Examining Localized Patterns of Air Quality Perception in Texas: A Spatial and Statistical Analysis

Environmental and human health issues associated with outdoor air pollution, such as ozone, sulfur dioxide, and other pollutants in metropolitan regions, are an area of growing concern for both policy officials and the general public. Increasing attention from the news media, new health data, and public debate over the effectiveness of clean air regulations have raised the importance of air quality in the public consciousness. While public perceptions of air quality have been studied thoroughly dating back to the 1960s, little empirical research has been conducted to explain the spatial aspects of these perceptions, particularly at the local level. Although recent studies suggest characteristics of local setting are important in shaping perceptions of air quality, the roles of proximity, neighborhood characteristics, and location have not been clarified. This study seeks to improve understanding of the major factors shaping public perceptions of air quality by examining the spatial pattern of local risk perception, the role of socioeconomic characteristics in forming these perceptions, and the relationship between perceived and scientifically measured air pollution. First, we map the spatial pattern of local air quality perceptions using Geographic Information Systems (GIS) across the Dallas and Houston metropolitan areas. Next, we explain these perceptions through local contextual factors using both bivariate correlations and multivariate regression analysis. Results indicate that perceptions of air quality in the study areas are not significantly correlated with air quality based on readings of air monitoring stations. Instead, perceptions appear to be influenced by setting (urban vs. rural), state identification, access to information, and socioeconomic characteristics such as age, race, and political identification. We discuss the implications of the findings and provide direction on how further research can provide a deeper understanding of the local contextual factors influencing public perceptions.     

Solving the part families problem in discrete-parts manufacture by simulated annealing

In the production planning and control of discrete-parts manufacture, aggregation of parts into families, on the basis of similarity, is carried out to ease both long-horizon planning and short-horizon scheduling. Additional advantages are related to those of group technology (GT), such as simplifying the flow of parts and tools and reducing both set-up and production costs. The problem of formally forming part families is presented and discussed. Previous work is reviewed and assessed. Two solution approaches, one based on a location model, the other on simulated annealing, are presented and compared along with test results. The location formulation, which results in an integer programming model solved by Lagrangian relaxation, proved capable of producing solutions of excellent quality, but only for relatively small problem instances. In contrast, simulated annealing, which is a general heuristic approach to combinatorial optimization, produced solutions of comparable quality and could handle realistically large problem instances. However, careful design of the simulated annealing algorithm is crucially important. An effective design is presented.     

Estimation of the parameters of symmetric stable ARMA and ARMA–GARCH models

In this article, we first propose the modified Hannan–Rissanen Method for estimating the parameters of autoregressive moving average (ARMA) process with symmetric stable noise and symmetric stable generalized autoregressive conditional heteroskedastic (GARCH) noise. Next, we propose the modified empirical characteristic function method for the estimation of GARCH parameters with symmetric stable noise. Further, we show the efficiency, accuracy and simplicity of our methods with Monte-Carlo simulation. Finally, we apply our proposed methods to model the financial data.     

Computer incompetents in the cross-hairs.

Human Resources managers are distressingly aware that more than half the middle and senior managers (40- and 50-year-olds) in their organizations are technologically incompetent. Having spent millions on technology, most corporate CEOs, many of whom can't use a computer either, are drawing a bead on middle managers who are passively resisting the computer revolution. Physician executives are no exception. Given the current shortage of physician managers with good track records and people skills, can middle managers skirt technology issues until retirement if they dance slowly enough? It's doubtful. Organizations are using new tactics to bar technically challenged managers from their ranks: They will only interview candidates with mastery of specific software and they're posting job opportunities on their web sites. Those who still believe they can ride out the computer revolution may want to rethink that strategy.     

Contractors and their Psychological Contracts

It is commonly assumed that contractors are largely calculative, instrumental and self-interested in their relationship with organizations and interface with them accordingly (e.g. low corporate interest and emotional investment). This paper describes a survey involving 117 contractors (62 on 'permanent' agency contracts and 55 on 'temporary' agency contracts) and a comparable (age, job level/grade, years of work experience) group of 86 direct employees (on fixed-term contracts). The survey comprised measures of the psychological contract, of organizational identification, social (corporate) attraction, team spirit and intention to leave. The findings show that contractors are not inevitably 'emotionally' detached from their place of work, in some cases investing in it as much as direct company employees. While transactional (e.g. financial gain, instrumentality) exchange considerations were more salient among contractors than employees, this did not appear to preclude the development of a relational (e.g. corporate integration and long-term investment) contractual orientation. 'Team spirit' and 'organizational identification' predicted the development of relational contracts over and above contractual status. The findings and their management implications are discussed in terms of 'strategic partnership'.     

From Resources to Value and Back: Competition Between and Within Organizations

Examining the relationship between the competitive processes between and within organizations, we use selection system theory to link resource value to product value. We identify three dimensions (in‐selection, before‐selection and after‐selection) that facilitate determining the value of resources based on the functions they serve in the competitive process between organizations in the product market, i.e. the external selection system. Subsequently, we use these dimensions to explore the competitive process among resource providers within organizations, i.e. the internal selection system. This leads us to formulate three propositions that link the competitive process within organizations to the competitive process between organizations. First, we posit that if resources that individually score highly along only one of the three dimensions are bundled, it is more likely that organizational performance can be sustained. Second, we argue that providers of resources scoring highly along multiple dimensions will enjoy stronger means of appropriation in comparison with providers of resources scoring highly along only one of the three dimensions. Third, we contend that the extent to which an organization endeavours to remunerate its resource providers based on their perceived contribution to the organization's competitive position has a curvilinear (inverted U‐shaped) relationship with organizational performance.     

Cancer risk estimation for mixtures of coal tars and benzo(a)pyrene.

Two-year chronic bioassays were conducted by using B6C3F1 female mice fed several concentrations of two different mixtures of coal tars from manufactured gas waste sites or benzo(a)pyrene (BaP). The purpose of the study was to obtain estimates of cancer potency of coal tar mixtures, by using conventional regulatory methods, for use in manufactured gas waste site remediation. A secondary purpose was to investigate the validity of using the concentration of a single potent carcinogen, in this case benzo(a)pyrene, to estimate the relative risk for a coal tar mixture. The study has shown that BaP dominates the cancer risk when its concentration is greater than 6,300 ppm in the coal tar mixture. In this case the most sensitive tissue site is the forestomach. Using low-dose linear extrapolation, the lifetime cancer risk for humans is estimated to be: Risk < 1.03 x 10(-4) (ppm coal tar in total diet) + 240 x 10(-4) (ppm BaP in total diet), based on forestomach tumors. If the BaP concentration in the coal tar mixture is less than 6,300 ppm, the more likely case, then lung tumors provide the largest estimated upper limit of risk, Risk < 2.55 x 10(-4) (ppm coal tar in total diet), with no contribution of BaP to lung tumors. The upper limit of the cancer potency (slope factor) for lifetime oral exposure to benzo(a)pyrene is 1.2 x 10(-3) per microgram per kg body weight per day from this Good Laboratory Practice (GLP) study compared with the current value of 7.3 x 10(-3) per microgram per kg body weight per day listed in the U.S. EPA Integrated Risk Information System.     

Improving Cancer Dose–Response Characterization by Using Physiologically Based Pharmacokinetic Modeling: An Analysis of Pooled Data for Acrylonitrile-Induced Brain Tumors to Assess Cancer Potency in the Rat

Historically, U.S. regulators have derived cancer slope factors by using applied dose and tumor response data from a single key bioassay or by averaging the cancer slope factors of several key bioassays. Recent changes in U.S. Environmental Protection Agency (EPA) guidelines for cancer risk assessment have acknowledged the value of better use of mechanistic data and better dose–response characterization. However, agency guidelines may benefit from additional considerations presented in this paper. An exploratory study was conducted by using rat brain tumor data for acrylonitrile (AN) to investigate the use of physiologically based pharmacokinetic (PBPK) modeling along with pooling of dose–response data across routes of exposure as a means for improving carcinogen risk assessment methods. In this study, two contrasting assessments were conducted for AN-induced brain tumors in the rat on the basis of (1) the EPA's approach, the dose–response relationship was characterized by using administered dose/concentration for each of the key studies assessed individually; and (2) an analysis of the pooled data, the dose–response relationship was characterized by using PBPK-derived internal dose measures for a combined database of ten bioassays. The cancer potencies predicted for AN by the contrasting assessments are remarkably different (i.e., risk-specific doses differ by as much as two to four orders of magnitude), with the pooled data assessments yielding lower values. This result suggests that current carcinogen risk assessment practices overestimate AN cancer potency. This methodology should be equally applicable to other data-rich chemicals in identifying (1) a useful dose measure, (2) an appropriate dose–response model, (3) an acceptable point of departure, and (4) an appropriate method of extrapolation from the range of observation to the range of prediction when a chemical's mode of action remains uncertain.     

The institutionalization of knowledge transfer activities within industry–university collaborative ventures

Due to the changing competitive landscape, organizations must increasingly focus on acquiring external knowledge to advance new technologies. This study examines the institutionalization of knowledge transfer activities between industrial firms and university research centers. Data were collected from 189 firms collaborating with 21 university research centers in the US. Results show that knowledge transfer activities are facilitated when industrial firms have more mechanistic structures, cultures that are more stable and direction-oriented, and when the firm is more trusting of its university research center partner. Implications for both industry and universities, including their effect on firm performance, are discussed.     

Collecting text messages from college students: Evaluating a novel methodology

Social interaction, particularly in older adolescents, increasingly involves computer‐mediated communication. Although studies of public computer‐mediated communication are increasingly common, studies of private text messaging remain rare. As approaches for obtaining such data evolve with technological advances, developmental scientists need designs in which to use such approaches that reduce sampling biases in both participants and text messages. In this study (n = 854; 46% male; 22% African American, 60% European American), we examined selection biases in the participant sample (i.e., factors associated with actual participation), procedural biases in the participant sample (i.e., factors related to failed data capture due to technological or procedural issues), and selection biases in the sample of text messages (i.e., based on self‐reported reasons for texting). Findings from our study suggest that studying human interaction directly through analysis of text message data is not only feasible, but also may be successfully undertaken with minimal biases regarding sample selection and text message selection among those who are engaged in research and engaged in text messaging outside of the study context. However, biases may occur depending on the type of platform (iPhone vs. Android) used by participants for texting.