Search Results (1,763)

The Relative Age Effect (RAE) describes systematic differences in athlete representation according to birth date, but it remains unclear whether the associated birth-quarter asymmetries vary across geographical contexts or reflect a broadly shared international pattern. This study examined birth-quarter distributions associated with the RAE in senior international football using a cross-sectional sample of 1248 players from the 48 national teams participating in the 2026 Fédération Internationale de Football Association (FIFA) World Cup. Birth-quarter distributions were assessed using χ² goodness-of-fit and independence tests, and a cumulative link mixed model evaluated the effects of age, height, playing position, and continental confederation, with national team included as a random effect. Marginal probabilities by age, spatial mapping of first-half-year births, and exploratory unsupervised cluster analysis were also performed. Birth-quarter distribution differed significantly from an equal reference distribution, with greater representation of players born in the first birth quarter (Q1: January–March) and second birth quarter (Q2: April–June) and lower representation in the fourth birth quarter (Q4: October–December). Playing position and confederation were not significantly associated with birth quarter, whereas player age was the only covariate that remained statistically significant in the mixed-effects model. Older age groups showed a lower representation of players born in Q4. Low between-team variance and weak cluster separation indicated limited differentiation in birth-quarter distributions among the national rosters analysed, although descriptive variation in first-half-year (H1: Q1 + Q2) representation was evident. These findings are consistent with an asymmetric birth-quarter distribution at the senior international level; however, because talent identification and development systems were not directly evaluated, these observations cannot establish specific organizational mechanisms or a uniform structural bias. Full article

Climate change can alter the potential distribution patterns of species, and the responses of medicinal plants to environmental change are directly relevant to resource conservation and the planning of suitable cultivation regions. Using the MaxEnt model, we combined occurrence records of four Alisma species (Alisma canaliculatum, A. gramineum, A. orientale, and A. plantago-aquatica) with climatic, topographic, edaphic, and human-activity variables to predict their potential suitable habitats under current conditions and two future periods (2041–2060 and 2081–2100) under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Two hypotheses were tested: (1) species with narrower thermal niches exhibit greater sensitivity to climate change; and (2) closely related species show significant divergence in dominant environmental factors and spatial responses. All models demonstrated good predictive performance (AUC > 0.9). Dominant environmental factors differed markedly among species: A. canaliculatum and A. orientale were primarily constrained by temperature-related variables, whereas A. gramineum and A. plantago-aquatica were more strongly associated with human activity intensity and precipitation-related variables. Consistent with the hypotheses, the potential suitable habitat of A. orientale was projected to change most strongly, while that of A. gramineum remained the most stable. Under the high-emission scenario, the potential suitable habitat of A. canaliculatum was projected to shift northward, accompanied by an increase in total suitable area. A. orientale and A. plantago-aquatica exhibited internal habitat reorganization, characterized by contraction of low-suitability areas and expansion of high-suitability areas. These findings clarify the niche differentiation patterns of closely related species and identify regions where habitat suitability may be retained, lost, or gained, thereby providing a scientific basis for the adaptive management and conservation planning of these medicinal plants under future climate change. Full article

This study proposes a novel multi-granularity broad fuzzy Apriori classifier (MGB-FAC) that addresses the high computational complexity and low generalization capability of FAC while sharing FAC’s high linguistic interpretability and strong uncertainty-handling ability. The basic idea of MGB-FAC is as follows: First, MGB-FAC creates its FAC sub-classifiers using improved feature subsets and randomly discards some rules for each sub-classifier. Second, MGB-FAC splits the rule sets of each sub-classifier into several new sub-classifiers with different rule granularity according to the length of the rules. Finally, MGB-FAC aggregates the outputs of all sub-classifiers using confidence-weighted learning to obtain the final output. MGB-FAC has three clear advantages: (1) It achieves a highly reduced computational burden while preserving the acceptable learning ability of each FAC sub-classifier. (2) It constructs many multi-granularity FAC sub-classifiers with greater diversity while requiring only a small additional computational cost without increasing the number of fuzzy rules. (3) It realizes a good broad ensemble by weighting the contribution of each FAC sub-classifier based on its confidence value and performance on input data, in terms of accuracy, precision, recall, and F1 score. The effectiveness of the proposed MGB-FAC is verified by extensive experiments using ten benchmarking datasets compared with seven comparative methods. Full article

This paper addresses low-altitude navigation of multiple UAVs through a shared two-dimensional environment with narrow passages, blocked cells, and predicted moving obstacles while preserving an assigned task order. The planner receives ordered task bundles from an allocator and checks static obstacles, moving-obstacle timing, sampled minimum inter-UAV separation, deadlines, risk budgets, and an energy proxy. It generates risk-weighted candidate path segments, repairs timing conflicts with waits and local detours, verifies service and terminal occupancy, and returns a certificate that records whether a segment is executable, its total travel cost, risk exposure, and energy proxy, or the reason for failure. We compare no feedback, context no-good, typed-failure, quantitative, and combined feedback under medium-load and high-stress test suites. Quantitative feedback lowers risk per completed task in both suites after correction for multiple comparisons. Failure-type feedback adds no detectable benefit, and completion-rate differences do not remain significant after the same correction. Fixed-bundle simulations show that the proposed planner can preserve scheduled executability while reducing threat exposure relative to a spatiotemporal-priority baseline. Single-UAV flights demonstrate waypoint execution, reference tracking, and avoidance of designated regions. Full article

The giant honeybee, Apis dorsata, is an important pollinator native to tropical and subtropical Asia. Understanding its potential response to climate change is important for pollinator conservation, ecological risk assessment, and biosecurity planning. This study used an optimized MaxEnt ecological niche modeling framework to predict the current and future global habitat suitability of A. dorsata. The model was developed using 1060 occurrence records and seven non-collinear bioclimatic variables and projected under three global climate models (IPSL-CM6A-LR, BCC-CSM2-MR, and MPI-ESM1-2-HR) and three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585) for 2041–2060, centered on 2050. The optimized model used linear, quadratic, and hinge features (LQH) with a regularization multiplier of 0.5 and demonstrated good predictive performance under 5-fold spatial cross-validation (mean AUC = 0.905 ± 0.007; TSS = 0.746 ± 0.010). The results indicate that the potential distribution of A. dorsata is primarily associated with the combined effects of seasonal temperature and moisture availability. Current projections identified high climatic suitability across South and Southeast Asia, while also revealing potentially suitable environments in parts of Africa, the Americas, and northern Australia. Future projections suggest that suitable climatic conditions will largely persist through 2050, with habitat gains generally exceeding losses and increasing under higher climate-forcing scenarios. Continued monitoring and proactive biosecurity are essential to address habitat loss within the native range and prevent establishment in newly suitable regions. This study highlights the potential redistribution of A. dorsata under future climate change. Full article

When many binary items are analyzed, most cells in the complete response table are empty. Full-table statistics may then be unreliable, and an omnibus result does not locate the misfit. This paper develops a local goodness-of-fit testing method for binary item response models by extending the weighted sequential sums-of-squares construction to pairwise concordance margins. The construction gives ordered one-degree-of-freedom components for individual item pairs. They are compared with Cholesky components and four local diagnostics under zero and wide symmetric intercepts. Omnibus statistics are examined separately under symmetric slopes. The sequential components have an empirical Type I error close to the nominal levels. With zero intercepts, all methods show substantial power for the target pairs, although pair order moves some shared discrepancy into non-target components. Cholesky gives higher target-pair power and broader moderate elevations across non-target pairs, whereas the sequential components show more concentrated, order-dependent peaks. With wide symmetric intercepts, power differs greatly among target pairs, and the Lagrange multiplier statistic is particularly sensitive to intercept distance. The main qualitative patterns persist across three nominal levels. Lower-order omnibus statistics generally maintain an empirical Type I error close to the nominal levels and detect the slope alternatives, whereas Pearson–Fisher is liberal in the sparse full table. A symmetric parameter vector therefore need not give uniform local diagnostic results. Full article

Multi-product production systems require effective coordination among production, intermediate storage, downstream processing, and customer demand, particularly under stochastic operating conditions and finite capacity. Unlike existing analytical studies that mainly examine either single-product push–pull systems or multi-product manufacturing systems separately, this work develops an exact CTMC framework that jointly captures product variety, shared buffering, downstream parallelization, sequence-dependent setups, and machine unreliability. The system comprises an unreliable upstream machine with sequence-dependent setup changes, a finite intermediate buffer, a distribution center modeled as a pooled processing resource with (M) identical reliable channels, and dedicated finished-goods buffers serving product-specific demand. A high-dimensional continuous-time Markov chain is formulated, and a systematic algorithm is developed to construct the infinitesimal generator matrix and compute steady-state performance measures. Numerical experiments examine intermediate buffer capacity, downstream processing capacity, priority rules, and upstream machine reliability. Increasing buffer capacity from 0 to 20 increases total throughput from 0.5937 to 1.0988, whereas further expansion to 100 yields only 1.1606, while average work-in-process reaches 19.8524. Downstream capacity exhibits similar diminishing performance gains, while priority rules and machine reliability affect product-level and overall throughput. These findings highlight throughput–inventory trade-offs and demonstrate the framework’s applicability for evaluating alternative configurations. Full article

Family science lacks a shared ontological account of its central referent: what kind of thing F-A-M-I-L-Y is remains unclear. This gap undermines theoretical coherence, inhibits cumulative knowledge-building, and weakens the field’s policy relevance. The essay traces how family science inherited distinct frames from parent disciplines at founding, without consolidating a shared ontological account. Drawing on the metaphysics of organized and feature social groups and the philosophy of deliberate care, the essay applies systematic ontological analysis to F-A-M-I-L-Y as a candidate distinct social kind. Comparison across six metaphysical dimensions reveals that F-A-M-I-L-Y shares features with organized groups but diverges in structural-functional organization, collective intentionality, member volition, and the source of these shared features. These are not definitional failures; they are a coherent ontological pattern. The paper suggests that F-A-M-I-L-Y is a care-constituted relational nexus: a structured web of care-bonds among particular persons, constituted by deliberate care oriented toward the adequate viability of those persons through the real conditions of their existence. This framework resolves apparent tensions between embattled conceptions of F-A-M-I-L-Y, accommodates technological complexity in reproduction, and provides actionable methodological guidance for researchers. Ontological precision and genuine inclusiveness are not competing goods; the care-constitution framework demonstrates they are mutually reinforcing. Full article

Tetrodotoxin (TTX) is a potent marine neurotoxin responsible for severe seafood poisoning in humans, characterized by neurological symptoms that may be fatal. Originally identified as a natural contaminant of pufferfish (Tetraodontidae family), over the last few years TTX and its analogs have also been detected in other edible marine organisms, including mollusks, gastropods and crustaceans. Consequently, there is a need for rapid, sensitive, and reliable methods for TTX detection in seafood. In this study, a functional assay based on the use of mouse neuroblastoma Neuro-2a cells has been optimized and characterized for TTX detection in mussels. The assay is based on the toxin’s ability to block voltage-gated sodium channels, thereby counteracting the sodium-dependent cytotoxicity induced by veratridine and ouabain. The linear range of the TTX standard curve fell between 0.44 and 33 ng/mL, with limits of TTX detection (LOD) and quantitation (LOQ) of 0.132 ng/mL and 0.439 ng/mL, respectively, and good intra- and inter-day repeatability (RSDr= 15 and 11%, respectively). The assay also detected saxitoxin, which shares the same mechanism of action as TTX, but was less sensitive towards 4,9-anhydro-TTX. The minimum mussel extract dilution of 1:100 did not result in matrix-related interference, allowing accurate TTX quantitation, with a LOQ of 0.54 µg TTX equivalents/kg mussel meat. Given its sensitivity, the optimized Neuro-2a assay represents a promising tool for toxicity-based TTX quantitation in mussels before their consumption. Full article

Existing CNN, TCN, residual, and lightweight network methods have achieved good performance in IGBT open-circuit fault diagnosis, but they often overlook the non-Euclidean relationships among signals. To address this limitation, this paper proposes a parallel graph–temporal network for T-NPC three-level inverters. A shared CNN extracts compact features from the three-phase currents and voltages, while the Sinkhorn–Wasserstein distance constructs a sample-level weighted dynamic graph for GCN-based relationship extraction. In parallel, BiGRU with global attention captures temporal information. Unlike fixed or equally weighted graphs, the proposed method adapts signal connections to different fault conditions. Furthermore, simulation models are constructed in MATLAB/Simulink, and the T-NPC converter operation is emulated on a real-time simulator Starsim MT6060. The proposed dual-stream model classifies 21 fault states, achieving an average validation accuracy of 99.88%, while maintaining high accuracy under severe noise. Full article

Concentrated sourcing is a structural property of the world economy rather than an occasional accident: across 168 national economies and 1118 four-digit product markets reconstructed from harmonized cross-border flow records, 27.7% of macro-level economy–product supply systems draw more than half of their imports from a single origin and 19.3% are critically dependent. Treating each such market as a system rather than as a set of bilateral links changes what can be asked of it, and this paper specifies the economy–product supply system in systems-engineering terms—boundary, elements, internal relations, external environment, state and state transition—and represents it as a time-evolving hyperedge over source countries. Three coupled questions follow, answered jointly by HyperSRM: which dependency state a system will occupy next year, whether it will diversify, reconcentrate, hold, or merely substitute one origin for another, and which origins are most consistent with the observed conditions preceding a material entry. Shared country and product embeddings support two temporal set-encoding branches, a candidate-conditioned branch for origin ranking and a candidate-free branch for state and mode forecasting, a sign-constrained gravity–capability–connectivity prior supplies an observational plausibility score with end use and maritime reachability as its context, and risk weights derived from the state head direct effort toward the most exposed systems. Developed on CEPII BACI, rebuilt independently on Eurostat Comext and audited against U.S. Census data at the level of the labels themselves, the framework returns calibrated state probabilities and a ten-origin shortlist that captures 58.1% of the following year’s risk-weighted material-entry mass and is accompanied by explicit out-of-pool diagnostics. These outputs describe the import-sourcing layer of resilience and are intended for analytical triage rather than a complete assessment of supply resilience. Three system-level regularities carry beyond the model: the arrival of a new origin is a weak proxy for diversification, critical dependency is close to absorbing for specified intermediate inputs but not for final goods, and the 2020–2021 contraction rearranged source sets without widening them—so resilience monitoring built on source counts misreads the direction of change. Full article

Ensuring food safety requires the detection of trace-level contaminants such as pesticides, mycotoxins, and heavy metals. Analytical approaches for these analytes should feature high sensitivity, good selectivity, and compatibility with aqueous matrices; surface-enhanced Raman spectroscopy (SERS) satisfies these requirements. Addressing the absence of a unified comparative analytical framework, this critical review surveys recent SERS-enabled sensing strategies for food contaminants. Detection strategies differ substantially across the three contaminant classes: pesticides can be directly detected at ppb levels through substrate engineering and deep learning; mycotoxins rely on affinity-recognition elements to reach pg-mL-level sensitivity; and Raman-inactive heavy metals demand indirect readout via functional probes. Crucially, despite these divergent analytical routes, the field confronts three shared bottlenecks—spectral irreproducibility, severe matrix interference, and the lack of standardized protocols, all of which hinder regulatory adoption. Compared with near-infrared spectroscopy (NIR) and hyperspectral imaging (HSI), SERS delivers outstanding sensitivity for confirmatory trace-level analysis, while its limited throughput may be compensated by multispectral data fusion. Future advances should prioritize portable sensing hardware, explainable Artificial Intelligence (AI), and multiplexed detection to transfer laboratory-scale sensitivity toward practical field-deployable testing tools. Full article

Objectives: Long-term or inappropriate use of benzodiazepine receptor agonists (BZRAs) in older adults is a medication-safety concern. This study mapped trends, contributors, knowledge structures, and research hotspots of BZRA deprescribing using a comparative dual-database bibliometric framework. Methods: English-language articles and reviews from 1 January 2008 to 21 May 2026 were retrieved from the Web of Science Core Collection (WoSCC) and Scopus. Of the 377 WoSCC and 558 Scopus records entering topical relevance screening, 306 and 418, respectively, met the final eligibility criteria. Among the final datasets, 225 publications were shared, yielding 499 unique publications. The BIBLIO framework guided reporting. Analyses used R, bibliometrix, and VOSviewer, whereas CiteSpace-based analyses were restricted to WoSCC. Data for 2026 were partial; trend models used complete years through 2025. Results: Publication output showed an overall upward trend, with output during 2021–2025 generally higher than in earlier years. Quadratic models based on 2008–2025 data showed good fit for WoSCC (R² = 0.8890) and Scopus (R² = 0.9104). The United States, Canada, and Australia were leading contributors, and the University of Montreal was the leading institution (WoSCC, n = 19; Scopus, n = 18). Across both databases, themes evolved from withdrawal, discontinuation, and potentially inappropriate prescribing toward medication safety, prescription optimization, medication review, patient education, and implementation in primary care and long-term care settings. Conclusions: BZRA deprescribing research has broadened from drug discontinuation toward a patient-centered medication-safety and prescription-optimization framework. Future research should evaluate individualized tapering, nonpharmacological support, multidisciplinary care models, and standardized long-term patient-centered and safety outcomes. Full article

Smart rings are emerging as a promising class of sensing devices that enable unobtrusive, always-available interaction with Internet of Things (IoT) ecosystems. These wearable devices support intuitive gesture-based control while minimizing user attention and preserving mobility. However, despite rapid advances in sensing hardware and gesture recognition algorithms, little is known about how users associate ring-based shared gestures with smart-home commands. To fill this gap, this paper presents Oringano, a framework for designing and evaluating a vocabulary of shared ring-based gestures for controlling IoT devices in a smart home. These gestures are original in that members of the same group can share the same gestures for the same actions, as well as gestures customized by each individual. The proposed approach combines (i) a synthesis of contemporary smart ring-based gesture interaction literature, (ii) a user-centered requirements elicitation identifying representative smart-home control actions, (iii) a gesture elicitation study involving $N=30$ participants to derive a vocabulary of shared ring-based gestures for 15 IoT control actions, (iv) an empirical analysis of gesture agreement and usability of Oringano, a smartphone prototype for managing shared ring-based gestures, and (v) a set of implications for designing shared gestures for future smart-ring systems. Experimental results demonstrate high agreement for concrete actions such as selection, navigation, and media control, whereas abstract actions exhibit greater variability, highlighting opportunities for personalized gestural interaction. The shared gestures benefit from a higher average agreement rate (+84%), a slightly lower goodness of fit (−13%), and a longer thinking time (+115%) than normal ring-based gestures. The subjective satisfaction resulting from the usability evaluation of Oringano, based on the elicited vocabulary, is overall positive (4.5/5). These results advance the design of next-generation ring-based systems by bridging user-centered gesture interaction with practical sensing technologies for IoT interaction. Full article

This study examined dynamic associations among stress, anxiety, and depressive symptoms during the first year of junior high school, a developmental period in early adolescence characterized by heightened vulnerability to psychological problems. A total of 503 students who had recently entered junior high school completed the Depression Anxiety Stress Scales-21 (DASS-21) at three time points, six months apart. Random-intercept cross-lagged panel modeling and network analysis were used to examine longitudinal symptom associations. Results revealed that, at the between-person level, symptoms of stress, anxiety, and depression were highly correlated (rs = 0.86–0.94), with their shared variance largely captured by a general factor. At the within-person level, anxiety showed significant autoregressive effects, and higher-than-usual anxiety at one time point was prospectively associated with higher-than-usual stress at the subsequent time point (ps ≤ 0.001). Among boys, breathing difficulty and worry about panic or embarrassment showed the highest out-expected influence values, whereas scared without any good reason and over-reacting to situations showed the highest values among girls. These findings suggest that, in the current study sample, anxiety may represent a potentially important focus for future intervention research and that the exploratory sex-stratified symptom patterns warrant further investigation. Full article