How social learning shapes the efficacy of preventative health behaviors in an outbreak

The global pandemic of COVID-19 revealed the dynamic heterogeneity in how individuals respond to infection risks, government orders, and community-specific social norms. Here we demonstrate how both individual observation and social learning are likely to shape behavioral, and therefore epidemiological, dynamics over time. Efforts to delay and reduce infections can compromise their own success, especially when disease risk and social learning interact within sub-populations, as when people observe others who are (a) infected and/or (b) socially distancing to protect themselves from infection. Simulating socially-learning agents who observe effects of a contagious virus, our modelling results are consistent with with 2020 data on mask-wearing in the U.S. and also concur with general observations of cohort induced differences in reactions to public health recommendations. We show how shifting reliance on types of learning affect the course of an outbreak, and could therefore factor into policy-based interventions incorporating age-based cohort differences in response behavior.

Rack and Pinion Steering System Design for a Passenger Car

The steering system plays a crucial role in the stability of the automobile, especially in the safety of the passengers and pedestrians. The aim of this work is to design a rack and pinion steering system that could equip a passenger car. In this process, many parameters are considered for the correct and effective directional response behavior of the vehicle. 2D models were sketched to validate the kinematic algorithm calculus used to optimize and refine the dimensions of the components of the steering system. After a satisfactory Ackermann percentage was achieved, steering system is designed and analysed in one of the most used CAD and CAE software in automotive, CATIA.

A Response-Time-Based Latent Response Mixture Model for Identifying and Modeling Careless and Insufficient Effort Responding in Survey Data

Careless and insufficient effort responding (C/IER) can pose a major threat to data quality and, as such, to validity of inferences drawn from questionnaire data. A rich body of methods aiming at its detection has been developed. Most of these methods can detect only specific types of C/IER patterns. However, typically different types of C/IER patterns occur within one data set and need to be accounted for. We present a model-based approach for detecting manifold manifestations of C/IER at once. This is achieved by leveraging response time (RT) information available from computer-administered questionnaires and integrating theoretical considerations on C/IER with recent psychometric modeling approaches. The approach a) takes the specifics of attentive response behavior on questionnaires into account by incorporating the distance–difficulty hypothesis, b) allows for attentiveness to vary on the screen-by-respondent level, c) allows for respondents with different trait and speed levels to differ in their attentiveness, and d) at once deals with various response patterns arising from C/IER. The approach makes use of item-level RTs. An adapted version for aggregated RTs is presented that supports screening for C/IER behavior on the respondent level. Parameter recovery is investigated in a simulation study. The approach is illustrated in an empirical example, comparing different RT measures and contrasting the proposed model-based procedure against indicator-based multiple-hurdle approaches.

Influence of mothers’ nighttime responses on the sleep–wake rhythm of 1-month-old infants

The purpose of this study was to analyze the influence of the mothers’ nighttime responses on the sleep–wake rhythm of their 1-month-old infants. This study used an anonymous self-administered survey questionnaire with 1133 mothers of 1-month-old infants. The questionnaire investigated basic information about the parents, growth environment of infants, mothers’ sleep patterns during pregnancy, and infants’ sleep patterns at the age of one month. Logistic regression analysis was used to analyze the influence of nighttime responses on the risk of infants sleeping longer during the day than at night. Regarding nighttime response behavior, it was found that immediately picking up 1-month-old infants results in longer sleep during the day than at night (OR 1.616 [1.017 − 2.566], p = 0.042), compared to delaying picking up the infant. It was suggested that the stimulation due to picking up an infant may affect sleep–wake rhythm formation.