Search Results (8,396)

Our regression analysis documents that energy policies to promote renewable energy development, as well as hydroelectric imports from Canada, lead to short-run reductions in average electricity prices (also known as merit-order effects) throughout the Northeast United States. Changes in the reliance upon renewable energy in one of the Northeast’s three interconnected electricity markets will impact wholesale prices in the other two. The retirement of a 1000 MW nuclear plant can increase prices by about 9% in the Independent System Operator of New England market and 7% in the New York Independent System Operator market in the short run at reference hubs, while also raising prices in neighboring markets. Some proposed large-scale off-shore wind farms would not only lower prices in local markets at the reference hubs modeled but would also lower prices in neighboring markets. Full article

Artificial intelligence (AI) has become ubiquitous in modern computing systems, from high-performance data centers to resource-constrained edge devices. As AI applications continue to expand into mobile and IoT domains, the need for energy-efficient neural network implementations has become increasingly critical. To meet this requirement of energy-efficient computing, this work presents a BWNN (binary-weighted neural network) architecture implemented using FeRAM (Ferroelectric RAM)-based synaptic arrays. By leveraging the non-volatile nature and low-power computing of FeRAM-based CIM (computing in memory), the proposed CIM architecture indicates significant reductions in both dynamic and standby power consumption. Simulation results in this paper demonstrate that scaling the ferroelectric capacitor size can reduce dynamic power by up to 6.5%, while eliminating DRAM-like refresh cycles allows standby power to drop by over 258× under typical conditions. Furthermore, the combination of binary weight quantization and in-memory computing enables energy-efficient inference without significant loss in recognition accuracy, as validated using MNIST datasets. Compared to prior CIM architectures of SRAM-CIM, DRAM-CIM, and STT-MRAM-CIM, the proposed FeRAM-CIM exhibits superior energy efficiency, achieving 230–580 TOPS/W in a 45 nm process. These results highlight the potential of FeRAM-based BWNNs as a compelling solution for edge-AI and IoT applications where energy constraints are critical. Full article

The growing adoption of serverless computing has highlighted critical challenges in resource allocation, policy fairness, and energy efficiency within multitenancy cloud environments. This research proposes a reinforcement learning (RL)-based adaptive resource allocation framework to address these issues. The framework models resource allocation as a Markov Decision Process (MDP) with dynamic states that include latency, resource utilization, and energy consumption. A reward function is designed to optimize the throughput, latency, and energy efficiency while ensuring fairness among tenants. The proposed model demonstrates significant improvements over heuristic approaches, achieving a 50% reduction in latency (from 250 ms to 120 ms), a 38.9% increase in throughput (from 180 tasks/s to 250 tasks/s), and a 35% improvement in energy efficiency. Additionally, the model reduces operational costs by 40%, achieves SLA compliance rates above 98%, and enhances fairness by lowering the Gini coefficient from 0.25 to 0.10. Under burst loads, the system maintains a service level objective success rate of 94% with a time to scale of 6 s. These results underscore the potential of RL-based solutions for dynamic workload management, paving the way for more scalable, cost-effective, and sustainable serverless multitenancy systems. Full article

Hydrazine, a highly toxic and reactive compound widely used as rocket fuel, poses significant environmental and health risks, particularly in long-term space missions. This study investigates the cometabolic capacity of Chlorella vulgaris and seven extremophilic Bacillus spp. strains—isolated from the arid Dead Sea region—to tolerate and degrade hydrazine at concentrations up to 25 ppm. The microalga C. vulgaris reduced hydrazine levels by 81% within 24 h at 20 ppm, while the Bacillus isolates achieved an average reduction of 45% over 120 h. Identified strains included B. licheniformis, B. cereus, and B. atrophaeus. Co-culture experiments demonstrated that C. vulgaris and B. cereus (isolate ISO-36) stably coexisted without antagonistic effects, suggesting a synergistic detoxification interaction. Flow cytometry revealed that most bacteria transitioned into spores under stress, highlighting a survival adaptation. Titanium, representing a biocompatible material common in aerospace hardware, did not inhibit microbial growth or hydrazine degradation. These findings underscore the potential of Dead Sea-derived microbial consortia for cometabolic hydrazine detoxification and support the feasibility of converting spacecraft components into functional photobioreactors. This approach offers dual-use benefits for space missions and industrial wastewater treatment. Future studies should investigate degradation pathways, stress resilience, and bioreactor scale-up. Full article

The identification and detection of planting holes, combined with UAV technology, provides an effective solution to the challenges posed by manual counting, high labor costs, and low efficiency in large-scale planting operations. However, existing target detection algorithms face difficulties in identifying planting holes based on their edge features, particularly in complex environments. To address this issue, a target detection network named YOLO-PH was designed to efficiently and rapidly detect planting holes in complex environments. Compared to the YOLOv8 network, the proposed YOLO-PH network incorporates the C2f_DyGhostConv module as a replacement for the original C2f module in both the backbone network and neck network. Furthermore, the ATSS label allocation method is employed to optimize sample allocation and enhance detection effectiveness. Lastly, our proposed Siblings Detection Head reduces computational burden while significantly improving detection performance. Ablation experiments demonstrate that compared to baseline models, YOLO-PH exhibits notable improvements of 1.3% in mAP50 and 1.1% in mAP50:95 while simultaneously achieving a reduction of 48.8% in FLOPs and an impressive increase of 26.8 FPS (frames per second) in detection speed. In practical applications for detecting indistinct boundary planting holes within complex scenarios, our algorithm consistently outperforms other detection networks with exceptional precision (F1-score = 0.95), low computational cost, rapid detection speed, and robustness, thus laying a solid foundation for advancing precision agriculture. Full article

Background: This study aims to evaluate the efficacy of a combined transcranial magnetic stimulation (TMS) protocol incorporating intermittent theta burst stimulation (iTBS) and low-frequency TMS in adults diagnosed with first-episode and recurrent depressive disorders. Methods: A prospective, double-blind, parallel-group trial was conducted involving 42 participants (21 with first-episode depressive disorder and 21 with recurrent depressive disorder) recruited from Chengdu, China. All subjects received 10 sessions of TMS over two weeks. The primary outcome measure was suicidal ideation, assessed using the Beck scale for suicide ideation. Secondary outcomes included sleep quality, depressive symptoms, anhedonia, and cognitive function. Event-related potentials (ERPs) were also recorded. Data were analyzed using SPSS V.21.0, with statistical significance defined as p < 0.05. Results: Both patient groups exhibited significant reductions in suicidal ideation following the composite TMS intervention. Secondary outcomes showed significant improvements in sleep quality, overall depressive symptoms, anhedonia, and cognitive function. Notably, a significant association was found between improvements in sleep quality and depressive symptoms in the first-episode group, suggesting differential underlying mechanisms compared to recurrent depression. Limitations: The relatively short intervention and follow-up period limits the ability to assess the long-term sustainability of the observed benefits. Future studies with extended follow-up periods are warranted to evaluate the persistence of TMS effects and the potential need for maintenance sessions. Conclusions: The combined protocol of iTBS and low-frequency TMS effectively reduces suicidal ideation and improves various clinical outcomes in both first-episode and recurrent depressive disorders, indicating the effectiveness of the physical intervention, especially for the first-episode patients. These findings underscore the importance of personalized treatment strategies based on the clinical history of depressive episodes. Further research with longer follow-up periods is warranted to assess the long-term sustainability of TMS effects. Full article

This study systematically investigated the corrosion evolution and protective mechanisms of X80 pipeline steel in Xinjiang’s saline soil environments under freeze–thaw cycling conditions. Combining regional soil characterization with laboratory-constructed corrosion systems, we employed electrochemical impedance spectroscopy, potentiodynamic polarization, and surface analytical techniques to quantify temporal–spatial corrosion behavior across 30 freeze–thaw cycles. Experimental results revealed a distinctive corrosion resistance pattern: initial improvement (cycles 1–10) attributed to protective oxide layer formation, followed by accelerated degradation (cycles 10–30) due to microcrack propagation and chloride accumulation. Synchrotron X-ray diffraction analyses identified sulfate–chloride ion synergism as the primary driver of localized corrosion disparities in heterogeneous soil matrices. A comparative evaluation of asphalt-coated specimens demonstrated a 62%–89% corrosion rate reduction, with effectiveness directly correlating with coating integrity and thickness (200–500 μm range). Molecular dynamics simulations using Materials Studio revealed atomic-scale ion transport dynamics at coating–substrate interfaces, showing preferential Cl⁻ permeation through coating defects. These multiscale findings establish quantitative relationships between environmental stressors, coating parameters, and corrosion kinetics, providing a mechanistic framework for optimizing protective coatings in cold-region pipeline applications. Full article

Objective: Retained primitive reflexes are associated with delayed motor and behavioral development in children with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). This study examined the effects of a 12-week structured exercise intervention on reflex integration, motor coordination, and socio-behavioral outcomes in these populations. Method: Fifteen children with ASD (13 boys, 2 girls) and twelve with ADHD (8 boys, 4 girls), aged 6–12 years, participated in rhythmic, balance, and coordination-based exercises. Primitive reflexes, including the asymmetrical tonic neck reflex (ATNR), were assessed using standardized protocols, and fine motor coordination was evaluated using the Finger and Thumb Opposition Test (FOT). Behavioral outcomes were measured using the Social Responsiveness Scale-2 (SRS-2) for the ASD group and the Conners 3 for the ADHD group. Results: The ASD group showed significant reductions in left-standing ATNR retention scores (p = 0.012) and improvements in right-hand FOT scores (p = 0.023). In the ADHD group, significant improvements were also observed in right-hand FOT scores (p = 0.007). Furthermore, Conners 3 Total and Global Index scores significantly decreased in the ADHD group (p = 0.016 and 0.020, respectively). Reflex retention patterns appeared broader and more bilateral in ASD than in ADHD, suggesting distinct motor developmental profiles. Conclusions: Short-term rhythmic, balance, and whole-body coordination exercise interventions may support behavioral and motor development in children with ASD and ADHD. Tailored programs emphasizing reflex integration hold promise for clinical and educational applications. Full article

Heatwaves intensified by climate change increasingly threaten urban populations, especially the elderly. However, most existing studies have concentrated on short-term or single-scale analyses, lacking a comprehensive understanding of how land cover changes and urbanization affect the vulnerability of the elderly to extreme heat. This study aims to investigate the spatiotemporal distribution patterns of heat-related health risks among the elderly in Nanchang City and to identify their key driving factors within the context of rapid urbanization. This study employs Crichton’s risk triangle framework to the heat-related health risks for the elderly in Nanchang, China, from 2002 to 2020 by integrating meteorological records, land surface temperature, land cover data, and socioeconomic indicators. The model captures the spatiotemporal dynamics of heat hazards, exposure, and vulnerability and identifies the key drivers shaping these patterns. The results show that the heat health risk index has increased significantly over time, with notably higher levels in the urban core compared to those in suburban areas. A 1% rise in impervious surface area corresponds to a 0.31–1.19 increase in the risk index, while a 1% increase in green space leads to a 0.21–1.39 reduction. Vulnerability is particularly high in economically disadvantaged, medically under-served peripheral zones. These findings highlight the need to optimize the spatial distribution of urban green space and control the expansion of impervious surfaces to mitigate urban heat risks. In high-vulnerability areas, improving infrastructure, expanding medical resources, and establishing targeted heat health monitoring and early warning systems are essential to protecting elderly populations. Overall, this study provides a comprehensive framework for assessing urban heat health risks and offers actionable insights into enhancing climate resilience and health risk management in rapidly urbanizing regions. Full article

To enhance the survivability of armed helicopters in high-threat environments, integrated infrared (IR) suppressors are increasingly adopted to reduce thermal signatures. However, such integration significantly alters the exhaust flow field, which may in turn affect both the infrared and acoustic characteristics of the helicopter. This study investigates the aerodynamic, infrared, and acoustic impacts of an integrated IR suppressor through the comparative analysis of two helicopter configurations: a conventional design and a design equipped with an integrated IR suppressor. Full-scale models are used to analyze flow field and IR radiation characteristics, while scaled models are employed for aeroacoustic simulations. The results show that although the integrated IR suppressor increases flow resistance and reduces entrainment performance within the exhaust mixing duct, it significantly improves the thermal dissipation efficiency of the exhaust plume. The infrared radiation analysis reveals that the integrated suppressor effectively reduces radiation intensity in both the 3~5 μm and 8~14 μm bands, especially under cruise conditions where the exhaust is more efficiently cooled by ambient airflow. Equivalent radiation temperatures calculated along principal axes confirm lower IR signatures for the integrated configuration. Preliminary acoustic analyses suggest that the slit-type nozzle and integrated suppressor layout may also offer potential benefits in jet noise reduction. Overall, the integrated IR suppressor provides a clear advantage in lowering the infrared observability of armed helicopters, with acceptable aerodynamic and acoustic trade-offs. These findings offer valuable guidance for the future development of low-observable helicopter platforms. Full article

Hyperspectral imaging for seed vigor detection faces the challenges of handling high-dimensional spectral data, information loss after dimensionality reduction, and low feature differentiation between vigor levels. To address the above issues, this study proposes an improved dynamic optimize MDS (DO-MDS) dimensionality reduction algorithm based on multidimensional scaling transformation. DO-MDS better preserves key features between samples during dimensionality reduction. Secondly, a dual-stream spectral collaborative attention (DSCA) module is proposed. The DSCA module adopts a dual-modal fusion approach combining global feature capture and local feature enhancement, deepening the characterization capability of spectral features. This study selected commonly used rice seed varieties in Zhejiang Province and constructed three individual spectral datasets and a mixed dataset through aging, spectral acquisition, and germination experiments. The experiments involved using the DO-MDS processed datasets with a convolutional neural network embedded with the DSCA attention module, and the results demonstrate vigor discrimination accuracy rates of 93.85%, 93.4%, and 96.23% for the Chunyou 83, Zhongzao 39, and Zhongzu 53 datasets, respectively, achieving 94.8% for the mixed dataset. This study provides effective strategies for spectral dimensionality reduction in hyperspectral seed vigor detection and enhances the differentiation of spectral information for seeds with similar vigor levels. Full article

There is still a need to develop scenarios and models aimed at substituting fuelwood and reducing the use of fossil fuels such as liquefied petroleum gas (LPG), on which low-income rural households in the Global South often depend. The use of these fuels for cooking and heating in domestic and productive activities poses significant health and environmental risks. This study validated, in three different phases, the sustainability of a model for the production and use of biogas from the treatment of swine-rearing wastewater (WWs) on a community farm: (i) A Multi-Criteria Analysis (MCA), incorporating environmental, social/health, technical, and economic criteria, identified the main weighted criterion to C8 (use of small-scale technologies and low-cost access), with a score of 0.44 points, as well as the Tubular biodigester (Tb) as the most suitable option for the study area, scoring 8.1 points. (ii) Monitoring of the Tb over 90 days showed an average biogas production of 2.6 m³ d⁻¹, with average correlation 0.21 m³ Biogas kg Biomass⁻¹. Using the experimental biogas production rate (k = 0.0512 d⁻¹), the process was simulated with the BgMod model, achieving an average deviation of only 10.4% during the final production phase. (iii) The quantification of benefits demonstrated significant reductions in firewood use: in Scenario S1 (kitchen energy needs), biogas replaced 83.1% of firewood, while in Scenario S2 (citronella essential oil production), the substitution rate was 24.1%. In both cases, the avoided emissions amounted to 0.52 tons of CO_2eq per month. Finally, this study proposes a synthesised, community-based rural biogas framework designed for replication in regions with similar socio-environmental, technical, and economic conditions. Full article

In practical engineering, buildings are predominantly subjected to combined forces, and reinforced concrete (RC) beams serve as the primary load-bearing components of buildings. However, there is a paucity of research on the torsional effects of RC beams, particularly concerning the torsional failure mechanisms of large-size beams. To address this gap, this paper establishes a meso-scale numerical analysis model for RC beams reinforced with Carbon Fiber Reinforced Polymer (CFRP) sheets under combined bending and torsion pressures. The research analyzes how the fiber ratio and torsion-bending ratio govern torsion-induced failure characteristics and size effects in CFRP-strengthened RC beams. The results indicate that an increase in the fiber ratio leads to accumulated damage distribution in the RC beam, a gradual decrease in CFRP sheet strain, and an increase in peak load and peak torque, albeit with diminishing amplitudes; as the torsion-bending ratio increases, crack distribution becomes more concentrated, the angle between cracks and the horizontal direction decreases, overall peak load decreases, peak torque increases, and CFRP sheet strain increases; and the nominal torsional capacity of CFRP-strengthened RC beams declines with increasing size, exhibiting a reduction of 24.1% to 35.6%, which distinctly demonstrates the torsional size effect under bending–torsion coupling conditions. A modified Torque Size Effect Law is formulated, characterizing in quantitative terms the dependence of the fiber ratio and the torsion-bending ratio. Full article

This paper proposes an improved wave function asperity elastic–plastic model. A cosine function that could better fit the geometric morphology was selected to construct the asperity, the elastic phase was controlled by the Hertz contact theory, the elastoplastic transition phase was corrected by the hyperbolic tangent function, and the fully plastic phase was improved by the projected area theory. The model broke through the limitations of the spherical assumption and was able to capture the stress concentration and plastic flow phenomena. The results show that the contact pressure in the elastic phase was 22% higher than that of the spherical shape, the plastic strain in the elastoplastic phase was 52% lower than that of the spherical shape, and the fully plastic phase reduced the contact area error by 20%. The improved hyperbolic tangent function eliminated the unphysical oscillation phenomenon in the elastoplastic phase and ensured the continuity and monotonicity of the contact variables, with an error of <5% from the finite element analysis. Meanwhile, extending the proposed model, we developed a rough surface contact model, and it was verified that the wavy asperity could better match the mechanical properties of the real rough surface and exhibited progressive stiffness reduction during the plastic flow process. The model in this paper can provide a theoretical basis for predicting stress distribution, plastic evolution, and multi-scale mechanical behavior in the connection interface. Full article

A novel strategy has been developed for extracting value-added resources from iron-lean, high-alumina- and -silica-containing red muds (RMs). With little or no recycling, such RMs are generally destined for waste dumps. Detailed results are presented on the carbothermic reduction of 100% RM (29.3 wt.% Fe₂O₃, 22.2 wt.% Al₂O₃, 20.0 wt.% SiO₂, 1.2 wt.% CaO, 12.2 wt.% Na₂O) and its 2:1 blends with Fe₂O₃ and red mill scale (MS). Synthetic graphite was used as the reductant. Carbothermic reduction of RM and blends was carried out in a Tamman resistance furnace at 1650 °C for 20 min in an Ar atmosphere. Reduction residues were characterized using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), elemental mapping and X-ray diffraction (XRD). Small amounts of Fe₃Si alloys, alumina, SiC and other oxide-based residuals were detected in the carbothermic residue of 100% RM. A number of large metallic droplets of Fe–Si alloys were observed for RM/Fe₂O₃ blends; no aluminium was detected in these metallic droplets. A clear segregation of alumina was observed as a separate phase. For the RM/red MS blends, a number of metallic Fe–Si droplets were seen embedded in an alumina matrix in the form of a cermet. This study has shown the regeneration of alumina and the formation of alumina-based cermets, Fe–Si alloys and SiC during carbothermic reduction of RM and its blends. This innovative recycling strategy could be used for extracting value-added resources from iron-lean RMs, thereby enhancing process productivity, cost-effectiveness of alumina regeneration, waste utilization and sustainable developments in the field. Full article