BRT- TRANSCARIOCA BOA OPÇÃO DE TRANSPORTE NA CIDADE DO RIO DE JANEIRO

Este trabalho debruça-se sobre o transporte público, os problemas advindos desse tema, a errada política brasileira, que por décadas vem privilegiando o sistema rodoviário individual, em detrimento ao transporte público coletivo de qualidade. Expõe o sistema BRT (Bus Rapid Transit), invoca o sistema carioca do BRT e suas linhas e esmiúça o BRT Transcarioca, uma das 4 linhas do sistema de BRT carioca. O texto permeia, ainda, as características do transporte público carioca e expõe o pouco investimento em transporte público. Especificamente sobre o BRT Transcarioca, descreve suas generalidades, percurso, estações, terminais, obras de arte, bairros interligados e por último, análises do ponto de vista da qualidade do sistema, comparativamente com o transporte usado pré-BRT, além de uma pesquisa de campo sobre o tempo de viagem

Reference Genes For Normalization Of Qpcr Assays In Sugarcane Plants Under Water Deficit

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Sugarcane (Saccharum spp.) is the main raw material for sugar and ethanol production. Among the abiotic stress, drought is the main one that negatively impact sugarcane yield. Although gene expression analysis through quantitative PCR (qPCR) has increased our knowledge about biological processes related to drought, gene network that mediates sugarcane responses to water deficit remains elusive. In such scenario, validation of reference gene is a major requirement for successful analyzes involving qPCR. Results: In this study, candidate genes were tested for their suitable as reference genes for qPCR analyses in two sugarcane cultivars with varying drought tolerance. Eight candidate reference genes were evaluated in leaves sampled in plants subjected to water deficit in both field and greenhouse conditions. In addition, five genes were evaluated in shoot roots of plants subjected to water deficit by adding PEG8000 to the nutrient solution. NormFinder and RefFinder algorithms were used to identify the most stable gene(s) among genotypes and under different experimental conditions. Both algorithms revealed that in leaf samples, UBQ1 and GAPDH genes were more suitable as reference genes, whereas GAPDH was the best reference one in shoot roots. Conclusion: Reference genes suitable for sugarcane under water deficit were identified, which would lead to a more accurate and reliable analysis of qPCR. Thus, results obtained in this study may guide future research on gene expression in sugarcane under varying water conditions.13Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) [Brazil-552381/2007-1]"Fundacao de Amparo a Pesquisa do Estado de Sao Paulo" (FAPESP) [Brazil-2011/50661-8, 2008/57495-3]CNPqCoordenacao de Aperfeicoamento de Pessoal de Nivel Superior-CAPESFAPESPConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

PROCESSO DE AUTOMAÇÃO DE RETRONANÁLISE DOS PARÂMETROS DO SOLO PELO MÉTODO DE FELLENIUS PARA FINS DE ESTABILIDADE DE TALUDE

O presente artigo aborda a frequência dos casos de desestabilidade de maciços de solo ocasionados por fatores naturais ou por intervenções urbanas e do aumento da demanda de projetos em estabilidade de taludes, faz-se necessário a elaboração de um programa que vise automatizar o processo de análise de dados. O presente trabalho trata da elaboração de um programa que visa automatizar os cálculos do método de Fellenius e propor uma retroanálise. A fim de obter maior confiabilidade serão comparados os resultados obtidos pelo método computacional e o método geométrico tradicional para análise em estabilidade de taludes e apresenta qual das possíveis soluções será a que apresenta os menores valores de parâmetros do solo

SISTEMA HÍBRIDO DE ENERGIA: FUNCIONAMENTO E UTILIZAÇÃO RESIDENCIA

Sabendo da escassez de fontes de energia ecologicamente sustentável, foi estudada uma alternativa para as fontes de energia elétrica comuns em nosso país, para que em meio à escassez de recursos hídricos, termelétricos e nucleares, possa haver um melhor aproveitamento da energia elétrica consumida pelo usuário final. A proposta apresenta uma alternativa através de uma fonte híbrida de geração, composta por um sistema que concilia energia eólica e fotovoltaica. O projeto apresenta um conceito inovador em âmbito nacional, mas comumente utilizado na Europa, chamado Sistema Smart Grid, que possibilita a junção da energia gerada pela concessionária e pela fonte híbrida para o consumo. A partir da estimativa de geração das fontes e de dados coletados de sistemas já implantados, estipulou-se que o sistema proposto, seria capaz de atender a demanda desejada.   Palavras-chave: Energia Eólica. Energia Solar. Sistema híbrido de energia. Sistema Smart Grid

Murine Dendritic Cells Transcriptional Modulation upon Paracoccidioides brasiliensis Infection

Limited information is available regarding the modulation of genes involved in the innate host response to Paracoccidioides brasiliensis, the etiologic agent of paracoccidioidomycosis. Therefore, we sought to characterize, for the first time, the transcriptional profile of murine bone marrow-derived dendritic cells (DCs) at an early stage following their initial interaction with P. brasiliensis. DCs connect innate and adaptive immunity by recognizing invading pathogens and determining the type of effector T-cell that mediates an immune response. Gene expression profiles were analyzed using microarray and validated using real-time RT-PCR and protein secretion studies. A total of 299 genes were differentially expressed, many of which are involved in immunity, signal transduction, transcription and apoptosis. Genes encoding the cytokines IL-12 and TNF-α, along with the chemokines CCL22, CCL27 and CXCL10, were up-regulated, suggesting that P. brasiliensis induces a potent proinflammatory response in DCs. In contrast, pattern recognition receptor (PRR)-encoding genes, particularly those related to Toll-like receptors, were down-regulated or unchanged. This result prompted us to evaluate the expression profiles of dectin-1 and mannose receptor, two other important fungal PRRs that were not included in the microarray target cDNA sequences. Unlike the mannose receptor, the dectin-1 receptor gene was significantly induced, suggesting that this β-glucan receptor participates in the recognition of P. brasiliensis. We also used a receptor inhibition assay to evaluate the roles of these receptors in coordinating the expression of several immune-related genes in DCs upon fungal exposure. Altogether, our results provide an initial characterization of early host responses to P. brasiliensis and a basis for better understanding the infectious process of this important neglected pathogen

Biomass Accumulation and Cell Wall Structure of Rice Plants Overexpressing a Dirigent-Jacalin of Sugarcane (ShDJ) Under Varying Conditions of Water Availability

A sugarcane gene encoding a dirigent-jacalin, ShDJ, was induced under drought stress. To elucidate its biological function, we integrated a ShDJ-overexpression construction into the rice Nipponbare genome via Agrobacterium-mediated transformation. Two transgenic lines with a single copy gene in T0 were selected and evaluated in both the T1 and T4 generations. Transgenic lines had drastically improved survival rate under water deficit conditions, at rates close to 100%, while WT did not survive. Besides, transgenic lines had improved biomass production and higher tillering under water deficit conditions compared with WT plants. Reduced pectin and hemicellulose contents were observed in transgenic lines compared with wild-type plants under both well-watered and water deficit conditions, whereas cellulose content was unchanged in line #17 and reduced in line #29 under conditions of low water availability. Changes in lignin content under water deficit were only observed in line #17. However, improvements in saccharification were found in both transgenic lines along with changes in the expression of OsNTS1/2 and OsMYB58/63 secondary cell wall biosynthesis genes. ShDJ-overexpression up-regulated the expression of the OsbZIP23, OsGRAS23, OsP5CS, and OsLea3 genes in rice stems under well-watered conditions. Taken together, our data suggest that ShDJ has the potential for improving drought tolerance, plant biomass accumulation, and saccharification efficiency

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