Attentional Control in Young Drivers: Does Training Help or Hinder Bottom-Up Processing in a Dynamic Driving Environment?

Anticipating hidden hazards on the road is a critical skill for safe driving, one that many young and novice drivers lack. Training programs are shown to improve hazard anticipation performance in young drivers, but whether these training effects persist in the presence of salient and potentially distracting stimuli remains relatively less explored. In this study, we examined whether the effectiveness of an existing driving training program, Risk Awareness Perception Training (RAPT), on increasing latent hazard anticipation on the road persisted with extraneous bottom-up stimuli in the road environment. Forty-one young drivers, aged 18-21, completed a series of driving scenarios with latent hazards, after completing RAPT or a placebo training, in a medium-fidelity driving simulator with their eyes tracked. The eye movement data showed that RAPT-trained drivers anticipated hazards correctly in more scenarios than Placebo-trained drivers, replicating previous works. Additionally, the results suggest that the effectiveness of RAPT persisted even in scenarios that involve dynamic onset of pedestrians presented simultaneously with the latent hazards. The results imply that RAPT can improve drivers’ latent hazard anticipation performance, protecting them from the adverse effect of attentional capture by stimulus movements that coexist with latent road hazards

Extracting market expectations from yield curves augmented by money market interest rates: the case of Japan

This paper attempts to extract market expectations about the Japanese economy and the BOJ’s policy stance from the yen yield curves augmented by money market interest rates, during the period from the end of the quantitative easing policy in March 2006. We use (i) the swap yield curves augmented by OIS interest rates (OIS/Swap), and (ii) the JGB yield curve augmented by FB/TB interest rates. First, using the Nelson-Siegel [1987] model, we estimate three latent dynamic factors, which can be interpreted as reflecting market expectations. Second, we investigate the relative importance of price discovery for each factor between OIS/Swap and FBTB/JGB, and find that the former has a more dominant role of price discovery for all factors. Third, we estimate the efficient price for each factor common to both yield curves using a time-series structural model, which enables us to decompose each factor into the efficient price and idiosyncratic factor. JEL Classification: E43, E52, G12overnight index swap, price discovery, structural time-series model, swap spread, yield curve

Tension Analysis in Survivor Interviews: A Computational Approach

Tension is an emotional experience that can occur in different contexts. This phenomenon can originate from a conflict of interest or uneasiness during an interview. In some contexts, such experiences are associated with negative emotions such as fear or distress. People tend to adopt different hedging strategies in such situations to avoid criticism or evade questions. In this thesis, we analyze several survivor interview transcripts to determine different characteristics that play crucial roles during tension situation. We discuss key components of tension experiences and propose a natural language processing model which can effectively combine these components to identify tension points in text-based oral history interviews. We validate the efficacy of our model and its components with experimentation on some standard datasets. The model provides a framework that can be used in future research on tension phenomena in oral history interviews