This study investigates response time as a behavioral indicator related to listening effort (LE) for evaluating speech enhancement (SE) systems. English and Norwegian intelligibility matrix tests were conducted within a single-task paradigm that incorporated click-time recording (logging the precise time of all participant clicks), enabling simultaneous estimation of speech intelligibility and LE-related temporal behavior. Three temporal proxy measures for LE were examined—time per stimulus, reaction time, and word click time—across a broad range of input signal-to-noise ratios (SNRs) and for both discriminative and generative enhancement approaches. Time per stimulus showed an inverted-U pattern across SNRs, whereas reaction time and word click time exhibited monotonic behavior, providing more directly interpretable metrics for comparative evaluation. Analyses of pairwise SNR comparisons revealed that increases in our LE-related temporal measures at higher SNRs precede measurable intelligibility declines, suggesting that these temporal metrics can be more sensitive than intelligibility in this regime. Overall, the proposed framework—where LE-related measurements remain unknown to participants—offers a comprehensive and nuanced behavioral tool for SE evaluation, complementing intelligibility particularly under realistic, moderate-to-high SNR conditions.
A new alternative numerical procedure to the Szegő quadrature formulas for the estimation of integrals with respect to a positive Borel measure μ supported on the unit circle is presented. As in many practical situations, we assume that the values of the integrand F are only known at a finite number of points, which we will assume to be equispaced on the unit circle. Our technique consists of obtaining an approximating Laurent polynomial L to F by interpolation in the Hermite sense in a collection of these points that mimic the zeros of a para-orthogonal polynomial with respect to μ, and to use the values of F at the remaining nodes to improve the accuracy of the approximation by a process of simultaneous complex regression. Some numerical examples are carried out.
Objectives To identify and analyze the individual, interpersonal, community, and environmental factors associated with active commuting to school (ACS) among Spanish adolescents, and to examine the contribution of correlates from multiple ecological domains to ACS. Methods A total of 307 Spanish adolescents (14.4 ± 0.6 years) participated. Data on potential correlates of ACS were collected using validated questionnaires (individual and interpersonal levels), school and city information (community level), and GIS-based indicators and MAPS-Global audits (environmental level). Binary logistic regression models were conducted separately for each ecological level, followed by a multivariable model including all significant factors. Results At the individual level, ownership of two or more motorized vehicles, identified motivation, and perceived environmental/safety barriers were associated with lower odds of ACS, whereas independent mobility, perceived competence for ACS, and integrated motivation were associated with higher odds. At the interpersonal level, parental barriers were associated with lower odds of ACS, whereas greater perceived proximity to destinations was associated with higher odds of ACS. At the community level, attending high-SES schools reduced the odds of ACS compared with low-SES schools. Environmentally, shorter home-school distance, greater leisure-time PA opportunities around the school, and higher aesthetic and social quality of the home neighborhood were significant correlates. In the final multivariable model, ACS was positively associated with perceived competence, integrated motivation, aesthetic and social quality, and higher active transport score around the home, whereas motorized vehicle ownership, identified motivation, perceived environmental/safety barriers, destinations and land use score, higher home-school distance, and higher grand score for leisure PA for home were negatively associated. Conclusion ACS among Spanish adolescents was associated with multiple individual and environmental correlates.
Our study developed and tested a triple serial mediation model of green ethical leadership (GEL). The study relationships were gauged via time-lagged data collected from hotel frontline employees (FLEs) in Türkiye (Study 1) and Ireland (Study 2) using partial least squares structural equation modeling. The following findings are valid for two studies. GEL fosters green creativity, while anticipated pride mediates the linkage between GEL and said outcome. Anticipated pride and green work engagement (GWEN) serially mediate the connection between GEL and green creativity. This is also true for job embeddedness (JEM) and GWEN as the serial mediators relating GEL to green creativity. More importantly, anticipated pride, JEM, and GWEN serially mediate the influence of GEL on FLEs’ green creativity. Our paper fills in research lacunas by reporting the outcomes and multiple/triple mediators of GEL simultaneously that have not been gauged in the pertinent literature so far.
Fatigue prognostic studies in composites often model the delamination evolution over time in one or two dimensions, for example, by depicting one-dimensional (1D) length or two-dimensional (2D) shape contour. However, these representations generally provide limited information about the spatial variation in damage severity within the delaminated region. In this context, this work proposes a prognostic framework for severity-graded fatigue delamination maps in composite laminates. Firstly, to facilitate downstream prognostic modeling, ultrasonic C-scan images are processed through pixel-intensity-based discretization, where pixel intensity values are transformed into discrete damage severity levels and replaced with integer class labels, resulting in severity-graded feature maps that simultaneously characterize the spatial extent and severity distribution of delamination-related damage. Then, a U-Net–transformer model is trained with prior-information-aided loss functions and employed to perform long-horizon prognostics of future severity-graded delamination maps. The framework is demonstrated through fatigue experiments on composite laminates monitored using ultrasonic C-scan inspections. The codes and data are publicly available at https://github.com/JingYuan93/3D-delamination-prognostics.
