Safety and immunogenicity of an inactivated SARS-CoV-2 vaccine (FAKHRAVAC®) in healthy adults aged 18-55 years: Randomized, double-blind, placebo-controlled, phase I clinical trial.

Background: The FAKHRAVAC®, an inactivated SARS-CoV-2 vaccine, was assessed for safety and immunogenicity.

Methods And Findings: In this double-blind, placebo-controlled, phase I trial, we randomly assigned 135 healthy adults between 18 and 55 to receive vaccine strengths of 5 or 10 μg/dose or placebo (adjuvant only) in 0-14 or 0-21 schedules. This trial was conducted in a single center in a community setting.

Impact of an exclusive narrow automated vehicle lane on adjacent lane driver behavior.

This study contributes to understanding the behavioral impacts of infrastructure adaptation to Automated Vehicles (AVs) on non-AV drivers. It attempts to answer the question of how a narrow (9 ft) lane dedicated to AVs would affect the behavior of drivers in terms of safety measures who are driving in the adjacent lane to the right. To this end, a custom designed driving simulator world was designed mimicking the Interstate 15 smart corridor in San Diego.

Computational model for behavior shaping as an adaptive health intervention strategy.

Adaptive behavioral interventions that automatically adjust in real-time to participants' changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation.

Red-light running violation prediction using observational and simulator data.

In the United States, 683 people were killed and an estimated 133,000 were injured in crashes due to running red lights in 2012. To help prevent/mitigate crashes caused by running red lights, these violations need to be identified before they occur, so both the road users (i.e.

Modeling driver stop/run behavior at the onset of a yellow indication considering driver run tendency and roadway surface conditions.

The ability to model driver stop/run behavior at signalized intersections considering the roadway surface condition is critical in the design of advanced driver assistance systems. Such systems can reduce intersection crashes and fatalities by predicting driver stop/run behavior. The research presented in this paper uses data collected from two controlled field experiments on the Smart Road at the Virginia Tech Transportation Institute (VTTI) to model driver stop/run behavior at the onset of a yellow indication for different roadway surface conditions.