Search Results (63,680)

In networked control systems, power line communication technique is used to transfer data over existing energy cables. A soft fault degrades the integrity of the signal without impacting the system behaviour. This work develops a transferometry-based method for detecting, localising, and estimating the severity of two simultaneous soft faults in such cables. A soft fault is modelled as a series impedance, and the transmission coefficient (TC) is computed from the ABCD cascade model of the cable. We prove that, under unmatched terminations, the time-domain TC exhibits a five-pulse signature whose peak positions and amplitudes map directly to the two fault positions and their individual severities. A residual signal constructed from this signature yields closed-form estimators for the fault positions and their combined severities; individual fault severities require a bounded nonlinear least-square fit, valid for approximately symmetric, known terminations. We further show that the method extends to n simultaneous soft faults under a combined soft-fault condition, with the $(2n+1)$-pulse pattern verified in simulation for $n\in \{1,2,3,4\}$. A Monte Carlo study using correct localisation probability as the detection criterion establishes a practical SNR threshold of 25 dB; fault-separation resolvability shows intermittent, sidelobe-driven degradation rather than a single threshold. Simulations on a measured 24 AWG cable, extrapolated beyond its characterised band, confirm reliable two-fault diagnosis under additive noise, with reliable multi-fault performance demonstrated for $n=1,2$, presented as a numerical proof of concept on this extrapolated cable model rather than a characterisation confirmed by measurement over the full simulated band. Full article

Accurate estimation of mangrove carbon stocks and the driving mechanisms behind their spatial patterns are crucial for blue carbon assessment and management. This study addresses several challenges in remote sensing estimation of mangroves, including the limited generalizability of single estimation models, the difficulty in directly inverting belowground biomass (BGB), and insufficient analysis of the driving mechanisms underlying spatial heterogeneity. Using typical coastal mangrove distribution regions as the study area, an analytical framework integrating species-specific modeling, high-accuracy species classification, and multi-dimensional mechanism analysis was constructed by combining GF-1 remote sensing images with field survey data. First, species-specific aboveground biomass (AGB) and belowground biomass estimation models were established. Subsequently, high-precision mangrove species classification was achieved, with an overall species classification accuracy of 98.18% and a Kappa coefficient of 0.94. Furthermore, a variety of methods—including SHAP analysis, geographical detectors, and structural equation modeling (SEM)—were comprehensively applied to systematically examine the driving mechanisms behind the spatial distribution of carbon stocks. The results indicate that spatial heterogeneity in carbon stocks is primarily driven by spatial characteristics (latitude (Lat) and longitude (Lon), explanatory power = 0.514), with topographic characteristics (DEM, slope, aspect, explanatory power = 0.239) playing a synergistic and enhancing auxiliary role, and significant interactions existing among these factors. This study significantly improves the accuracy of mangrove carbon stock estimation and deepens the understanding of its driving mechanisms, providing scientific methodology and a case study support for refined monitoring, conservation, and carbon sink management of coastal blue carbon ecosystems. Full article

Pneumatic artificial muscles, including McKibben-type actuators, offer high power-to-weight ratio, compliance, and inherent safety, but their nonlinear pressure–contraction behavior, hysteresis, saturation, and load-dependent dynamics make accurate position control challenging. This study develops a practical data-driven workflow that derives a branchwise feedforward compensator and an LQI or PID controller from one open-loop characterization experiment. Quasi-static characterization first identifies a conservative control-ready voltage window. A bounded random excitation within this window is replayed with $4\mathrm{s}$ holds to expose terminal and transient behavior. The same experiment supplies branchwise discrete plant models and a feedforward lookup. Two open-loop-derived transient layers, voltage creep compensation and dynamic pressure referencing, are applied to the raw lookup before simulation. Four controller variants are compared on a common simulated closed-loop benchmark built from the identified plant: a feedforward-only baseline, a branchwise proportional–integral–derivative (PID) baseline, a base linear quadratic integral (LQI) controller with displacement and pressure feedback, and a velocity-state LQI extension with a filtered velocity estimate. A multi-metric optimization score balances tracking RMS, settled oscillation, command activity, saturation, and gain magnitude. The score selects the base LQI within the LQI family. The selected gains and transient layers are deployed in a real-time implementation with manually reduced position gains. The controllers are then evaluated on a common reference stream against the physical actuator. Although simulation metrics cannot be transferred directly to the real system, the combined-metric ranking of the controllers remains unchanged. Full article

Plain river networks are weakly flushed and frequently regulated, which can decouple instantaneous water quality from biological responses. We integrated physicochemical variables, phytoplankton, zooplankton, benthic macroinvertebrates and fish environmental DNA (eDNA) to diagnose ecological condition in the Lixiahe plain river network, China. Regional water quality was assessed at 62 sites, and coupled analyses used 36 sites with complete multi-trophic data. Moderate pollution accounted for 62.90% of classified sites, with total nitrogen as the principal pressure. After Benjamini–Hochberg correction, seven independent associations with primary biological indicators remained significant, mainly linking TOC and TDS with planktonic metrics; the TOC-MEII correlation was treated separately as a non-independent composite association. Mean fish eDNA observed OTU richness declined to 22.33 at the three severely polluted matched sites, although grade-wise contrasts were descriptive because both extreme groups contained only three sites. Adjusted R² values for the four RDA models ranged from 9.8% to 11.4%; all overall fixed-seed permutation tests were significant (p = 0.0002–0.0298), indicating a detectable but limited water-quality signal. The study-specific MEII ranged from 29.50 to 67.42 (mean 48.04). These results show asynchronous trophic responses and support MEII as a preliminary within-survey screening tool that should be interpreted with its component sub-indices rather than as a calibrated reference-condition index. Full article

Atmospheric turbulence is a key multi-scale motion affecting numerical weather prediction, aviation safety, and atmospheric mass-energy exchange. Thorpe analysis is a classic method for turbulence retrieval, but traditional observations are limited by low spatiotemporal resolution, the absence of a stratospheric turbulence inversion framework, and insufficient cross-layer comparisons between northern and southern China, restricting the understanding of turbulence modulation mechanisms. Based on the domestic round-trip intelligent sounding system, atmospheric observations at 12 stations in Guangdong and Inner Mongolia from December 2022 to March 2023 are collected, with ascending-phase profiles used in the turbulence analysis and synergistically analyzed with ERA5 reanalysis data, which provide the background wind fields for westerly jet identification and precipitation data for environmental modulation assessment. Results show that turbulence in the study area shows significant layered differentiation and a latitudinal contrast between the southern and northern stations: the troposphere is the main turbulent layer, southern tropospheric turbulence is mainly associated with solar radiation, and northern tropospheric turbulence is mainly related to large-scale dynamic processes; stratospheric turbulence occurs sporadically only at northern stations under westerly jet-induced wind shear and is nearly absent in the south. Precipitation modulates southern tropospheric turbulence, while the westerly jet acts as a key dynamic factor for northern stratospheric turbulence. By integrating in situ radiosonde profiling with reanalysis data, this work supports refined turbulence detection and parameterization model optimization, and provides a scientific basis for weather forecast improvement and aviation route planning. Full article

Background/Objectives: Traumatic bladder rupture often accompanies pelvic fracture, making it uncertain whether differences between extraperitoneal bladder rupture (EPBR) and intraperitoneal bladder rupture (IPBR) reflect the rupture site itself or overall trauma burden. Prior multi-institutional evidence has focused on EPBR. We therefore examined whether rupture site was associated with hospital length of stay after accounting for concomitant pelvic fracture and injury severity. Methods: We retrospectively reviewed 46 adults with definite traumatic bladder rupture treated at a single regional trauma center from January 2014 through December 2024. Rupture site was the primary exposure, hospital length of stay was the primary outcome, and intensive care unit (ICU) length of stay was the secondary outcome. Parsimonious exploratory log-linear models included rupture site, concomitant pelvic fracture, and Injury Severity Score (ISS). Results: Twenty-one patients had IPBR, 25 had EPBR, and 26 had concomitant pelvic fracture. In the adjusted primary-outcome analysis, rupture site was not clearly associated with hospital length of stay (EPBR versus IPBR adjusted ratio, 1.02; 95% CI, 0.59–1.76). The secondary adjusted analysis likewise showed no clear association with ICU length of stay (adjusted ratio for ICU days + 1, 1.31; 95% CI, 0.77–2.21). In unadjusted comparisons, pelvic fracture was observed more frequently with EPBR (72.0% versus 38.1%; p = 0.021; FDR q = 0.078), and EPBR was associated with longer hospital stay (median, 44.0 versus 24.0 days; p = 0.024; FDR q = 0.078) and ICU stay (8.0 versus 4.0 days; p = 0.007; FDR q = 0.037). Among 42 surgically treated patients, EPBR was associated with a longer admission-to-repair interval (adjusted ratio for days + 1, 2.21; 95% CI, 1.28–3.82). Conclusions: After adjustment for concomitant pelvic fracture and ISS, rupture site was not clearly associated with hospital or ICU length of stay. The conditional admission-to-repair finding may reflect complex trauma-care pathways rather than diagnostic delay. The frequent coexistence of bladder rupture and pelvic fracture reinforces the clinical importance of careful bladder assessment in patients with severe pelvic trauma. Full article

Early-exit deep neural networks (DNNs) can reduce edge-inference latency, but abrupt variations in wireless and computing resources can destabilize split-inference policies. This paper proposes a meta-learning-driven adaptive control framework for joint backbone splitting and early-exit routing in MobileViT. The framework formulates multi-exit splitting as a constrained Markov decision process (CMDP) and introduces splitting-aware multi-dimensional adaptive proximal policy optimization (SMAPPO). SMAPPO combines nonlinear quality-of-service (QoS) penalties with topology-aware action masking, while cross-environment meta-initialization supports edge-local adaptation after resource disturbances. Under the stated simulation assumptions, SMAPPO reached the highest performance-index plateau among six methods in a representative 500-episode stationary trace and achieved the lowest normalized total cost across three latency–energy preference settings. Across ten seeds and nine stationary or disturbed scenarios, online SMAPPO achieved a 77.20% measured accuracy and 22.40 mJ of system energy. With an adaptation horizon of $K=14$, SMAPPO yielded a post-disturbance mean latency of 37.68 ms, a QoS-violation rate of 2.24%, and an on-time completion rate of 98.69%. These results indicate that combining meta-initialization, nonlinear constraint shaping, and topology-aware action masking improves stationary optimization and disturbance recovery within the controlled simulator. Full article

Understanding microbial community assembly mechanisms in aquatic habitats is fundamental to predicting ecosystem responses to environmental change, yet systematic comparisons of deterministic versus stochastic process contributions among different water types remain limited. We conducted monthly sampling over one year from four freshwater habitats, including two aquaculture ponds (WC01, WC02), an enclosed urban lake (TZ), and a flowing river (XJ), and applied a phylogenetic-bin-based null model framework to uncover how bacterial community assembly processes change among habitats and time/season. The results indicated that homogeneous selection (33.5%), dispersal limitation (31.0%), and drift (26.5%) jointly governed community assembly across all samples. Among the four investigated systems, water type, rather than season or their interactions, emerged as the primary factor regulating assembly process differentiation. Specifically, homogeneous selection was significantly stronger in the two aquaculture ponds (WC01, WC02) than in the natural water bodies (TZ and XJ), while the flowing river XJ exhibited the highest dispersal limitation and the lowest drift. At the phylogenetic bin level, over 98% of bins switched their dominant assembly strategies across the four water bodies, especially between the two aquaculture ponds and the two natural water bodies. Environmental factor analyses also revealed habitat-specific driving patterns: nitrogen and phosphorus nutrients dominated homogeneous selection in the aquaculture ponds, whereas dissolved oxygen, turbidity and oxidation reduction potential mainly regulated dispersal limitation in the natural waters. Collectively, these findings reveal a hierarchical pattern of freshwater bacterial assembly with multi-process coordination, habitat dominance, and lineage-level differentiation, and underscore that lineage-level analyses are essential for uncovering assembly patterns hidden at the community level, offering practical guidance for microbial management under diverse hydrological conditions. Full article

Asian elephants (Elephas maximus) face substantial thermoregulatory constraints because of their large body size, low relative surface area, sparse hair, and lack of functional sweat glands. Reliable body temperature measurement is essential for assessing thermal status and evaluating welfare in both wild and managed populations, but conventional rectal thermometry requires close physical contact, animal training, and repeated manual handling, making high-frequency, continuous, large-scale monitoring impractical. This study developed a non-invasive framework for automatically detecting the outer ear and extracting auricular surface temperature from infrared thermograms. Rectal temperature, regional surface temperatures, ambient temperature, and relative humidity were measured synchronously in eight semi-captive Asian elephants, yielding 425 matched observations. The associations between rectal temperature and the surface temperatures of three anatomical regions (head, outer ear, torso and limbs) were analyzed using repeated-measures correlation accounting for the non-independence of repeated measurements. Mean outer-ear temperature showed the strongest within-individual association with rectal temperature (r_rm = 0.395, p < 0.001), identifying the outer ear as the optimal thermal window for subsequent automated monitoring. Eight lightweight YOLO models—YOLOv5n, YOLOv5s, YOLOv8n, YOLOv8s, YOLO11n, YOLO11s, YOLO26n, and YOLO26s—were trained on 2178 annotated infrared images and evaluated on an independent 194-image test set from extra elephants. Model performance was assessed using detection metrics, inference speed, Bland–Altman agreement, Taylor diagram statistics, and a weighted multi-criteria score with Monte Carlo sensitivity analysis. YOLO11n achieved the best overall performance, with an mAP50 of 0.933 and an inference speed of 164 frames per second. The proposed framework provides an efficient method for automated auricular temperature monitoring and has potential applications in elephant welfare management and remote physiological surveillance. Full article

To address the challenge of quantitatively identifying thermal-resistance contributions from multi-layer packaging structures within liquid-cooled insulated-gate bipolar transistor (IGBT) modules, this study establishes a three-dimensional conjugate heat-transfer model incorporating the chip, solder layer, direct-bonded copper (DBC) ceramic layer, substrate, elliptical pin-fin heat sink, and fluid domain. The IGBT and fast-recovery diode (FRD) power losses under typical motor controller operating conditions are modeled as volumetric heat sources applied to the chip region. Based on model validation, an internal thermal bottleneck evaluation method is proposed using inter-layer temperature-drop decomposition, introducing the thermal bottleneck number (BN) to quantify the temperature-drop contribution of each packaging layer along the target chip’s heat-dissipation path. Results show that in the baseline structure, the DBC ceramic layer is the critical internal thermal bottleneck, with a BN value of 11.05%. When the DBC thermal conductivity increases from 20 W/(m·K) to 80 W/(m·K), the maximum junction temperature of the IGBT decreases from 413.32 K to 396.79 K, and the BN drops from 11.05% to 3.69%. Conversely, when the DBC thickness increases from 0.20 mm to 0.50 mm, the maximum junction temperature rises from 405.45 K to 424.42 K. Further analysis reveals that after weakening the DBC thermal bottleneck, the relative temperature-drop contribution of the solder interface becomes increasingly apparent; notably, a central 20% low-conductivity defect in the solder layer raises the maximum junction temperature to 517.16 K, 103.84 K higher than under normal solder conditions. These findings provide valuable insights for identifying internal thermal bottlenecks and optimizing packaging structures in liquid-cooled IGBT modules. Full article

Cyber incidents can disrupt many virtual power plant (VPP) assets through shared software and communication services. This study links preventive finance, cyber defense, dispatch, and restoration in one multi-timescale model. An attacker, a VPP operator, a bond vehicle, and a regulator interact in a partially observable stochastic game. The operator controls hardening, dispatch, isolation, and recovery. The bond provides restricted pre-event capital and releases collateral through an auditable index of service loss, control availability, network stress, and recovery delay. A risk-constrained multi-agent policy enforces power-system feasibility, investor impairment, sponsor affordability, and trigger–loss limits. Tests use transparent synthetic VPP-39 and VPP-118 portfolios and 20 out-of-sample seeds. The proposed design lowers normalized social cost to 0.691 and 0.704 and weighted basis risk to 0.065 and 0.071. It also improves critical-load continuity and restoration relative to self-insurance and three bond baselines. The VPP-118 case recovers in 11.8 h, compared with 14.3 h for the closest rule-based benchmark. Ablations separate the effects of finance and control. Removing the coupon–control link reduces verified hardening from 0.672 to 0.519. Removing the safety projection raises unsafe proposals from 0.4% to 5.9%. These results show that stochastic multi-timescale control can support adaptable and resilient VPP operation while keeping the financial mechanism within explicit risk limits. Full article

Fashion trend forecasting is crucial for proactive supply chain management, sustainable production, and personalized marketing. However, accurately predicting fine-grained fashion trends across diverse user groups remains challenging, as conventional numerical models rely solely on historical popularity signals and cannot explicitly exploit the high-level semantic context underlying trend evolution. To address this limitation, we propose a Dual-Stream Driven Fashion Trend Forecasting (DDFTF) framework that integrates numerical forecasting with textual semantic reasoning. The numerical stream employs a multi-scale patch Transformer with metadata-aware feature fusion to capture temporal dynamics, while the semantic stream converts historical trends into structured textual descriptions, extracting interpretable semantic representations of global trends and turning points. A residual fusion module combines both streams by treating semantic signals as complementary corrections to numerical predictions. Extensive experiments on the FIT and GeoStyle benchmarks demonstrate that DDFTF consistently outperforms state-of-the-art methods, achieving up to a 14.6% relative MAE reduction in long-term forecasting. Ablation and qualitative analyses further show that the performance gains arise from meaningful semantic information rather than increased model capacity, while also improving the interpretability of fashion trend prediction. Our code is publicly available. Full article

Axial blood pumps serve as vital auxiliary therapeutic devices for patients with end-stage heart failure, and parameter optimization of the controller is critical to improve system performance. Existing optimization methods cannot satisfy the parameter optimization requirements of variable-speed axial blood pump controllers in terms of optimization accuracy. Therefore, this paper investigates a many-objective optimization method adapted to the operating characteristics of blood pumps. Firstly, a many-objective optimization model is established for the controller. To efficiently solve the proposed model, an optimization algorithm integrating deep reinforcement learning, named DQN-NSGA-CT, is developed. On the basis of the population evolution state, the optimal strategy learned by DQN dynamically adjusts the crossover probability and mutation probability, which adaptively balances population diversity in the early iteration stage and convergence speed in the later iteration stage. Meanwhile, a novel environmental selection strategy is used to reconcile population convergence and diversity. To select the best compromise solution, an entropy weight–Copula–TOPSIS comprehensive evaluation method is proposed, which realizes objective weight assignment, objective correlation correction and multi-attribute ranking. Experimental results verify the efficiency of the DQN-NSGA-CT algorithm in solving the many-objective optimization model of the controller. The research addresses the many-objective optimization problem of variable-speed axial blood pump control. Full article

As urban mining plays an increasingly important role in resource security and sustainable development, insufficient coordination among reverse supply chain participants has become a major constraint on the efficient recovery of urban mineral resources. From the perspective of interfirm cooperative innovation, this study takes waste mobile phones as an application context and develops a four-party evolutionary game model involving the government, recyclers, remanufacturers, and consumers. The model incorporates opportunistic behavior in cooperative innovation, government subsidy intensity, and product pricing into a unified analytical framework. Replicator dynamics, Jacobian-based stability analysis, and numerical simulations are employed to examine the evolutionary mechanisms and stability conditions of multi-actor collaborative governance. The results identify four stable equilibrium configurations and show that: (1) excessive innovation spillovers and asymmetric interdependence between recyclers and remanufacturers may weaken incentive compatibility and induce opportunistic behavior; (2) the effects of government subsidies vary across evolutionary stages and depend on the strategic responses of other actors; and (3) interfirm transfer prices and final market prices promote stable cooperation only within specific ranges. These findings provide a theoretical basis and policy implications for improving collaborative governance in reverse supply chains for urban mineral resource recovery and supporting sustainable urban mining. Full article

This study investigated the long-term relationship between land-use change and land-cover-based ecological quality patterns in Ordos City, a typical coal resource-based city in northern China. To explicitly capture land-use transitions driven by coal exploitation, mining areas were classified as an independent land-cover type. An improved U-Net semantic segmentation model integrating multispectral information and land surface temperature was subsequently employed to generate multi-temporal land-cover maps. In the internal semantic segmentation validation, the proposed model achieved a mean Intersection over Union (mIoU) of 69.51%, a mean accuracy (mAcc) of 81.65%, and a pixel-level overall accuracy (aAcc) of 83.16%. An independent point-based accuracy assessment of the final land-cover map yielded an overall accuracy (OA) of 66.00% and a Kappa coefficient of 0.6033, indicating acceptable classification reliability in complex mining areas. Based on the classification results, three indicators, namely the land-use transition matrix, ecological environmental quality index (EQI), and ecological contribution index, were adopted to analyze spatiotemporal land-use dynamics and associated land-cover-based ecological quality patterns in Ordos City over the past 25 years. The results indicate that: (1) Marked land-use changes occurred in the land-use pattern of the study area during 2000–2025, with grassland and unused land consistently remaining the dominant land-use types. The area classified as Mining increased from 105.83 km² to 1184.17 km² in 2020, exhibiting distinct characteristics of phased expansion and subsequent adjustment. Built-up land continued to expand, whereas the water area decreased by 47.55%. (2) The land-cover-based EQI exhibited a pattern of decline, recovery, and stabilization, decreasing from 0.529 in 2000 to 0.489 in 2015 before recovering to 0.522 in 2025. This pattern was associated with changes in land-cover composition over the study period, including mining expansion and restoration-related transitions. The findings provide a scientific basis for ecological restoration planning and high-quality transformation in Ordos and other coal resource-based cities with similar arid and semi-arid environmental conditions. Full article