Electron-neutral collision cross sections for H2O: I. Complete and consistent set

This work proposes a complete and consistent set of cross sections (CSs) for electron collisions with water molecules to be published in the IST-Lisbon database on LXCat. The set is validated from the comparison between experimental and computed electron swarm parameters. The former are collected from literature while the latter are calculated using a space-homogeneous two-term Boltzmann solver, assuming isotropic scattering in inelastic collisions. Rotational CSs, based on the Born approximation, are optimised by means of the electron swarm analysis technique. Superelastic rotational and vibrational collisions are accounted for in the calculations and found to be particularly important for low-energy electrons interacting with water molecules. The set can be used with codes assuming space-homogeneous conditions, in particular common two-term Boltzmann solvers, ensuring a good agreement with experiments. Therefore, it constitutes an important tool for fast calculations and modelling of complex plasma chemistries

Self-reported visual symptoms and high visual demand activities in professional football players: a cross-sectional survey

Background: Vision is crucial for football players, impacting decision-making and athletic performance. Despite its global popularity, football lacks comprehensive evaluations of the impact of digital device use on ocular symptoms during high-demand activities. Purpose: To gain knowledge about the time spent by football players in high visual demand activities, the symptoms associated with binocular vision dysfunction, and their relationship with sports performance. Methods: A cross-sectional observational study was conducted in 2020 using an online survey targeting football players from Portugal, England, Spain, and Saudi Arabia. The survey, distributed over 5 weeks, aimed to collect data from approximately 5,000 football players. Information on player profiles, competitive levels, vision habits, and symptoms related to binocular vision dysfunctions was collected. The Convergence Insufficiency Symptom Survey (CISS) employed a 5-point Likert scale to indicate the average frequency of each symptom. Due to non-normality, non-parametric tests were used (p < 0.05). Specifically, Mann-Whitney U, Kruskal-Wallis, Chi-square, and Spearman's rank correlation tests were used as appropriate. Results: Analyzing male professional football players (mean age: 27.4 ± 5.0 years, 95% CI, 26.7–28.1), it was found that 38.1% of the players had been called up to the national team and 6.9% had played over 50 games. Self-rated last season's performance had a mean score of 6.5 ± 2.1 (95% CI, 6.2–6.8)(on a scale of 1 to 10). Smartphone use exceeded 1 h daily for all players, with 36.0% surpassing 4 h. Visual symptoms, notably associated with smartphone use (35.5%), were observed. Regarding the CISS score, the mean was 7.1 ± 7.7 (IC95%: 6.6 to 8.8). A weak negative correlation (rho = −0.215, p = 0.003) emerged between CISS scores and self-perceived sports performance. Football players using prescription lenses had significantly higher CISS scores (11.9 ± 10.4, 95% CI, 12.3–7.7) compared to non-users (6.2 ± 6.8, 95% CI, 7.8–5.7) (p < 0.001). Conclusion: This study reveals that professional football players engage in high visual demand tasks, notably on smartphones. One-third of the players link smartphone use to ocular symptoms. The Convergence Insufficiency Symptoms Survey indicates that 6.3% exhibit binocular vision dysfunction symptoms. Those with fewer ocular symptoms perceive that they have better sports performance than their counterparts.The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UIDB/04650/202

Electron-neutral collision cross sections for H2O: II. Anisotropic scattering and assessment of the validity of the two-term approximation

This work proposes a complete and consistent set of cross sections (CS) for electron collisions with water gas molecules to be published in the IST-Lisbon database on LXCat. The set is validated by the electron swarm analysis technique. The anisotropic angular distribution of electrons in rotational collisions is considered by means of the Born approximation in a two-term Boltzmann solver (LisbOn KInetics two-term Boltzmann solver (LoKI-B)) and a Monte Carlo simulations code (LoKI-MC), both freely available as open-source codes. The inclusion of electron anisotropic scattering in rotational collisions significantly improves the agreement between calculations and measurements of the electron drift velocity, reduced mobility, characteristic energy, reduced Townsend ionisation coefficient, reduced effective Townsend coefficient and reduced attachment coefficient. The MC simulations are deemed more accurate and shown to yield similar results as LoKI-B with the proposed set. The use of LoKI-MC also validates the set of CSs against parameters that cannot be obtained by LoKI-B, such as the longitudinal diffusion coefficient or the bulk transport coefficients

Towards a user-specific ergonomics-based approach for an activity assessment tool

Work-related musculoskeletal disorders (WRMSDs) are the most reported work-related health problem in European Union. These are multifactorial disorders, influenced not only by sustained or repeated awkward postures but also by each worker’s individual and psychosocial context. Thus, it becomes crucial to quantify and automatize risk assessment, in an attempt to prevent and reduce WRMSD. This work presents the design of a solution for a user-specific assessment based on ergonomics for posture correction through an intuitive haptic feedback strategy to increase posture self-awareness and guide the user into a more neutral posture. The user’s angular configurations are continuously evaluated with a risk score, based on an ergonomic method, and then associated with the postures where those risks occurred. Posture is intended to be predicted by a deep learning model. Moreover, a joint kinematic wear index is used to carry out a cumulative assessment, taking into account the past postures’ scores. Inertial data from three individuals was collected and analyzed to perform movement analysis and define the ground truth of the recognition model. The resulting kinematic parameters’ ranges are presented. An offline risk assessment was also conducted, showing the potential of the cumulative approach for a more complete and meaningful evaluation.This work was supported in part by the Fundação para a Ciência e Tecnologia (FCT) under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020, and by the FEDER Funds through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI) and P2020 with the Reference Project SmartOs Grant POCI-01-0247-FEDER-039868. Sara Cerqueira was supported by the doctoral Grant SFRH/BD/151382/2021, financed by the Portuguese Foundation for Science and Technology (FCT), under MIT Portugal Program