92 research outputs found

    Incorporating a Hyperspectral Direct-Diffuse Pyranometer in an Above-Water Reflectance Algorithm

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    In situ hyperspectral remote-sensing reflectance (Rrs(λ)) is used to derive water quality products and perform autonomous monitoring of aquatic ecosystems. Conventionally, above-water Rrs(λ) is estimated from three spectroradiometers which measure downwelling planar irradiance(Ed(λ)), sky radiance (Ls(λ)), and total upwelling radiance (Lt(λ)), with a scaling of Ls(λ)/Ed(λ)used to correct for surface-reflected radiance. Here, we incorporate direct and diffuse irradiance,(Edd(λ)) and Eds(λ)), from a hyperspectral pyranometer (HSP) in an Rrs(λ) processing algorithm from a solar-tracking radiometry platform (So-Rad). HSP measurements of sun and sky glint (scaled Edd(λ)/Ed(λ) and Eds(λ)/Ed(λ)) replace model-optimized terms in the 3C (three-glint component) Rrs(λ) algorithm, which estimates Rrs(λ) via spectral optimization of modelled atmospheric and water properties with respect to measured radiometric quantities. We refer to the HSP-enabled method as DD (direct-diffuse) and compare differences in Rrs(λ) and Rrs(λ) variability (assessed over 20 min measurement cycles) between 3C and DD as a function of atmospheric optical state using data from three ports in the Western Channel. The greatest divergence between the algorithms occurs in the blue part of the spectrum where DD has significantly lower Rrs(λ) variability than 3C in clearer sky conditions. We also consider Rrs(λ) processing from a hypothetical two-sensor configuration (using only the Lt(λ) spectroradiometer and the HSP and referred to as DD2) as a potential lower-cost measurement solution, which is shown to have comparable Rrs(λ) and Rrs(λ) variability to DD in clearer sky conditions. Our results support that the HSP sensor can fulfil a dual role in aquatic ecosystem monitoring by improving precision in Rrs(λ) alongside its primary function to characterize aerosols

    An Improved Method of Photometric Mode Identification: Applications to Slowly Pulsating B, beta Cephei, delta Scuti and gamma Doradus Stars

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    peer reviewedWe present an improved version of the method of photometric mode identification based upon the inclusion of non-adiabatic eigenfunctions determined in the stellar atmosphere, according to the formalism recently proposed by Dupret et al. (2002). We apply our method to beta Cephei, Slowly Pulsating B, delta Scuti and gamma Doradus stars. Besides identifying the degree l of the pulsating stars, our method is also a tool for improving the knowledge of stellar interiors and atmospheres, by imposing constraints on the metallicity for beta Cephei and SPBs, the characteristics of the superficial convection zone for delta Scuti and gamma Doradus stars and the limb-darkening law

    AIMS - A new tool for stellar parameter determinations using asteroseismic constraints

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    A key aspect in the determination of stellar properties is the comparison of observational constraints with predictions from stellar models. Asteroseismic Inference on a Massive Scale (AIMS) is an open source code that uses Bayesian statistics and a Markov Chain Monte Carlo approach to find a representative set of models that reproduce a given set of classical and asteroseismic constraints. These models are obtained by interpolation on a pre-calculated grid, thereby increasing computational efficiency. We test the accuracy of the different operational modes within AIMS for grids of stellar models computed with the Li\`ege stellar evolution code (main sequence and red giants) and compare the results to those from another asteroseismic analysis pipeline, PARAM. Moreover, using artificial inputs generated from models within the grid (assuming the models to be correct), we focus on the impact on the precision of the code when considering different combinations of observational constraints (individual mode frequencies, period spacings, parallaxes, photospheric constraints,...). Our tests show the absolute limitations of precision on parameter inferences using synthetic data with AIMS, and the consistency of the code with expected parameter uncertainty distributions. Interpolation testing highlights the significance of the underlying physics to the analysis performance of AIMS and provides caution as to the upper limits in parameter step size. All tests demonstrate the flexibility and capability of AIMS as an analysis tool and its potential to perform accurate ensemble analysis with current and future asteroseismic data yields.Comment: Accepted for publication in MNRAS. 17 pages, 17 figure

    A Modified Progressive Supranuclear Palsy Rating Scale

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    Background: The Progressive Supranuclear Palsy Rating Scale is a prospectively validated physician-rated measure of disease severity for progressive supranuclear palsy. We hypothesized that, according to experts' opinion, individual scores of items would differ in relevance for patients' quality of life, functionality in daily living, and mortality. Thus, changes in the score may not equate to clinically meaningful changes in the patient's status. Objective: The aim of this work was to establish a condensed modified version of the scale focusing on meaningful disease milestones. Methods: Sixteen movement disorders experts evaluated each scale item for its capacity to capture disease milestones (0 = no, 1 = moderate, 2 = severe milestone). Items not capturing severe milestones were eliminated. Remaining items were recalibrated in proportion to milestone severity by collapsing across response categories that yielded identical milestone severity grades. Items with low sensitivity to change were eliminated, based on power calculations using longitudinal 12-month follow-up data from 86 patients with possible or probable progressive supranuclear palsy. Results: The modified scale retained 14 items (yielding 0–2 points each). The items were rated as functionally relevant to disease milestones with comparable severity. The modified scale was sensitive to change over 6 and 12 months and of similar power for clinical trials of disease-modifying therapy as the original scale (achieving 80% power for two-sample t test to detect a 50% slowing with n = 41 and 25% slowing with n = 159 at 12 months). Conclusions: The modified Progressive Supranuclear Palsy Rating Scale may serve as a clinimetrically sound scale to monitor disease progression in clinical trials and routine

    Upstream Supply Chain Visibility and Complexity Effect on Focal Company’s Sustainable Performance: Indian Manufacturers’ Perspective

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    Understanding supply chain sustainability performance is increasingly important for supply chain researchers and managers. Literature has considered supply chain sustainability and the antecedents of performance from a triple bottom line (economic, social, and environmental) perspective. However, the role of supply chain visibility and product complexity contingency in achieving sustainable supply chain performance has not been explored in depth. To address this gap, this study utilizes a contingent resource-based view theory perspective to understand the role of product complexity in shaping the relationship between upstream supply chain visibility (resources and capabilities) and the social, environmental, and economic performance dimensions. We develop and test a theoretical model using survey data gathered from 312 Indian manufacturing organizations. Our findings indicate that supply chain visibility (SCV) has significant influence on social and environmental performance under the moderation effect of product complexity. Hence, the study makes significant contribution to the extant literature by examining the impact of SCV under moderating effect of product complexity on social performance and environmental performance

    Dausenau bei Bad Ems : Ortsbeschreibung, Sage u. Geschichte, Sehenswürdigkeiten

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    bearb. und zsgest. von J. C. Grötsc

    What can we learn from asteroseismology of β Cephei stars through forward approach modelling?

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    The beta Cephei pulsating stars present a unique opportunity to test and probe our knowledge on the interior of massive stars. The information we can obtain depends on the quality and number of observational constraints, both seismic and classical ones. The asteroseismology of beta Cephei stars proceeds by a forward approach, which often result in multiple solutions, without clear indication on the level of confidence. We seek a method to derive confidence intervals on stellar parameters obtained by forward approach and investigate how these latter behave depending the seismic data accessible to the observer. We realise forward modelling with help of a grid of pre-computed models and use Monte-Carlo simulations to build confidence intervals on the inferred stellar parameters. We apply and test this method in a series of hare and hound exercises on a subset of theoretical models simulating observed stars. Results show that a set of 5 frequencies (with knowledge of their associated angular degree) yields good seismic constraints. In particular, presence of mixed modes provides a strong diagnosis on the evolutionary state of the star. Significant errors on the determinination of the extent of the central mixed region appear when the theoretical models do not present the same chemical mixture as the observed star
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