Orbital and strongly orbital spaces

We say that a (countably dimensional) topological vector space X is orbital if there is T∈L(X) and a vector x∈X such that X is the linear span of the orbit {Tnx:n=0,1,…}. We say that X is strongly orbital if, additionally, x can be chosen to be a hypercyclic vector for T. Of course, X can be orbital only if the algebraic dimension of X is finite or infinite countable. We characterize orbital and strongly orbital metrizable locally convex spaces. We also show that every countably dimensional metrizable locally convex space X does not have the invariant subset property. That is, there is T∈L(X) such that every non-zero x∈X is a hypercyclic vector for T. Finally, assuming the Continuum Hypothesis, we construct a complete strongly orbital locally convex space.

As a byproduct of our constructions, we determine the number of isomorphism classes in the set of dense countably dimensional subspaces of any given separable infinite dimensional Fréchet space X. For instance, in X=ℓ2×ω, there are exactly 3 pairwise non-isomorphic (as topological vector spaces) dense countably dimensional subspaces.

Learning to Interpret and Generate Instructional Recipes

Thesis (Ph.D.)--University of Washington, 2016-08

On the effect of word frequency on distributional similarity

The dependency of word similarity in vector space models on the frequency of words has been noted in a few studies, but has received very little attention. We study the influence of word frequency in a set of 10 000 randomly selected word pairs for a number of different combinations of feature weighting schemes and similarity measures. We find that the similarity of word pairs for all methods, except for the one using singular value decomposition to reduce the dimensionality of the feature space, is determined to a large extent by the frequency of the words. In a binary classification task of pairs of synonyms and unrelated words we find that for all similarity measures the results can be improved when we correct for the frequency bias.

Análisis y simulación de un rectificador trifásico controlado Active Front End (AFE)

Este artículo presenta un resultado de investigación financiado con recursos propios en el que se expone un modelo en espacio de estados de un rectificador trifásico controlado active front end. Utilizando este modelo se deriva una ley de control orientado al voltaje (VOC), enfocado en el comportamiento como carga resistiva, factor de potencia unitario, el cual es probado mediante simulación usando el Toolbox SimPowerSystem en Simulink de Matlab®.

Credit risk & forward price models

Doutoramento em Gestão

The efficiency of multivariate macroeconomic forecasts

We examine the efficiency of multivariate macroeconomic forecasts by estimating a vector autoregressive model on the forecast revisions of four variables (GDP, inflation, unemployment and wages). Using a data set of professional forecasts for the G7 countries, we find evidence of cross‐series revision dynamics. Specifically, forecasts revisions are conditionally correlated to the lagged forecast revisions of other macroeconomic variables, and the sign of the correlation is as predicted by conventional economic theory. This indicates that forecasters are slow to incorporate news across variables. We show that this finding can be explained by forecast underreaction.

Connected Hopf algebras of finite Gelfand-Kirillov dimension

Following the seminal work of Zhuang, connected Hopf algebras of finite GK-dimension over algebraically closed fields of characteristic zero have been the subject of several recent papers. This thesis is concerned with continuing this line of research and promoting connected Hopf algebras as a natural, intricate and interesting class of algebras. We begin by discussing the theory of connected Hopf algebras which are either commutative or cocommutative, and then proceed to review the modern theory of arbitrary connected Hopf algebras of finite GK-dimension initiated by Zhuang. We next focus on the (left) coideal subalgebras of connected Hopf algebras of finite GK-dimension. They are shown to be deformations of commutative polynomial algebras. A number of homological properties follow immediately from this fact. Further properties are described, examples are considered and invariants are constructed. A connected Hopf algebra is said to be "primitively thick" if the difference between its GK-dimension and the vector-space dimension of its primitive space is precisely one . Building on the results of Wang, Zhang and Zhuang,, we describe a method of constructing such a Hopf algebra, and as a result obtain a host of new examples of such objects. Moreover, we prove that such a Hopf algebra can never be isomorphic to the enveloping algebra of a semisimple Lie algebra, nor can a semisimple Lie algebra appear as its primitive space. It has been asked in the literature whether connected Hopf algebras of finite GK-dimension are always isomorphic as algebras to enveloping algebras of Lie algebras. We provide a negative answer to this question by constructing a counterexample of GK-dimension 5. Substantial progress was made in determining the order of the antipode of a finite dimensional pointed Hopf algebra by Taft and Wilson in the 1970s. Our final main result is to show that the proof of their result can be generalised to give an analogous result for arbitrary pointed Hopf algebras.

Studies in search of a suitable experimental insect model for xenodiagnosis of hosts with Chagas' disease: 3 - On the interaction of vector species and parasite strain in the reaction of bugs to infection by Trypanosoma cruzi

The reaction of nine vector species of Chagas' disease to infection by seven different Trypanosoma cruzi strains; Berenice, Y, FL, CL, S. Felipe, Colombiana and Gávea, are examined and compared. On the basis of the insects' ability to establish and maintain the infection, vector species could be divided into two distinct groups which differ in their reaction to an acute infection by T. cruzi. While the proportion of positive bugs was found to be low in Triatoma infestans and Triatoma dimidiata it was high, ranging from 96.9% to 100% in the group of wild (Rhodnius neglectus, Triatoma rubrovaria)and essentially sylvatic vectors in process of adaptation to human dwellings, maintained under control following successful insecticidal elimination of Triatoma infestans (Panstrongylus megistus, Triatoma sordida and Triatoma pseudomaculata). An intermediate position is held by Triatoma brasiliensis and Rhodnius prolixus. This latter has been found to interchange between domestic and sylvatic environments. The most important finding is the strikingly good reaction between each species of the sylvatic bugs and practically all T. cruzi strains herein studied, thus indicating that the factors responsible for the excellent reaction of P.megistus to infection by Y strain, as previously reported also come into operation in the reaction of the same vector species to acute infections by five of the remaining T.cruzi strains. Comparison or data reported by other investigators with those herein described form the basis of the discussion of Dipetalogaster maximus as regards its superiority as a xenodiagnostic agent.

Studies in search of a suitable experimental insect model for xenodiagnosis of hosts with Chagas' disease: 4 - The reflection of parasite stock in the responsiveness of different vector species to chronic infection with different Trypanosoma cruzi stocks

Previous studies (1982,1987) have emphasized the superiority of sylvatic vector species over domestic species as xenodiagnostic agents in testing hosts with acute or chronic infections by T. cruzi "Y" stock. The present study, which is unique in that it contains data on both infectivity rates produced by the same stock in 11 different vector species and also the reaction of the same vector species to seven different parasite stocks, establishes the general validity of linking efficiency of xenodiagnosis to the biotope of its agent. For example, infectivity rates produced by "São Felipe" stock varied from 82.5% to 98.3% in sylvatic vectors but decreased to 42.5% to 71.3% in domestic species. "Colombiana" stock produced in the same sylvatic vectors infectivity rates ranging from 12.5% to 45%. These shrank to 5%-22.5% in domestic bugs. The functional role of the biotope in the vector-parasite interaction has not been eluddated. But since this phenomenon has been observed to be stable and easy to reproduce, it leads us to believe that the results obtained are valid. Data presented also provide increasing evidence that the infectivity rates exhibited by bugs from xenodiagnosis in chronic hosts, are parasite stock specific. For example, infectivity rates produced by "Berenice", "Y", "FL" and "CL" varied in R. neglectus from 26.3% to 75%; in P. megistus from 56.3% to 83.8%; in T. sordida from 28.8% to 58.8% in T. pseudomaculata from 41.3% to 66.3% and in T. rubrovaria from 48.8% to 85%. Data from xenodiagnosis in the same hosts, carrying acute infections by the same parasite stocks, gave the five sylvatic vectors a positive rating of approximately 100%, thus suggesting that the heavy loads of parasites circulating in the acute hosts obscured the characteristic interspecific differences for the parasite stock. Nonetheless these latter were revealed in the same hosts with chronic infections stimulated by very low numbers of the same parasite stocks. Certain observations here described lead us to speculate as to the possibility of further results from other parasite stocks, allowing the association of the infectivity rates produced in bugs by different parasite stocks with the isoenzymic patterns revealed by these stocks.

Malaria transmission model for different levels of acquired immunity and temperature-dependent parameters (vector)

OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes) are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Effects of Non-Susceptible Hosts on the Infection with Trypanosoma cruzi of the Vector Triatoma infestans: an Experimental Model

We tested experimentally the effects of the presence of non-susceptible hosts on the infection with Trypanosoma cruzi of the vector Triatoma infestans. The experiment consisted in two treatments: with chickens, including two chickens (non-susceptible hosts) and two infected guinea pigs (susceptible hosts), and without chickens, including only two infected guinea pigs. The hosts were held unrestrained in individual metal cages inside a closed tulle chamber. A total of 200 uninfected T. infestans third instar nymphs were liberated in each replica, collected on day 14, and examined for infection and blood meal sources on day 32-36. The additional presence of chickens relative to infected guinea pigs: (a) significantly modified the spatial distribution of bugs; (b) increased significantly the likelihoods of having a detectable blood meal on any host and molting to the next instar; (c) did not affect the bugs' probability of death by predation; and (d) decreased significantly the overall percentage of T. infestans infected with T. cruzi. The bugs collected from inside or close to the guinea pigs' cages showed a higher infection rate (71-88%) than those collected from the chickens' cages (22-32%). Mixed blood meals on chickens and guinea pigs were detected in 12-21% of bugs. Although the presence of chickens would decrease the overall percentage of infected bugs in short term experiments, the high rate of host change of T. infestans would make this difference fade out if longer exposure times had been provided.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Loss Modelling of Three-Level Inverters controlled with Space Vector Modulation Technique

The objective of this master’s thesis is to investigate the loss behavior of three-level ANPC inverter and compare it with conventional NPC inverter. The both inverters are controlled with mature space vector modulation strategy. In order to provide the comparison both accurate and detailed enough NPC and ANPC simulation models should be obtained. The similar control model of SVM is utilized for both NPC and ANPC inverter models. The principles of control algorithms, the structure and description of models are clarified. The power loss calculation model is based on practical calculation approaches with certain assumptions. The comparison between NPC and ANPC topologies is presented based on results obtained for each semiconductor device, their switching and conduction losses and efficiency of the inverters. Alternative switching states of ANPC topology allow distributing losses among the switches more evenly, than in NPC inverter. Obviously, the losses of a switching device depend on its position in the topology. Losses distribution among the components in ANPC topology allows reducing the stress on certain switches, thus losses are equally distributed among the semiconductors, however the efficiency of the inverters is the same. As a new contribution to earlier studies, the obtained models of SVM control, NPC and ANPC inverters have been built. Thus, this thesis can be used in further more complicated modelling of full-power converters for modern multi-megawatt wind energy conversion systems.