Search Results (6,437)

The rapid expansion of artificial intelligence and cloud computing is straining terrestrial data center infrastructure, motivating exploration of space-based data centers (SBDCs) as a scalable and energy-efficient alternative. While orbital platforms offer unique advantages, including continuous solar energy, radiative cooling, and global coverage, their practical deployment is constrained by unresolved reliability challenges across the mission lifecycle. This study presents a lifecycle-oriented reliability and risk assessment for SBDCs spanning launch, orbital operation, maintenance, and end-of-life phases, using a structured systems-level analysis of failure modes and operational dependencies. This paper focuses on compute-centric SBDC architectures, treating storage solely as a supporting resource. We identify and classify space-environment-specific risks, including launch-induced mechanical stress, radiation-driven degradation, thermal extremes, and single points of failure in power and communication subsystems. By integrating engineering constraints with economic considerations, we develop a unified risk-chain framework that shows how reliability limitations propagate from component design to system cost and operational viability. The analysis reveals a critical trade-off: achieving terrestrial-grade reliability in orbit requires substantial redundancy and radiation hardening, increasing mass and cost and reducing economic feasibility, whereas lower-reliability designs introduce operational and financial risks that challenge sustainability. These findings establish reliability as the central determinant of SBDC viability, providing an applied foundation for fault-tolerant, modular, and lifecycle-aware design strategies essential for transitioning orbital cloud infrastructure from concept to scalable reality. Full article

Salt cavern Compressed Air Energy Storage (CAES) is one of the critical technologies for energy storage and an important infrastructure supporting the construction of new power systems and facilitating the achievement of the dual carbon goals. The salt rock resources in China are primarily composed of continental strata salt rocks, characterized by high heterogeneity, well-developed thin-layer interbedding, dissolution resistance among different lithologies, and significant creep variations. These features, to some extent, limit the improvement of wellbore construction accuracy, the reliability of abandoned well sealing, the safety of natural gas storage operations, and enhancements in gas injection–brine displacement efficiency. This study takes the continental bedded salt rock in the Dawenkou Basin as the research object and adopts a method combining theoretical analysis and field engineering verification to improve the systematic construction technology system, covering the whole process of drilling engineering, abandoned well plugging, the design of an injection and brine extraction device, and gas injection and brine drainage. The research results optimize four key technologies, including precise wellbore trajectory control, dual-section milling, and multi-stage redundant plugging of abandoned wells and long-term anti-corrosion completion with laser cladding, and dual-mode adaptive gas injection and brine drainage, and improve the technical system from wellbore construction to salt cavity formation. This study can provide valuable theoretical references and engineering demonstration guidance for underground space development projects in similar salt basins in China. Full article

Accurate non-invasive voltage measurement is critical for the stable operation of ultra-high-voltage direct-current (UHVDC) grids. In practical converter valve environments, voltage inversion based on the charge simulation method (CSM) may be affected by nearby charged conductors. To address this problem, this paper proposes a non-invasive voltage measurement method combining radially aligned near-conductor two-sensor differential electric-field measurement with three-dimensional electrostatic finite-element modelling. The differential electric field between two radial sensing positions is used for voltage inversion, which suppresses distant common-mode interference. When a nearby interference conductor exists, a weighted differential correction coefficient k is introduced to compensate for the residual radial interference component. Theoretical and simulation results show that k is a scenario-dependent coefficient affected by the measured voltage, sensor spacing, interference voltage, and geometric configuration. In an ultra-high-voltage (UHV) converter valve bridge-arm scenario with a 400 kV interference conductor, the absolute voltage inversion error is reduced from 0.50–1.57% FS before correction to below 0.20% FS after correction. Experiments on a 30 kV-scaled platform further verify the method under different measured voltages, sensor spacings, and interference-voltage levels, with the best-tested case reducing the maximum error from 0.93% FS to 0.16% FS. Full article

Real-world information diffusion frequently spans multiple heterogeneous platforms and relational layers, making multilayer influence maximization (MLIM) a critical and challenging problem. Existing methods for multilayer networks often rely on local structural signals for surrogate evaluation, failing to accurately characterize multi-hop diffusion and inter-layer coupling effects. In discrete combinatorial search, meta-heuristic random exploration often disrupts the structural inheritance and reuse of effective node configurations, compromising search stability and quality. To address these challenges, this paper proposes a Probabilistic-Based Multilayer Slime Mold Algorithm (PB-MSMA). It employs the slime mold algorithm as its search framework to perform discrete combinatorial optimization within a controlled candidate space. It utilizes the Preference-based Expected Diffusion Value (P-EDV) as a surrogate fitness metric during the search phase. This design reduces the need for repeated Monte Carlo simulations for iterative candidate evaluation while improving the characterization of inter-layer and higher-order diffusion effects. Furthermore, a probabilistic pipeline mechanism is introduced to encode recurring effective node configurations from historical searches as statistical priors, guiding the search process to enhance structural inheritance and stability. After the seed sets are obtained, the final influence spread of all compared methods is evaluated using 10,000 Monte Carlo simulations under the MLIC model. Experiments on six real-world multilayer network datasets and nine seed budgets show that PB-MSMA achieves a dataset-level improvement range of 3.68–14.50% over representative baselines, including CELF, DPSOMIM, Degree, DIRCI, and PRGC, with an average improvement of 10.32%. These results indicate that PB-MSMA provides an efficient seed-selection strategy for multilayer diffusion scenarios where repeated simulation-based evaluation is costly. Full article

Elderly individuals in rural China are highly vulnerable to extreme weather events and temperature fluctuations due to inadequate infrastructure in the built environment and constrained economic conditions, thereby increasing their health risks. Outdoor spaces represent one of the primary daily activity settings for rural older adults. However, existing research rarely links spatiotemporal patterns of outdoor activities to evidence-based thermal environment optimization, leaving a critical knowledge gap for age-friendly and sustainable rural design. This study focuses on the spatiotemporal differentiation patterns of daily outdoor activities among elderly people aged 60 years and above in rural Xi’an, as well as the optimization of spatial variations in thermal environments. Using on-site interviews, thermal environment measurements, thermal comfort questionnaires, continuous thermal environment monitoring, and machine learning based on random forest, this study drew the following conclusions: (1) outdoor activities in winter were concentrated between 9:00–11:00 and 13:00–17:00, while in summer, they shifted to the morning and evening periods, namely 6:00–9:00 and 17:00–21:00. (2) Models for outdoor clothing adjustment, thermal sensation, and thermal acceptability among elderly residents were established. The calculated neutral temperature was 10.19 °C, with a 90% outdoor thermal acceptability range of 9.6–27.2 °C and an 80% outdoor thermal acceptability range of 6.2–30.6 °C. These findings differ from those documented in regions with distinct climate zones and geographical settings. This discrepancy stems from regional climatic features, lifestyle variations between urban and rural older adults, and differences in the thermal environment quality of elderly-oriented outdoor activity spaces. (3) In winter, the acceptable period of the Universal Thermal Climate Index (UTCI) at south-facing entrances (10:30–16:30) was significantly longer than that in the courtyard (13:30–14:00). In summer, the comfortable period in the courtyard (before 10:00 and after 20:00) was longer than that at north-facing entrances (before 09:00). A random forest model for thermal sensation was established, and the relative importance of each parameter influencing thermal sensation was analyzed. On this basis, priority improvement pathways and strategies for the thermal environment, as well as suggestions for the subjective adaptive behaviors of elderly residents, were proposed. The research results of this study can provide technical solutions for age-friendly thermal environment design in rural areas, thereby safeguarding the comfort, health, and social well-being of the elderly population in rural areas. Full article

The high-value utilization of construction and demolition waste is critical for sustainable development in the building sector. However, in construction and demolition waste (CDW) recycling supply chains, existing studies lack a systematic analysis of pricing mechanisms for such recycled CDW as substrate products, particularly regarding interest coordination and the quantification of green value. To reveal the bargaining mechanism between farmers as recyclers and processors and supermarkets as retailers under an asymmetric bargaining structure, this study applies Nash bargaining theory to construct a dynamic game model. The study revealed that (1) when the green degree of a product reaches a certain level, it can obtain a sustainable market premium and create a stable income space for both parties. (2) The relative strength of the bargaining power between the two sides significantly affects the impact of market base scale changes on profit distribution. When the bargaining power of the supermarket is lower than the threshold and the bargaining power of the farmers is higher than the threshold, the difference in profit between the farmers and the supermarket is negatively correlated with the market base scale of the CDW as a substrate. (3) The green sensitivity level of consumers affects the difference in profit of the main body with the government subsidy to farmers. This level is determined by the value of the green sensitivity coefficient of consumers and presents a differentiated adjustment effect in different value ranges, which in turn affects the transmission direction of government subsidies to profit distribution. (4) When the green sensitivity coefficient and the green communication intensity of farmers and the investment level are lower than the corresponding critical values, the difference in social welfare with or without subsidies is positively correlated with the amount of the subsidy. This study provides decision support for farmers and supermarkets in designing rational bargaining strategies and offers insights for improving coordination and sustainability in construction and demolition waste recycling supply chains. Full article

Home indoor environments are characterized by alternating open spaces and obstacle-cluttered regions, which pose critical challenges to the autonomous navigation of home service robots. Existing hybrid path planning algorithms generally suffer from three core limitations: low global search efficiency, weak global-local planning coordination, and poor dynamic scene adaptability. To tackle these issues, this paper presents a novel hierarchical path planning framework combining an enhanced Jump Point Search (JPS) and a fuzzy-optimized Dynamic Window Approach (DWA). In the global planning layer, an adaptive Octile heuristic JPS based on local obstacle density is designed to reduce redundant node expansion and accelerate global path search, with a bounded suboptimality guarantee. To bridge global and local planning, a look-ahead distance-based dynamic waypoint selection strategy is developed to match the optimal waypoint in real time according to the robot’s motion state and environmental complexity, enabling seamless coordination between global path guidance and local trajectory generation. In the local planning layer, a fuzzy logic controller is introduced to dynamically tune the weights of the DWA trajectory evaluation function, which significantly improves the robot’s dynamic obstacle avoidance capability and motion smoothness. Comparative simulation experiments verify that the proposed method not only outperforms the conventional hybrid path planning algorithm, reducing expanded nodes by 68.09% and global planning time by 52.94%, while improving dynamic obstacle avoidance success rate by 31.43% and overall navigation efficiency by 23.95%, it also achieves better comprehensive navigation performance than the widely adopted PSO-DWA comparison algorithm. The proposed framework shows superior comprehensive performance and is well suited for the indoor autonomous navigation of home service robots. Full article

With the rapid evolution of cyberattack techniques, identifying dynamic behavioral intents from Application Programming Interface call sequences has become a fundamental modality for ensuring reliable malware detection and information security. However, existing detection methods face the dual challenges of semantic sparsity and inadequate spatial dependency modeling when processing these sequences, which fundamentally undermines their stability against complex structural variations and in-the-wild evasive patterns. To address these critical vulnerabilities, we propose LLM-SGCF, a highly effective malware detection framework that jointly models deep behavioral semantics and spatial structures. Specifically, our framework leverages generative Large Language Models, which are subsequently encoded by BERT, to transform sparse API calls into rich and contextualized descriptions. Concurrently, it employs a novel Spatially Guided Convolution (SGC) module to localize critical malicious segments and extract cross-position dependencies in a two-dimensional semantic space. Extensive experiments on the public Aliyun and Catak datasets demonstrate that LLM-SGCF exhibits exceptional resilience to real-world structural complexity and significantly outperforms state-of-the-art baselines, achieving a peak binary-classification accuracy of 95.82%. Further ablation analyses confirm that the synergistic fusion of semantic enhancement driven by Large Language Models and spatial structural modeling dramatically improves the resilience of the framework against complex attack chains, providing a highly reliable paradigm for next-generation malware recognition systems. Full article

To elucidate the wear evolution and failure mechanisms of VL-type composite seals in aviation hydraulic actuators under multiple operating conditions, a two-dimensional plane-strain finite element model was developed for a VL seal consisting of a PTFE L-ring and an NBR O-ring. The model incorporated the Mooney–Rivlin hyperelastic constitutive law and the Archard wear model. The effects of O-ring compression ratio, hydraulic pressure, sliding velocity, and temperature on cumulative wear, wear rate, and contact state were systematically investigated. The results show that the compression ratio has a nonlinear influence on wear. Within 8–16%, the peak wear increases approximately linearly with compression ratio; above 16%, the peak wear reaches a plateau and a secondary wear zone appears, indicating a transition from single-contact to multi-contact sealing. Hydraulic pressure promotes wear over the range of 4–28 MPa, and at 28 MPa the opposite lip edge of the L-ring comes into contact with the cylinder wall, weakening the sealing effectiveness. Within 0.1–0.3 m/s, wear increases approximately linearly with sliding velocity. However, under high velocity and insufficient hydraulic pressure, the L-ring may undergo inversion, resulting in complete seal failure. Temperature exhibits a non-monotonic effect: material softening reduces local contact stress and wear from −55 to 80 °C, whereas excessive softening at 135 °C causes the peak wear rate to increase again. A parametric analysis scheme involving an increased L-ring height and thickness, a reduced O-ring cross-section diameter, and reserved deformation space raises the critical compression ratio for stable single-contact sealing from 16% to above 20%. These findings clarify the contact-stress/contact-area competition mechanism governing VL seal wear and provide guidance for the design of aviation hydraulic actuator seals. Full article

Modeling historically situated gender ideology remains challenging for language models, as contemporary embeddings struggle to reflect temporally specific semantic structures beyond surface lexical patterns. Although large language models exhibit extensive general-purpose performance, their direct use with history-specific semantic analysis is limited by the distributional mismatch between contemporary training data and historical linguistic patterns. These constraints encourage the distillation of temporally based semantic knowledge into small student architectures. To solve this issue, we propose Temporally Informed Distillation of Embedding Semantics (TIDES), which integrates continued pretraining on temporally specific corpora with feature-level distillation from large embedding teachers. We evaluate TIDES across teacher architectures with distinct pretraining objectives. While continued pretraining provides lexical and syntactic adaptation, our results show that improvements in ideological modeling cannot be attributed to additional training exposure alone. Rather, teacher–student structural alignment is also critical to transfer effectiveness. Contrastive, encoder-aligned teachers yield substantially more stable preservation of fine-grained, historically situated semantic distinctions. These findings suggest that temporal ideology transfer is representation-dependent: ideological meaning can be shaped by the geometry and training objectives of embedding spaces. By introducing TIDES and providing evidence that architectural compatibility can influence ideological inheritance, this study advances a representation-centered account of modeling ideology in temporally grounded semantic research. Full article

The ionosphere is the ionized region of the atmosphere, extending roughly from 60 km to 1000 km in altitude. During flares, the near-Earth space is subjected to high-energy X-ray and EUV (extreme ultraviolet radiation) radiation, which also impacts the ionosphere. The changes in the ionospheric parameters measured by ionosondes, namely the f_min (minimum frequency) and foF2 (F2-layer ordinary-mode critical frequency) values, were examined during solar flares that occurred in geomagnetically quiet conditions (Dst (Disturbance Storm Time index) > −40 nT, Kp (planetary K-index) < 4). The necessary data were obtained by manually evaluating ionograms recorded by the Czech DPS4D ionosonde at Pruhonice (PQ052). The degree of variation was compared to quiet reference days, allowing for the determination of the deviations in the required values (df_min, dfoF2). The time series of the deviations were investigated. Furthermore, the relationship between the deviations and a “geoeffectiveness” parameter of the solar flare was also examined. The X-ray flux, the solar zenith angle of the station at the time of the event, and the position of the flare on the solar disk were also taken into account for the determination of the “geoeffectiveness” parameter. A positive correlation was observed between df_min and the geoeffectiveness parameter of the flare, which was more significant than the correlation between the dfoF2 and the geoeffectiveness parameter. Full article

We investigate how causal DAG learning algorithms and structural assumptions influence counterfactual decision safety. Four structure learning regimes are compared: expert-guided edge-constrained HC+BIC, unconstrained HC+BIC, MMPC+HC+BIC, and the PC-Stable algorithm. Evaluation is conducted using a leave-one-state-out protocol over a fully enumerated state–action space in a controlled offline autonomous driving setting. The environment is characterized by seven Boolean state variables and six actions, allowing us to disentangle the effects of learning strategies on counterfactual decisions. All models are implemented as probabilistic logic twin networks (PLTNs), with additional sensitivity analysis across parameter configurations. The learning regimes produce markedly different counterfactual decisions. Edge-constrained HC+BIC recommends a diverse set of safe actions, while unconstrained HC+BIC yields fewer but consistently safe alternatives. MMPC+HC+BIC frequently fails to identify safe actions, often associated with weak connectivity of the outcome variable. PC-Stable produces varied recommendations but may include unsafe actions, which is linked to incorrect edge orientations between actions and outcomes. These findings show that structure learning choices and prior knowledge influence counterfactual decisions through the learned structure, affecting the identification of safe alternatives in safety-critical applications. Full article

Large-aperture steerable reflector antennas are pivotal for deep-space exploration and satellite communication, but their high-frequency performance is often compromised by wind-induced structural deformations. This study employs a high-fidelity fluid–structure interaction (FSI) framework, coupling Computational Fluid Dynamics (CFD) and the Finite Element Method (FEM), to investigate the dynamic response of an 18 m Square Kilometre Array (SKA) antenna under transient wind loads. The structural FEM is validated against experimental modal data, ensuring the capture of essential vibration characteristics. We evaluate steady-state wind pressure coefficients ($C_p$) and transient responses under a simulated Davenport wind spectrum across the antenna’s full operational elevation range. Surface accuracy degradation is rigorously quantified using the Root Mean Square Error (RMSE) of the best-fit paraboloid. The results demonstrate a significant correlation between peak deformation and surface error, pinpointing 15° and 90° pitch angles as the most critical configurations for profile degradation due to the “air pocket effect” and asymmetric pressure distributions, respectively. These insights establish a robust theoretical basis for structural optimization and the development of active surface control strategies for next-generation aerospace signal acquisition infrastructure. Full article

Direct current (DC) surface flashover on polystyrene (PS) remains a critical bottleneck that impedes its reliable application in high-voltage insulation apparatus. To circumvent the protracted processing durations and stringent film-forming conditions inherent in conventional surface modification techniques, this study proposes a novel “liquid-film-assisted in situ rapid plasma curing” strategy. By harnessing atmospheric-pressure dielectric barrier discharge (DBD) technology within an argon ambient, the rapid (<6 min) and efficient deposition of a fluorosilane (FAS-13) functional coating onto the substrate was achieved. Microscopic characterizations coupled with isothermal surface potential decay (SPD) measurements reveal that this coating substantially mitigates the detrapping and surface migration of charge carriers. Macroscopic DC flashover testing corroborates that, under the optimal modification ratio, the surface breakdown voltage of PS is elevated to 14.04 kV, yielding an insulation gain of 26.94%. To elucidate the underlying physical mechanisms, density functional theory (DFT) calculations were conducted, revealing that the energy band misalignment between the wide-bandgap fluorinated layer and the substrate facilitates the construction of a high-density deep trap network (with a depth of ~0.8 eV) at the coating–substrate interface. By robustly anchoring primary electrons and inducing the formation of a homopolar space charge shielding layer, these deep traps physically arrest the evolution of the secondary electron emission avalanche (SEEA). Consequently, this work not only establishes a viable engineering framework for the rapid, large-scale surface reinforcement of DC insulation equipment but also provides profound quantum chemical insights into interfacial trap regulation within all-organic dielectrics. Full article

The highly nonlinear aerodynamic interference in tandem-airfoil configurations significantly hinders the precise exploitation of their aerodynamic potential. To address this issue, this study establishes a high-fidelity computational fluid dynamics benchmark. A high-quality sample set is constructed using Latin hypercube sampling combined with an intra-layer replacement strategy. Subsequently, a Gaussian process surrogate model and Bayesian optimization are employed to maximize the total system lift coefficient across a four-dimensional design space comprising longitudinal and vertical separations, fore airfoil angle of attack, and angle of attack difference. Global sensitivity analysis indicates that longitudinal separation dominates the interference modes. Optimization reveals a distinct mode switching phenomenon using a longitudinal separation of twice the chord length as the critical threshold. In the close-coupled configuration, a negative optimal angle of attack difference enhances the slot effect and upwash induction, thereby delaying rear airfoil stall and achieving synergistic lift enhancement. Conversely, in the distant-coupled configuration, the system transitions to a decoupled compensation mode, where a positive angle of attack difference compensates for the effective angle of attack loss induced by wake downwash. This research elucidates the competitive mechanisms between inter-airfoil slot flow and wake interference, providing a theoretical reference for the aerodynamic layout optimization of tandem-airfoil aircraft. Full article