Search Results (691)

Offshore wind development in the Colombian Caribbean requires characterization of tropical cyclone exposure to support climate-resilient planning, yet objective regime classifications for this basin remain limited. This study develops an unsupervised Self-Organizing Map (SOM) framework using the NOAA HURDAT2 best-track database for 1970–2023, comprising 668 six-hourly observations from 103 storms and nine physically interpretable features describing position, intensity, kinematics, and seasonality. A 4 × 4 SOM combined with hierarchical Ward clustering identified four cyclone exposure regimes: R0, late-season slow north-eastward disturbances near San Andrés (11.5%); R1, fast westward mature tropical storms across the central Caribbean (62.0%); R2, slow north-westward disturbances off Central America (21.9%); and R3, rare major hurricanes crossing the central Caribbean (4.6%, seven storms; historical mean recurrence interval 7.7 years). R3 exhibited mean maximum sustained winds of 67.8 m/s and a minimum central pressure of 938.5 hPa, with peak winds reaching 79.7 m/s. The results provide a complementary historical hazard characterization layer for offshore wind planning, supporting risk-informed spatial and operational assessment. However, the identified regimes do not represent wind-resource conditions or probabilistic design return periods and should therefore be integrated with site-specific wind, wave, and structural assessments. Full article

Background: Football performance emerges from the interaction of technical, physical, and perceptual-cognitive abilities, yet talent identification protocols often assess these components separately. This study examined whether football-specific dual-task (DT) performance, assessed using the Soccer Skills and Cognitive Aptitude Test (SoSCAT), could discriminate between coach-rated talent levels in youth football players. Methods: A total of 181 male football players aged 12–18 years participated in this cross-sectional study and were classified into U14 (n = 70), U16 (n = 63), and U18 (n = 48) categories. Based on coaches’ evaluations, players were also classified as more talented (n = 46) or less talented (n = 135). Participants completed football-specific technical, physical, cognitive, and DT assessments. Results: Coach-rated talented players demonstrated superior football-specific DT performance, with faster completion times under DT conditions (partial η² = 0.190), a smaller increase in completion time (ΔTime; partial η² = 0.095), lower DTC (r_rβ = −0.351), and fewer decision errors (r_rβ = −0.211). Older players showed better absolute DT performance and fewer decision errors, although ΔTime and DTC did not differ between age categories. Age, coach-rated talent status, league goals, and football-specific technical performance remained independently associated with SoSCAT DT performance (adjusted R² = 0.500). ROC analysis showed good discriminative ability for SoSCAT DT performance (AUC = 0.822). Conclusions: Football-specific DT performance demonstrated good discriminative ability between coach-rated talent levels. The SoSCAT may represent a valuable complementary tool for multidimensional player assessment by integrating football-specific technical execution and perceptual-cognitive demands. However, its interpretation should consider the cross-sectional design, absence of biological maturation assessment, and reliance on coach-rated talent classification. Full article

Low adult density can suppress recruitment through mate limitation or cooperative reproductive failure, even when a host improves adult survival. Motivated by this ecological tension, we introduce a fecundity-related component Allee effect into a stage-structured commensalism model with a Holling type II host benefit. The nonlinear recruitment term is $f\left(x_2\right)=\alpha x_2^2/(x_2+A)$, and the independently growing host converges to its carrying capacity, yielding an asymptotically autonomous commensal subsystem. We obtain a complete analytical classification. If the long-term host benefit D exceeds mature mortality ${\delta }_2$, a unique coexistence equilibrium attracts every nontrivial commensal population. If the benefit is insufficient, fecundity limitation can instead create two positive equilibria: a low-density saddle whose stable set is the basin boundary and a stable high-density coexistence state. Thus, extinction and coexistence are both possible, depending on initial stage composition and host abundance. Stronger fecundity limitation enlarges the extinction region, whereas greater recruitment, maturation or host benefit promotes persistence. At the critical boundary, the positive equilibria merge in a non-degenerate saddle-node bifurcation. Rigorous global arguments and numerical comparisons with the linear-recruitment model show how a component Allee effect can induce strong-Allee-type demographic behavior, including bistability and threshold-mediated extinction. Full article

Background/Objectives: Skeletal maturity assessment is essential for timing orthodontic growth-modification treatment. The cervical vertebral maturation (CVM) method is widely used, but manual staging is subjective and prone to inter-observer variability, and artificial intelligence (AI) may improve its consistency and accuracy. The aim of this study was to develop and externally validate a fully automated deep-learning pipeline for CVM assessment and to determine its diagnostic accuracy for three-phase and six-stage classification against calibrated expert staging. Methods: A cross-sectional three-stage deep-learning pipeline was trained and internally cross-validated on 523 cephalometric radiographs from King Abdulaziz University. Images were CLAHE-enhanced; YOLOv8 detected the C2–C4 region; a ResNet-50 classifier assigned the growth phase (Early, Peak, Late); and phase-specific binary classifiers assigned CVM stages (CS1–CS6). External validation used the independent ‘Aariz dataset (n = 150). Results: The detector achieved mAP@0.5 = 0.9939 and mean IoU = 0.8884. On external validation, the three-phase classifier reached 96.0% accuracy, macro-F1 0.919, weighted κ 0.951 and ROC-AUC 0.998, whereas the end-to-end six-stage cascade reached 79.3% accuracy, macro-F1 0.735, weighted κ 0.910 and ROC-AUC 0.923. Most errors occurred between adjacent stages, with 98.7% of predictions within ±1 stage of the reference standard. Conclusions: The automated pipeline showed promising performance for three-phase CVM classification and moderate performance for six-stage classification on one independent external benchmark. Further multicenter prospective validation is required to establish its generalizability and clinical utility. Full article

Forensic age determination in presumed minors is affected by a structural tension between biological uncertainty, juridical thresholds, and the ethical duty to protect childhood. Conventional dental age estimation methods provide point estimates of chronological age but do not directly address the question central to legal proceedings: whether adult status can be affirmed with certainty. This short communication introduces MIDAS (Maturity Index for Determination of Adult Status), a certainty-based, hybrid human–AI framework for adult age determination. Two forensic odontologists independently assessed mandibular third-molar development (Radicular Completion Ratio, R₈; Apical Closure Index, A₈) in 180 anonymized orthopantomographs of individuals aged 14–25 years, complemented by an AI-assisted radiomorphometric module extracting root density relative to enamel (D₇) and trabecular texture homogeneity (T_m). These parameters were integrated into a continuous Integrated Dental Maturity Index (IMD). By raising the biological reference age to 20 years and excluding the 17–20-year interval from affirmative adult classification, the framework operationalizes the precautionary principle, interpreting residual uncertainty in favor of childhood protection. As a proof of concept, this study establishes the conceptual and operational architecture of MIDAS rather than its diagnostic accuracy. Formal validation on larger and more diverse populations is required before routine forensic and medico-legal application. Should such validation confirm its performance, MIDAS could offer an ethically grounded, legally coherent, and scientifically transparent complement to conventional methods of dental age estimation and adulthood determination. Full article

Free amino acids serve as a crucial hub connecting plant life activities with human nutrition. The fruits of Cucurbitaceae crops are natural nitrogen reservoirs, rich in free amino acids such as citrulline, arginine, and γ-aminobutyric acid (GABA). To investigate the spatial accumulation characteristics and differential distribution of free amino acids in cucurbit fruits, this study measured the contents of 19 free amino acids in the fruit stem, epicarp, endocarp, pulp, and seeds of 10 cucurbit species (12 varieties) at the mature stage. The results revealed that free amino acid accumulation exhibits significant tissue specificity and species specificity, forming diverse nitrogen metabolism hubs. Glutamine, aspartate, asparagine, arginine, and citrulline constitute a highly coordinated core module of nitrogen metabolism in Cucurbitaceae. Methionine, valine, and some other amino acids were consistently present at extremely low levels across tissues, indicating a competitive diversion of conserved metabolic pathways coexisting among species. Species classification based on free amino acids differed markedly from traditional taxonomy based on gene domestication, implying environmental selection pressures and non-linear gene-metabolite network relationships. Glutamine, GABA, citrulline, and arginine were identified as core hub metabolites supporting tissue type classification. This study revealed the allocation characteristics of free amino acids in fruits of various cucurbit crops and established a functional model integrating nitrogen assimilation, flavor/energy metabolism, stress tolerance/defense signaling, and storage across different tissue types of multiple cucurbit crops, providing new perspectives for precision breeding and domestication mechanism research in Cucurbitaceae. Full article

Background/Objectives: Field-based health screening in adolescents requires accurate, non-invasive, and feasible diagnostic tools. This study evaluated the discriminatory capacity of anthropometric parameters and physical fitness tests for identifying waist-to-height ratio (WHtR)-defined surrogate cardiometabolic risk across sex and biological maturity status, determining exploratory cut-off thresholds. Methods: A cross-sectional study was conducted with 2944 Spanish adolescents (1459 males, 1485 females; age: 13.35 ± 1.20 years). Anthropometric variables (BMI, skinfolds, fat/muscle mass) and physical fitness tests (20-m shuttle run, handgrip, CMJ, SBJ, 20-m sprint, curl-up; evaluated in raw and body-mass-normalized formats) were assessed. Biological maturation was estimated via Age at Peak Height Velocity (APHV) using Mirwald equations and categorized into early, on-time, and late maturers relative to the sample mean. Surrogate risk was operationalized strictly as WHtR ≥ 0.50, without direct assessment of biochemical or hemodynamic parameters. Receiver operating characteristic (ROC) curves, optimal Youden-derived cut-offs, and internal bootstrap validation (1000 resamples) were performed. Results: Anthropometric parameters demonstrated high discriminatory performance for detecting WHtR-defined surrogate risk across all sex and maturation cohorts (AUC = 0.88–0.98). Unadjusted physical fitness tests showed poor overall classification performance. However, normalizing fitness metrics for body mass (particularly relative CMJ and cardiorespiratory fitness) substantially improved discriminatory capacity. Optimal cut-off values for anthropometric indicators displayed an observed descending pattern across progressively later-maturing cohorts. Conclusions: Anthropometric parameters represent highly accurate field proxies for WHtR-defined surrogate risk screening in adolescents. While unadjusted fitness metrics have limited utility for this anthropometric outcome, body-mass-normalized fitness parameters substantially recover classification capacity. Biological maturation timing should be carefully considered when future research derives and externally validates adolescent screening thresholds, as current cut-offs remain exploratory and sample-derived. Full article

Closely related Aspergillus section Nigri species are difficult to resolve taxonomically, while short-read comparisons may be influenced by reference-genome choice. We applied reciprocal genome projection to 31 whole-genome sequencing libraries representing South African clinical section-Nigri isolates, Japanese and USA A. niger-labeled isolates, and A. welwitschiae-labeled isolates. Reads were aligned independently to A. niger ATCC 1015 and A. welwitschiae Aspwel1, followed by reference-specific differential-representation and KEGG analyses. Species-level classification showed substantial overlap between A. niger and A. welwitschiae. The A. welwitschiae–South African comparison identified 44 and 59 effect-qualified features under the respective projections, including 20 reciprocal feature pairs defining a reference-robust A. welwitschiae-associated core. The clinical Japanese–South African comparison identified 116 and 127 features, with 14 concordant KEGG orthologs involving sterol modification, protein prenylation, cofactor metabolism, redox processing, cell-wall turnover and ribosome maturation. No pathway remained significant after false discovery-rate correction; nominal pathway signals were reference-sensitive. Reciprocal projection, therefore, recovered localized cohort-associated genomic differentiation while identifying reference-conditioned effects. These findings represent differential genomic-read representation and do not independently establish copy-number variation, pathway activity, virulence or antifungal resistance. Full article

The energy sector is considered one of the most critical sectors because disruptions to the power supply, problems with systems for monitoring operational parameters, and issues with power management processes have a direct impact on the economy, public order, and national security. On the one hand, the technological maturity of energy facilities is changing, and the share of grid-inverter-connected renewable energy sources (GICRES) is expanding. In this article, the authors discuss the basic concepts and classifications of stability-related subsystems. The new trends and challenges facing the resilience of the electrical energy system (EES) in the context of dynamic processes arising from the deployment of renewable energy sources (RES) are analyzed. This paper aims to present a more comprehensive concept of the static and dynamic stability of the EES, considering the impact of grid-inverter-connected renewable energy sources (GICRES). Full article

Two claims dominate popular discussion of US food safety: (1) Food recalls are rising year over year, and (2) undeclared allergens have become the leading cause. In this study, we aimed to (1) test both claims against the openFDA Food Enforcement bulk export for fiscal years (FY) 2013–2025, the post-FSMA-core period following implementation of the FDA Food Safety Modernization Act (FSMA), including 24,761 conventional human-food product recall records; (2) identify the dominant microbiological hazards and undeclared allergens that drive FDA recalls; (3) compare the FDA recall record with USDA Food Safety and Inspection Service (FSIS) recalls of meat, poultry, and egg products; and (4) evaluate potential correlations between FDA and FSIS recall activity and the foodborne-illness burden recorded in CDC’s National Outbreak Reporting System (NORS). Product recall records were recoded into five hazard categories using a validated 70-rule keyword scheme. Our analysis showed that annual product recall records did not increase (mean falling from 2403/yr in FY2013–2017 to 1593/yr in FY2018–2025, Welch t = 3.08, p = 0.024), and microbiological hazards were the largest category in 12 of 13 years, exceeding allergens 1.7-fold cumulatively. Listeria monocytogenes was a major driver of microbiological food recalls concentrated in fresh produce, ice cream/frozen desserts, and dairy/cheese; whereas undeclared milk was by a wide margin the most-cited allergen in food recalls concentrated in dairy/cheese, ice cream, and bakery products. Compared to FDA recalls, FSIS recalls were fewer, more severe (68.6% vs. 45.6% Class I), and allergen-led, reflecting differing inspection frameworks rather than a uniform allergen surge. Overall, food recalls and foodborne outbreak illnesses did not display a significant correlation (Spearman rho = 0.30). Classification lag shortened over the period (rho = −0.32, p < 0.001), a process-efficiency gain that can masquerade as rising recall activity in count-based trackers. Across all four objectives, the recall record describes a maturing, severity-weighted surveillance system rather than a deteriorating food supply. Full article

Industrial Control Systems (ICSs), which underpin communications and operations in industrial environments in general and in critical infrastructures in particular, are targeted by malicious actors for diverse reasons. To strengthen their resilience against cybersecurity attacks, testbeds play a fundamental role in supporting experimentation, the validation of defense mechanisms, dataset generation, and architecture evaluation, among other activities. However, existing testbeds differ considerably in their functional capabilities, architectural completeness, implemented technologies, and degree of documentation, making systematic comparison and classification difficult. This paper presents a comparative analysis of 34 ICS cybersecurity testbeds within a Purdue-aligned framework based on two complementary dimensions: Functional Maturity (FM) and Architectural Completeness (AC). The former evaluates capabilities relevant to cybersecurity experimentation, while the latter measures the coverage of Purdue-aligned and supporting IT/OT components the testbed includes. To address this problem, we propose a methodology that enables the identification of technology adoption patterns, capability distributions, and recurring architectural characteristics across contemporary testbed implementations. Results reveal that many platforms provide advanced experimentation capabilities while offering only partial representation of industrial and enterprise environments. Moreover, the analysis also highlights underrepresented architectural components that may influence the scope of cybersecurity, Industrial Internet of Things (IIoT), and Industry 5.0 research that can be conducted within a testbed. Finally, based on these findings, a Purdue-aligned testbed blueprint is proposed as a reusable conceptual baseline for the design and comparison of future industrial cybersecurity experimentation environments. Full article

Building facades are continually exposed to weathering, material aging, hygrothermal cycling, and service-related disturbances. Cracks, delamination, spalling, and seepage can compromise durability and safety, while associated thermal anomalies provide indirect evidence of deterioration. Deep learning, UAV inspection, infrared thermography, LiDAR, building information modeling (BIM), and digital twins have shifted facade inspection toward automated sensing and spatially referenced assessment. Yet most studies remain focused on isolated measures of model accuracy and give limited attention to the full pathway from detection and quantification to component localization, condition rating, and repair. This review organizes the evidence along five dimensions: annotation granularity (A0–A2/A2*), visual task hierarchy (T1–T5), fusion level (F0–F3), spatial mapping level (S0–S3), and engineering maturity (M1–M3). The synthesis indicates that acquisition conditions, material heterogeneity, negative-sample composition, and annotation rules constrain model generalization. Single-modality methods cover classification, detection, segmentation, and partial geometric quantification, but facade-specific external validation remains limited. Multimodal gains depend on registration quality, thermophysical conditions, defect mechanisms, and sensor reliability. Mapping two-dimensional outputs to point clouds, BIM, and digital twins is technically feasible, but error propagation, component matching, and condition-rating protocols remain inconsistent. Interpretability tools and vision foundation models may support verification, annotation, and reporting but cannot replace dedicated systems with validated error bounds. Future work should prioritize cross-dataset benchmarks, facade-specific lightweight models, reproducible multimodal evaluation, standardized 2D-to-3D accuracy protocols, uncertainty-aware manual review, and engineering condition-rating frameworks. Full article

Pulmonary hypertension (PH) is a heterogeneous clinical syndrome in which similar haemodynamic abnormalities may arise from distinct vascular, cardiac, pulmonary, thromboembolic, and molecular mechanisms. This complexity limits the ability of conventional classifications and risk scores to fully capture individual disease trajectories and treatment responses. Artificial intelligence (AI) offers a framework for integrating clinical data, electrocardiography, multimodal imaging, invasive haemodynamics, biomarkers, and multi-omics information across the PH care pathway. This review summarises current applications of machine learning and deep learning in early detection, diagnostic referral, right-ventricular and pulmonary vascular phenotyping, molecular endotyping, risk stratification, and therapeutic decision support. Available studies show promising results for AI-assisted electrocardiographic screening, automated echocardiographic and cardiac magnetic resonance analysis, computed tomography (CT)-based phenotyping, and multimodal prognostic modelling. True multi-omics integration in PH remains limited to discovery studies and has not yet yielded externally validated endotype or treatment-response classifiers. Evidence maturity is task-dependent: screening and phenotyping span several PH groups, whereas validated risk tools, molecular endotyping, and pathway-directed therapy remain predominantly PAH-based, particularly in idiopathic/heritable PAH. However, most evidence remains retrospective, derives from selected referral populations, and lacks robust external or prospective validation. No AI-based model currently supports routine drug selection or autonomous clinical decision-making. Future progress will require harmonised multicentre datasets and standardised acquisition protocols, transparent and interpretable models, and prospective studies demonstrating meaningful clinical benefit. AI should therefore be viewed as an emerging decision-support tool that may strengthen precision medicine in PH while complementing clinical expertise across diagnosis, phenotyping, risk assessment, and therapeutic stratification pathways. Full article

Extensive small-ruminant grazing sustains food production on the Mediterranean land with few alternative uses, yet supervision is intermittent and welfare oversight weak. Digital monitoring is expected to close that gap, but detection alone does not produce intervention. In remote rangelands the link is unreliable, so an inference may reach the farmer late, degraded or not at all, and an alert arriving after the animal has moved is not a weaker alert but a different decision. This study develops a human-in-the-loop decision framework in which the delivery state of the link becomes a decision variable rather than a transport detail, coupling technology, farmer behaviour and governance. Constructed through design science research and structured analysis of an EU-funded project’s specifications and evaluation plans, it comprises a seven-layer architecture, a decision-episode schema, a connectivity-aware alert lifecycle, a decision-provenance matrix, and an evidence-maturity classification constraining what may be claimed. Five decision classes from a Cretan sheep and goat pilot instantiate it. After applying it, specification inconsistencies invisible to component-level review surfaced, among which is an alert payload lacking the coordinates, confidence and severity that its own indicators require. The framework is an instantiated specification, not a validated intervention: no detection, delivery, acknowledgement, usability or sustainability outcome is measured. Full article

Background: Heritable thoracic aortic disease (HTAD) accounts for approximately 20–25% of thoracic aortic aneurysm and dissection (TAAD) cases and is a major cause of premature death in young adults. Methods: This is a narrative, non-systematic review. We performed a selective synthesis of clinical practice guidelines (ACC/AHA 2022, EACTS/STS 2024), the revised Ghent nosology, large multicenter cohort studies (Montalcino Aortic Consortium), randomized pharmacotherapy trials, and molecular mechanism data published between 2010 and 2025; quantitative figures are reported as published in individual primary sources and were not pooled or re-analyzed. Results: The advent of next-generation sequencing (NGS) has driven a paradigm shift in HTAD management, from risk assessment based purely on phenotype (aortic diameter) to risk stratification based on genotype (molecular mutation). The 2022 ACC/AHA guideline identifies eleven genes with confirmed high-penetrance risk for HTAD; these, together with the established Loeys–Dietz gene TGFB3 (recognized through gene–disease validity assessment rather than the ACC/AHA list), can be grouped into three pathogenic mechanisms: extracellular matrix dysregulation, TGF-β signaling dysregulation, and vascular smooth muscle contractile dysfunction. Gene–disease association should be distinguished from guideline-defined classification and regarded as evolving, since additional candidate genes such as LTBP3 are already emerging in gene-negative families. Multigene panel testing identifies a pathogenic or likely pathogenic variant in roughly 8% of patients referred for suspected HTAD, a yield that rises substantially when applied to syndromic or strongly familial presentations. Prophylactic surgical thresholds are individualized by gene and are generally lower (around 4.0 cm) for high-risk TGFBR1/TGFBR2 and PRKG1 variants and higher (around 5.0 cm) for FBN1 and TGFB3, in contrast with the uniform 5.5 cm threshold historically applied to all patients. Randomized trials over the past decade—including the AIMS irbesartan trial, the Marfan Treatment Trialists’ individual patient data meta-analysis, and the celiprolol and irbesartan trials in vascular Ehlers–Danlos syndrome—now provide direct evidence that angiotensin receptor blockade slows the rate of aortic root dilation in Marfan syndrome, with more limited evidence in vascular Ehlers–Danlos syndrome and uncertain effects on dissection or mortality, while valve-sparing aortic root replacement provides durable long-term outcomes in reported single-center experience. These thresholds and pharmacotherapy recommendations rest predominantly on observational cohort, registry, and randomized trial data of varying maturity and should be interpreted as graded, evolving recommendations rather than fixed cut-points. Conclusions: This review synthesizes the molecular pathogenesis, diagnostic nosology, gene-specific epidemiologic and prognostic data, genetic testing yield, pharmacotherapy evidence, surgical outcomes, and updated prophylactic intervention algorithms per the ACC/AHA (2022) and EACTS/STS (2024) guidelines, providing a practical reference framework for individualizing surveillance and surgical decision-making in patients with HTAD. Full article