Choice and control in a museal environment: a study with science teachers

This study aims to understand teachers’ strategies of planning students’ visits to science museums and how they intend to relate this visit to formal science teaching. The study was conducted with 21 teachers of Science, Physics, Chemistry and Biology, randomly identified among visitors to a science museum, who were accompanying their students. Interviews and written records of teachers about teachers strategies were analyzed using the textual discursive analysis revealed five levels of control (or choice) adopted by teachers for planning and tracking of students' visits to the museum. The results showed that most teachers surveyed use control elements, requesting notes for reports to be retrieved in school. The evaluation mechanisms planned by teachers after the visit showed an intention for preserving and contextualization of the museum experience in other contexts, like in school

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Catálogo Taxonômico da Fauna do Brasil: setting the baseline knowledge on the animal diversity in Brazil

The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

O processo de significa??o da experi?ncia museal : um estudo sobre o contexto pessoal de professores de ci?ncias

Made available in DSpace on 2015-04-14T14:12:44Z (GMT). No. of bitstreams: 1 428083.pdf: 1140524 bytes, checksum: c54d4f64571ee88f70bcc304451fd467 (MD5) Previous issue date: 2010-03-31Diversos pesquisadores v?m estudando os resultados cognitivos e afetivos das experi?ncias de visitas de grupos escolares aos museus de ci?ncias, assim como os fatores que ampliam a experi?ncia de aprendizagem nestes espa?os de educa??o n?o-formal. No entanto, poucas investiga??es t?m analisado o papel do professor na iniciativa de realiza??o de uma visita ao museu com seu grupo de alunos. Este trabalho se prop?e a investigar as percep??es dos professores que visitam o MCT-PUCRS com seus alunos, sob a ?tica do processo de constru??o de significados da experi?ncia museal, dentro do contexto pessoal do professor, analisando suas expectativas, motiva??es, estrat?gias e conex?es pretendidas entre a visita ao museu e o ensino de ci?ncias na escola. A pesquisa foi orientada por uma abordagem quantitativa e qualitativa, com entrevistas feitas com os professores visitantes. Os discursos foram analisados utilizando a an?lise discursiva textual. Os resultados mostram que os professores, em sua maioria, freq?entam o museu anualmente e suas primeiras experi?ncias de visita remetem a mem?rias de sua adolesc?ncia, como alunos da educa??o b?sica ou superior, sempre marcadas por emo??es positivas e pelo encantamento. Os professores revelam motiva??es intr?nsecas para a visita, como a amplia??o de conhecimentos e uma forma??o continuada, assim como justificativas ligadas ao crescimento e aprendizagem dos alunos. Motiva??es extr?nsecas, como atividades planejadas pela escola s?o utilizadas por uma minoria. As expectativas dos professores est?o diretamente relacionadas ?s suas motiva??es, incluindo modifica??es em sua pr?tica docente. O prazer e divers?o esperados na visita n?o est?o desvinculados da aprendizagem, assim como a amplia??o do interesse e a curiosidade dos alunos em ci?ncias e a complementa??o de conte?dos. Sobre as pr?ticas de visitas dos professores e suas perspectivas de rela??o com o ensino formal, encontra-se uma grande diversidade de op??es de escolha e controle das atividades dos alunos, que revelam diferentes concep??es de aprendizagem. As atividades planejadas no retorno ?s escolas, relacionadas ? visita??o, incluem relatos orais e escritos e organiza??o de mostras ou feiras de ci?ncias. Todos esses mecanismos de avalia??o p?s-visita mostram uma preocupa??o com a preserva??o e contextualiza??o da experi?ncia museal em outros contextos, como na escola. Os resultados da pesquisa mostram que o Modelo Contextual de Aprendizagem, de Falk e Dierking (2000), apresenta-se como uma base te?rica ?til na organiza??o e an?lise das investiga??es sobre a aprendizagem em espa?os de educa??o n?o formal

Search for narrow resonances using the dijet mass spectrum in pp collisions at s√=8 TeV

Results are presented of a search for the production of new particles decaying to pairs of partons (quarks, antiquarks, or gluons), in the dijet mass spectrum in proton-proton collisions at s√=8  TeV. The data sample corresponds to an integrated luminosity of 4.0  fb−1, collected with the CMS detector at the LHC in 2012. No significant evidence for narrow resonance production is observed. Upper limits are set at the 95% confidence level on the production cross section of hypothetical new particles decaying to quark-quark, quark-gluon, or gluon-gluon final states. These limits are then translated into lower limits on the masses of new resonances in specific scenarios of physics beyond the standard model. The limits reach up to 4.8 TeV, depending on the model, and extend previous exclusions from similar searches performed at lower collision energies. For the first time mass limits are set for the Randall–Sundrum graviton model in the dijet channel