Search Results (7,030)

Background and Objectives: Stroke remains a major contributor to global morbidity and mortality, with substantial geographic variation in incidence and outcomes. Although declining trends in stroke incidence and mortality have been documented in several Western European populations, countries in Eastern Europe have historically experienced a disproportionately high cardiovascular disease burden. Comprehensive long-term evaluations assessing simultaneous trends in stroke attack rates, mortality, and case-fatality in Lithuania are limited. This study aimed to investigate 24-year trends (2000–2023) in stroke epidemiology among working-age residents of Kaunas city. Materials and Methods: Data were derived from the Kaunas population-based stroke registry and included individuals aged 25–64 years. Age-standardized attack rates, mortality rates, and case-fatality rates per 100,000 population were calculated using the World Health Organization standard population. Temporal trends were assessed using Joinpoint regression analysis to estimate annual percentage changes (APCs) with corresponding 95% confidence intervals (CIs). Analyses were stratified by sex, age group (25–54 and 55–64 years), and stroke subtype (ischemic and hemorrhagic). Results: During 2000–2023, overall stroke attack rates declined significantly in both sexes, with a more pronounced reduction observed among females. Stroke mortality decreased significantly among females over the entire study period, whereas no significant overall change was observed among males, largely due to increases during 2010–2021 that attenuated earlier and subsequent improvements. Case-fatality rates demonstrated no significant overall long-term trend in either sex but exhibited marked temporal variability, including significant increases during 2010–2021 followed by substantial declines after 2021. Age-stratified analyses confirmed significant reductions in attack rates across both age groups. Ischemic stroke incidence declined significantly in both sexes, while hemorrhagic stroke mortality decreased significantly among males and females. The period 2021–2023 was characterized by pronounced reductions in mortality and case-fatality across multiple subgroups. Conclusions: Over the past two decades, the stroke burden among working-age residents of Kaunas has declined substantially, particularly among females. Despite period-specific deteriorations, recent improvements underscore the impact of advances in stroke prevention and acute care. Sustained risk factor control and continued healthcare system development remain essential to maintain favourable trends. Full article

Background: Cemented and cementless fixation techniques in total hip arthroplasty (THA) each present distinct biomechanical properties and perioperative risk profiles. While cementless fixation has gained increasing popularity, large-scale nationally representative comparisons of perioperative outcomes between cemented and cementless elective THA remain limited. This study aimed to compare complication rates, healthcare utilization, and temporal trends between cemented and cementless elective THA using the National Inpatient Sample. Methods: A retrospective cohort study was conducted using the National Inpatient Sample database from 2016 to 2021. Adult patients undergoing elective primary total hip arthroplasty were identified using ICD-10-PCS codes and categorized into cemented and cementless fixation groups. Patient demographics, comorbidities, indications, postoperative complications, length of stay, hospital charges, and in-hospital mortality were compared. Multivariate logistic regression analysis was performed to evaluate the independent association between fixation type and postoperative complications while adjusting for demographic, clinical, and hospital-level variables. Results: A total of 81,668 elective THAs were identified, including 40,290 cemented (49.33%) and 41,378 cementless (50.67%) procedures. Cemented THA was associated with a shorter length of stay (2.09 ± 1.88 vs. 2.26 ± 2.47 days, p < 0.001) and lower total hospital charges ($65,584.53 ± 48,797.21 vs. $72,186.84 ± 49,860.20, p < 0.001). Unadjusted analyses demonstrated higher rates of acute kidney injury and sepsis in the cementless group. After multivariate adjustment, cemented fixation was associated with lower odds of acute kidney injury (OR 0.87, 95% CI 0.79–0.96, p = 0.004). However, cemented THA was associated with higher odds of postoperative delirium (OR 1.20, 95% CI 1.02–1.42, p = 0.030), blood transfusion (OR 1.27, 95% CI 1.17–1.37, p < 0.001), and periprosthetic fracture (OR 1.32, 95% CI 1.02–1.71, p = 0.035). Rates of myocardial infarction, pneumonia, venous thromboembolism, urinary tract infection, and in-hospital mortality were similar between groups. Temporal analysis demonstrated comparable utilization trends, with a decline in elective procedures during 2020–2021. Conclusions: In this nationwide analysis, cemented total hip arthroplasty was associated with lower risk of acute kidney injury, shorter length of stay, and lower hospital charges, but higher odds of postoperative delirium, blood transfusion, and periprosthetic fracture compared with cementless fixation. These findings highlight distinct perioperative risk profiles between fixation strategies and may assist surgeons in individualized decision-making for elective total hip arthroplasty. Full article

Drought in Angola is a recurrent and cyclical natural phenomenon that poses significant environmental, economic, and social challenges, affecting water resources, agriculture, ecosystems, livestock, and vulnerable communities. This study investigates the temporal evolution and spatial behavior of drought in the provinces of Cunene, Huila, and Namibe over the period 1980–2024. Drought conditions were assessed using the Standardized Precipitation Index (SPI) and the Standard Precipitation–Evapotranspiration Index (SPEI) at multiple time scales. Trends were evaluated using the Modified Mann–Kendall test and Sen’s slope estimator, while drought intensity was analyzed using run theory. The results reveal a clear intensification of drought conditions in the last decade, characterized by an increase in frequency and intensity, particularly after 2010. Extreme drought events were identified in the early 1980s, the mid-1990s, and more recently in 2019 and 2021. Despite some regional variability, the three provinces exhibit consistent temporal patterns, with drought events generally occurring simultaneously over the study period. These findings highlight the increasing pressure on water and environmental systems and underscore the need for improved drought monitoring and forecasting approaches to support more effective adaptation and decision-making. Full article

This study evaluates the robustness and time consistency of GNSS coordinate solutions obtained from a suite of scientific and legacy commercial software packages, with the aim of assessing their suitability for rapid preliminary framing of institutional geodetic networks. The analysis includes Pinnacle 1.0, Topcon Tools v.8, TGOffice 1.63, Leica Geo Office Combined 7.0, NDA Lite, and the scientific-grade NDA Professional, together with PPP solutions generated through the CSRS service. A one-year dataset from the UNIPA GNSS CORS network was processed to derive monthly coordinate estimates, which were compared in terms of geocentric (ΔXYZ), horizontal (ΔEN), and vertical (ΔUp) deviations, as well as temporal behavior and statistical significance (Welch’s t-test). The results show that NDA Professional provides the most stable and time-consistent solutions, with mean horizontal and vertical dispersions typically below 2–3 mm. Topcon Tools and Pinnacle also exhibit good performance, with average ΔEN values of approximately 3–4 mm and ΔH values generally within 5–7 mm. In contrast, Leica LGO and NDA Lite display larger variability, particularly in the vertical component, where monthly deviations may exceed 10 mm. The CSRS solution, due to its PPP-based intrinsic nature, reveals a statistically significant temporal trend (on the order of 5–8 mm/year), which prevents direct comparison with static network solutions; however, once detrended, its dispersion becomes comparable to the best-performing static software, with ΔEN and ΔUp values of 2–4 mm. Full article

The occurrence of marine heatwaves (MHWs) and phytoplankton blooms is accelerating under climate change, yet the frequency and drivers of their compound co-occurrence remain poorly understood. Using coastal-optimized satellite observations from 2003–2020, we mapped global compound MHW–phytoplankton bloom (MHW-PB) events across coastal large marine ecosystems and quantified their spatiotemporal trends and environmental predictors. Compound events are increasing at 4.8% yr⁻¹, driven primarily by a 6.5% yr⁻¹ rise in MHW frequency; a temporal shuffle test confirms this trend falls below random co-occurrence expectation, indicating biological suppression actively constrains compound event growth. The compound independence factor (CIF) reveals latitudinal heterogeneity: low-latitude upwelling systems show MHW–PB mutual exclusivity, while high-latitude and eutrophic coastal regions show positive co-occurrence tendency. Interpretable machine learning further shows that nutrient availability dominates bloom responses at low latitudes whereas light dominates at high latitudes, with MHW intensity exhibiting nutrient-dependent non-linear associations with bloom probability. Paradoxically, compound frequency accelerates nearly twice as fast in low latitudes (6.1% yr⁻¹) as in high latitudes (3.5% yr⁻¹), driven by rapid tropical MHW acceleration. These diverging regimes signal dual ecological risks: trophic mismatches in upwelling systems and escalating hypoxia and harmful algal bloom hazards in eutrophic coastal waters. Full article

Background: Vancomycin-resistant Enterococcus (VRE) bacteremia represents a major therapeutic and epidemiological challenge, particularly in regions with high antimicrobial resistance rates such as Southern Europe. Longitudinal local data are essential to guide infection control and antimicrobial stewardship strategies. This study aimed to evaluate temporal trends in incidence, management, and mortality of VRE bacteremia in a tertiary care center in Greece over a six-year period, including comparison before and after the coronavirus disease 2019 (COVID-19) pandemic. Methods: This retrospective observational study included adult patients with VRE bacteremia at the University Hospital of Heraklion, Greece, from 2018 to 2023. Demographic and clinical data, such as the Pitt Bacteremia Index (PBI), as well as microbiological, and treatment data were collected from patient records. Incidence was calculated per 10,000 patient-days. Comparisons were performed between survivors and non-survivors and between pre- and post-COVID-19 eras. Multivariate regression analysis was used to identify predictors of in-hospital mortality. Results: A total of 96 patients were included (mean age 68.6 ± 14.5 years; 56.3% male). The incidence of VRE bacteremia increased more than five-fold during the study period, from 0.242 cases per 10,000 patient-days in 2018 to a peak of 1.344 per 10,000 patient-days in 2022, remaining elevated in 2023 (1.001 per 10,000 patient-days). The overall in-hospital mortality was 54.2%. Non-survivors had significantly higher PBI scores compared to survivors (median 2.5 vs. 0, p = 0.005). In the multivariate analysis, higher PBI was independently associated with in-hospital mortality [odds ratio: 1.449 (95% confidence intervals: 1.166–1.801)]. Appropriate empirical therapy was administered in 41.7% of cases and was not significantly associated with survival. Post-COVID-19 patients were older (69.9 vs. 61.4 years, p = 0.0365), and antimicrobial regimens were more frequently adjusted according to susceptibility testing (55.7% vs. 18.2%, p = 0.0141), but mortality did not significantly differ between periods. Conclusion: VRE bacteremia incidence increased dramatically over the six-year study period in our tertiary center, with persistently high mortality exceeding 50%. Severity of illness at the diagnosis of bacteremia, as measured by the PBI, was an independent predictor of in-hospital mortality. Strengthened infection prevention measures, optimized antimicrobial stewardship, and early aggressive management are urgently needed to mitigate the growing burden of VRE bacteremia. Full article

Background/Objectives: Atrial fibrillation (AF) is highly prevalent among older adults and is associated with increased thromboembolic risk. Although anticoagulant therapy (AC) is strongly recommended, its use in elderly and multimorbid patients remains suboptimal. This study aimed to describe long-term trends in AC prescribing patterns among hospitalized older patients with AF. Methods: We conducted a retrospective observational analysis using data from the Italian REPOSI registry, including patients aged ≥65 years hospitalized with AF between 2010 and 2023. AC at admission and discharge was analyzed, including vitamin K antagonists (VKAs), direct oral anticoagulants (DOACs), and antiplatelet agents. Temporal trends, admission-to-discharge treatment changes, and patient characteristics associated with therapy modification were assessed descriptively. Results: The study included 2061 AF patients, characterized by multimorbidity and high thromboembolic risk. A marked shift from VKAs to DOACs was observed over time. However, a substantial proportion of cases remained without AC or received only antiplatelet therapy at both admission and discharge, with untreated individuals being generally older and more clinically complex. DOAC use increased steadily but showed a slight decline at discharge after 2020. Clinical variables available in the registry only partially explained AC changes during hospitalization. Conclusions: Despite increasing adoption of DOACs, AC underuse remains frequent among elderly hospitalized patients with AF. These real-world data highlight persistent challenges in AC management in complex older adults and underscore the need for more comprehensive clinical information and data-driven tools to support individualized therapeutic decision-making. Full article

Camera rotation estimation is a key component in video stabilization and motion analysis. In many practical scenarios, inertial measurements are unavailable or temporally unreliable, while classical geometric pipelines degrade under blur, low texture, and low illumination. This paper investigates whether substantially downsampled optical flow can retain sufficient structure for accurate frame-to-frame rotation regression. We present VisualRNet, a lightweight rotation-specific visual regression framework trained with cross-modal IMU supervision. Our design uses coordinate-aware feature encoding, depthwise separable convolutions, lightweight attention, and a compact 6D rotation head to model the spatial structure of rotational flow fields. On Deep-FVS, VisualRNet achieves a mean rotation error of 0.3151${}^{\circ }$ on the test set. The VisualRNet regression head contains 7.7 K parameters, 0.002 GFLOPs, and runs at 729 FPS, while the full pipeline with the FastFlowNetv2 frontend contains 1.374 M parameters, 7.194 GFLOPs, and runs at approximately 113 FPS. A cross-camera adaptation experiment on TUM VI further indicates that the learned motion representation can be aligned to a new camera system with limited calibration data. These results support low-resolution optical flow as a practical input for visual rotation estimation and suggest particular value in stabilization-oriented and cost-sensitive applications where approximate rotational trend matters more than full scene geometry. Full article

Atmospheric heatwaves (AHWs) and marine heatwaves (MHWs) are intensifying under climate change, yet their coupled behavior in the Red Sea remains insufficiently quantified. This study investigates the spatial and temporal characteristics of AHWs, MHWs, and their concurrent occurrence across the Red Sea from 1990 to 2024 using ERA5 surface air temperature (SAT) and NOAA OISST v2.1 satellite-derived sea surface temperature (SST). Remote-sensing daily satellite-derived Level-4 (L4) OISST products were used in this study to enable spatially complete and temporally consistent detection of MHWs in this narrow, semi-enclosed basin despite contamination and coastal sampling constraints. Both SAT and SST exhibit statistically significant warming trends (p < 0.05), with basin mean increases of 0.40 ± 0.07 °C/decade and 0.31 ± 0.05 °C/decade, respectively. The strongest warming was observed in the central and northern Red Sea. This warming is accompanied by significant increases in the frequency and duration of AHWs, MHWs, and their concurrent AHW-MHW events, particularly after 2010, indicating a shift toward more frequent heatwave conditions. AHWs occur more frequently than MHWs across the Red Sea, whereas MHWs exhibit long duration, particularly in the northern Red Sea, where annual durations exceed 45–50 days/year. Concurrent AHW-MHW events account for about 66% of MHWs in the Red Sea, and their characteristics show a significant increasing trend across the entire basin. These findings identify the Red Sea as a regional hotspot of increasing concurrent heatwave events and highlight the importance of satellite-based monitoring for assessing evolving climate risks in semi-enclosed basins. Full article

As a novel tool for predicting stock trends, hypergraphs are used to effectively represent high-order relationships among stocks, capturing symmetric dependencies inherent in market interactions. However, the instability of hyperedges limits their ability to capture dynamic stock changes, and existing methods neglect the influence of time decay on feature importance. To address these challenges, a hybrid hypergraph–dynamic graph attention network based on temporal decay attention and conditional aggregation for stock trend prediction, namely HDGAN, is developed. Specifically, we utilize dynamic graphs to capture the dynamic relationships among stocks, which mitigates the instability of the hyperedge structure in dynamic markets. A temporal decay attention mechanism is designed to identify important feature points in the evolution of stock prices, and then a conditional aggregation method is proposed to aggregate information from different pathways. Extensive experiments on A-share, NASDAQ, and NYSE datasets demonstrate HDGAN outperforms other state-of-the-art methods in stock trend prediction and investment return. Full article

Background and Objectives: The epidemiological characteristics of Candida species have changed worldwide, with an increasing number of reports on co-infections with non-albicans Candida species (NACs) and multidrug-resistant bacteria. A longer length of hospital stay, more severely ill patients, and empirical antimicrobial use in intensive care units (ICUs) increased the prevalence of Candida healthcare-associated infections (HAIs). If the diagnosis or treatment of invasive candidiasis is delayed, the morbidity and mortality of patients will significantly increase. Materials and Methods: We conducted a nationwide surveillance study to analyze data on HAIs in the ICUs of medical centers and regional hospitals between 2018 and 2023. We assessed the temporal trends of Candida species (including Candida albicans and NACs) across all HAIs, bloodstream infections (BSIs), and urinary tract infections (UTIs), and simultaneously assessed the corresponding trends of Enterococcus faecium (Efm). A linear trend for the proportions of microorganisms from 2018 to 2023 was noted according to the Mantel–Haenszel chi-square test. Spearman’s rank correlation coefficients were used to analyze the correlations between pathogen proportions, systemic antimicrobial agent consumption, and length of ICU stay. Results: The overall proportion of all Candida species in HAIs in the ICUs increased significantly from 15.13% to 16.74% (p < 0.001); this increase was driven mainly by NACs (increasing from 6.84% to 7.91%, p < 0.001) from 2018 to 2023. The proportion of Efm increased significantly, from 7.7% to 11.11% (p < 0.001). The proportions of all Candida species significantly increased in UTIs (from 24.63% to 28.13%, p < 0.001), especially NACs, while the proportion of Efm also increased significantly in UTIs (from 9.47% to 15.32%, p < 0.001). With respect to the UTIs, the proportion of all the Candida species, C.albicans, and NACs were positively correlated with the amount of systemic antibiotics used. A longer hospital stay was strongly correlated with all Candida HAIs and UTIs, especially NACs. Significantly ecological associations between all the Candida strains and Efm were observed for UTIs. Conclusions: This study revealed that a persistent expansion of NAC infections was associated with increased Efm infections and rising antibiotic consumption. The changes in the proportions of different Candida species in UTIs were most pronounced. These findings support an ecological model in which antibiotic stress and chronic critical illness contribute to the expansion of fungal–bacterial co-infections in the ICU setting and underscore the need for integrated antibiotic management and multi-infection surveillance. Full article

Background: Plantar fasciitis is a leading cause of heel pain, affecting approximately 10% of the population. Despite its prevalence, treatments may result in symptom recurrence and chronicity, which can significantly increase patient dissatisfaction. Google Trends provides insights into public interest through search volume analysis. This study examines global and USA trends in plantar fasciitis, focusing on temporal, seasonal, and income-based variations. Methods: Google Trends data for “Plantar Fasciitis” (2004–2024) were analyzed for both global and USA search trends. Monthly and seasonal search volumes were grouped by time and location. Regression and post hoc tests were conducted to identify significant patterns. Comparisons were made between high- and low-income states in the USA. Results: Public interest in plantar fasciitis increased significantly over time, both globally (R² = 0.871, p < 0.001) and in the USA (R² = 0.854, p < 0.001). Interest peaked in summer and declined in winter, with seasonal differences significant worldwide (p < 0.05). Monthly variations were significant only in the USA. No significant difference was found between high- and low-income states (p > 0.05). Conclusions: Interest in plantar fasciitis has grown steadily, reflecting its prevalence and impact. The findings emphasize the need for accessible, high-quality information to address public demand. These insights can guide healthcare professionals and policymakers in developing targeted resources. Full article

Railways constitute a core component of China’s national comprehensive transportation network, and their spatial organization and temporal accessibility jointly shape transport integration and system efficiency. Identifying their evolution from the dual perspectives of spatial expansion and time compression is therefore of both theoretical and practical significance. Drawing on fractal theory, this study examines the structural characteristics, evolutionary trends, and driving factors of railway networks in China’s five major urban systems from 2014 to 2024 from a “space–time” dual perspective. The results show that railway networks exhibit a staged pattern of “spatial filling preceding temporal correlation”, with a lag of approximately 1–8 years—about 1 year in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), 5 years in the Middle Yangtze River (MYR) region and Beijing–Tianjin–Hebei (BTH), and up to 8 years in the Chengdu–Chongqing (CC) region. In addition, clear regional differences are observed: the Yangtze River Delta (YRD) is polycentric, with the greatest potential, projected to continue rapid spatial growth until 2027 and to remain in a fast-growth phase of temporal correlation; GBA is highly coordinated; BTH is developed but characterized by dual-core agglomeration; CC grows rapidly with lagging functionality; and MYR is corridor-dependent with limited potential. These findings indicate that network functionality does not emerge synchronously with infrastructure expansion, but depends on subsequent improvements in operational organization and service capacity. Compared with single-scale-based indicators, the “spatial distribution–temporal correlation” framework more effectively captures network performance and provides quantitative support for transport optimization and coordinated regional development. Full article

3D multi-object tracking (MOT) for autonomous driving remains challenging due to frequent identity switches in crowded scenes, trajectory fragmentation during occlusions, and the difficulty of adapting association strategies to varying scene complexities. While existing methods rely on fixed geometric or appearance-based associations, they struggle to handle ambiguous cases and detection failures. We present an adaptive multi-level 3D MOT framework that achieves robust tracking through three key innovations: (1) multi-granularity temporal modeling that captures both fine-grained short-term motion and coarse long-term trends via dual-scale spatio-temporal attention, enabling accurate motion prediction across different object dynamics; (2) Transformer-based Appearance Association that employs cross-attention to model global inter-object relationships, resolving ambiguous associations in crowded scenarios where geometric cues alone fail; and (3) scene-adaptive learned thresholds that automatically adjust association strictness based on object density, motion complexity, and occlusion levels, avoiding the one-size-fits-all limitations of fixed thresholds. Our hierarchical four-level tracking strategy progressively handles cases from easy geometric matching (Level 1) to complex interval-frame recovery (Level 4), with SOT-based virtual detection generation bridging detector failures. Extensive experiments on the nuScenes benchmark demonstrate state-of-the-art performance. Full article

Nowadays, educational software across all learning levels is increasingly enhanced with Artificial Intelligence (AI), primarily through content generation or post-session learning analytics. However, most existing systems remain weakly connected to learners’ real-time affective states and rarely exploit emotional information as a direct control signal for instructional adaptation. In this work, we propose a proof-of-concept closed-loop affect-aware educational adaptation framework that integrates real-time facial emotion recognition into a dynamic learning control system. The proposed approach is built upon a dual-model ensemble architecture, combining a transformer-based model (CAGE) and a CNN-based model (DDAMFN++) trained on large-scale in-the-wild datasets. To bridge heterogeneous emotion representations, we introduce a probabilistic fusion strategy that aligns continuous valence–arousal predictions with discrete emotion classification via a Gaussian Mixture Model (GMM), enabling unified emotion inference in real time. Based on the fused emotional state, a temporal aggregation mechanism is applied to capture sustained affective trends rather than transient expressions. These aggregated signals are then mapped to instructional decisions through an emotion-driven adaptive control policy, which adjusts activity difficulty using an Average Emotion Score (AES). This establishes a fully automated closed-loop adaptation cycle, where detected learner affect directly influences the learning environment without requiring explicit user input or post-session questionnaires. The framework is integrated into an open-source educational platform (eduActiv8) to demonstrate feasibility and system-level behavior. Results from alpha-level validation show that the system can continuously monitor learner affect, generate interpretable emotional analytics, and dynamically adjust task difficulty in real time, while reducing user interaction overhead. This study contributes a modular architecture for affect-aware educational systems by combining real-time ensemble emotion recognition, probabilistic fusion of heterogeneous outputs, and closed-loop instructional adaptation. The proposed framework provides a foundation for future research in scalable, emotion-driven intelligent tutoring and adaptive learning environments. Full article