Developing predictive models of health literacy.

IntroductionLow health literacy (LHL) remains a formidable barrier to improving health care quality and outcomes. Given the lack of precision of single demographic characteristics to predict health literacy, and the administrative burden and inability of existing health literacy measures to estimate health literacy at a population level, LHL is largely unaddressed in public health and clinical practice. To help overcome these limitations, we developed two models to estimate health literacy.MethodsWe analyzed data from the 2003 National Assessment of Adult Literacy (NAAL), using linear regression to predict mean health literacy scores and probit regression to predict the probability of an individual having 'above basic' proficiency. Predictors included gender, age, race/ethnicity, educational attainment, poverty status, marital status, language spoken in the home, metropolitan statistical area (MSA) and length of time in U.S.ResultsAll variables except MSA were statistically significant, with lower educational attainment being the strongest predictor. Our linear regression model and the probit model accounted for about 30% and 21% of the variance in health literacy scores, respectively, nearly twice as much as the variance accounted for by either education or poverty alone.ConclusionsMultivariable models permit a more accurate estimation of health literacy than single predictors. Further, such models can be applied to readily available administrative or census data to produce estimates of average health literacy and identify communities that would benefit most from appropriate, targeted interventions in the clinical setting to address poor quality care and outcomes related to LHL

Parametric Modeling of the Church in the Studenica Monastery in Serbia

This project reveals surveying data and architectural design of the major church in the Studenica monastery complex in Serbia reflected in a variety of 3D models and the analysis of the church interior and exterior. Architecture-driven computational parametric modeling was done by using two types of data: close range photogrammetry and high precision laser scanning. The modeling, based on geometric parameters and other planimetric and volumetric analysis, is devised during the four-year study as part of the project Parametric Research of the Studenica Church, a UNESCO Heritage Site, as a Model for Advanced Studies of Medieval Architecture. These models allow for better understanding and representation of the proportional, aesthetic and illumination qualities of the Studenica church and for prototyping procedures for examining other medieval domed churches where we lack more detailed references about their architectural design

Modeling the illumination of the church at Studenica monastery during evening services

This paper presents an analytical model to analyze illumination of the church interior during the evening service. The focus is on the artificial light achieved using church lighting fixtures known as polycandela, which are suspended directly below the church dome. The analysis focuses on the main church (katholikon) at Studenica Monastery, built in Serbia sometime before 1208/9. By using a computer-generated model of the Studenica church derived from high-precision laser scanning and close-range photogrammetry rather than from more conventional architectural drawings of the church, we recreate the actual three-dimensional space of the church interior. Our model allows for a quantitative calculation and analysis of the amount of artificial light that could have been achieved inside medieval churches. We apply this model for the church at Studenica to better understand the lighting of medieval structures as well as more abstract and diagrammatic qualities of the sacred space of the church manifested by light conditions.Radovi sa radionice će biti publikovni u tematskom zborniku pod istim nazivom u izdanju poznatog izdavača akademskih radova - Koninklijke Brill NV, Leiden, Netherlands

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO

Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI. Supplemental material in the ancillary file

Three-Dimensional Microscopy Characterization of Death Receptor 5 Expression by Over-Activated Human Primary CD4+ T Cells and Apoptosis

Activation-induced cell death is a natural process that prevents tissue damages from over-activated immune cells. TNF-Related apoptosis ligand (TRAIL), a TNF family member, induces apoptosis of infected and tumor cells by binding to one of its two death receptors, DR4 or DR5. TRAIL was reported to be secreted by phytohemagglutinin (PHA)-stimulated CD4+ T cells in microvesicles

EpIG‐DB: A database of vascular epiphyte assemblages in the Neotropics

Vascular epiphytes are a diverse and conspicuous component of biodiversity in tropical and subtropical forests. Yet, the patterns and drivers of epiphyte assemblages are poorly studied in comparison with soil‐rooted plants. Current knowledge about diversity patterns of epiphytes mainly stems from local studies or floristic inventories, but this information has not yet been integrated to allow a better understanding of large‐scale distribution patterns. EpIG‐DB, the first database on epiphyte assemblages at the continental scale, resulted from an exhaustive compilation of published and unpublished inventory data from the Neotropics. The current version of EpIG‐DB consists of 463,196 individual epiphytes from 3,005 species, which were collected from a total of 18,148 relevés (host trees and ‘understory’ plots). EpIG‐DB reports the occurrence of ‘true’ epiphytes, hemiepiphytes and nomadic vines, including information on their cover, abundance, frequency and biomass. Most records (97%) correspond to sampled host trees, 76% of them aggregated in forest plots. The data is stored in a TURBOVEG database using the most up‐to‐date checklist of vascular epiphytes. A total of 18 additional fields were created for the standardization of associated data commonly used in epiphyte ecology (e.g. by considering different sampling methods). EpIG‐DB currently covers six major biomes across the whole latitudinal range of epiphytes in the Neotropics but welcomes data globally. This novel database provides, for the first time, unique biodiversity data on epiphytes for the Neotropics and unified guidelines for future collection of epiphyte data. EpIG‐DB will allow exploration of new ways to study the community ecology and biogeography of vascular epiphytes