Desafios e impacto da educação em saúde associada a cinesioterapia laboral para a promoção da saúde em servidores do estado do Paraná

Introdução: A Fisioterapia atua na saúde do trabalhador pela promoção e prevenção a saúde. Diversos recursos podem ser utilizados para tal finalidade, como a educação em saúde e a cinesioterapia laboral. Objetivo: Verificar os desafios e os efeitos da educação em saúde associada a cinesioterapia laboral sobre a qualidade de vida, percepção da saúde e dor musculoesquelética em servidores públicos do Estado do Paraná. Metodologia: Trata-se de um estudo experimental desenvolvido por meio da disciplina de Habilidades Fisioterapêuticas. Foram aplicados questionários para avaliação da qualidade de vida (SF-36), percepção da saúde e dor musculoesquelética (Nórdico). A prática de educação em saúde foi realizada por meio de cartilhas informativas e foi associada a cinesioterapia laboral. As atividades foram realizadas na Procuradoria Geral do Estado do Paraná uma vez por semana, totalizando 12 encontros. A comparação dos momentos pré e pós intervenção foi realizada pelos testes de Wilcoxon e Qui-Quadrado. Resultados: A análise dos dados evidenciou que grande parte dos servidores melhorou os domínios de capacidade funcional e dor da qualidade de vida e a percepção da saúde. A maior queixa de dor lombar e apresentou redução de sua prevalência após o experimento. Conclusão: O grande desafio da atividade proposta foi a aderência e participação dos servidores. Apesar disso, os servidores que participaram ativamente do programa de educação em saúde com a cinesioterapia laboral evidenciaram efeitos positivos sobre a qualidade de vida, percepção da saúde e dores musculoesqueléticas, sendo estas sugeridas como uma ferramenta importante para a promoção da saúde de servidores

TRY plant trait database – enhanced coverage and open access

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

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

Probing effective field theory operators in the associated production of top quarks with a Z boson in multilepton final states at root s=13 TeV

Peer reviewe

The global spectrum of plant form and function: enhanced species-level trait dataset.

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date