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

Design interativo de agentes inteligentes de interface para software educativo de matemática

A quantidade de programas educacionais e as diferentes modalidades do uso do computador demonstram sua utilidade no processo de ensino e aprendizagem (Valente 1993). Embora seja notório que máquinas como o computador representam avanço tecnológico e que existe, nele, um grande potencial como máquina de ensinar. Isso não determina que o seu uso ofereça garantias de desenvolvimento e aprendizagem de conceitos. É necessário, portanto, planejar sua inserção nas práticas escolares e fazer uma avaliação criteriosa dos softwares que serão utilizados. Dessa forma, avaliar um software educativo significa estimar o seu potencial enquanto ferramenta para aprendizagem de conceitos e, sendo assim, se faz necessário a utilização de técnicas e referenciais teóricos que possibilitem a verificação da aprendizagem ainda durante o seu desenvolvimento. Esta dissertação tem como objetivo o design de agentes de interface para uma aplicação educativa que visa ao ensino de estruturas aditivas; para tanto a interface educativa que ora propomos foi desenvolvida sob a perspectiva construtivista de aprendizagem, adotada através do uso de um estilo de interação utilizado para criar situações capazes de promover a reflexão e conduzir o usuário à revisão dos seus planos iniciais. Esta interface foi concebida através de uma metodologia que contemplou a identificação do contexto de uso; a análise de competidores; prototipagem rápida; e análise qualitativa da usabilidade, comunicabilidade e aprendizagem através da observação dos critérios construtivistas de aprendizagem. Durante o seu desenvolvimento, considerou-se constantemente a perspectiva dos usuários representativos em todo o ciclo de desenvolvimento, através de uma metodologia realizada em interação com o usuário e que utiliza os feedbacks do mesmo para melhorar aspectos relativos à usabilidade e a aprendizagem. A proposta pedagógica adotada nesta interface foi o reforço instrucional, que é fornecido durante a resolução de problemas. A tal reforço, a literatura sobre educação chama de Scaffolding. Por meio da metodologia, foi possível conceber formas de reforço condizentes tanto com o usuário, quanto com a tarefa em execução. Além das formas de reforço, apresentamos uma metodologia capaz de estimar o potencial de uma interface educativa, ainda em seu processo de design e, dessa forma, alinhar as ações e percepções do usuário acerca da interface às suas necessidades, as quais serão avaliadas em um contexto de uso rea

ESTUDIO DE LA PREVALENCIA DE MORDIDA CRUZADA EN LOS PACIENTES PREORTODÓNCICOS EN SÃO LUÍS - MA.

El objetivo de esta investigación fue describir la mordida cruzada analizando su prevalencia y aspectosrelativos a sus modalidades, el genero, la edad, el factor etiológico, la raza y la clasificación de Angle. Lamuestra fue constituida de 623 pacientes pre - ortodóncicos de consultorios odontológicos e institucionesde enseñanza de odontología de São Luís, estado de Maranhão - Brasil, en el grupo etario de 8 a 15años. Fue realizado un análisis descriptivo de los datos los cuales fueron sometidos a la prueba del Chicuadrado.Los resultados encontrados mostraron que: a) la prevalencia de mordida cruzada fue de29,05%, la mordida cruzada anterior la más frecuente, con 12,05%; b) no hubo asociación significativade la mordida cruzada con el raza, género, edad y local de tratamiento; c) portadores de maloclusiónclase III fueron los más afectados observándose asociación significativa de la mordida cruzada con esavariable; d) el apiñamiento fue el factor etiológico más registrado. Se concluyó que la prevalencia demordida cruzada fue elevada y la procura de tratamiento parece estar más relacionada con la cuestiónestética.ABSTRACT The purpose of this research is to study crossbites, analyzing their prevalence and aspects relative tomodality, gender, age, etiologic factor, race, and Angle Classification. The sample consisted of 623preorthodontic patients from private dental offices and dental educational institutions of São Luís, thestate of Maranhão, Brazil, between the ages of 8- and 15- years-old. A descriptive analysis was carriedout and the data were submitted to the chi-square test. The results showed that: a) the prevalence ofcrossbite was 29.05%, being anterior crossbite the most frequent type, with 12.05%; b) there was no significant association of crosssbite with race, gender, age and place of treatment; c) Class IIImalocclusion patients were the most affected with crossbites, demonstrating association between thesevariables. It was concluded that the prevalence of crossbite was elevated and the demand seems to bemore related to esthetic concerns.&nbsp