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.

Experimental studies of di-jet survival and surface emission bias in Au plus Au collisions via angular correlations with respect to back-to-back leading hadrons

We report first results from an analysis based on a new multi-hadron correlation technique, exploring jet-medium interactions and di-jet surface emission bias at the BNL Relativistic Heavy Ion Collider (RHIC). Pairs of back-to-back high-transverse-momentum hadrons are used for triggers to study associated hadron distributions. In contrast with two-and three-particle correlations with a single trigger with similar kinematic selections, the associated hadron distribution of both trigger sides reveals no modification in either relative pseudorapidity Delta eta or relative azimuthal angle Delta phi from d + Au to central Au + Au collisions. We determine associated hadron yields and spectra as well as production rates for such correlated back-to-back triggers to gain additional insights on medium properties.

K*(0) production in Cu plus Cu and Au plus Au collisions at root s(NN)=62.4 GeV and 200 GeV

We report on K*(0) production at midrapidity in Au + Au and Cu + Cu collisions at root s(NN) = 62.4 and 200 GeV collected by the Solenoid Tracker at the Relativistic Heavy Ion Collider detector. The K*(0) is reconstructed via the hadronic decays K*(0) -> K(+)pi(-) and (K*(0)) over bar -> K(+)pi(-). Transverse momentum, p(T), spectra are measured over a range of p(T) extending from 0.2 GeV/c up to 5 GeV/c. The center-of-mass energy and system size dependence of the rapidity density, dN/dy, and the average transverse momentum, < p(T)>, are presented. The measured N(K*(0))/N(K) and N(phi)/N(K*(0)) ratios favor the dominance of rescattering of decay daughters of K*(0) over the hadronic regeneration for the K*(0) production. In the intermediate p(T) region (2.0 < p(T) < 4.0 GeV/c), the elliptic flow parameter, v(2), and the nuclear modification factor, R(CP), agree with the expectations from the quark coalescence model of particle production.

Azimuthal di-hadron correlations in d plus Au and Au plus Au collisions at root s(NN)=200 GeV measured at the STAR detector

Yields, correlation shapes, and mean transverse momenta p(T) of charged particles associated with intermediate-to high-p(T) trigger particles (2.5 < p(T) < 10 GeV/c) in d + Au and Au + Au collisions at root s(NN) = 200 GeV are presented. For associated particles at higher p(T) greater than or similar to 2.5 GeV/c, narrow correlation peaks are seen in d + Au and Au + Au, indicating that the main production mechanism is jet fragmentation. At lower associated particle pT < 2 GeV/c, a large enhancement of the near- (Delta phi similar to 0) and away-side (Delta phi similar to pi) associated yields is found, together with a strong broadening of the away-side azimuthal distributions in Au + Au collisions compared to d + Au measurements, suggesting that other particle production mechanisms play a role. This is further supported by the observed significant softening of the away-side associated particle yield distribution at Delta phi similar to pi in central Au + Au collisions.

Balance functions from Au+Au, d+Au, and p+p collisions at root s(NN)=200 GeV

Balance functions have been measured for charged-particle pairs, identified charged-pion pairs, and identified charged-kaon pairs in Au + Au, d + Au, and p + p collisions at root s(NN) = 200 GeV at the Relativistic Heavy Ion Collider using the STAR detector. These balance functions are presented in terms of relative pseudorapidity, Delta eta, relative rapidity, Delta y, relative azimuthal angle, Delta phi, and invariant relative momentum, q(inv). For charged-particle pairs, the width of the balance function in terms of Delta eta scales smoothly with the number of participating nucleons, while HIJING and UrQMD model calculations show no dependence on centrality or system size. For charged-particle and charged-pion pairs, the balance functions widths in terms of Delta eta and Delta y are narrower in central Au + Au collisions than in peripheral collisions. The width for central collisions is consistent with thermal blast-wave models where the balancing charges are highly correlated in coordinate space at breakup. This strong correlation might be explained by either delayed hadronization or limited diffusion during the reaction. Furthermore, the narrowing trend is consistent with the lower kinetic temperatures inherent to more central collisions. In contrast, the width of the balance function for charged-kaon pairs in terms of Delta y shows little centrality dependence, which may signal a different production mechanism for kaons. The widths of the balance functions for charged pions and kaons in terms of q(inv) narrow in central collisions compared to peripheral collisions, which may be driven by the change in the kinetic temperature.

Three-Particle Coincidence of the Long Range Pseudorapidity Correlation in High Energy Nucleus-Nucleus Collisions

We report the first three-particle coincidence measurement in pseudorapidity (Delta eta) between a high transverse momentum (p(perpendicular to)) trigger particle and two lower p(perpendicular to) associated particles within azimuth |Delta phi| < 0.7 in root s(NN) = 200 GeV d + Au and Au + Au collisions. Charge ordering properties are exploited to separate the jetlike component and the ridge (long range Delta eta correlation). The results indicate that the correlation of ridge particles are uniform not only with respect to the trigger particle but also between themselves event by event in our measured Delta eta. In addition, the production of the ridge appears to be uncorrelated to the presence of the narrow jetlike component.

Charged and strange hadron elliptic flow in Cu plus Cu collisions at root s(NN)=62.4 and 200 GeV

We present the results of an elliptic flow, v(2), analysis of Cu + Cu collisions recorded with the solenoidal tracker detector (STAR) at the BNL Relativistic Heavy Ion Collider at root s(NN) = 62.4 and 200 GeV. Elliptic flow as a function of transverse momentum, v(2)(p(T)), is reported for different collision centralities for charged hadrons h(+/-) and strangeness-ontaining hadrons K(S)(0), Lambda, Xi, and phi in the midrapidity region vertical bar eta vertical bar < 1.0. Significant reduction in systematic uncertainty of the measurement due to nonflow effects has been achieved by correlating particles at midrapidity, vertical bar eta vertical bar < 1.0, with those at forward rapidity, 2.5 < vertical bar eta vertical bar < 4.0. We also present azimuthal correlations in p + p collisions at root s = 200 GeV to help in estimating nonflow effects. To study the system-size dependence of elliptic flow, we present a detailed comparison with previously published results from Au + Au collisions at root s(NN) = 200 GeV. We observe that v(2)(p(T)) of strange hadrons has similar scaling properties as were first observed in Au + Au collisions, that is, (i) at low transverse momenta, p(T) < 2 GeV/c, v(2) scales with transverse kinetic energy, m(T) - m, and (ii) at intermediate p(T), 2 < p(T) < 4 GeV/c, it scales with the number of constituent quarks, n(q.) We have found that ideal hydrodynamic calculations fail to reproduce the centrality dependence of v(2)(p(T)) for K(S)(0) and Lambda. Eccentricity scaled v(2) values, v(2)/epsilon, are larger in more central collisions, suggesting stronger collective flow develops in more central collisions. The comparison with Au + Au collisions, which go further in density, shows that v(2)/epsilon depends on the system size, that is, the number of participants N(part). This indicates that the ideal hydrodynamic limit is not reached in Cu + Cu collisions, presumably because the assumption of thermalization is not attained.

Long range rapidity correlations and jet production in high energy nuclear collisions

The STAR Collaboration at the Relativistic Heavy Ion Collider presents a systematic study of high-transverse-momentum charged-di-hadron correlations at small azimuthal pair separation Delta phi in d+Au and central Au+Au collisions at s(NN)=200 GeV. Significant correlated yield for pairs with large longitudinal separation Delta eta is observed in central Au+Au collisions, in contrast to d+Au collisions. The associated yield distribution in Delta eta x Delta phi can be decomposed into a narrow jet-like peak at small angular separation which has a similar shape to that found in d+Au collisions, and a component that is narrow in Delta phi and depends only weakly on Delta eta, the ""ridge."" Using two systematically independent determinations of the background normalization and shape, finite ridge yield is found to persist for trigger p(t)>6 GeV/c, indicating that it is correlated with jet production. The transverse-momentum spectrum of hadrons comprising the ridge is found to be similar to that of bulk particle production in the measured range (2 < p(t)< 4 GeV/c).

Passage of radiation through wormholes of arbitrary shape

We study quasinormal modes and scattering properties via calculation of the S matrix for scalar and electromagnetic fields propagating in the background of spherically symmetric and axially symmetric traversable Lorentzian wormholes of a generic shape. Such wormholes are described by the general Morris-Thorne ansatz. The properties of quasinormal ringing and scattering are shown to be determined by the behavior of the wormhole's shape function b(r) and shift factor Phi(r) near the throat. In particular, wormholes with the shape function b(r), such that b(dr) approximate to 1, have very long-lived quasinormal modes in the spectrum. We have proved that the axially symmetric traversable Lorentzian wormholes, unlike black holes and other compact rotating objects, do not allow for superradiance. As a by-product we have shown that the 6th order WKB formula used for scattering problems of black or wormholes gives quite high accuracy and thus can be used for quite accurate calculations of the Hawking radiation processes around various black holes.

Anisotropic singularities in modified gravity models

We show that the common singularities present in generic modified gravity models governed by actions of the type S = integral d(4)x root-gf(R, phi, X). with X = -1/2 g(ab)partial derivative(a)phi partial derivative(b)phi, are essentially the same anisotropic instabilities associated to the hypersurface F(phi) = 0 in the case of a nonminimal coupling of the type F(phi)R, enlightening the physical origin of such singularities that typically arise in rather complex and cumbersome inhomogeneous perturbation analyses. We show, moreover, that such anisotropic instabilities typically give rise to dynamically unavoidable singularities, precluding completely the possibility of having physically viable models for which the hypersurface partial derivative f/partial derivative R = 0 is attained. Some examples are explicitly discussed.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Lossless filter for multiple repeats with bounded edit distance

Background: Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results: The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion: To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

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.