921 resultados para Built-in test
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Pós-graduação em Educação para a Ciência - FC
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Entomologia Agrícola) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Estudos Literários - FCLAR
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.
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Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.
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Pós-graduação em Agronomia (Entomologia Agrícola) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Estudos Literários - FCLAR
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The aim of this study was the isolation of the LAAO from Lachesis muta venom (LmLAAO) and its biochemical, functional and structural characterization. Two different purification protocols were developed and both provided highly homogeneous and active LmLAAO. It is a homodimeric enzyme with molar mass around 120 kDa under non-reducing conditions, 60 kDa under reducing conditions in SDS-PAGE and 60852 Da by mass spectrometry. Forty amino acid residues were directly sequenced from LmLAAO and its complete cDNA was identified and characterized from an Expressed Sequence Tags data bank obtained from a venom gland. A model based on sequence homology was manually built in order to predict its three-dimensional structure. LmLAAO showed a catalytic preference for hydrophobic amino acids (K-m of 0.97 mmol/L with Leu). A mild myonecrosis was observed histologically in mice after injection of 100 mu g of LmLAAO and confirmed by a 15-fold increase in CK activity. LmLAAO induced cytotoxicity on AGS cell line (gastric adenocarcinoma, IC50: 22.7 mu g/mL) and on MCF-7 cell line (breast adenocarcinoma, IC50:1.41 mu g/mL). It presents antiparasitic activity on Leishmania brasiliensis (IC50: 2.22 mu g/nnL), but Trypanosoma cruzi was resistant to LmLAAO. In conclusion, LmLAAO showed low systemic toxicity but important in vitro pharmacological actions. (C) 2012 Elsevier Ltd. All rights reserved.
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Samples of 40SiO(2)center dot 30Na(2)O center dot 1Al(2)O(3)center dot(29 - x)B2O3 center dot xFe(2)O(3) (mol%), with 0.0 <= x <= 17.5, were prepared by the fusion method and investigated by electron paramagnetic resonance (EPR), optical absorption (OA) and Mossbauer spectroscopy (MS). The EPR spectra of the as-synthesized samples exhibit two well-defined EPR signals around g = 4.27 and g = 2.01 and a visible EPR shoulder around g = 6.4, assigned to isolated Fe3+ ion complexes (g = 4.27 and g = 6.4) and Fe3+-based clusters (g = 2.01). Analyses of both EPR line intensity and line width support the model picture of Fe3+-based clusters built in from two sources of isolated ions, namely Fe2+ and Fe3+; the ferrous ion being used to build in iron-based clusters at lower x-content (below about x = 2.5%) whereas the ferric ion is used to build in iron-based clusters at higher x-content (above about x = 2.5%). The presence of Fe2+ ions incorporated within the glass template is supported by OA data with a strong band around 1100 nm due to the spin-allowed E-5(g)-T-5(2g) transition in an octahedral coordination with oxygen. Additionally, Mossbauer data (isomer shift and quadrupole splitting) confirm incorporation of both Fe2+ and Fe3+ ions within the template, more likely in tetrahedral-like environments. We hypothesize that ferrous ions are incorporated within the glass template as FeO4 complex resulting from replacing silicon in non-bridging oxygen (SiO3O-) sites whereas ferric ions are incorporated as FeO4 complex resulting from replacing silicon in bridging-like oxygen silicate groups (SiO4). (C) 2012 Elsevier Masson SAS. All rights reserved.
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Background: Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results: We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions: The use of an established and well-known graphical language in the development of biomedical ontologies provides a more intuitive form of capturing and representing knowledge than using only text-based notations. The use of the profile requires the domain expert to reason about the underlying semantics of the concepts and relationships being modeled, which helps preventing the introduction of inconsistencies in an ontology under development and facilitates the identification and correction of errors in an already defined ontology.