Search Results (15,390)

Heavy episodic drinking (HED) is prevalent in young adulthood, yet its relationship with psychosocial well-being remains complex. This study examines the association between HED and perceived social isolation among young adults and tests whether this relationship varies by sexual orientation. Using pooled, nationally representative data from the 2022 and 2024 Health Information National Trends Survey (HINTS), this study analyzed adults aged 18–29 (N = 723). Perceived social isolation was measured using the PROMIS Social Isolation Short Form. Weighted multivariable linear regression models assessed interactions between sexual orientation and HED occasions (0 vs. 1+), adjusting for sociodemographic variables and psychological distress. 45.5% reported HED. Lesbian/gay (B = 5.62, SE = 0.58, p < 0.001) and bisexual (B = 1.66, SE = 0.34, p < 0.001) young adults reported higher isolation than straight peers; HED was inversely associated with isolation (B = −1.71, SE = 0.20, p < 0.001). A significant interaction indicated that among lesbian/gay young adults, heavy drinking was associated with lower perceived isolation (B = −5.77, SE = 0.98, p < 0.001). Interventions should account for the social meanings of alcohol use to avoid unintentionally increasing isolation among sexual minoritized populations. Full article

The emergence of variant strains of Avian orthoreovirus (ARV) has caused substantial economic losses in the poultry industry worldwide, but the molecular features of goose-origin strains and viral transmission among different avian species remain poorly understood. Here, we describe a goose-origin avian orthoreovirus strain, SD0407, associated with growth retardation and joint swelling. Complete genome analysis identified ten double-stranded RNA segments. Sequence comparison indicated that SD0407 is closely related to previously reported duck-origin reovirus strains. Phylogenetic and recombination analyses showed that most segments clustered with duck-origin strains, indicating close genetic relatedness among waterfowl-origin orthoreoviruses. Sequence and structural analysis of the σC attachment protein revealed ten unique amino acid substitutions, including D250 within the DE-loop region involved in receptor-binding. Molecular docking suggested that σC interacts with the conserved AnxA2-S100A10 heterotetrameric receptor complex, providing a possible structural basis for receptor compatibility across avian species. Although SD0407 replicated efficiently in goose embryo fibroblasts, it did not induce expression of type I, II or III interferons. Transcriptome profiling revealed weak activation of innate immune signaling and downregulation of metabolic and cytoskeletal genes, consistent with effective suppression of antiviral responses. These findings demonstrate that SD0407 combines structural variability with immune evasion to enhance host adaptability and underscore the importance of sustained ARV surveillance in waterfowl populations. Full article

Background: Owing to significant clinical heterogeneity, the achievement of accurate survival forecasting for individuals with colorectal cancer and peritoneal metastasis continues to be a complex undertaking. We aimed to transcend traditional prognostic limitations by evaluating machine learning boosting models against standard regression-based methods in terms of estimating overall survival (OS). Methods: Utilizing a multi-institutional registry of 150 patients diagnosed with synchronous peritoneal metastasis of colorectal cancer, we integrated 124 clinicopathological variables to refine our predictive models. Beyond standard preprocessing—including standardization and median imputation—we rigorously compared XGBoost and LightGBM against Ridge, Lasso, and linear regression via five-fold cross-validation. To specifically address right-censoring, an XGBoost Cox model was implemented and validated using Harrell’s C-index, with SHAP and LIME providing essential model interpretability. Results: Boosting models consistently outperformed linear alternatives, which struggled with high error rates and negative R2 values. Specifically, XGBoost achieved an MAE of 475 ± 60 and an RMSE of 585 ± 88. The XGBoost Cox model reached a C-index of 0.64 ± 0.06. SHAP analysis highlighted inflammatory markers and peritoneal disease extent as the most influential prognostic drivers. Conclusions: While boosting models offer a clear accuracy advantage over linear methods, their prognostic power remains moderate. These findings underscore the potential of ensemble learning in oncology, yet mandate external validation before these tools can be integrated into clinical decision-making. Full article

Precision agriculture has become a major direction of agricultural technological development in recent decades, addressing efficiency, environmental, and economic challenges simultaneously. Input optimization based on site-specific data collection—particularly variable-rate nutrient application, precision irrigation systems, and targeted crop protection—has been shown to generate measurable cost and resource savings. The aim of the study is to explore and systematically evaluate the economic impacts influencing precision technology in crop production. Although the technical and environmental benefits of precision technologies are widely documented, their economic performance and farm-level profitability remain inconsistently interpreted. The study is based on a systematic literature review of peer-reviewed English-language journal articles retrieved from the Web of Science, Scopus, ScienceDirect, and JSTOR databases. Study selection and evaluation were conducted in accordance with the PRISMA 2020 methodological framework. The literature indicates that precision technologies achieve average input savings of 8–20% and yield increases of 2–6%, while reported return on investment (ROI) values typically range between 5% and 15%. Economic viability is strongly dependent on farm size, with most studies identifying profitability above 100–200 ha. Additional benefits include improved management of soil heterogeneity, enhanced nutrient-use efficiency, and reduced excess input application, although adoption remains constrained by high investment costs and technological complexity. Full article

Surface electromyography (sEMG) enables non-invasive measurement of muscle activity for applications such as human–machine interaction, rehabilitation, and prosthesis control. However, high noise levels, inter-subject variability, and the complex nature of muscle activation hinder robust gesture classification. This study proposes a multistream hybrid deep-learning architecture for the FORS-EMG dataset to address these challenges. The model integrates Temporal Convolutional Networks (TCN), depthwise separable convolutions, bidirectional Long Short-Term Memory (LSTM)–Gated Recurrent Unit (GRU) layers, and a Transformer encoder to capture complementary temporal and spectral patterns, and an ArcFace-based classifier to enhance class separability. We evaluate the approach under three protocols: subject-wise, random split without augmentation, and random split with augmentation. In the augmented random-split setting, the model attains 96.4% accuracy, surpassing previously reported values. In the subject-wise setting, accuracy is 74%, revealing limited cross-user generalization. The results demonstrate the method’s high performance and highlight the impact of data-partition strategies for real-world sEMG-based gesture recognition. Full article

Background: Campylobacter jejuni, a leading foodborne pathogen in poultry, relies heavily on iron for survival and colonizes the gastrointestinal tract (GIT). Iron supplementation in poultry diets can inadvertently promote pathogen growth, particularly when excess or poorly absorbed iron accumulates in the lower GIT. Encapsulated iron products, such as SQM^® Iron, offer a controlled-release mechanism that may mitigate this risk by reducing iron availability to microbes. Objective: This study evaluated the effects of free (FeSO₄) versus polysaccharide–iron complex (PIC) on C. jejuni growth under iron-limited conditions, hypothesizing that encapsulated iron would support slower and more limited bacterial proliferation due to delayed iron release. Methods: Growth kinetics of C. jejuni ATCC 700819 were assessed in chelated Mueller–Hinton broth supplemented with three iron concentrations (10, 20, and 50 ppm) of FeSO₄, PIC, or PIC matrix without iron. Optical density was measured every 20 min over 48 h under microaerophilic conditions. Maximum growth rate (µmax) and carrying capacity (K) were derived using non-linear curve modeling. ANOVA evaluated statistical significance with Tukey’s HSD post hoc comparisons. Results: Free iron (FeSO₄) consistently supported the highest µmax and K values across both trials, indicating rapid and robust C. jejuni proliferation. The effect of encapsulated iron was variable: at higher concentrations (50 ppm) it approached FeSO₄ performance, but at lower concentrations (10 ppm) its effect differed markedly between trials, sometimes supporting growth comparable to free iron and sometimes supporting substantially slower growth. The PIC matrix alone did not promote growth. These variable results indicate that the relationship between encapsulated iron and C. jejuni proliferation is complex and concentration-dependent. Conclusions: Free iron consistently promotes robust C. jejuni growth due to immediate bioavailability. The impact of encapsulated iron on C. jejuni proliferation is nuanced and variable, particularly at lower concentrations, suggesting its role in pathogen control is not straightforward and requires further investigation under controlled conditions. Furthermore, in vivo research is warranted to validate its utility in poultry pathogen management strategies. Full article

The increasing burden of dengue represents a growing global public health concern. Among the factors associated with rising dengue incidence, climate change, particularly increasing temperatures, has been frequently highlighted, alongside other environmental, biological, and social determinants. The emergence of dengue in previously non-endemic areas and its sustained increase in incidence have become increasingly common in recent decades. Objective: The aim of this study was to describe national dengue case trends in Mexico from 1990 to 2023 and to assess their association with temperature over the same period using a descriptive, retrospective analysis of epidemiological surveillance and temperature data. Methods: Epidemiological data on confirmed dengue cases and incidence were obtained from the Morbidity Yearbook of the General Directorate of Epidemiology (DGE) of the Mexican Ministry of Health. These data were used to construct epidemic curves and to analyze the geographic distribution of incidence using quartiles. Temperature data were derived from the national annual mean calculated from monthly reports issued by the National Water Commission (CONAGUA). Associations between temperature and dengue cases and incidence were explored over the study period. Results: Temporal analysis revealed a significant increase in both dengue cases and incidence in Mexico, with a positive association with temperature during the same period. Quartile-based geographic analysis showed that state-level classifications remained relatively stable across periods, with several states clustering within or tending toward the group considered endemic. Conclusions: The results of this study show an increase in cases and incidence of dengue over time, as well as a positive association between cases/incidence of dengue in Mexico and the increase in the national average temperature during the study period; however, due to its descriptive and retrospective design, causal inference is not possible. Dengue transmission is inherently multifactorial, and the observed trends likely reflect the combined influence of climatic conditions, historical expansion of transmission cycles, vector establishment, and unmeasured socio-epidemiological factors. The absence of entomological indicators, additional climatic variables, and spatially or seasonally disaggregated analyses limits the ability to capture localized dynamics. Overall, temperature should be interpreted as a contributing factor within a complex system rather than as the sole driver of dengue trends, underscoring the need for integrated surveillance and control strategies in both endemic and non-endemic regions. Full article

Background and Clinical Significance: Neurosarcoidosis (NS) is a rare manifestation of systemic sarcoidosis involving the central nervous system, with highly variable neurological and endocrine presentations. Among these, anterior pituitary dysfunction is particularly uncommon and diagnostically challenging. Case Presentation: We report the case of a 37-year-old woman with a 4-year history of secondary amenorrhoea and an initially suspected pituitary microadenoma, who was ultimately diagnosed with probable NS presenting with multiaxial anterior pituitary insufficiency. Early magnetic resonance imaging (MRI) revealed a small pituitary lesion and isolated pituitary stalk thickening, without other central nervous system abnormalities. Subsequent imaging demonstrated contrast-enhancing lesions involving the meninges and cranial nerves, along with progression of pituitary stalk involvement and loss of the posterior pituitary bright spot. Further evaluation confirmed systemic sarcoidosis. High-dose corticosteroid therapy led to partial clinical and radiological improvement; however, relapse necessitated methotrexate, and persistent pituitary hormone deficiencies required long-term hormonal replacement. Conclusions: This case highlights the diagnostic complexity of NS presenting with isolated endocrine dysfunction and subtle imaging findings. It underscores the need to consider systemic sarcoidosis in patients with unexplained hypopituitarism. Full article

Alcoholic fermentation in winemaking is a complex bioprocess governed by physicochemical parameters such as temperature, density, pH, CO₂ and redox potential, which critically affect yeast metabolism and wine quality. This review provides an integrated analysis of fermentative dynamics and emerging sensorization technologies, highlighting how their combined implementation enables real-time monitoring and advanced control in precision enology. Advances in conventional physicochemical sensors, spectroscopic techniques (NIR/MIR/UV-Vis) and non-conventional devices (e-noses, electronic tongues) integrated into IoT platforms enable continuous data acquisition, overcoming traditional manual sampling limitations. Predictive modeling, including kinetic models, machine learning approaches (e.g., Random Forest, XGBoost) and model predictive control (MPC/NMPC), supports anomaly detection, optimization of enological interventions and energy-efficient thermal management, while virtual sensors based on Kalman filters improve the estimation of non-measurable states (e.g., biomass, ethanol kinetics). Despite current challenges in calibration and interoperability, these innovations foster sustainable and reproducible winemaking under climate variability and pave the way for digital twins and semi-autonomous fermentation systems. Full article

Aiming to improve radar multi-target tracking (MTT) accuracy and association performance in complex scenarios involving dense clutter, missed detections, and maneuvering targets, an improved tracklet generation approach based on the expectation–maximization (EM) framework is proposed in which data association variables and motion model variables are jointly modeled as latent variables. These variables are estimated through iterative updates based on the loopy belief propagation (LBP) algorithm and the interacting multiple model (IMM) filtering and smoothing algorithms to generate high-confidence tracklets. Then, a delayed decision-making strategy based on the multi-hypothesis approach is employed to associate these tracklets into complete target trajectories. The resulting algorithm is named IMM-TrackletMHT. The performance of the IMM-TrackletMHT algorithm is evaluated and compared with several baseline algorithms in simulated scenarios under different clutter rates and detection probabilities. The simulation results demonstrate that the proposed algorithm consistently outperforms the baseline methods in terms of tracking accuracy, exhibits strong robustness to variations in the operating environment, and achieves higher computational efficiency in multi-scan measurement processing, thereby demonstrating the effectiveness and superiority of the proposed tracklet generation approach for maneuvering MTT. Full article

Background/Objectives: Non-invasive hemodynamic monitoring technologies are being developed to support clinical decisions while reducing risks from invasive procedures. Usability evaluation is essential to assess safety and effectiveness before commercial release. This study examined the usability of a novel patch-type ultrasound-based system (CW10) designed for continuous monitoring in perioperative settings. Methods: A summative evaluation was conducted following IEC 62366-1 with 15 anesthesiologists. Potential hazards were identified via the FDA MAUDE database (Code: DQK) to inform test scenarios. Participants were stratified by clinical experience (1–<5, 5–<10, and ≥10 years) to observe potential variations in operation. In a simulated operating room, users performed 9 clinical scenarios (49 tasks). Metrics included task success rates, subjective satisfaction (5-point Likert scale), and the System Usability Scale (SUS). Results: The overall task success rate was 98.2%. No statistically significant differences were observed across groups in performance, subjective ratings, or SUS scores (p > 0.05). The mean SUS score was 78.5, corresponding to a “Good” usability level. While some use errors occurred in tasks like probe orientation, root cause analysis suggested these were likely due to negative transfer from prior device experience rather than interface complexity. Conclusions: The results suggest the system demonstrates acceptable usability and consistent operation across experience levels. Integrated automated features and the patch design may contribute to reducing inter-user variability for continuous monitoring. This study provides usability evidence that may inform the development of similar non-invasive technologies. Full article

Amidst global urbanization and rising psychological stress, urban green spaces are increasingly recognized as critical infrastructure for sustainable urban development and public health. However, the mechanisms by which summer vegetation structure mediates both physiological and psychological restoration, and the interplay between these two dimensions, remain poorly understood. Understanding these mechanisms is essential for designing sustainable, health-promoting urban environments that can support growing urban populations in a warming climate. This study employed a controlled field experiment in Xi’an during summer to examine the effects of five vegetation structure types (Single-Layer Grassland, single-layer woodland, tree–shrub–grass composite woodland, tree–grass composite woodland, and a non-vegetated square) on university students’ physiological (heart rate variability) and psychological (perceived restorativeness and affective states) restoration. Following stress induction, 300 participants engaged with the green spaces through both quiet sitting and walking. The results revealed three key findings: (1) the tree–shrub–grass composite woodland consistently showed the most favorable trends other vegetation types across all psychological restoration dimensions, while also showing favorable trends in physiological recovery, underscoring the importance of structural complexity for restorative quality; (2) walking significantly enhanced physiological recovery compared to seated observation across all settings, confirming the role of physical activity as a critical activator of green space benefits; (3) correlation analysis identified a specific cross-system association: the R-R interval recovery value showed a weak but significant correlation with positive affect (PA) scores, suggesting that physiological calmness and positive emotional experience are linked, yet their weak coupling under short-term exposure indicates they may operate as parallel processes with distinct temporal dynamics. These findings indicate that the restorative potential of summer green spaces emerges from an integrated framework combining vegetation complexity and activity support. We propose that future sustainable landscape design should prioritize multi-layered vegetation structures as nature-based solutions that simultaneously enhance human well-being and urban resilience. These findings provide empirical evidence for integrating health-promoting green infrastructure into sustainable urban planning frameworks, supporting multiple Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Full article

Baroclinic instability is a fundamental mechanism of midlatitude atmospheric variability, and the Eady model remains one of its most useful idealized representations. In this work, we revisit the Eady configuration from the viewpoint of solution-space geometry rather than the classical normal-mode/growth-rate analysis. Starting from the reduced Eady vertical-structure equation, we show that the ratio of two independent solutions satisfies a Schwarzian-type relation that is invariant under homographic transformations, which naturally leads to an SL(2R) projective symmetry of the solution family. On this basis, we introduce a complex amplitude representation and reformulate coherence in terms of phase–amplitude synchronization constrained by projective invariants. Using Riccati-type constructions along geodesic parametrizations, the reduced dynamics are connected to a Stoler-type transform. Numerical exploration of the reduced model shows a systematic dependence on the control parameter $\omega$: small $\omega$ is associated with simple oscillatory or burst-like behavior, intermediate $\omega$ with period-doubling-like behavior, and large $\omega$ with strongly modulated dynamics and more intricate reconstructed attractors. These results should be interpreted as properties of the reduced symmetry-based model, and they suggest that projective invariants may provide a useful framework for classifying organization regimes in Eady-type disturbances, complementary to classical growth-rate analyses. Full article

Background: Neonatal and infant aortic arch reconstruction remains a high-risk cardiovascular procedure requiring effective cerebral and myocardial protection. Variability in perfusion strategies may influence early hemodynamic stability and postoperative recovery. This study aimed to evaluate the early and short-term cardiovascular outcomes of a standardized beating-heart aortic arch reconstruction strategy incorporating simultaneous antegrade selective cerebral and continuous coronary perfusion. Methods: In this retrospective single-center cohort study, 31 consecutive neonates and infants undergoing aortic arch reconstruction between November 2022 and December 2025 were analyzed. A standardized surgical protocol was applied, consisting of extensive ductal tissue resection, interdigitating posterior end-to-end anastomosis, anterior autologous pericardial patch augmentation, and moderate hypothermic antegrade selective cerebral perfusion combined with continuous coronary perfusion via innominate artery cannulation. Early postoperative outcomes and short-term echocardiographic follow-up results were assessed. Results: The cohort included 31 patients, 22.6% of whom had complex associated cardiac anomalies requiring concomitant procedures. Median cardiopulmonary bypass and aortic cross-clamp times were 119 and 64 min, respectively. There was no in-hospital mortality. Major complications were infrequent, and median intensive care unit stay was 5 days. During a median follow-up of 6.8 months, one patient (3.2%) developed recoarctation requiring reintervention. No late mortality was observed. Conclusions: A fully standardized beating-heart aortic arch reconstruction strategy incorporating simultaneous cerebral and coronary perfusion demonstrated favorable early cardiovascular and short-term outcomes, even in anatomically complex cases. Preservation of continuous coronary perfusion may be associated with improved myocardial stability and early postoperative recovery; however, these findings should be interpreted as observational and hypothesis-generating given the absence of a control group. Larger multicenter studies with longer follow-up are warranted to confirm these findings. Full article

Chickpea (Cicer arietinum L.) is a globally important legume crop whose grain yield is strongly influenced by environmental and agronomic variability. This study aimed to predict chickpea grain yield using artificial neural networks (ANNs) and to identify key traits associated with yield formation across different genotypes under semi-arid conditions. The dataset consisted of 96 chickpea genotypes evaluated over two growing seasons (2022–2023) in Sivas, Türkiye. The results demonstrated that reproductive traits, particularly seed weight per plant, number of pods per plant, and number of seeds per plant, were the most influential factors determining grain yield. Environmental variability also contributed significantly to yield prediction, highlighting the importance of genotype–environment interactions. The developed ANN model showed high predictive accuracy, indicating its robustness in capturing complex relationships among yield-related traits. Beyond prediction, the model provides biologically meaningful insights into trait prioritization, supporting its application in chickpea breeding programs. Overall, the findings suggest that ANN-based approaches can serve as effective decision-support tools in precision agriculture by enabling accurate yield estimation, facilitating the selection of high-performing genotypes, and identifying key breeding traits for sustainable crop improvement. Full article