MAPA CONCEITUAL POR MEIO DO BRAINSTORMING E CLUSTERING: EXPERIÊNCIA NA DISCIPLINA PRÁTICA DE ENSINO EM FÍSICA

We live in an increasingly dynamic world, so it is necessary to think and organize new teaching strategies, since one of the objectives of Basic Education is to prepare the student for citizenship. The discipline of Teaching Practice in Physics I has brought new approaches to the teaching-learning process that allow this reflection. Initially, students were asked to think about possible answers to the questions: What is the main objective of teaching Physics and Chemistry in Elementary School (9th grade)? And how to make this happen? Aiming to make the process more meaningful, groups were organized that used brainstorming and clustering to construct a conceptual map to answer guiding questions. The construction process started individually, and later each member presented a few words to the team so that they were grouped together. During these stages the discussions became intense, giving rise to the key concepts: human construction, daily life, desires, scientific knowledge, mobilization, Physics and Chemistry. In the end, the academics used CmapTools to construct the conceptual map and presented their conclusions. From this, it was possible to verify that there is not a single goal to be sought, nor a single way for it to be achieved, after all Education is a complex system.Vivemos em um mundo dinâmico, portanto é necessário que se pense e organize novas estratégias de ensino, pois um dos objetivos da Educação Básica é preparar o estudante para a cidadania. A disciplina Prática de Ensino em Física I trouxe abordagens sobre o processo de ensino-aprendizagem que possibilitam essa reflexão. Foi proposto aos estudantes que pensassem em possíveis respostas para as perguntas: Qual é o principal objetivo do ensino de Física e de Química no Ensino Fundamental? E como fazer para que este objetivo seja atingido? Visando tornar o processo mais significativo, foram organizadas equipes de estudantes que utilizaram o brainstorming e o clustering para a construção de um mapa conceitual para responder as questões. O processo de construção iniciou de modo individual, posteriormente, cada membro apresentou palavras, para que fossem agrupadas. Durante essas etapas as discussões se tornaram intensas, dando origem aos conceitos-chaves: construção humana, cotidiano, desejos, conhecimento cientifico, mobilização, Física e Química. Ao final, os acadêmicos utilizaram o CmapTools para construção do mapa conceitual e apresentaram suas conclusões. Foi possível constatar que não existe um único objetivo a se buscar, nem uma única forma para que ele seja alcançado, afinal a Educação é um sistema complexo

CONSTRUINDO A EQUAÇÃO DA CIRCUNFERÊNCIA E DA SUPERFÍCIE ESFÉRICA POR MEIO DO SOFTWARE GEOGEBRA 3D: UMA EXPERIÊNCIA COM ALUNOS DO ENSINO MÉDIO

Este artigo apresenta uma investigação realizada pelo primeiro autor, sob a orientação do segundo, tendo o software GeoGebra 3D como ferramenta para construir a equação reduzida da circunferência e da superfície esférica. Foi aplicada, em uma escola pública estadual, no município de Candelária/RS, com três alunos bolsistas de um projeto de pesquisa (Programa de Iniciação em Ciências, Matemática, Engenharias, Tecnologias Criativas e Letras-PICMEL), no segundo semestre de 2014. Teve por objetivo explorar a visualização, no processo de construção das equações da circunferência e da superfície esférica, utilizando uma tecnologia computacional. Conclui-se que o objetivo foi alcançado, pois os alunos conseguiram deduzir, tanto a equação da circunferência no plano, quanto a da superfície esférica no espaço, por meio de recursos visuais. Além disso, o uso doGeoGebra, com suas janelas de álgebra e de visualização, favoreceu a relação entre as duas formas de representação. Portanto, ele foi decisivo para a aprendizagem do conteúdo matemático envolvido

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

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good

An embedding technique to determine ττ backgrounds in proton-proton collision data

An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe