Background and aim
The rate of drug poisoning (or overdose) deaths in England and Wales has risen annually since 2010. We aimed to measure seasonal and other cyclical changes in these deaths within ...years.
Methods
We used the daily count of deaths due to drug poisoning in England and Wales between 1 January 1993 and 31 December 2018 to investigate variation by season, weekday, week‐of‐month and public holiday. We used Poisson regression to estimate the count of deaths per day for each of these variables and peak‐to‐low ratios. We also stratified the analysis by time period and whether an opioid was mentioned on the death certificate.
Results
78 583 deaths occurred between 1993 and 2018, increasing from 5.50 (95% confidence interval CI = 5.24–5.77) per day in 1993 to 13.18 (95% CI = 12.66–13.72) per day in 2018. The rate peaked in Spring and was 1.07 (95% CI = 1.04–1.09) times higher in April than in October. This seasonal pattern emerged in the past decade and was only present for opioid‐related deaths. The rate at New Year was 1.28 (95% CI = 1.17–1.41) times higher than on non‐holidays; and this peak was only present for deaths that were not related to opioids. The rate was higher on Saturday than on other weekdays. We did not find evidence that the number of deaths varied by week‐of‐month.
Conclusions
Deaths due to drug poisoning in England and Wales are seasonal and peak in Spring and briefly at New Year. This suggests a role of external triggers. These seasonal variations are small compared with long‐term increases in drug‐related deaths.
Traditional nonintelligent signal control systems are typically used in road traffic signal systems, which cannot provide optimal guidance and have low traffic efficiency during rush hour. This study ...proposes a traffic signal phase dynamic timing optimization strategy based on a time convolution network and attention mechanism to improve traffic efficiency at intersections. The corresponding optimization was performed after predicting traffic conditions with different impacts using the digital twinning technique. This method uses a time-convolution network to extract the cross-time nonlinear characteristics of traffic data at road intersections. An attention mechanism was introduced to capture the relationship between the importance distribution and duration of the historical time series to predict the traffic flow at an intersection. The interpretability and prediction accuracy of the model was effectively improved. The model was tested using traffic flow data from a signalized intersection in Shangrao, Jiangxi Province, China. The experimental results indicate that the model generated by training has a strong learning ability for the temporal characteristics of traffic flow. The model has high prediction accuracy, good optimization results, and wide application prospects in different scenarios.
Purpose
The effects of travel motivation and emotional experience on both tourist satisfaction and destination loyalty are recognized and have been extensively researched as key factors in tourism ...success. However, the structural relationships between these factors, considering the mediating effects of eudaimonic well-being (optimal psychological functioning), have been scarcely investigated in the consumer tourist behaviors literature. This study aims to develop an integrated model explaining the impact of travel motivation and emotional experience on tourist satisfaction and destination loyalty, mediated by eudaimonic well-being in the realm of domestic tourism.
Design/methodology/approach
A quantitative survey was conducted with 321 domestic tourists visiting Aqaba in Jordan; structural equation modeling was used to analyze the empirical data.
Findings
The findings of this study indicate that both travel motivation and emotional experience have a direct effect on eudaimonic well-being and that eudaimonic well-being has a direct effect on both tourist satisfaction and destination loyalty. Additionally, travel motivation and emotional experience have significant indirect impacts on post-consumption behaviors mediated by eudaimonic well-being.
Originality/value
This study contributes to the literature on consumer behavior in a tourism context by developing a fresh model that improves theoretical knowledge of the relationships between travel motivation, emotional experience and eudaimonic well-being, which underlie tourist satisfaction and destination loyalty formation. This study also advances theoretical understanding of the key roles of eudaimonic well-being in the tourist experience. Managerial implications of these findings are discussed.
China is confronting increasing ozone (O3) pollution that worsens air
quality and public health. Extreme O3 pollution occurs more
frequently under special events and unfavorable meteorological ...conditions.
Here we observed significantly elevated maximum daily 8 h average (MDA8)
O3 (up to 98 ppb) during the Chinese National Day holiday (CNDH) in
2018 throughout China, with a prominent rise by up to 120 % compared to
the previous week. The air quality model shows that increased precursor
emissions and regional transport are major contributors to the elevation. In
the Pearl River Delta region, the regional transport contributed up to 30 ppb O3 during the CNDH. Simultaneously, aggravated health risk occurs
due to high O3, inducing 33 % additional deaths throughout China.
Moreover, in tourist cities such as Sanya, daily mortality even increases
significantly from 0.4 to 1.6. This is the first comprehensive study to
investigate O3 pollution during the CNDH at the national level, aiming to
arouse more focus on the O3 holiday impact of the public.
Skin cancer is caused by solar UVR, which is also essential for vitamin D production. DNA damage (thymine dimers: T-T dimers) and vitamin D (25(OH)D) synthesis are both initiated by solar UVB. We ...aimed to investigate the simultaneous adverse and beneficial effects of solar UVB exposure in holidaymakers. Sun-seekers and skiers (n=71) were observed over 6 days through on-site monitoring, personal diary entries, and recording of personal UVB exposure doses with electronic dosimeters. Urine and blood samples were analyzed for T-T dimers and 25(OH)D, respectively. The volunteers had a statistically significant increase in vitamin D. There were strong associations between UVB exposure and post-holiday levels of T-T dimers and vitamin D, as well as between post-holiday T-T dimers and vitamin D. We conclude that UVB-induced vitamin D synthesis is associated with considerable DNA damage in the skin. These data, on two major health predictors, provide a basis for further field studies that may result in better understanding of the risks and benefits of “real life” solar exposure. However, vitamin D status can be improved more safely through the use of vitamin D dietary supplements.
Reported high drug use at music festivals coupled with factors such as public urination can lead to the direct release of illicit drugs into the environment. Glastonbury Festival 2019 had 203,000 ...attendees, its site is intercepted by the Whitelake River providing a direct route for illicit drug pollution into the local environment. We tested for popular illicit drugs such as cocaine and MDMA in the river upstream and downstream of the festival site as well as in the neighbouring Redlake River. Both rivers were sampled the weeks before, during and after the festival. Cocaine, benzoylecgonine and MDMA were found at all sample sites; concentrations, and mass loads (mass carried by the river per unit of time) were significantly higher in the Whitelake site, downstream of the festival. MDMA mass loads were 104 times greater downstream in comparison to upstream sites (1.1–61.0 mg/h vs 114.7 mg/h; p < .01). Cocaine and benzoylecgonine mass loads were also 40 times higher downstream of the festival (1.3–4.2 mg/h vs 50.4 mg/h; p < .01) (22.7–81.4 mg/h vs 854.6 mg/h; p < .01). MDMA reached its highest level during the weekend after the festival with a concentration of 322 ng/L. This concentration is deemed harmful to aquatic life using Risk Quotient assessment (RQ) and provides evidence of continuous release after the festival due to leaching of MDMA from the site. Cocaine and benzoylecgonine concentrations were not at levels deemed harmful to aquatic life according to RQ assessment yet were three times higher than MDMA concentrations. Redlake River experienced no significant changes (p > .05) in any illicit drug levels, further confirming that drug release was likely dependent on the festival site. The release of environmentally damaging levels of illicit drugs into Whitelake River during the period of Glastonbury Festival suggests an underreported potential source of environmental contamination from greenfield festival sites.
•Illicit drugs were found in the river running through the Glastonbury Festival.•MDMA was found at environmentally damaging levels in the local aquatic ecosystem.•MDMA release was delayed suggesting sorption and subsequent leaching from the site.•Levels of cocaine were high enough to disrupt the lifecyle of the European eel.•Use of treatment wetlands and preventing public urination could reduce the issue.
Leisure engagement plays a key role in individuals' well-being. While the majority of research focuses on the health and wellness benefits of everyday leisure participation, in recent years, ...vacation-taking, as an extraordinary leisure type, attracts scholarly interest from various disciplines to investigate how it contributes to individuals' subjective well-being. Nevertheless, there is still no cohesive understanding of this relationship. In this integrative review, we reviewed 125 articles on this topic, paid particular attention to understanding the different ways and conditions under which people can benefit from vacation-taking, and we highlighted the potential pathways (i.e., how and why) through which leisure vacation can increase well-being. Meanwhile, we offer a future research agenda including cross-level investigations of vacationers' well-being, integrating the influences from individual, professional, and social forces.
City-wide traffic flow forecasting is a significant function of the Intelligent Transport System (ITS), which plays an important role in city traffic management and public travel safety. However, ...this remains a very challenging task that is affected by many complex factors, such as road network distribution and external factors (e.g., weather, accidents, and holidays). In this paper, we propose a deep-learning-based multi-branch model called TFFNet (Traffic Flow Forecasting Network) to forecast the short-term traffic status (flow) throughout a city. The model uses spatiotemporal traffic flow matrices and external factors as its input and then infers and outputs the future short-term traffic status (flow) of the whole road network. For modelling the spatial correlations of the traffic flows between current and adjacent road segments, we employ a multi-layer fully convolutional framework to perform cross-correlation calculation and extract the hierarchical spatial dependencies from local to global scales. Also, we extract the temporal closeness and periodicity of traffic flow from historical observations by constructing a high-dimensional tensor comprised of traffic flow matrices from three fragments of the time axis: recent time, near history, and distant history. External factors are also considered and trained with a fully connected neural network and then fused with the output of the main component of TFFNet. The multi-branch model is automatically trained to fit complex patterns hidden in the traffic flow matrices until reaching pre-defined convergent criteria via the back-propagation method. By constructing a rational model input and network architecture, TFFNet can capture spatial and temporal dependencies simultaneously from traffic flow matrices during model training and outperforms other typical traffic flow forecasting methods in the experimental dataset.
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