Background: Across the nation, growing numbers of individuals are exploring the use of cannabis for medical or recreational purposes, and the proportion of cannabis-positive drivers involved in fatal crashes increased from 8 percent in 2013 to 17 percent in 2014, raising concerns about the impact of cannabis use on driving. Previous studies have demonstrated that cannabis use is associated with impaired driving performance, but thus far, research has primarily focused on the effects of acute intoxication.
Methods: The current study assessed the potential impact of cannabis use on driving performance using a customized driving simulator in non-intoxicated, heavy, recreational cannabis users and healthy controls (HCs) without a history of cannabis use.
Results: Overall, cannabis users demonstrated impaired driving relative to HC participants with increased accidents, speed, and lateral movement, and reduced rule-following. Interestingly, however, when cannabis users were divided into groups based on age of onset of regular cannabis use, significant driving impairment was detected and completely localized to those with early onset (onset before age 16) relative to the late onset group (onset ≥16 years old). Further, covariate analyses suggest that impulsivity had a significant impact on performance differences.
Conclusions: Chronic, heavy, recreational cannabis use was associated with worse driving performance in non-intoxicated drivers, and earlier onset of use was associated with greater impairment. These results may be related to other factors associated with early exposure such as increased impulsivity.
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http://dx.doi.org/10.1016/j.drugalcdep.2019.107771 | DOI Listing |
J Environ Manage
January 2025
Tetra Tech, Inc., P.O. Box 14409, Research Triangle Park, NC, 27709, United States. Electronic address:
Due to the recent improved availability of global and regional climate change (CC) models and associated data, the projected impact of CC on urban stormwater management is well documented. However, most studies are based on simplified design storm analysis and unit-area runoff models; evaluations of the long-term, continuous hydrologic response of extensive stormwater control measures (SCM) implementation under future CC scenarios are limited. Moreover, channel stability in response to CC is seldom evaluated due to the input data required to develop a long-term, continuous sediment transport model.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Department of Physical-Chemistry, Complutense University of Madrid, Madrid, Spain.
Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Agricultural Engineering, Technical and Vocational University, Tehran, Iran.
With the growing need for sustainable transportation solutions, understanding the relationship between driving characteristic parameters, vehicle type, and their impact on emissions and fuel consumption over real driving scenarios is becoming increasingly important. In this paper, four conventional vehicles and one hybrid vehicle with different technologies were compared in four distinct routes in Tehran city. Nineteen real driving cycles were generated using widely employed K-means and PCA algorithms.
View Article and Find Full Text PDFTraffic Inj Prev
January 2025
China Merchants Chongqing Communications Technology Research & Design Institute Co., Ltd, Chongqing, China.
Objective: This study aimed to analyze the influence of different tunnel reinforcement measures on drivers and to evaluate the associated driving safety risks.
Methods: Experimental data of driving behavior and physiological response were collected under different driving simulation scenarios, such as cover arch erection, corrugated steel, grouting, Steel strips, and fire; an evaluation index system was established based on electrocardiographic (ECG), electrodermal activity(EDA), standard deviation of speed (SDSP), Steering Entropy(SE), standard deviation of lateral position (SDLP) and other indices. The classical domain rank standard of each evaluation index was divided using K-Means algorithm, and a synthetic evaluation matter-element model was established to comprehensively evaluate and analyze the safety risks of each scenario.
Traffic Inj Prev
January 2025
School of Traffic & Transportation Engineering, Changsha University of Science & Technology, Changsha, Hunan, China.
Objective: This study aims to investigate the causes of 2-vehicle collisions involving an autonomous vehicle (AV) and a conventional vehicle (CV). Prior research has primarily focused on the causes of crashes from the perspective of AVs, often neglecting the interactions with CVs.
Method: To address this limitation, the study proposes a classification framework for crash causation patterns in 2-vehicle collisions involving an AV and a CV, considering their interactions.
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