A Quantitative Model for Truck Parking Utilization with Hours of Service Regulations

Continual growth in traffic volume on U.S. Highways and insufficient parking for commercial trucking vehicles has led to significant safety concerns for truck drivers. Hours of Service (HOS) regulations dictate driving and rest periods of truck drivers. When a truck driver must stop as designated by the HOS regulations and the nearest parking location is at capacity, the trucker must either continue driving past the HOS limit or park in an undesignated and possibly illegal or unsafe spot such as an off-ramp. The combination of these two variables play an important role in the safety of truck drivers on a daily basis. Previous research on truck parking shortages has followed a survey-based approach while research on HOS regulations in conjunction with truck routing and driver scheduling has not included the full suite of HOS regulations as well as restrictions on parking availability. Current research techniques do not take into account parking capacity on a driver’s route while following HOS regulations. Because there are limitations governing where along a route a driver can rest, including some customer locations and parking locations at capacity, these models do not prove to be an accurate measure of trip planning for truck drivers. This research aims to develop a mathematical model to link truck parking with hours of service regulations in order to determine feasible routes for truck drivers and optimal truck parking locations on the highway network

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe