955 resultados para BINARY RESPONSE MODELS


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Trees and shrubs in tropical Africa use the C3 cycle as a carbon fixation pathway during photosynthesis, while grasses and sedges mostly use the C4 cycle. Leaf-wax lipids from sedimentary archives such as the long-chain n-alkanes (e.g., n-C27 to n-C33) inherit carbon isotope ratios that are representative of the carbon fixation pathway. Therefore, n-alkane d13C values are often used to reconstruct past C3/C4 composition of vegetation, assuming that the relative proportions of C3 and C4 leaf waxes reflect the relative proportions of C3 and C4 plants. We have compared the d13C values of n-alkanes from modern C3 and C4 plants with previously published values from recent lake sediments and provide a framework for estimating the fractional contribution (areal-based) of C3 vegetation cover (fC3) represented by these sedimentary archives. Samples were collected in Cameroon, across a latitudinal transect that accommodates a wide range of climate zones and vegetation types, as reflected in the progressive northward replacement of C3-dominated rain forest by C4-dominated savanna. The C3 plants analysed were characterised by substantially higher abundances of n-C29 alkanes and by substantially lower abundances of n-C33 alkanes than the C4 plants. Furthermore, the sedimentary d13C values of n-C29 and n-C31 alkanes from recent lake sediments in Cameroon (-37.4 per mil to -26.5 per mil) were generally within the range of d13C values for C3 plants, even when from sites where C4 plants dominated the catchment vegetation. In such cases simple linear mixing models fail to accurately reconstruct the relative proportions of C3 and C4 vegetation cover when using the d13C values of sedimentary n-alkanes, overestimating the proportion of C3 vegetation, likely as a consequence of the differences in plant wax production, preservation, transport, and/or deposition between C3 and C4 plants. We therefore tested a set of non-linear binary mixing models using d13C values from both C3 and C4 vegetation as end-members. The non-linear models included a sigmoid function (sine-squared) that describes small variations in the fC3 values as the minimum and maximum d13C values are approached, and a hyperbolic function that takes into account the differences between C3 and C4 plants discussed above. Model fitting and the estimation of uncertainties were completed using the Monte Carlo algorithm and can be improved by future data addition. Models that provided the best fit with the observed d13C values of sedimentary n-alkanes were either hyperbolic functions or a combination of hyperbolic and sine-squared functions. Such non-linear models may be used to convert d13C measurements on sedimentary n-alkanes directly into reconstructions of C3 vegetation cover.

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Context: The stellar population of the 30 Doradus star-forming region in the Large Magellanic Cloud contains a subset of apparently single, rapidly rotating O-type stars. The physical processes leading to the formation of this cohort are currently uncertain. 

Aims: One member of this group, the late O-type star VFTS 399, is found to be unexpectedly X-ray bright for its bolometric luminosity-in this study we aim to determine its physical nature and the cause of this behaviour. 

Methods: To accomplish this we performed a time-resolved analysis of optical, infrared and X-ray observations. 

Results: We found VFTS 399 to be an aperiodic photometric variable with an apparent near-IR excess. Its optical spectrum demonstrates complex emission profiles in the lower Balmer series and select He i lines-taken together these suggest an OeBe classification. The highly variable X-ray luminosity is too great to be produced by a single star, while the hard, non-thermal nature suggests the presence of an accreting relativistic companion. Finally, the detection of periodic modulation of the X-ray lightcurve is most naturally explained under the assumption that the accretor is a neutron star. 

Conclusions: VFTS 399 appears to be the first high-mass X-ray binary identified within 30 Dor, sharing many observational characteristics with classical Be X-ray binaries. Comparison of the current properties of VFTS 399 to binary-evolution models suggests a progenitor mass 25 M for the putative neutron star, which may host a magnetic field comparable in strength to those of magnetars. VFTS 399 is now the second member of the cohort of rapidly rotating "single" O-type stars in 30 Dor to show evidence of binary interaction resulting in spin-up, suggesting that this may be a viable evolutionary pathway for the formation of a subset of this stellar population.

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Die Fähigkeit, geschriebene Texte zu verstehen, d.h. eine kohärente mentale Repräsentation von Textinhalten zu erstellen, ist eine notwendige Voraussetzung für eine erfolgreiche schulische und außerschulische Entwicklung. Es ist daher ein zentrales Anliegen des Bildungssystems Leseschwierigkeiten frühzeitig zu diagnostizieren und mithilfe zielgerichteter Interventionsprogramme zu fördern. Dies erfordert ein umfassendes Wissen über die kognitiven Teilprozesse, die dem Leseverstehen zugrunde liegen, ihre Zusammenhänge und ihre Entwicklung. Die vorliegende Dissertation soll zu einem umfassenden Verständnis über das Leseverstehen beitragen, indem sie eine Auswahl offener Fragestellungen experimentell untersucht. Studie 1 untersucht inwieweit phonologische Rekodier- und orthographische Dekodierfertigkeiten zum Satz- und Textverstehen beitragen und wie sich beide Fertigkeiten bei deutschen Grundschüler(inne)n von der 2. bis zur 4. Klasse entwickeln. Die Ergebnisse legen nahe, dass beide Fertigkeiten signifikante und eigenständige Beiträge zum Leseverstehen leisten und dass sich ihr relativer Beitrag über die Klassenstufen hinweg nicht verändert. Darüber hinaus zeigt sich, dass bereits deutsche Zweitklässler(innen) den Großteil geschriebener Wörter in altersgerechten Texten über orthographische Vergleichsprozesse erkennen. Nichtsdestotrotz nutzen deutsche Grundschulkinder offenbar kontinuierlich phonologische Informationen, um die visuelle Worterkennung zu optimieren. Studie 2 erweitert die bisherige empirische Forschung zu einem der bekanntesten Modelle des Leseverstehens—der Simple View of Reading (SVR, Gough & Tunmer, 1986). Die Studie überprüft die SVR (Reading comprehension = Decoding x Comprehension) mithilfe optimierter und methodisch stringenter Maße der Modellkonstituenten und überprüft ihre Generalisierbarkeit für deutsche Dritt- und Viertklässler(innen). Studie 2 zeigt, dass die SVR einer methodisch stringenten Überprüfung nicht standhält und nicht ohne Weiteres auf deutsche Dritt- und Viertklässler(innen) generalisiert werden kann. Es wurden nur schwache Belege für eine multiplikative Verknüpfung von Dekodier- (D) und Hörverstehensfertigkeiten (C) gefunden. Der Umstand, dass ein beachtlicher Teil der Varianz im Leseverstehen (R) nicht durch D und C aufgeklärt werden konnte, deutet darauf hin, dass das Modell nicht vollständig ist und ggf. durch weitere Komponenten ergänzt werden muss. Studie 3 untersucht die Verarbeitung positiv-kausaler und negativ-kausaler Kohärenzrelationen bei deutschen Erst- bis Viertklässler(inne)n und Erwachsenen im Lese- und Hörverstehen. In Übereinstimmung mit dem Cumulative Cognitive Complexity-Ansatz (Evers-Vermeul & Sanders, 2009; Spooren & Sanders, 2008) zeigt Studie 3, dass die Verarbeitung negativ-kausaler Kohärenzrelationen und Konnektoren kognitiv aufwändiger ist als die Verarbeitung positiv-kausaler Relationen. Darüber hinaus entwickelt sich das Verstehen beider Kohärenzrelationen noch über die Grundschulzeit hinweg und ist für negativ-kausale Relationen am Ende der vierten Klasse noch nicht abgeschlossen. Studie 4 zeigt und diskutiert die Nützlichkeit prozess-orientierter Lesetests wie ProDi- L (Richter et al., in press), die individuelle Unterschiede in den kognitiven Teilfertigkeiten des Leseverstehens selektiv erfassen. Hierzu wird exemplarisch die Konstruktvalidität des ProDi-L-Subtests ‚Syntaktische Integration’ nachgewiesen. Mittels explanatorischer Item- Repsonse-Modelle wird gezeigt, dass der Test Fertigkeiten syntaktischer Integration separat erfasst und Kinder mit defizitären syntaktischen Fertigkeiten identifizieren kann. Die berichteten Befunde tragen zu einem umfassenden Verständnis der kognitiven Teilfertigkeiten des Leseverstehens bei, das für eine optimale Gestaltung des Leseunterrichts, für das Erstellen von Lernmaterialien, Leseinstruktionen und Lehrbüchern unerlässlich ist. Darüber hinaus stellt es die Grundlage für eine sinnvolle Diagnose individueller Leseschwierigkeiten und für die Konzeption adaptiver und zielgerichteter Interventionsprogramme zur Förderung des Leseverstehens bei schwachen Leser(inne)n dar.

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Dissertação de Mestrado em Ciências da Educação - Especialização em Educação Especial. Apresentada à Escola Superior de Educação de Paula Frassinetti.

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Esta tese incide sobre o desenvolvimento de modelos computacionais e de aplicações para a gestão do lado da procura, no âmbito das redes elétricas inteligentes. É estudado o desempenho dos intervenientes da rede elétrica inteligente, sendo apresentado um modelo do produtor-consumidor doméstico. O problema de despacho económico considerando previsão de produção e consumo de energia obtidos a partir de redes neuronais artificiais é apresentado. São estudados os modelos existentes no âmbito dos programas de resposta à procura e é desenvolvida uma ferramenta computacional baseada no algoritmo de fuzzy-clustering subtrativo. São analisados perfis de consumo e modos de operação, incluindo uma breve análise da introdução do veículo elétrico e de contingências na rede de energia elétrica. São apresentadas aplicações para a gestão de energia dos consumidores no âmbito do projeto piloto InovGrid. São desenvolvidos sistemas de automação para, aquisição monitorização, controlo e supervisão do consumo a partir de dados fornecidos pelos contadores inteligente que permitem a incorporação das ações dos consumidores na gestão do consumo de energia elétrica; SMART GRIDS - COMPUTATIONAL MODELS DEVELOPMENT AND DEMAND SIDE MANAGMENT APPLICATIONS Abstract: This thesis focuses on the development of computational models and its applications on the demand side management within the smart grid scope. The performance of the electrical network players is studied and a domestic prosumer model is presented. The economic dispatch problem considering the production forecast and the energy consumption obtained from artificial neural networks is also presented. The existing demand response models are studied and a computational tool based on the fuzzy subtractive clustering algorithm is developed. Energy consumption profiles and operational modes are analyzed, including a brief analysis of the electrical vehicle and contingencies on the electrical network. Consumer energy management applications within the scope of InovGrid pilot project are presented. Computational systems are developed for the acquisition, monitoring, control and supervision of consumption data provided by smart meters allowing to incorporate consumer actions on their electrical energy management.

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Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.

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Thirteen international netballers viewed static images of scenarios taken from netball open play. Two ‘team mates’, each marked by one opponent, could be seen in each image; each team mate-opponent pair was located on opposite sides of the vertical meridian, such that a binary response was required (‘left’ or ‘right’) from the participant, in order to select a team mate to whom they would pass the ball. For each trial, a spoken word (“left”/“right”) was presented monaurally at the onset of the visual image. Spatially invalid auditory cues (i.e., in the ear contralateral to the correct passing option), reduced performance accuracy relative to valid ones. Semantically invalid cues (e.g., a call of “left” when the target was right-located), increased response times relative to valid ones. However, there were no accompanying changes in visual attention to the team mates and their markers. The effects of auditory cues on covert attentional shifts and decision-making are discussed.

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La presente investigación tiene como objetivo realizar un estudio piloto de la demanda de cocinas de inducción del año 2014-2015 y posteriormente un análisis comparativo. Este estudio es aplicado a la parroquia El Valle, perteneciente al cantón Cuenca, excluyendo el área urbana, empleando como objeto de estudio a los jefes de hogar de la parroquia, a través de dos modelos Logit binario con iguales características para realizar la comparación de ambos años. Los principales resultados en el año 2014 muestran que, en relación al tamaño de la muestra en la parroquia rural El Valle, el 33% de la población están dispuestos a adquirir la cocina de inducción, los factores que influyen en la decisión de adquirir la cocina de inducción son: el ingreso obteniendo un efecto positivo y el costo con un efecto negativo. En la estimación del costo se obtiene que, considerando que todos los hogares encuestados de la parroquia rural El Valle adquirirán la cocina de inducción, los costos totales por hogar en promedio es de $573.34. Mientras los resultados del año 2015 son, que el 20% de la población encuestada en la parroquia adquirirán la cocina de inducción, las variables edad y pago de factura eléctrica son las que tienen mayor influencia en el modelo, existiendo una relación inversa en ambas y en la determinación del costo se obtiene que es de $526.70 aproximadamente.

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Studies have demonstrated that public policies to support private firms’ investment have the ability to promote entrepreneurship, but the sustainability of subsidized firms has not often been analysed. This paper aims to examine this dimension specifically through evaluating the mortality of subsidized firms in the long-term. The analysis focuses on a case study of the LEADER+ Programme in the Alentejo region of Portugal. With this purpose, the paper examines the activity status (active or not active) of 154 private, rural, for-profit firms in Alentejo that had received a subsidy to support investment between 2002 and 2008 under the LEADER+ Programme. The methodology is based on binary choice models in order to study the probability of these firms still being active. The explanatory variables used are the following: (1) the characteristics of entrepreneurs and managers’ strategic decisions, (2) firm profile and characteristics, (3) regional economic environment. Data assessment showed that the cumulative mortality rate of firms on 31st December 2013 is over 20 %. Interpretation of the regression model revealed that he probability of firms’ survival increases with higher investment, firm age and regional business concentration, whereas the number of applications made by firms has a negative impact on their survival. So it seems that for subsidized firms the amount of investment is as important as its frequency.

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Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

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Blends of milk fat and canola oil (MF:CNO) were enzymatically interesterified (EIE) by Rhizopus oryzne lipase immobilized on polysiloxane-polyvinyl alcohol (SiO(2)-PVA) composite, in a solvent-free system. A central composite design (CCD) was used to optimize the reaction, considering the effects of different mass fractions of binary blends of MF:CNO (50:50, 65:35 and 80:20) and temperatures (45, 55 and 65 degrees C) on the composition and texture properties of the interesterified products, taking the interesterification degree (ID) and consistency (at 10 degrees C) as response variables. For the ID variable both mass fraction of milk fat in the blend and temperature were found to be significant, while for the consistency only mass fraction of milk fat was significant. Empiric models for ID and consistency were obtained that allowed establishing the best interesterification conditions: blend with 65 % of milk fat and 35 %, of canola oil, and temperature of 45 degrees C. Under these conditions, the ID was 19.77 %) and the consistency at 10 degrees C was 56 290 Pa. The potential of this eco-friendly process demonstrated that a product could be obtained with the desirable milk fat flavour and better spreadability under refrigerated conditions.

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Context. Tight binaries discovered in young, nearby associations are ideal targets for providing dynamical mass measurements to test the physics of evolutionary models at young ages and very low masses. Aims. We report the binarity of TWA22 for the first time. We aim at monitoring the orbit of this young and tight system to determine its total dynamical mass using an accurate distance determination. We also intend to characterize the physical properties (luminosity, effective temperature, and surface gravity) of each component based on near-infrared photometric and spectroscopic observations. Methods. We used the adaptive-optics assisted imager NACO to resolve the components, to monitor the complete orbit and to obtain the relative near-infrared photometry of TWA22 AB. The adaptive-optics assisted integral field spectrometer SINFONI was also used to obtain medium-resolution (R(lambda) = 1500-2000) spectra in JHK bands. Comparison with empirical and synthetic librairies were necessary for deriving the spectral type, the effective temperature, and the surface gravity for each component of the system. Results. Based on an accurate trigonometric distance (17.5 +/- 0.2 pc) determination, we infer a total dynamical mass of 220 +/- 21 M(Jup) for the system. From the complete set of spectra, we find an effective temperature T(eff) = 2900(-200)(+200) K for TWA22A and T(eff) = 2900(-100)(+200) for TWA22 B and surface gravities between 4.0 and 5.5 dex. From our photometry and an M6 +/- 1 spectral type for both components, we find luminosities of log(L/L(circle dot)) = -2.11 +/- 0.13 dex and log(L/L(circle dot)) = -2.30 +/- 0.16 dex for TWA22 A and B, respectively. By comparing these parameters with evolutionary models, we question the age and the multiplicity of this system. We also discuss a possible underestimation of the mass predicted by evolutionary models for young stars close to the substellar boundary.

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Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

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Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-All binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes. (C) 2001 by Elsevier Science Inc.