The role of personality characteristics in young adult driving

BACKGROUND: Motor vehicle injury is the major cause of mortality among young adults. Information about the individual characteristics of those who drive dangerously could enhance traffic safety programs. The goal of this research was to examine the association between various personality-related characteristics and risky driving behaviors. METHODS: Young adults in Michigan, USA (n = 5,362) were surveyed by telephone regarding several personality factors (risk-taking, hostility, aggression, tolerance of deviance, achievement expectations) and driving behaviors (competitive driving, risk-taking driving, high-risk driving, aggressive driving, and drink/driving). Michigan driver records were obtained to examine offenses, serious offenses, driving offense points, crashes and serious crashes in the three pre-interview years. Multivariate regression analyses, adjusting for age, race, and marital status were conducted separately by sex to identify personality factors related to driving. RESULTS: For men and women, greater risk-taking propensity, physical/verbal hostility, aggression, and tolerance of deviance were significant predictors of a competitive attitude toward driving, risk-taking driving, high-risk driving, driving aggression, and drink/driving. Greater risk-taking propensity, physical/verbal hostility, aggression, and to a small degree, expectations for achievement predicted higher numbers of offenses, serious offenses, and points. CONCLUSION: Traffic safety policies and programs could be enhanced through recognition of the role personality factors play in driving behavior and the incorporation of this knowledge into the design and implementation of interventions that modify the behaviors associated with them.     

PREDICTABILITY OF SURFACE WATER POLLUTION LOADING IN PENNSYLVANIA USING WATERSHED‐BASED LANDSCAPE MEASUREMENTS1

ABSTRACT: We formally evaluated the relationship between landscape characteristics and surface water quality in the state of Pennsylvania (USA) by regressing two different types of pollutant responses on landscape variables that were measured for whole watersheds. One response was the monthly exported mass of nitrogen estimated from field measurements, while the other response was a GIS‐modeled pollution potential index. Regression models were built by the stepwise selection protocol, choosing an optimal set of landscape predictors. After factoring out the effect of physiography, the dominant predictors were the proportion of “annual herbaceous” land and “total herbaceous” land for the nitrogen loading and pollution potential index, respectively. The strength of these single predictors is encouraging because the marginal land cover proportions are the simplest landscape measurements to obtain once a land cover map is in hand; however, the optimal set of predictors also included several measurements of spatial pattern. Thus, for watersheds at this general hierarchical scale, gross landscape pattern may be an important influence on instream pollution loading. Overall, there is strong evidence that using landscape measurements alone, obtained solely from remotely sensed data, can explain most of the water quality variability (R²= approx. 0.75) within these watersheds.     

Efficient and recyclable palladium enriched magnetic nanocatalyst for reduction of toxic environmental pollutants

In this paper, highly stable, powerful, and recyclable magnetic nanoparticles tethered N-heterocyclic carbene-palladium(II) ((CH₃)₃[email protected]₃O₄) as magnetic nanocatalyst was successfully synthesized from a simplistic multistep synthesis under aerobic conditions through easily available low-cost chemicals. Newly synthesized (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst was characterized from various analytical tools and catalytic potential of the (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst was studied for the catalytic reduction of toxic 4-nitrophenol (4-NP), hexavalent chromium (Cr(VI)), Methylene Blue (MB) and Methyl Orange (MO) at room temperature in aqueous media. UV-Visible spectroscopy was employed to monitor the reduction reactions. New (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst exhibited excellent catalytic activity for the reduction of toxic environmental pollutants. Moreover, (CH₃)₃[email protected]₃O₄ magnetic nanocatalyst could be easily and rapidly separated from the reaction mixture with the help of an external magnet and recycled minimum five times in reduction of 4-NP, MB, MO and four times in Cr(VI) without significant loss of catalytic potential and remains stable even after reuse.     

Sensitivity of normal theory methods to model misspecification in the calculation of upper confidence limits on the risk function for continuous responses

Normal theory procedures for calculating upper confidence limits (UCL) on the risk function for continuous responses work well when the data come from a normal distribution. However, if the data come from an alternative distribution, the application of the normal theory procedures may lead serious over- or under-coverage depending upon the alternative distribution. In this paper we conduct simulation studies to investigate the sensitivity of three normal theory UCL procedures to departures from normality. Data from several gamma, reciprocal gamma, and lognormal distributions are considered. The normal theory procedures are applied to both the raw data and the log-transformed data.     

The psychological benefits of indoor plants: A critical review of the experimental literature

People have been bringing plants into residential and other indoor settings for centuries, but little is known about their psychological effects. In the present article, we critically review the experimental literature on the psychological benefits of indoor plants. We focus on benefits gained through passive interactions with indoor plants rather than on the effects of guided interactions with plants in horticultural therapy or the indirect effect of indoor plants as air purifiers or humidifiers. The reviewed experiments addressed a variety of outcomes, including emotional states, pain perception, creativity, task-performance, and indices of autonomic arousal. Some findings recur, such as enhanced pain management with plants present, but in general the results appear to be quite mixed. Sources of this heterogeneity include diversity in experimental manipulations, settings, samples, exposure durations, and measures. After addressing some overarching theoretical issues, we close with recommendations for further research with regard to experimental design, measurement, analysis, and reporting.     

Estimating prevalence using composites

We are interested in estimating the fraction of a population that possesses a certain trait, such as the presence of a chemical contaminant in a lake. A composite sample drawn from a population has the trait in question whenever one or more of the individual samples making up the composite has the trait. Let the true fraction of the population that is contaminated be p. Classical estimators of p, such as the MLE and the jackknife, have been shown to be biased. In this study, we introduce a new shrinking estimator which can be used when doing composite sampling. The properties of this estimator are investigated and compared with those of the MLE and the jackknife.     

Temporal scale-induced uncertainty in load duration curves for instream-dissolved oxygen

Load duration curves were developed using the Hydrological Simulation Program FORTRAN (HSPF) for dissolved oxygen (DO) for the Amite River in Louisiana, USA. The concept of ‘dissolved oxygen reserve’, defined as the total quantity of DO, is introduced. The effect of temporal resolution on duration curves of DO reserve was examined using duration curves developed based on daily, weekly, biweekly, and monthly average data. Duration curves for DO exhibited high variability in the load estimated using daily data as compared to those based on biweekly and monthly data. A seasonal analysis revealed the trend in the DO reserve. The daily DO reserve for the Amite River at Port Vincent was 44,049.31 kg when daily summer data were used and 74,255.15 kg for daily annual data. A surplus of 10,691 kg of DO reserve was shown in the monthly data during critical summer months. The coefficient of variation (CV), used to define the temporal scale-induced uncertainty, was found to be linearly and inversely correlated with the logarithm of the time scale. Regression equations were developed to extrapolate near real-time flow and water quality data, greatly simplifying flow and water quality monitoring and reducing the cost involved in flow and water quality monitoring.     

Effectiveness of ionic liquid-supported membranes for carbon dioxide capture: a review

Environmental Science and Pollution Research - The world’s population explosion creates a need for natural resources for energy, which will become a significant contributor to global climate...     

Biomarker-assisted assessment of aquatic health using the cosmopolitan common carp,Cyprinus carpio (L): a case study of bisphenol-A exposures

Environmental Science and Pollution Research - Monitoring aquatic health from environmental pollutants is critical, none more so than bisphenol-A (BPA), a ubiquitous endocrine-disrupting chemical...