Full moon and traffic accident-related emergency ambulance transport: A nationwide case-crossover study

Food Waste and Lunar Phases: Evidence from a Randomized Controlled Trial

To examine a potential correlation between food waste and lunar phases, we have devised a randomized controlled trial. The experiment spanned from 31 March to 10 July 2022, during which we employed the direct weighing method to collect 1903 valid data points on food waste. Utilizing propensity score matching, we meticulously controlled for various factors, including dining dates, the number of diners, dining times, spending levels, and store activities. The study revealed a close relationship between lunar phases and food waste. During the new moon phase, there was an increase in both orders and waste generated by consumers. Specifically, individuals, on average, squandered an additional 6.27% of animal protein (0.79 g), 24.5% of plant protein (1.26 g), 60.95% of starchy foods (3.86 g), and 61.09% of vegetables (5.12 g), resulting in an aggregate food waste of 32.14% (10.79 g). Conversely, during the full moon phase, consumers decreased their orders and subsequently decreased food waste. On average, individuals wasted 44.65% less animal protein (5.76 g), 43.36% less plant protein (2.5 g), 85.39% less seafood (0.73 g), and 8.43% less vegetables (0.93 g), resulting in a 20.52% (7.81 g) reduction in food waste. Furthermore, we validated our conclusions through various validation methods, including model replacement, to ensure robustness and reliability.

A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations

With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011-2021). A number of digital databases (i.e., IEEE Xplore®, ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.

Effects of weather and moon phases on emergency medical use after fall injury: A population-based nationwide study

Background

Previous studies reported that changes in weather and phases of moon are associated with medical emergencies and injuries. However, such studies were limited to hospital or community level without explaining the combined effects of weather and moon phases. We investigated whether changes in weather and moon phases affected emergency department (ED) visits due to fall injuries (FIs) based on nationwide emergency patient registry data.

Methods

Nationwide daily data of ED visits after FI were collected from 11 provinces (7 metropolitan cities and 4 rural provinces) in Korea between January 2014 and December 2018. The daily number of FIs was standardized into FI per million population (FPP) in each province. A multivariate regression analysis was conducted to elucidate the relationship between weather factors and moon phases with respect to daily FPP in each province. The correlation between weather factors and FI severity was also analyzed.

Results

The study analyzed 666,912 patients (418,135 in metropolitan and 248,777 in rural areas) who visited EDs on weekdays. No regional difference was found in age or gender distribution between the two areas. Precipitation, minimum temperature and wind speed showed a significant association with FI in metropolitan areas. In addition, sunshine duration was also substantial risk factors for FI in rural areas. The incidence of FIs was increased on full moon days than on other days in rural areas. Injury severity was associated with weather factors such as minimum temperature, wind speed, and cloud cover.

Conclusion

Weather changes such as precipitation, minimum temperature, and wind speed are associated with FI in metropolitan and rural areas. In addition, sunshine duration and full moon are significantly associated with FI incidence only in rural areas. Weather factors are associated with FI severity.

Synodic lunar phases and suicide: based on 2605 suicides over 23 years, a full moon peak is apparent in premenopausal women from northern Finland

Suicide data for this study were available for the period of March 1988 to June 2011, and involved 2111 male and 494 female victims from the Finnish province of Oulu. Data for lunar phases during that period were categorised into three groups: new moon (<25% visible), full moon (>75% visible) and other times with values in between. Seasonal effects were controlled with definitions for winter (Nov, Dec, Jan), spring (Feb, Mar, Apr), summer (May, June, July), and autumn (Aug, Sep, Oct). Suicide occurrences during different lunar phases were compared with their expected distribution using multinomial tests with all tests being two-tailed. Statistical significance was set at p < 0.05. No correlation between suicides and moon phase in any of the four seasons was apparent for male victims, but in winter for women it was (p = 0.001). Further analysis of the data revealed that the full moon association was statistically significant only for premenopausal women, defined as female victims younger than 45 years of age. To explain this unexpected finding a number of factors were considered, e.g., the darkness of a northern Finnish winter with increases of SAD and depression especially in premenopausal women, the influence of the lunar periodicity on the menstrual cycle, and cosmogeophysical effects on the humoral and autonomous nervous system.

Lunar Phases and Wildlife-Vehicle Collisions: Application of the Lunar Disk Percentage Method

Simple Summary

The moon is ubiquitous in the night sky and considered an important abiotic factor that influences animal activity. However, little is known about the relationship between moonlight and the daily, monthly, or seasonal frequency of wildlife–vehicle collisions (WVCs). Traditionally, the influence of moonlight on WVCs has been analyzed using the lunar phase (quarters) approach, which evaluates moonlight on a rough scale (only four 25% steps of the visible moon disc and a strict arrangement of phases over time). We used a different approach; we compared WVCs to the actual lunar disc illumination that is based on the specific daily percentage of the visible lunar disk (LDP). Our findings indicated a significant trend of increasing WVC frequencies with increasing LDP at night. We also examined the correlation between the daily numbers of WVCs and LDP for different months and seasons. Positive correlations between LDP and WVCs were stronger at night and during the late autumn–winter months, particularly in December, suggesting the importance of lunar illumination on WVCs. Our study suggests that the LDP approach may provide more possibilities for the evaluation and quantification of WVCs and lunar light relationships than the traditional lunar phase approach. The results can be useful for predicting and reducing WVCs at different times of the lunar illumination cycle and in different seasons.

Abstract

We investigated the relationship between lunar illumination based on the percentage of the visible lunar disk (LDP) and the frequency of wildlife–vehicle collisions (WVCs) in Lithuania. We analyzed WVC frequency during ten 10% LDP intervals to more precisely reflect the relationship between LDP and WVC. The 10% LDP interval approach showed a significant trend of increasing WVC frequencies with an increasing LDP at night. We also examined the correlation between the daily numbers of WVCs and LDP for different months and seasons. The relationship seemed to be stronger at night and during the late autumn–winter months, particularly in December, suggesting the importance of lunar illumination on WVCs. There was a weak positive correlation between LDP and overall daily number of WVCs (r_s = 0.091; p < 0.001) and between LDP and night WVCs (r_s = 0.104; p < 0.001). We found significant positive correlations for winter (December–February) (r_s = 0.118; p = 0.012) and autumn (August–November) (r_s = 0.127; p = 0.007). Our study suggests that the LDP interval approach may provide more possibilities for the evaluation and quantification of WVCs and lunar light relationships than the traditional lunar phase approach.

Differences in Driving Intention Transitions Caused by Driver's Emotion Evolutions

Joining worldwide efforts to understand the relationship between driving emotion and behavior, the current study aimed at examining the influence of emotions on driving intention transition. In Study 1, taking a car-following scene as an example, we designed the driving experiments to obtain the driving data in drivers’ natural states, and a driving intention prediction model was constructed based on the HMM. Then, we analyzed the probability distribution and transition probability of driving intentions. In Study 2, we designed a series of emotion-induction experiments for eight typical driving emotions, and the drivers with induced emotion participated in the driving experiments similar to Study 1. Then, we obtained the driving data of the drivers in eight typical emotional states, and the driving intention prediction models adapted to the driver’s different emotional states were constructed based on the HMM severally. Finally, we analyzed the probabilistic differences of driving intention in divers’ natural states and different emotional states, and the findings showed the changing law of driving intention probability distribution and transfer probability caused by emotion evolution. The findings of this study can promote the development of driving behavior prediction technology and an active safety early warning system.

Measuring performance of road transportation industry in China in terms of integrated environmental efficiency in view of Streaming Data

Road transportation industry not only promotes economic development, but also brings many environmental issues in China. It is necessary to evaluate the integrated environmental efficiency of road transportation industry, including carbon dioxide emissions, traffic accident and traffic noise which is a Steaming Data. In this study, a parallel DEA model with sub-system preference is proposed to measuring the integrated environmental efficiency of road transportation industry in 2013-2017 considering various undesirable outputs. Then, the convergence analysis approach is employed to investigate the regional differences in terms of efficiency of road transportation. The empirical results show that the overall integrated environmental efficiency underperformed nationwide, and the passenger transportation sub-system outperformed freight transportation when the latter is restricted in some hours. From a regional perspective, the efficiency performances show downward trends in areas eastern, central and western. The passenger transportation sub-system outperforms in eastern area and the freight transportation outperforms in central area. Furthermore, the convergence analysis results indicate that the integrated environmental efficiency in eastern and western areas not only converged to their own stable levels but also that the differences in the integrated environmental efficiency between eastern and western areas are condensing. The contributions of this study lie in not only proposing a parallel DEA model with sub-system preference and considering the streaming data, but also providing suggestions to improving the road transportation industry in terms of integrated environmental efficiency. Finally, the research limitations and further research directions were conducted.