Attentional processes in stereotype formation: A common model for category accentuation and illusory correlation.

Stereotype formation may be based on the exaggeration of real group differences (category accentuation) or the misperception of group differences that do not exist (illusory correlation). This research sought to account for both phenomena with J. K. Kruschke's (1996, 2001, 2003) attention theory of category learning. According to the model, the features of majority groups are learned earlier than the features of minority groups. In turn, the features that become associated with a minority are those that most distinguish it from the majority. This second process is driven by an attention-shifting mechanism that directs attention toward group-attribute pairings that facilitate differentiation of the two groups and may lead to the formation of stronger minority stereotypes. Five experiments supported this model as a common account for category accentuation and distinctiveness-based illusory correlation. Implications for the natures of stereotype formation, illusory correlation, and impression formation are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Prejudice and Stereotype Maintenance Processes: Attention, Attribution, and Individuation.

Three experiments examined the relationship between prejudice and processing of stereotypic information. Higher levels of prejudice were associated with greater attention to and more thorough encoding of stereotype-inconsistent than stereotype-consistent behaviors but only when processing capacity was plentiful (Experiments 1 and 3). High-prejudice participants attributed consistent behaviors to internal factors and inconsistent behaviors to external forces (Experiment 2). Together, these results suggest that high-prejudice people attend carefully to inconsistent behaviors to explain them away but only if they have sufficient resources to do so. Results also showed that low-prejudice but not high-prejudice participants formed individuated impressions by integrating the implications of the target's behaviors (i.e., individuating). High levels of prejudice appear to be associated with biased encoding and judgment processes that may serve to maintain stereotypes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Characterizing peak exposure of secondhand smoke using a real-time PM2.5 monitor

Although short-duration elevated exposures (peak exposures) to pollutants may trigger adverse acute effects, epidemiological studies to understand their influence on different health effects are hampered by lack of methods for objectively identifying peaks. Secondhand smoke from cigarettes (SHS) in the residential environment can lead to peak exposures. The aim of this study was to explore whether peaks in continuous PM_2.5 data can indicate SHS exposure. A total of 41 children (21 with and 20 without SHS exposure based on self-report) from 28 families in New York City (NY, USA) were recruited. Both personal and residential continuous PM_2.5 monitoring were performed for five consecutive days using MicroPEM sensors (RTI International, USA). A threshold detection method based on cumulative distribution function was developed to identify peaks. When children were home, the mean accumulated peak area (APA) for peak exposures was 297 ± 325 hour*µg/m³ for children from smoking families and six times that of the APA from non-smoking families (~50 ± 54 hour*µg/m³). Average PM_2.5 mass concentrations for SHS exposed and unexposed children were 24 ± 15 µg/m³ and 15 ± 9 µg/m³, respectively. The average SHS exposure duration represents ~5% of total exposure time, but ~13% of children's total PM_2.5 exposure dose, equivalent to an additional 2.6 µg/m³ per day. This study demonstrated the feasibility of peak analysis for quantifying SHS exposure. The developed method can be adopted more widely to support epidemiology studies on impacts of short-term exposures.     

Grid Computing and Beyond: The Context of Dynamic Data Driven Applications Systems

The advent of Grid computing has enhanced our capabilities to model and simulate complex systems arising in scientific, engineering, and commercial applications. The premise of Grid computing has been "on-demand" availability of computational resources to an application as needed, in the same manner as electricity is provided readily through electrical power grids. The computational grid (or simply the "Grid") entails ubiquitous access to resources (local or remote), such as computation and communication resources, as well as access to storage systems and visualization systems. As Grid computing technologies mature, it behooves to look beyond the current capabilities, into more advanced future environments. The environments of interest here are the enhanced capabilities that can be created by the paradigm of dynamic data driven applications systems (DDDAS). DDDAS entails the ability to incorporate additional data into an executing application and, in reverse, the ability of applications to dynamically steer the measurement process. The DDDAS concept offers the promise of improving application models and methods, and augmenting the analysis and prediction capabilities of application simulations and the effectiveness of measurement systems. Enabling this synergistic feedback and control loop between application simulations and measurements requires novel application modeling approaches and frameworks, algorithms stable under dynamic data injection and steering conditions, and new systems software and computational infrastructure capabilities. Recent advances in complex applications and the advent of Grid computing and sensor systems are some of the technologies that make it timely to embark in developing DDDAS capabilities. DDDAS environments extend the current notion of Grid infrastructure to also include the measurement systems in an integrated and synergistic way. DDDAS environments require support and services that go beyond the current Grid services in terms of t     

Variability of total exposure to PM2.5 related to indoor and outdoor pollution sources Krakow study in pregnant women

The study is a part of an ongoing prospective cohort study on the relationship between the exposure to environmental factors during pregnancy and birth outcomes and health of newborns. We have measured personal PM(2.5) level in the group of 407 non-smoking pregnant women during the 2nd trimester of pregnancy. On average, the participants from the city center were exposed to higher exposure than those from the outer city area (GM=42.0 microg/m(3), 95% CI: 36.8-48.0 vs. 35.8 microg/m(3), 95% CI: 33.5-38.2 microg/m(3)). More than 20% of study subjects were affected by high level of PM(2.5) pollution (above 65 microg/m(3)). PM(2.5) concentrations were higher during the heating season (GM=43.4 microg/m(3), 95% CI: 40.1-46.9 microg/m(3)) compared to non-heating season (GM=29.8 microg/m(3), 95% CI: 27.5-32.2 microg/m(3)). Out of all potential outdoor air pollution sources (high traffic density, bus depot, waste incinerator, industry etc.) considered in the bivariate analysis, only the proximity of industrial plant showed significant impact on the personal exposure (GM=54.3 microg/m(3), 95% CI: 39.4-74.8 microg/m(3)) compared with corresponding figure for those who did not declare living near the industrial premises (GM=36.2 microg/m(3), 95% CI: 34.1-38.4 microg/m(3)). The subjects declaring high exposure to ETS (>10 cigarettes daily) have shown very high level of personal exposure (GM=88.8 microg/m(3), 95% CI: 73.9-106.7 microg/m(3)) compared with lower ETS exposure (< or =10 cigarettes) (GM=46.3 microg/m(3), 95% CI: 40.0-53.5 microg/m(3)) and no-ETS exposure group (GM=33.9 microg/m(3), 95% CI: 31.8-36.1 microg/m(3)). The contribution of the background ambient PM(10) level was very strong determinant of the total personal exposure to PM(2.5) and it explained about 31% of variance between the subjects followed by environmental tobacco smoke (10%), home heating by coal/wood stoves (2%), other types of heating (2%) and the industrial plant localization in the proximity of household (1%).     

Effect of prenatal exposure to fine particulate matter and intake of Paracetamol (Acetaminophen) in pregnancy on eczema occurrence in early childhood

The goal of the study was to test the hypothesis that prenatal Paracetamol exposure increases the risk of developing eczema in early childhood and that this association may be stronger in children who are exposed in fetal period to higher concentrations of fine particulate matter (PM_2.5). The study sample consisted of 322 women recruited from January 2001 to February 2004 in the Krakow inner city area who gave birth to term babies and completed 5-year follow-up. Paracetamol use in pregnancy was collected by interviews and prenatal personal exposure to PM_2.5 over 48 h was measured in recruited women in the second trimester of pregnancy. After delivery, every three months in the first 24 months of the newborn's life and every 6 months later, a detailed standardized face-to-face interview on the infant's health was administered to each mother by trained interviewers. During the interviews at each of the study periods after birth, a history of eczema was recorded.The incident rate ratio (IRR) for frequency of eczema events over the follow-up was estimated from the Poisson regression model and the overall effect of main exposure variables on eczema was assessed by odds ratios (ORs) by the logistic model. The estimated relative risk of eczema occurring whenever in the follow-up was related significantly neither with prenatal Paracetamol nor higher PM_2.5 exposure, however, their joint effect was significant (OR interaction term = 6.04; 95%CI: 1.04-35.16). Of potential confounders considered in the analysis only damp/moldy home significantly increased the risk of eczema (OR = 1.53; 95%CI: 1.14-2.05). In contrast, there was an inverse significant association between the presence of older siblings and eczema (OR = 0.55; 95%CI: 0.35-0.84). The joint effect of the main exposure variables significantly increased frequency of eczema events (IRR = 1.78, 95%CI: 1.22-2.61).In conclusion, the findings of the study suggest that Paracetamol use by mothers in pregnancy is not an independent risk factor for eczema in children, however, even very small doses of Paracetamol taken in pregnancy may contribute to the occurrence of allergic symptoms in early childhood if there is prenatal co-exposure to higher airborne fine particulate matter.     

The Next Generation Software Program

The papers in this issue provide an overview of the research fostered by the NSF Next Generation Software (NGS) Program², and some representative projects funded under the program. The NGS Program was announced in October of 1998, and with several calls for proposals between 1998 and 2004 has supported research in two broad technical thrusts. One program component has supported research for developing Technology for Performance Engineered Systems (TPES) for the Design, Management and Runtime Support of Computing Systems and Applications. The second program component, Complex Application Development and runtime Support Systems (CADSS) has sought to create new systems’ software technology, including enhanced compiler capabilities, and tools for the development, runtime support and dynamic composition of complex applications executing on complex computing platforms, such as Computational Grids, assemblies of embedded systems and sensor systems, as well as high-end platforms (Grids-in-a-Box) and special purpose processing systems. Work along the directions of the NGS Program presently continues under the successor program, the NSF Computer Systems Research Program.     

Dimensions that characterize supervisor interventions delivered in the context of live supervision of practicum counselors.

Examined underlying dimensions from actual supervisory statements taken from interventions occurring during live supervision of counseling interviews. 27 supervisor interventions were identified and transcribed from the 3rd and 4th counseling sessions of 16 counseling dyads. 26 judges sorted and rated these transcribed interventions. Multidimensional scaling revealed 6 dimensions that characterized the supervisor interventions. The dimensions were interpreted as Directing-Instructing vs Deepening, Cognitive Clarification vs Emotional Encouragement, Confronting vs Encouraging the Client, Didactic-Distant vs Emotionally Involved, Joining With vs Challenging the Trainee, and Providing Direction vs Resignation. The findings are discussed in relation to the supervision literature. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Spatial and temporal trends of polycyclic aromatic hydrocarbons and other traffic-related airborne pollutants in New York City

Traffic-related air pollutants have been associated with adverse health effects. We hypothesized that exposure to polycyclic aromatic hydrocarbons (PAHs), elemental carbon (EC, diesel indicator), particulate matter (PM2.5), and a suite of metals declined from 1998 to 2006 in NYC due to policy interventions. PAH levels from personal monitoring of pregnant mothers participating in the Columbia's Center for Children's Environmental Health birth cohort study, and EC, PM2.5, and metal data from five New York State Department of Environmental Conservation stationary monitors were compared across sites and over time (1998-2006). Univariate analysis showed a decrease in personal PAHs exposures from 1998 to 2006 (p < 0.0001). After controlling for environmental tobacco smoke, indoor heat, and cooking, year of personal monitoring remained a predictor of decline in sigmaPAHs (beta = -0.269, p < 0.001). Linear trend analysis also suggested that PM2.5 declined (p = 0.09). Concentrations of EC and most metals measured by stationary site monitors, as measured by ANOVA, did not decline. Across stationary sites, levels of airborne EC and metals varied considerably. By contrast PM2.5 levels were highly intercorrelated (values ranged from 0.725 to 0.922, p < 0.01). Further policy initiatives targeting traffic-related air pollutants may be needed for a greater impact on public health.     

Realistic model for the output beam profile of stripe and tapered superluminescent light-emitting diodes

We present a new model to analyse the spatial characteristics of the output beam of conventional (straight-stripe) and tapered superluminescent light-emitting diodes. The device model includes both spontaneous and stimulated emission processes as well as a nonuniform carrier density distribution to correctly represent current spreading and carrier diffusion effects. Near- and far-field intensity profiles computed with this model are accurately verified over a wide range of injection currents by comparisons with experimental results measured from in-house fabricated devices.