Age group differences in collision risk

Introduction

The purpose of the current study was to examine differences in factors associated with self-reported collision involvement of three age groups of drivers based on a large representative sample of Ontario adults. Method: This study was based on data from the CAMH Monitor, an ongoing cross-sectional telephone survey of Ontario adults 18 years and older from 2002 to 2005. Three age groups were examined: 18-34 (n = 1,294), 35-54 (n = 2,428), and 55+ (n = 1,576). For each age group sample, a logistic regression analysis was conducted of self-reported collision involvement in the last 12 months by risk factor measures of driving exposure (kilometers driven in a typical week, driving is stressful, and driving on busy roads), consuming five or more drinks of alcohol on one occasion (past 12 months), cannabis use (lifetime, and past 12 months), and driving after drinking among drinkers (past 12 months), controlling for demographics (gender, region, income, and marital status). Results: The study identified differences in factors associated with self-reported collision involvement of the three age groups of adult drivers. The logistic regression model for the youngest group revealed that drivers who reported that driving was stressful at least some of the time, drank five or more drinks on an occasion, and drove after drinking had an increased risk of collision involvement. For the middle age group, those who reported using cannabis in the last 12 months had significantly increased odds of reporting collision involvement. None of the risk factor measures showed significant associations with collision risk for older drivers (aged 55+). Impact: The results suggest potential areas for intervention and new directions for future research.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Learning and development factors related to perceptions of job content and hierarchical plateauing

This study applied theory from the employee learning and development literature to examine factors related to employees' perceptions of being job content plateaued and hierarchically plateaued. Results indicated that both types of plateauing were related to support from top management, career planning, job involvement, and education level. Furthermore, career exploration, motivation to learn, organizational tenure, and job tenure were related to perceptions of hierarchical plateauing, while supervisor support was related to job content plateauing. Additionally, the two types of plateauing differed in the relative strength of their relationship with the variables studied. Implications and future research suggestions are provided. Copyright © 1999 John Wiley & Sons, Ltd.     

Biodegradation of N,N-bis(carboxymethyl)-L-glutamate and its utilization as sole source of carbon,nitrogen, and energy by a Rhizobium radiobacter strain in seawater

Biodegradation of N,N-bis(carboxymethyl)-L-glutamate and its utilization by micro-organisms in marine environments were studied in Organization of Economic Development and Cooperation (OECD) screening tests and with pure bacterial cultures. Biodegradation in excess of 60% was achieved in closed bottle tests in less than 60 days, suggesting complete degradation. The bacterial strain isolated from marine sandy sediment and utilizing N,N-bis(carboxymethyl)-L-glutamate as sole source of carbon, nitrogen, and energy was identified as Rhizobium radiobacter. The strain was capable to mineralize N,N-bis(carboxymethyl)-L-glutamate in seawater and in synthetic media containing 0–60 g L^?1 sea salts. Growth and adaptation studies indicated that N-carboxymethyl-L-glutamate and L-glutamate are main metabolites.