A Keck Survey of Gravitational Lens Systems: I. Spectroscopy of SBS 0909+532, HST 1411+5211, and CLASS B2319+051

We present new results from a continuing Keck program to study gravitational lens systems. We have obtained redshifts for three lens systems, SBS 0909+532, HST 1411+5211, and CLASS B2319+051. For all of these systems, either the source or lens redshift (or both) has been previously unidentified. We find (z_l, z_s) = (0.830, 1.377) for SBS 0909+532; (z_l, z_s) = (0.465, 2.811) for HST 1411+5211, although the source redshift is still tentative; and (z_l1, z_l2) = (0.624, 0.588) for the two lensing galaxies in CLASS B2319+051. The background radio source in B2319+051 has not been detected optically; its redshift is, therefore, still unknown. We find that the spectral features of the central lensing galaxy in all three systems are typical of an early-type galaxy. The observed image splittings in SBS 0909+532 and HST 1411+5211 imply that the masses within the Einstein ring radii of the lensing galaxies are 1.4 x 10^{11} and 2.0 x 10^{11} h^{-1} M_sun, respectively. The resulting B band mass-to-light ratio for HST 1411+5211 is 41.3 +/- 1.2 h (M/L)_sun, a factor of 5 times higher than the average early-type lensing galaxy. This large mass-to-light is almost certainly the result of the additional mass contribution from the cluster CL 3C295 at z = 0.46. For the lensing galaxy in SBS 0909+532, we measure (M/L)_B = 4^{+11}_{-3} h (M/L)_sun where the large errors are the result of significant uncertainty in the galaxy luminosity. While we cannot measure directly the mass-to-light ratio of the lensing galaxy in B2319+051, we estimate that (M/L)_B is between 3-7 h (M/L)_sun.Comment: Accepted for publication in Astronomical Journal. 21 pages, including 7 figure

An Imprecise Probability Approach for Abstract Argumentation based on Credal Sets

Some abstract argumentation approaches consider that arguments have a degree of uncertainty, which impacts on the degree of uncertainty of the extensions obtained from a abstract argumentation framework (AAF) under a semantics. In these approaches, both the uncertainty of the arguments and of the extensions are modeled by means of precise probability values. However, in many real life situations the exact probabilities values are unknown and sometimes there is a need for aggregating the probability values of different sources. In this paper, we tackle the problem of calculating the degree of uncertainty of the extensions considering that the probability values of the arguments are imprecise. We use credal sets to model the uncertainty values of arguments and from these credal sets, we calculate the lower and upper bounds of the extensions. We study some properties of the suggested approach and illustrate it with an scenario of decision making.Comment: 8 pages, 2 figures, Accepted in The 15th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2019

Mesoscopic Kondo Effect in an Aharonov-Bohm Ring

An interacting quantum dot inserted in a mesoscopic ring is investigated. A variational ansatz is employed to describe the ground state of the system in the presence of the Aharonov-Bohm flux. It is shown that, for even number of electrons with the energy level spacing smaller than the Kondo temperature, the persistent current has a value similar to that of a perfect ring with the same radius. On the other hand, for a ring with odd number electrons, the persistent current is found to be strongly suppressed compared to that of an ideal ring, which implies the suppression of the Kondo-resonant transmission. Various aspects of the Kondo-assisted persistent current are discussed.Comment: 4 pages Revtex, 4 Postscript figures, final version to appear in Phys. Rev. Lett. 85, No.26 (Dec. 25, 2000

Free Magnetic Moments in Disordered Metals

The screening of magnetic moments in metals, the Kondo effect, is found to be quenched with a finite probability in the presence of nonmagnetic disorder. Numerical results for a disordered electron system show that the distribution of Kondo temperatures deviates strongly from the result expected from random matrix theory. A pronounced second peak emerges for small Kondo temperatures, showing that the probability that magnetic moments remain unscreened at low temperatures increases with disorder. Analytical calculations, taking into account correlations between eigenfunction intensities yield a finite width for the distribution in the thermodynamic limit. Experimental consequences for disordered mesoscopic metals are discussed.Comment: RevTex 4.0, 4.3 pages, 4 EPS figures; typos fixed, reference added, final published versio

The Kondo Box: A Magnetic Impurity in an Ultrasmall Metallic Grain

We study the Kondo effect generated by a single magnetic impurity embedded in an ultrasmall metallic grain, to be called a ``Kondo box''. We find that the Kondo resonance is strongly affected when the mean level spacing in the grain becomes larger than the Kondo temperature, in a way that depends on the parity of the number of electrons on the grain. We show that the single-electron tunneling conductance through such a grain features Kondo-induced Fano-type resonances of measurable size, with an anomalous dependence on temperature and level spacing.Comment: 4 Latex pages, 4 figures, submitted to Phys. Rev. Let

Kondo Resonance in a Mesoscopic Ring Coupled to a Quantum Dot: Exact Results for the Aharonov-Bohm/Casher Effects

We study the persistent currents induced by both the Aharonov-Bohm and Aharonov-Casher effects in a one-dimensional mesoscopic ring coupled to a side-branch quantum dot at Kondo resonance. For privileged values of the Aharonov-Bohm-Casher fluxes, the problem can be mapped onto an integrable model, exactly solvable by a Bethe ansatz. In the case of a pure magnetic Aharonov-Bohm flux, we find that the presence of the quantum dot has no effect on the persistent current. In contrast, the Kondo resonance interferes with the spin-dependent Aharonov-Casher effect to induce a current which, in the strong-coupling limit, is independent of the number of electrons in the ring.Comment: Replaced with published version; 5 page

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

Gene regulation in parthenocarpic tomato fruit

Parthenocarpy is potentially a desirable trait for many commercially grown fruits if undesirable changes to structure, flavour, or nutrition can be avoided. Parthenocarpic transgenic tomato plants (cv MicroTom) were obtained by the regulation of genes for auxin synthesis (iaaM) or responsiveness (rolB) driven by DefH9 or the INNER NO OUTER (INO) promoter from Arabidopsis thaliana. Fruits at a breaker stage were analysed at a transcriptomic and metabolomic level using microarrays, real-time reverse transcription-polymerase chain reaction (RT-PCR) and a Pegasus III TOF (time of flight) mass spectrometer. Although differences were observed in the shape of fully ripe fruits, no clear correlation could be made between the number of seeds, transgene, and fruit size. Expression of auxin synthesis or responsiveness genes by both of these promoters produced seedless parthenocarpic fruits. Eighty-three percent of the genes measured showed no significant differences in expression due to parthenocarpy. The remaining 17% with significant variation (P <0.05) (1748 genes) were studied by assigning a predicted function (when known) based on BLAST to the TAIR database. Among them several genes belong to cell wall, hormone metabolism and response (auxin in particular), and metabolism of sugars and lipids. Up-regulation of lipid transfer proteins and differential expression of several indole-3-acetic acid (IAA)- and ethylene-associated genes were observed in transgenic parthenocarpic fruits. Despite differences in several fatty acids, amino acids, and other metabolites, the fundamental metabolic profile remains unchanged. This work showed that parthenocarpy with ovule-specific alteration of auxin synthesis or response driven by the INO promoter could be effectively applied where such changes are commercially desirable

Functional Connectivity Analyses in Imaging Genetics: Considerations on Methods and Data Interpretation

Functional magnetic resonance imaging (fMRI) can be combined with genotype assessment to identify brain systems that mediate genetic vulnerability to mental disorders (“imaging genetics”). A data analysis approach that is widely applied is “functional connectivity”. In this approach, the temporal correlation between the fMRI signal from a pre-defined brain region (the so-called “seed point”) and other brain voxels is determined. In this technical note, we show how the choice of freely selectable data analysis parameters strongly influences the assessment of the genetic modulation of connectivity features. In our data analysis we exemplarily focus on three methodological parameters: (i) seed voxel selection, (ii) noise reduction algorithms, and (iii) use of additional second level covariates. Our results show that even small variations in the implementation of a functional connectivity analysis can have an impact on the connectivity pattern that is as strong as the potential modulation by genetic allele variants. Some effects of genetic variation can only be found for one specific implementation of the connectivity analysis. A reoccurring difficulty in the field of psychiatric genetics is the non-replication of initially promising findings, partly caused by the small effects of single genes. The replication of imaging genetic results is therefore crucial for the long-term assessment of genetic effects on neural connectivity parameters. For a meaningful comparison of imaging genetics studies however, it is therefore necessary to provide more details on specific methodological parameters (e.g., seed voxel distribution) and to give information how robust effects are across the choice of methodological parameters

Gene network interconnectedness and the generalized topological overlap measure

BACKGROUND: Network methods are increasingly used to represent the interactions of genes and/or proteins. Genes or proteins that are directly linked may have a similar biological function or may be part of the same biological pathway. Since the information on the connection (adjacency) between 2 nodes may be noisy or incomplete, it can be desirable to consider alternative measures of pairwise interconnectedness. Here we study a class of measures that are proportional to the number of neighbors that a pair of nodes share in common. For example, the topological overlap measure by Ravasz et al. [1] can be interpreted as a measure of agreement between the m = 1 step neighborhoods of 2 nodes. Several studies have shown that two proteins having a higher topological overlap are more likely to belong to the same functional class than proteins having a lower topological overlap. Here we address the question whether a measure of topological overlap based on higher-order neighborhoods could give rise to a more robust and sensitive measure of interconnectedness. RESULTS: We generalize the topological overlap measure from m = 1 step neighborhoods to m ≥ 2 step neighborhoods. This allows us to define the m-th order generalized topological overlap measure (GTOM) by (i) counting the number of m-step neighbors that a pair of nodes share and (ii) normalizing it to take a value between 0 and 1. Using theoretical arguments, a yeast co-expression network application, and a fly protein network application, we illustrate the usefulness of the proposed measure for module detection and gene neighborhood analysis. CONCLUSION: Topological overlap can serve as an important filter to counter the effects of spurious or missing connections between network nodes. The m-th order topological overlap measure allows one to trade-off sensitivity versus specificity when it comes to defining pairwise interconnectedness and network modules