Populations III.1 and III.2 gamma-ray bursts: constraints on the event rate for future radio and X-ray surveys

Aims. We calculate the theoretical event rate of gamma-ray bursts (GRBs) from the collapse of massive first-generation (Population III; Pop III) stars. The Pop III GRBs could be super-energetic with the isotropic energy up to E(iso) greater than or similar to 10(55-57) erg, providing a unique probe of the high-redshift Universe. Methods. We consider both the so-called Pop III.1 stars (primordial) and Pop III.2 stars (primordial but affected by radiation from other stars). We employ a semi-analytical approach that considers inhomogeneous hydrogen reionization and chemical evolution of the intergalactic medium. Results. We show that Pop III.2 GRBs occur more than 100 times more frequently than Pop III.1 GRBs, and thus should be suitable targets for future GRB missions. Interestingly, our optimistic model predicts an event rate that is already constrained by the current radio transient searches. We expect similar to 10-10(4) radio afterglows above similar to 0.3 mJy on the sky with similar to 1 year variability and mostly without GRBs (orphans), which are detectable by ALMA, EVLA, LOFAR, and SKA, while we expect to observe maximum of N < 20 GRBs per year integrated over at z > 6 for Pop III.2 and N < 0.08 per year integrated over at z > 10 for Pop III.1 with EXIST, and N < 0.2 for Pop III.2 GRBs per year integrated over at z > 6 with Swift.

Recovery of the star formation history of the LMC from the VISTA survey of the Magellanic system

The VISTA near infrared survey of the Magellanic System (VMC) will provide deep YJK(s) photometry reaching stars in the oldest turn-off point throughout the Magellanic Clouds (MCs). As part of the preparation for the survey, we aim to access the accuracy in the star formation history (SFH) that can be expected from VMC data, in particular for the Large Magellanic Cloud (LMC). To this aim, we first simulate VMC images containing not only the LMC stellar populations but also the foreground Milky Way (MW) stars and background galaxies. The simulations cover the whole range of density of LMC field stars. We then perform aperture photometry over these simulated images, access the expected levels of photometric errors and incompleteness, and apply the classical technique of SFH-recovery based on the reconstruction of colour-magnitude diagrams (CMD) via the minimisation of a chi-squared-like statistics. We verify that the foreground MW stars are accurately recovered by the minimisation algorithms, whereas the background galaxies can be largely eliminated from the CMD analysis due to their particular colours and morphologies. We then evaluate the expected errors in the recovered star formation rate as a function of stellar age, SFR(t), starting from models with a known age-metallicity relation (AMR). It turns out that, for a given sky area, the random errors for ages older than similar to 0.4 Gyr seem to be independent of the crowding. This can be explained by a counterbalancing effect between the loss of stars from a decrease in the completeness and the gain of stars from an increase in the stellar density. For a spatial resolution of similar to 0.1 deg(2), the random errors in SFR(t) will be below 20% for this wide range of ages. On the other hand, due to the lower stellar statistics for stars younger than similar to 0.4 Gyr, the outer LMC regions will require larger areas to achieve the same level of accuracy in the SFR( t). If we consider the AMR as unknown, the SFH-recovery algorithm is able to accurately recover the input AMR, at the price of an increase of random errors in the SFR(t) by a factor of about 2.5. Experiments of SFH-recovery performed for varying distance modulus and reddening indicate that these parameters can be determined with (relative) accuracies of Delta(m-M)(0) similar to 0.02 mag and Delta E(B-V) similar to 0.01 mag, for each individual field over the LMC. The propagation of these errors in the SFR(t) implies systematic errors below 30%. This level of accuracy in the SFR(t) can reveal significant imprints in the dynamical evolution of this unique and nearby stellar system, as well as possible signatures of the past interaction between the MCs and the MW.

Exogenous Cx43 expression decrease cell proliferation rate in rat hepatocarcinoma cells independently of functional gap junction

Background: Gap junction intercellular communication (GJIC) is considered to play a role in the regulation of homeostasis because it regulates important processes, such as cell proliferation and cell differentiation. A reduced or lost GJIC capacity has been observed in solid tumors and studies have demonstrated that GJIC restoration in tumor cells contribute to reversion of the transformed phenotype. This observation supports the idea that restoration of the functional channel is essential in this process. However, in the last years, reports have proposed that just the increase in the expression of specific connexins can contribute to reversion of the malign phenotype in some tumor cells. In the present work, we studied the effects of exogenous Connexin 43 (Cx43) expression on the proliferative behavior and phenotype of rat hepatocarcinoma cells. Results: The exogenous Cx43 did not increase GJIC capacity of transfected cells, but it was critical to decrease the cell proliferation rate as well as reorganization of the actin filaments and cell flattening. We also observed more adhesion capacity to substrate after Cx43 transfection. Conclusion: Cx43 expression leads to a decrease of the growth of the rat hepatocellular carcinoma cells and it contributes to the reversion of the transformed phenotype. These effects were independent of the GJIC and were probably associated with the phosphorylation pattern changes and redistribution of the Cx43 protein.

Electron dephasing scattering rate in two-dimensional GaAs/InGaAs heterostructures with embedded InAs quantum dots

We report a comprehensive study of weak-localization and electron-electron interaction effects in a GaAs/InGaAs two-dimensional electron system with nearby InAs quantum dots, using measurements of the electrical conductivity with and without magnetic field. Although both the effects introduce temperature dependent corrections to the zero magnetic field conductivity at low temperatures, the magnetic field dependence of conductivity is dominated by the weak-localization correction. We observed that the electron dephasing scattering rate tau(-1)(phi), obtained from the magnetoconductivity data, is enhanced by introducing quantum dots in the structure, as expected, and obeys a linear dependence on the temperature and elastic mean free path, which is against the Fermi-liquid model. (c) 2008 American Institute of Physics. [DOI: 10.1063/1.2996034]

Anomalous dephasing scattering rate of two-dimensional electrons in double quantum well structures

The results on the measurement of electrical conductivity and magnetoconductivity of a GaAs double quantum well between 0.5 and 1.1 K are reported. The zero magnetic-field conductivity is well described from the point of view of contributions made by both the weak localization and electron-electron interaction. At low field and low temperature, the magnetoconductivity is dominated by the weak localization effect only. Using the weak localization method, we have determined the electron dephasing times tau(phi) and tunneling times tau(t). Concerning tunneling, we concluded that tau(t) presents a minimum around the balance point; concerning dephasing, we observed an anomalous dependence on temperature and conductivity (or elastic mean free path) of tau(phi). This anomalous behavior cannot be explained in terms of the prevailing concepts for the electron-electron interaction in high-mobility two-dimensional electron systems.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

DISTRIBUTION OF CAPYBARAS IN AN AGROECOSYSTEM, SOUTHEASTERN BRAZIL, BASED ON ECOLOGICAL NICHE MODELING

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most Occurrences of capybaras were in flat areas with water bodies Surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3-3.4%), but higher commission error (91.0-98.5%); these ""model failures"" seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

A new monitor for routine thermal and epithermal neutron fluence rate monitoring in k(0) INAA

The Zr-Au set for monitoring the thermal and epithermal neutron fluence rate and the epithermal spectrum parameter a is not always practicable for routine application of INAA in well-thermalized facilities. An alternative set consisting of Cr, Au and Mo provides values for the thermal neutron fluence rate, f and alpha that are not significantly different from those found via the Zr-Au method and the Cd-covered Zr-method. The IRMM standard SMELS-II was analyzed using the (Au-Cr-Mo) monitor and a good agreement was obtained. (C) 2008 Elsevier Ltd. All rights reserved.

Sequential injections as an alternative to gradient exploitation for implementing differential kinetic analysis in a flow injection system

A novel flow-based strategy for implementing simultaneous determinations of different chemical species reacting with the same reagent(s) at different rates is proposed and applied to the spectrophotometric catalytic determination of iron and vanadium in Fe-V alloys. The method relies on the influence of Fe(II) and V(IV) on the rate of the iodide oxidation by Cr(VI) under acidic conditions, the Jones reducing agent is then needed Three different plugs of the sample are sequentially inserted into an acidic KI reagent carrier stream, and a confluent Cr(VI) solution is added downstream Overlap between the inserted plugs leads to a complex sample zone with several regions of maximal and minimal absorbance values. Measurements performed on these regions reveal the different degrees of reaction development and tend to be more precise Data are treated by multivariate calibration involving the PLS algorithm The proposed system is very simple and rugged Two latent variables carried out ca 95% of the analytical information and the results are in agreement with ICP-OES. (C) 2010 Elsevier B V. All rights reserved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

Exercise training associated with diet improves heart rate recovery and cardiac autonomic nervous system activity in obese children

The purpose of this study was to test the hypotheses that in obese children: 1) hypocaloric diet (D) improves both heart rate recovery at 1 min (Delta HRR1) cfter an exercise test, and cardiac autonomic nervous system activity (CANSA) in obese children; 2) Diet and exercise training (DET) combined leads to greater improvement in both Delta HRR1 after an exercise test and in CANSA, than D alone. Moreover, we examined the relationships among Delta HRR1, CANSA, cardiorespiratory fitness and anthropometric variables (AV) in obese children submitted to D and to DET. 33 obese children (10 +/- 0.2 years; body mass index (BMI) >95(th) percentile) were divided into 2 groups: D (n = 15; BMI = 31 +/- 1 kg/m(2)) and DET (n = 18; 29 +/- 1 kg/m(2)). All children performed a maximal cardiopulmonary exercise test on a treadmill. The Delta HRR1 was defined as the difference between heart rate at peak and at 1-min post-exercise. CANSA was assessed using power spectral analysis of heart rate variability at rest. The sympathovagal balance (low frequency and high frequency ratio, LF/HF) was measured. After interventions, all obese children showed reduced body weight (P < 0.05). The D group did not improve in terms of peak VO(2), Delta HRR1 or LF/HF ratio (P > 0.05). In contrast, the DET group showed increased peak VO(2) (P = 0.01) and improved Delta HRR1 (Delta HRR1 = 37.3 +/- 2.6; P = 0.01) and LF/HF ratio (P = 0.001). The DET group demonstrated significant relationships among Delta HRR1, peak VO(2) and CANSA (P < 0.05). In conclusion, DET, in contrast to D, promoted improved Delta HRR1 and CANSA in obese children, suggesting a positive influence of increased levels of cardiorespiratory fitness by exercise training on cardiac autonomic activity.

Influence of high- and low-carbohydrate diet following glycogen-depleting exercise on heart rate variability and plasma catecholamines

The purpose of this study was to investigate the effects of a short-term low-or high-carbohydrate (CHO) diet consumed after exercise on sympathetic nervous system activity. Twelve healthy males underwent a progressive incremental test; a control measurement of plasma catecholamines and heart rate variability (HRV); an exercise protocol to reduce endogenous CHO stores; a low-or high-CHO diet (counterbalanced order) consumed for 2 days, beginning immediately after the exercise protocol; and a second resting plasma catecholamine and HRV measurement. The exercise and diet protocols and the second round of measurements were performed again after a 1-week washout period. The mean (+/- SD) values of the standard deviation of R-R intervals were similar between conditions (control, 899.0 +/- 146.1 ms; low-CHO diet, 876.8 +/- 115.8 ms; and high-CHO diet, 878.7 +/- 127.7 ms). The absolute high-and low-frequency (HF and LF, respectively) densities of the HRV power spectrum were also not different between conditions. However, normalized HF and LF (i.e., relative to the total power spectrum) were lower and higher, respectively, in the low-CHO diet than in the control diet (mean +/- SD, 17 +/- 9 normalized units (NU) and 83 +/- 9 NU vs. 27 +/- 11 NU and 73 +/- 17 NU, respectively; p < 0.05). The LF/HF ratio was higher with the low-CHO diet than with the control diet (mean +/- SD, 7.2 +/- 6.2 and 4.2 +/- 3.2, respectively; p < 0.05). The mean values of plasma catecholamines were not different between diets. These results suggest that the autonomic control of the heart rate was modified after a short-term low-CHO diet, but plasma catecholamine levels were not altered.

Peak torque and rate of torque development in elderly with and without fall history

Background Falls are one of the greatest concerns among the elderly A number of studies have described peak torque as one of the best fall-related predictor. No studies have comprehensively focused on the rate of torque development of the lower limb muscles among elderly fallers. Then, the aim of this study was to determine the relationship between muscle peak torque and rate of torque development of the lower limb joints in elderly with and without fall history It was also aimed to determine whether these parameters of muscle performance (i e, peak torque and rate of torque development) are related to the number of falls. Methods: Thirty-one women volunteered to participate in the study and were assigned in one of the groups according to the number of falls over the 12 months that preceded the present Then, participants with no fall history (Cl; n = 13; 67.6[7.5] years-old), one fall (GII; n = 8, 66 0[4 91 years-old) and two or more falls (GIII, n = 10; 67.8[8.8] years-old) performed a number of lower limb maximal isometric voluntary contractions from which peak torque and rate of torque development were quantified Findings. Primary outcomes indicated no peak torque differences between experimental groups in any lower limb joint. The rate of torque development of the knee flexor muscles observed in the non-fallers (Cl) was greater than that observed in the fallers (P < 0.05) and had a significant relationship with the number of falls (P < 0 05) Interpretation. The greater knee flexor muscles` rate of torque development found in the non-fallers in comparison to the fallers indicated that the ability of the elderly to rapidly reorganise the arrangement of the lower limb may play a significant role in allowing the elderly to recover balance after a trip. Thus, training stimulus aimed to improve the rate of torque development may be more beneficial to prevent falls among the elderly than other training stimulus, which are not specifically designed to improve the ability to rapidly produce large amounts of torque (C) 2010 Published by Elsevier Ltd

Resting Heart Rate is Associated with Blood Pressure in Male Children and Adolescents

Objectives To analyze the association between resting heart rate and blood pressure in male children and adolescents and to identify if this association is mediated by important confounders. Study design Cross-sectional study carried out with 356 male children and adolescents from 8 to 18 years old. Resting heart rate was measured by a portable heart rate monitor according to recommendations and stratified into quartiles. Blood pressure was measured with an electronic device previously validated for pediatric populations. Body fatness was estimated by a dual-energy x-ray absorptiometry. Results Obese subjects had values of resting heart rate 7.8% higher than nonobese (P = .001). Hypertensive children and adolescents also had elevated values of resting heart rate (P = .001). When the sample was stratified in nonobese and obese, the higher quartile of resting heart rate was associated with hypertension in both groups of children and adolescents. Conclusions This study confirms the existence of a relationship between elevated resting heart rate and increased blood pressure in a pediatric population, independent of adiposity, ethnicity and age. (J Pediatr 2011; 158:634-7).