Vegetation composition and structure of woody plant communities along urban interstate corridors in Louisville,KY, U.S.A.

Urban forests adjacent to interstate corridors are understudied ecosystems across cities. Despite their small area, these forests may be strategically located to provide large ecosystem services due to their ability to act as a barrier against air pollutants and noise as well as to provide flood control. The woody vegetation composition and structure of forests adjacent to urban interstates is an important determinant of their ability to provide these services. However, these forest communities may be particularly susceptible to the introduction of exotic invasive species via the interstate and the surrounding city that can potentially alter current and future forest composition. The purpose of this study was to investigate the distribution of native and exotic woody vegetation and tree regeneration in forests along three interstate corridors in Louisville, KY, and to determine potential factors (e.g., traffic density) that are correlated with patterns in the woody vegetation community. We found the most important determinants of vegetation composition along these interstate corridors were the distance from the city center and the presence of an exotic invasive shrub, Amur honeysuckle (Lonicera maackii). Compared with forested plots within 10 km of the city center, plots further from the city center had 81% lower stem density of Amur honeysuckle, 96% higher tree seedling regeneration, and 51% greater woody plant species richness. The primarily native species composition of adult trees in forests alongside urban interstates in Louisville and the regeneration of native tree species provide optimism that these forests can maintain native species while experiencing multiple impacts from the interstate as well as from the surrounding city, emphasizing their important potential for maintaining natural forest functions across the urban landscape.     

Risk Factors for Clinically Significant Intimate Partner Violence Among Active‐Duty Members

Hypothesized risk factors for men's and women's clinically significant intimate partner violence (CS‐IPV) from four ecological levels (i.e., individual, family, workplace, community) were tested in a representative sample of active‐duty U.S. Air Force members (N = 42,744). When considered together, we expected only individual and family factors to account for unique variance in CS‐IPV perpetration. Hypothesized factors from all four ecological levels were related to men's CS‐IPV perpetration bivariately, but, as expected, only individual and family factors accounted for unique variance across ecological levels. For women, only risk factors from the individual and family levels were significantly related to CS‐IPV perpetration even bivariately. Results imply somewhat different risk profiles across gender and identify ecological risk factors of men's CS‐IPV not previously studied.     

Mental Rotation of Dynamic,Three‐Dimensional Stimuli by 3‐Month‐Old Infants

Mental rotation involves transforming a mental image of an object so as to accurately predict how the object would look if it were rotated in space. This study examined mental rotation in male and female 3‐month‐olds, using the stimuli and paradigm developed by Moore and Johnson (2008) . Infants were habituated to a video of a three‐dimensional object rotating back and forth through a 240° angle around the vertical axis. After habituation, infants were tested both with videos of the same object rotating through the previously unseen 120° angle, and with the mirror image of that display. Unlike females, who fixated the test displays for approximately equal durations, males spent significantly more time fixating the familiar object than the mirror‐image object. Because familiarity preferences like this emerge when infants are relatively slow to process a habituation stimulus, the data support the interpretation that mental rotation of dynamic three‐dimensional stimuli is relatively difficult—but possible—for 3‐month‐old males. Interpretation of the sex differences observed in 3‐ and 5‐month‐olds’ performances is discussed.     

Employee exposure to coworker substance use and negative consequences: the moderating effects of work group membership.

The current study assesses: (1) whether the relationship between individual exposure to coworker substance use and negative consequences resulting from exposure depends on work group membership, and (2) whether group-level characteristics moderate the relationship between exposure and consequences. At the group-level, we assessed occupations involving safety risk or high mobility and social factors of drinking climate and group cohesiveness. We conducted Hierarchical Linear Modeling (HLM) across two samples of municipal employees (ns = 650, 878; n of groups = 50, 49). Our results revealed that groups with higher proportions of jobs involving risk (e.g., machine work) and, to a lesser extent, groups with a higher level of drinking climate were those most vulnerable to consequences under conditions of exposure. Importantly, our findings controlled for individual risk factors (e.g., personal drinking, job stress). Our discussion examines the implications of this study for theory and policy related to workplace substance abuse.     

THE PHYSICIAN LABOR MARKET IN A MANAGED CARE-DOMINATED ENVIRONMENT

The belief that doctors respond to declining demand by treating patients more aggressively has created skepticism about relying on market forces to restructure physician supply. We argue that even if the physician labor market is dysfunctional under fee-for-service incentives, it can perform better as managed care becomes dominant. Our model implies a nonlinear effect of managed care penetration on incomes. Physicians can offset most or all of initial declines in demand, but cannot insulate themselves indefinitely. This may explain the observation that, until recently, the growth of managed care has not been accompanied by large physician income changes. ( JEL III, J31)     

The coming medical apocalypse.

Is there a medical apocalypse in our future? Will it happen soon? No one can say for sure, but five ominous trends suggest that a medical meltdown could occur at any time. These trends are: (1) The practice of providing medical care becoming too complex from both a business and a legal perspective; (2) Less money being spent on medical care without any corresponding reduction in services provided, creating long-term operating deficits; (3) Investor-owned, for-profit corporations changing the focus of medicine by putting shareholder concerns ahead of patient care; (4) Employment-linked health care insurance creating a growing uninsured population, adding extra financial stress to our hospitals; and, (5) Providers losing faith in their future and becoming increasingly demoralized about practicing the healing arts. These dangerous trends are considered, along with some suggestions that physician executives and organizations might take to protect themselves.     

A Discrete Variable Chain Graph for Applicants for Credit

A bank offering unsecured personal loans may be interested in several related outcome variables, including defaulting on the repayments, early repayment or failing to take up an offered loan. Current predictive models used by banks typically consider such variables individually. However, the fact that they are related to each other, and to many interrelated potential predictor variables, suggests that graphical models may provide an attractive alternative solution. We developed such a model for a data set of 15 variables measured on a set of 14 000 applications for unsecured personal loans. The resulting global model of behaviour enabled us to identify several previously unsuspected relationships of considerable interest to the bank. For example, we discovered important but obscure relationships between taking out insurance, prior delinquency with a credit card and delinquency with the loan.     

Observable trend-projecting state-space models

Much attention has focused in recent years on the use of state-space models for describing and forecasting industrial time series. However, several state-space models that are proposed for such data series are not observable and do not have a unique representation, particularly in situations where the data history suggests marked seasonal trends. This raises major practical difficulties since it becomes necessary to impose one or more constraints and this implies a complicated error structure on the model. The purpose of this paper is to demonstrate that state-space models are useful for describing time series data for forecasting purposes and that there are trend-projecting state-space components that can be combined to provide observable state-space representations for specified data series. This result is particularly useful for seasonal or pseudo-seasonal time series. A well-known data series is examined in some detail and several observable state-space models are suggested and compared favourably with the constrained observable model.