Search Results (51)

In response to the issues of low synergy efficiency between gas extraction and water injection, unclear procedural connections, and high costs in coal mine gas disaster prevention, this paper proposes a collaborative prevention technology for coal mine gas disasters termed “pump–injection–lock.” First, based on the kinetics of gas desorption in gas-bearing coal under different water-bearing conditions, an optimization model for the sequence of gas extraction and high-pressure water injection was developed. This model reduced the gas desorption rate in the experimental area by 32.5% and increased the effective extraction radius of boreholes by 18.7%. Second, based on the coupling relationship between water lock formation pressure, interfacial tension, and pore structure, a criterion model for process transition was constructed, enabling quantifiable identification of the transition node between “pump–injection.” The water lock’s inhibition of gas release duration was improved by over 25% compared to conventional water injection. Finally, by integrating the multiple effects of high-pressure water injection—enhancing permeability, softening, displacement, and flow limitation—a “multi-purpose” synergistic pathway was established. This increased the pre-drainage gas concentration in the test working face by 40%, the pure gas extraction volume by 28%, and reduced gas over-limit incidents by over 50%. Experiments and industrial trials demonstrated that the application of this technology in the 15^# coal seam of Yixin Coal Mine shortened gas extraction by 36%, reduced borehole engineering by 72.8%, eliminated gas over-limit incidents during mining, and cumulatively generated economic benefits exceeding 425 million yuan in the same year, significantly improving the efficiency and cost-effectiveness of gas disaster prevention. Full article

Memory function is susceptible to decline with age, stress, and neurological diseases, highlighting the importance of exploring effective and sustainable strategies to enhance memory consolidation. Epinephrine plays a key role in memory consolidation; acute, moderate elevations enhance memory, while chronic high levels are inhibitory. Given the limitations of pharmacological interventions, this study aims to investigate exercise as a non-pharmacological means to promote post-learning memory consolidation by inducing acute epinephrine release, focusing on its mechanisms and optimized implementation strategies. This narrative review systematically reviews evidence from neurophysiology, molecular biology, and behavioral experiments and finds that exercise can safely and controllably activate the sympathetic–adrenal system, leading to a rapid rise in epinephrine. The release kinetics align highly with the critical time window for memory consolidation. Moderate-intensity aerobic exercise implemented within 30 min post-learning can significantly improve memory retention. The mechanisms involve not only epinephrine enhancing synaptic plasticity and LTP by activating hippocampal β-adrenergic receptors, but also synergistic effects across multiple systems, such as promoting osteocalcin signaling, upregulating BDNF expression, inducing neurogenesis, and optimizing cerebral metabolism and blood flow. Evidence suggests that exercise, as a non-pharmacological intervention, significantly enhances post-learning memory consolidation through the precise modulation of epinephrine release and multi-system synergy, offering both high efficacy and safety. Future research should focus on developing precise exercise prescriptions based on individual characteristics and leveraging wearable devices and digital technologies to improve intervention adherence and applicability, promoting its widespread use in educational and clinical settings. Full article

The growing pressure to achieve carbon neutrality has exposed major limitations in current industrial processes, which often operate in isolation, rely on simplified mass-balance assumptions, and struggle to manage increasingly complex material and energy flows. Traditional industrial symbiosis and circular economy strategies have improved resource efficiency, yet they rarely capture molecular-level interactions or enable coordinated optimization across multiple facilities, restricting their ability to support large-scale decarbonization. In this context, Carbon–Hydrogen–Oxygen Symbiosis Networks (CHOSYNs) have emerged as an advanced framework that integrates atomic-level targeting with multi-scale process systems engineering to identify synergies, valorization pathways, and cross-sector exchanges that conventional approaches overlook. This review consolidates the theoretical foundations, historical development, and recent applications of CHOSYNs, illustrating how it can enhance efficiency, reduce emissions, and strengthen resilience in energy systems, chemical industries, and circular resource management. Although the literature remains limited, existing studies demonstrate the promise of CHOSYNs as a unifying methodology for designing low-carbon industrial ecosystems. Key challenges related to scalability, validation, governance, and operational robustness are examined, and a roadmap is proposed to guide the evolution and practical deployment of CHOSYNs toward 2035. Full article

The selective catalytic reduction (SCR) system is a key component for addressing NOx emissions from internal combustion engines. To resolve the issues of modeling distortion in SCR systems and the difficulty in characterizing the local reaction mechanism, a multi-dimensional SCR reaction model based on the coupling of Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) dual mechanisms was established and conducted by experiment. The SCR catalytic characteristics and the dual-mechanism reaction process were systematically investigated. Additionally, based on the combined analysis of species concentration distribution coupled with temperature characteristics, a calculation method for the synergy of concentration-temperature fields was developed, and the synergistic characteristics of the concentration-temperature fields were explored. The results showed that high load accelerated the light-off speed, but this effect was counteracted by the negative impact of high flow rate. A strong negative correlation was maintained between temperature and NOx concentration across the full load range, and the axial consistency increased with load increasing. The results provide important theoretical support for the mechanism analysis of diesel engine SCR reactions and the optimization of thermal management. Full article

The current study presents a holistic technology evaluation and integration methodology for enhancing the aerodynamic efficiency and performance of a tactical, fixed-wing Blended-Wing-Body (BWB) Unmanned Aerial Vehicle (UAV) through the synergetic integration of several aerodynamic and performance-enhancing technologies. Based upon several individual technology investigations conducted in the framework of the EURRICA (Enhanced Unmanned aeRial vehicle platfoRm using integrated Innovative layout Configurations And propulsion technologies) research project for BWB UAVs, a structured Technology Identification, Evaluation, and Selection (TIES) is conducted. That is, a synergetic examination is made involving technologies from three domains: configuration layout, flow control techniques, and hybrid-electric propulsion systems. Six technology alternatives, slats, wing fences, Dielectric Barrier Discharge (DBD) plasma actuators, morphing elevons, hybrid propulsion system and a hybrid solar propulsion system, are assessed using a deterministic Multi-Attribute Decision Making (MADM) framework based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Evaluation metrics include stall velocity (V_s), takeoff distance (s_g), gross takeoff weight (GTOW), maximum allowable GTOW, and fuel consumption reduction. Results demonstrate that certain configurations yield significant improvements in low-speed performance and endurance, while the corresponding technology assumptions and constraints are, respectively, discussed. Notably, the configuration combining slats, morphing control surfaces, fences, and hybrid propulsion achieves the highest ranking under a performance-future synergy scenario, leading to over 25% fuel savings and more than 100 kg allowable GTOW increase. These findings provide quantitative evidence for the potential of several technologies in future UAV developments, even when a novel configuration, such as BWB, is used. Full article

Decarbonising the construction industry’s substantial ecological footprint demands credible substitutes that preserve structural performance while valorising waste. Although construction and demolition waste (CD&W) has been widely studied, the vast potential of agricultural residues (e.g., corncob, rice husk) and, crucially, their synergy remains underexplored. This study couples a systematic literature review with mathematical modelling to evaluate binary CD&W–agro-waste binders. A modified Andreasen–Andersen packing framework and pozzolanic activity indices inform multi-objective optimisation and Pareto analysis. The optimum identified is a 70:30 CD&W-to-agricultural ratio at 20% total cement replacement, predicted to retain 86.0% of OPC compressive strength versus a 79.4% average for single-waste systems (8.3% non-additive uplift). Life-cycle assessment (cradle-to-gate) shows a 20.3% carbon reduction for the synergistic blend (vs. 19.6% CD&W-only; 19.3% agro-only); when normalised by strength (kg CO₂-eq/MPa·m³), the blend delivers 6.3% better carbon efficiency than OPC (5.63 vs. 6.01), outperforming agro-only (5.79) and CD&W-only (6.61). Global diversion arithmetic indicates feasible redirection of 0.246 Gt y⁻¹ of wastes (5.7% of CD&W and 1.8% of agricultural residues) at 30% market penetration. Mechanistically, synergy arises from particle size complementarity, complementary Ca–Si reactivity generating additional C–S–H, and improved rheology at equivalent flow. Monte Carlo analysis yields a 91.2% probability of ≥40 MPa and 78.3% probability of ≥80% strength retention for the optimum; the 95% interval is 39.5–55.3 MPa. Variance-based sensitivity attributes 38.9% of output variance to the Bolomey constant and 44% to pozzolanic indices; interactions contribute 19.5%, justifying global (not local) uncertainty propagation. While promising, claims are bounded by cradle-to-gate scope and the absence of empirical durability and end-of-life evidence. The results nevertheless outline a tractable pathway to circular, lower-carbon concretes using co-processed waste. The approach directly supports circular economy goals and scalable regional deployment. Full article

Adult neurogenesis is well established in canonical niches—the dentate gyrus and the subventricular zone, where aerobic exercise reliably enhances progenitor proliferation, survival, and synaptic integration via increased cerebral blood flow, neurotrophins (e.g., BDNF, IGF-1), neurotransmitter regulation, and reduced neuroinflammation. Nutraceuticals (e.g., polyphenols, omega-3, creatine, vitamins) further support neuroplasticity and neuronal survival through convergent trophic, anti-inflammatory, and metabolic pathways. By contrast, the hypothalamus, a metabolically pivotal, non-canonical niche, remains comparatively understudied. Here, we synthesize anatomical and functional features of hypothalamic neural stem cells, primarily tanycytes (α1, α2, β1, β2), which line the third ventricle and differentially contribute to neuronal activity regulation, metabolic signaling, and cerebrospinal fluid–portal vasculature coupling, thereby linking neurogenesis to endocrine control. Notably, tanycytes can form neurospheres in vitro, enabling mechanistic interrogation. Although evidence for adult hypothalamic neurogenesis in humans is debated due to methodological constraints, animal data suggest potential relevance to disorders characterized by neuronal loss, metabolic dysregulation, and impaired neuroendocrine function. We propose that an integrative framework is timely: exercise and diet likely interact in the hypothalamic niche through shared mediators (BDNF, IGF-1, CNTF, GPR40) and exercise-derived signals (e.g., lactate, IL-6) that may be complemented by defined nutraceuticals. Yet critical uncertainties persist, including the extent of bona fide hypothalamic neurogenesis, nucleus-specific responses (arcuate nucleus, paraventricular nucleus, ventromedial hypothalamic nucleus), and the mechanistic integration of lifestyle signals in this region. To address these gaps, we outline actionable priorities: (i) single-cell and lineage-tracing studies of tanycyte subtypes under distinct training modalities (aerobic, high-intensity interval training, resistance); (ii) combinatorial interventions pairing structured exercise with nutraceuticals to test synergy on progenitor dynamics and inflammation; and (iii) multi-omics and translational studies to identify biomarkers and establish clinical relevance. Clarifying these interactions will determine whether lifestyle and supplementation strategies can synergistically modulate hypothalamic neurogenesis and inform therapies for neurological, neuropsychiatric, and metabolic disorders. Full article

We propose a local–global attention fusion network for benign–malignant discrimination of ovarian tumors in color Doppler ultrasound (CDFI). The framework integrates three complementary modules: a local enhancement module (LEM) to capture fine-grained texture and boundary cues, a Global Attention Module (GAM) to model long-range dependencies with flow-aware priors, and a Fusion Discriminator (FD) to align and adaptively reweight heterogeneous evidence for robust decision-making. The method was evaluated on a multi-center clinical dataset comprising 820 patient cases (482 benign and 338 malignant), ensuring a realistic and moderately imbalanced distribution. Compared with classical baselines including ResNet-50, DenseNet-121, ViT, Hybrid CNN–Transformer, U-Net, and SegNet, our approach achieved an accuracy of 0.923, sensitivity of 0.911, specificity of 0.934, AUC of 0.962, and F1-score of 0.918, yielding improvements of about three percentage points in the AUC and F1-score over the strongest baseline. Ablation experiments confirmed the necessity of each module, with the performance degrading notably when the GAM or the LEM was removed, while the complete design provided the best results, highlighting the benefit of local–global synergy. Five-fold cross-validation further demonstrated stable generalization (accuracy: 0.922; AUC: 0.961). These findings indicate that the proposed system offers accurate and robust assistance for preoperative triage, surgical decision support, and follow-up management of ovarian tumors. Full article

To address the problems of eutrophication exacerbation in water bodies caused by low carbon-to-nitrogen ratio (C/N) wastewater and the limited nitrogen removal efficiency of conventional constructed wetlands, this study proposes the use of biochar (Corncob biochar YBC, Walnut shell biochar HBC, and Manure biochar FBC) coupled with intermittent aeration technology to enhance nitrogen removal in constructed wetlands. Through the construction of vertical flow wetland systems, hydraulic retention time (HRT = 1–3 d) and influent C/N ratios (1, 3, 5) were regulated, before being combined with material characterization (FTIR/XPS) and microbial analysis (16S rRNA) to reveal the synergistic nitrogen removal mechanisms. HBC achieved efficient NH₄⁺-N adsorption (32.44 mg/L, Langmuir R² = 0.990) through its high porosity (containing Si-O bonds) and acidic functional groups. Under optimal operating conditions (HRT = 3 d, C/N = 5), the CW-HBC system achieved removal efficiencies of 97.8%, 98.8%, and 79.6% for NH₄⁺-N, TN, and COD, respectively. The addition of biochar shifted the dominant bacterial phylum toward Actinobacteriota (29.79%), with its slow-release carbon source (TOC = 18.5 mg/g) alleviating carbon limitation. Mechanistically, HBC synergistically optimized nitrogen removal pathways through “adsorption-biofilm (bacterial enrichment)-microzone oxygen regulation (pore oxygen gradient).” Based on technical validation, a dual-track institutionalization pathway of “standards-legislation” is proposed: incorporating biochar physicochemical parameters and aeration strategies into multi-level water environment technical standards; converting common mechanisms (such as Si-O adsorption) into legal requirements through legislative amendments; and innovating legislative techniques to balance precision and universality. This study provides an efficient technical solution for low C/N wastewater treatment while constructing an innovative framework for the synergy between technical specifications and legislation, supporting the improvement of watershed ecological restoration systems. Full article

With the deep integration of Internet of Vehicles (IoV) and edge computing technologies, the spatiotemporal dynamics, burstiness, and load fluctuations of user requests pose severe challenges to microservices auto-scaling. Existing static or periodic resource adjustment strategies struggle to adapt to IoV edge environments and often neglect service dependencies and multi-objective optimization synergy, failing to fully utilize implicit regularities like the symmetry in spatiotemporal patterns. This paper proposes a dual-phase dynamic scaling mechanism: for long-term scaling, the Spatio-Temporal Graph Transformer (STGT) is employed to predict traffic flow by capturing correlations in spatial–temporal distributions of vehicle movements, and the improved Multi-objective Graph-based Proximal Policy Optimization (MGPPO) algorithm is applied for proactive resource optimization, balancing trade-offs among conflicting objectives. For short-term bursts, the Fast Load-Aware Auto-Scaling algorithm (FLA) enables rapid instance adjustment based on the M/M/S queuing model, maintaining balanced load distribution across edge nodes—a feature that aligns with the principle of symmetry in system design. The model comprehensively considers request latency, resource consumption, and load balancing, using a multi-objective reward function to guide optimal strategies. Experiments show that STGT significantly improves prediction accuracy, while the combination of MGPPO and FLA reduces request latency and enhances resource utilization stability, validating its effectiveness in dynamic IoV environments. Full article

This study develops a synergistic optimization method of multiple gates integrating hydrodynamic simulation and data-driven methods, with the goal of improving the accuracy of water distribution and regulation efficiency. This approach addresses the challenges of large prediction deviation of hydraulic response and unclear synergy mechanisms in the coupled regulation of multiple gates in irrigation areas. The NSGA-II multi-objective optimisation algorithm is used to minimise the water distribution error and the water level deviation before the gate as the objective function in order to achieve global optimisation of the regulation of the complex canal system. A one-dimensional hydrodynamic model based on St. Venant’s system of equations is built to generate the feature dataset, which is then combined with the random forest algorithm to create a nonlinear prediction model. An example analysis demonstrates that the optimal feedforward time of the open channel gate group is negatively connected with the flow condition and that the method can manage the water distribution error within 13.97% and the water level error within 13%. In addition to revealing the matching mechanism between the feedforward time and the flow condition, the study offers a stable and accurate solution for the cooperative regulation of multiple gates in irrigation districts. This effectively supports the need for precise water distribution in small irrigation districts. Full article

This study focuses on the systematic conservation of historical architectural heritage in Heilongjiang Province, particularly addressing the challenges of point-based protection and spatial fragmentation. It explores the construction of a connected and conductive heritage corridor network, using historical building clusters across the province as empirical cases. A comprehensive analytical framework is established by integrating the nearest neighbor index, kernel density estimation, minimum cumulative resistance (MCR) model, entropy weighting, circuit theory, and network structure metrics. Kernel density analysis reveals a distinct spatial aggregation pattern, characterized by “one core, multiple zones.” Seven resistance factors—including elevation, slope, land use, road networks, and service accessibility—are constructed, with weights assigned through an entropy-based method to generate an integrated resistance surface and suitability map. Circuit theory is employed to simulate cultural “current” flows, identifying 401 potential corridors at the provincial, municipal, and district levels. A hierarchical station system is further developed based on current density, forming a coordinated structure of primary trunks, secondary branches, and complementary nodes. The corridor network’s connectivity is evaluated using graph-theoretic indices (α, β, and γ), which indicate high levels of closure, structural complexity, and accessibility. The results yield the following key findings: (1) Historical architectural resources in Heilongjiang demonstrate significant coupling with the Chinese Eastern Railway and multi-ethnic cultural corridors, forming a “one horizontal, three vertical” spatial configuration. The horizontal axis (Qiqihar–Harbin–Mudanjiang) aligns with the core cultural route of the railway, while the three vertical axes (Qiqihar–Heihe, Harbin–Heihe, and Mudanjiang–Luobei) correspond to ethnic cultural pathways. This forms a framework of “railway as backbone, ethnicity as wings.” (2) Comparative analysis of corridor paths, railways, and highways reveals structural mismatches in certain regions, including absent high-speed connections along northern trunk lines, insufficient feeder lines in secondary corridors, sparse terminal links, and missing ecological stations near regional boundaries. To address these gaps, a three-tier transportation coordination strategy is recommended: it comprises provincial corridors linked to high-speed rail, municipal corridors aligned with conventional rail, and district corridors connected via highway systems. Key enhancement zones include Yichun–Heihe, Youyi–Hulin, and Hegang–Wuying, where targeted infrastructure upgrades and integrated station hubs are proposed. Based on these findings, this study proposes a comprehensive governance paradigm for heritage corridors that balances multi-level coordination (provincial–municipal–district) with ecological planning. A closed-loop strategy of “identification–analysis–optimization” is developed, featuring tiered collaboration, cultural–ecological synergy, and multi-agent dynamic evaluation. The framework provides a replicable methodology for integrated protection and spatial sustainability of historical architecture in Heilongjiang and other cold-region contexts. Full article

The global transition toward low-carbon energy systems necessitates fundamental innovations in demand-side flexibility, particularly in industrial load regulation. This study presents a systematic review and critical analysis of 90 key research works (2015–2025) to establish a comprehensive framework for industrial load flexibility enhancement. We rigorously examined the tripartite interdependencies among the following: (1) Multi-energy flow physical coupling, addressing temporal-scale disparities in electricity-thermal-gas coordination under renewable penetration; (2) Uncertainty quantification, integrating data-driven and physics-informed modeling for robust decision-making; (3) Market mechanism synergy, analyzing demand response, carbon-P2P hybrid markets, and regulatory policy impacts. Our analysis reveals three fundamental challenges: the accuracy-stability trade-off in cross-timescale optimization, the policy-model disconnect in carbon-aware scheduling, and the computational complexity barrier for real-time industrial applications. The paper further proposes a roadmap for next-generation industrial load regulation systems, emphasizing co-optimization of technical feasibility, economic viability, and policy compliance. These findings advance both academic research and practical implementations for carbon-neutral power systems. Full article

Under the dual pressures of global climate change and rapid urbanization, urban drainage systems (UDS) face severe challenges caused by extreme precipitation events and altered surface hydrological processes. The drainage paradigm is shifting toward resilient systems integrating grey and green infrastructure, necessitating a comprehensive review of the design and operation of grey infrastructure. This study systematically summarizes advances in urban stormwater process-wide regulation, focusing on drainage network design optimization, siting and control strategies for flow control devices (FCDs), and coordinated management of Quasi-Detention Basins (QDBs). Through graph theory-driven topological design, real-time control (RTC) technologies, and multi-objective optimization algorithms (e.g., genetic algorithms, particle swarm optimization), the research demonstrates that decentralized network layouts, dynamic gate regulation, and stormwater resource utilization significantly enhance system resilience and storage redundancy. Additionally, deep learning applications in flow prediction, flood assessment, and intelligent control exhibit potential to overcome limitations of traditional models. Future research should prioritize improving computational efficiency, optimizing hybrid infrastructure synergies, and integrating deep learning with RTC to establish more resilient and adaptive urban stormwater management frameworks. Full article

Traditional settlements are vital carriers of Chinese agricultural civilization yet face mounting challenges in protection and inheritance amid rapid urbanization. Taking ancient Huizhou as a case study, this research analyzes the spatial distribution patterns of cross-provincial traditional settlements and constructs a multi-level heritage corridor network through circuit theory modeling and space syntax analysis. The study reveals a “small aggregation, large dispersion” spatial structure shaped by natural geography and socio-cultural dynamics. Simulation of multi-path cultural flows and network analysis show that high betweenness corridors concentrate along the northeast–southwest axis, promoting efficient cultural circulation, while low betweenness areas highlight gaps in direct connectivity. Closeness analysis identifies She County as the cultural core with a single-center radial structure, though internal fragmentation persists. Based on these findings, the study proposes a “three-core-driven, two-axis linkage, multi-source synergy” protection strategy to strengthens the spatial integrity and resilience of the heritage network. This research not only provides a systematic framework for the holistic conservation of Huizhou settlement heritage but also offers methodological references for the protection of traditional settlements in broader regions. Full article