Bayesian model selection for time series using Markov chain Monte Carlo

We present a stochastic simulation technique for subset selection in time series models, based on the use of indicator variables with the Gibbs sampler within a hierarchical Bayesian framework. As an example, the method is applied to the selection of subset linear AR models, in which only significant lags are included. Joint sampling of the indicators and parameters is found to speed convergence. We discuss the possibility of model mixing where the model is not well determined by the data, and the extension of the approach to include non-linear model terms.

Bayesian learning of noisy Markov decision processes

This work addresses the problem of estimating the optimal value function in a Markov Decision Process from observed state-action pairs. We adopt a Bayesian approach to inference, which allows both the model to be estimated and predictions about actions to be made in a unified framework, providing a principled approach to mimicry of a controller on the basis of observed data. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from theposterior distribution over the optimal value function. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.

Replicator Dynamics and Evolutionary Stable Strategies in Heterogeneous Games

We generalise and extend the work of Iñarra and Laruelle (2011) by studying two person symmetric evolutionary games with two strategies, a heterogenous population with two possible types of individuals and incomplete information. Comparing such games with their classic homogeneous version vith complete information found in the literature, we show that for the class of anti-coordination games the only evolutionarily stable strategy vanishes. Instead, we find infinite neutrally stable strategies. We also model the evolutionary process using two different replicator dynamics setups, each with a different inheritance rule, and we show that both lead to the same results with respect to stability.

New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

Dialog Systems based on Markov decision processes over two real tasks

In this work the state of the art of the automatic dialogue strategy management using Markov decision processes (MDP) with reinforcement learning (RL) is described. Partially observable Markov decision processes (POMDP) are also described. To test the validity of these methods, two spoken dialogue systems have been developed. The first one is a spoken dialogue system for weather forecast providing, and the second one is a more complex system for train information. With the first system, comparisons between a rule-based system and an automatically trained system have been done, using a real corpus to train the automatic strategy. In the second system, the scalability of these methods when used in larger systems has been tested.

STREAM Country Strategy Paper: Sri Lanka

In Sri Lanka the incidence of poverty varies among regions and livelihoods; aquatic resources users represent a poor category in many regions and therefore a vulnerable group. In December 2004 the country was hit by a Tsunami originating off the coast of Aceh in Indonesia, which affected the livelihoods of a large section of coastal aquatic resource users. The country is currently engaged in a major humanitarian effort to improve the livelihoods of aquatic resources users through various donor-funded projects. (PDF contains 18 pages)

STREAM Country Strategy Paper: Vietnam

Vietnam is a coastal country in Southeast Asia with a population of over 80 million. Although Vietnam has long been listed among the poorest countries of the world, it has recently made large strides in reducing poverty and improving food security. However, the dramatic gains in poverty reduction in Vietnam still remain quite fragile. There is growing evidence to indicate that dependence on aquatic resources is correlated to poverty, and that aquatic resources constitute an important component of wider livelihoods strategies (largely from the Mekong Delta, Central Coast and the Northern Mountains). (PDF contains 19 pages)

Adaptive Scalable SVD Unit for Fast Processing of Large LSE Problems

Singular Value Decomposition (SVD) is a key linear algebraic operation in many scientific and engineering applications. In particular, many computational intelligence systems rely on machine learning methods involving high dimensionality datasets that have to be fast processed for real-time adaptability. In this paper we describe a practical FPGA (Field Programmable Gate Array) implementation of a SVD processor for accelerating the solution of large LSE problems. The design approach has been comprehensive, from the algorithmic refinement to the numerical analysis to the customization for an efficient hardware realization. The processing scheme rests on an adaptive vector rotation evaluator for error regularization that enhances convergence speed with no penalty on the solution accuracy. The proposed architecture, which follows a data transfer scheme, is scalable and based on the interconnection of simple rotations units, which allows for a trade-off between occupied area and processing acceleration in the final implementation. This permits the SVD processor to be implemented both on low-cost and highend FPGAs, according to the final application requirements.

Simple Coalitional Strategy Profiles in Repeated Games

This paper is a version of the discussion paper titled "Simple coalitional strategy profiles"

Structural and Biophysical Characterization of Variants of the Mechanosensitive Channel of Large Conductance (MSCL)

The ability to sense mechanical force is vital to all organisms to interact with and respond to stimuli in their environment. Mechanosensation is critical to many physiological functions such as the senses of hearing and touch in animals, gravitropism in plants and osmoregulation in bacteria. Of these processes, the best understood at the molecular level involve bacterial mechanosensitive channels. Under hypo-osmotic stress, bacteria are able to alleviate turgor pressure through mechanosensitive channels that gate directly in response to tension in the membrane lipid bilayer. A key participant in this response is the mechanosensitive channel of large conductance (MscL), a non-selective channel with a high conductance of ~3 nS that gates at tensions close to the membrane lytic tension.

It has been appreciated since the original discovery by C. Kung that the small subunit size (~130 to 160 residues) and the high conductance necessitate that MscL forms a homo-oligomeric channel. Over the past 20 years of study, the proposed oligomeric state of MscL has ranged from monomer to hexamer. Oligomeric state has been shown to vary between MscL homologues and is influenced by lipid/detergent environment. In this thesis, we report the creation of a chimera library to systematically survey the correlation between MscL sequence and oligomeric state to identify the sequence determinants of oligomeric state. Our results demonstrate that although there is no combination of sequences uniquely associated with a given oligomeric state (or mixture of oligomeric states), there are significant correlations. In the quest to characterize the oligomeric state of MscL, an exciting discovery was made about the dynamic nature of the MscL complex. We found that in detergent solution, under mild heating conditions (37 °C – 60 °C), subunits of MscL can exchange between complexes, and the dynamics of this process are sensitive to the protein sequence.

Extensive efforts were made to produce high diffraction quality crystals of MscL for the determination of a high resolution X-ray crystal structure of a full length channel. The surface entropy reduction strategy was applied to the design of S. aureus MscL variants and while the strategy appears to have improved the crystallizability of S. aureus MscL, unfortunately the diffraction qualities of these crystals were not significantly improved. MscL chimeras were also screened for crystallization in various solubilization detergents, but also failed to yield high quality crystals.

MscL is a fascinating protein and continues to serve as a model system for the study of the structural and functional properties of mechanosensitive channels. Further characterization of the MscL chimera library will offer more insight into the characteristics of the channel. Of particular interest are the functional characterization of the chimeras and the exploration of the physiological relevance of intercomplex subunit exchange.

Micromechanical damage and fracture in elastomeric polymers

This thesis aims at a simple one-parameter macroscopic model of distributed damage and fracture of polymers that is amenable to a straightforward and efficient numerical implementation. The failure model is motivated by post-mortem fractographic observations of void nucleation, growth and coalescence in polyurea stretched to failure, and accounts for the specific fracture energy per unit area attendant to rupture of the material.

Furthermore, it is shown that the macroscopic model can be rigorously derived, in the sense of optimal scaling, from a micromechanical model of chain elasticity and failure regularized by means of fractional strain-gradient elasticity. Optimal scaling laws that supply a link between the single parameter of the macroscopic model, namely the critical energy-release rate of the material, and micromechanical parameters pertaining to the elasticity and strength of the polymer chains, and to the strain-gradient elasticity regularization, are derived. Based on optimal scaling laws, it is shown how the critical energy-release rate of specific materials can be determined from test data. In addition, the scope and fidelity of the model is demonstrated by means of an example of application, namely Taylor-impact experiments of polyurea rods. Hereby, optimal transportation meshfree approximation schemes using maximum-entropy interpolation functions are employed.

Finally, a different crazing model using full derivatives of the deformation gradient and a core cut-off is presented, along with a numerical non-local regularization model. The numerical model takes into account higher-order deformation gradients in a finite element framework. It is shown how the introduction of non-locality into the model stabilizes the effect of strain localization to small volumes in materials undergoing softening. From an investigation of craze formation in the limit of large deformations, convergence studies verifying scaling properties of both local- and non-local energy contributions are presented.

A new strategy of enhancing two-photon absorption in benzothiazole-containing fluorene molecules: Introduction of auxiliary donor-acceptor effects

A series of benzothiazole-containing fluorene molecules have been designed and their one- and two-photon absorption properties have been investigated theoretically by using the ZINDO method. The effects of electron-excessive/deficient heterocyclic bridges as auxiliary donors (auxD)/acceptors (auxA) on TPA cross-sections were studied. The results show that the molecules with D-pi-auxA-A, D-aux D-pi-A, or D-auxD-pi-auxA-A structure types have large TPA cross-section, which can be a valuable strategy in the design of two-photon absorption materials. Also, a linear relationship between the first hyperpolarizability and the TPA cross-section is observed. (c) 2006 Elsevier B.V. All rights reserved.

Systematics of the North American menhadens: molecular evolutionary reconstructions in the genus Brevoortia (Clupeiformes: Clupeidae)

Evolutionary associations among the four North American species of menhadens (Brevoortia spp.) have not been thoroughly investigated. In the present study, classifications separating the four species into small-scaled and large-scaled groups were evaluated by using DNA data, and genetic associations within these groups were explored. Specifically, data from the nuclear genome (microsatellites) and the mitochondrial genome (mtDNA sequences) were used to elicit patterns of recent and historical evolutionary associations. Nuclear DNA data indicated limited contemporary gene flow among the species, and also indicated higher relatedness within the small-scaled and large-scaled menhadens than between these groups. Mitochondrial DNA sequences of the large-scaled menhadens indicated the presence of two ancestral lineages, one of which contained members of both species. This result may indicate genetic diver-gence (reproductive isolation) followed by secondary contact (hybridization) between these species. In contrast, a single ancestral lineage indicated incomplete genetic divergence between the small-scaled menhaden. These results are discussed in the context of the biology and demographics of each species.

Segmentação de nome e endereço por meio de modelos escondidos de Markov e sua aplicação em processos de vinculação de registros

A segmentação dos nomes nas suas partes constitutivas é uma etapa fundamental no processo de integração de bases de dados por meio das técnicas de vinculação de registros. Esta separação dos nomes pode ser realizada de diferentes maneiras. Este estudo teve como objetivo avaliar a utilização do Modelo Escondido de Markov (HMM) na segmentação nomes e endereços de pessoas e a eficiência desta segmentação no processo de vinculação de registros. Foram utilizadas as bases do Sistema de Informações sobre Mortalidade (SIM) e do Subsistema de Informação de Procedimentos de Alta Complexidade (APAC) do estado do Rio de Janeiro no período entre 1999 a 2004. Uma metodologia foi proposta para a segmentação de nome e endereço sendo composta por oito fases, utilizando rotinas implementadas em PL/SQL e a biblioteca JAHMM, implementação na linguagem Java de algoritmos de HMM. Uma amostra aleatória de 100 registros de cada base foi utilizada para verificar a correção do processo de segmentação por meio do modelo HMM.Para verificar o efeito da segmentação do nome por meio do HMM, três processos de vinculação foram aplicados sobre uma amostra das duas bases citadas acima, cada um deles utilizando diferentes estratégias de segmentação, a saber: 1) divisão dos nomes pela primeira parte, última parte e iniciais do nome do meio; 2) divisão do nome em cinco partes; (3) segmentação segundo o HMM. A aplicação do modelo HMM como mecanismo de segmentação obteve boa concordância quando comparado com o observador humano. As diferentes estratégias de segmentação geraram resultados bastante similares na vinculação de registros, tendo a estratégia 1 obtido um desempenho pouco melhor que as demais. Este estudo sugere que a segmentação de nomes brasileiros por meio do modelo escondido de Markov não é mais eficaz do que métodos tradicionais de segmentação.