Hyperbolic-like estimates for higher order equations

The main goal of this paper is to derive long time estimates of the energy for the higher order hyperbolic equations with time-dependent coefficients. in particular, we estimate the energy in the hyperbolic zone of the extended phase space by means of a function f (t) which depends on the principal part and on the coefficients of the terms of order m - 1. Then we look for sufficient conditions that guarantee the same energy estimate from above in all the extended phase space. We call this class of estimates hyperbolic-like since the energy behavior is deeply depending on the hyperbolic structure of the equation. In some cases, these estimates produce a dissipative effect on the energy. (C) 2012 Elsevier Inc. All rights reserved.

Social cliques in male northern muriquis Brachyteles hypoxanthus

Analyses of spatial relationships and social interactions provide insights into the social structure of animal societies and the ways in which social preferences among and between dyads affect higher order social relationships. In this paper we describe the patterns of spatial associations and social interactions among adult male northern muriquis in order to evaluate the dynamics of their social networks above the dyadic levels. Systematic observations were made on the 17 adult males present in a multi-male/multi-female group from April 2004 through February 2005, and in July 2005. Analyses of their spatial relationships identified two distinct male cliques; some adult males (called "N" males) were more connected to the females and immatures than other adult males ("MU" males), which were more connected to one another. Affiliative interactions were significantly higher among dyads belonging to the same clique than to different cliques. Although frequencies of dyadic agonistic interactions were similarly low among individuals within and between cliques, MU males appeared to be subordinate to N males. Nonetheless, there were no significant differences in the copulation rates estimated for MU males and N males. Mutual benefits of cooperation between MU and N cliques in intergroup encounters might explain their ongoing associations in the same mixed-sex group [Current Zoology 58 (2): 342-352, 2012].

Within-plant isoprene oxidation confirmed by direct emissions of oxidation products methyl vinyl ketone and methacrolein

Isoprene is emitted from many terrestrial plants at high rates, accounting for an estimated 1/3 of annual global volatile organic compound emissions from all anthropogenic and biogenic sources combined. Through rapid photooxidation reactions in the atmosphere, isoprene is converted to a variety of oxidized hydrocarbons, providing higher order reactants for the production of organic nitrates and tropospheric ozone, reducing the availability of oxidants for the breakdown of radiatively active trace gases such as methane, and potentially producing hygroscopic particles that act as effective cloud condensation nuclei. However, the functional basis for plant production of isoprene remains elusive. It has been hypothesized that in the cell isoprene mitigates oxidative damage during the stress-induced accumulation of reactive oxygen species (ROS), but the products of isoprene-ROS reactions in plants have not been detected. Using pyruvate-2-13C leaf and branch feeding and individual branch and whole mesocosm flux studies, we present evidence that isoprene (i) is oxidized to methyl vinyl ketone and methacrolein (iox) in leaves and that iox/i emission ratios increase with temperature, possibly due to an increase in ROS production under high temperature and light stress. In a primary rainforest in Amazonia, we inferred significant in plant isoprene oxidation (despite the strong masking effect of simultaneous atmospheric oxidation), from its influence on the vertical distribution of iox uptake fluxes, which were shifted to low isoprene emitting regions of the canopy. These observations suggest that carbon investment in isoprene production is larger than that inferred from emissions alone and that models of tropospheric chemistry and biotachemistryclimate interactions should incorporate isoprene oxidation within both the biosphere and the atmosphere with potential implications for better understanding both the oxidizing power of the troposphere and forest response to climate change.

Gender-based violence and socioeconomic inequalities: Does living in more deprived neighbourhoods increase women's risk of intimate partner violence?

This study investigates the influence of neighbourhood socioeconomic conditions on women's likelihood of experiencing intimate partner violence (IPV) in Sao Paulo, Brazil. Data from 940 women who were interviewed as part of the WHO multi-country study on women's health and domestic violence against women, and census data for Sao Paulo City, were analyzed using multilevel regression techniques. A neighbourhood socioeconomic-level scale was created, and proxies for the socioeconomic positions of the couple were included. Other individual level variables included factors related to partner's behaviour and women's experiences and attitudes. Women's risk of IPV did not vary across neighbourhoods in Sao Paulo nor was it influenced by her individual socioeconomic characteristics. However, women in the middle range of the socioeconomic scale were significantly more likely to report having experienced violence by a partner. Partner behaviours such as excessive alcohol use, controlling behaviour and multiple sexual partnerships were important predictors of IPV. A women's likelihood of IPV also increased if either her mother had experienced IPV or if she used alcohol excessively. These findings suggest that although the characteristics of people living in deprived neighbourhoods may influence the probability that a woman will experience IPV, higher-order contextual dynamics do not seem to affect this risk. While poverty reduction will improve the lives of individuals in many ways, strategies to reduce IPV should prioritize shifting norms that reinforce certain negative male behaviours. (C) 2012 Elsevier Ltd. All rights reserved.

Corneal wavefront-guided photorefractive keratectomy with mitomycin-C for hyperopia after radial keratotomy: Two-year follow-up

PURPOSE: To assess corneal wavefront-guided photorefractive keratectomy (PRK) to correct hyperopia after radial keratotomy (RK). SETTING: Sadalla Amin Ghanem Eye Hospital, Joinville, Santa Catarina, Brazil. DESIGN: Case series. METHODS: Excimer laser corneal wavefront-guided PRK with intraoperative mitomycin-C (MMC) 0.02% was performed. Main outcome measures were uncorrected (UDVA) and corrected (CDVA) distance visual acuities, spherical equivalent (SE), corneal aberrations, and haze. RESULTS: The mean time between RK and PRK in the 61 eyes (39 patients) was 18.8 years +/- 3.8 (SD). Before PRK, the mean SE was +4.17 +/- 1.97 diopters (D); the mean astigmatism, -1.39 +/- 1.04 D; and the mean CDVA, 0.161 +/- 0.137 logMAR. At 24 months, the mean values were 0.14 +/- 0.99 D (P<.001), -1.19 +/- 1.02 D (P=.627), and 0.072 +/- 0.094 logMAR (P<.001), respectively; the mean UDVA was 0.265 +/- 0.196 (P<.001). The UDVA was 20/25 or better in 37.7% of eyes and 20/40 or better in 68.9%. The CDVA improved by 1 or more lines in 62.3% of eyes. Two eyes (3.3%) lost 2 or more lines, 1 due to corneal ectasia. Thirty eyes (49.2%) were within +/- 0.50 D of intended SE and 45 (73.8%) were within +/- 1.00 D. From 6 to 24 months, the mean SE regression was +0.39 D (P<.05). A significant decrease in coma, trefoil, and spherical aberration occurred. Three eyes developed peripheral haze more than grade 1. CONCLUSION: Corneal wavefront-guided PRK with MMC for hyperopia after RK significantly improved UDVA, CDVA, and higher-order corneal aberrations with a low incidence of visually significant corneal haze.

Parametric resonances in a base-excited double pendulum

Two parametrically-induced phenomena are addressed in the context of a double pendulum subject to a vertical base excitation. First, the parametric resonances that cause the stable downward vertical equilibrium to bifurcate into large-amplitude periodic solutions are investigated extensively. Then the stabilization of the unstable upward equilibrium states through the parametric action of the high-frequency base motion is documented in the experiments and in the simulations. It is shown that there is a region in the plane of the excitation frequency and amplitude where all four unstable equilibrium states can be stabilized simultaneously in the double pendulum. The parametric resonances of the two modes of the base-excited double pendulum are studied both theoretically and experimentally. The transition curves (i.e., boundaries of the dynamic instability regions) are constructed asymptotically via the method of multiple scales including higher-order effects. The bifurcations characterizing the transitions from the trivial equilibrium to the periodic solutions are computed by either continuation methods and or by time integration and compared with the theoretical and experimental results.

The nuclear electric quadrupole moment of hafnium from the molecular method

The molecular method is used to obtain nuclear electric quadrupole moment (NQM) values for hafnium through electric field gradients (EFGs) at this nucleus in HfO and HfS. Dirac-Coulomb calculations with the Coupled Cluster approach, DC-CCSD (T) and DC-CCSD-T, were carried out to achieve the most accurate estimates of these EFGs. Higher order corrections are also added. Hence, the most reliable values for 177Hf and 179Hf determined here are 3319(33) and 3750(37) mbarn, respectively, in nice accordance with the best currently accepted NQMs for this element. (C) 2012 Elsevier B.V. All rights reserved.

Alteration of distortion product otoacoustic emission input/output functions in subjects with a previous history of middle ear dysfunction

Background: The aim of this study was to investigate the effects of sub-clinical alterations on the amplitudes and slopes of the DPOAE input-output responses from subjects with previous history of middle ear dysfunction. Material/Methods: The study included 15 subjects with and 15 subjects without a history of otitis media in the last 10 years. All participants were assessed with acoustic immittance, pure-tone audiometry, and DPOAEs. For the later, I/O functions and I/O slopes were estimated at 1501, 2002, 3174, 4004 and 6384Hz. Results: No statistically significant differences were found between the 2 groups in terms of behavioral thresholds. The group with a previous history of middle ear dysfunction presented significantly lower mean DPOAE amplitudes at 2002, 3174 and 4004 Hz. In terms of DPOAE slopes, no statistically significant differences were observed at the tested frequencies, except at 3174 Hz. Conclusions: Middle ear pathologies can produce subclinical alterations that are undetectable with traditional pure-tone audiometry. The data from the present study show that reduced amplitude DPOAEs are associated with a previous history of middle ear complications. The corresponding DPOAE slopes were affected at only 1 tested frequency, suggesting that the cochlear non-linearity is preserved. Considering these results, it remains to be elucidated to what degree the DPOAE amplitude attenuation interferes with higher-order auditory tasks.

Microstructural characterization of as-cast hf-b alloys

An accurate knowledge of several metal-boron phase diagrams is important to evaluation of higher order systems such as metal-silicon-boron ternaries. The refinement and reassessment of phase diagram data is a continuous work, thus the reevaluation of metal-boron systems provides the possibility to confirm previous data from an investigation using higher purity materials and better analytical techniques. This work presents results of rigorous microstructural characterization of as-cast hafnium-boron alloys which are significant to assess the liquid composition associated to most of the invariant reactions of this system. Alloys were prepared by arc melting high purity hafnium (minimum 99.8%) and boron (minimum 99.5%) slices under argon atmosphere in water-cooled copper crucible with non consumable tungsten electrode and titanium getter. The phases were identified by scanning electron microscopy, using back-scattered electron image mode and X-ray diffraction. In general, a good agreement was found between our data and those from the currently accepted Hafnium-Boron phase diagram. The phases identified are αHfSS and B-RhomSS, the intermediate compounds HfB and HfB2 and the liquide L. The reactions are the eutectic L ⇔ αHfSS + HfB and L ⇔ HfB2 + B-Rhom, the peritectic L + HfB2 ⇔ HfB and the congruent formation of HfB2.

Design methodology of piezoelectric energy-harvesting skin using topology optimization

Abstract This paper describes a design methodology for piezoelectric energy harvester s that thinly encapsulate the mechanical devices and expl oit resonances from higher- order vibrational modes. The direction of polarization determines the sign of the pi ezoelectric tensor to avoid cancellations of electric fields from opposite polarizations in the same circuit. The resultant modified equations of state are solved by finite element method (FEM). Com- bining this method with the solid isotropic material with penalization (SIMP) method for piezoelectric material, we have developed an optimization methodology that optimizes the piezoelectric material layout and polarization direc- tion. Updating the density function of the SIMP method is performed based on sensitivity analysis, the sequen- tial linear programming on the early stage of the opti- mization, and the phase field method on the latter stage

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Word sense disambiguation via high order of learning in complex networks

Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.