102 research outputs found
E-cigarette and waterpipe use in two adolescent cohorts: cross-sectional and longitudinal associations with conventional cigarette smoking.
Alternative tobacco products are increasing in popularity. An important question is whether their use is associated with or even leads to conventional smoking, but large-scale (European) studies are scarce. In two cohorts of Dutch adolescents (Cohort I n = 6819, mean age = 13.8 SD = 1.1, 48.2% female; Cohort II n = 2758, mean age = 17.3 SD = 1.8, 61.3% female), we investigated use of electronic (e)-cigarettes with nicotine, e-cigarettes without nicotine and waterpipe. Generalized estimating equation modelling was conducted with ever conventional smoking as the dependent variable (0 = no, 1 = yes) and ever alternative tobacco use as the independent variable, correcting for clustering within schools, age, sex and education in both cohorts. In a subsample (n = 2100), the association between alternative tobacco use at baseline and conventional smoking 6 months later was tested, taking into account smoking propensity (based on personality, susceptibility to peer pressure and smoking intentions). Ever use prevalence was 13.7% for e-cigarettes with nicotine, 29.4% for e-cigarettes without nicotine and 22.1% for waterpipe in Cohort I and 12.3, 27.6 and 45.3% respectively in Cohort II. Ever smokers had tried alternative tobacco products more often than never smokers. Among never-smoking adolescents at baseline, alternative tobacco use predicted ever smoking 6 months later (e-cigarettes with nicotine OR 11.90 95% CI 3.36-42.11; e-cigarettes without nicotine OR 5.36 95% CI 2.73-10.52; waterpipe OR 5.36 95% CI 2.78-10.31). This association was strongest for adolescents with a low baseline risk of smoking. Experimenting with alternative tobacco products is common among Dutch youth. Alternative tobacco use predicts (future) smoking, especially among adolescents with a low smoking propensity
Simulating crowd evacuation with socio-cultural, cognitive, and emotional elements
In this research, the effects of culture, cognitions, and emotions on crisis management and prevention are analysed. An agent-based crowd evacuation simulation model was created, named IMPACT, to study the evacuation process from a transport hub. To extend previous research, various socio-cultural, cognitive, and emotional factors were modelled, including: language, gender, familiarity with the environment, emotional contagion, prosocial behaviour, falls, group decision making, and compliance. The IMPACT model was validated against data from an evacuation drill using the existing EXODUS evacuation model. Results show that on all measures, the IMPACT model is within or close to the prescribed boundaries, thereby establishing its validity. Structured simulations with the validated model revealed important findings, including: the effect of doors as bottlenecks, social contagion speeding up evacuation time, falling behaviour not affecting evacuation time significantly, and travelling in groups being more beneficial for evacuation time than travelling alone. This research has important practical applications for crowd management professionals, including transport hub operators, first responders, and risk assessors
Formal modeling and analysis of cognitive agent behavior
From an external perspective, cognitive agent behavior can be described by specifying (temporal) correlations of a certain
complexity between stimuli (input states) and (re)actions (output states) of the agent. From an internal perspective the agent’s
dynamics can be characterized by direct (causal) temporal relations between internal and mental states of the agent. The latter
type of specifications can be represented in a relatively simple, executable format, which enables different types of analysis
of the agent’s behavior. In particular, simulations of the agent’s behavior under different (environmental) circumstances
can be explored. Furthermore, by applying verification techniques, automated analysis of the consequences of the agent’s behavior
can be carried out. To enable such types of analysis when only given an external behavioral specification, this has to be
transformed first into some type of executable format. An automated procedure for such a transformation is proposed in this
paper. The application of the transformation procedure is demonstrated for a number of cases, showing examples of the types
of analysis as mentioned for different forms of behavior
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