Search Results (112)

Background/Objective: Postural stability and motor coordination require precise regulation of agonist and antagonist muscle activities. Jaw clenching modulates neuromuscular control during static and reactive postural tasks. However, its effects on dynamic voluntary movement remain unclear. This pilot study aimed to investigate the effects of jaw clenching on muscle activity and kinematics during repetitive single-leg sit-to-stand task performance. Methods: Eleven healthy adults (age: 21.2 ± 0.4 years; 6 males and 5 females; height: 167.9 ± 9.6 cm; body weight: 59.7 ± 8.1 kg) performed repetitive single-leg sit-to-stand tasks for 30 s under jaw-clenching and control conditions. Electromyography (EMG) signals from eight muscles and kinematic data from 16 inertial measurement unit sensors were analyzed, focusing on the seat-off phase. Results: Jaw clenching resulted in a significantly lower success rate than the control condition (success rate: 0.96 ± 0.13 vs. 0.78 ± 0.29, p = 0.047). Under the jaw clenching condition, failed trials exhibited higher medial gastrocnemius and masseter EMG activity (p < 0.001), lower erector spinae longus EMG activity (p < 0.001), and altered kinematics, including increased trunk yaw and roll angles (p < 0.001). Jaw clenching increased the coactivation of the gastrocnemius and tibialis anterior muscles (p < 0.001), disrupting the reciprocal muscle patterns critical for task performance. Conclusions: These findings suggest that jaw clenching may reduce task performance by altering neuromuscular coordination during dynamic postural tasks. Full article

The persistent challenge of designing digital interfaces that minimize users’ perceived waiting time remains critical for user satisfaction and conversion rates. This research integrates Attentional Gate Theory to investigate how loading animation type (static vs. dynamic) influences perceived waiting duration through temporal attention focus, and examines moderating roles of task involvement and browsing goal orientation. Across four online experiments—Study 1 (N = 198, MTurk) tested the main effect of animation type; Study 2 (N = 411, Prolific) validated full mediation via temporal attention focus using PROCESS analysis; Study 3 (2 × 2 design, N = 400, Prolific) examined task involvement as a moderator; and Study 4 (2 × 2 design, N = 400, Prolific) explored hedonic versus utilitarian browsing goals—the dynamic animation consistently shortened perceived waiting time relative to static displays. Mediation analyses confirmed that reduced temporal attention focus fully explains this effect, which is amplified under low task involvement and hedonic browsing but attenuated when involvement is high or goals are utilitarian. Theoretically, this work extends Attentional Gate Theory to user experience design by uncovering cognitive processes underlying time perception during waits. Managerially, it offers evidence-based recommendations for tailoring loading animations to user context, ultimately enhancing satisfaction and reducing abandonment. Full article

Hemodynamics significantly impact the biology of endothelial cells (ECs) lining the blood vessels. ECs are exposed to various hemodynamic forces, particularly frictional shear stress from flowing blood. While physiological flows are critical for the normal functioning of ECs, abnormal flow dynamics, known as disturbed flows, may trigger endothelial dysfunction leading to atherosclerosis and other vascular conditions. Such flows can occur due to sudden geometrical variations and vascular abnormalities in the cardiovascular system. In the current study, a microfluidic system was used to investigate the impact of different flow conditions (i.e, normal vs. disturbed) on ECs in vitro. We particularly explored the relationship between specific flow patterns and cellular pathways linked to oxidative stress and inflammation related to atherosclerosis. Here, we utilized a 2D cell culture perfusion system featuring an immortalized human vascular endothelial cell line (EA.hy926) connected to a modified peristaltic pump system to generate either steady laminar flows, representing healthy conditions, or disturbed oscillatory flows, representing diseased conditions. EA.hy926 were exposed to an oscillatory flow shear stress of 0.5 dynes/cm² or a laminar flow shear stress of 2 dynes/cm² up to 24 h. Following flow exposure, cells were harvested from the perfusion chamber for quantitative PCR analysis of gene expression. Reactive oxygen species (ROS) generation under various shear stress conditions was also measured using DCFDA/H2DCFDA fluorescent assays. Under oscillatory shear stress flow conditions (0.5 dynes/cm²), EA.hy926 ECs showed a 3.5-fold increase in the transcription factor nuclear factor (NFκ-B) and a remarkable 28.6-fold increase in cyclooxygenase-2 (COX-2) mRNA expression, which are both proinflammatory markers, compared to static culture. Transforming growth factor-beta (TGFβ) mRNA expression was downregulated in oscillatory and laminar flow conditions compared to the static culture. Apoptosis marker transcription factor Jun (C-Jun) mRNA expression increased in both flow conditions. Apoptosis marker C/EBP homologous protein (CHOP) mRNA levels increased significantly in oscillatory flow, with no difference in laminar flow. Endothelial nitric oxide synthase (eNOS) mRNA expression was significantly decreased in cells exposed to oscillatory flow, whereas there was no change in laminar flow. Endothelin-1 (ET-1) mRNA expression levels dropped significantly by 0.5- and 0.8-fold in cells exposed to oscillatory and laminar flow, respectively. ECs subjected to oscillatory flow exhibited a significant increase in ROS at both 4 and 24 h compared to the control and laminar flow. Laminar flow-treated cells exhibited a ROS generation pattern similar to that of static culture, but at a significantly lower level. Overall, by exposing ECs to disturbed and normal flows with varying shear stresses, significant changes in gene expression related to inflammation, endothelial function, and oxidative stress were observed. In this study, we present a practical, optimized system as an in vitro model that can be employed to investigate flow-associated diseases, such as atherosclerosis and aortic aneurysm, thereby supporting the understanding of the underlying molecular mechanisms. Full article

Background/Objectives: Inflammation plays a key role in the pathophysiology of acute myocardial infarction (AMI). Yet static measures of C-reactive protein (CRP) provide limited prognostic information. CRP velocity (CRPv), which reflects the rate of CRP rise within the first 24 h, may better depict the dynamic inflammatory response. To investigate the prognostic role of CRPv in patients presenting with a first AMI. Methods: Consecutive patients presenting with first AMI were enrolled. CRPv was calculated as the difference between CRP at admission and after 24 ± 8 h, divided by time. A prognostic CRPv cut-off was derived from spline curve analysis to dichotomize the population. Patients were followed up for the primary composite endpoint of cardiovascular death, non-fatal AMI, and hospitalization for heart failure. Results: Among 604 patients, 189 (31.3%) had CRPv ≥ 1.36 mg/L/h and 415 (68.7%) had CRPv < 1.36 mg/L/h. Higher hs-cTnT (adjusted odds ratio [aOR] 2.552, 95% CI, 1.520–4.286; p < 0.001) and NT-proBNP (aOR 2.229, 95% CI, 1.241–4.002; p = 0.007) were independently associated with CRPv ≥ 1.36 mg/L/h. At a median follow-up of 13.8 months, 115 patients (19.0%) reached the primary composite endpoint. High CRPv patients had significantly lower event-free survival rate than low CRPv patients (66.7% vs. 85.5%, log-rank p < 0.001). CRPv independently predicted the primary composite endpoint [adjusted hazard ratio 1.226, 95% CI 1.102–1.364, p < 0.001]. Adding CRPv on top of clinical, echocardiographic, and biochemical risk factors significantly improved model discrimination (p < 0.001), whereas single CRP on admission (p = 0.947) or CRP 24 ± 8 h from admission (p = 0.064) did not. Conclusions: CRPv appears to be a robust predictor of adverse outcomes in first AMI patients, offering incremental prognostic value beyond established clinical and biomarker indices. Its feasibility and low cost support its integration into early clinical risk stratification. Full article

The Strait of Malacca faces persistent maritime safety challenges due to high vessel density and complex navigational conditions. Current risk assessment methods often lean towards treating static accident analysis and dynamic traffic modeling separately, although some nascent hybrid approaches exist. However, these hybrids frequently lack the capacity for comprehensive, real-time factor integration. This study proposes an integrated framework coupling accident hotspot identification with vessel traffic network analysis. The framework combines trajectory clustering using improved DBSCAN with directional filters, Kernel Density Estimation (KDE) for accident hotspots, and Fuzzy Analytic Hierarchy Process (FAHP) for multi-factor risk evaluation, acknowledging its subjective and region-specific nature. The model was trained and tuned exclusively on the 2023 dataset (47 incidents), reserving the 2024 incidents (24 incidents) exclusively for independent, zero-information-leakage validation. Results demonstrate superior performance: Area Under the ROC Curve (AUC) improved by 0.14 (0.78 vs. 0.64; +22% relative to KDE-only), and Precision–Recall AUC (PR-AUC) improved by 0.16 (0.65 vs. 0.49); both p < 0.001. Crucially, all model tuning and parameter finalization (including DBSCAN/Fréchet, FAHP weights, and adaptive thresholds) relied solely on 2023 data, with the 2024 incidents reserved exclusively for independent temporal validation. The model captures 75.2% of reported incidents within 20% of the study area. Cross-validation confirms stability across all folds. The framework reveals accidents concentrate at network bottlenecks where traffic centrality exceeds 0.15 and accident density surpasses 0.6. Model-based associations suggest amplification through three pathways: environmental-mediated (34%), traffic convergence (34%), and historical persistence (23%). The integrated approach enables identification of both where and why maritime accidents cluster, providing practical applications for vessel traffic services, risk-aware navigation, and evidence-based safety regulation in congested waterways. Full article

Skin compatibility is a common issue and can often be worsened by certain ingredients in cosmetics. This is why developing well-balanced and -tolerated formulas is now an essential challenge. In this work we developed a cream rich in antioxidant, soothing, and moisturizing agents complying with concentration limits for sensitive skin. An initial optimization was carried out, and the best-performing formula was fully characterized to test its rheological properties under static or dynamic conditions and product safety. The formulation proved to be highly stable even under thermal stress, as shown by Turbiscan Lab analyses, which reported backscattering values ±2. Rheological tests also indicated a solid-like behavior with reduced viscosity at skin temperature of 32 °C, confirming the good spreadability of the cream. Finally, in vivo tests on healthy volunteers showed excellent safety results and good overall appreciation of the product. No changes in transepidermal water loss (7.9 ± 3.5 vs. 5.5 ± 0.4, p > 0.05), skin hydration (44.2 ± 18.6 vs. 50.5 ± 14.1, p > 0.05), or color were detected within 6 h from application, compared with baseline values. Moreover, volunteers highlighted the cream’s suitability for dry skin and expressed satisfaction with spreadability, a nourishing and hydrating sensation after application, and the absence of residues, consistently rating them ≥4 in the skin feeling questionnaire. These results are promising and support the potential use of the product on sensitive skin. Full article

Conventional balance assessments often miss subtle deficits in sarcopenia patients due to compensatory strategies. This study develops a computational framework using multidimensional temporal analysis of center-of-pressure (COP) signals to quantify variations in compensatory reserve—the capacity to mask balance impairments—within these patients. COP data were collected from 82 older adults (sarcopenia vs. controls) during static standing on a standard clinical force platform (routine for geriatric balance testing). The framework integrates Dynamic Time Warping distances from a healthy template, fixed-weight LSTM embeddings, and statistical metrics, with feature selection and 5-fold cross-validation (SMOTE) to mitigate overfitting. Semi-tandem stance was most discriminative, achieving 0.84 ± 0.04 accuracy and 0.86 ± 0.05 ROC-AUC—outperforming conventional kinematic features. SHAP analysis identified DTW-based features as primary drivers, correlating with clinical severity indicators, while intra-group variability in prediction probabilities indicated a compensatory reserve gradient. This study introduces a feasible bioengineering methodology based on clinical COP platform analysis, laying the groundwork for future validation and translation into routine clinical assessment tools. Full article

Background/Objectives: Single-phase CT angiography (sCTA) is widely used to assess collateral circulation in acute ischemic stroke, but its static nature can lead to an underestimation of collateral flow. Our study aimed to develop and validate a direct, qualitative dynamic CTA (dCTA) collateral score based on CTP source images, without the need for post-processing software, to provide a more accurate prognostic tool. Methods: We retrospectively analyzed 112 patients with anterior circulation ischemic stroke from a prospective registry who underwent non-contrast CT, sCTA, and CTP within 8 h of onset. Collateral circulation was graded using a 4-point sCTA score and our novel 4-point dCTA score, which incorporates temporal filling patterns. We used linear regression to compare the association of both scores with CTP-derived core/hypoperfusion volumes, infarct growth, and final infarct volume. Results: The dCTA method frequently reclassified patients with poor collaterals on sCTA to good collaterals on dCTA (n = 23), while the reverse was rare (n = 5). A better collateral score was significantly associated with smaller core volume for both sCTA and dCTA, but the dCTA score demonstrated a superior model fit (R² = 0.36 vs. 0.32). Similar superior correlations for dCTA were observed for hypoperfusion, infarct growth, and final infarct volumes. Critically, only the dCTA score significantly modified the association between core volume and time since stroke onset (p for interaction = 0.04). Conclusions: A collateral score derived from CTP source images (dCTA) offers a more reliable prediction of infarct lesion sizes and progression than conventional sCTA. By incorporating temporal resolution without requiring extra software, dCTA provides a robust correlation with stroke temporal evolution and represents a readily implementable tool to enhance patient selection in acute stroke. Full article

Spanish “Fino”-style white wines are traditionally aged by a dynamic process under a flor veil of Saccharomyces cerevisiae, requiring ≥15% (v/v) ethanol, which is typically achieved through fortification. Market demand for lower-alcohol wines and the need to reduce production costs have encouraged the development of alternative approaches. Here, static biological aging was evaluated as a method for producing Fino-type wines with reduced ethanol content. Base wines with ~14% and ~15% (v/v) ethanol were aged for nine months, during which chemical, microbiological, and sensory parameters were analyzed, along with flor veil activity. Lower-ethanol wines showed greater flor activity, with approximately 20 more yeast isolates in the wines with 14% (v/v) ethanol. Higher acetaldehyde levels were detected in these wines, reaching about 377 mg L⁻¹ compared to 230 mg L⁻¹ in the control wines (≥15% v/v ethanol). Significant changes were observed in pH (3.13–3.47 vs. 3.04–3.46), volatile acidity (0.20–0.26 g L⁻¹ vs. 0.31–0.66 g L⁻¹), and several volatile compounds, resulting in chemical and sensory profiles consistent with traditional biologically aged wine. Static biological aging can yield lower-alcohol Fino-style white wines with sensory and chemical attributes comparable to the traditional fortified versions, providing a cost-effective alternative that aligns with evolving consumer preferences. Full article

Dynamic pressure measurement is an important component in the turbo engine testing process. This paper presents a comparative analysis between two types of multichannel electronic pressure measurement systems, commonly known as pressure scanners, used for this purpose: ZOC17/8Px, with analog amplification per channel, and MPS4264, a modern digital system with integrated A/D conversion. The study was conducted in two stages: a metrological verification and validation in static mode, using a high-precision pressure standard, and an experimental stage in dynamic mode, where data was acquired from a turbojet engine test stand, in constant engine speed mode. The signal stability of the pressure scanners was statistically analyzed by determining the coefficient of variation in the signal and the frequency spectrum (FFT) for each channel of the pressure scanners. Furthermore, comprehensive uncertainty budgets were calculated for both systems. The results highlight the superior stability and reduced uncertainty of the MPS4264 pressure scanner, attributing its enhanced performance to digital integration and a higher resilience to external noise. The findings support the adoption of modern digital systems for dynamic applications and provide a robust metrological basis for the optimal selection of measurement systems. Full article

Schatzker type V bicondylar tibial plateau fractures present a major challenge due to the difficulty of achieving stable fixation with minimally invasive strategies. This study introduces a dual-thread lag and locking plate (DLLP) design that integrates lag screw compression with unilateral locking plate fixation. A custom-built compression evaluation platform and standardized 3D-printed fracture models were employed to assess biomechanical performance. DLLP produced measurable interfragmentary compression during screw insertion, with a mean displacement of 1.22 ± 0.11 mm compared with 0.02 ± 0.04 mm for conventional single lateral locking plates (SLLPs) (p < 0.05). In static testing, DLLP demonstrated a significantly greater maximum failure force (7801.51 ± 358.95 N) than SLLP (6224.84 ± 411.20 N, p < 0.05) and improved resistance to lateral displacement at 2 mm (3394.85 ± 392.81 N vs. 2766.36 ± 64.51 N, p = 0.03). Under dynamic fatigue loading simulating one year of functional use, all DLLP constructs survived 1 million cycles with <2 mm displacement, while all SLLP constructs failed prematurely (mean fatigue life: 408,679 ± 128,286 cycles). These findings highlight the critical role of lag screw compression in maintaining fracture stability and demonstrate that DLLP provides superior biomechanical performance compared with SLLP, supporting its potential as a less invasive alternative to dual plating in the treatment of complex tibial plateau fractures. Full article

The proliferation of image sharing on social media poses significant privacy risks. Although some previous works have proposed to detect privacy attributes in image sharing, they suffer from the following shortcomings: (1) reliance only on legacy architectures, (2) failure to model the label correlations (i.e., semantic dependencies and co-occurrence patterns among privacy attributes) between privacy attributes, and (3) adoption of static, one-size-fits-all user preference models. To address these, we propose a comprehensive framework for visual privacy protection. First, we establish a new state-of-the-art (SOTA) architecture using modern vision backbones. Second, we introduce Graph Convolutional Networks (GCN) as a classifier head to counter the failure to model label correlations. Third, to replace static user models, we design a dynamic personalization module using Federated Learning (FL) for privacy preservation and Reinforcement Learning (RL) to continuously adapt to individual user preferences. Experiments on the VISPR dataset demonstrate that our approach can outperform the previous work by a substantial margin of 6% in mAP (52.88% vs. 46.88%) and improve the Overall F1-score by 10% (0.770 vs. 0.700). This provides more meaningful and personalized privacy recommendations, setting a new standard for user-centric privacy protection systems. Full article

Despite growing interest in AI-driven Heating, Ventilation, and Air Conditioning (HVAC) systems, existing approaches often rely on static control strategies or offline simulations that fail to adapt to real-time environmental changes, especially in high-risk healthcare settings. There remains a critical gap in integrating dynamic, physics-informed control with human-centric design to simultaneously address infection control, energy efficiency, and occupant comfort in hospital environments. This study presents an AI-driven ventilation system integrating BIM, adaptive control, and computational fluid dynamics (CFD) to optimize hospital environments dynamically. The framework features (1) HVAC control using real-time sensor datasets; (2) CFD-validated architectural interventions (1.8 m partitions and the pressure range at a return vent); and (3) patient flow prediction for spatial efficiency. The system reduces airborne pathogen exposure by 61.96% (159 s vs. 418 s residence time) and achieves 51.85% energy savings (0.19 m/s airflow) while maintaining thermal comfort. Key innovations include adaptive energy management, pandemic-resilient design, and human-centric spatial planning. This work establishes a scalable model for sustainable hospitals that manages infection risk, energy use, and occupant comfort. Future directions include waste heat recovery and lifecycle analysis to further enhance dynamic system performance. Full article

Conventional static fixation for distal radius fractures (DRF) is clinically challenging, with methods often leading to complications such as malunion and pressure-related injuries. These issues stem from uncontrolled pressure and a lack of real-time biomechanical feedback, resulting in suboptimal functional recovery. To overcome these limitations, we engineered an intelligent, adaptive orthopedic device. The system is built on a patient-specific, 3D-printed architecture for a lightweight, personalized fit. It embeds an array of thin-film pressure sensors at critical anatomical sites to continuously quantify biomechanical forces. This data is transmitted via an Internet of Things (IoT) module to a cloud platform, enabling real-time remote monitoring by clinicians. The core innovation is a closed-loop feedback controller governed by a robust Interval Type-2 Fuzzy Logic (IT2-FLC) algorithm. This system autonomously adjusts servo-driven straps to dynamically regulate fixation pressure, adapting to changes in limb swelling. In a preliminary clinical evaluation, the group receiving the integrated treatment protocol, which included the smart splint and TCM herbal therapy, demonstrated superior anatomical restoration and functional recovery, evidenced by higher Cooney scores (91.65 vs. 83.15) and lower VAS pain scores. This proof-of-concept study validates a new paradigm for adaptive orthopedic devices, showing high potential for clinical translation. Full article

Despite rapid progress in natural language processing, current interactive AI systems continue to struggle with interpreting ambiguous, idiomatic, and contextually rich human language, a barrier to natural human–computer interaction. Many deployed applications, such as language games or educational tools, showcase surface-level adaptation but do not systematically probe or advance the deeper semantic understanding of user intent in open-ended, creative settings. In this paper, we present Semantrix, a web-based semantic word-guessing platform, not merely as a game but as a living testbed for evaluating and extending the semantic capabilities of state-of-the-art Transformer models in human-facing contexts. Semantrix challenges models to both assess the nuanced meaning of user guesses and generate dynamic, context-sensitive hints in real time, exposing the system to the diversity, ambiguity, and unpredictability of genuine human interaction. To empirically investigate how advanced semantic representations and adaptive language feedback affect user experience, we conducted a preregistered 2 × 2 factorial study (N = 42), independently manipulating embedding depth (Transformers vs. Word2Vec) and feedback adaptivity (dynamic hints vs. minimal feedback). Our findings revealed that only the combination of Transformer-based semantic modelling and adaptive hint generation sustained user engagement, motivation, and enjoyment; conditions lacking either component led to pronounced attrition, highlighting the limitations of shallow or static approaches. Beyond benchmarking game performance, we argue that the methodologies applied in platforms like Semantrix are helpful for improving machine understanding of natural language, paving the way for more robust, intuitive, and human-aligned AI approaches. Full article