Mixing and non-mixing local minima of the entropy contrast for blind source separation

In this paper, both non-mixing and mixing local minima of the entropy are analyzed from the viewpoint of blind source separation (BSS); they correspond respectively to acceptable and spurious solutions of the BSS problem. The contribution of this work is twofold. First, a Taylor development is used to show that the \textit{exact} output entropy cost function has a non-mixing minimum when this output is proportional to \textit{any} of the non-Gaussian sources, and not only when the output is proportional to the lowest entropic source. Second, in order to prove that mixing entropy minima exist when the source densities are strongly multimodal, an entropy approximator is proposed. The latter has the major advantage that an error bound can be provided. Even if this approximator (and the associated bound) is used here in the BSS context, it can be applied for estimating the entropy of any random variable with multimodal density.Comment: 11 pages, 6 figures, To appear in IEEE Transactions on Information Theor

Low-Energy Properties of a One-dimensional System of Interacting bosons with Boundaries

The ground state properties and low-lying excitations of a (quasi) one-dimensional system of longitudinally confined interacting bosons are studied. This is achieved by extending Haldane's harmonic-fluid description to open boundary conditions. The boson density, one-particle density matrix, and momentum distribution are obtained accounting for finite-size and boundary effects. Friedel oscillations are found in the density. Finite-size scaling of the momentum distribution at zero momentum is proposed as a method to obtain from the experiment the exponent that governs phase correlations. The strong correlations between bosons induced by reduced dimensionality and interactions are displayed by a Bijl-Jastrow wave function for the ground state, which is also derived.Comment: Final published version. Minor changes with respect to the previous versio

Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach

Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identifying the key factors of a biological network that are essential in determining the cell's fate. Here our goal is the identification of perturbed pathways from high-throughput gene expression data. We develop a three-level hierarchical model, where (i) the first level captures the relationship between gene expression and biological pathways using confirmatory factor analysis, (ii) the second level models the behavior within an underlying network of pathways induced by an unknown perturbation using a conditional autoregressive model, and (iii) the third level is a spike-and-slab prior on the perturbations. We then identify perturbations through posterior-based variable selection. We illustrate our approach using gene transcription drug perturbation profiles from the DREAM7 drug sensitivity predication challenge data set. Our proposed method identified regulatory pathways that are known to play a causative role and that were not readily resolved using gene set enrichment analysis or exploratory factor models. Simulation results are presented assessing the performance of this model relative to a network-free variant and its robustness to inaccuracies in biological databases

Distinct subpopulations of enteric neuronal progenitors defined by time of development, sympathoadrenal lineage markers and Mash-1-dependence

Enteric and sympathetic neurons have previously been proposed to be lineally related. We present independent lines of evidence that suggest that enteric neurons arise from at least two lineages, only one of which expresses markers in common with sympathoadrenal cells. In the rat, sympathoadrenal markers are expressed, in the same order as in sympathetic neurons, by a subset of enteric neuronal precursors, which also transiently express tyrosine hydroxylase. If this precursor pool is eliminated in vitro by complement-mediated lysis, enteric neurons continue to develop; however, none of these are serotonergic. In the mouse, the Mash-1−/− mutation, which eliminates sympathetic neurons, also prevents the development of enteric serotonergic neurons. Other enteric neuronal populations, however, including those that contain calcitonin gene related peptide are present. Enteric tyrosine hydroxylase-containing cells co-express Mash-1 and are eliminated by the Mash-1−/− mutation, consistent with the idea that in the mouse, as in the rat, these precursors generate serotonergic neurons. Serotonergic neurons are generated early in development, while calcitonin gene related peptide-containing enteric neurons are generated much later. These data suggest that enteric neurons are derived from at least two progenitor lineages. One transiently expresses sympathoadrenal markers, is Mash-1-dependent, and generates early-born enteric neurons, some of which are serotonergic. The other is Mash-1-independent, does not express sympathoadrenal markers, and generates late-born enteric neurons, some of which contain calcitonin gene related peptide

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

BACKGROUND: Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. RESULTS: S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. CONCLUSIONS: This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved.Published versio

Sensing coherent dynamics of electronic spin clusters in solids

We present experimental observations and a study of quantum dynamics of strongly interacting electronic spins, at room temperature in the solid state. In a diamond substrate, a single nitrogen vacancy (NV) center coherently interacts with two adjacent S = 1/2 dark electron spins. We quantify NV-electron and electron-electron couplings via detailed spectroscopy, with good agreement to a model of strongly interacting spins. The electron-electron coupling enables an observation of coherent flip-flop dynamics between electronic spins in the solid state, which occur conditionally on the state of the NV. Finally, as a demonstration of coherent control, we selectively couple and transfer polarization between the NV and the pair of electron spins. These results demonstrate a key step towards full quantum control of electronic spin registers in room temperature solids

Robust High-Dynamic-Range Vector Magnetometry via Nitrogen-Vacancy Centers in Diamond

We demonstrate a robust, scale-factor-free vector magnetometer, which uses a closed-loop frequency-locking scheme to simultaneously track Zeeman-split resonance pairs of nitrogen-vacancy (NV) centers in diamond. Compared with open-loop methodologies, this technique is robust against fluctuations in temperature, resonance linewidth, and contrast; offers a three-order-of-magnitude increase in dynamic range; and allows for simultaneous interrogation of multiple transition frequencies. By directly detecting the resonance frequencies of NV centers aligned along each of the diamond's four tetrahedral crystallographic axes, we perform full vector reconstruction of an applied magnetic field

Magnetic structure of Cd-doped CeCoIn5

The heavy fermion superconductor CeCoIn5 is believed to be close to a magnetic instability, but no static magnetic order has been found. Cadmium doping on the In-site shifts the balance between superconductivity and antiferromagnetism to the latter with an extended concentration range where both types of order coexist at low temperatures. We investigated the magnetic structure of nominally 10% Cd-doped CeCoIn5, being antiferromagnetically ordered below T_N=3 K and superconducting below T_c=1.3 K, by elastic neutron scattering. Magnetic intensity was observed only at the ordering wave vector Q_AF = (1/2,1/2,1/2) commensurate with the crystal lattice. Upon entering the superconducting state the magnetic intensity seems to change only little. The commensurate magnetic ordering in CeCo(In1-xCdx)5 is in contrast to the incommensurate antiferromagnetic ordering observed in the closely related compound CeRhIn5. Our results give new insights in the interplay between superconductivity and magnetism in the family of CeTIn5 (T=Co, Rh, and Ir) based compounds.Comment: 4 pages, 4 figure

Coupled SDW and Superconducting Order in FFLO State of CeCoIn5_5

The mechanism of incommensurate (IC) spin-density-wave (SDW) order observed in the Flude-Ferrell-Larkin-Ovchinnikov (FFLO) phase of CeCoIn$_5$ is discussed on the basis of new mode-coupling scheme among IC-SDW order, two superconducting orders of FFLO with B$_{1{\rm g}}$ ($d_{x^{2}-y^{2}}$) symmetry and $\pi$-pairing of odd-parity. Unlike the mode-coupling schemes proposed by Kenzelmann et al, Sciencexpress, 21 August (2008), that proposed in the present Letter can offer a simple explanation for why the IC-SDW order is observed only in FFLO phase and the IC wave vector is rather robust against the magnetic field.Comment: 3pages, 1 figure, accepted for publication in J. Phys. Soc. Jpn., Vol.77 (2008), No.1

Crowdsourcing Dialect Characterization through Twitter

We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character.Comment: 10 pages, 5 figure