Exploring nighttime pedestrian crash patterns at intersection and segments: Findings from the machine learning algorithm.

INTRODUCTION: Pedestrian safety at nighttime is an ongoing critical traffic safety concern. Although poor visibility is primarily associated with nighttime pedestrian crashes, other contributing factors such as humans, vehicles, roadways, and environmental factors interact with each other to cause a crash. Additionally, the pattern of nighttime pedestrian crashes differs significantly according to the intersection and segment location, which requires further exploration. DATA: This study applied Association Rules Mining (ARM), a rule-based machine learning method, to reveal the association of nighttime pedestrian crash risk factors according to the intersection and segment locations using 2,505 nighttime pedestrian fatal and injury crashes in Louisiana (2015-2019). RESULTS AND CONCLUSIONS: Based on the generated rules, the results show that nighttime pedestrian crashes at the intersection are associated with right-turn vehicle movement, older drivers (>64 years) at the high-speed intersection, senior pedestrians (>64 years) in rainy weather conditions, violation by pedestrian age group '<15 years', and alcohol-intoxicated pedestrian violation in business/industrial areas. Additionally, 'careless operation' at the intersection is associated with alcohol-involved drivers. Most of the nighttime pedestrian crashes at segments are associated with roadways with no physical separation and the absence of streetlights. Driver alcohol involvement and their physical condition (inattentive/distracted) are also associated with pedestrian crashes associated at the segment location at night. Other segment pedestrian crashes are linked to the interstate in dark conditions, open country locations, and high-speed roadways. Additionally, the crash site investigation identified several critical pedestrian safety concerns including the lack of crosswalk facilities, high driveway density, and pedestrian behavioral patterns (e.g., crossing at roadway segments close to the intersection location). PRACTICAL APPLICATIONS: The findings of this study can be used for selecting the appropriate countermeasures based on a case-by-case basis. The exposure patterns can be used in educational campaigns to strategically reduce nighttime pedestrian crashes.

Identifying roadway departure crash patterns on rural two-lane highways under different lighting conditions: Association knowledge using data mining approach.

INTRODUCTION: More than half of all fatalities on U.S. highways occur due to roadway departure (RwD) each year. Previous research has explored various risk factors that contribute to RwD crashes, however, a comprehensive investigation considering the effect of lighting conditions has been insufficiently addressed. DATA: Using the Louisiana Department of Transportation and Development crash database, fatal and injury RwD crashes occurring on rural two-lane (R2L) highways between 2008-2017 were analyzed based on daylight and dark (with and without streetlight). METHOD: This research employed a safe system approach to explore meaningful complex interactions among multidimensional crash risk factors. To accomplish this, an unsupervised data mining algorithm association rules mining (ARM) was utilized. RESULTS AND CONCLUSIONS: Based on the generated rules, the findings reveal several interesting crash patterns in the daylight, dark-with-streetlight, and dark-no-streetlight, emphasizing the importance of investigating RwD crash patterns depending on the lighting conditions. In daylight condition, fatal RwD crashes are associated with cloudy weather conditions, distracted drivers, standing water on the roadway, no seat belt use, and construction zones. In dark lighting condition (with and without streetlight), the majority of the RwD crashes are associated with alcohol/drug involvement, young drivers (15-24 years), driver condition (e.g., inattentive, distracted, illness/fatigued/asleep), and colliding with animal(s). PRACTICAL APPLICATIONS: The findings also reveal how certain driver behavior patterns are connected to RwD crashes, such as a strong association between alcohol/drug intoxication and no seat belt usage in the dark-no-streetlight condition. Based on the identified crash patterns and behavioral characteristics under different lighting conditions, the findings could aid researchers and safety specialists in developing the most effective RwD crash mitigation strategies.

The Mechanobiology of Endothelial-to-Mesenchymal Transition in Cardiovascular Disease.

Endothelial cells (ECs) lining the cardiovascular system are subjected to a highly dynamic microenvironment resulting from pulsatile pressure and circulating blood flow. Endothelial cells are remarkably sensitive to these forces, which are transduced to activate signaling pathways to maintain endothelial homeostasis and respond to changes in the environment. Aberrations in these biomechanical stresses, however, can trigger changes in endothelial cell phenotype and function. One process involved in this cellular plasticity is endothelial-to-mesenchymal transition (EndMT). As a result of EndMT, ECs lose cell-cell adhesion, alter their cytoskeletal organization, and gain increased migratory and invasive capabilities. EndMT has long been known to occur during cardiovascular development, but there is now a growing body of evidence also implicating it in many cardiovascular diseases (CVD), often associated with alterations in the cellular mechanical environment. In this review, we highlight the emerging role of shear stress, cyclic strain, matrix stiffness, and composition associated with EndMT in CVD. We first provide an overview of EndMT and context for how ECs sense, transduce, and respond to certain mechanical stimuli. We then describe the biomechanical features of EndMT and the role of mechanically driven EndMT in CVD. Finally, we indicate areas of open investigation to further elucidate the complexity of EndMT in the cardiovascular system. Understanding the mechanistic underpinnings of the mechanobiology of EndMT in CVD can provide insight into new opportunities for identification of novel diagnostic markers and therapeutic interventions.

Multiscale Experimental and Computational Modeling Approaches to Characterize Therapy Delivery to the Heart from an Implantable Epicardial Biomaterial Reservoir.

Delivery of therapeutic-laden biomaterials to the epicardial surface of the heart presents a promising method of treating a variety of diseased conditions by offering targeted, localized release with limited systemic recirculation and enhanced myocardial tissue uptake. A vast range of biomaterials and therapeutic agents using this approach been investigated. However, the fundamental factors that govern transport of the drug molecules from the biomaterials to the tissue are not well understood. Here, the transport of a drug analog from a biomaterial reservoir to the epicardial surface is characterized using experimental techniques and microscale modeling. Using the experimentally determined parameters, a multiscale model of transport is developed. The model is then used to study the effect of important design parameters such as loading conditions, biomaterial geometry, and orientation relative to the cardiac fibers on drug delivery to the myocardium. The simulations highlight the significance of the cardiac fiber anisotropy as a crucial factor in governing drug distribution on the epicardial surface and limiting factor for penetration into the myocardium. The multiscale model can be useful for rapid iteration of different device concepts and for determination of designs for epicardial drug delivery that may be optimal and most promising for the ultimate therapeutic goal.

Sustained release of targeted cardiac therapy with a replenishable implanted epicardial reservoir.

The clinical translation of regenerative therapy for the diseased heart, whether in the form of cells, macromolecules or small molecules, is hampered by several factors: the poor retention and short biological half-life of the therapeutic agent, the adverse side effects from systemic delivery, and difficulties with the administration of multiple doses. Here, we report the development and application of a therapeutic epicardial device that enables sustained and repeated administration of small molecules, macromolecules and cells directly to the epicardium via a polymer-based reservoir connected to a subcutaneous port. In a myocardial infarct rodent model, we show that repeated administration of cells over a four-week period using the epicardial reservoir provided functional benefits in ejection fraction, fractional shortening and stroke work, compared to a single injection of cells and to no treatment. The pre-clinical use of the therapeutic epicardial reservoir as a research model may enable insights into regenerative cardiac therapy, and assist the development of experimental therapies towards clinical use.

Comparative Dynamics and Sequence Dependence of DNA and RNA Binding to Single Walled Carbon Nanotubes.

Noncovalent polymer-single walled carbon nanotube (SWCNT) conjugates have gained recent interest due to their prevalent use as electrochemical and optical sensors, SWCNT-based therapeutics, and for SWCNT separation. However, little is known about the effects of polymer-SWCNT molecular interactions on functional properties of these conjugates. In this work, we show that SWCNT complexed with related polynucleotide polymers (DNA, RNA) have dramatically different fluorescence stability. Surprisingly, we find a difference of nearly 2500-fold in fluorescence emission between the most fluorescently stable DNA-SWCNT complex, C30 DNA-SWCNT, compared to the least fluorescently stable complex, (AT)7A-(GU)7G DNA-RNA hybrid-SWCNT. We further reveal the existence of three regimes in which SWCNT fluorescence varies nonmonotonically with SWCNT concentration. We utilize molecular dynamics simulations to elucidate the conformation and atomic details of SWCNT-corona phase interactions. Our results show that variations in polynucleotide sequence or sugar backbone can lead to large changes in the conformational stability of the polymer SWCNT corona and the SWCNT optical response. Finally, we demonstrate the effect of the coronae on the response of a recently developed dopamine nanosensor, based on (GT)15 DNA- and (GU)15 RNA-SWCNT complexes. Our results clarify several features of the sequence dependence of corona phases produced by polynucleotides adsorbed to single walled carbon nanotubes, and the implications for molecular recognition in such phases.