981 resultados para C-alpha model
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BACKGROUND: Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. OBJECTIVE: The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. METHODS: The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies’ safety conditions were also analyzed. RESULTS: Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies’ safety conditions; the organizational scale is the one that best reflects the actual safety conditions. CONCLUSIONS: The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups’ safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.
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In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.
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[Excerpt] The advantages resulting from the use of numerical modelling tools to support the design of processing equipment are almost consensual. The design of calibration systems in profile extrusion is not an exception . H owever , the complex geome tries and heat exchange phenomena involved in this process require the use of numerical solvers able to model the heat exchange in more than one domain ( calibrator and polymer), the compatibilization of the heat transfer at the profile - calibrator interface and with the ability to deal with complex geometries. The combination of all these features is usually hard to find in commercial software. Moreover , the dimension of the meshes required to ob tain accurate results, result in computational times prohibitive for industrial application. (...)
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A search for the Standard Model Higgs boson produced in association with a pair of top quarks, tt¯H, is presented. The analysis uses 20.3 fb−1 of pp collision data at s√ = 8 TeV, collected with the ATLAS detector at the Large Hadron Collider during 2012. The search is designed for the H to bb¯ decay mode and uses events containing one or two electrons or muons. In order to improve the sensitivity of the search, events are categorised according to their jet and b-tagged jet multiplicities. A neural network is used to discriminate between signal and background events, the latter being dominated by tt¯+jets production. In the single-lepton channel, variables calculated using a matrix element method are included as inputs to the neural network to improve discrimination of the irreducible tt¯+bb¯ background. No significant excess of events above the background expectation is found and an observed (expected) limit of 3.4 (2.2) times the Standard Model cross section is obtained at 95% confidence level. The ratio of the measured tt¯H signal cross section to the Standard Model expectation is found to be μ=1.5±1.1 assuming a Higgs boson mass of 125 GeV.
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Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a marked decline in cognition and memory function. Increasing evidence highlights the essential role of neuroinflammatory and immune-related molecules, including those produced at the brain barriers, on brain immune surveillance, cellular dysfunction and amyloid beta (Aß) pathology in AD. Therefore, understanding the response at the brain barriers may unravel novel pathways of relevance for the pathophysiology of AD. Herein, we focused on the study of the choroid plexus (CP), which constitutes the blood-cerebrospinal fluid barrier, in aging and in AD. Specifically, we used the PDGFB-APPSwInd (J20) transgenic mouse model of AD, which presents early memory decline and progressive Aß accumulation, and littermate age-matched wild-type (WT) mice, to characterize the CP transcriptome at 3, 5-6 and 11-12months of age. The most striking observation was that the CP of J20 mice displayed an overall overexpression of type I interferon (IFN) response genes at all ages. Moreover, J20 mice presented a high expression of type II IFN genes in the CP at 3months, which became lower than WT at 5-6 and 11-12months. Importantly, along with a marked memory impairment and increased glial activation, J20 mice also presented a similar overexpression of type I IFN genes in the dorsal hippocampus at 3months. Altogether, these findings provide new insights on a possible interplay between type I and II IFN responses in AD and point to IFNs as targets for modulation in cognitive decline.
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Analogues of Peptaibolin, a peptaibol with antibiotic activity, incorporating α,α-dialkylglycines (Deg, Dpg, and Ac6c) at selected positions were synthesised by MW-SPPS and fully characterized. A control analogue incorporating L-alanine was also prepared. The native peptide and the analogues were studied by fluorescence spectroscopy for their membrane permeating activity. Small unilamellar vesicles (SUVs) of egg phosphatidylcholine/ cholesterol (70:30) containing an encapsulated fluorescence probe (6-carboxyfluorescein) were used as membrane models. The assays of carboxyfluorescein release from SUVs upon peptide addition showed that Peptaibolin-Dpg and Peptaibolin-Ac6c are the most active peptides. These results indicate that the structure of the α,α-dialkylglycines is crucial for the membrane permeating ability of these Peptaibolin analogues.
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We perform Monte-Carlo simulations of the three-dimensional Ising model at the critical temperature and zero magnetic field. We simulate the system in a ball with free boundary conditions on the two dimensional spherical boundary. Our results for one and two point functions in this geometry are consistent with the predictions from the conjectured conformal symmetry of the critical Ising model.
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A modified version of the metallic-phase pseudofermion dynamical theory (PDT) of the 1D Hubbard model is introduced for the spin dynamical correlation functions of the half-filled 1D Hubbard model Mott– Hubbard phase. The Mott–Hubbard insulator phase PDT is applied to the study of the model longitudinal and transverse spin dynamical structure factors at finite magnetic field h, focusing in particular on the sin- gularities at excitation energies in the vicinity of the lower thresholds. The relation of our theoretical results to both condensed-matter and ultra-cold atom systems is discussed.
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OBJECTIVES: To describe the process of translation and linguistic and cultural validation of the Evidence Based Practice Questionnaire for the Portuguese context: Questionário de Eficácia Clínica e Prática Baseada em Evidências (QECPBE). METHOD: A methodological and cross-sectional study was developed. The translation and back translation was performed according to traditional standards. Principal Components Analysis with orthogonal rotation according to the Varimax method was used to verify the QECPBE's psychometric characteristics, followed by confirmatory factor analysis. Internal consistency was determined by Cronbach's alpha. Data were collected between December 2013 and February 2014. RESULTS: 358 nurses delivering care in a hospital facility in North of Portugal participated in the study. QECPBE contains 20 items and three subscales: Practice (α=0.74); Attitudes (α=0.75); Knowledge/Skills and Competencies (α=0.95), presenting an overall internal consistency of α=0.74. The tested model explained 55.86% of the variance and presented good fit: χ2(167)=520.009; p = 0.0001; χ2df=3.114; CFI=0.908; GFI=0.865; PCFI=0.798; PGFI=0.678; RMSEA=0.077 (CI90%=0.07-0.08). CONCLUSION: confirmatory factor analysis revealed the questionnaire is valid and appropriate to be used in the studied context.
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Transforming growth factor beta (TGF-ß) plays an important role in carcinogenesis. Two polymorphisms in the TGF-ß1 gene (-509C/T and 869T/C) were described to influence susceptibility to gastric and breast cancers. The 869T/C polymorphism was also associated with overall survival in breast cancer patients. In the present study, we investigated the relevance of these TGF-ß1 polymorphism in glioma risk and prognosis. A case-control study that included 114 glioma patients and 138 cancer-free controls was performed. Single nucleotide polymorphisms (SNPs) were evaluated by polymerase chain reaction followed by restriction fragment length polymorphism (PCR-RFLP). Univariate and multivariate logistic regression analyses were used to calculate odds ratio (OR) and 95 % confidence intervals (95 % CI). The influence of TGF-ß1 -509C/T and 869T/C polymorphisms on glioma patient survival was evaluated by a Cox regression model adjusted for patients' age and sex and represented in Kaplan-Meier curves. Our results demonstrated that TGF-ß1 gene polymorphisms -509C/T and 869T/C are not significantly associated with glioma risk. Survival analyses showed that the homozygous -509TT genotype associates with longer overall survival of glioblastoma (GBM) patients when compared with patients carrying CC + CT genotypes (OR, 2.41; 95 % CI, 1.06-5.50; p = 0.036). In addition, the homozygous 869CC genotype is associated with increased overall survival of GBM patients when compared with 869TT + TC genotypes (OR, 2.62; 95 % CI, 1.11-6.17; p = 0.027). In conclusion, this study suggests that TGF-ß1 -509C/T and 869T/C polymorphisms are not significantly associated with risk for developing gliomas but may be relevant prognostic biomarkers in GBM patients.
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This paper considers model spaces in an Hp setting. The existence of unbounded functions and the characterisation of maximal functions in a model space are studied, and decomposition results for Toeplitz kernels, in terms of model spaces, are established
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Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.
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Dissertação de mestrado em Molecular Genetics
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This paper presents a model predictive current control applied to a proposed single-phase five-level active rectifier (FLAR). This current control strategy uses the discrete-time nature of the active rectifier to define its state in each sampling interval. Although the switching frequency is not constant, this current control strategy allows to follow the reference with low total harmonic distortion (THDF). The implementation of the active rectifier that was used to obtain the experimental results is described in detail along the paper, presenting the circuit topology, the principle of operation, the power theory, and the current control strategy. The experimental results confirm the robustness and good performance (with low current THDF and controlled output voltage) of the proposed single-phase FLAR operating with model predictive current control.
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OBJETIVO: Avaliar o impacto do tratamento da obesidade nas adipocitocinas, na proteína C-reativa (PCR) e na sensibilidade à insulina em pacientes hipertensas com obesidade central. MÉTODOS: O estudo foi realizado a partir do banco de dados e de amostras estocadas de soro de pacientes submetidas previamente a um estudo para tratamento de obesidade. Foram selecionadas 30 mulheres hipertensas, com idade entre 18 e 65 anos, índice de massa corpórea (IMC) > 27 kg/m², com distribuição central de gordura. As pacientes foram aleatoriamente submetidas a dieta hipocalórica e orlistat 120 mg três vezes por dia ou apenas a dieta hipocalórica, durante 16 semanas. As pacientes que apresentaram perda de peso superior a 5% (n = 24) foram avaliadas em relação a níveis pressóricos, valores antropométricos, gordura visceral, índices de resistência (HOMA-R - homeostasis model assessment of insulin resistance) e de sensibilidade à insulina (ISI - Insulin Sensitivity Index), perfil lipídico, e dosagens das adipocitocinas (adiponectina, leptina, IL-6 e TNF-a) e de PCR. RESULTADOS: Após redução do IMC de cerca de 8% em ambos os grupos, foi verificada diminuição de gordura visceral, glicemia de jejum, triglicérides e TNF-a. Apenas o grupo orlistat, que inicialmente era mais resistente à insulina, apresentou redução significativa da glicemia pós-sobrecarga oral de glicose e aumento da sensibilidade à insulina. CONCLUSÃO: Os achados deste estudo indicam que a perda de peso superior a 5% se associa à melhora do perfil inflamatório e à redução da resistência à insulina, a qual ocorreu de maneira independente das variações de adiponectina e de TNF-a. Os maiores benefícios na sensibilidade à insulina obtidos no grupo orlistat não puderam ser atribuídos ao uso do medicamento em virtude da maior concentração de indivíduos resistentes à insulina nesse grupo.