Determinação dos parâmetros de resistência, "Creep" e de Relaxação de Tensões de uma argila mole do Rio de Janeiro

Determining the geotechnical characteristics of a layer of soft clay. The influence of the organic matter on the consistency index is discussed. The compressibility of this clay is compared to that of other clays as these of the "Baixada Fluminense" and these of "Santos" and the effect of the preconsolidation pressure is analysed. The stress-strain curves of the triaxial tests are represented by the hyperbolic formula. The strength and stress-strain parametersare determined and compared with those of other clays. The results of triaxial tests performed on undisturbed and disturbed samples are discussed. The stress-strain-time relationships are studied using results of creep and stress-relaxation tests performed in undrained conditions. Finally conditions are drawn concerning the geotechnical parameters which would be of more interest for the design of a deep excavation in this clay.Determina as propriedades geotécnicas de uma camada de argila mole. Discute-se a influência da matéria orgânica nos Índices de Consistência. Compara-se a compressibilidade da argila em estudo com a de outros depósitos, tais como os da Baixada Fluminense e os de Santos e estuda-se o efeito da pressão de quase pré-adensamento. Utiliza-se a formulação hiperbólica para simular as curvas tensão-deformação de ensaios triaxiais. Os parâmetros de resistência, tensão-deformação são obtidos e comparados com os de outras argilas. Discute-se os resultados de ensaios triaxiais em amostras indeformadas e amolgadas. As relações tensão-deformação-tempo são estudadas a partir de resultados de ensaios de "Creep" e de Relaxação de Tensões, ambos sob condições não-drenadas. Finalmente apresentam-se conclusões relativas aos parâmetros geotécnicos mais representativos para uso em um projeto de engenharia envolvendo escavações profundas neste depósito

Programa de Educación Tutorial en salud bucal : la experiencia en atención primaria en el centro de salud de Itapoã-DF

Este artigo apresenta o relato de experiência do Programa de Educação Tutorial em Odontologia da Universidade de Brasília, durante o período de março a dezembro de 2010. O cenário de prática das atividades de campo é a Regional Administrativa do Itapoã, no Distrito Federal, e a atuação do grupo tutorial acontece junto às Equipes de Saúde da Família por meio de rotinas educativo-preventivas em saúde bucal durante as visitas domiciliares, atividades clínicas e desenvolvimento de pesquisas. Alunos e preceptores estão sendo capazes de reconhecer os determinantes sociais do processo saúdedoença, analisar os indicadores de saúde bucal da população, aprimorar práticas educativas utilizadas na Estratégia Saúde da Família e promover saúde no âmbito da comunidade. As principais dificuldades encontradas dizem respeito a limitação de espaço físico e de recursos capazes de atender a demanda do grupo tutorial e das famílias assistidas. Esta experiência tutorial junto à Estratégia Saúde da Família possibilita um aprendizado que vai muito mais além do que a tradição de ensino bio-tecnicista da odontologia, bem como permite aos discentes de odontologia da UnB ‘vivenciar uma experiência real’ e refletir sobre os conhecimentos teóricos obtidos nos ‘bancos da universidade’. _________________________________________________________________________________________________________________ ABSTRACTThis paper presents an experience report of the Tutorial Program in Dentistry from the University of Brasília, during the period from March to December, 2010. The scenario of practice is the Itapoã - an Administrative Area of the Distrito Federal - and the activities of the tutorial group take place in partnership with the Family Health Team through a preventive educational oral health routine during home visits, as well as clinical activities and development of research. Students and preceptors are being able to recognize the social determinants of the health-disease process, analyze oral health indicators of the population, improve educational practices and promote health within the community. The main barriers of the tutorial group are the lack of physical space and dental equipment capable of meeting the demand of the tutorial group and assisted families. This tutorial experience within the Family Health Strategy provides a learning experience that goes far beyond the tradition of teaching bio-technicalities of dentistry, as well as allows dental students real to live through a real field experience and reflect on the theoretical knowledge obtained from the ‘university seats’. _________________________________________________________________________________________________________________ RESUMENEste documento presenta el relato de la experiencia del Programa de Educación Tutorial en Odontología de la Universidad de Brasília, durante el período de Marzo a Diciembre de 2010. El escenário de práctica de las actividades de campo es el Sector Regional Administrativo de Itapoã, en el Distrito Federal, donde el trabajo del grupo tutorial acompaña el trabajo de los Equipos de Salud de la Família a través de la educación preventiva de rutina en la salud bucal de la población, mejorando las prácticas educativas utilizadas en la estrategia de salud familiar y promoviendo la salud en la comunidad. Las principales dificultades se refieren a la limitación del espacio físico y el equipo dental capaces de satisfacer la demanda del grupo tutorial y de las famílias atendidas. Esta actividad tutorial con la Estrategia de Salud de la Família ofrece una experiencia de aprendizaje que vá más allá de la tradición de la enseñanza de técnicas bio-odontológicas, así como permite a los estudiantes de odontología de la UnB “pasar una verdadera experiencia” y reflexionar sobre el conocimiento teórico obtenido en “los bancos de datos de la universidad”

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

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

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

Performance of a modular ton-scale pixel-readout liquid argon time projection chamber

International audienceThe Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements, and provide comparisons to detector simulations