Search Results (68)

The corrosion of high-strength steel wires is a key factor impacting the durability and reliability of cable-stayed bridges. In this study, the corrosion pit features on a high-strength steel wire, which had been in service for 27 years, were extracted and modeled using three-dimensional point cloud data obtained through 3D surface scanning. The Otsu method was applied for image binarization, and each corrosion pit was geometrically represented as an ellipse. Key pit parameters—including length, width, depth, aspect ratio, and a defect parameter—were statistically analyzed. Results of the Kolmogorov–Smirnov (K–S) test at a 95% confidence level indicated that the directional angle component (θ) did not conform to any known probability distribution. In contrast, the pit width (b) and defect parameter (Φ) followed a generalized extreme value distribution, the aspect ratio (b/a) matched a Beta distribution, and both the pit length (a) and depth (d) were best described by a Gaussian mixture model. The obtained results provide valuable reference for assessing the stress state, in-service performance, and predicted remaining service life of operational stay cables. Full article

Activity space offers a valuable perspective for analyzing urban travel behavior and evaluating the performance of transportation systems in increasingly complex urban environments. However, the research on measuring activity spaces in multimodal transportation contexts remains limited. This study investigates multimodal transportation activity spaces in Hangzhou using 2023 smart card data. Multimodal travel chains are extracted, and residents’ activity spaces are quantified using 95% confidence ellipses. By applying the XGBoost and GeoShapley models, this study reveals the nonlinear effects and geospatial heterogeneity in how built environment and socioeconomic factors influence activity spaces. The key findings show that the distance to the nearest metro station, commercial POIs, and GDP significantly shape activity spaces through nonlinear relationships. Moreover, the interaction between the distance to the nearest metro station and geographical location generates pronounced geospatial effects. The results highlight the importance of multimodal integration in urban transport planning and provide empirical insights for enhancing system efficiency and sustainability. Full article

Body mass index (BMI) is not equipped to adequately detect obesity in individuals, leading to conditions such as normal-weight obesity, which disproportionately impact older women. Bioelectrical impedance vector analysis (BIVA) is a non-invasive and accessible method for assessing body composition and cellular health (e.g., resistance/height, reactance/height, phase angle), yet little is known about how BMI categories differ in cellular health. This cross-sectional study compared bioimpedance and adiposity across BMI classifications (normal weight, overweight, and obese) among 196 community-dwelling older women (age: 74.5 ± 7.0 years, BMI: 30.3 ± 6.3 kg/m²) using a one-way ANOVA and BIVA software. Individual and group bioimpedance were plotted within tolerance and 95% confidence ellipses. Body fat percentage (F = 70.6, p < 0.001, η_p² = 0.42) and resistance/height (F = 36.4, p < 0.001, η_p² = 0.27) differed between normal-weight, overweight, and obese groups. Reactance/height (F = 36.4, p < 0.001, η_p² = 0.27) and phase angle (F = 4.77, p = 0.01, η_p² = 0.05) only differed between normal-weight and obese groups. When plotted with 95% BIVA confidence ellipses, BMI categories occupied distinct positions from each other (T² = 16.1 − 66.6, D = 0.68 − 1.48, p < 0.05). Within BIVA tolerance ellipses, overweight and obese categories fell in the “obese” quadrant, while the normal-weight category fell in the “athletic” quadrant. However, individual participants were predominantly scattered throughout the “cachectic,” “obese,” and “athletic” quadrants regardless of BMI. These findings suggest that BMI appears to be adequate for assessing population averages but not individual body composition. Future research should investigate the utility of bioelectrical resistance as a marker of obesity. Full article

Accurate and predictive models of lithium-ion batteries are essential for optimizing performance, extending lifespan, and ensuring safety. The reliability of these models depends on the accurate estimation of internal electrochemical and mechanical parameters, many of which are not directly measurable and must be identified via model-based fitting of experimental data. Unlike other parameter-estimation procedures, this study introduces a novel approach that integrates mechanical measurements with electrical data, with a specific application for lithium iron phosphate (LFP) cells. An error analysis—based on the Root Mean Square Error (RMSE) and confidence ellipses—confirms that the inclusion of mechanical measurements significantly improves the accuracy of the identified parameters and the reliability of the algorithm compared to approaches relying just on electrochemical data. Two scenarios are analyzed: in the first, a teardown of the cell provides direct measurements of electrode thicknesses and the number of layers; in the second, these values are treated as additional unknown parameters. In the teardown case, the electrochemical–mechanical approach achieves significantly lower RMSEs and smaller confidence ellipses, proving its superior accuracy and consistency. In the second scenario, while the RMSE values of electrochemical-mechanical model are similar to those of the purely electrochemical one, the smaller ellipses still indicate better consistency and convergence in the parameter estimates. Furthermore, a sensitivity analysis to initial guesses shows that the electrochemical-mechanical approach is more stable, consistently converging to coherent parameter values and confirming its greater reliability. Full article

We investigate the stochastic disruption of synchronization patterns in a system of two non-identical Rulkov neurons coupled via an electrical synapse. By analyzing the system deterministic dynamics, we identify regions of mono-, bi-, and tristability, corresponding to distinct synchronization regimes as a function of coupling strength. Introducing stochastic perturbations to the coupling parameter, we explore how noise influences synchronization patterns, leading to transitions between different regimes. Notably, we find that increasing noise intensity disrupts lag synchronization, resulting in intermittent switching between a synchronous three-cycle regime and asynchronous chaotic states. This intermittency is closely linked to the structure of chaotic transient basins, and we determine a noise intensity range in which such behavior persists, depending on the coupling strength. Using both numerical simulations and an analytical confidence ellipse method, we provide a comprehensive characterization of these noise-induced effects. Our findings contribute to the understanding of stochastic synchronization phenomena in coupled neuronal systems and offer potential implications for neural dynamics in biological and artificial networks. Full article

Nervousness is a complex emotional state characterized by high arousal and ambiguous valence, often triggered in high-stress environments. This study presents a mathematical and computational framework for defining and classifying nervousness using facial expression data projected onto a valence–arousal (V–A) space. A statistical approach employing the Minimum Covariance Determinant (MCD) estimator is used to construct 90% and 99% confidence ellipses for nervous and non-nervous states, respectively, using Mahalanobis distance. These ellipses form the basis for binary labeling of the AffectNet dataset. We apply a deep learning model trained via knowledge distillation, with EmoNet as the teacher and MobileNetV2 as the student, to efficiently classify nervousness. The experimental results on the AffectNet dataset show that our proposed method achieves a classification accuracy of 81.08%, improving over the baseline by approximately 6%. These results are obtained by refining the valence–arousal distributions and applying knowledge distillation from EmoNet to MobileNetV2. We use accuracy and F1-score as evaluation metrics to validate the performance. Furthermore, we perform a qualitative analysis using action unit (AU) activation graphs to provide deeper insight into nervous facial expressions. The proposed method demonstrates how mathematical tools and deep learning can be integrated for robust affective state modeling. Full article

Identification of paleoclimate oscillation from various climate proxies across different regions is important for the mechanistic research of paleoclimate. Phytoliths from the lacustrine sediment of central NE China were extracted for paleoclimate reconstruction and abrupt event recognition. The combined phytolith assemblages; indices of Iw, Iph, D/P, Pi/P, and T/P; and the 66.4% PCA information with 95% confidence ellipse showed six global synchronously paleo-stages in the past 25,000 years: mixed coniferous broadleaf forest in a semi-humid cool climate (25,165–22,180 cal aB.P.), cold and arid steppe (22,180–18,080 cal aB.P.), semi-humid and semi-arid steppe (18,080–11,380); semi-humid cool grassland (11,380–7790 cal aB.P.), humid warm forest steppe (7790–4300 cal aB.P.), and semi-arid and cool meadow steppe (4300 cal aB.P. to the present). The global abrupt events of the 4.2-kiloyear event, 8.2-kiloyear event, Younger Dryas (YD), Heinrich1 (H1), and Heinrich2 (H2) were also captured by phytolith indices. The regional character of the reduction in humidity of the YD might have been affected by the combined influence of the Okhotsk High and the surrounding mountains. These findings not only strengthen phytolith palaeoresearch but also provide basic information for the mechanistic research of palaeoclimate in the edge area of Northeast Asia and promote global climate change research. Full article

Aiming to mitigate the substantial dispersion in arrival angle estimation due to colored and white noise interference, which may seriously affect the accuracy of short-wave single-station positioning, this paper introduces an approach to optimizing angles based on the statistical features. By utilizing the extraction of the main peak area of the probability density distribution of the measured angle, as well as the two-dimensional Gaussian fitting and confidence ellipse bounding, the angle measurement results affected by colored noise interference and the noise points with large deviations can be sequentially filtered out. Combining experimental scenarios and confirmed by actual measurement data, the dispersion of arrival angle estimation results has been significantly constrained, and, correspondingly, the positioning accuracy has also been significantly improved by about 3%. Full article

This paper presents an autonomous collision avoidance method that integrates path planning and control for articulated steering vehicles (ASVs) operating in underground tunnel environments. The confined nature of tunnel spaces, combined with the complex structure of ASVs, increases the risk of collisions due to path-tracking inaccuracies. To address these challenges, we propose a DWA-based obstacle avoidance algorithm specifically tailored for ASVs. The method incorporates a confidence ellipse, derived from the time-varying distribution of tracking errors, into the DWA evaluation function to effectively assess collision risk. Furthermore, the execution accuracy of DWA is improved by integrating a kinematic-based Model Predictive Control. The proposed approach is validated through simulations and field tests, with results demonstrating significant enhancements in collision avoidance and path-tracking accuracy in confined spaces compared to conventional DWA methods. Full article

Background/Objectives: To obtain bioelectrical data to assess nutritional status for extremely low-birth-weight (ELBW) infants upon reaching term-corrected age. Methods: A descriptive, observational, prospective, and single-center study, which included ELBW preterm infants was performed. The study variables collected were gestational age, sex, and anthropometry at birth and at term-corrected age. Bioelectrical impedance vector analysis (BIVA) was performed by a phase-sensitive device (BIA 101 BIVA PRO AKERN srl, Pisa, Italy). The components of the impedance vector—resistance (R) and reactance (Xc)—were normalized for body height (H). For each subject, the measurement was taken between the 36th and 44th weeks of postmenstrual age (PMA). A semi-quantitative analysis of body composition was performed using the vector modality of the BIA. Using the RXc graph method, the bivariate 95% confidence intervals of the mean vectors were constructed. From the bivariate normal distribution of R/H and Xc/H, the bivariate 95%, 75%, and 50% tolerance intervals for this cohort were drawn. The individual impedance vectors were compared with the distribution of the vectors from other populations. Results: 85 ELBW infants (40 male, 45 female) were included, with a mean gestational age at birth of 26 + 6 weeks (±1.76). Mean R/H was 870.33 (±143.21) Ohm/m and Xc/H was 86.84 (±19.05) Ohm/m. We found differences in the bioelectrical data with regard to gender, with resistance values being significantly higher in females. Our ellipses align closely with those from other term neonatal cohorts. Conclusions: Bioelectrical data and the confidence and tolerance ellipses of an ELBW infant cohort are presented and can be used as a reference standard for nutritional assessment at discharge. Full article

Inertial Motor sensors (IMUs) are valid instruments for measuring postural sway but their ability to detect changes derived from visual deprivation in healthy older adults requires further investigations. We examined the validity and relationship of IMU sensor-derived postural sway measures compared to force plates for different eye conditions in healthy older adults (32 females, 33 males). We compared the relationship of the center of mass and center of pressure (CoM and CoP)-derived total length, root means square (RMS) distance, mean velocity, and 95% confidence interval ellipse area (95% CI ellipse area). In addition, we examined the relationship of the IMU sensor in discriminating between open- (EO) and closed-eye (EC) conditions compared to the force plate. A significant effect of the instruments and eye conditions was found for almost all the variables. Overall, EO and EC variables within (force plate r, from 0.38 to 0.78; IMU sensor r, from 0.36 to 0.69) as well as between (r from 0.50 to 0.88) instruments were moderately to strongly correlated. The EC:EO ratios of RMS distance and 95% CI ellipse area were not different between instruments, while there were significant differences between total length (p = 0.973) and mean velocity (p = 0.703). The ratios’ correlation coefficients between instruments ranged from moderate (r = 0.65) to strong (r = 0.87). The IMU sensor offers an affordable, valid alternative to a force plate for objective, postural sway assessment. Full article

Reliable, standardized balance tests for dogs are not available yet. The purpose of this study was to investigate the reliability of static and dynamic posturography in healthy dogs. Healthy dogs (n = 20) were positioned with four paws longitudinally and with the forepaws only transversely on a modified pressure-sensitive balance platform (Posturomed-FDM-JS, Zebris, Isny, Germany). Three static and dynamic posturographic trials were recorded (recording duration: 20 s) and repeated after 7–14 days. Center of pressure (COP) parameters COP-path-length (PL; mm), 95% COP-confidence-ellipse-area (CEA; mm²), and COP-average-velocity (AV; mm/s) were calculated for the first steady-state 5 s intervals of each trial. The reliability of COP parameters was assessed with robust linear mixed effects models with nested random effects of patient and trial. The training effect was analyzed using Cohen’s d. For static posturography, PL, CEA, and AV did not differ significantly between time points; CEA had the highest reliability (p = 0.92). For dynamic posturography, AV and PL differed significantly between time points (AV: p ≤ 0.043; PL: p ≤ 0.045). Slight training effects were observed for transverse positioning (Cohen’s d: PL 0.65; AV 0.267) and moderate training effects for longitudinal positioning (Cohen’s d: PL: 0.772; AV: 0.783). This study showed that static posturography on a modified Posturomed-balance platform was reliable in healthy dogs but indicated training effects during dynamic posturography. Full article

University women are vulnerable to engaging in risky sexual behaviors (RSBs), which are related to academic stress, alcohol, and tobacco consumption. The aim of this study was to identify profiles of university women who associate RSBs with alcohol consumption, tobacco consumption level, and frequency of academic stress. A total of 534 female university students from Mexican universities answered an online questionnaire with five instruments related to their sexual behavior, alcohol consumption, tobacco consumption, and academic stress. They were studying to become professionals in health sciences, administration and social sciences, engineering, and “others” with grade point averages ranging from 5.7 to 10/10. They had to sign an informed consent and acknowledge having had at least one sexual relationship with anal or vaginal penetration before participating. A multiple correspondence analysis yielded a parsimonious solution with the following three dimensions that explained 38.60% of the variance: 1 “pregnancy”; 2 “number of sexual partners”; 3 “substance use”. Using a point cloud clustering strategy based on the Euclidean distance between categories in a two-dimensional space, five profiles were identified: Conservative and Prudent, Active Promiscuous, Vulnerable Reproductive Health, STI Risk, and Moderate Risk Behaviors. The estimation of ellipses with 95% confidence from the calculation of centroids allowed for the integration of two profiles: Lower probability of RSB and Higher probability of RSB. The contribution of academic stress was null with respect to the model solution, so this variable was discarded. The results identified particular risk profiles in female university students. These findings are useful for the development of differentiated intervention strategies to reduce RSB in this vulnerable group. Full article

Background/Objectives: The main aim of our study was to analyze the stabilometric parameters in relation to hip and knee muscle force in children with unilateral slipped capital femoral epiphysis (SCFE) who had undergone surgical treatment. Another objective was to compare the stabilometry in three testing situations (eyes open, eyes closed, and head retroflexed). Methods: In total, 26 patients with unilateral right SCFE treated via in situ fixation with one percutaneous screw performed stabilometry assessments under three different situations (with their eyes open, with their eyes closed, and with their head retroflexed) and isometric muscle force assessment of the bilateral hip flexors, extensors, abductors and adductors and bilateral knee flexors and extensors. Results: No significant differences between the right side (affected hip) and left side (non-affected hip) were recorded for all of the tested muscle groups. We found significant negative correlations between the 90% confidence ellipse area (eyes open condition) and left knee extensors (p = 0.028), right knee flexors (p = 0.041), and left knee flexors (p = 0.02), respectively. When performing the comparison between the eyes open and eyes closed situations, there were significant differences in CoP path length (p < 0.0001) and maximum CoP speed (p = 0.048); the parameters increased in the eyes closed situation. Conclusions: Better postural stability is acquired when assessed with eyes open or with the head retroflexed in contrast with eyes closed testing. Full article

Postural imbalance is a leading cause of injury in older adults. Our study investigated the effectiveness of virtual reality (VR)-based interventions on balance ability in this population. Here, we examined 21 older, healthy adults (75.8 ± 5.2 years old). Participants performed 6 weeks of balance training, twice per week for 30 min; the experimental group donned an Oculus VR headset during the training while control participants did not. To assess balance ability, a force platform measured displacement of the center of pressure (COP) during quiet standing in double-leg, tandem, and single-leg stances with eyes closed pre- and post-assessment. COP measurements included mediolateral (ML) and anterior–posterior (AP) directions for root mean square (RMS), peak-to-peak displacement (MAXD), total excursion (TE), and 95% confidence area ellipse (AE) parameters. Post-training assessments showed improvements (significant decreases) in the COP parameters. Control group COP parameters improved in various stances ranging from a 3% to 40% decrease on average. The VR group improved MAXD, TE, and 95% AE ranging from a 5% to 47% decrease, on average, across various stances post- compared to pre-training. VR-based exercise training programs may encourage older adults to engage in mobility exercises, leading to a reduced risk of falls or injuries. Full article