Search Results (36,726)

Continuous structural health monitoring is essential for ensuring the safe operation of critical engineering systems. Ultrasonic guided waves are widely used for damage detection and localization due to their ability to cover large areas with high sensitivity to structural changes. This work evaluates the robustness of a previously proposed guided-wave localization approach by applying it to the complex geometry of carbon fiber composite plates with integrated omega stringers. The measurement data used in this study were provided within the framework of the Open Guided Waves project. We employ an interpretable machine-learning framework based on the normalized root mean square deviation to extract damage-sensitive features. Damage localization is further improved by modeling the spatial damage probability using a normal distribution, which enhances spatial coverage of the structure. The influence of 13 damages with progressively increasing size on classification and localization performance is systematically analyzed. The proposed method achieves an average classification accuracy of 95% and a mean localization error of 5 mm, demonstrating its suitability for damage characterization in complex composite structures. Full article

Citrus is an important fruit crop worldwide and Colletotrichum species are important pathogens of this crop. Colletotrichum species infect a wide range of citrus tissue such as leaves, twigs, flower petals, immature and mature fruit, causing substantial losses in yield, fruit quality, and marketability. This review is a critical assessment of the major Colletotrichum species associated with citrus diseases, their global diversity, distribution, and biosecurity implications. This review also identifies areas in need of further research. Thirty-nine Colletotrichum species have been reported in association with citrus globally. Most Colletotrichum species are plant pathogens, while several are saprobes or exhibit endophytic or latent lifestyles. They also vary in host range, aggressiveness, and environmental adaptation. Several species can infect citrus hosts or tissues beyond those from which they were originally isolated, while some also infect plants from other genera. The nature of infection by Colletotrichum species highlights the need to include non-wound inoculation in bioassays designed to assess the ability of Colletotrichum isolates to penetrate the cuticle and epidermis and cause infection. Accurate identification, pathogenicity testing, and rapid molecular detection are therefore important for disease management, quarantine inspection, and plant biosecurity risk assessment. Full article

Accurately evaluating the effective stress coefficient ($\mathsf{\alpha }$) of rock fractures under hydro-mechanical (HM) coupling is paramount for assessing the stability of fractured rock in deep underground engineering. This study conducted triaxial HM tests under varying normal stresses and multi-stage fluid pressures on marble fractures from a deep-buried water transport tunnel. Coupled with numerical simulations, the dynamic evolution and mesoscopic physical mechanisms of $\mathsf{\alpha }$ under complex stress paths were elucidated. Results demonstrate that $\mathsf{\alpha }$ is highly stress-dependent and generally less than 0.4 for smooth marble fractures. Under low normal stress, $\mathsf{\alpha }$ increases approximately linearly with elevated fluid pressure. Conversely, under high normal stress, $\mathsf{\alpha }$ exhibits low sensitivity to fluid pressure variations until surpassing a critical threshold (10–12 MPa), after which it manifests a pronounced exponential increase. Mesoscopic analysis reveals that severe contact occlusion induced by high normal stress restricts fluid permeation, leading to a heterogeneous fluid pressure distribution. This heterogeneity restricts the applicability of the traditional effective stress principle under extreme conditions. Once fluid pressure crosses the threshold, a “wedging effect” triggered by high-pressure fluid forces rapid failure of contact spots, causing a precipitous reduction in the contact area ratio ($S_c$). This contact state evolution constitutes the physical essence underlying the exponential surge of $\mathsf{\alpha }$. Based on experimental and inverted data, an improved empirical model for fracture effective stress was established, incorporating the coupled influences of normal stress and fluid pressure. This model possesses explicit physical significance, providing a scientific theoretical basis for evaluating surrounding rock stability in deep-buried tunnels. Full article

Population ageing challenges the social sustainability of high-density cities, where equitable eldercare access underpins SDG 3, SDG 10 and SDG 11. In China, rapid expansion of community-based eldercare facilities (CEFs) under the “90-7-3” framework has produced a tripartite system of government, operating enterprises and older adult users whose spatial priorities conflict, threatening both distributive equity and long-term operational viability. Existing single-dimensional evaluations inadequately capture this complexity. This study develops an integrated four-dimensional spatial evaluation framework—supply–demand accessibility, spatial equity, functional diversity and market competition—applying the Gaussian two-step floating catchment area method, isochrone-based service-area analysis and a preference-weighted Shannon index to 697 CEFs across 130 sub-districts in Beijing’s central urban area. Results reveal a pronounced core–periphery divide. For service-type CEFs, 90.17% of communities (87.95% of older adults) lie within a 15-min walking catchment, yet service-area overlap reaches 199.32%, indicating redundant resource deployment and intense localised competition in core districts. For residential-type CEFs, only 53.91% of communities are within walkable reach and total coverage drops to 15.84%, exposing care blind spots and spatial inequity in outer districts. Functional diversity, by contrast, is evenly distributed and micro-environmentally shaped. The framework offers replicable diagnostics for sustainable ageing-in-place provision in rapidly ageing high-density cities. Full article

Urban–rural transition zones (URTZs) represent critical spatial units where urban expansion interacts with ecosystems. In arid regions, however, the response of ecological environmental quality (EEQ) to rapid urban expansion and spatial restructuring remains insufficiently understood. Taking Xinjiang as a representative arid-region case, this study develops an analytical framework integrating dynamic URTZs identification, EEQ assessment, and the analysis of influencing factors and nonlinear responses to systematically investigate URTZs expansion and EEQ changes across 13 typical urban agglomerations from 2002 to 2022. URTZs were identified using K-means clustering by integrating population density, nighttime light intensity, and impervious surface information. An improved remote sensing ecological index (ARSEI) was then developed by incorporating the abundance index (AI) into the traditional RSEI framework. Finally, XGBoost and SHAP were employed to identify the key determinants of EEQ and reveal their nonlinear responses and interactions. The results showed that: (1) URTZs expanded rapidly and continuously from 2002 to 2022, with their total area increasing by more than threefold and exhibiting a spatial restructuring pattern characterized by expansion from central cities toward multiple nodes. (2) Despite the rapid expansion of URTZs, overall EEQ remained at a relatively high level; however, the grade structure exhibited a trend of “expansion at both ends and contraction in the middle,” intensifying the spatial differentiation of EEQ. (3) XGBoost and SHAP analyses identified precipitation (PRE), population density (POP), digital elevation model (DEM), and slope as major factors explaining the spatial variation in EEQ. Interaction analysis further revealed strong interactions between PRE × DEM and PRE × POP. High EEQ values were primarily distributed in areas characterized by favorable precipitation conditions, moderate elevations, and gentle terrain, indicating that the synergistic effects of hydrothermal conditions and topographic constraints play a significant role in shaping EEQ in URTZs. These findings demonstrate that rapid URTZs expansion in arid regions does not necessarily lead to an overall decline in EEQ but may intensify its spatial differentiation. Therefore, ecological governance of URTZs should shift from a singular focus on controlling urban expansion toward differentiated spatial management that jointly considers hydrothermal conditions, topographic constraints, population concentration, and ecological carrying capacity, thereby promoting coordinated urbanization and ecological conservation. Full article

Semi-outdoor spaces on university campuses support circulation, temporary stays, and a range of everyday activities. This study presents an exploratory case study of four semi-outdoor study sites at Tokai University Shonan Campus in Japan, examining differences in activity composition and self-reported intended dwell time in relation to their spatial characteristics. The sites were documented using a common framework covering spatial dimensions and form, overhead and vertical configuration, lateral boundary conditions, access conditions, furniture and seating configuration, and surrounding functional conditions. Four survey rounds were conducted from November 2024 to July 2025 using the same survey procedure at all sites, yielding 189 valid responses. Activity composition differed among the four sites (Fisher–Freeman–Halton exact test, Monte Carlo p = 0.039; Cramér’s V = 0.184), as did the distribution of self-reported intended dwell time (p < 0.001; V = 0.234). Activity type was also associated with intended dwell time (p = 0.005; V = 0.274). Eating was the most common activity overall, while the proportions of studying, resting, conversation, and waiting varied among sites. However, these differences did not show a consistent relationship with any single spatial characteristic, including area, W/D ratio, spatial height, boundary configuration, or seating capacity. The findings suggest that campus semi-outdoor spaces should be interpreted through multiple spatial characteristics and surrounding functional conditions rather than a single spatial parameter. As an exploratory single-campus case study, this study provides a basis for broader comparative research. Full article

Shale reservoirs are characterized by high tightness and strong heterogeneity; determining the lower limit of movable pore throats is a core scientific issue for reservoir evaluation and development optimization. Targeting shale in the Jiyang Depression, Bohai Bay Basin, this study employed mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR) combined with centrifugal experiments, and simulated elastic depressurization production tests to investigate the pore throat structure and fluid mobility of three types of dominant lithofacies. The dominant lithofacies in the study area are laminated cryptocrystalline argillaceous limestone, bedded cryptocrystalline argillaceous limestone, and laminated cryptocrystalline calcareous mudstone, with significant differences in mineral composition among the three lithofacies. Laminated cryptocrystalline calcareous mudstone exhibits the smallest average pore throat radius, yet possesses optimal pore throat connectivity and fluid mobilization capability, with uniform pore throat distribution concentrated in the small pore-size range. The two argillaceous limestone lithofacies develop multi-modal pore systems. Elastic depletion production simulation indicates that the lower limit of movable pore throats for the bedded cryptocrystalline argillaceous limestone lithofacies is 34.6 nm under the tested depletion conditions, demonstrating that stress sensitivity can elevate the actual lower limit of movable pore throats by approximately one order of magnitude; this threshold is lithofacies- and condition-specific and requires validation before generalization. The lower limits of movable pore throats for different lithofacies follow the order: bedded cryptocrystalline argillaceous limestone > laminated cryptocrystalline argillaceous limestone > laminated cryptocrystalline calcareous mudstone. Full article

As aerodynamic configurations become increasingly integrated with propulsion systems, internal–external flow coupling has become a key issue in airframe–engine integration. For embedded-inlet configurations, however, the airframe and inlet/exhaust system have different geometric shaping requirements, making their design variables difficult to represent within a unified gradient-based optimization framework. This study develops a continuous parameterization method for embedded inlets that simultaneously controls cross-sectional profiles, area distribution, and centerline under large cross-sectional rotation angles. The method combines B-spline curves, shape blending functions, quaternion-based transformations, and free-form deformation (FFD) to establish a hybrid parameterization framework for coupled internal–external flow optimization. Analytical geometric sensitivities of the inlet surface mesh with respect to profile, area-distribution, and centerline variables are derived through the complete parameterization chain and coupled with discrete-adjoint flow sensitivities, enabling gradient evaluation for both external aerodynamic-shape and internal inlet-geometry variables. The framework is applied to full-configuration multipoint optimization of an aircraft with an embedded inlet. Aerodynamic drag is reduced by 2.82% and 2.36% at the two design points, while inlet drag decreases by 4.44 and 4.63 counts (1 count = 0.0001). Under distortion-coefficient and mass-flow-rate constraints, the inlet-exit total pressure recovery coefficient increases by 0.54% and 0.41%, respectively. These results demonstrate the effectiveness of the proposed method for integrated internal–external flow optimization and its potential for airframe–engine integrated design. Full article

Mechanical activation (MA), an intensive milling process capable of inducing physicochemical changes in solid materials, was applied to a vanadiferous titanomagnetite (VTM) originating from the Lac Doré Complex, Chibougamau, QC, Canada. The objective of this study was to investigate the structural and microstructural evolution of VTM under intensive milling conditions and the associated changes in particle characteristics, with particular emphasis on X-ray diffraction (XRD) peak intensity and broadening, microstrain, phase composition, particle size, and specific surface area. Mechanical activation was investigated by varying three milling parameters: milling time (5 g powder, 10 Hz, variable milling time), ball-to-powder ratio (variable powder mass, 10 Hz, 15 min), and milling frequency (5 g powder, variable frequency, 15 min). The XRD results reveal significant changes in the diffraction pattern of chamosite, including variations in peak intensity and pronounced peak broadening under the more intensive milling conditions of 5 g powder, 15 Hz, and 15 min. In contrast, the diffraction peaks associated with ilmenite and magnetite became more pronounced, while the calculated microstrain increased. Scanning electron microscopy (SEM) showed substantial changes in particle morphology following mechanical activation. Brunauer–Emmett–Teller (BET) analysis further demonstrated an increase in specific surface area with increasing milling frequency, while laser diffraction measurements revealed systematic variations in particle-size distribution among the three experimental series. Overall, the results demonstrate that mechanical activation produces measurable modifications to the mineralogical, structural, microstructural, and particle characteristics of Lac Doré VTM. These findings provide a basis for further investigation of the relationship between milling-induced structural changes, VTM reactivity, and subsequent metal-extraction performance. Full article

Lithium-ion battery energy storage stations are being rapidly deployed for peak regulation, renewable energy integration, and emergency power supply in power systems. Their fire risk is governed by interacting factors, including cell thermal runaway, equipment failure, operating environment, personnel behavior, management systems, and information systems, and is characterized by coupling, dynamic evolution, and confined-space fire spread. Existing static risk assessment methods cannot fully represent feedback among multiple risk factors or connect risk assessment results with the physical-field evolution of fires in energy storage compartments. This study develops an integrated grey relational analysis, system dynamics, and FDS framework. Personnel, equipment, environmental, management, and information risk factors are first established, and their weights are calculated using grey relational analysis. A system dynamics model is then used to analyze the temporal evolution of overall risk and subsystem risk responses. Finally, FDS is applied to simulate fire spread in a 30 ft containerized lithium-ion battery energy storage compartment under no-suppression and water-mist suppression conditions. The results show that the central fire-source region and battery module layer are key areas of gas-phase high-temperature accumulation and potential fire spread. In the no-suppression scenario, the high-temperature region remains localized near the fire source at 3.0 s, expands along the module layer from 30.0 to 50.0 s, and approaches a relatively stable distribution after 70.0 s. Under the investigated simulation conditions, water mist reduces near-source heating, weakens smoke-layer development, and slows spatial fire spread through evaporative cooling, reduced thermal radiation feedback, and disturbance of the hot smoke layer. These findings provide a methodological reference for fire risk assessment and fire suppression design in containerized battery energy storage stations. Full article

The global expansion of interconnected edge network components requires immediate strategies for securing low-power computing nodes. Cryptographic algorithms executing over binary extension fields yield considerable computational benefits because their carry-free arithmetic significantly optimizes dynamic power consumption. However, general-purpose silicon architectures lack the dedicated hardware structures to run these finite-field operations efficiently, resulting in severe processing throughput bottlenecks. This study addresses this limitation by introducing a parallelized modular multiplier framework designed to integrate smoothly with the multicore execution environments of modern embedded platforms. Our approach deploys a progressive multiplier reduction (PMR) protocol that segments dense mathematical workloads into distributed structural thread groups. This architectural alignment allows multiplication matrices and spatial field reductions to take place concurrently, balancing localized workloads while decreasing intermediate data buffering demands. We present two distinct topological styles based on column division and row division techniques, deriving comprehensive analytical formulations to capture precise silicon area footprints, critical path delays, and total operational cycle counts. The resulting hardware metrics demonstrate that the parallel PMR design achieves a highly competitive area–delay product alongside optimized dynamic consumption characteristics. This structural paradigm delivers a scalable and robust security alternative for general edge hardware, ensuring system runtime stability while meeting tight environmental power constraints, protecting vital industrial assets, and sustaining emerging macroeconomic infrastructure. Full article

Antimicrobial resistance (AMR) represents one of the foremost global public health threats, undermining the efficacy of antibiotic therapies across all clinical disciplines, including dentistry. The oral cavity, housing one of the most diverse microbial ecosystems in the human body, contains a largely underappreciated reservoir of antibiotic resistance genes (ARGs), collectively defined as the oral resistome. This review synthesises current evidence on the oral resistome across five thematic areas. First, we contextualise the global burden of AMR, highlighting its scale and implications for oral healthcare. Second, we define the oral resistome and characterise its composition, distribution across oral microhabitats, and the principal determinants that govern its structure and dynamics. Third, we critically appraise metagenomic approaches, from early culture-based and PCR-targeted methods to shotgun metagenomics and functional screening, that have expanded the resolution of resistome characterisation. Fourth, we examine multi-omics integration, including genomics, transcriptomics, and metabolomics, and its capacity to reveal the ecological and molecular drivers of resistance within the oral ecosystem. Finally, we explore how resistome profiling can inform precision oral health, enabling individualised antimicrobial stewardship, microbiome-based risk stratification, and patient-tailored preventive and therapeutic strategies in the era of personalised dentistry. Full article

Glacier retreat is creating extensive areas of newly exposed terrain where primary succession drives the transition from abiotic substrates to developing ecosystems. Monitoring these early successional stages remains challenging because pioneer communities, including biological soil crusts (BSCs), often exhibit weak and heterogeneous spectral signatures. This study investigates the potential of Sentinel-2 multispectral imagery for detecting and mapping primary succession within the Forni Glacier forefield (Italian Alps), using terrain exposed by glacier retreat between 1954 and 2015 as a natural chronosequence. A hierarchical classification framework integrating vegetation-sensitive (NDVI-Narrow), moisture-sensitive (NDMI-Narrow), and water-sensitive (NDWI) indices was developed to identify four major land-cover classes: Water/Snow/Ice, Intermediate Pioneer Stage, Initial Moisture-Sensitive Stage, and Barren Rock/Debris. The classification revealed that Barren Rock/Debris was the dominant class (73.4%), followed by Initial Moisture-Sensitive Stage (13.9%), Water/Snow/Ice (10.7%), and Intermediate Pioneer Stage (2.0%). Independent validation yielded Overall Accuracy values ranging from 72.5% to 80%, supporting the robustness of the proposed approach despite the intrinsic heterogeneity of proglacial environments. Analysis of seven exposure-age intervals revealed significant age-related changes in land-cover distribution. Spearman’s rank correlation showed a strong positive association between the Initial Moisture-Sensitive Stage and terrain exposure age (rs = 0.93), whereas Water/Snow/Ice exhibited a strong negative correlation (rs = −0.78), supporting the existence of a directional successional trajectory following glacier retreat. The results also suggest the presence of a possible ecological transition occurring approximately 18–25 years after deglaciation, potentially associated with increasing ecosystem stabilization. The proposed framework provides a scalable and transferable approach for monitoring ecosystem development in glacier forefields and demonstrates that moisture-sensitive spectral information can complement vegetation-based indicators by identifying distinct moisture-sensitive transitional surfaces within recently deglaciated terrain. Full article

Background/Objectives: Molecular docking and molecular dynamics are accurate but computationally expensive, so the compounds entering them must be chosen well. The present study proposes CADT, a confidence-gated affinity–ADME-T docking-triage cascade that decides which compounds are worth docking. Methods: The gate combines an ensemble estimate of drug–target affinity with its epistemic uncertainty and an applicability-domain check. Predicted absorption, distribution, metabolism, excretion, and toxicity (ADME-T) developability is added as a soft flag. All components were trained on openly licensed Therapeutics Data Commons data. Ranking was assessed on the DAVIS and KIBA kinase panels and on BindingDB $K_d$, under three split protocols over five seeds. The routing decision was then examined against molecular docking, in which 407 compound–target pairs were docked into six withheld kinases. Results: A Morgan-fingerprint gradient-boosting model reached a concordance index of $0.866\pm 0.006$, with $0.813$ for unseen targets and $0.720$ for unseen drugs. Across eight ADME-T endpoints, the area under the ROC curve ranged from $0.65$ to $0.91$. On the cold-target split the cascade reduced the compounds sent to docking by $86\%$ while retaining $61\%$ of the true strong binders. Docking measured that reduction at $85\%$, and at an equal budget, the gate enriched true binders more than the docking score itself. Conclusions: A transparent pre-screen can prioritise compounds ahead of structure-based calculation at a fraction of its cost. However, the uncertainty and applicability-domain terms act as an abstention mechanism rather than an accuracy gain, and that abstention is not free. 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