Search Results (9,092)

Large-scale chest X-ray (CXR) datasets often rely on report-derived or weak labels, introducing missing and incorrect annotations that can degrade downstream models and limit trust. We study training-free mislabel detection in multi-label CXRs by scoring neighborhood label consistency in a fixed embedding space. Using the NIH Chest X-ray Kaggle sample (5606 CXRs), we extract intermediate CoAtNet features and obtain 64-dimensional embeddings with a frozen CoAtNet backbone and a lightweight refinement head. On top of these embeddings, we compare kNN consistency baselines with distance weighting and label-set similarity against LPV-DW-CS, clustered prototype voting weighted by distance and cluster support. We evaluate three synthetic label-noise regimes with review budgets matched to the corruption rate: random single-label (5% and 20%), boundary-noise (20% corruption within the lowest-density 20% subset), and disjoint-label replacement (20% within that subset). LPV-DW-CS yields the highest downstream macro-AUROC after filtering top-ranked samples (up to 0.8860), while kNN variants achieve higher Recall@budget at the same review rates (up to 99.44%). An image-only expert Likert review of top-ranked real samples finds substantial label-set inconsistencies (54.1% for LPV-DW-CS-280-A; 60.5% for KNN-DW-LSS), supporting neighborhood-consistency ranking as a practical, training-free tool for targeted dataset auditing. Full article

Impacted mandibular third-molar surgery commonly causes early postoperative pain, swelling, and trismus. This randomized, controlled, three-arm parallel trial evaluated whether intra-alveolar corticosteroid delivery via an absorbable gelatin sponge improves postoperative recovery compared with a saline control. Fifty-five patients were assessed for eligibility; 37 healthy adults (18–35 years) undergoing standardized mandibular third-molar extraction were randomized to dexamethasone 8 mg (Decort^®), methylprednisolone 40 mg (Prednol^®), or control (saline), all applied intra-alveolarly using a gelatin sponge carrier. Doses were selected using standard systemic glucocorticoid equivalence tables as a pragmatic potency reference, acknowledging unknown intra-alveolar pharmacokinetics/bioavailability. The prespecified primary endpoint (used for sample size planning) was postoperative Day 1 VAS pain; key secondary endpoints were Day 1 analgesic consumption and Day 3 facial swelling. Pain (VAS), analgesic use, trismus, and facial swelling (tragus–pogonion, tragus–labial commissure, and angulus–canthus distances) were assessed on postoperative Days 1, 2, 3, and 7 by a blinded evaluator. Two participants in the methylprednisolone group did not attend postoperative visits. To address potential attrition bias, an Intention-to-Treat (ITT) sensitivity analysis using conservative control-median imputation was performed alongside the available-case analyses. A global False Discovery Rate (FDR) correction was also applied to control for multiplicity. In both analyses, the steroid groups showed lower Day 1 pain scores than the control group. Methylprednisolone was associated with lower Day 3 swelling values than control for the tragus–pogonion and angulus–canthus measurements. These findings should be interpreted as preliminary, given the small sample size, linear swelling measurements, and lack of blinding verification. Full article

Vulnerable road users in informal urban environments confront a distinct set of hazards that standard computer vision datasets are ill-equipped to represent: artisanal speed bumps constructed without regulatory compliance, deteriorated road markings, and the mototaxi—a three-wheeled motorized vehicle that constitutes the primary informal transport mode in intermediate Andean cities yet is absent from all major international repositories. This paper presents QHAWAY—from Quechua qhaway, a transitive verb meaning “to look; to observe”—an Advanced Driver Assistance System (ADAS) predicated on instance segmentation, monocular distance estimation via the pinhole camera model, and Time-to-Collision (TTC) computation, developed for the road environment of Ayacucho, Peru (2761 m a.s.l.), a city recognised by UNESCO as a Creative City of Crafts and Folk Art since 2019. A hybrid dataset comprising 25,602 images with 127,525 annotated instances across 12 classes was assembled by combining an original local collection of 4598 images (10,701 instances) captured through four complementary acquisition methods across the five urban districts of the Huamanga province with three established international datasets (BDD100K, BSTLD, RLMD; 21,004 images, 116,824 instances). A three-phase progressive training strategy with monotonically increasing resolution (640, 800, and 1024 pixels) was evaluated as an ablation study. A multi-architecture comparison spanning YOLOv8L-seg and the YOLO26 family (nano, small, large) identified YOLO26L-seg as the best-performing model, attaining mAP50 Box of 0.829 and mAP50 Mask of 0.788 at epoch 179. The integration of ByteTrack multi-object tracking with the pinhole equation $D=(H_{\mathrm{real}}\times f)/h_{\mathrm{px}}$ delineates operational risk zones aligned with the NHTSA forward collision warning standard (danger: <3 m; caution: 3–7 m; TTC threshold ≤ 2.4 s). The system sustains processing rates of 19.2–25.4 FPS on an NVIDIA RTX 5080 GPU. A systematic field survey established that 96% of the audited speed bumps fail to comply with MTC Directive No. 01-2011-MTC/14, constituting the first quantitative record of informal road infrastructure non-compliance in the Andean region. Validation was conducted under naturalistic driving conditions without staged scenarios. Grad-CAM explainability analysis, encompassing three complementary visualisation algorithms (Grad-CAM, Grad-CAM++, and EigenCAM), confirmed that model attention concentrates consistently on safety-critical objects. Full article

With the rapid development of the low-altitude economy, constructing an accurate unmanned aerial vehicle (UAV) air-to-ground channel model is crucial for ensuring communication quality. However, due to the significant fluctuations in UAV operation altitudes and the complex propagation environment, traditional empirical models struggle to achieve universal high-precision prediction within a 3D airspace. This paper proposes a Physics-Informed Feature Engineering (PIFE) method and constructs a 3D signal strength prediction model in combination with Gradient Boosting Decision Tree (XGBoost). Unlike traditional purely data-driven methods, this paper explicitly extracts physical propagation features such as three-dimensional Euclidean distance and height-to-angle ratio, and specifically designs a height–path loss interaction term to capture the nonlinear coupling relationship of signal attenuation at different operating heights. The experimental results demonstrate that the model proposed in this paper performs excellently in multi-altitude airspace scenarios ranging from 70 m to 150 m. At the typical operation height of 70 m, the model achieves a high goodness of fit ($R^2$) of 0.843. Ablation experiments further confirm that the introduction of physical interaction features successfully breaks through the performance bottleneck of pure geometric features, proving the necessity of explicitly modeling the height–distance coupling effect in complex three-dimensional airspace. The research in this paper demonstrates the effectiveness of integrating physical priors with machine learning algorithms, providing an important theoretical basis and technical support for future drone network planning and coverage optimization in complex low-altitude environments. Full article

To address the limitations of existing perception methods for nighttime encounter situation recognition of unmanned surface vessels (USVs), this study proposes an image-based method for navigation-light recognition and encounter situation recognition. In accordance with the International Regulations for Preventing Collisions at Sea (COLREGs), a parameterized 3D geometric model of vessel navigation lights and encounter scenario models is established. Based on the camera imaging principle, a dataset of navigation-light images under various encounter situations is generated through simulation experiments. By analyzing the variation patterns of navigation-light images in different encounter situations, a feature vector composed of area-domain and azimuth-domain features is constructed, and an encounter situation recognition method is developed accordingly. To mitigate the effects of water reflections and interfering light sources in real images, a navigation-light image-processing method is designed for the stable extraction of feature parameters. Simulation results show that the classification accuracy ranges from 96.6% to 98.3% at different distance conditions. In field experiments conducted with a small USV under a three-light configuration, the proposed method achieves a navigation-light recognition accuracy of 96.2% and an encounter situation recognition accuracy of 94.94%. The proposed method provides an interpretable and lightweight complementary visual solution for nighttime encounter situation recognition, complementing existing nighttime perception technologies. Full article

Marine organisms that episodically aggregate near coastal nuclear power plant water intakes pose a substantial risk to cooling water security. Predicting the spatial distribution of such high-risk species remains challenging because their occurrence is shaped not only by environmental conditions but also by complex trophic interactions. In this study, we model the habitat distribution of three high-risk nektonic species, Dotted gizzard shad (Konosirus punctatus), Japanese swimming crab (Charybdis japonica) and squid (Loligo sp.), in the cooling water intake area of a coastal nuclear power plant in eastern Liaodong Bay using generalized linear models (GLMs) and joint species distribution models (JSDMs). Based on summer surveys conducted in 2024–2025, we explicitly incorporated trophic linkages among target species, their prey, and predators within JSDMs. Model performance was evaluated using cross-validation based on AUC, RMSE, and coefficient of determination (R²). Our results indicate that water depth was the dominant environmental driver for all three species, while chlorophyll-a concentration and distance to the intake exerted species-specific effects. By incorporating interspecific trophic associations and environmental responses, JSDMs showed consistently improved predictive performance relative to GLMs, with approximately 1.5-fold higher R² values and 10–30% lower RMSE, while offering enhanced ecological interpretability. The models revealed strong positive associations between target species and both lower-trophic prey and higher-trophic predators, suggesting that top–down and bottom–up processes jointly regulate aggregation dynamics. This study demonstrates that integrating trophic interactions into species distribution modeling substantially improves predictions of high-risk marine species near coastal infrastructure and provides an ecological basis for proactive management of cooling water intake systems. Full article

Urban seismic vulnerability poses severe challenges for disaster preparedness in Lima, Peru, where a long-standing seismic gap increases risk to a metropolitan population of approximately ten million residents. This study presents an adaptive multi-objective optimization framework that dynamically adjusts shelter allocation priorities across earthquake intensity scenarios. The methodology integrates spatial data on population distribution, infrastructure vulnerability, and seismic hazard zones to optimize three competing objectives through the NSGA-III algorithm: inter-shelter spacing, population coverage, and safety. Model parameters were calibrated using controlled synthetic scenarios and subsequently validated with real-world data from Lima. Under the high-impact scenario used by the Municipality of Lima, the official set of 356 designated shelters was compared with an optimized configuration selected from 5855 potential sites under identical hazard and demand conditions. The optimized solution increased population coverage by 66.82% and reduced the average distance to critical resources by 24.55%, while reducing service gaps in peripheral districts. Scenario-adaptive optimization improved the robustness of shelter planning by producing configurations that were better aligned with operational priorities as hazard severity escalated, supporting more equitable access in a resource-constrained urban context. This research contributes an evidence-based decision-support tool for emergency management, translating multi-objective trade-offs into actionable shelter layouts for Lima. Full article

Ants play a central role in seed dispersal and predation, shaping plant recruitment, yet their foraging behavior is increasingly influenced by anthropogenic food subsidies. In human-modified landscapes, processed food waste may disrupt ant–seed interactions by diverting foragers or altering activity patterns, but the extent and mechanisms of these effects across habitats remain unclear. We conducted three field experiments in Panama to test how common food residues affect seed removal by ants in urban and forest environments. Using oat seeds as standardized diaspores, we (1) tested whether potato chips surrounding seed depots reduced removal, (2) evaluated the effects of adjacent chips or cookies on removal rates, ant activity, and species composition, and (3) manipulated the distance between chips and seeds (0, 30, 60 cm) to distinguish behavioral distraction from physical obstruction. Across experiments, seeds near food residues were removed significantly more slowly than controls, approximately half as fast in both habitats, despite differences in ant assemblages. Ant activity near seeds declined in the presence of food, particularly in the urban site. Suppression of seed removal occurred at close range but disappeared at 60 cm. These findings indicate that food waste disrupts ant-mediated seed removal through fine-scale behavioral shifts across contrasting habitats. Full article

Deploying conditional Generative Adversarial Networks (cGANs) for industrial texture synthesis faces two barriers: the prohibitive cost of manual data annotation and the uncertain alignment between automated evaluation metrics and human perception. This study addresses both challenges for marble texture synthesis using 289 high-resolution industrial scans. We adapt an unsupervised segmentation pipeline combining Simple Linear Iterative Clustering (SLIC) superpixels, Gaussian Mixture Models (GMMs), and graph cut optimization to extract vein structures without manual annotation. Four cGAN architectures—baseline cGAN, Pix2Pix, BicycleGAN, and GauGAN—are benchmarked using a dual-evaluation protocol contrasting ten automated metrics with structured human-centered assessment. The results reveal a significant metric–perception discrepancy. Pix2Pix achieved the best Fréchet Inception Distance (FID = 85.3) yet received the lowest human ratings due to periodic texture artifacts. GauGAN produced textures statistically indistinguishable from real marble, achieving a Visual Turing Pass Rate (VTPR) of 0.533 and a Mean Opinion Score on Marble Authenticity (MOS-MA) of 2.89, despite an inferior FID (87.3). These findings make three contributions: an annotation-free segmentation pipeline, empirical evidence that automated metrics alone are insufficient for architecture selection, and a dual-evaluation framework that establishes human-in-the-loop assessment as essential for quality-critical industrial deployment. Full article

Several well-known models in present-day computer vision take the form of Markov random fields. Any model of this kind amounts to a network of soft constraints, which are called potentials. These are the subject of this study. First, three kinds of information that are involved in any computer vision inference task are identified, namely, evidence, target, and principled information, and the concept of a variable as applied in this context is discussed. The general meaning of a potential is then described, which is a local soft constraint that aims to promote a corresponding desired condition. Following this, the formal structure of a potential is highlighted, which includes a set of parameters and an analytic frame, with this being a hierarchy of operations by which the value of the potential can be computed. The possible presence of a core in the analytic frame is considered, and two salient kinds of cores are distinguished and illustrated using examples from the literature: one involving a distance function and the other given by a probabilistic conditional. In summary, this contribution highlights substantial aspects of the semantics and syntax of potentials in Markov field models of computer vision, and constructs a framework within which these aspects may be consistently arranged and explained. Full article

Singapore’s AI sustainability discourse has intensified around data centre energy demand and ESG finance, yet how public attention and affect co-evolve in response to policy events remains poorly understood. This study analyses 3305 Singapore-related Reddit documents (709 original posts, 2596 comments) from 2022 to 2025 using Structural Topic Modelling (K = 15) and transformer-based emotion classification. Topic prevalence is modelled as a function of year; emotion classification is restricted to original posts as discourse-initiating units. Three focal events structure the analysis: ChatGPT-3.5’s launch (November 2022), Singapore’s National AI Strategy 2.0 (December 2023), and intensified ESG attention (March 2024). Results reveal pronounced event-linked topical restructuring, most notably a 345% surge in Energy Markets discourse following ChatGPT-3.5, alongside compositional shifts confirmed by ILR-transformed Welch t-tests and Euclidean distance analysis. However, the affective register of original posts remains stable and predominantly neutral throughout, with intermittent fear (mean classifier confidence 71.3%) and no evidence of sustained directional change in emotion intensities. Latent dimensional analysis identifies three affective structures, namely Pragmatic Neutrality, Evaluative Engagement, and Affective Valence, with AI energy topics clustering in the pragmatic-curiosity region. These findings suggest that Singapore’s technocratic governance culture and affective saturation from chronic environmental exposure produce a discourse in which topical reconfiguration unfolds without corresponding emotional mobilisation. Full article

Fishways play a critical role in restoring river connectivity and conserving fishery resources, yet their efficiency is often limited by mismatches between hydraulic conditions and species-specific behavioral traits. To quantify the upstream migration behavior of fish under the combined influence of flow heterogeneity and schooling effects, this study examined the endangered species L. elongata in the Yangtze River Basin. Volitional swimming behavior was tested in an open-channel flume under three spatially heterogeneous flow regimes (I: Low–Moderate–High; II: High–Moderate–Low; III: Moderate–High–Low). A video monitoring system recorded the upstream movement of solitary fish and three-individual schools. Swimming trajectories, upstream migration time, preferred flow velocities, and schooling metrics—including nearest neighbor distance (NND) and mean pairwise distance (MPD)—were analyzed. Linear mixed-effects models were employed to account for repeated measures and individual variability. Results showed that schooling behavior significantly enhanced upstream migration efficiency: schooling fish arrived at the target area on average 8.93 s earlier than solitary individuals (p < 0.01), while flow condition alone had no detectable effect on arrival time. L. elongata consistently preferred low-velocity zones (0.20–0.50 m/s) and avoided high-velocity regions (0.75–1.25 m/s), with meandering upstream trajectories predominating. NND showed no significant differences across flow conditions (p > 0.05), indicating stable schooling cohesion. However, MPD increased significantly under Flow III compared to Flows I and II (p < 0.01), suggesting that higher flow heterogeneity leads to more dispersed group spacing while overall cohesion is maintained. Distinct movement strategies were observed: solitary fish predominantly utilized boundary regions as hydraulic refuges (wall-following: 63.8–80.5%), whereas schools exhibited greater spatial exploration and reduced wall-following. These findings demonstrate that schooling enhances migration efficiency while preserving a cohesive group structure and that flow heterogeneity influences within-group spatial organization. To optimize fishway performance for L. elongata, we recommend maintaining flow velocities within 0.20–0.50 m/s. This study provides scientific guidance for hydraulic regulation in fishway design and habitat restoration, emphasizing the combined effects of flow heterogeneity and schooling behavior on migration performance. Full article

The genus Acanthosaura is characterized by a high level of cryptic species diversity and is subdivided into several species complexes. The phylogenetic relationships within the A. coronata complex remain unresolved due to the presence of cryptic lineages and limited molecular data for several species. In this study, these relationships are clarified using a molecular genetic analysis that integrates newly collected field samples and historical museum specimens with previously uncertain identification. Three mitochondrial genes (cyt b, COI, and ND2) from samples, including fresh collections of A. murphyi from Phu Yen Province (Vietnam) and museum specimens from Vietnam and Myanmar, were analyzed. In addition, morphological characters of the examined specimens with diagnostic traits of known species were compared. Phylogenetic analyses confirmed the distinct species status of A. murphyi and enabled the taxonomic reassignment of previously undetermined museum specimens to this species. Specimens from Vietnam and Myanmar formed a single, well-supported clade, suggesting a broader distribution for A. murphyi than previously recognized. It is demonstrated for the first time that A. murphyi belongs to the A. coronata complex, together with A. coronata and A. cuongi, a result consistently supported by both genetic distances and phylogenetic tree topology. Full article

This study examines how local social policies addressing young people’s well-being and working-life capacities within the framework of sustainable development are understood, and how they might be further developed in a Swedish municipal context. The study draws on three qualitative datasets: professionals from municipal social services, representatives of municipal units and civil society organisations, and young people aged 15–19. Data were analysed using abductive thematic analysis informed by Doyal and Gough’s theory of Human Need and Helne and Hirvilammi’s Having–Doing–Loving–Being model of relational well-being. Findings indicate that professional participants recognise links between social, economic, and ecological dimensions of sustainability, yet practice is largely oriented towards individual and social concerns, with limited engagement with the natural environment. Youth participants indicated detachment from both nature and societal processes, framed responsibility as habitual, and exhibited intergenerational detachment alongside temporal and geographical distance from sustainability issues. The findings also indicate siloed municipal sustainability policies. The study concludes that current policies may insufficiently integrate the ecological and relational dimensions of human needs and that there is a need to develop ecosocial policies and practices that promote more sustainable well-being and working-life capacities, especially for young people. Full article

This study investigated interlimb asymmetries in lower limb performance using both vertical and horizontal jump tests in elite young basketball players. Specifically, it aimed to determine whether (1) unilateral jump performance and (2) the magnitude of interlimb asymmetry differed across maturity groups, whether (3) limb dominance influences performance, and whether (4) asymmetry direction is consistent across tests. One hundred elite male basketball players (U13 to U19) were categorised into three maturational stages: Pre-PHV (n = 19), Circa-PHV (n = 29), and Post-PHV (n = 52). Each athlete performed the following unilateral tests with both the dominant and non-dominant leg: single-leg hop, triple hop for distance, 6 m timed hop, single-leg countermovement jump (SL-CMJ), and single-leg drop jump (SL-DJ) from a 30 cm box. The Bilateral Strength Asymmetry (BSA) index was computed for each test. All tests showed significant differences between Pre-PHV and Circa-PHV groups (p < 0.001), whereas only the 6 m timed hop differed between Circa-PHV and Post-PHV (p < 0.01). BSA did not differ significantly across maturation stages in any test, except for the single-leg hop. Agreement in asymmetry direction between test pairs was slight to fair (kappa ≤ 0.29). BSA values remained largely stable across maturational stages, suggesting that interlimb asymmetries are established before PHV, likely during childhood. Limb dominance did not affect jump performance, and asymmetry direction varied between tests, confirming they are not interchangeable. Full article