Modelling of soil water content and soil salinity with HYDRUS-1D

Mestrado em Engenharia Agronómica. Universidade de Lisboa, Instituto Superior de AgronomiaSalt-affected soils may result in highly negative impacts on the soils’ functions, limiting the soils’ productivity and ultimately leading to desertification. The area of salt-affected soils is increasing globally as a result of inadequate irrigation practices and of climate change. This work was carried out within the SoilSalAdapt project, which studies the hypothesis that adaptation of soil microbiome to soil salinity may result in increased crop tolerance. The aim of this work was to model the soils’ water content and soil salinity in the three different soils used in the experiment carried out by the project team at the Lincoln University, UK. In experiment, spinach was grown in vases, without fertilization, inside a polytunnel, during two growth cycles. Spinach was irrigated with non-saline water and, at the end of the second cycle, with highly-saline water. In this work, SIMDualKc was used to calculate crop evapotranspiration under standard conditions using the dual crop coefficient method. HYDRUS-1D was used to model the soil water content and electrical conductivity of soil water, integrating water and salinity stresses to obtain the actual crop evapotranspiration. The models resulted in a root mean square error between 0.024 and 0.063 cm3cm-3 for soil water content and between 1.74 and 3.31 dSm-1 for soil salinity. The errors were lower when considering only the first growth cycle. At the end of the second cycle, when saline water was applied, the models underestimated the water content and overestimated the salinity. These larger errors reflect the fact that observed data, which was measured with a TDR, overestimated the soil water content when soil salinity was high. The models obtained in this thesis will allow the simulation of soil salinity under short- and long-term conditions, considering different irrigation managements and future climate conditions, and the estimation of potential productivity losses.A salinidade pode afetar os solos resultando em impactos negativos nas funções do solo, limitando a sua produtividade e podendo levar à desertificação. A área afetada pela salinidade está a crescer mundialmente, resultado de uma gestão inadequada da rega e das alterações climáticas. Este trabalho foi feito no âmbito do projeto SoilSalAdapt, que estuda a hipótese de pré-adaptar o microbioma à salinidade do solo através da gestão da salinidade da rega, conferindo tolerância às culturas. O objetivo deste trabalho é modelar o teor de água do solo e a salinidade em três tipos de solo usados na experiência efetuada pela equipa da Universidade de Lincoln. Na experiência, espinafres cresceram em vasos dentro de uma estufa, sem fertilização, durante dois ciclos de crescimento. Foram regados com água não salina e no final do segundo ciclo com água extremamente salina. Foi usado o SIMDualKc para calcular a evapotranspiração cultural em condições padrão usando a metodologia dos coeficientes duais. O HYDRUS-1D foi usado para modelar o teor de água do solo e a condutividade elétrica da água do solo, integrando o stress salino e hídrico, para obter a evapotranspiração cultural real. A raiz do erro quadrático médio foi de 0,024 a 0,063 cm3cm-3 para o teor de água e entre 1,74 até 3,31 dSm-1 para a salinidade. Os erros foram mais baixos no primeiro ciclo quando comparados com o segundo. No final do segundo ciclo, quando a rega salina é aplicada, os modelos subestimam o teor de água do solo e sobrestimam a salinidade. Estes erros superiores devem-se aos dados medidos com o TDR, que sobrestimam o teor de água no solo quando a salinidade é elevada. Os modelos obtidos permitem simular a salinidade a curto e longo prazo, considerando diferentes gestões de regas e alterações climáticas, e estimar potenciais perdas de produtividade.N/

Frequency and predictors of symptomatic intracranial hemorrhage after intravenous thrombolysis for acute ischemic stroke in a Brazilian public hospital

OBJECTIVE: Scarce data are available on the occurrence of symptomatic intracranial hemorrhage related to intravenous thrombolysis for acute stroke in South America. We aimed to address the frequency and clinical predictors of symptomatic intracranial hemorrhage after stroke thrombolysis at our tertiary emergency unit in Brazil. METHOD: We reviewed the clinical and radiological data of 117 consecutive acute ischemic stroke patients treated with intravenous thrombolysis in our hospital between May 2001 and April 2010. We compared our results with those of the Safe Implementation of Thrombolysis in Stroke registry. Univariate and multiple regression analyses were performed to identify factors associated with symptomatic intracranial transformation. RESULTS: In total, 113 cases from the initial sample were analyzed. The median National Institutes of Health Stroke Scale score was 16 (interquartile range: 10-20). The median onset-to-treatment time was 188 minutes (interquartile range: 155-227). There were seven symptomatic intracranial hemorrhages (6.2%; Safe Implementation of Thrombolysis in Stroke registry: 4.9%; p = 0.505). In the univariate analysis, current statin treatment and elevated National Institute of Health Stroke Scale scores were related to symptomatic intracranial hemorrhage. After the multivariate analysis, current statin treatment was the only factor independently associated with symptomatic intracranial hemorrhage. CONCLUSIONS: In this series of Brazilian patients with severe strokes treated with intravenous thrombolysis in a public university hospital at a late treatment window, we found no increase in the rate of symptomatic intracranial hemorrhage. Additional studies are necessary to clarify the possible association between statins and the risk of symptomatic intracranial hemorrhage after stroke thrombolysis

Blunt traumatic diaphragmatic rupture

A incidência de lesão traumática do diafragma, relatada na literatura, varia de0,6 a 1,2% dentre os pacientes vítimas de traumas, elevando-se para 5% nospacientes com trauma fechado submetidos a laparotomia. A suspeita clínicaassociada à avaliação radiológica contribui para o diagnóstico precoce. Alesão diafragmática isoladamente é de bom prognóstico. Assim, em geral, aslesões associadas à rotura diafragmática são os preditores da pior evoluçãodo paciente. As lesões do diafragma direito e as lesões bilaterais apresentampior prognóstico. A tomografia computadorizada com multidetectores (MDCT)de tórax oferece a possibilidade de reconstrução multiplanar permitindomelhor acurácia no diagnóstico. A correção cirúrgica por meio de laparotomiae/ou toracotomia na fase aguda do trauma apresenta boa evolução e evitaas complicações crônicas da hérnia diafragmática. Os autores apresentam ocaso de um paciente jovem do sexo masculino, vítima de trauma abdominalfechado por acidente automobilístico que apresentou rotura do diafragma, lesãoesplênica e renal. O diagnóstico foi feito através da tomografia computadorizadade tórax e abdome e confirmada durante laparotomia exploradora.Traumatic injury of the diaphragm ranges from 0.6 to 1.2% and rise up to 5%among patients who were victims of blunt trauma and underwent laparotomy.Clinical suspicion associated with radiological assessment contributes to earlydiagnosis. Isolated diaphragmatic injury has a good prognosis. Generallyworse outcomes are associated with other trauma injuries. Bilateral andright diaphragmatic lesions have worse prognosis. Multi detector computed tomography (MDCT) scan of the chest and abdomen provides better diagnosticaccuracy using the possibility of image multiplanar reconstruction. Surgicalrepair via laparotomy and/ or thoracotomy in the acute phase of the injury hasa better outcome and avoids chronic complications of diaphragmatic hernia.The authors present the case of a young male patient, victim of blunt abdominaltrauma due to motor vehicle accident with rupture of the diaphragm, spleenand kidney injuries. The diagnosis was made by computed tomography of thethorax and abdomen and was confirmed during laparotomy

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

O USO DE TECNOLOGIA NO ENSINO FUNDAMENTAL II

<p>O presente trabalho tem a finalidade de apresentar várias características de metodologias de ensino voltadas a matemática com o conhecimento em estatística e probabilidades. Sobre a disciplina em sala de aula, especificamente estatística e probabilidade, tende-se a proporcionar todo ensino e conhecimento de metodologia para criar uma ferramenta descrição e interpretação dos temas expostos. Em relação ao que está relacionado na aprendizagem, é possível criar uma solução de organização de modo a tornar um entendimento eficaz. De acordo com os dados coletados, a não aplicação do conhecimento, seja por meios tecnológicos ou por interdisciplinaridade, proporcionou uma lacuna sobre a disciplina de matemática voltada à estatística e probabilidade. Esse projeto tem um papel fundamental de indicar solução cabível para maior entendimento no decorrer do curso, facilitando a mediação educador e o educando.</p><p>Relatório Técnico - Cientifico apresentado na disciplina de Projeto Integrador para o curso de Licenciatura em Ciências Naturais e Matemática da Fundação Universidade Virtual do Estado de São Paulo (UNIVESP), em 2018.</p><p>Tutora: Juliana Alves Pereira Sato</p&gt

A DIVERSIDADE NO CONTEXTO ESCOLAR

<p>O presente trabalho tem por objetivo apresentar as dificuldades com aprendizagem de matemática para crianças do 7º ano do ensino Fundamental II, propondo como solução uma abordagem lúdica. Todo conceito histórico, demonstrado com referências aos mestres Piaget e Vygotsky e com a vasta obra de ambos sobre o estudo do comportamento humano, serve de fundamentação teórica para embasar a proposta de metodologia lúdica. Utilizam-se jogos e brincadeiras já existentes e relativamente simples, tais como bingo, dominó, xadrez, etc, mas que são de grande valia para constatação da importância de que a utilização do lúdico pode trazer leveza ao aluno e ao educador, diante das dificuldades existentes na aplicação da matéria. Vale ressaltar, que mais do que os métodos e ferramentas, apoia-se na interação social, peça chave para o sucesso da proposta. De nada adiantará todo recurso e toda gama de atividades se a aproximação dos indivíduos, enquanto seres humanos, não acontecer. Por fim, tão cristalino como água está a certeza de que para o projeto tenha sucesso é necessário um grau de interação superior à média cotidiana e uma efetiva colaboração e aceitação por parte da escola e de todos envolvidos.</p><p>Relatório Técnico - Cientifico apresentado na disciplina de Projeto Integrador para o curso de Licenciatura em Ciências Naturais e Matemática da Fundação Universidade Virtual do Estado de São Paulo (UNIVESP), em 2017.</p><p>Tutor: André Stocco de Oliveira</p&gt