Hardy-Muckenhoupt Bounds for Laplacian Eigenvalues

We present two graph quantities Psi(G,S) and Psi_2(G) which give constant factor estimates to the Dirichlet and Neumann eigenvalues, lambda(G,S) and lambda_2(G), respectively. Our techniques make use of a discrete Hardy-type inequality due to Muckenhoupt

Caractérisation des situations hydro-biologiques et potentialités de pêche thonière au Cap Lopez en Juin et Juillet 1972 et 1974

Surface temperature was measured by remote sensing through Cape Lopez (Gulf of Guinea) frontal region during the fishing season in June and July 1972 and 1974. Twelve typical situations are analysed through four main directions: surface situation, tendency, hydrobiological structure and availability to fisheries. The tuna behavior is analysed in relation with the frontal zone movements and a mechanism which tends to aggregate important shoals of tunas is presented

Simulations of the angular dependence of the dipole-dipole interaction among Rydberg atoms

The dipole-dipole interaction between two Rydberg atoms depends on the relative orientation of the atoms and on the change in the magnetic quantum number. We simulate the effect of this anisotropy on the energy transport in an amorphous many atom system subject to a homogeneous applied electric field. We consider two experimentally feasible geometries and find that the effects should be measurable in current generation imaging experiments. In both geometries atoms of $p$ character are localized to a small region of space which is immersed in a larger region that is filled with atoms of $s$ character. Energy transfer due to the dipole-dipole interaction can lead to a spread of $p$ character into the region initially occupied by $s$ atoms. Over long timescales the energy transport is confined to the volume near the border of the $p$ region which is suggestive of Anderson localization. We calculate a correlation length of 6.3~$\mu$m for one particular geometry.Comment: 6 pages, 5 figures, revised draf

Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion

Atmospheric trace-gas inversion refers to any technique used to predict spatial and temporal fluxes using mole-fraction measurements and atmospheric simulations obtained from computer models. Studies to date are most often of a data-assimilation flavour, which implicitly consider univariate statistical models with the flux as the variate of interest. This univariate approach typically assumes that the flux field is either a spatially correlated Gaussian process or a spatially uncorrelated non-Gaussian process with prior expectation fixed using flux inventories (e.g., NAEI or EDGAR in Europe). Here, we extend this approach in three ways. First, we develop a bivariate model for the mole-fraction field and the flux field. The bivariate approach allows optimal prediction of both the flux field and the mole-fraction field, and it leads to significant computational savings over the univariate approach. Second, we employ a lognormal spatial process for the flux field that captures both the lognormal characteristics of the flux field (when appropriate) and its spatial dependence. Third, we propose a new, geostatistical approach to incorporate the flux inventories in our updates, such that the posterior spatial distribution of the flux field is predominantly data-driven. The approach is illustrated on a case study of methane (CH$_4$) emissions in the United Kingdom and Ireland.Comment: 39 pages, 8 figure

Empirical model for quasi direct current interruption with a convoluted arc

This contribution considers various aspects of a quasi direct current, convoluted arc produced by a magnetic field (B-field) connected in parallel with an RLC circuit that have not been considered in combination. These aspects are the arc current limitation due to the arc convolution, changes in arc resistance due to the B-field and material ablation, and the relative significance of the RLC circuit in producing an artificial current zero. As a result, it has been possible to produce an empirical equation for predicting the current interruption capability in terms of the B-field magnitude and RLC components

Brachial Artery Constriction during Brachial Artery Reactivity Testing Predicts Major Adverse Clinical Outcomes in Women with Suspected Myocardial Ischemia: Results from the NHLBI-Sponsored Women's Ischemia Syndrome Evaluation (WISE) Study

Background:Limited brachial artery (BA) flow-mediated dilation during brachial artery reactivity testing (BART) has been linked to increased cardiovascular risk. We report on the phenomenon of BA constriction (BAC) following hyperemia.Objectives:To determine whether BAC predicts adverse CV outcomes and/or mortality in the women's ischemic Syndrome Evaluation Study (WISE). Further, as a secondary objective we sought to determine the risk factors associated with BAC.Methods:We performed BART on 377 women with chest pain referred for coronary angiography and followed for a median of 9.5 years. Forearm ischemia was induced with 4 minutes occlusion by a cuff placed distal to the BA and inflated to 40mm Hg > systolic pressure. BAC was defined as >4.8% artery constriction following release of the cuff. The main outcome was major adverse events (MACE) including all-cause mortality, non-fatal MI, non-fatal stroke, or hospitalization for heart failure.Results:BA diameter change ranged from -20.6% to +44.9%, and 41 (11%) women experienced BAC. Obstructive CAD and traditional CAD risk factors were not predictive of BAC. Overall, 39% of women with BAC experienced MACE vs. 22% without BAC (p=0.004). In multivariate Cox proportional hazards regression, BAC was a significant independent predictor of MACE (p=0.018) when adjusting for obstructive CAD and traditional risk factors.Conclusions:BAC predicts almost double the risk for major adverse events compared to patients without BAC. This risk was not accounted for by CAD or traditional risk factors. The novel risk marker of BAC requires further investigation in women. © 2013 Sedlak et al

Alignment of patient and primary care practice member perspectives of chronic illness care: a cross-sectional analysis

Polly H. Noel and Luci K. Leykum are with the South Texas Veterans Health Care System, 7400 Merton Minter Blvd, San Antonio, TX 78229, USA -- Polly H. Noel, Ray F. Palmer, Raquel L. Romero, Luci K. Leykum, Holly J. Lanham, and Krista W. Bowers are with the Department of Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229, USA -- Michael L. Parchman is with the MacColl Center for Healthcare Innovation, Group Health Research Institute, Group Health Cooperative, 1730 Minor Ave 1600, Seattle, WA 98101, USA -- Holly J. Leykum is with the The McCombs School of Business, The University of Texas at Austin, 2110 Speedway, Stop B6000, Austin, TX 78712, USA -- John E. Zeber is with the Central Texas Veterans Health Care System, 1901 S. 1st St, Temple, TX 76504, USA and Scott and White Healthcare Center for Applied Health Research, 2401 S. 31st St, Temple, TX 76508, USABackground: Little is known as to whether primary care teams’ perceptions of how well they have implemented the Chronic Care Model (CCM) corresponds with their patients’ own experience of chronic illness care. We examined the extent to which practice members’ perceptions of how well they organized to deliver care consistent with the CCM were associated with their patients’ perceptions of the chronic illness care they have received. Methods: Analysis of baseline measures from a cluster randomized controlled trial testing a practice facilitation intervention to implement the CCM in small, community-based primary care practices. All practice “members” (i.e., physician providers, non-physician providers, and staff) completed the Assessment of Chronic Illness Care (ACIC) survey and adult patients with 1 or more chronic illnesses completed the Patient Assessment of Chronic Illness Care (PACIC) questionnaire. Results: Two sets of hierarchical linear regression models accounting for nesting of practice members (N = 283) and patients (N = 1,769) within 39 practices assessed the association between practice member perspectives of CCM implementation (ACIC scores) and patients’ perspectives of CCM (PACIC). ACIC summary score was not significantly associated with PACIC summary score or most of PACIC subscale scores, but four of the ACIC subscales were consistently associated with PACIC summary score and the majority of PACIC subscale scores after controlling for patient characteristics. The magnitude of the coefficients, however, indicates that the level of association is weak. Conclusions: The ACIC and PACIC scales appear to provide complementary and relatively unique assessments of how well clinical services are aligned with the CCM. Our findings underscore the importance of assessing both patient and practice member perspectives when evaluating quality of chronic illness care.Information, Risk, and Operations Management (IROM)[email protected]

Impact of Social Determinants of Health on Healthcare Disparities in Florida

Objective Healthcare disparities disproportionately affect underserved and marginalized communities due to social determinants of health (SDoH), contributing to significant differences in health outcomes and life expectancy within different communities in Florida. This observational study aimed to understand the impact of SDoH, such as race/ethnicity, income level, and education attainment on healthcare access in Florida. Methods Self-reported data from the 2020 Behavioral Risk Factor Surveillance System were pooled to evaluate disparities in healthcare access by race/ethnicity, income, and education level in Florida. Results Health status and healthcare access vary based on characteristics related to SDoH, including race/ethnicity, income level, and educational attainment. Health status and healthcare access increased with income and education attainment. There were no significant disparities in health status and healthcare access among racial and ethnic groups. Conclusion While race and ethnicity were not significant predictors of health status nor healthcare access, income level and education were positively correlated which may be related to policy including Florida\u27s lack of Medicaid expansion or population characteristics such as health-seeking behaviors. Understanding the prevalence of healthcare disparities based on SDoH can inform and support the implementation of evidence-based strategies for improving the accessibility and affordability of culturally competent care for underserved populations