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We examine the informational roles of trades and time between trades in the domestic and overseas US Treasury markets. A vector autoregressive model is employed to assess the information content of trades and time duration between trades. We find significant impacts of trades and time duration between trades on price changes. Larger trade size induces greater price revision and return volatility, and higher trading intensity is associated with a greater price impact of trades, a faster price adjustment to new information and higher volatility. Higher informed trading and lower liquidity contribute to larger bid–ask spreads off the regular daytime trading period.

Fatigue effects related to answering a sequence of choice tasks have received much scrutiny in the stated choice experiments (SCE) literature. However, decision fatigue related to the time of day when respondents answer questionnaires has been largely overlooked in this literature even though time of day related fatigue effects are well known in the psychology literature. The purpose of this paper is to hypothesize that variations in the time of day when respondents answer an online food choice experiment will translate into observable fatigue effects in the food choices.

An empirical SCE concerning food choices is conducted using a web-based questionnaire for interviews in a pre-recruited online panel of consumers. Timestamps collected during the online interviews provide knowledge about the time of day at which each respondent has answered the survey. This information is linked with knowledge from a food sociology survey on typical meal times as well as biophysical research linking food intake to blood sugar and mental energy in order to generate a proxy variable for each respondent’s level of mental energy when answering the food choice tasks in the questionnaire.

Results show evidence of a time of day effect on error variance in the stated food choices as well as the subsequently estimated market share predictions. Specifically, respondents provide less consistent answers during the afternoon than at other times of the day.

The results indicate that time of day can affect responses to an online survey through increased fatigue and correspondingly less choice consistency. Thus, especially online surveys might account for this in data analysis or even restrict accessibility to the online survey for certain times of day.

Ramadan intermittent fasting (RIF) has produced heterogeneous and domain-specific effects on cognitive function. This study aims to investigate the effect of RIF on verticality perception or estimation of subjective visual vertical (SVV) in young adults. The significance of SVV is that it is essential for spatial orientation, upon which many daily activities depend.

Verticality perception was assessed with a computerized rod and frame test (CRFT) in two visual conditions: without a surrounding frame and with a distracting tilted frame. The tilted frame condition measures level of visual dependence or reliance of visual cues for posture and orientation. In total, 39 young adult men were recruited at different stages of Ramadan fasting: 21 were tested at the end of the first week (Week 1) and 18 others at the end of the third week (Week 3) of Ramadan. Also, 39 participants were recruited to serve as a non-fasting control group. Factorial ANOVA analyses were conducted to identify the main effects of fasting status, time-of-day and the interaction between them on blood glucose levels, nocturnal sleep duration and vertical alignment errors.

The main effect of fasting status on glucose level was significant (p = 0.03). There was a significant time-of-day main effect on glucose levels (p = 0.007) and sleep duration (p = 0.004) only in fasting participants. Neither the main effects of fasting status nor time-of-day were significant for rod alignment errors in both visual conditions. The interaction of fasting status and time-of-day was not significant either. This may indicate that any negative effect of Ramadan fasting on activities that are critically dependent on verticality perception and spatial orientation, such as sports and driving, may not be due to verticality misperception.

The present study was the first to investigate the effect of Ramadan fasting on spatial orientation. It demonstrated robustness of verticality perception to fasting status and the point of fasting during Ramadan. Verticality perception was also unaffected by time-of-day effects in non-fasting and fasting groups at two different points of Ramadan. This study corroborates others reporting heterogeneous effects of Ramadan fasting on cognitive function.

To address the safety concerns generated by truck crashes occurred in big cities, this paper analyzes the zip code tabulation area (ZCTA)-based truck crash frequency across four temporal intervals – morning (6:00–10:00), mid-day (10:00–15:00), afternoon (15:00–19:00), and night (19:00–6:00) in New York City in 2010. A multivariate conditional autoregressive count model is used to recognize both spatial and temporal dependences. The results prove the presence of spatial and temporal dependencies for truck crashes that occurred in neighboring areas. Built environment attributes such as various types of business establishment density and traffic volume for different types of vehicles, which are important factors to consider for crashes occurred in an urban setting, are also examined in the study.

The purpose of this paper is to examine factors affecting the engagement metrics of the hotel Facebook page. Such factors include time-of-day, day-of-week, age, gender and distance between the hotel and users’ origin of residence. Another purpose is to assess the impact of Facebook engagement on electronic word-of-mouth (eWOM), to better understand the importance of the engagement metrics within the hotel Facebook context.

This study uses secondary data from the Facebook page of a 147-room hotel in Northeast America. A total of 181 observations reflecting primary Facebook metrics are adopted via Facebook Insights between January 2014 and June 2014.

The number of daily-engaged users positively affects the number of daily people talking about the page (eWOM). Moreover, the number of engaged users differs significantly by the external factors (time-of-day, day-of-week, age, gender and distance).

Hotel Facebook developers should post the most important promotions on Monday afternoon, targeting females aged between 25 and 34 years living within 50 miles of the hotel. Posting on hotel Facebook a few hours before “traffic” to avoid competition and gain visibility is important. Marketers should focus on giving feedback during peak times.

This empirical study extends prior studies on social media metrics to the effects of external factors on the engagement metrics within the hotel Facebook context. Increasing the number of engaged users improves the effectiveness of eWOM for a hotel, which lacks empirical evidence.

We investigate how household disadvantage affects the time use of 15–18 year olds using 2003–2006 data from the American Time Use Survey. Applying competing-risk hazard models, we distinguish between the incidence and duration of activities and incorporate the daily time constraint. We find that teens living in disadvantaged households spend less time in nonclassroom educational activities than other teens. Girls spend some of this time in work activities, suggesting that they are taking on adult roles. However, we find more evidence of substitution into unsupervised activities, suggesting that it may be less-structured environments that reduce educational investment.

Fatigue associated with shift work is a well-established and pervasive problem in policing that affects officer performance, safety, and health. It is critical to understand the extent to which fatigue degrades officer driving performance. Drowsy driving among post-shift workers is a well-established risk factor yet no data are available about officer injuries and deaths due to drowsy driving. The purpose of this paper is to assess the impact of fatigue associated with work shift and prior sleep on officers’ non-operational driving using laboratory experiments to assess post-shift drowsy driving risks and the ability of a well-validated vigilance and reaction-time task to assess these risks.

Experienced police patrol officer volunteers (n=78) from all four shifts of a medium-sized city’s police department were tested using a within- and between-subjects design to assess the impact of fatigue on individual officers, as well as the impact of different work shifts, on post-shift driving performance. Controlled laboratory experiments were conducted during which participants drove high-fidelity driving training simulators on two occasions: immediately following five consecutive 10:40-hour patrol shifts (fatigued condition) and again 72 hours after completing the last shift in a work cycle (rested condition).

Generalized linear mixed-model analyses of driving performance showed that officers working night shifts had significantly greater lane deviation during post-shift, non-operational driving than those working day shifts (F=4.40, df=1, 150, p=0.038). The same method also showed that easy to measure psychomotor vigilance test scores for reaction time predicted both lane deviation (F=31.48, df=1, 151, p < 0.001) and collisions (F=14.10, df=1, 151, p < 0.001) during the simulated drives.

Simulated driving tasks done by participants were generally less challenging than patrol or off-duty driving and likely underestimate the impact of fatigue on police driving post-shift or during extended shifts.

This is the first experimental research to assess the impact of shiftwork, fatigue, and extended shifts on police post-shift drowsy driving, a known risk factor for shift workers in general.

Many transport and logistics companies nowadays use raw vehicle GPS data for travel time prediction. However, they face difficult challenges in terms of the costs of information storage, as well as the quality of the prediction. This paper aims to systematically investigate various meta-data (features) that require significantly less storage space but provide sufficient information for high-quality travel time predictions.

The paper systematically studied the combinatorial effects of features and different model fitting strategies with two popular decision tree ensemble methods for travel time prediction, namely, random forests and gradient boosting regression trees. First, the investigation was conducted using pseudo travel time data that were generated using a pseudo travel time sampling algorithm, which allows generating travel time data using different noise processes so that the prediction performance under different travel conditions and noise characteristics can be studied systematically. The results and findings were then further compared and evaluated through a real-life case.

The paper provides empirical insights and guidelines about how raw GPS data can be reduced into a small-sized feature vector for the purposes of vehicle travel time prediction. It suggests that, add travel time observations from the previous departure time intervals are beneficial to the prediction, particularly when there is no other types of real-time information (e.g. traffic flow, speed) are available. It was also found that modular model fitting does not improve the quality of the prediction in all experimental settings used in this paper.

The findings are primarily based on empirical studies on limited real-life data instances, and the results may lack generalisabilities. Therefore, the researchers are encouraged to test them further in more real-life data instances.

The paper includes implications and guidelines for the development of efficient GPS data storage and high-quality travel time prediction under different types of travel conditions.

This paper systematically studies the combinatorial feature effects for tree-ensemble-based travel time prediction approaches.

Nocturnal headaches among adolescents were reported to be increased with the development of modern technology. The purpose of this paper is to investigate the smartphone electromagnetic radiation related to nocturnal headaches among high school students.

The time series study of all 12,969 records from 145 high school students Chiang Mai Province was selected from the population in the first phase by setting criteria. The samples completed a headache diary utilizing a smartphone application. The smartphone output power (SOP) was measured and recorded by the smartphone application and transmitted by e-mail to a researcher. The smartphone use, sleep quality, anxiety and depression also were assessed. Data were analyzed using Generalized Estimating Equation adjusting for demographic data, smartphone use, and sleep quality and otherwise.

The resulted showed the prevalence of repeated headaches to be 13.4 percent, nocturnal headache only 5.3 percent and the strongest effect of day time SOP at a 1.80–1.99×10⁻⁵ mW range on nocturnal headaches (OR_adj5.18; 95% CI: 3.44–7.81). Meanwhile, Lag_6 of daily SOP exposure produced a nocturnal headache effect in a reverse dose-response manner. Furthermore, the nocturnal headache also had the strongest association with age, internet use and device brand (OR_adj2.33; 95% CI: 1.08–5.05, OR_adj2.14; 95% CI: 1.07–4.2 and OR_adj1.68; 95% CI: 1.1–2.4).

The electromagnetic radiation from a smartphone is the environmental variables influences on headache. The results suggested that there should be limited times for smartphone use and older age to start using a smartphone to prevent headache attacks at night.

Understanding how health status and physiological factors affect performance is a daunting task. This chapter will discuss physiological, behavioral, and psychological factors that influence or determine the capacity to fight, and will consider metrics that can be used to measure their status. The premise of this discussion is that there is a set of physiological and psychological factors that intimately affect performance and that the relative contribution of these variables is individually unique. These factors can be identified and assessed, and are amenable to modification. A fuller understanding of these variables can lead the effort to maintain and improve performance in the adverse and challenging environments of military operations.