Turbulence Hierarchy in a Random Fibre Laser

Turbulence is a challenging feature common to a wide range of complex phenomena. Random fibre lasers are a special class of lasers in which the feedback arises from multiple scattering in a one-dimensional disordered cavity-less medium. Here, we report on statistical signatures of turbulence in the distribution of intensity fluctuations in a continuous-wave-pumped erbium-based random fibre laser, with random Bragg grating scatterers. The distribution of intensity fluctuations in an extensive data set exhibits three qualitatively distinct behaviours: a Gaussian regime below threshold, a mixture of two distributions with exponentially decaying tails near the threshold, and a mixture of distributions with stretched-exponential tails above threshold. All distributions are well described by a hierarchical stochastic model that incorporates Kolmogorov's theory of turbulence, which includes energy cascade and the intermittence phenomenon. Our findings have implications for explaining the remarkably challenging turbulent behaviour in photonics, using a random fibre laser as the experimental platform.Comment: 9 pages, 5 figure

Humor para aprender Matemática: Tarefas matemáticas para rir e aprender

A boa disposição e o bem-estar facilitam o trabalho e a aprendizagem. O humor tem essa particularidade, de bem-dispor e fazer rir as pessoas, aliviando situações de stress e facilitando a comunicação. De entre as diversas formas de humor, o humor gráfico, baseado em tiras e cartoons, tem larga difusão em revistas, nos jornais e na internet. No projeto HUMAT: Humor no ensino da Matemática criámos um conjunto de tarefas matemáticas baseadas em diversas situações de humor gráfico que estão disponíveis na internet e em revistas, de diversos autores, e que incidem sobre vários conteúdos matemáticos, que são trabalhados em diversos anos de escolaridade. Este é, portanto, um livro destinado a alunos, tendo como objetivo apoiar a aprendizagem da Matemática, tanto em contextos de sala de aula como extra sala de aula, de uma forma bem-disposta. Em todas as tarefas deste livro, apresentamos uma tira ou um cartoon e colocamos, a propósito dela, um conjunto de questões que estimulam o pensamento matemático dos alunos, ao mesmo tempo que, esperamos, despertem momentos de boa disposição. Em todas as tarefas, a questão inicial procura levar os alunos a descrever a situação e a apreciar o humor nela presente. Para apoiar a resposta a esta questão, propomos o seguinte roteiro, focado em quatro pontos: Ambiente (em que contexto/cenário ocorrem os eventos? quais são os elementos do desenho que nos fazem identificar esse cenário?); Sujeitos (quem são os personagens? o que se sabe sobre eles? o que representam?); Ação (o que acontece?); Choque de expectativas/final inesperado (o que causa humor? qual é a circunstância que torna a situação engraçada?). Para além das tarefas se dirigirem a diferentes anos de escolaridade e de versarem conteúdos matemáticos diversos, têm também uma duração estimada diferenciada. Algumas são curtas, outras são mais longas. Em todos os casos, esperamos que delas resulte um texto escrito. Podendo ser realizadas individualmente ou em grupo, podem depois ser partilhadas e discutidas as suas resoluções. O projeto HUMAT tem um site onde se podem partilhar as resoluções produzidas em sala de aula ou fora dela.FCT / IP Viseuinfo:eu-repo/semantics/publishedVersio

Humor para aprender Matemática - Tareas matemáticas para reír y aprender

Una buena disposición y bienestar facilitan el trabajo y el aprendizaje. El humor tiene esa particularidad, la de bien disponer y hacer reir a las personas, aliviando situaciones de estres y facilitando la comunicación. De entre las diversas formas de humor, el humor gráfico, basado en tiras y cartoons, tiene amplia difusión en revistas, en diarios y en internet. En el proyecto HUMAT: Humor en la enseñanza de la Matemática elaboramos um conjunto de tareas matemáticas basadas en diversas situaciones de humor gráfico que están disponibles en internet y en revistas, de diversos autores y que inciden sobre varios contenidos matemáticos, que se trabajan en diversos cursos escolares. Este es, por tanto, un libro destinado a los alumnos, teniendo como objetivo apoyar el aprendizaje de la Matemática, tanto en el aula escolar como en casa, de una forma bien dispuesta. En todas las tareas de este libro, presentamos una historieta o un cartoon y planeamos, a propósito de ella, un conjunto de cuestiones que estimulam el pensamento matemático de los alumnos, al mismo tiempo que, esperamos, despierten momentos de buena disposición. En todas las tareas, la primera cuestión pretende llevar a los alumnos a describir la situación y a apreciar el humor en la misma. Para facilitar la respuesta a esta cuestión, proponemos el siguiente guión, basado en cuatro puntos: - Ambiente (¿en qué contexto/escenario ocurren los acontecimientos? ¿Cuáles son los elementos del dibujo que nos hacen identificar este escenario?); - Sujetos (¿quién son los personages? ¿qué sabes sobre ellos? ¿qué características tienen?); - Acción (¿qué sucede?); - Choque de expectativas/final inesperado (¿qué es lo que causa humor? ¿cuál es la circunstancia que hace que la situación sea graciosa?). Estas tareas se dirigiren a diferentes edades y cursos escolares y tratan diversos contenidos matemáticos, tienen también distinto tiempo estimado de resolución. Algunas son cortas y otras más largas. En todos los casos, esperamos que de ellas se realice un texto escrito. Se pueden realizar individualmente o en grupo, después pueden ser compartidas y discutidas las resoluciones aportadas. El proyecto HUMAT tiene un dominio al que se pueden enviar las resoluciones, tanto las realizadas en clases escolares como las que se hagan fuera de ellas.info:eu-repo/semantics/publishedVersio

Humor no ensino da Matemática: tarefas para a sala de aula

Este livro, Humor no Ensino da Matemática: Tarefas para a sala de aula, surge no âmbito do projeto de investigação HUMAT (Humor in Mathematics Teaching), desenvolvido pela Escola Superior de Educação de Viseu (Portugal), em parceria com a Universidade do Minho (Portugal), a Universidade de Granada (Espanha) e a Universidade de Mendoza (Argentina), com o apoio do Instituto Politécnico de Viseu (Portugal) e CI&DETS. O projeto assume duas ideias fundamentais. Por um lado, assume a importância que o humor tem na criação de um ambiente de aprendizagem que pode impulsionar a motivação para aprender Matemática. Por outro lado, assume que a compreensão do humor e a aprendizagem da Matemática são duas atividades que exigem boa capacidade de raciocínio. Admite ainda que o ensino exploratório da Matemática, baseado no trabalho dos alunos com tarefas matemáticas desafiantes, tem um elevado potencial para a aprendizagem. Nesta medida, surge este livro de tarefas matemáticas de cunho humorístico, que procuram cumprir estas duas funções, ou seja, predispor os alunos para aprender e levá-los a raciocinar sobre situações humorísticas que envolvem conceitos matemáticos.CI&DETS e Instituto Politécnico de Viseuinfo: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 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

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

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