Visual fields: back to the future.

This article provides an overview of recent research in perimetry as well as some emerging ideas for improving the ability of perimetric testing to detect glaucoma and its progression. It discusses the benefits of carrying out perimetric tests as part of the evaluation and management of patients with glaucoma and those suspected of having the condition, arguing that stable technology is necessary for continued monitoring

Structures for Reentry Heating

The basic structural approaches for dealing with reentry heating of manned vehicles are summarized. The weight and development status of both radiative and ablative shields are given and the application of these shields to various vehicles is indicated

Self-reported predictors of depressive symptomatology in an elderly population with type 2 diabetes mellitus: a prospective cohort study

<p>Abstract</p> <p>Background</p> <p>The prevalence of depression increases among the elderly with chronic medical conditions like diabetes. Hence, the purpose of this study was to determine predictors of depressive symptomatology in Medicare enrolled elderly population with type 2 diabetes mellitus.</p> <p>Methods</p> <p>A prospective cohort study was conducted by administrating health risk assessment questionnaire to elderly (≥65 years) with type 2 diabetes. Responses were linked with administrative claim's data. Data were obtained from elderly with type 2 diabetes who were enrolled in Medicare Health Maintenance Organization (HMO) in southeastern United States. The instrument collected information related to demographics, health status, medication use, and healthcare service utilization prior to enrollment. Responses were combined with the administrative claims data of HMO to obtain information on actual utilization of healthcare resources. The Short Form Center for Epidemiologic Studies Depression scale was used to assess depressive symptoms. Multivariable logistic regression analyses were conducted to determine predictor variables.</p> <p>Results</p> <p>Of 792 respondents, about 17% had depressive symptoms. Almost 96% of patients were using 1 or more antidiabetic medications. Overall, increased risk of depression was associated with lower health related quality of life (HRQoL) (OR: 0.97; 95% CI: 0.96–0.98) and higher impairments in instrumental activities of daily living (IADLs) (OR: 1.31; 95% CI: 1.14–0.52) in elderly patients. Poor health related quality of life (OR: 0.97, 95%CI: 0.95–0.99) was associated with higher risk of depression in patients on insulin therapy.</p> <p>Conclusion</p> <p>Impairments in daily activities and lower HRQoL were predictors of depressive symptomatology in elderly with diabetes. Determinants of depression varied according to pharmacotherapeutic class of antidiabetic medications.</p

Diabetes management before and after cancer diagnosis: missed opportunity

Background Few studies have examined the management of comorbidities in cancer patients. This study used population-based data to estimate the guideline concordance rates for diabetes management before and after cancer diagnosis and examined if diabetes management services among cancer patients was associated with characteristics of the hospital where the patient was treated. Methods We linked 2005-2009 Medicare claims data to information on 2,707 breast and colorectal cancers patients in state cancer registry files. Multivariate logistic regression models examined hospital characteristics associated with receipt of diabetes management care after cancer diagnosis. Results The rates of HbAlc testing, LDL-C testing, and retinal eye exam decreased from 72.7%, 79.6%, and 57.9% before cancer diagnosis to 58.3%, 69.5%, and 55.8% after diagnosis. The pre- and post-diagnosis diabetes management care was not significantly different by hospital characteristics in the bivariate analysis except for that the distance between residence and hospital was negatively related to retinal eye exam after diagnosis (P Conclusions Cancer patients received fewer diabetes management care after diagnosis than prior to diagnosis, even for those who were treated in large comprehensive centers. This may reflect a missed opportunity to connect diabetic cancer patients to diabetes care. This study provides benchmarks to measure improvements in comorbidity management among cancer patients

Dataset for Response of the Invasive Alliaria Petiolata to Extreme Temperatures and Drought

Alliaria petiolata, a strict biennial in North America, can have annual alternating high abundance of rosettes and flowering plants. We monitored changes in abundance of rosettes and flowering plants in permanent plots (2004 to 2014). Three times during our study the alternating yearly cycle was not observed (2007-2008, 2008-2009, and 2013-2014). We concluded stochastic Extreme Climate Events (ECEs), deviating from long-term climatic data norms (10th or 90th. percentile), likely caused negative organism responses. Long-term data from a local NOAA station located 25 km from our study site included monthly data (1) total precipitation, (2) number of days with \u3e 0.13 cm precipitation, and (3) mean and minimum temperatures. September 2007 met criteria for ECEs for all monthly variables. We first observed A. petiolata on our study site in 1988 and by the early 1990’s it was abundant. To determine if September 2007 significantly differed from other Septembers (1984-2014) we used six variables related to drought: (1) total precipitation, (2) number of days with precipitation, (3) number of contiguous days without precipitation, (4) mean monthly temperature, (5) mean maximum daily temperature, and (6) the number of days with temperatures \u3e 30 o C. The first two variables likely increase plant stress as they decrease, whereas stress declines as the remaining variables decrease. We used the six variables to generate a Principal Component Analysis (PCA) biplot. Axes 1 and 2 accounted for 74.3% of the variance. Record-breaking minimum temperatures (ECEs) for January (2009) and February-March (2014) likely reduced rosette abundance and disrupted reestablishment of alternating high abundance of rosettes and flowering plants. Our data suggest that a single ECE variable, minimum temperature, and multiple ECE variables related to drought likely had negative effects on A. petiolata

Constraints preserving genetic algorithm for learning fuzzy measures with an application to ontology matching

Abstract. Both the fuzzy measure and integral have been widely studied for multi-source information fusion. A number of researchers have proposed optimization techniques to learn a fuzzy measure from training data. In part, this task is difficult as the fuzzy measure can have a large number of free parameters (2 N − 2 for N sources) and it has many (monotonicity) constraints. In this paper, a new genetic algorithm approach to constraint preserving optimization of the fuzzy measure is present for the task of learning and fusing different ontology matching results. Preliminary results are presented to show the stability of the leaning algorithm and its effectiveness compared to existing approaches

Adjuvant therapy use among Appalachian breast cancer survivors

There is a paucity of literature systemically examining the effects of access to cancer care resources on adjuvant endocrine therapy (AET) use behaviors, especially in underserved regions such as the Appalachian region in the United States, where gaps in healthcare access are well documented. The objectives of this study were to explore AET adherence and persistence in Appalachia, delineate the effects of access to care cancer on adherence/persistence, and evaluate the influences of adherence and persistence on overall survival. A retrospective cohort study from 2006 to 2008 was conducted among female breast cancer survivors living in the Appalachian counties of 4 states (PA, OH, KY, and NC). We linked cancer registries to Medicare claims data and included patients with invasive, nonmetastatic, hormone-receptor-positive breast cancer who received guideline-recommended AET. Medication adherence was defined as corresponding to a Medication Possession Ratio (MPR) ≥0.8 and logistic regression was utilized to assess predictors of adherence. Medication nonpersistence was defined as the discontinuation of drugs after exceeding a 60-day medication gap, and multivariate adjusted estimates of nonpersistence were obtained using the Cox proportional hazards (PH) model. About 31% of the total 428 patients were not adherent to AET, and 30% were not persistent over an average follow-up period of 421 days. Tamoxifen, relative to aromatase inhibitors, was associated with higher odds of adherence (odds ratio = 2.82, P \u3c 0.001) and a lower risk of nonpersistence (hazard ratio = 0.40, P \u3c 0.001). Drug-related side effects like pain may be an important factor leading to nonadherence and early discontinuation. In addition, aromatase inhibitor (AI) adherence and persistence were significantly influenced by out-of-pocket drug costs, dual eligibility status, and coverage gaps. Nonadherence to and nonpersistence with AET were associated with higher risks of all-cause mortality. Our findings of suboptimal AET adherence/persistence in Appalachia as well as positive associations between AET adherence/persistence and overall survival outcomes further underscore the importance of ensuring appropriate AET use in this population to reduce breast cancer mortality disparities. Our findings also suggest that intervention strategies focusing on individualized treatment and medication-related factors may improve adjuvant treatment use

Magnetocentrifugal Winds in 3D: Nonaxisymmetric Steady State

Outflows can be loaded and accelerated to high speeds along rapidly rotating, open magnetic field lines by centrifugal forces. Whether such magnetocentrifugally driven winds are stable is a longstanding theoretical problem. As a step towards addressing this problem, we perform the first large-scale 3D MHD simulations that extend to a distance $\sim 10^2$ times beyond the launching region, starting from steady 2D (axisymmetric) solutions. In an attempt to drive the wind unstable, we increase the mass loading on one half of the launching surface by a factor of $\sqrt{10}$, and reduce it by the same factor on the other half. The evolution of the perturbed wind is followed numerically. We find no evidence for any rapidly growing instability that could disrupt the wind during the launching and initial phase of propagation, even when the magnetic field of the magnetocentrifugal wind is toroidally dominated all the way to the launching surface. The strongly perturbed wind settles into a new steady state, with a highly asymmetric mass distribution. The distribution of magnetic field strength is, in contrast, much more symmetric. We discuss possible reasons for the apparent stability, including stabilization by an axial poloidal magnetic field, which is required to bend field lines away from the vertical direction and produce a magnetocentrifugal wind in the first place.Comment: 10 pages, 2 figures, accepted for publication in ApJ