Upper and lower bounds on the learning curve for Gaussian processes

In this paper we introduce and illustrate non-trivial upper and lower bounds on the learning curves for one-dimensional Gaussian Processes. The analysis is carried out emphasising the effects induced on the bounds by the smoothness of the random process described by the Modified Bessel and the Squared Exponential covariance functions. We present an explanation of the early, linearly-decreasing behavior of the learning curves and the bounds as well as a study of the asymptotic behavior of the curves. The effects of the noise level and the lengthscale on the tightness of the bounds are also discussed.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

The dimerization and topological specificity functions of MinE reside in a structurally autonomous C-terminal domain

Correct placement of the division septum in Escherichia coli requires the co-ordinated action of three proteins, MinC, MinD and MinE. MinC and MinD interact to form a non-specific division inhibitor that blocks septation at all potential division sites. MinE is able to antagonize MinCD in a topologically sensitive manner, as it restricts MinCD activity to the unwanted division sites at the cell poles, Here, we show that the topological specificity function of MinE residues in a structurally autonomous, trypsin-resistant domain comprising residues 31-88, Nuclear magnetic resonance (NMR) and circular dichroic spectroscopy indicate that this domain includes both alpha and beta secondary structure, while analytical ultracentrifugation reveals that it also contains a region responsible for MinE homodimerization. While trypsin digestion indicates that the anti-MinCD domain of MinE (residues 1-22) does not form a tightly folded structural domain, NMR analysis of a peptide corresponding to MinE(1-22) indicates that this region forms a nascent helix in which the peptide rapidly interconverts between disordered (random coil) and alpha-helical conformations, This suggests that the N-terminal region of MinE may be poised to adopt an alpha-helical conformation when it interacts with the target of its anti-MinCD activity, presumably MinD.

Complex language functions and subcortical mechanisms: evidence from Huntington's disease and patients with non-thalamic subcortical lesions

The neuropathological changes associated with Huntington's disease (HD) are most marked in the head of the caudate nucleus and, to a lesser extent, in the putamen and globus pallidus, suggesting that at least part of the language impairments found in patients with HD may result from non-thalamic subcortical (NTS) pathology. The present study aimed to test the hypothesis that a signature profile of impaired language functions is found in patients who have sustained damage to the non-thalamic subcortex, either focally induced or resulting from neurodegenerative pathology. The language abilities of a group of patients with Huntington's disease (n=13) were compared with those of an age- and education-matched group of patients with chronic NTS lesions following stroke (n=13) and a non-neurologically impaired control group (n=13). The three groups were compared on language tasks that assessed both primary and more complex language abilities. The primary language battery consisted of The Western Aphasia Battery and The Boston Naming Test, whilst the more complex cognitive-linguistic battery employed selected subtests from The Test of Language Competence-Expanded, The Test of Word Knowledge and The Word Test-Revised. On many of the tests of primary language function from the Western Aphasia Battery, both the HD and NTS participants performed in a similar manner to the control participants. The language performances of the HD participants were significantly more impaired (p<0.05 using modified Bonferroni adjustments) than the control group, however, on various lexico-semantic tasks (e. g. the Boston Naming Test and providing definitions), on both single-word and sentence-level generative tasks (e. g. category fluency and formulating sentences), and on tasks which required interpretation of ambiguous, figurative and inferential meaning. The difficulties that patients with HD experienced with tasks assessing complex language abilities were strikingly similar, both qualitatively and quantitatively, to the language profile produced by NTS participants. The results provide evidence to suggest that a signature language profile is associated with damage to the non-thalamic subcortex resulting from either focal neurological insult or a degenerative disease.

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

Comments on ‘‘Modeling fractional stochastic systems as non-random fractional dynamics driven Brownian motions

Applied Mathematical Modelling, Vol.33

Avaliação do potencial eólico para geração de energia eléctrica

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia

Genetic variation between susceptible and non-susceptible snails to Schistosoma infection using random amplified polymorphic DNA analysis (RAPDs)

Susceptibility of snails to infection by certain trematodes and their suitability as hosts for continued development has been a bewildering problem in host-parasite relationships. The present work emphasizes our interest in snail genetics to determine what genes or gene products are specifically responsible for susceptibility of snails to infection. High molecular weight DNA was extracted from both susceptible and non-susceptible snails within the same species Biomphalaria tenagophila. RAPD was undertaken to distinguish between the two types of snails. Random primers (10 mers) were used to amplify the extracted DNA by the polymerase chain reaction (PCR) followed by polyacrylamide gel electrophoresis (PAGE) and silver staining. The results suggest that RAPD represents an efficient means of genome comparison, since many molecular markers were detected as genetic variations between susceptible and non-susceptible snails.

Non-classical error bounds in the central limit theorem

The classical central limit theorem states the uniform convergence of the distribution functions of the standardized sums of independent and identically distributed square integrable real-valued random variables to the standard normal distribution function. While first versions of the central limit theorem are already due to Moivre (1730) and Laplace (1812), a systematic study of this topic started at the beginning of the last century with the fundamental work of Lyapunov (1900, 1901). Meanwhile, extensions of the central limit theorem are available for a multitude of settings. This includes, e.g., Banach space valued random variables as well as substantial relaxations of the assumptions of independence and identical distributions. Furthermore, explicit error bounds are established and asymptotic expansions are employed to obtain better approximations. Classical error estimates like the famous bound of Berry and Esseen are stated in terms of absolute moments of the random summands and therefore do not reflect a potential closeness of the distributions of the single random summands to a normal distribution. Non-classical approaches take this issue into account by providing error estimates based on, e.g., pseudomoments. The latter field of investigation was initiated by work of Zolotarev in the 1960's and is still in its infancy compared to the development of the classical theory. For example, non-classical error bounds for asymptotic expansions seem not to be available up to now ...

Gaussian estimates for the density of the non-linear stochastic heat equation in any space dimension

In this paper, we establish lower and upper Gaussian bounds for the probability density of the mild solution to the stochastic heat equation with multiplicative noise and in any space dimension. The driving perturbation is a Gaussian noise which is white in time with some spatially homogeneous covariance. These estimates are obtained using tools of the Malliavin calculus. The most challenging part is the lower bound, which is obtained by adapting a general method developed by Kohatsu-Higa to the underlying spatially homogeneous Gaussian setting. Both lower and upper estimates have the same form: a Gaussian density with a variance which is equal to that of the mild solution of the corresponding linear equation with additive noise.

Analysis of angiotensin II- and ACTH-driven mineralocorticoid functions and omental adiposity in a non-genetic, hyperadipose female rat phenotype

The hypothalamic damage induced by neonatal treatment with monosodium l-glutamate (MSG) induces several metabolic abnormalities, resulting in a rat hyperleptinemic-hyperadipose phenotype. This study was conducted to explore the impact of the neonatal MSG treatment, in the adult (120 days old) female rat on: (a) the in vivo and in vitro mineralocorticoid responses to ACTH and angiotensin II (AII); (b) the effect of leptin on ACTH- and AII-stimulated mineralocorticoid secretions by isolated corticoadrenal cells; and (c) abdominal adiposity characteristics. Our data indicate that, compared with age-matched controls, MSG rats displayed: (1) enhanced and reduced mineralocorticoid responses to ACTH and AII treatments, respectively, effects observed in both in vivo and in vitro conditions; (2) adrenal refractoriness to the inhibitory effect of exogenous leptin on ACTH-stimulated aldosterone output by isolated adrenocortical cells; and (3) distorted omental adiposity morphology and function. This study supports that the adult hyperleptinemic MSG female rat is characterized by enhanced ACTH-driven mineralocorticoid function, impaired adrenal leptin sensitivity, and disrupted abdominal adiposity function. MSG rats could counteract undesirable effects of glucocorticoid excess, by developing a reduced AII-driven mineralocorticoid function. Thus, chronic hyperleptinemia could play a protective role against ACTH-mediated allostatic loads in the adrenal leptin resistant, MSG female rat phenotype.

Non-random fertilization in mice correlates with the MHC and something else

One evolutionary explanation for the success of sexual reproduction assumes that sex is an advantage in the coevolutionary arms race between pathogens and hosts. Accordingly, an important criterion in mate choice and maternal selection thereafter could be the allelic specificity at polymorphic loci involved in parasite-host interactions, e.g. the MHC (major histocompatibility complex). The MHC has been found to influence mate choice and selective abortions in mice and humans. However, it could also influence the fertilization process itself, i.e. (i) the oocyte's choice for the fertilizing sperm, and (ii) the outcome of the second meiotic division after the sperm has entered the egg. We tested both hypotheses in an in vitro fertilization experiment with two inbred mouse strains congenic for their MHC. The genotypes of the resulting blastocysts were determined by polymerase chain reaction. We found nonrandom MHC combinations in the blastocysts which may result from both possible choice mechanisms. The outcome changed significantly over time, indicating that a choice for MHC combinations during fertilization may be influenced by one or several external factors.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.