Building the Brazilian Academic Genealogy Tree

Along the history, many researchers provided remarkable contributions to science, not only advancing knowledge but also in terms of mentoring new scientists. Currently, identifying and studying the formation of researchers over the years is a challenging task as current repositories of theses and dissertations are cataloged in a decentralized way through many local digital libraries. Following our previous work in which we created and analyzed a large collection of genealogy trees extracted from NDLTD, in this paper we focus our attention on building such trees for the Brazilian research community. For this, we use data from the Lattes Platform, an internationally renowned initiative from CNPq, the Brazilian National Council for Scientific and Technological Development, for managing information about individual researchers and research groups in Brazil

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis)

Living Shorelines Support Nearshore Benthic Communities in Upper and Lower Chesapeake Bay

Human population growth and sea-level rise are increasing the demand for protection of coastal property against shoreline erosion. Living shorelines are designed to provide shoreline protection and are constructed or reinforced using natural elements. While living shorelines are gaining popularity with homeowners, their ability to provide ecological services (e.g., habitat provision and trophic transfer) is not well understood, and information is needed to improve coastal and resource management decision-making. We examined benthic community responses to living shorelines in two case-study subestuaries of Chesapeake Bay using a before-after control-impact study design. At Windy Hill, a bulkhead was removed and replaced by three tombolos, sand fill, and native marsh vegetation. At Lynnhaven, 25 m of eroding marsh shoreline was stabilized with coir logs, sand fill, and native marsh vegetation. Communities of large (\u3e 3 mm) infauna adjacent to living shorelines at both locations tended to increase in biomass by the end of the study period. Community compositions changed significantly following living shoreline construction at Windy Hill, reflecting a trend toward higher density and biomass of large bivalves at living shorelines compared to pre-construction. Increasing trends in density and biomass of clams and simultaneously decreasing density and decreasing trends in biomass of polychaetes suggest a transition toward stable infaunal communities at living shorelines over time, though longer-term studies are warranted

A survey for low mass spectroscopic binary stars in the young clusters around sigma Orionis and lambda Orionis

We have obtained multi-epoch, high-resolution spectroscopy of 218 candidate low-mass stars and brown dwarfs in the young clusters around sigma Ori and lambda Ori. We find that 196 targets are cluster members based on their radial velocity, the equivalent width of their NaI 8200 lines and the spectral type from their TiO band strength. We have identified 11 new binary stars among the cluster members based on their variable radial velocity and an additional binary from the variation in its line width and shape. The sample covers the magnitude range Ic=14-18.9 (mass =~ 0.55-0.03 Msun), but all of the binary stars are brighter than Ic=16.6 (mass =~ 0.12Msun) and 10 are brighter than Ic=15.5 (mass =~ 0.23Msun). There is a significant lack of spectroscopic binaries in our sample at faint magnitudes even when we account for the decrease in sensitivity with increasing magnitude. We can reject the hypothesis that the fraction of spectroscopic binaries is a uniform function of Ic magnitude with more than 99% confidence. The spectroscopic binary fraction for stars more massive than about 0.1Msun (Ic < 16.9) is f_bright=0.095(+0.012)(-0.028). The 90% confidence upper limit to the spectroscopic binary fraction for very low mass (VLM) stars (mass < 0.1Msun) and brown dwarfs (BDs) is f_faint < 7.5%. The hypothesis that f_bright and f_faint are equal can be rejected with 90% confidence. We conclude that we have found strong evidence for a change in the fraction of spectroscopic binaries among young VLM stars and brown dwarfs when compared to more massive stars in the same star-forming region. This implies a difference in the total binary fraction between VLM stars and BDs compared to more massive stars or a difference in the distribution of semi-major axes, or both. (Abridged

The mapping class group and the Meyer function for plane curves

For each d>=2, the mapping class group for plane curves of degree d will be defined and it is proved that there exists uniquely the Meyer function on this group. In the case of d=4, using our Meyer function, we can define the local signature for 4-dimensional fiber spaces whose general fibers are non-hyperelliptic compact Riemann surfaces of genus 3. Some computations of our local signature will be given.Comment: 24 pages, typo adde

Local stressors mask the effects of warming in freshwater ecosystems

Climate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this knowledge gap by testing the ability of three contrasting null models to predict the joint impacts of warming and a range of other aquatic stressors using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were usually best explained by the effect of the stronger stressor alone (the dominance null model), especially if this stressor was a local disturbance associated with human land use. Prediction accuracy depended on stressor identity and how asymmetric stressors were in the magnitude of their effects. These findings suggest we can effectively predict the impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration, nutrients and contamination often override the biological consequences of higher temperatures in freshwater ecosystems

Clinical predictors of antipsychotic use in children and adolescents with autism spectrum disorders: a historical open cohort study using electronic health records.

JOURNAL ARTICLEThe final publication is available at Springer via http://dx.doi.org/ 10.1007/s00787-015-0780-7Children with autism spectrum disorders (ASD) are more likely to receive antipsychotics than any other psychopharmacological medication, yet the psychiatric disorders and symptoms associated with treatment are unclear. We aimed to determine the predictors of antipsychotic use in children with ASD receiving psychiatric care. The sample consisted of 3482 children aged 3-17 with an ICD-10 diagnosis of ASD referred to mental health services between 2008 and 2013. Antipsychotic use outcome, comorbid diagnoses, and other clinical covariates, including challenging behaviours were extracted from anonymised patient records. Of the 3482 children (79 % male) with ASD, 348 (10 %) received antipsychotic medication. The fully adjusted model indicated that comorbid diagnoses including hyperkinetic (OR 1.44, 95 %CI 1.01-2.06), psychotic (5.71, 3.3-10.6), depressive (2.36, 1.37-4.09), obsessive-compulsive (2.31, 1.16-4.61) and tic disorders (2.76, 1.09-6.95) were associated with antipsychotic use. In addition, clinician-rated levels of aggression, self-injurious behaviours, reduced adaptive function, and overall parental concern for their child's presenting symptoms were significant risk factors for later antipsychotic use. In ASD, a number of comorbid psychiatric disorders are independent predictors for antipsychotic treatment, even after adjustment for familial, socio-demographic and individual factors. As current trial evidence excludes children with comorbidity, more pragmatic randomised controlled trials with long-term drug monitoring are needed.NIHRBiomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and King’s College LondonGuy’s and St. Thomas’ CharityMaudsley CharityMR