Relative entropy measures applied to healthy and pathological voice characterization

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.

Sensitivity of complex networks measurements

Complex networks obtained from real-world networks are often characterized by incompleteness and noise, consequences of imperfect sampling as well as artifacts in the acquisition process. Because the characterization, analysis and modeling of complex systems underlain by complex networks are critically affected by the quality and completeness of the respective initial structures, it becomes imperative to devise methodologies for identifying and quantifying the effects of the sampling on the network structure. One way to evaluate these effects is through an analysis of the sensitivity of complex network measurements to perturbations in the topology of the network. In this paper, measurement sensibility is quantified in terms of the relative entropy of the respective distributions. Three particularly important kinds of progressive perturbations to the network are considered, namely, edge suppression, addition and rewiring. The measurements allowing the best balance of stability (smaller sensitivity to perturbations) and discriminability (separation between different network topologies) are identified with respect to each type of perturbation. Such an analysis includes eight different measurements applied on six different complex networks models and three real-world networks. This approach allows one to choose the appropriate measurements in order to obtain accurate results for networks where sampling bias cannot be avoided-a very frequent situation in research on complex networks.

Consistency in approximate entropy given by a volumetric estimate

Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.

Gaining ligand selectivity in thyroid hormone receptors via entropy

Nuclear receptors are important targets for pharmaceuticals, but similarities between family members cause difficulties in obtaining highly selective compounds. Synthetic ligands that are selective for thyroid hormone (TH) receptor beta (TR beta) vs. TR alpha reduce cholesterol and fat without effects on heart rate; thus, it is important to understand TR beta-selective binding. Binding of 3 selective ligands (GC-1, KB141, and GC-24) is characterized at the atomic level; preferential binding depends on a nonconserved residue (Asn-331 beta) in the TR beta ligand-binding cavity (LBC), and GC-24 gains extra selectivity from insertion of a bulky side group into an extension of the LBC that only opens up with this ligand. Here we report that the natural TH 3,5,3`-triodothyroacetic acid (Triac) exhibits a previously unrecognized mechanism of TR beta selectivity. TR x-ray structures reveal better fit of ligand with the TR alpha LBC. The TR beta LBC, however, expands relative to TR alpha in the presence of Triac (549 angstrom(3) vs. 461 angstrom(3)), and molecular dynamics simulations reveal that water occupies the extra space. Increased solvation compensates for weaker interactions of ligand with TR beta and permits greater flexibility of the Triac carboxylate group in TR beta than in TR alpha. We propose that this effect results in lower entropic restraint and decreases free energy of interactions between Triac and TR beta, explaining subtype-selective binding. Similar effects could potentially be exploited in nuclear receptor drug design.

Cross-entropy optimizer: a new tool to study precession in astrophysical jets

Evidence of jet precession in many galactic and extragalactic sources has been reported in the literature. Much of this evidence is based on studies of the kinematics of the jet knots, which depends on the correct identification of the components to determine their respective proper motions and position angles on the plane of the sky. Identification problems related to fitting procedures, as well as observations poorly sampled in time, may influence the follow-up of the components in time, which consequently might contribute to a misinterpretation of the data. In order to deal with these limitations, we introduce a very powerful statistical tool to analyse jet precession: the cross-entropy method for continuous multi-extremal optimization. Only based on the raw data of the jet components (right ascension and declination offsets from the core), the cross-entropy method searches for the precession model parameters that better represent the data. In this work we present a large number of tests to validate this technique, using synthetic precessing jets built from a given set of precession parameters. With the aim of recovering these parameters, we applied the cross-entropy method to our precession model, varying exhaustively the quantities associated with the method. Our results have shown that even in the most challenging tests, the cross-entropy method was able to find the correct parameters within a 1 per cent level. Even for a non-precessing jet, our optimization method could point out successfully the lack of precession.

MODELING VERY LONG BASELINE INTERFEROMETRIC IMAGES WITH THE CROSS-ENTROPY GLOBAL OPTIMIZATION TECHNIQUE

We present a new technique for obtaining model fittings to very long baseline interferometric images of astrophysical jets. The method minimizes a performance function proportional to the sum of the squared difference between the model and observed images. The model image is constructed by summing N(s) elliptical Gaussian sources characterized by six parameters: two-dimensional peak position, peak intensity, eccentricity, amplitude, and orientation angle of the major axis. We present results for the fitting of two main benchmark jets: the first constructed from three individual Gaussian sources, the second formed by five Gaussian sources. Both jets were analyzed by our cross-entropy technique in finite and infinite signal-to-noise regimes, the background noise chosen to mimic that found in interferometric radio maps. Those images were constructed to simulate most of the conditions encountered in interferometric images of active galactic nuclei. We show that the cross-entropy technique is capable of recovering the parameters of the sources with a similar accuracy to that obtained from the very traditional Astronomical Image Processing System Package task IMFIT when the image is relatively simple (e. g., few components). For more complex interferometric maps, our method displays superior performance in recovering the parameters of the jet components. Our methodology is also able to show quantitatively the number of individual components present in an image. An additional application of the cross-entropy technique to a real image of a BL Lac object is shown and discussed. Our results indicate that our cross-entropy model-fitting technique must be used in situations involving the analysis of complex emission regions having more than three sources, even though it is substantially slower than current model-fitting tasks (at least 10,000 times slower for a single processor, depending on the number of sources to be optimized). As in the case of any model fitting performed in the image plane, caution is required in analyzing images constructed from a poorly sampled (u, v) plane.

Relative effects of fragment size and connectivity on bird community in the Atlantic Rain Forest: Implications for conservation

It is known that large fragment sizes and high connectivity levels are key components for maintaining species in fragments; however, their relative effects are poorly understood, especially in tropical areas. In order to test these effects, we built models for explaining understory birds occurrence in a fragmented Atlantic Rain Forest landscape with intermediate habitat cover (3%). Data from over 9000 mist-net hours from 17 fragments differing in size (2-175 ha) and connectivity (considering corridor linkages and distance to nearby fragments) were ranked under a model selection approach. A total 1293 individuals of 62 species were recorded. Species richness, abundance and compositional variation were mainly affected by connectivity indices that consider the capacity of species to use corridors and/or to cross short distances up to 30 m through the matrix. Bird functional groups were differently affected by area and connectivity: while terrestrial insectivores, omnivores and frugivores were affected by both area and connectivity, the other groups (understory insectivores, nectarivores, and others) were affected only by connectivity. In the studied landscape, well connected fragments can sustain an elevated number of species and individuals. Connectivity gives the opportunity for individuals to use multiple fragments, reducing the influence of fragment size. While preserving large fragments is a conservation target worldwide and should continue to be, our results indicated that connectivity between fragments can enhance the area functionally connected and is beneficial to all functional groups and therefore should be a conservation priority. (C) 2008 Elsevier Ltd. All rights reserved.

Relative effect of litter quality, forest type and their interaction on leaf decomposition in south-east Brazilian forests

Decomposition was studied in a reciprocal litter transplant experiment to examine the effects of forest type, litter quality and their interaction on leaf decomposition in four tropical forests in south-east Brazil. Litterbags were used to measure decomposition of leaves of one tree species from each forest type: Calophyllum brasiliense from restinga forest; Guapira opposita from Atlantic forest; Esenbeckia leiocarpa from semi-deciduous forest; and Copaifera langsdorffii from cerradao. Decomposition rates in rain forests (Atlantic and restinga) were twice as fast as those in seasonal forests (semi-deciduous and cerradao), suggesting that intensity and distribution of precipitation are important predictors of decomposition rates at regional scales. Decomposition rates varied by species, in the following order: E. leiocarpa > C. langsdorffii > G. opposita > C. brasiliense. However, there was no correlation between decomposition rates and chemical litter quality parameters: C:N, C:P, lignin concentration and lignin:N. The interaction between forest type and litter quality was positive mainly because C. langsdorffii decomposed faster than expected in its native forest. This is a potential indication of a decomposer`s adaptation to specific substrates in a tropical forest. These findings suggest that besides climate, interactions between decomposers and plants might play an essential role in decomposition processes and it must be better understood.

Retinoic Acid and VEGF Delay Smooth Muscle Relative to Endothelial Differentiation to Coordinate Inner and Outer Coronary Vessel Wall Morphogenesis

Rationale: Major coronary vessels derive from the proepicardium, the cellular progenitor of the epicardium, coronary endothelium, and coronary smooth muscle cells (CoSMCs). CoSMCs are delayed in their differentiation relative to coronary endothelial cells (CoEs), such that CoSMCs mature only after CoEs have assembled into tubes. The mechanisms underlying this sequential CoE/CoSMC differentiation are unknown. Retinoic acid (RA) is crucial for vascular development and the main RA-synthesizing enzyme is progressively lost from epicardially derived cells as they differentiate into blood vessel types. In parallel, myocardial vascular endothelial growth factor (VEGF) expression also decreases along coronary vessel muscularization. Objective: We hypothesized that RA and VEGF act coordinately as physiological brakes to CoSMC differentiation. Methods and Results: In vitro assays (proepicardial cultures, cocultures, and RALDH2 [retinaldehyde dehydrogenase-2]/VEGF adenoviral overexpression) and in vivo inhibition of RA synthesis show that RA and VEGF act as repressors of CoSMC differentiation, whereas VEGF biases epicardially derived cell differentiation toward the endothelial phenotype. Conclusion: Experiments support a model in which early high levels of RA and VEGF prevent CoSMC differentiation from epicardially derived cells before RA and VEGF levels decline as an extensive endothelial network is established. We suggest this physiological delay guarantees the formation of a complex, hierarchical, tree of coronary vessels. (Circ Res. 2010;107:204-216.)

Relative contribution of pre- and post-synaptic effects to the neostigmine-induced recovery of neuromuscular transmission blocked by vecuronium

The relative contribution of the pre- and post-synaptic effects to the neostigmine-induced recovery of neuromuscular transmission blocked by vecuronium was studied. A conjunction of myographical and electrophysiological techniques was employed. The preparation was the sciatic nerve-extensor digitorum longus muscle of the rat, in vitro. The physiological variables recorded were nerve-evoked twitches (generated at 0.1 Hz), tetanic contractions (generated at 50 Hz) and end-plate potentials (epps), generated in trains of 50 Hz. The epps were analyzed in: amplitude of first epp in the train; mean amplitude of the 30th to the 59th epp in the train (epps-plateau); half-decay time of the epp; early tetanic rundown of epps in the train; plateau tetanic rundown of epps in the train; quantal content of the epps and quantal size. In myographical experiments, a concentration of vecuronium was found (0.8 mu m) that affected both twitches and tetanic contractions and a concentration of neostigmine was found (0.048 mu m) that completely restored the twitch affected by vecuronium. The cellular effects of vecuronium and neostigmine, studied alone or in association, in the above-mentioned concentrations, were scrutinized by means of electrophysiological techniques. These showed that vecuronium alone decreased the peak amplitude, the quantal content of epps and the quantal size and reinforced the tetanic rundown of epps. Neostigmine alone increased the peak amplitude, the quantal content and the half-decay time of the epps. When employed in the presence of vecuronium, neostigmine increased both the quantal content of the epps (via a presynaptic effect) and the half-decay time of the epps (via a postsynaptic effect). Seeing the pre- and the post-synaptic effects of neostigmine were of similar magnitude, they permit to conclude that both these effects contributed significantly to the restoration by neostigmine of the neuromuscular transmission blocked by vecuronium.

Relative populations and toxin production by Aspergillus flavus and Fusarium verticillioides in artificially inoculated corn at various stages of development under field conditions

The presence, development and production of mycotoxins by Aspergillus flavus and Fusarium verticillioides were studied in corn ears under field conditions after artificial contamination of corn silks. The planted area was divided into five treatments: T1, inoculated with A.flavus solution containing 1 x 10(8) spores, ears covered; T2, inoculated with F. verticillioides solution containing 1 X 10(8) spores, ears covered; T3, inoculated with E verticillioides plus A. flavus solution containing 1 x 10(8) spores of each, ears covered; T4, sprayed with sterile phosphate-buffered saline, ears covered; TS, non-sprayed silks, uncovered ears. Soil and air samples were also collected and analysed for the occurrence of fungi. Water activity, relative air humidity, rainfall and temperature were determined to assess the correlation between abiotic factors and the presence of fungi in the samples. Contamination with the inoculated fungus predominated in T1 and T2. In the other treatments, F. verticillioides was the most frequently isolated contaminant irrespective of treatment. Considering the production of mycotoxins, a positive relation between the production of fumonisins B-1 and B-2 and the frequency of F. verticillioides was statistically verified in all treatments. (C) 2007 Society of Chemical Industry.

Entropy-Based Approach to Analyze and Classify Mineral Aggregates

This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.

Relative roles of biogenic emissions and Saharan dust as ice nuclei in the Amazon basin

Some aerosol particles, known as ice nuclei, can initiate ice formation in clouds, thereby influencing precipitation, cloud dynamics and the amount of incoming and outgoing solar radiation. In the absence of biomass burning, aerosol mass concentrations in the Amazon basin are low(1). Tropical forests emit primary biological particles directly into the atmosphere; secondary organic aerosols form from the emission and oxidation of biogenic gases(2). In addition, particles derived from biomass burning in central Africa, marine aerosols, and windblown dust from North Africa(3-5) often reach the central part of the Amazon basin during the wet season. The contribution of these aerosol sources to ice nucleation in the region is uncertain. Here we present observations of the concentration and elemental composition of ice nuclei in the Amazon basin during the wet season. Using transmission electron microscopy combined with energy-dispersive X-ray spectroscopy, we show that ice nuclei are primarily composed of carbonaceous material and dust. We show that biological particles dominate the carbonaceous fraction, whereas import of Saharan dust explains the intermittent appearance of dust-containing nuclei. We conclude that ice-nucleus concentration and abundance can be explained almost entirely by local emissions of biological particles supplemented by import of Saharan dust. Using a simple model, we tentatively suggest that the contribution of local biological particles to ice nucleation is increased at higher atmospheric temperatures, whereas the contribution of dust particles is increased at lower temperatures.

An analytical relation between entropy production and quantum Lyapunov exponents for Gaussian bipartite systems

We study and compare the information loss of a large class of Gaussian bipartite systems. It includes the usual Caldeira-Leggett-type model as well as Anosov models ( parametric oscillators, the inverted oscillator environment, etc), which exhibit instability, one of the most important characteristics of chaotic systems. We establish a rigorous connection between the quantum Lyapunov exponents and coherence loss, and show that in the case of unstable environments coherence loss is completely determined by the upper quantum Lyapunov exponent, a behavior which is more universal than that of the Caldeira-Leggett-type model.

Structural, electronic, and magnetic entropy contributions of the orbital order-disorder transition in LaMnO(3)

Measurements of X-ray diffraction, electrical resistivity, and magnetization are reported across the Jahn-Teller phase transition in LaMnO(3). Using a thermodynamic equation, we obtained the pressure derivative of the critical temperature (T(JT)), dT(JT)/dP = -28.3 K GPa(-1). This approach also reveals that 5.7(3)J(mol K)(-1) comes from the volume change and 0.8(2)J(mol K)(-1) from the magnetic exchange interaction change across the phase transition. Around T(JT), a robust increase in the electrical conductivity takes place and the electronic entropy change, which is assumed to be negligible for the majority of electronic systems, was found to be 1.8(3)J(mol K)(-1).