10,326 research outputs found

    The Core, Periphery, and Beyond: Stock Market Comovements among EU and Non-EU Countries

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    We thank conference participants at the 2016 Financial Management Association and our discussant Fernando Moreira, and two anonymous referees for immensely helpful comments. We also thank Andrew Patton and James P. LeSage for sharing their MATLAB codes for computing quantile dependence. The authors of this paper are responsible for any errors or omissions. The Securities and Exchange Commission, as a matter of policy, disclaims responsibility for any private publication or statement by any of its employees. The views expressed herein are those of the authors and do not necessarily reflect the views of the Commission or the authors\u27 colleagues on the staff of the Commission

    Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology

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    The green area displayed by a crop is a good indicator of its photosynthetic capacity, while chlorophyll retention or ‘stay-green’ is regarded as a key indicator of stress adaptation. Remote-sensing methods were tested to estimate these parameters in diverse wheat genotypes under different growing conditions. Two wheat populations (a diverse set of 294 advanced lines and a recombinant inbred line population of 169 sister lines derived from the cross between Seri and Babax) were grown in Mexico under three environments: drought, heat, and heat combined with drought. In the two populations studied here, a moderate heritable expression of stay-green was found–when the normalized difference vegetation index (NDVI) at physiological maturity was estimated using the regression of NDVI over time from the mid-stages of grain-filling to physiological maturity–and for the rate of senescence during the same period. Under heat and heat combined with drought environments, stay-green calculated as NDVI at physiological maturity and the rate of senescence, showed positive and negative correlations with yield, respectively. Moreover, stay-green calculated as an estimation of NDVI at physiological maturity and the rate of senescence regressed on degree days give an independent measurement of stay-green without the confounding effect of phenology. On average, in both populations under heat and heat combined with drought environments CTgf and stay-green variables accounted for around 30% of yield variability in multiple regression analysis. It is concluded that stay-green traits may provide cumulative effects, together with other traits, to improve adaptation under stress further

    Seriation and Multidimensional Scaling: A Data Analysis Approach to Scaling Asymmetric Proximity Matrices

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    A number of model-based scaling methods have been developed that apply to asymmetric proximity matrices. A flexible data analysis approach is pro posed that combines two psychometric procedures— seriation and multidimensional scaling (MDS). The method uses seriation to define an empirical order ing of the stimuli, and then uses MDS to scale the two separate triangles of the proximity matrix defined by this ordering. The MDS solution con tains directed distances, which define an "extra" dimension that would not otherwise be portrayed, because the dimension comes from relations between the two triangles rather than within triangles. The method is particularly appropriate for the analysis of proximities containing temporal information. A major difficulty is the computa tional intensity of existing seriation algorithms, which is handled by defining a nonmetric seriation algorithm that requires only one complete itera tion. The procedure is illustrated using a matrix of co-citations between recent presidents of the Psychometric Society.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

    The analysis of very small samples of repeated measurements II: a modified box correction

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    There is a need for appropriate methods for the analysis of very small samples of continuous repeated measurements. A key feature of such analyses is the role played by the covariance matrix of the repeated observations. When subjects are few it can be difficult to assess the fit of parsimonious structures for this matrix, while the use of an unstructured form may lead to a serious lack of power. The Kenward-Roger adjustment is now widely adopted as a means of providing an appropriate inferences in small samples, but does not perform adequately in very small samples. Adjusted tests based on the empirical sandwich estimator can be constructed that have good nominal properties, but are seriously underpowered. Further, when such data are incomplete, or unbalanced, or non-saturated mean models are used, exact distributional results do not exist that justify analyses with any sample size. In this paper, a modification of Box's correction applied to a linear model based FF-statistic is developed for such small sample settings and is shown to have both the required nominal properties and acceptable power across a range of settings for repeated measurements

    Matrix and Stimulus Sample Sizes in the Weighted MDS Model: Empirical Metric Recovery Functions

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    The only guidelines for sample size that exist in the multidimensional scaling (MDS) literature are a set of heuristic "rules-of-thumb" that have failed to live up to Young's (1970) goal of finding func tional relationships between sample size and metric recovery. This paper develops answers to two im portant sample-size questions in nonmetric weight ed MDS settings, both of which are extensions of work reported in MacCallum and Cornelius (1977): (1) are the sample size requirements for number of stimuli and number of matrices compensatory? and (2) what type of functional relationships exist between the number of matrices and metric recov ery ? The graphs developed to answer the second question illustrate how such functional relation ships can be defined empirically in a wide range of MDS and other complicated nonlinear models.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

    Association between Work-Related Hyperthermia Emergency Department Visits and Ambient Heat in Five Southeastern States, 2010-2012--A Case-Crossover Study

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    The objective of this study is to assess ambient temperatures\u27 and extreme heat events\u27 contribution to work-related emergency department (ED) visits for hyperthermia in the southeastern United States to inform prevention. Through a collaborative network and established data framework, work-related ED hyperthermia visits in five participating southeastern U.S. states were analyzed using a time stratified case-crossover design. For exposure metrics, day- and location-specific measures of ambient temperatures and county-specific identification of extreme heat events were used. From 2010 to 2012, 5,017 work-related hyperthermia ED visits were seen; 2,298 (~46%) of these visits occurred on days when the daily maximum heat index was at temperatures the Occupational Safety and Health Administration designates as having lower or moderate heat risk. A 14% increase in risk of ED visit was seen for a 1°F increase in average daily mean temperature, modeled as linear predictor across all temperatures. A 54% increase in risk was seen for work-related hyperthermia ED visits during extreme heat events (two or more consecutive days of unusually high temperatures) when controlling for average daily mean temperature. Despite ambient heat being a well-known risk to workers\u27 health, this study\u27s findings indicate ambient heat contributed to work-related ED hyperthermia visits in these five states. Used alone, existing OSHA heat-risk levels for ambient temperatures did not appear to successfully communicate workers\u27 risk for hyperthermia in this study. Findings should inform future heat-alert communications and policies, heat prevention efforts, and heat-illness prevention research for workers in the southeastern United States

    Open access increases citations of papers in ecology

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    Open access (OA) can effectively increase the accessibility and visibility of scientific articles and thus potentially confer them with citation advantages. Such an impact may be more pronounced in developing countries where the cost for journal subscription is comparably expensive and usually unaffordable. By comparing one OA article with one non‐OA article published in the same issue, we tested the impact of OA on citation advantages of articles published in 46 ecology journals indexed in the Journal Citation Reports (JCR). We compared OA to non‐OA articles published in the same issue of these journals, thereby controlling for potentially confounding effects of publication requirement and period. OA articles received significantly more citations than non‐OA articles, and this citation advantage of approximately one citation per year was sustained across publication years from 2009 to 2013. The OA citation advantage did not depend upon income of the country of origin of the citing scientists, and the OA citation advantage was found for citing scientists from North America, Europe, Asia, Africa, and Oceania, but not for Latin America. A total of 10 countries contributed more than 1000 citations each, and the OA citation advantage was found in all the 10 countries except Canada. Therefore, in ecology journals OA confers articles with citation advantages and such an impact accumulates with years and independent of the economic status of the countries. This information may guide decisions of scientific societies, journals, and individual authors as they weigh the relative costs and benefits of open electronic accessibility of scientific research
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