43 resultados para MUTUAL INFORMATION

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Hydrodynamic studies were conducted in a semi-cylindrical spouted bed column of diameter 150 mm, height 1000 mm, conical base included angle of 60 degrees and inlet orifice diameter 25 mm. Pressure transducers at several axial positions were used to obtain pressure fluctuation time series with 1.2 and 2.4 mm glass beads at U/U-ms from 0.3 to 1.6, and static bed depths from 150 to 600 mm. The conditions covered several flow regimes (fixed bed, incipient spouting, stable spouting, pulsating spouting, slugging, bubble spouting and fluidization). Images of the system dynamics were also acquired through the transparent walls with a digital camera. The data were analyzed via statistical, mutual information theory, spectral and Hurst`s Rescaled Range methods to assess the potential of these methods to characterize the spouting quality. The results indicate that these methods have potential for monitoring spouted bed operation.

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In order to provide adequate multivariate measures of information flow between neural structures, modified expressions of partial directed coherence (PDC) and directed transfer function (DTF), two popular multivariate connectivity measures employed in neuroscience, are introduced and their formal relationship to mutual information rates are proved.

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Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

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We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009

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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

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The feasibility of detecting instability in wet spouted beds via pressure fluctuation (PF) time-series analyses was investigated. Experiments were carried out in a cylindrical Plexiglas column of diameter 150 mm with a conical base of internal angle 60 degrees, an inlet orifice diameter of 25 mm and glass beads of diameter 2.4 mm. Transducers at several axial positions measured PF time series with incremental addition of aqueous sucrose solutions of different concentrations. Liquid addition affected the spouted bed dynamics, causing irregular spouting, increased voidage in the annulus, increased fountain height, irregular annulus height, channelling, agglomeration, and adhesion of particles to the column walls. Autocorrelations indicated the appearance of periodicities in the PF signals with increasing sucrose addition. Dominant peaks in power-spectral density developed at low frequencies with changing system dynamics. The results indicate that PF signals furnish relevant information on system dynamics, useful for monitoring and control of spouted bed operations such as particle coating and drying of paste-like materials.

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The feasibility of characterizing the dynamics of a spouted bed based on acoustic emission (AE) signals is evaluated. Acoustic emission signals were measured in a semi-cylindrical Plexiglas column of diameter 150 mm and height 1000 mm with a conical base of internal angle 60 degrees and 25 mm inlet orifice diameter. Data were obtained for U/U(ms), from 0.3 to 2.0, static bed height from 250 to 500 mm, and glass beads of diameter 1.2 and 2.4 mm. AE signals reflected the effects of particle size and U/U(ms), but in general were insensitive to bed depth, even when there were drastic changes in spouting flow patterns. The results indicate that the AE signals were insensitive to the spouted bed hydrodynamics for the conditions studied. Overall, it appears that the AE analysis is unlikely to be a suitable technique for discriminating spouted bed flow regimes, at least for the range of frequencies and operating conditions investigated.

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This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.

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Nowadays, noninvasive methods of diagnosis have increased due to demands of the population that requires fast, simple and painless exams. These methods have become possible because of the growth of technology that provides the necessary means of collecting and processing signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this paper is to characterize healthy and pathological voice signals with the aid of relative entropy measures. Phase space reconstruction technique is also used as a way to select interesting regions of the signals. Three groups of samples were used, one from healthy individuals and the other two from people with nodule in the vocal fold and Reinke`s edema. All of them are recordings of sustained vowel /a/ from Brazilian Portuguese. The paper shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Relative entropy is well suited due to its sensibility to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. The results showed that the pathological groups had higher entropy values in accordance with other vocal acoustic parameters presented. This suggests that these techniques may improve and complement the recent voice analysis methods available for clinicians. (C) 2008 Elsevier Inc. All rights reserved.

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Assuming as a starting point the acknowledge that the principles and methods used to build and manage the documentary systems are disperse and lack systematization, this study hypothesizes that the notion of structure, when assuming mutual relationships among its elements, promotes more organical systems and assures better quality and consistency in the retrieval of information concerning users` matters. Accordingly, it aims to explore the fundamentals about the records of information and documentary systems, starting from the notion of structure. In order to achieve that, it presents basic concepts and relative matters to documentary systems and information records. Next to this, it lists the theoretical subsides over the notion of structure, studied by Benveniste, Ferrater Mora, Levi-Strauss, Lopes, Penalver Simo, Saussure, apart from Ducrot, Favero and Koch. Appropriations that have already been done by Paul Otlet, Garcia Gutierrez and Moreiro Gonzalez. In Documentation come as a further topic. It concludes that the adopted notion of structure to make explicit a hypothesis of real systematization achieves more organical systems, as well as it grants pedagogical reference to the documentary tasks.

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The present study investigated the distribution profile of dental caries and its association with areas of social deprivation at the individual and contextual level. The cluster sample consisted of 1,002 12-year-old schoolchildren from Piracicaba, SP, Brazil. The DMFT Index was used for dental caries and the Care Index was used to determine access to dental services. On the individual level, variables were associated with a better oral status. On the contextual level, areas were not associated with oral status. However, maps enabled determining that the central districts have better social and oral conditions than the deprived outlying districts.

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Background: During mating, insect males eject accessory gland proteins (Acps) into the female genital tract. These substances are known to affect female post-mating behavior and physiology. In addition, they may harm the female, e. g., in reducing its lifespan. This is interpreted as a consequence of sexual antagonistic co-evolution. Whereas sexual conflict abounds in non-social species, the peculiar life history of social insects (ants, bees, wasps) with lifelong pair-bonding and no re-mating aligns the reproductive interests of the sexes. Harming the female during mating would negatively affect male fitness and sexual antagonism is therefore not expected. Indeed, mating appears to increase female longevity in at least one ant species. Acps are presumed to play a role in this phenomenon, but the underlying mechanisms are unknown. In this study, we investigated genes, which are preferentially expressed in male accessory glands of the ant Leptothorax gredleri, to determine which proteins might be transferred in the seminal fluid. Results: By a suppression subtractive hybridization protocol we obtained 20 unique sequences (USs). Twelve had mutual best matches with genes predicted for Apis mellifera and Nasonia vitripennis. Functional information (Gene Ontology) was available only for seven of these, including intracellular signaling, energy-dependent transport and metabolic enzyme activities. The remaining eight USs did not match sequences from other species. Six genes were further analyzed by quantitative RT-PCR in three life cycle stages of male ants. A gene with carboxy-lyase activity and one of unpredicted function were significantly overexpressed in accessory glands of sexually mature males. Conclusions: Our study is the first one to investigate differential gene expression in ants in a context related to mating. Our findings indicate that male accessory glands of L. gredleri express a series of genes that are unique to this species, possibly representing novel genes, in addition to conserved ones for which functions can be predicted. Identifying differentially expressed genes might help to better understand molecular mechanisms involved in reproductive processes in eusocial Hymenoptera. While the novel genes could account for rapidly evolving ones driven by intra-sexual conflict between males, conserved genes imply that rather beneficial traits might get fixed by a process described as inter-sexual cooperation between males and females.

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How information transmission processes between individuals are shaped by natural selection is a key question for the understanding of the evolution of acoustic communication systems. Environmental acoustics predict that signal structure will differ depending on general features of the habitat. Social features, like individual spacing and mating behavior, may also be important for the design of communication. Here we present the first experimental study investigating how a tropical rainforest bird, the white-browed warbler Basileuterus leucoblepharus, extracts various information from a received song: species-specific identity, individual identity and location of the sender. Species-specific information is encoded in a resistant acoustic feature and is thus a public signal helping males to reach a wide audience. Conversely, individual identity is supported by song features susceptible to propagation: this private signal is reserved for neighbors. Finally, the receivers can locate the singers by using propagation-induced song modifications. Thus, this communication system is well matched to the acoustic constraints of the rain forest and to the ecological requirements of the species. Our results emphasize that, in a constraining acoustic environment, the efficiency of a sound communication system results from a coding/decoding process particularly well tuned to the acoustic properties of this environment.

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This article evaluates social implications of the ""SIGA"" Health Care Information System (HIS) in a public health care organization in the city of Sao Paulo. The evaluation was performed by means of an in-depth case study with patients and staff of a public health care organization, using qualitative and quantitative data. On the one hand, the system had consequences perceived as positive such as improved convenience and democratization of specialized treatment for patients and improvements in work organization. On the other hand, negative outcomes were reported, like difficulties faced by employees due to little familiarity with IT and an increase in the time needed to schedule appointments. Results show the ambiguity of the implications of HIS in developing countries, emphasizing the need for a more nuanced view of the evaluation of failures and successes and the importance of social contextual factors.

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This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.