Tobacco Use and Health Insurance Literacy Among Vulnerable Populations: Implications for Health Reform

Background: Under the Affordable Care Act (ACA), millions of Americans have been enrolling in the health insurance marketplaces. Nearly 20% of them are tobacco users. As part of the ACA, tobacco users may face up to 50% higher premiums that are not eligible for tax credits. Tobacco users, along with the uninsured and racial/ethnic minorities targeted by ACA coverage expansions, are among those most likely to suffer from low health literacy – a key ingredient in the ability to understand, compare, choose, and use coverage, referred to as health insurance literacy. Whether tobacco users choose enough coverage in the marketplaces given their expected health care needs and are able to access health care services effectively is fundamentally related to understanding health insurance. However, no studies to date have examined this important relationship.Methods: Data were collected from 631 lower-income, minority, rural residents of Virginia. Health insurance literacy was assessed by asking four factual questions about the coverage options presented to them. Adjusted associations between tobacco use and health insurance literacy were tested using multivariate linear regression, controlling for numeracy, risk-taking, discount rates, health status, experiences with the health care system, and demographics.Results: Nearly one third (31%) of participants were current tobacco users, 80% were African American and 27% were uninsured. Average health insurance literacy across all participants was 2.0 (SD 1.1) out of a total possible score of 4. Current tobacco users had significantly lower HIL compared to non-users (−0.22, p \u3c 0.05) after adjustment. Participants who were less educated, African American, and less numerate reported more difficulty understanding health insurance (p \u3c 0.05 each.)Conclusions: Tobacco users face higher premiums for health coverage than non-users in the individual insurance marketplace. Our results suggest they may be less equipped to shop for plans that provide them with adequate out-of-pocket risk protection, thus placing greater financial burdens on them and potentially limiting access to tobacco cessation and treatment programs and other needed health services

High Fidelity Satellite Navigation Receiver Front-End for Advanced Signal Quality Monitoring and Authentication

Over the last several years, interest in utilizing foreign satellite timing and navigation (satnav) signals to augment GPS has grown. Doing so is not without risks; foreign satnav signals must be vetted and determined to be trustworthy before use in military applications. Advanced signal quality monitoring methods can help to ensure that only authentic and reliable satnav signals are utilized. To effectively monitor and authenticate signals, the front-end must impress as little distortions upon the received signal as possible. The purpose of this study is to design, fabricate, and test the performance of a high-fidelity satnav receiver front-end for advanced monitoring of foreign and domestic space vehicle signals

Poisson\u27s Equation

This presentation deals with how to solve Poisson\u27s Equation for a two dimensional plate. The numbers can be represented as heat, charge density, and gravitational force. This is a generalization of Laplace\u27s Equation, which are steady state problems. In this problem, it is broken up into two simpler problems. For the first part, there are two ways of solving it since it is two dimensional. This presentation covers both ways of solving it using separation of variables, orthogonality, and partial differential equations. In addition, it shows how to solve the second part and finalize Poisson\u27s Equation

System Geometries and Transit / Eclipse Probabilities

Transiting exoplanets provide access to data to study the mass-radius relation and internal structure of extrasolar planets. Long-period transiting planets allow insight into planetary environments similar to the Solar System where, in contrast to hot Jupiters, planets are not constantly exposed to the intense radiation of their parent stars. Observations of secondary eclipses additionally permit studies of exoplanet temperatures and large-scale exo-atmospheric properties. We show how transit and eclipse probabilities are related to planet-star system geometries, particularly for long-period, eccentric orbits. The resulting target selection and observational strategies represent the principal ingredients of our photometric survey of known radial-velocity planets with the aim of detecting transit signatures (TERMS).Comment: 3 pages, 2 figures. Comments: To appear in the ASP Conference Proceedings: Detection and Dynamics of Transiting Exoplanets; Proceedings of Haute Provence Observatory Colloquium (23-27 August 2010); Edited by F. Bouchy, R. F. Diaz, and C. Mouto

Noncontact electrical metrology of Cu/low-k interconnect for semiconductor production wafers

We have demonstrated a technique capable of in-line measurement of dielectric constant of low-k interconnect films on patterned wafers utilizing a test key of ~50x50 \mu m in size. The test key consists of a low-k film backed by a Cu grid with >50% metal pattern density and <250 nm pitch, which is fully compatible with the existing dual-damascene interconnect manufacturing processes. The technique is based on a near-field scanned microwave probe and is noncontact, noninvasive, and requires no electrical contact to or grounding of the wafer under test. It yields <0.3% precision and 2% accuracy for the film dielectric constant

Impact of Mechanical Ventilation and Indoor Air Recirculation Rates on the Performance of an Active Membrane Energy Exchanger System

As concern for indoor air quality grows, many buildings will likely opt to provide higher rates of outdoor air than would traditionally be specified. This imposes a challenge on air conditioning systems since the latent loads associated with ventilation air are much higher than those associated with recirculated air. Membrane-based technologies, which enable mechanical separation of water vapor from air, have recently emerged as promising candidates for efficiently providing dehumidification, however, limitations remain. To date, most modeling work on these types of systems has focused on 100% outdoor air configurations that employ isothermal dehumidification designs. However, we have proposed a design referred to as the Active Membrane Energy Exchanger (AMX) that integrates cooling and membrane dehumidification into one device (thus non-isothermal) for a range of benefits. This work presents a specific application of the AMX in a system configuration that includes the treatment of both outdoor ventilation air and recirculated air. The system’s performance is analyzed over a broad range of ambient conditions and the effect of ventilation rates on the system performance is studied in detail. This configuration is found to be capable of providing three times the ventilation air of conventional systems with comparable or less energy consumption for the given conditions. Additionally, the optimal membrane module-outlet air temperature is found to be 18-20 ℃. Lastly, a case study using EnergyPlus building simulations shows that this configuration can reduce annual cooling energy requirements by as much as 34% in hot and humid cities for buildings with high latent loads and high ventilation rates

Comparing Maintenance Strategies for Rooftop Units having Multiple Faults through Simulation

Maintenance strategies currently used for commercial building rooftop units (RTU) can be classified into two categories: reactive strategies and proactive strategies. In reactive strategies, maintenance and service is performed only when needed, e.g. when a system is unable to maintain setpoint. In proactive strategies, maintenance is scheduled at routine intervals to avoid service interruptions regardless of whether the system actually needs it. While these strategies could not be more different, it is unclear which strategy is more optimal. Moreover, whether one strategy is more optimal than the other more than likely depends on the application – contributing to much uncertainty. A third category of maintenance has been enabled by automated fault detection and diagnostics (AFDD) technologies that aims to provide building operators and service providers more detailed information about the actual state of equipment in the field. This third strategy, called condition-based maintenance, aims to optimize service and maintenance decisions throughout the life of equipment based on updated measurements of performance and service costs. In this work, these three types of maintenance strategies are compared using a commercial building simulation model utilizing a fault impact equipment model. Along with comparing different strategies under the same fault scenario, ambient conditions, and loads, optimal maintenance schedules are generated using dynamic programming. Benefits of a condition-based maintenance approach utilizing a suite of AFDD methodologies are highlighted with respect to reducing operating costs

Artificial Neural Networks for Fast Rooftop Unit Fault Impact Modeling and Simulation

Like any electromechanical system, direct-expansion (DX) air conditioners and heat pumps often develop faults over time that contribute to reduced operating efficiency, more frequent comfort violations, or even premature failure. Automated fault detection and diagnosis (AFDD) methods have been developed for these systems and much experimental effort has been undertaken for their evaluation. In order to reduce development costs required for AFDD technologies, additional research related to modeling DX equipment subject to faults has been undertaken. Investigation of AFDD methods in a virtual environment typically requires relatively detailed equipment models based in some part on thermodynamic principles. Because of these embedded constraints, simulation of faulty equipment operating performance can be time consuming and computationally intensive. In this work, meta-models based on previously developed greybox fault impact models for DX equipment have been developed using artificial neural networks. After tuning these neural network meta-models for different equipment, AFDD performance and fault impacts were simulated using a simple building load model. Significant computational speedups were realized over the original greybox equipment models without loss of significant accuracy. Ultimately through careful meta-model training, it is believed that using neural networks to approximate detailed, computationally-intensive equipment or building models may be useful in applications that require frequent model evaluations