, LEHP2 and LEHP3 expression was upregulated by 23.8-fold and 2.35-fold on day 22 than day 0. Cis-element analysis identified MYB binding sites in all three LEHP genes. Genome-wide screening combined with qRT-PCR revealed two MYB transcription factors, LeMYB2 and LeMYB5, whose expression synchronized with LEHP genes. Transient expression assays in tobacco leaves confirmed their nuclear localization, consistent with transcription factor characteristics. Electrophoretic Mobility Shift Assay (EMSA) and Dual-Luciferase Reporter Assay (DLR) experiments further demonstrated that LeMYB2 and LeMYB5 directly activate LEHP2 and LEHP3 promoters, highlighting their key regulatory roles in postharvest browning of shiitake mushrooms. Full article

This study presents a comprehensive assessment of the energy systems in eight Eastern European countries—Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, Slovakia, and Slovenia—focusing on their energy transition, security of supply, decarbonisation, and energy efficiency. Using principal component analysis (PCA) and clustering techniques, we identify three different energy profiles: countries dependent on fossil fuels (e.g., Poland, Bulgaria), countries with a balanced mix of nuclear and fossil fuels (e.g., the Czech Republic, Slovakia, Hungary), and countries focusing mainly on renewables (e.g., Slovenia, Croatia). The sectoral analysis shows that industry and transport are the main drivers of energy consumption and CO₂ emissions, and the challenges and policy priorities of decarbonisation are determined. Regression modelling shows that dependence on fossil fuels strongly influences the use of renewable energy and electricity consumption patterns, while national differences in per capita electricity consumption are influenced by socio-economic and political factors that go beyond the energy structure. The Decarbonisation Level Index (DLI) indicator shows that Bulgaria and the Czech Republic achieve a high degree of self-sufficiency in domestic energy, while Hungary and Slovakia are the most dependent on imports. A typology based on energy intensity and import dependency categorises Romania as resilient, several countries as balanced, and Hungary, Slovakia, and Croatia as vulnerable. The projected investments up to 2030 indicate an annual increase in clean energy production of around 123–138 TWh through the expansion of nuclear energy, the development of renewable energy, the phasing out of coal, and the improvement of energy efficiency, which could reduce CO₂ emissions across the region by around 119–143 million tons per year. The policy recommendations emphasise the accelerated phase-out of coal, supported by just transition measures, the use of nuclear energy as a stable backbone, the expansion of renewables and energy storage, and a focus on the electrification of transport and industry. The study emphasises the significant influence of European Union (EU) policies—such as the “Clean Energy for All Europeans” and “Fit for 55” packages—on the design of national strategies through regulatory frameworks, financing, and market mechanisms. This analysis provides important insights into the heterogeneity of Eastern European energy systems and supports the design of customised, coordinated policy measures to achieve a sustainable, secure, and climate-resilient energy transition in the region. Full article

The harsh conditions of the space environment necessitate advanced materials capable of withstanding extreme temperature fluctuations and ultraviolet (UV) radiation. While epoxy-based composites are widely utilized in aerospace due to their favorable strength-to-weight ratio, they are prone to degradation, especially under prolonged high-energy UV-C exposure. This study investigated the mechanical and chemical stability of epoxy composites reinforced with nanosilica at 0, 2, 5, and 10 wt% before and after UV-C irradiation. Dynamic mechanical analysis (DMA) revealed that increased nanosilica content enhanced the storage modulus below the glass transition temperature (Tg) but reduced both Tg and the damping factor. Following UV-C exposure, all samples showed a decrease in storage modulus and Tg; however, composites with higher nanosilica content maintained better property retention. Frequency sweeps corroborated these findings, indicating improved instantaneous modulus but accelerated relaxation with increased nanosilica. Fourier-transform infrared (FTIR) spectroscopy of UV-C-exposed samples demonstrated significant oxidation and carboxylic group formation in neat epoxy, contrasting with minimal spectral changes in nanosilica-modified composites, signifying improved chemical resistance. Overall, nanosilica incorporation substantially enhances the thermomechanical and oxidative stability of epoxy composites under simulated space conditions, highlighting their potential for more durable performance in low Earth orbit applications. Full article

Microcontroller units (MCUs) serve as the core components of embedded systems. In the era of smart IoT, embedded devices are increasingly deployed on mobile platforms, leading to a growing demand for low-power consumption. As a result, low-power technology for MCUs has become increasingly critical. This paper systematically reviews the development history and current technical challenges of MCU low-power technology. It then focuses on analyzing system-level low-power optimization pathways for integrating MCUs with artificial intelligence (AI) technology, including lightweight AI algorithm design, model pruning, AI acceleration hardware (NPU, GPU), and heterogeneous computing architectures. It further elaborates on how AI technology empowers MCUs to achieve comprehensive low power consumption from four dimensions: task scheduling, power management, inference engine optimization, and communication and data processing. Through practical application cases in multiple fields such as smart home, healthcare, industrial automation, and smart agriculture, it verifies the significant advantages of MCUs combined with AI in performance improvement and power consumption optimization. Finally, this paper focuses on the key challenges that still need to be addressed in the intelligent upgrade of future MCU low power consumption and proposes in-depth research directions in areas such as the balance between lightweight model accuracy and robustness, the consistency and stability of edge-side collaborative computing, and the reliability and power consumption control of the sensor-storage-computing integrated architecture, providing clear guidance and prospects for future research. Full article

Advanced energy storage solutions are required to mitigate grid destabilization caused by high-penetration renewable energy integration. Superconducting Magnetic Energy Storage (SMES) offers ultrafast response (<1 ms), high efficiency (>95%), and almost unlimited cycling life. However, its commercialization is hindered by the complex modeling of critical current with anisotropic behaviors and the computational inefficiency of high-dimensional optimization for megajoule (MJ)-class magnets. This paper proposes an integrated design framework synergizing a two-dimensional axisymmetric magnetic field model based on Conway’s current-sheet theory, a critical current anisotropy characterization model, and an adaptive genetic algorithm (AGA). A superconducting magnet optimization model incorporating co-calculation of electromagnetic parameters is established. A dual-module chromosome encoding strategy (discrete gap index + nonlinear increment) and parallel acceleration techniques were developed. This approach achieved efficient optimization of MJ-class magnets. For a single solenoid, the critical current increased by 22.6% (915 A) and energy storage capacity grew by 41.8% (1.12 MJ). A 20-unit array optimized by coordinated gap adjustment achieved a matched inductance/current of 0.15 H/827 A (20 MJ), which can enhance transient stability control capability in smart grids. The proposed method provides a computationally efficient design paradigm and user-friendly teaching software tool for high-current SMES magnets, supporting the development of large-scale High-Temperature Superconducting (HTS) magnets, promoting the deployment of large-scale HTS magnets in smart grids and high-field applications. Full article