Aplicação de redes neurais artificiais na cultura do mogno (Khaya spp. e Swietenia spp.)

Due to their high commercial value and acceptance in the international market, mahogany species have been exploited indiscriminately, even in protected areas, resulting in threat of extinction. Mahogany species are desirable both in terms of color and grain patterns and in their properties. physical and mechanical. Both species have similar characteristics and are considered resistant to the attack of fungi and termites. Mahogany (Khaya spp. and Swietenia spp.) Has great productive potential in Brazil, being a good alternative to the most expressive crops in the country, for example. Since they are noble woods, and like Mahogany, Artificial Neural Networks (RNAs) are also good alternatives to estimate different dendrometric variables in different cultures, and studies show that this technique has been producing excellent adjustments, especially when compared to regression models. Traditional Thus, this review aimed to provide information on the different applications of RNAs in mahogany crops in Brazil.Devido ao seu alto valor comercial e aceitação no mercado internacional, as espécies de mogno foram exploradas indiscriminadamente, mesmo em áreas protegidas, resultando em ameaça de extinção. As espécies de mogno são desejáveis ​​tanto em termos de cores e padrões de grãos quanto em suas propriedades físicas e mecânicas. Ambas as espécies têm características semelhantes e são consideradas resistentes ao ataque de fungos e cupins. A cultura do Mogno (Khaya spp. e Swietenia spp.) apresenta grande potencial produtivo no Brasil, sendo uma boa alternativa às culturas de maior expressão no país, por se tratar de madeiras nobres, e assim como o Mogno, as Redes Neurais Artificiais (RNAs) também são boas alternativas para estimar diferentes variáveis dendrométricas em diferentes culturas, e estudos comprovam que essa técnica vem produzindo ótimos ajustes, principalmente quando comparados aos modelos de regressão tradicionais. Sendo assim a presente revisão teve como objetivo trazer informações das diferentes aplicações das RNAs nas culturas do Mogno no Brasil

Extracorporeal Membrane Oxygenation and Lung Transplantation: Initial Experience at a Single Brazilian Center

OBJECTIVE: To report initial experience from the use of extracorporeal membrane oxygenation (ECMO) in patients who received lung transplantation. METHODS: Retrospective study of a single tertiary center in the Brazilian state of Sa˜o Paulo, a national reference in lung transplantation, based on the prospective collection of data from electronic medical records. The period analyzed extended from January 2009 (beginning of the program) until December 2018. RESULTS: A total of 75 lung transplants were performed, with ECMO used in 8 (10.7%) cases. Of the patients, 4 (50%) were female. The mean age was 46.4±14.3 years. The causes of the end-stage lung disease that led to transplantation were pulmonary arterial hypertension in 3 (37.5%) patients, bronchiectasis in 2 (25%) patients, pulmonary fibrosis in 2 (25%) patients, and pulmonary emphysema in 1 (12.5%) patient. In our series, 7 (87.5%) cases were sequential bilateral transplantations. Prioritization was necessary in 4 (50%) patients, and in 1 patient, ECMO was used as a bridge to transplantation. The ECMO route was central in 4 (50%), peripheral venovenous in 2 (25%) and peripheral venoarterial in 2 (25%) patients. The mean length of the intensive care unit (ICU) stay was 14±7.5 days and of the hospital stay was 34.1±34.2 days. The mean ECMO duration was 9.3±6.6 days with a 50% decannulation rate. Three patients were discharged (37.5%). CONCLUSION: Lung transplantation requires complex treatment, and ECMO has allowed extending the indications for transplantation and provided adjuvant support in the clinical management of these patients

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

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

La administración electrónica como herramienta de inclusión digital

¿Puede ser la administración electrónica una herramienta de inclusión digital? ¿Qué puede aportar la administración electrónica para avanzar en la inclusión digital? ¿Qué podemos hacer, cada uno desde nuestra actividad, para favorecer la inclusión digital? Estas son algunas de las preguntas que se formulaban los participantes en las III Jornadas sobre Derecho y Tecnología así como al XI Encuentro de Gobierno Electrónico e Inclusión Digital, celebrados en Zaragoza los días 23 y 24 de mayo de 2011. Cada uno, desde su perspectiva, trató de aportar ideas en esa línea que marcamos en la convocatoria del evento: «La administración electrónica como herramienta de inclusión digital». Estas aportaciones están recogidas en este libro, agrupadas en tres bloques diferentes. En el primero, bajo el título Políticas de inclusión digital desde la perspectiva de la administración electrónica, tienen cabida aquellas reflexiones sobre qué hacer para favorecer la inclusión digital desde la administración electrónica, con enfoques concretos en Brasil o Iberoamérica, o de tipo general, aplicable en cualquier país. En el segundo, el título Casos reales de inclusión digital desde la perspectiva de la administración electrónica reúne experiencias concretas llevadas a cabo en España y Brasil. Por último, y no menos importante, el título Inclusión digital desde las aulas universitarias recoge propuestas para fomentar la inclusión digital desde las aulas universitarias

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