Genomic selection in rubber tree breeding: A comparison of models and methods for managing G×E interactions

Several genomic prediction models combining genotype × environment (G×E) interactions have recently been developed and used for genomic selection (GS) in plant breeding programs. G×E interactions reduce selection accuracy and limit genetic gains in plant breeding. Two data sets were used to compare the prediction abilities of multienvironment G×E genomic models and two kernel methods. Specifically, a linear kernel, or GB (genomic best linear unbiased predictor [GBLUP]), and a nonlinear kernel, or Gaussian kernel (GK), were used to compare the prediction accuracies (PAs) of four genomic prediction models: 1) a single-environment, main genotypic effect model (SM); 2) a multienvironment, main genotypic effect model (MM); 3) a multienvironment, single-variance G×E deviation model (MDs); and 4) a multienvironment, environment-specific variance G×E deviation model (MDe). We evaluated the utility of genomic selection (GS) for 435 individual rubber trees at two sites and genotyped the individuals via genotyping-by-sequencing (GBS) of single-nucleotide polymorphisms (SNPs). Prediction models were used to estimate stem circumference (SC) during the first 4 years of tree development in conjunction with a broad-sense heritability (H2) of 0.60. Applying the model (SM, MM, MDs, and MDe) and kernel method (GB and GK) combinations to the rubber tree data revealed that the multienvironment models were superior to the single-environment genomic models, regardless of the kernel (GB or GK) used, suggesting that introducing interactions between markers and environmental conditions increases the proportion of variance explained by the model and, more importantly, the PA. Compared with the classic breeding method (CBM), methods in which GS is incorporated resulted in a 5-fold increase in response to selection for SC with multienvironment GS (MM, MDe, or MDs). Furthermore, GS resulted in a more balanced selection response for SC and contributed to a reduction in selection time when used in conjunction with traditional genetic breeding programs. Given the rapid advances in genotyping methods and their declining costs and given the overall costs of large-scale progeny testing and shortened breeding cycles, we expect GS to be implemented in rubber tree breeding programs

Cartilage Tissue Engineering and Regeneration

Cartilaginous tissue is mainly present in the joints, and it consists predominantly of type II collagen and glycoproteins, which promote functions of supporting biomechanical forces generated during the ambulation. The cartilage has a very limited regenerating capacity, causing traumas or degenerative diseases in this region difficult to solve. The current treatments for regeneration of the articular cartilages may be conservative or surgical, but they are not very successful, since the damaged tissue is replaced by fibrous tissue or fibrocartilage, with predominantly type I collagen, which present inferior functions. Cellular therapies, biomaterials, and tissue engineering to assist the healing process have been showing great potential. For example, the in vitro chondrogenesis of mesenchymal stem cells (MSCs) is a technique that stimulates undifferentiated cells to transform into chondrocytes, creating a dense mass of aggregated MSCs and an environment with strong cell-cell interactions

Risk of Credit Cooperatives: An analysis based on the profile of the cooperated

This work has as purpose to analyze among the credit operations, those that generate larger breach of contract risk for the cooperative, with base in the profile of the cooperated, and to identify which the strategies can be pointed to avoid possible flaws in the next credit analyses. The work was divided in three stages. The first stage refers to the National Financial System, with the objective of demonstrating as in him the Cooperatives of Credit are inserted. The second stage approaches the System of Cooperative Credit, it presents that form is structured and his/her hierarchical level. The third stage treats of the System of Risk of Credit, in the which the risk, administration and the models of credit evaluation will be analyzed. It was verified that the most appropriate models for analysis of the Cooperatives of Credit are Credit Scoring Models and Credit Bureau, us which, through statistical techniques as the analysis discriminante and regression logistics, the characteristics of considered credits of larger breach of contract risk were demonstrated. The analysis based on identifying the "worse customer", because this generates larger breach of contract risk and it influences in the financial administration. It was ended that the most relevant variables to identify the breach of contract risk were the rude monthly income and the value liberated in the credit concession, because the largest concentration of breach of contract risk

Corporate governance : value creation and performance in credit unions

In this study, we examine the relationship between good corporate governance practices and the creation of value/performance of credit unions from 2010 to 2012. The objective was to create and validate a corporate governance index for credit unions, and to then analyse the relationship between good governance practices and the creation of value/performance. The problem question is: do good corporate governance practices provide value creation for credit unions? The research started by creating indices from factor analysis to identify latent dependent variables related to value creation and performance; next indices were created from the principal component analysis for the creation of independent latent variables related to corporate governance. Finally, based on panel data from regression models, the influence of the variables and indices related to corporate governance on the indices of value creation and performance was verified. Based on the research, it became evident that the Corporate Governance Index (IGC) is mainly impacted by Executive Management, with 40.31% of the IGC value, followed by the Representation and Participation dimension, with 34.07% of the IGC value. The contribution for academics was the creation of the Corporate Governance Index (IGC) applied for credit unions. As for the contribution to the system of credit unions, the highlight was the effectiveness of the mechanisms for economic-financial and asset management adopted by BACEN, credit unions and OCEMG.Nesta pesquisa, procurou-se analisar a relação entre as boas práticas de governança corporativa e a relação com a criação de valor/desempenho, das cooperativas de crédito ao longo do período de 2010 e 2012. O objetivo da pesquisa foi criar e validar um índice de governança corporativa para as cooperativas de crédito para então analisar a relação entre boas práticas de governança e a criação de valor/desempenho, tendo como questão problema: as boas práticas de governança corporativa proporcionam criação de valor para as cooperativas de crédito? Assim, iniciou-se a pesquisa por meio da criação de índices a partir da análise fatorial para a identificação de variáveis latentes dependentes relacionadas à criação de valor e desempenho; em seguida, a criação de índices a partir da análise de componentes principais para a criação de variáveis latentes independentes relacionadas à governança corporativa. Finalmente, verificou-se, a partir de modelos de regressão com dados em painel, a influência das variáveis e índices relacionados à governança corporativa com os índices de criação de valor e desempenho. Com base na pesquisa, ficou evidenciado que o Índice de Governança Corporativa (IGC) é impactado principalmente pela Gestão Executiva, representando 40,31% da importância do IGC, seguido da dimensão Representação e Participação com 34,07% da importância do IGC. A contribuição do trabalho para a academia foi a criação de Índice de Governança Corporativa (IGC) aplicável às cooperativas de crédito. Quanto à contribuição para o sistema de cooperativas de crédito, assinala-se a constatação de efetividade dos mecanismos de gestão econômico-financeira e patrimonial adotados pelo BACEN, Centrais de Cooperativas de Crédito e a OCEMG

Correlation between clinical performance and degree of conversion of resin cements: a literature review

AbstractResin-based cements have been frequently employed in clinical practice to lute indirect restorations. However, there are numerous factors that may compromise the clinical performance of those cements. The aim of this literature review is to present and discuss some of the clinical factors that may affect the performance of current resin-based luting systems. Resin cements may have three different curing mechanisms: chemical curing, photo curing or a combination of both. Chemically cured systems are recommended to be used under opaque or thick restorations, due to the reduced access of the light. Photo-cured cements are mainly indicated for translucent veneers, due to the possibility of light transmission through the restoration. Dual-cured are more versatile systems and, theoretically, can be used in either situation, since the presence of both curing mechanisms might guarantee a high degree of conversion (DC) under every condition. However, it has been demonstrated that clinical procedures and characteristics of the materials may have many different implications in the DC of currently available resin cements, affecting their mechanical properties, bond strength to the substrate and the esthetic results of the restoration. Factors such as curing mechanism, choice of adhesive system, indirect restorative material and light-curing device may affect the degree of conversion of the cement and, therefore, have an effect on the clinical performance of resin-based cements. Specific measures are to be taken to ensure a higher DC of the luting system to be used

O Cultivo de Organismos Geneticamente Modificados e a Contaminação da Água

Este artigo tem como objetivo discutir as consequências negativas associadas ao uso intensivo de agrotóxicos, herbicidas e fertilizantes nos cultivos de organismos geneticamente modificados . Tais consequências estão relacionadas, principalmente, aos danos ambientais e à saúde humana (de trabalhadores, famílias rurais e consumidores,) cujos custos acabam sendo socializados. O presente estudo analisa, a partir de dados obtidos por meio de Pesquisa e Revisão Bibliográfica, a contaminação da água como consequência do uso indiscriminado desses produtos. Conclui-se que o artigo pode contribuir para a formulação de políticas no sentido de auxiliar o desenho dos instrumentos de regulação e fornecer subsídios para a tomada de decisão mais rápida e eficiente em relação ao cultivo de organismos geneticamente modificados

Oropouche virus: clinical, epidemiological, and molecular aspects of a neglected orthobunyavirus.

Oropouche virus (OROV) is an important cause of arboviral illness in Latin American countries, more specifically in the Amazon region of Brazil, Venezuela and Peru, as well as in other countries such as Panama. In the past decades, the clinical, epidemiological, pathological, and molecular aspects of OROV have been published and provide the basis for a better understanding of this important human pathogen. Here, we describe the milestones in a comprehensive review of OROV epidemiology, pathogenesis, and molecular biology, including a description of the first isolation of the virus, the outbreaks during the past six decades, clinical aspects of OROV infection, diagnostic methods, genome and genetic traits, evolution, and viral dispersal

Generating criteria for the decision-making process using geoprocessing techniques

The use of GIS and the geoprocessing techniques have allowed applications in different areas. The MCDA – Multicriteria Decision Aided – provides support for the generation of criteria that are satisfactory both qualitatively and quantitatively. The present paper aims at providing an overall examination of a research previously conducted, using a case study, and extend the conclusions of that research and present the MCDA as good alternatives for establishing criteria that have been used in geoprocessed data

Indicadores de Liquidez Versus Modelo Dinâmico: Aplicação no Período Pré e Pós-Crise no Segmento Bancos

Pesquisas mostram que o Brasil, diante da crise financeira de 2008, que assolou a economia mundial, conseguiu atravessar a turbulência criada neste contexto e as instituições financeiras bancárias se mantiveram relativamente sólidas durante esse período, sofrendo apenas pequenos impactos, quando observado empresas estrangeiras, que sofreram severamente, sendo algumas vendidas a preços irrisórios e outras declarando falência. Um item que pode explicar este fato é a boa gestão de recursos financeiros que os bancos brasileiros praticam, visando a liquidez nas suas operações. Na literatura, encontram-se duas técnicas de gestão financeira para a tomada de decisões: o modelo tradicional, utilizando indicadores de liquidez e o modelo dinâmico (Modelo Fleuriet). A fim de se verificar a solidez dos bancos brasileiros antes e após a crise, nesta pesquisa buscou-se analisar a qualidade da gestão financeira aplicando as duas técnicas citadas. A pesquisa apontou que as mudanças na gestão financeira, retração de crédito, alavancagem nas aplicações financeiras e, em títulos e valores mobiliários foram pontos que neutralizaram os impactos provocados pela crise financeira. Ressaltam-se as formas efetivas de atuação do Bacen quanto aos aspectos regulatórios de mitigação de riscos junto do sistema financeiro nacional, proporcionando liquidez, alavancagem operacional e estrutura de capital compatível com as necessidades exigidas pelo comportamento do mercado interno

A divide-and-conquer approach for genomic prediction in rubber tree using machine learning

International audienceRubber tree ( Hevea brasiliensis ) is the main feedstock for commercial rubber; however, its long vegetative cycle has hindered the development of more productive varieties via breeding programs. With the availability of H. brasiliensis genomic data, several linkage maps with associated quantitative trait loci have been constructed and suggested as a tool for marker-assisted selection. Nonetheless, novel genomic strategies are still needed, and genomic selection (GS) may facilitate rubber tree breeding programs aimed at reducing the required cycles for performance assessment. Even though such a methodology has already been shown to be a promising tool for rubber tree breeding, increased model predictive capabilities and practical application are still needed. Here, we developed a novel machine learning-based approach for predicting rubber tree stem circumference based on molecular markers. Through a divide-and-conquer strategy, we propose a neural network prediction system with two stages: (1) subpopulation prediction and (2) phenotype estimation. This approach yielded higher accuracies than traditional statistical models in a single-environment scenario. By delivering large accuracy improvements, our methodology represents a powerful tool for use in Hevea GS strategies. Therefore, the incorporation of machine learning techniques into rubber tree GS represents an opportunity to build more robust models and optimize Hevea breeding programs