Air pollution and health: bridging the gap from sources to health outcomes: conference summary

Air Pollution and Health: Bridging the Gap from Sources to Health Outcomes, an international specialty conference sponsored by the American Association for Aerosol Research, was held to address key uncertainties in our understanding of adverse health effects related to air pollution and to integrate and disseminate results from recent scientific studies that cut across a range of air pollution-related disciplines. The Conference addressed the science of air pollution and health within a multipollutant framework (herein "multipollutant" refers to gases and particulate matter mass, components, and physical properties), focusing on five key science areas: sources, atmospheric sciences, exposure, dose, and health effects. Eight key policy-relevant science questions integrated across various parts of the five science areas and a ninth question regarding findings that provide policy-relevant insights served as the framework for the meeting. Results synthesized from this Conference provide new evidence, reaffirm past findings, and offer guidance for future research efforts that will continue to incrementally advance the science required for reducing uncertainties in linking sources, air pollutants, human exposure, and health effects. This paper summarizes the Conference findings organized around the science questions. A number of key points emerged from the Conference findings. First, there is a need for greater focus on multipollutant science and management approaches that include more direct studies of the mixture of pollutants from sources with an emphasis on health studies at ambient concentrations. Further, a number of research groups reaffirmed a need for better understanding of biological mechanisms and apparent associations of various health effects with components of particulate matter (PM), such as elemental carbon, certain organic species, ultrafine particles, and certain trace elements such as Ni, V, and Fe(II), as well as some gaseous pollutants. Although much debate continues in this area, generation of reactive oxygen species induced by these and other species present in air pollution and the resulting oxidative stress and inflammation were reiterated as key pathways leading to respiratory and cardiovascular outcomes. The Conference also underscored significant advances in understanding the susceptibility of populations, including the role of genetics and epigenetics and the influence of socioeconomic and other confounding factors and their synergistic interactions with air pollutants. Participants also pointed out that short-and long-term intervention episodes that reduce pollution from sources and improve air quality continue to indicate that when pollution decreases so do reported adverse health effects. In the limited number of cases where specific sources or PM2.5 species were included in investigations, specific species are often associated with the decrease in effects. Other recent advances for improved exposure estimates for epidemiological studies included using new technologies such as microsensors combined with cell phone and integrated into real-time communications, hybrid air quality modeling such as combined receptor-and emission-based models, and surface observations used with remote sensing such as satellite data.

Modeling and Identification of an Open-frame Underwater Vehicle: The Yaw Motion Dynamics

A semi-autonomous unmanned underwater vehicle (UUV), named LAURS, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions of deep water oil fields. In this work, a method of modeling and identification of yaw motion dynamic system model of an open-frame underwater vehicle is presented. Using an on-board low cost magnetic compass sensor the method is based on the utilization of an uncoupled 1-DOF (degree of freedom) dynamic system equation and the application of the integral method which is the classical least squares algorithm applied to the integral form of the dynamic system equations. Experimental trials with the actual vehicle have been performed in a test tank and diving pool. During these experiments, thrusters responsible for yaw motion are driven by sinusoidal voltage signal profiles. An assessment of the feasibility of the method reveals that estimated dynamic system models are more reliable when considering slow and small sinusoidal voltage signal profiles, i.e. with larger periods and with relatively small amplitude and offset.

BEM modeling of saturated porous media susceptible to damage

This paper deals with the numerical analysis of saturated porous media, taking into account the damage phenomena on the solid skeleton. The porous media is taken into poro-elastic framework, in full-saturated condition, based on Biot's Theory. A scalar damage model is assumed for this analysis. An implicit boundary element method (BEM) formulation, based on time-independent fundamental solutions, is developed and implemented to couple the fluid flow and two-dimensional elastostatic problems. The integration over boundary elements is evaluated using a numerical Gauss procedure. A semi-analytical scheme for the case of triangular domain cells is followed to carry out the relevant domain integrals. The non-linear problem is solved by a Newton-Raphson procedure. Numerical examples are presented, in order to validate the implemented formulation and to illustrate its efficacy. (C) 2011 Elsevier Ltd. All rights reserved.

Implant Stability Measurements of Two Immediate Loading Protocols for the Edentulous Mandible: Rigid and Semi-rigid Splinting of the Implants

Aim: Primary and secondary stabilities of immediately loaded mandibular implants restored with fixed prostheses (FP) using rigid or semirigid splinting systems were clinically and radiographically evaluated. Methods: Fifteen edentulous patients were rehabilitated using hybrid FP; each had 5 implants placed between the mental foramens. Two groups were randomly divided: group 1-FP with the conventional rigid bar splinting the implants and group 2-semi-rigid cantilever extension system with titanium bars placed in the 2 distal abutment cylinders. Primary stability was evaluated using resonance frequency analysis after installation of the implant abutments. The measurements were made at 3 times: T0, at baseline; T1, 4 months after implant placement; and T2, 8 months after implant placement. Presence of mobility and inflammation in the implant surrounding regions were checked. Stability data were submitted to statistical analysis for comparison between groups (P, 0.05). Results: Implant survival rate for the implants was of 100% in both groups. No significant differences in the mean implant stability quotient values were found for both groups from baseline and after the 8-month follow-up. Conclusion: The immediate loading of the implants was satisfactory, and both splinting conditions (rigid and semi-rigid) can be successfully used for the restoration of edentulous mandibles. (Implant Dent 2012;21:486-490)

Longitudinal familial analysis of blood pressure involving parametric (co)variance functions

Abstract Background For analyzing longitudinal familial data we adopted a log-linear form to incorporate heterogeneity in genetic variance components over the time, and additionally a serial correlation term in the genetic effects at different levels of ages. Due to the availability of multiple measures on the same individual, we permitted environmental correlations that may change across time. Results Systolic blood pressure from family members from the first and second cohort was used in the current analysis. Measures of subjects receiving hypertension treatment were set as censored values and they were corrected. An initial check of the variance and covariance functions proposed for analyzing longitudinal familial data, using empirical semi-variogram plots, indicated that the observed trait dispersion pattern follows the assumptions adopted. Conclusion The corrections for censored phenotypes based on ordinary linear models may be an appropriate simple model to correct the data, ensuring that the original variability in the data was retained. In addition, empirical semi-variogram plots are useful for diagnosis of the (co)variance model adopted.

Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks

Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provade a very Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that interferences can be performed in time linear in the number of nodes if there is a single observed node. Because our proof is construtive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynominal-time algorithm for SQPn. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.