54 resultados para Commandino, Federico, 1509-1575.

em Queensland University of Technology - ePrints Archive


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BACKGROUND: Although we know much about the molecular makeup of the sinus node (SN) in small mammals, little is known about it in humans. The aims of the present study were to investigate the expression of ion channels in the human SN and to use the data to predict electrical activity. METHODS AND RESULTS: Quantitative polymerase chain reaction, in situ hybridization, and immunofluorescence were used to analyze 6 human tissue samples. Messenger RNA (mRNA) for 120 ion channels (and some related proteins) was measured in the SN, a novel paranodal area, and the right atrium (RA). The results showed, for example, that in the SN compared with the RA, there was a lower expression of Na(v)1.5, K(v)4.3, K(v)1.5, ERG, K(ir)2.1, K(ir)6.2, RyR2, SERCA2a, Cx40, and Cx43 mRNAs but a higher expression of Ca(v)1.3, Ca(v)3.1, HCN1, and HCN4 mRNAs. The expression pattern of many ion channels in the paranodal area was intermediate between that of the SN and RA; however, compared with the SN and RA, the paranodal area showed greater expression of K(v)4.2, K(ir)6.1, TASK1, SK2, and MiRP2. Expression of ion channel proteins was in agreement with expression of the corresponding mRNAs. The levels of mRNA in the SN, as a percentage of those in the RA, were used to estimate conductances of key ionic currents as a percentage of those in a mathematical model of human atrial action potential. The resulting SN model successfully produced pacemaking. CONCLUSIONS: Ion channels show a complex and heterogeneous pattern of expression in the SN, paranodal area, and RA in humans, and the expression pattern is appropriate to explain pacemaking.

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Air pollution is ranked by the World Health Organisation as one of the top ten contributors to the global burden of disease and injury. Exposure to gaseous air pollutants, even at a low level, has been associated with cardiorespiratory diseases (Vedal, Brauer et al. 2003). Most recent epidemiological studies of air pollution have used time-series analyses to explore the relationship between daily mortality or morbidity and daily ambient air pollution concentrations based on the same day or previous days (Hajat, Armstrong et al. 2007). However, most of the previous studies have examined the association between air pollution and health outcomes using air pollution data from a single monitoring site or average values from a few monitoring sites to represent the whole population of the study area. In fact, for a metropolitan city, ambient air pollution levels may differ significantly among the different areas. There is increasing concern that the relationships between air pollution and mortality may vary with geographical area (Chen, Mengersen et al. 2007). Additionally, some studies have indicated that socio-economic status can act as a confounder when investigating the relation between geographical location and health (Scoggins, Kjellstrom et al. 2004). This study examined the spatial variation in the relationship between long-term exposure to gaseous air pollutants (including nitrogen dioxide (NO2), ozone (O3) and sulphur dioxide (SO2)), and cardiorespiratory mortality in Brisbane, Australia, during the period 1996 - 2004.

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Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.

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Published in concomitance with the adoption of the United Nations Declaration on the Rights of Indigenous Peoples, this volume brings together a group of renowned legal experts and activists from different parts of the world who, from international and comparative perspectives, investigate the right of indigenous peoples to reparation for breaches of their individual and collective rights. The first part of the book is devoted to general aspects of this important matter, providing a comprehensive assessment of the relevant international legal framework and including overviews of the topic of reparations for human rights violations, the status of indigenous peoples in international law, and the vision of reparations as conceived by the communities concerned. The second part embraces a comprehensive investigation of the relevant practice at the international, regional, and national level, examining the best practices of reparations according to the ideologies and expectations of indigenous peoples and offering a comparative perspective on the ways in which the right of these peoples to redress for the injuries suffered is realized worldwide. The global picture painted by these contributions provides a view of the status of relevant international law that is synthesized in the two final chapters of the book, which include a concrete example of how a judicial claim for reparation is to be structured and prescribes the best practices and strategies to be adopted in order to maximize the opportunities for indigenous peoples to obtain effective redress. As a whole, this volume offers a comprehensive vision of its subject matter in international and comparative law, with a practical approach aimed at supporting legal academics, administrators, and practitioners in improving the avenues and modalities of reparations for indigenous peoples

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Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

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Optimal design methods have been proposed to determine the best sampling times when sparse blood sampling is required in clinical pharmacokinetic studies. However, the optimal blood sampling time points may not be feasible in clinical practice. Sampling windows, a time interval for blood sample collection, have been proposed to provide flexibility in blood sampling times while preserving efficient parameter estimation. Because of the complexity of the population pharmacokinetic models, which are generally nonlinear mixed effects models, there is no analytical solution available to determine sampling windows. We propose a method for determination of sampling windows based on MCMC sampling techniques. The proposed method attains a stationary distribution rapidly and provides time-sensitive windows around the optimal design points. The proposed method is applicable to determine sampling windows for any nonlinear mixed effects model although our work focuses on an application to population pharmacokinetic models.

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Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

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Sodium and cesium mordenite (denoted NaM and CsM, respectively) were investigated as potential catalysts for the synthesis of polyacetylene ((CH) x). Both were successful in initiating polymerization of purified gaseous acetylene at room temperature as evidenced by Raman spectroscopic studies. The polyacetylene synthesised in this way exhibited resonance enhancement of the polyene skeletal vibrations. trans-Polyacetylene, but no cis-(CH) x, was detected. As no apparent coloration of the NaM and CsM substrates accompanied the formation of trans-(CH) x it was concluded that only small quantities of the polymer were present. The number of conjugated double bonds was estimated from the frequencies of the Raman active C-C and C=C stretching vibrations, and it was shown that the trans-(CH) x formed on CsM has a distribution of conjugation lengths ranging from less than 6 to at least 30 double bonds. The polyacetylene formed on NaM was significantly shorter and was produced in lower yields than that synthesized on CsM. "Sliced" resonance excitation profiles of polyacetylene formed on CsM were obtained using nearly 40 different excitation wavelengths and these confirmed that the adsorbed trans-(CH) x was composed of segments having a distribution of conjugated lengths. The architecture of the mordenite pore system permitted only a single polymer molecule per channel, thereby preventing cross-linking. Raman spectroscopic studies of the effects of exposure to air revealed that progressive oxidative degradation occurred with a reduction in the number of conjugated double bond

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Instances of parallel ecotypic divergence where adaptation to similar conditions repeatedly cause similar phenotypic changes in closely related organisms are useful for studying the role of ecological selection in speciation. Here we used a combination of traditional and next generation genotyping techniques to test for the parallel divergence of plants from the Senecio lautus complex, a phenotypically variable groundsel that has adapted to disparate environments in the South Pacific. Phylogenetic analysis of a broad selection of Senecio species showed that members of the S. lautus complex form a distinct lineage that has diversified recently in Australasia. An inspection of thousands of polymorphisms in the genome of 27 natural populations from the S. lautus complex in Australia revealed a signal of strong genetic structure independent of habitat and phenotype. Additionally, genetic differentiation between populations was correlated with the geographical distance separating them, and the genetic diversity of populations strongly depended on geographical location. Importantly, coastal forms appeared in several independent phylogenetic clades, a pattern that is consistent with the parallel evolution of these forms. Analyses of the patterns of genomic differentiation between populations further revealed that adjacent populations displayed greater genomic heterogeneity than allopatric populations and are differentiated according to variation in soil composition. These results are consistent with a process of parallel ecotypic divergence in face of gene flow.

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Adaptation to replicate environments is often achieved through similar phenotypic solutions. Whether selection also produces convergent genomic changes in these situations remains largely unknown. The variable groundsel, Senecio lautus, is an excellent system to investigate the genetic underpinnings of convergent evolution, because morphologically similar forms of these plants have adapted to the same environments along the coast of Australia. We compared range-wide patterns of genomic divergence in natural populations of this plant and searched for regions putatively affected by natural selection. Our results indicate that environmental adaptation followed complex genetic trajectories, affecting multiple loci, implying both the parallel recruitment of the same alleles and the divergence of completely different genomic regions across geography. An analysis of the biological functions of candidate genes suggests that adaptation to coastal environments may have occurred through the recruitment of different genes participating in similar processes. The relatively low genetic convergence that characterizes the parallel evolution of S. lautus forms suggests that evolution is more constrained at higher levels of biological organization.

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Bi-2212 tapes were fabricated using a powder-in-tube method and their superconducting properties were measured as a function of heat treatment. The tapes were heated to temperature, T1 (884-915 °C), and kept at that temperature for 20 min to induce partial (incongruent) melting. The samples were cooled to T2 with a ramp rate of 120 °C h-1 and then slowly cooled to T3 with a cooling rate, R2, and from T3 to T4 with a cooling rate, R3. The tapes were kept at the temperature T4 for P1 hours and then cooled to room temperature. Both R1 and R2 were chosen between 2 and 8 °C h-1. It was found that the structure and Jc of the tapes depend on the sintering conditions, i.e. T1-4, R1-3 and P1. The highest Jc of 5800 Å cm-2 was obtained at 77 K in a self-field with heat treatment where T1 = 894 and 899 °C, R1 = R2 = 5 °C h-1 and P1 = 6 h were employed. When 0.7% of bend strain, which is equivalent to a bend radius of 5 mm, was applied to the tape, 80% of the initial Jc was sustained.