91 research outputs found

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Inequalities in public water supply fluoridation in Brazil: An ecological study

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    Background. The literature is scarce on the social and geographic inequalities in the access to and implementation of the fluoridation of public water supplies. This study adds knowledge to the Brazilian experience of the chronic privation of water and wastewater policies, access to potable water and fluoridation in the country. Thus, the aim of this study was to verify possible inequalities in the population's access to fluoridated drinking water in 246 Brazilian municipalities. Methods. The information on the process of water fluoridation in the municipalities and in the macro region in which each municipality is located was obtained from the national epidemiological survey which was concluded in 2003. The data relating to the human development index at municipal level (HDI-M) and access to mains water came from the Brazilian Human Development Atlas, whilst the size of the population was obtained from a governmental source. The Fisher exact test (P < 0.05) was employed to identify significant associations between the explanatory variables and their ability to predict the principal outcomes of interest to this study, namely the presence or absence of the water fluoridation process in the municipalities as well as the length of time during which this measure has been implemented. Linear regression was used to observe the associations between the relevant variables in a multivariate environment. Results. The results clearly showed that there is a relationship between municipalities with larger populations, located in more socio-economically advantaged regions and with better HDI-M, and where fluoridation is both present and has been implemented for a longer period of time (started before 1990). Conclusion. 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(2006) Sozial und Präventiv Medizin, 51 (5), pp. 1-9Peres, K.G., Bastos, J.R., Mrdo, L., Relationship between severity of dental caries and social and behavioral factors in children (2000) Rev Saude Publica, 34 (4), pp. 402-8. , 10973161Maltz, M., Barbachan Silva, E.B., Relationship between caries, gingivitis and fluorosis and the socioeconomic status among school children (2001) Rev Saude Publica, 35 (2), pp. 170-6. , 11359204Moysés, S.J., Desigualdades em Sade Bucal e Desenvolvimento Humano: Um ensaio em preto, branco e alguns tons de cinza (2001) Rev Bras Odontol Sade Coletiva, 1 (1), pp. 7-17Patussi, M.P., Marcenes, W., Croucher, R., Sheiham, A., Social deprivation, income inequality, social cohesion and dental caries in Brazilian school children (2001) Soc Sci Med, 53 (7), pp. 915-25. , 10.1016/S0277-9536(00)00391-9 11522137Antunes, J.L.F., Frazão, P., Narvai, P.C., Bispo, C.M., Pegoretti, T., Spatial analysis to identify differentials in dental needs by area-based measures (2002) Community Dent Oral Epidemiol, 30 (2), pp. 133-42. , 10.1034/j.1600-0528.2002.300207.x 12000354Peres, M.A., Peres, K.G., Antunes, J.L.F., Junqueira, S.R., Frazão, P., Narvai, P.C., The association between socioeconomic development at the town level and the distribution of dental caries in Brazilian children (2003) Rev Panam Salud Publica, 14 (3), pp. 149-57. , 10.1590/S1020-49892003000800001 14653902Antunes, J.L.F., Narvai, P.C., Nugent, Z.J., Measuring inequalities in the distribution of dental caries (2004) Community Dent Oral Epidemiol, 32 (1), pp. 41-8. , 10.1111/j.1600-0528.2004.00125.x 14961839Antunes, J.L.F., Peres, M.A., De Campos Mello, T.R., Waldman, E.A., Multilevel assessment of determinants of dental caries experience in Brazil (2006) Community Dent Oral Epidemiol, 34 (2), pp. 146-152. , 10.1111/j.1600-0528.2006.00274.x 16515679Narvai, P.C., Frazão, P., Roncalli, A.G., Antunes, J.L.F., Dental caries in Brazil: Decline, polarization, inequality and social exclusion (2006) Rev Panam Salud Publica, 19 (6), pp. 385-93. , 10.1590/S1020-49892006000600004 16968593Projeto, S.B., Brasil, Condiçes de sade bucal da população brasileira 2002-2003. 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    TRY plant trait database - enhanced coverage and open access

    Get PDF
    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Dijet Resonance Search with Weak Supervision Using root S=13 TeV pp Collisions in the ATLAS Detector

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    This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A → BC, for mA ∼ OðTeVÞ, mB; mC ∼ Oð100 GeVÞ and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 ffiffi s p ¼ 13 TeV pp collision dataset of 139 fb−1 recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width A, B, and C particles vary with mA, mB, and mC. For example, when mA ¼ 3 TeV and mB ≳ 200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on mC. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model boson
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