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Autonomous Vehicles (AV) technology is emerging. Field tests on public roads have been on going in several states in the US as well as in Europe and Asia. During the US public road tests, crashes with AV involved happened, which becomes a concern to the public. Most previous studies on AV safety relied heavily on assessing drivers’ performance and behaviors in a simulation environment and developing automated driving system performance in a closed field environment. However, contributing factors and the mechanism of AV-related crashes have not been comprehensively and quantitatively investigated due to the lack of field AV crash data. By harnessing California’s Report of Traffic Collision Involving an Autonomous Vehicle Database, which includes the AV crash data from 2014 to 2018, this paper investigates by far the most current and complete AV crash database in the US using statistical modeling approaches that involve both ordinal logistic regression and CART classification tree. The quantitative analysis based on ordinal logistic regression and CART models has successfully explored the mechanism of AV-related crash, via both perspectives of crash severity and collision types. Particularly, the CART model reveals and visualize the hierarchical structure of the AV crash mechanism with knowledge of how these traffic, roadway, and environmental contributing factors can lead to crashes of various serveries and collision types. Statistical analysis results indicate that crash severity significantly increases if the AV is responsible for the crash. The highway is identified as the location where severe injuries are likely to happen. AV collision types are affected by whether the vehicle is on automated driving mode, whether the crashes involve pedestrians/cyclists, as well as the roadway environment. The method used in this research provides a proven approach to statistically analyze and understand AV safety issues. And this benefit is potential be even enhanced with an increasing sample size of AV-related crashes records in the future. The comprehensive knowledge obtained ultimately facilitates assessing and improving safety performance of automated vehicles. [ABSTRACT FROM AUTHOR]

Recent years have seen tremendous advances in the scientific study of networks, as more and larger data sets of relationships among nodes have become available in many different fields. This has led to pathbreaking discoveries of near-universal network behavior over time, including the principle of preferential attachment and the emergence of scaling in complex networks. Missing from the set of network analysis methods to date is a measure that describes for each node how its relationship (or links) with other nodes changes from one period to the next. Conventional measures of network change for the most part show how the degrees of a node change; these are scalar comparisons. Our contribution is to use, for the first time, the cosine similarity to capture not just the change in degrees of a node but its relationship to other nodes. These are vector (or matrix)-based comparisons, rather than scalar, and we refer to them as “rewiring” coefficients. We apply this measure to three different networks over time to show the differences in the two types of measures. In general, bigger increases in our rewiring measure are associated with larger increases in network density, but this is not always the case. [ABSTRACT FROM AUTHOR]

Despite considerable air pollution prevention and control measures that have been put into practice in recent years, outdoor air pollution remains one of the most important risk factors for health outcomes. To identify the potential research gaps, we conducted a scoping review focused on health outcomes affected by outdoor air pollution across the broad research area. Of the 5759 potentially relevant studies, 799 were included in the final analysis. The included studies showed an increasing publication trend from 1992 to 2008, and most of the studies were conducted in Asia, Europe, and North America. Among the eight categorized health outcomes, asthma (category: respiratory diseases) and mortality (category: health records) were the most common ones. Adverse health outcomes involving respiratory diseases among children accounted for the largest group. Out of the total included studies, 95.2% reported at least one statistically positive result, and only 0.4% showed ambiguous results. Based on our study, we suggest that the time frame of the included studies, their disease definitions, and the measurement of personal exposure to outdoor air pollution should be taken into consideration in any future research. The main limitation of this study is its potential language bias, since only English publications were included. In conclusion, this scoping review provides researchers and policy decision makers with evidence taken from multiple disciplines to show the increasing prevalence of outdoor air pollution and its adverse effects on health outcomes. [ABSTRACT FROM AUTHOR]

The tetraploid wheat species Triticum turgidum and Triticum timopheevii are morphologically similar, and misidentification of material collected from the wild is possible. We compared published sequences for the Ppd-A1, Ppd-B1 and Ppd-G1 genes from multiple accessions of T. turgidum and T. timopheevii and devised a set of four polymerase chain reactions (PCRs), two specific for Ppd-B1 and two for Ppd-G1. We used these PCRs with 51 accessions of T. timopheevii and 20 of T. turgidum. Sixty of these accessions gave PCR products consistent with their taxon identifications, but the other eleven accessions gave anomalous results: ten accessions that were classified as T. turgidum were identified as T. timopheevii by the PCRs, and one T. timopheevii accession was typed as T. turgidum. We believe that these anomalies are not due to errors in the PCR tests because the results agree with a more comprehensive analysis of genome-wide single nucleotide polymorphisms, which similarly suggest that these eleven accessions have been misclassified. Our results therefore show that the accepted morphological tests for discrimination between T. turgidum and T. timopheevii might not be entirely robust, but that species identification can be made cheaply and quickly by PCRs directed at the Ppd-1 gene. [ABSTRACT FROM AUTHOR]

Introduction: There is evidence that greater neighbourhood walkability (i.e., neighbourhoods with more amenities and well-connected streets) is associated with higher levels of total walking in Europe and in Asia, but it remains unclear if this association holds in the Canadian context and in chronic disease populations. We examined the relationships of different walkability measures to biosensor-assessed total walking (i.e., steps/day) in adults with type 2 diabetes living in Montreal (QC, Canada). Materials and Methods: Participants (60.5±10.4 years; 48.1% women) were recruited through McGill University-affiliated clinics (June 2006 to May 2008). Steps/day were assessed once per season for one year with pedometers. Neighbourhood walkability was evaluated through participant reports, in-field audits, Geographic Information Systems (GIS)-derived measures, and the Walk Score®. Relationships between walkability and daily steps were estimated using Bayesian longitudinal hierarchical linear regression models (n = 131). Results: Participants who reported living in the most compared to the least walkable neighbourhoods completed 1345 more steps/day (95% Credible Interval: 718, 1976; Quartiles 4 versus 1). Those living in the most compared to the least walkable neighbourhoods (based on GIS-derived walkability) completed 606 more steps per day (95% CrI: 8, 1203). No statistically significant associations with steps were observed for audit-assessed walkability or the Walk Score®. Conclusions: Adults with type 2 diabetes who perceived their neighbourhoods as more walkable accumulated more daily steps. This suggests that knowledge of local neighborhood features that enhance walking is a meaningful predictor of higher levels of walking and an important component of neighbourhood walkability. [ABSTRACT FROM AUTHOR]