An Empirical Study on Teachers’ Choice of Extensive Literature in the Swedish Upper Secondary EFL Classroom

The importance of extensive literature reading in the English as a Foreign Language (EFL) context has been given increasing attention in recent research. Literature reading is also a required part of the national syllabi of the (EFL) courses offered to both adolescents and adults at Upper Secondary level in Sweden. This thesis aims to investigate the teachers’ process of making literature choices for extensive reading in upper secondary EFL courses in Sweden. Eight teachers of three different student groups took part in the study, representing adolescent university preparatory programs and vocational programs, as well as programs for adult students. Questionnaires were used and the data was analyzed for patterns revealing three main factors affecting teachers’ literature choice: language proficiency, reading experience and contextual factors. These three factors were fitted into the theoretical framework of psycholinguistic and sociolinguistic reading models, with the addition of a perspective of motivational research. The results of this survey underline the importance of extensive reading, according to teachers, and that motivation for literature choice can be primarily related to factors associated with psycholinguistic reading models. The survey also points to the need for further investigating of teachers’ own experiences of literature reading, searching for deeper motivational factors which influence teaching choices. Another future field of research is the choice of reading activities assigned together with the chosen literature, which probably also influence teachers’ choices in the Swedish EFL classroom.

Models of complexity in Robert Coover's John's wife and the adventures of Lucky Pierre

This doctoral dissertation analyzes two novels by the American novelist Robert Coover as examples of hypertextual writing on the book bound page, as tokens of hyperfiction. The complexity displayed in the novels, John's Wife and The Adventures of Lucky Pierre, integrates the cultural elements that characterize the contemporary condition of capitalism and technologized practices that have fostered a different subjectivity evidenced in hypertextual writing and reading, the posthuman subjectivity. The models that account for the complexity of each novel are drawn from the concept of strange attractors in Chaos Theory and from the concept of rhizome in Nomadology. The transformations the characters undergo in the degree of their corporeality sets the plane on which to discuss turbulence and posthumanity. The notions of dynamic patterns and strange attractors, along with the concept of the Body without Organs and Rhizome are interpreted, leading to the revision of narratology and to analytical categories appropriate to the study of the novels. The reading exercised throughout this dissertation enacts Daniel Punday's corporeal reading. The changes in the characters' degree of materiality are associated with the stages of order, turbulence and chaos in the story, bearing on the constitution of subjectivity within and along the reading process. Coover's inscription of planes of consistency to counter linearity and accommodate hypertextual features to the paper supported narratives describes the characters' trajectory as rhizomatic. The study led to the conclusion that narrative today stands more as a regime in a rhizomatic relation with other regimes in cultural practice than as an exclusively literary form and genre. Besides this, posthuman subjectivity emerges as class identity, holding hypertextual novels as their literary form of choice.

Evaluating Value-at-Risk models via Quantile regressions

This paper is concerned with evaluating value at risk estimates. It is well known that using only binary variables to do this sacrifices too much information. However, most of the specification tests (also called backtests) avaliable in the literature, such as Christoffersen (1998) and Engle and Maganelli (2004) are based on such variables. In this paper we propose a new backtest that does not realy solely on binary variable. It is show that the new backtest provides a sufficiant condition to assess the performance of a quantile model whereas the existing ones do not. The proposed methodology allows us to identify periods of an increased risk exposure based on a quantile regression model (Koenker & Xiao, 2002). Our theorical findings are corroborated through a monte Carlo simulation and an empirical exercise with daily S&P500 time series.

Estimation of random coefficients logit demand models: an application to the Brazilian fixed income fund market

Estimation of demand and supply in differentiated products markets is a central issue in Empirical Industrial Organization and has been used to study the effects of taxes, merges, introduction of new goods, market power, among others. Logit and Random Coefficients Logit are examples of demand models used to study these effects. For the supply side it is generally supposed a Nash equilibrium in prices. This work presents a detailed discussion of these models of demand and supply as well as the procedure for estimation. Lastly, is made an application to the Brazilian fixed income fund market.

Binary integer programming formulations for scheduling in market-driven foundries

This paper describes the development and solution of binary integer formulations for production scheduling problems in market-driven foundries. This industrial sector is comprised of small and mid-sized companies with little or no automation, working with diversified production, involving several different metal alloy specifications in small tailor-made product lots. The characteristics and constraints involved in a typical production environment at these industries challenge the formulation of mathematical programming models that can be computationally solved when considering real applications. However, despite the interest on the part of these industries in counting on effective methods for production scheduling, there are few studies available on the subject. The computational tests prove the robustness and feasibility of proposed models in situations analogous to those found in production scheduling at the analyzed industrial sector. (C) 2010 Elsevier Ltd. All rights reserved.

Allocation of protective devices in distribution circuits using nonlinear programming models and genetic algorithms

The optimized allocation of protective devices in strategic points of the circuit improves the quality of the energy supply and the system reliability index. This paper presents a nonlinear integer programming (NLIP) model with binary variables, to deal with the problem of protective device allocation in the main feeder and all branches of an overhead distribution circuit, to improve the reliability index and to provide customers with service of high quality and reliability. The constraints considered in the problem take into account technical and economical limitations, such as coordination problems of serial protective devices, available equipment, the importance of the feeder and the circuit topology. The use of genetic algorithms (GAs) is proposed to solve this problem, using a binary representation that does (1) or does not (0) show allocation of protective devices (reclosers, sectionalizers and fuses) in predefined points of the circuit. Results are presented for a real circuit (134 busses), with the possibility of protective device allocation in 29 points. Also the ability of the algorithm in finding good solutions while improving significantly the indicators of reliability is shown. (C) 2003 Elsevier B.V. All rights reserved.

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.

Conserved currents in gravitational models with quasi-invariant Lagrangians: Application to teleparallel gravity

Conservation laws in gravitational theories with diffeomorphism and local Lorentz symmetry are studied. Main attention is paid to the construction of conserved currents and charges associated with an arbitrary vector field that generates a diffeomorphism on the spacetime. We further generalize previous results for the case of gravitational models described by quasi-invariant Lagrangians, that is, Lagrangians that change by a total derivative under the action of the local Lorentz group. The general formalism is then applied to the teleparallel models, for which the energy and the angular momentum of a Kerr black hole are calculated. The subsequent analysis of the results obtained demonstrates the importance of the choice of the frame.

Dynamic viscosity of binary and ternary mixtures containing poly(ethylene glycol), potassium phosphate, and water

Dynamic viscosity of binary mixtures of poly(ethylene glycol) molar mass 1500 da + water, potassium phosphate + water, and ternary mixtures of poly(ethylene glycol) molar mass 1500 da + potassium phosphate + water were determined at 303.15 K Binary and ternary mixture viscosities showed a direct logarithm-type relation with the increase of poly(ethylene glycol) and potassium phosphate contents. The models used for viscosity correlation gave a good fit to the experimental data.

Molecular models of cyclin-dependent kinase 1 complexed with inhibitors

Roscovitine and flavopiridol have been shown to potently inhibit cyclin-dependent kinase 1 and 2 (CDK1 and 2). The structures of CDK2 complexed with roscovitine and deschoroflavopiridol have been reported, however no crystallographic structure is available for complexes of CDK1 with inhibitors. The present work describes two molecular models for the binary complexes CDK1:roscovitine and CDK1:flavopiridol. These structural models indicate that both inhibitors strongly bind to the ATP-binding pocket of CDKI and structural comparison of the CDK complexes correlates the structures with differences in inhibition of these CDKs by flavopiridol and roscovitine. This article explains the structural basis for the observed differences in activity of these inhibitors. (C) 2004 Elsevier B.V. All rights reserved.

Rheological behavior of binary aqueous solutions of poly(ethylene glycol) of 1500 g·mol-1 as affected by temperature and polymer concentration

The rheological behavior of poly(ethylene glycol) of 1500 g·mol -1(PEG1500) aqueous solutions with various polymer concentrations (w = 0.05, 0.10, 0.15, 0.20 and 0.25) was studied at different temperatures (T = 283.15, 288.15, 293.15, 298.15 and 303.15) K. The analyses were carried out considering shear rates ranging from (20 to 350) s-1, using a cone-and-plate rheometer under controlled stress and temperature. Classical rheological models (Newton, Bingham, Power Law, Casson, and Herschel-Bulkley) were tested. The Power Law model was shown suitable to mathematically represent the rheological behavior of these solutions. Well-adjusted empirical models were derived for consistency index variations in function of temperature (Arrhenius-type model; R2 > 0.96), polymer concentration (exponential model; R2 > 0.99) or the combination of both (R 2 > 0.99). Additionally, linear models were used to represent the variations of behavior index in the functions of temperature (R2 > 0.83) and concentration (R2 > 0.87). © 2013 American Chemical Society.

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Comparison of a genetic group and unknown paternity models for growth traits in Nellore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The NINJA-2 project: detecting and characterizing gravitational waveforms modelled using numerical binary black hole simulations

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave (GW) astrophysics communities. The purpose of NINJA is to study the ability to detect GWs emitted from merging binary black holes (BBH) and recover their parameters with next-generation GW observatories. We report here on the results of the second NINJA project, NINJA-2, which employs 60 complete BBH hybrid waveforms consisting of a numerical portion modelling the late inspiral, merger, and ringdown stitched to a post-Newtonian portion modelling the early inspiral. In a 'blind injection challenge' similar to that conducted in recent Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo science runs, we added seven hybrid waveforms to two months of data recoloured to predictions of Advanced LIGO (aLIGO) and Advanced Virgo (AdV) sensitivity curves during their first observing runs. The resulting data was analysed by GW detection algorithms and 6 of the waveforms were recovered with false alarm rates smaller than 1 in a thousand years. Parameter-estimation algorithms were run on each of these waveforms to explore the ability to constrain the masses, component angular momenta and sky position of these waveforms. We find that the strong degeneracy between the mass ratio and the BHs' angular momenta will make it difficult to precisely estimate these parameters with aLIGO and AdV. We also perform a large-scale Monte Carlo study to assess the ability to recover each of the 60 hybrid waveforms with early aLIGO and AdV sensitivity curves. Our results predict that early aLIGO and AdV will have a volume-weighted average sensitive distance of 300 Mpc (1 Gpc) for 10M circle dot + 10M circle dot (50M circle dot + 50M circle dot) BBH coalescences. We demonstrate that neglecting the component angular momenta in the waveform models used in matched-filtering will result in a reduction in sensitivity for systems with large component angular momenta. This reduction is estimated to be up to similar to 15% for 50M circle dot + 50M circle dot BBH coalescences with almost maximal angular momenta aligned with the orbit when using early aLIGO and AdV sensitivity curves.

Microencapsulation of turmeric oleoresin in binary and ternary blends of gum arabic, maltodextrin and modified starch

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)