Urban predator–prey association: coyote and deer distributions in the Chicago metropolitan area

We examined how predator or prey presence, as well as local and landscape factors, influence the distribution of coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in the Chicago metropolitan area. We collected data for 2 years at 93 study sites along 3 transects of urbanization using motion-triggered cameras. Our primary objective was to determine the relationship among coyote and deer spatial and temporal distribution, habitat characteristics, and human activity using multi-season patch occupancy models. Coyote occupancy was most strongly linked to rates of site visitation by humans and dogs, and was more likely farther from the urban center, with coyote colonization of sites inversely related to road density, housing density, and human and dog site visitation. Deer more frequently occupied sites with high canopy cover near water sources and colonized smaller sites with reduced housing density and human and dog presence. Expected predator–prey dynamics were altered in this highly urban system. Though we predicted deer would avoid coyotes on the landscape based on an “ecology of fear” framework, deer and coyote occupancy showed a strong positive association. We suggest that a scarcity of quality habitat in urban areas may cause the species to co-occupy habitat despite potential fawn predation. Modifying human foot traffic in green spaces may represent a useful tool for management and conservation of large urban mammals.     

Managing amidst mosaic: Integrating values and rationalization in the nonprofit arts

This ethnographic study of visionary art environment Philadelphia's Magic Gardens (PMG) draws on theories of rationalization in nonprofits to explore factors that influence the impact of this process on organizations. Responding to theories that rationalization attenuates expressive drivers of nonprofit activity, an analysis of PMG is used to explore and contextualize a literature‐derived theoretical framework that suggests variables that may influence the outcome of rationalization processes in organizations. The PMG case supports and adds nuance to a notion that the strength of expressive and rationalizing impulses and the convergence or divergence of intra‐organizational values influence whether growing nonprofits are able to integrate instrumental structures and expressive motivations.     

Separating online scheduling algorithms with the relative worst order ratio

The relative worst order ratio is a measure for the quality of online algorithms. Unlike the competitive ratio, it compares algorithms directly without involving an optimal offline algorithm. The measure has been successfully applied to problems like paging and bin packing. In this paper, we apply it to machine scheduling. We show that for preemptive scheduling, the measure separates multiple pairs of algorithms which have the same competitive ratios; with the relative worst order ratio, the algorithm which is “intuitively better” is also provably better. Moreover, we show one such example for non-preemptive scheduling.     

Allowing Family to be Family: End-of-Life Care in Veterans Affairs Medical Foster Homes

The Medical Foster Home program is a unique long-term care program coordinated by the Veterans Health Administration. The program pairs Veterans with private, 24-hour a day community-based caregivers who often care for Veterans until the end of life. This qualitative study explored the experiences of care coordination for Medical Foster Home Veterans at the end of life with eight Veterans’ family members, five Medical Foster Home caregivers, and seven Veterans Health Administration Home-Based Primary Care team members. A case study, qualitative content analysis identified these themes addressing care coordination and impact of the Medical Foster Home model on those involved: (a) Medical Foster Home program supports Veterans’ families; (b) Medical Foster Home program supports the caregiver as family; (c) Veterans’ needs are met socially and culturally at the end of life; and (d) the changing needs of Veterans, families, and caregivers at Veterans’ end of life are addressed. Insights into how to best support Medical Foster Home caregivers caring for Veterans at the end of life were gained including the need for more and better respite options and how caregivers are compensated in the month of the Veteran’s death, as well as suggestions to navigate end-of-life care coordination with multiple stakeholders involved.     

The hierarchical model for load balancing on two machines

Following previous work, we consider the hierarchical load balancing model on two machines of possibly different speeds. We first focus on maximizing the minimum machine load and show that no competitive algorithm exists for this problem. We overcome this barrier in two ways, both related to previously known models. The first one is fractional assignment, where each job can be arbitrarily split between the machines. The second one is a semi-online model where the sum of jobs is known in advance. We design algorithms of best possible competitive ratios for both these cases. Furthermore, we show that the combination of the two models leads to the existence of an optimal algorithm (i.e., an algorithm of competitive ratio 1). This algorithm is clearly optimal for the makespan minimization problem as well. For the latter problem, we consider the fractional assignment model and design an algorithm of best possible competitive ratio for it. This work was submitted as the M.Sc. thesis of the first author.     

Marketing and Quality of Life: A Model for Improving Perinatal Health Status

Introduction: A marketing/business model using non-traditional Quality of Life measures was developed to assess perinatal health status on a micro-geographic level. This perinatal health status needs assessment study for Georgia South Central Region was conducted for the years 1994–1999. The model may be applied to any geographic unit in the U.S. – from a block group level to a state or a region. Methodology: An Infant Health Risk Score was created for each county and census tract by calculating the Z-scores of various Medical, Lifestyle, and Access variables so as to construct a Quality of Life Index. The scores identified the areas in the region that were at high risk for certain medical, lifestyle, and access variables (i.e., high risk for preterm births, low education levels, and poor access to perinatal services). A marketing tool, Claritas PRIZM Clusters, was used to identify a specific cluster and associated marketing information for each census tract within the region. Results: The Infant Health Quality of Life Risk Scores were linked with the PRIZM cluster marketing data to target areas in the region that exhibit high risk medical, lifestyle, and access scores. Health promotion and disease prevention strategies were developed using a marketing/business model. Specifically, media usage and consumer behavior purchasing patterns were identified and processed for every high risk area in the region. The categories for media usage were television, radio, and magazines and the categories for consumer behavior included restaurants, food items, and shopping locations. Discussion: The Perinatal Region is developing strategies to implement the media usage and consumer behavior marketing information to focus their prevention efforts to the high risk areas in the region based on the Quality of Life Measurements. Linking marketing business tools with a Quality of Life health status needs assessment has significant potential for improving the planning, the evaluation, and the focus of prevention efforts.