Constraint-preserving boundary treatment for a harmonic formulation of the Einstein equations

We present a set of well-posed constraint-preserving boundary conditions for a first-order in time, second-order in space, harmonic formulation of the Einstein equations. The boundary conditions are tested using robust stability, linear and nonlinear waves, and are found to be both less reflective and constraint preserving than standard Sommerfeld-type boundary conditions.Comment: 18 pages, 7 figures, accepted in CQ

Spectroscopic scanning tunneling microscopy insights into Fe-based superconductors

In the first three years since the discovery of Fe-based high Tc superconductors, scanning tunneling microscopy (STM) and spectroscopy have shed light on three important questions. First, STM has demonstrated the complexity of the pairing symmetry in Fe-based materials. Phase-sensitive quasiparticle interference (QPI) imaging and low temperature spectroscopy have shown that the pairing order parameter varies from nodal to nodeless s\pm within a single family, FeTe1-xSex. Second, STM has imaged C4 -> C2 symmetry breaking in the electronic states of both parent and superconducting materials. As a local probe, STM is in a strong position to understand the interactions between these broken symmetry states and superconductivity. Finally, STM has been used to image the vortex state, giving insights into the technical problem of vortex pinning, and the fundamental problem of the competing states introduced when superconductivity is locally quenched by a magnetic field. Here we give a pedagogical introduction to STM and QPI imaging, discuss the specific challenges associated with extracting bulk properties from the study of surfaces, and report on progress made in understanding Fe-based superconductors using STM techniques.Comment: 36 pages, 23 figures, 229 reference

Integration of Machine Learning and Mechanistic Models Accurately Predicts Variation in Cell Density of Glioblastoma Using Multiparametric MRI

Glioblastoma (GBM) is a heterogeneous and lethal brain cancer. These tumors are followed using magnetic resonance imaging (MRI), which is unable to precisely identify tumor cell invasion, impairing effective surgery and radiation planning. We present a novel hybrid model, based on multiparametric intensities, which combines machine learning (ML) with a mechanistic model of tumor growth to provide spatially resolved tumor cell density predictions. The ML component is an imaging data-driven graph-based semi-supervised learning model and we use the Proliferation-Invasion (PI) mechanistic tumor growth model. We thus refer to the hybrid model as the ML-PI model. The hybrid model was trained using 82 image-localized biopsies from 18 primary GBM patients with pre-operative MRI using a leave-one-patient-out cross validation framework. A Relief algorithm was developed to quantify relative contributions from the data sources. The ML-PI model statistically significantly outperformed (p \u3c 0.001) both individual models, ML and PI, achieving a mean absolute predicted error (MAPE) of 0.106 ± 0.125 versus 0.199 ± 0.186 (ML) and 0.227 ± 0.215 (PI), respectively. Associated Pearson correlation coefficients for ML-PI, ML, and PI were 0.838, 0.518, and 0.437, respectively. The Relief algorithm showed the PI model had the greatest contribution to the result, emphasizing the importance of the hybrid model in achieving the high accuracy

Factors associated with health-seeking behavior among migrant workers in Beijing, China

<p>Abstract</p> <p>Background</p> <p>Migrant workers are a unique phenomenon in the process of China's economic transformation. The household registration system classifies them as temporary residents in cities, putting them in a vulnerable state with an unfair share of urban infrastructure and social public welfare. The amount of pressure inflicted by migrant workers in Beijing, as one of the major migration destinations, is currently at a threshold. This study was designed to assess the factors associated with health-seeking behavior and to explore feasible solutions to the obstacles migrant workers in China faced with when accessing health-care.</p> <p>Methods</p> <p>A sample of 2,478 migrant workers in Beijing was chosen by the multi-stage stratified cluster sampling method. A structured questionnaire survey was conducted via face-to-face interviews between investigators and subjects. The multilevel methodology (MLM) was used to demonstrate the independent effects of the explanatory variables on health seeking behavior in migrant workers.</p> <p>Results</p> <p>The medical visitation rate of migrant workers within the past two weeks was 4.8%, which only accounted for 36.4% of those who were ill. Nearly one-third of the migrant workers chose self-medication (33.3%) or no measures (30.3%) while ill within the past two weeks. 19.7% of the sick migrants who should have been hospitalized failed to receive medical treatment within the past year. According to self-reported reasons, the high cost of health service was a significant obstacle to health-care access for 40.5% of the migrant workers who became sick. However, 94.0% of the migrant workers didn't have any insurance coverage in Beijing. The multilevel model analysis indicates that health-seeking behavior among migrants is significantly associated with their insurance coverage. Meanwhile, such factors as household monthly income per capita and working hours per day also affect the medical visitation rate of the migrant workers in Beijing.</p> <p>Conclusion</p> <p>This study assesses the influence of socio-demographic characteristics on the migrant workers' decision to seek health care services when they fall ill, and it also indicates that the current health service system discourages migrant workers from seeking appropriate care of good quality. Relevant policies of public medical insurance and assistance program should be vigorously implemented for providing affordable health care services to the migrants. Feasible measures need to be taken to reduce the health risks associated with current hygiene practices and equity should be assured in access to health care services among migrant workers.</p

Food allergy knowledge, attitudes and beliefs: Focus groups of parents, physicians and the general public

<p>Abstract</p> <p>Background</p> <p>Food allergy prevalence is increasing in US children. Presently, the primary means of preventing potentially fatal reactions are avoidance of allergens, prompt recognition of food allergy reactions, and knowledge about food allergy reaction treatments. Focus groups were held as a preliminary step in the development of validated survey instruments to assess food allergy knowledge, attitudes, and beliefs of parents, physicians, and the general public.</p> <p>Methods</p> <p>Eight focus groups were conducted between January and July of 2006 in the Chicago area with parents of children with food allergy (3 groups), physicians (3 groups), and the general public (2 groups). A constant comparative method was used to identify the emerging themes which were then grouped into key domains of food allergy knowledge, attitudes, and beliefs.</p> <p>Results</p> <p>Parents of children with food allergy had solid fundamental knowledge but had concerns about primary care physicians' knowledge of food allergy, diagnostic approaches, and treatment practices. The considerable impact of children's food allergies on familial quality of life was articulated. Physicians had good basic knowledge of food allergy but differed in their approach to diagnosis and advice about starting solids and breastfeeding. The general public had wide variation in knowledge about food allergy with many misconceptions of key concepts related to prevalence, definition, and triggers of food allergy.</p> <p>Conclusion</p> <p>Appreciable food allergy knowledge gaps exist, especially among physicians and the general public. The quality of life for children with food allergy and their families is significantly affected.</p

Modern microwave methods in solid state inorganic materials chemistry: from fundamentals to manufacturing

No abstract available

The Potential for Enhancing the Power of Genetic Association Studies in African Americans through the Reuse of Existing Genotype Data

We consider the feasibility of reusing existing control data obtained in genetic association studies in order to reduce costs for new studies. We discuss controlling for the population differences between cases and controls that are implicit in studies utilizing external control data. We give theoretical calculations of the statistical power of a test due to Bourgain et al (Am J Human Genet 2003), applied to the problem of dealing with case-control differences in genetic ancestry related to population isolation or population admixture. Theoretical results show that there may exist bounds for the non-centrality parameter for a test of association that places limits on study power even if sample sizes can grow arbitrarily large. We apply this method to data from a multi-center, geographically-diverse, genome-wide association study of breast cancer in African-American women. Our analysis of these data shows that admixture proportions differ by center with the average fraction of European admixture ranging from approximately 20% for participants from study sites in the Eastern United States to 25% for participants from West Coast sites. However, these differences in average admixture fraction between sites are largely counterbalanced by considerable diversity in individual admixture proportion within each study site. Our results suggest that statistical correction for admixture differences is feasible for future studies of African-Americans, utilizing the existing controls from the African-American Breast Cancer study, even if case ascertainment for the future studies is not balanced over the same centers or regions that supplied the controls for the current study

The Endogenous Th17 Response in NO<inf>2</inf>-Promoted Allergic Airway Disease Is Dispensable for Airway Hyperresponsiveness and Distinct from Th17 Adoptive Transfer

Severe, glucocorticoid-resistant asthma comprises 5-7% of patients with asthma. IL-17 is a biomarker of severe asthma, and the adoptive transfer of Th17 cells in mice is sufficient to induce glucocorticoid-resistant allergic airway disease. Nitrogen dioxide (NO2) is an environmental toxin that correlates with asthma severity, exacerbation, and risk of adverse outcomes. Mice that are allergically sensitized to the antigen ovalbumin by exposure to NO2 exhibit a mixed Th2/Th17 adaptive immune response and eosinophil and neutrophil recruitment to the airway following antigen challenge, a phenotype reminiscent of severe clinical asthma. Because IL-1 receptor (IL-1R) signaling is critical in the generation of the Th17 response in vivo, we hypothesized that the IL-1R/Th17 axis contributes to pulmonary inflammation and airway hyperresponsiveness (AHR) in NO2-promoted allergic airway disease and manifests in glucocorticoid-resistant cytokine production. IL-17A neutralization at the time of antigen challenge or genetic deficiency in IL-1R resulted in decreased neutrophil recruitment to the airway following antigen challenge but did not protect against the development of AHR. Instead, IL-1R-/- mice developed exacerbated AHR compared to WT mice. Lung cells from NO2-allergically inflamed mice that were treated in vitro with dexamethasone (Dex) during antigen restimulation exhibited reduced Th17 cytokine production, whereas Th17 cytokine production by lung cells from recipient mice of in vitro Th17-polarized OTII T-cells was resistant to Dex. These results demonstrate that the IL-1R/Th17 axis does not contribute to AHR development in NO2-promoted allergic airway disease, that Th17 adoptive transfer does not necessarily reflect an endogenously-generated Th17 response, and that functions of Th17 responses are contingent on the experimental conditions in which they are generated. © 2013 Martin et al