Health Effects Caused by Primary Fine Particulate Matter (PM2.5) Emitted from Buses in the Helsinki Metropolitan Area, Finland

Fine particle (PM(2.5)) emissions from traffic have been associated with premature mortality. The current work compares PM(2.5)-induced mortality in alternative public bus transportation strategies as being considered by the Helsinki Metropolitan Area Council, Finland. The current bus fleet and transportation volume is compared to four alternative hypothetical bus fleet strategies for the year 2020: (1) the current bus fleet for 2020 traffic volume, (2) modern diesel buses without particle traps, (3) diesel buses with particle traps, and (4) buses using natural gas engines. The average population PM(2.5) exposure level attributable to the bus emissions was determined for the 1996-1997 situation using PM(2.5) exposure measurements including elemental composition from the EXPOLIS-Helsinki study and similar element-based source apportionment of ambient PM(2.5) concentrations observed in the ULTRA study. Average population exposure to particles originating from the bus traffic in the year 2020 is assumed to be proportional to the bus emissions in each strategy. Associated mortality was calculated using dose-response relationships from two large cohort studies on PM(2.5) mortality from the United States. Estimated number of deaths per year (90% confidence intervals in parenthesis) associated with primary PM(2.5) emissions from buses in Helsinki Metropolitan Area in 2020 were 18 (0-55), 9 (0-27), 4 (0-14), and 3 (0-8) for the strategies 1-4, respectively. The relative differences in the associated mortalities for the alternative strategies are substantial, but the number of deaths in the lowest alternative, the gas buses, is only marginally lower than what would be achieved by diesel engines equipped with particle trap technology. The dose-response relationship and the emission factors were identified as the main sources of uncertainty in the model.     

A new approach to the measurement of polarization for grouped data

In this paper we develop a measure of polarization for discrete distributions of non-negative grouped data. The measure takes into account the relative sizes and homogeneities of individual groups as well as the heterogeneities between all pairs of groups. It is based on the assumption that the total polarization within the distribution can be understood as a function of the polarizations between all pairs of groups. The measure allows information on existing groups within a population to be used directly to determine the degree of polarization. Thus the impact of various classifications on the degree of polarization can be analysed. The treatment of the distribution’s total polarization as a function of pairwise polarizations allows statements concerning the effect of an individual pair or an individual group on the total polarization.     

Child Abuse: A Cognitive Behavioral Intervention Model

The frequency of child abuse, together with its generational pattern of reocurrence, has created a need for additional models for child abuse treatment. Presented herein is a six-step child abuse intervention model based upon cognitive-behavioral change strategies. Allowing immediate alleviation of abuse when only one adult family member is in contact with the assisting agency, the proposed model provides for the restructuring of parenting style to increase the probabilities of permanent change.
This model is currently being utilized by one of the authors to assist self-referred abusive patients in a group setting.     

TigerPlace, A State-Academic-Private Project to Revolutionize Traditional Long-Term Care

The Aging in Place Project at the University of Missouri (MU) required legislation in 1999 and 2001 to be fully realized. An innovative home health agency was initiated by the Sinclair School of Nursing specifically to help older adults age in place in the environment of their choice. In 2004, an innovative independent living environment was built and is operated by a private long term care company, as a special facility where residents can truly age in place and never fear being moved to a traditional nursing home unless they choose to do so. With care provided by the home care agency with registered nurse care coordination services, residents receive preventative and early illness recognition assistance that have markedly improved their lives. Evaluation of aging in place reveal registered nurse care coordination improves outcomes of cognition, depression, activities of daily living, incontinence, pain, and shortness of breath as well as delaying or preventing nursing home placement. Links with MU students, faculty, and nearly every school or college on campus enrich the lives of the students and residents of the housing environment. Research projects are encouraged and residents who choose to participate are enjoying helping with developing cutting technology to help other seniors age in place.     

Drivers of private-label purchase behavior across quality tiers and product categories

Private labels hold a substantial share of consumers’ wallets and their popularity is still growing as they spread into various product categories and quality tiers. To determine the right branding strategy, in terms of offering uniform or different private-label brands across product categories, retailers have to know whether consumers use their private-label experience across product categories and private-label tiers. Therefore, we examine different determinants of consumers’ consideration sets. We apply proneness for certain private-label tiers, product categories purchased, purchase frequency, and variety seeking as internal determinants, which contribute to consumers’ knowledge and experience with private labels. Further, we use consumers’ price consciousness and promotion sensitivity as external determinants, which the retailer can use to influence consumers’ consideration sets in the short run. Our analyses are based on large-scale loyalty program data for a period of 24 months. In particular, we use the first 12 months to derive the determinants of consumers’ share of wallets regarding different private-label quality tiers in the second half of the sample. We conduct our analyses for 12 different product categories and aggregate the results by using meta-analytic techniques. Notably, some determinants show dissimilar effects across product categories (e.g., price consciousness and promotion sensitivity), while others (e.g., private-label proneness) are rather similar. We find that consumers’ general proneness for certain private-labels tiers leads to a propensity to purchase them in a specific category and in adjacent quality tiers. Further, we reveal that product category characteristics moderate the determinants of private-label share.     

CLUSTERING IN N‐PLAYER PREEMPTION GAMES

We study a complete information preemption game in continuous time. A finite number of firms decide when to make an irreversible, observable investment. Upon investment, a firm receives flow profits, which decrease in the number of firms that have invested. The cost of investment declines over time exogenously. We characterize the subgame‐perfect equilibrium outcome, which is unique up to a permutation of players. When the preemption race among late investors is sufficiently intense, the preemption incentive for earlier investors disappears, and two or more investments occur at the same time. We identify a sufficient condition in terms of model parameters: clustering of investments occurs if the flow profits from consecutive investments are sufficiently close. This shows how clustering can occur in the absence of coordination failures, informational spillovers, or positive payoff externalities.