Label-Dependencies Aware Recurrent Neural Networks

In the last few years, Recurrent Neural Networks (RNNs) have proved effective on several NLP tasks. Despite such great success, their ability to model \emph{sequence labeling} is still limited. This lead research toward solutions where RNNs are combined with models which already proved effective in this domain, such as CRFs. In this work we propose a solution far simpler but very effective: an evolution of the simple Jordan RNN, where labels are re-injected as input into the network, and converted into embeddings, in the same way as words. We compare this RNN variant to all the other RNN models, Elman and Jordan RNN, LSTM and GRU, on two well-known tasks of Spoken Language Understanding (SLU). Thanks to label embeddings and their combination at the hidden layer, the proposed variant, which uses more parameters than Elman and Jordan RNNs, but far fewer than LSTM and GRU, is more effective than other RNNs, but also outperforms sophisticated CRF models.Comment: 22 pages, 3 figures. Accepted at CICling 2017 conference. Best Verifiability, Reproducibility, and Working Description awar

Fabrication of FeSe1-x superconducting films with bulk properties

We have fabricated high-quality FeSe1-x superconducting films with a bulk Tc of 11-12 K on different substrates, Al2O3(0001), SrTiO3(100), MgO(100), and LaAlO3(100), by using a pulsed laser deposition technique. All the films were grown at a high substrate temperature of 610 oC, and were preferentially oriented along the (101) direction, the latter being to be a key to fabricating of FeSe1-x superconducting thin films with high Tc. According to the energy dispersive spectroscopy data, the Fe:Se composition ratio was 1:0.90+-0.02. The FeSe1-x film grown on a SrTiO3 substrate showed the best quality with a high upper critical magnetic field [Hc2(0)] of 56 T

Resolving photon number states in a superconducting circuit

Electromagnetic signals are always composed of photons, though in the circuit domain those signals are carried as voltages and currents on wires, and the discreteness of the photon's energy is usually not evident. However, by coupling a superconducting qubit to signals on a microwave transmission line, it is possible to construct an integrated circuit where the presence or absence of even a single photon can have a dramatic effect. This system is called circuit quantum electrodynamics (QED) because it is the circuit equivalent of the atom-photon interaction in cavity QED. Previously, circuit QED devices were shown to reach the resonant strong coupling regime, where a single qubit can absorb and re-emit a single photon many times. Here, we report a circuit QED experiment which achieves the strong dispersive limit, a new regime of cavity QED in which a single photon has a large effect on the qubit or atom without ever being absorbed. The hallmark of this strong dispersive regime is that the qubit transition can be resolved into a separate spectral line for each photon number state of the microwave field. The strength of each line is a measure of the probability to find the corresponding photon number in the cavity. This effect has been used to distinguish between coherent and thermal fields and could be used to create a photon statistics analyzer. Since no photons are absorbed by this process, one should be able to generate non-classical states of light by measurement and perform qubit-photon conditional logic, the basis of a logic bus for a quantum computer.Comment: 6 pages, 4 figures, hi-res version at http://www.eng.yale.edu/rslab/papers/numbersplitting_hires.pd

The impact of European embryonic stem cell patent decisions on research strategies

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Single-shot qubit readout in circuit Quantum Electrodynamics

The future development of quantum information using superconducting circuits requires Josephson qubits [1] with long coherence times combined to a high-fidelity readout. Major progress in the control of coherence has recently been achieved using circuit quantum electrodynamics (cQED) architectures [2, 3], where the qubit is embedded in a coplanar waveguide resonator (CPWR) which both provides a well controlled electromagnetic environment and serves as qubit readout. In particular a new qubit design, the transmon, yields reproducibly long coherence times [4, 5]. However, a high-fidelity single-shot readout of the transmon, highly desirable for running simple quantum algorithms or measur- ing quantum correlations in multi-qubit experiments, is still lacking. In this work, we demonstrate a new transmon circuit where the CPWR is turned into a sample-and-hold detector, namely a Josephson Bifurcation Amplifer (JBA) [6, 7], which allows both fast measurement and single-shot discrimination of the qubit states. We report Rabi oscillations with a high visibility of 94% together with dephasing and relaxation times longer than 0:5 \mu\s. By performing two subsequent measurements, we also demonstrate that this new readout does not induce extra qubit relaxation.Comment: 14 pages including 4 figures, preprint forma

Limited Effect of CpG ODN in Preventing Type 1 Diabetes in NOD Mice

Type 1 diabetes is considered as Th1 cell mediated autoimmune disease and the suppression of Th1 cells or the activation of Th2 cells has been regarded as a plausible immunologic intervention for the prevention of type 1 diabetogenesis in a rodent model. CpG ODN is an immunostimulatory sequence primarily present in bacterial DNA, viral DNA and BCG. CpG ODN is conventionally classified as a Th1 cell activator, which has been clinically applied to cancer, allergy and infectious disease. Recently, there was a promising report of that CpG ODN administration suppressed the development of type 1 diabetes in NOD mice by inducing Th2 cell mediated cytokine. However, the antidiabetogenic effect of CpG ODN on NOD mice is controversial. Thus, two studies were serially undertaken with various kinds of CpG motif to find a more optimal sequence and administration method. In the first study, CpG ODN was vaccinated four times and pancreatic inflammation and the quantity of serum insulin subsequently evaluated. In the second study, the amounts of IFN γ and IL-4 in sera were measured as representative cytokines of Th1 and Th2 cells, respectively. As a result, vaccination or continuous injection of CpG ODN failed to show a preventive effect on type 1 diabetogenesis in NOD mice. Structural differences of CpG ODN also had no affect on the result. CpG ODN also consistently showed affect on the pancreatic pathology. The productions of IFN and IL-4 were γ detected only in the K and D type CpG ODN administration groups. Comparison of the two cytokines leads to the conclusion that CpG ODN generated a Th1-weighted response in both study groups. It was assumed that CpG ODN failed to produce Th2-weighted cytokine milieu, which can overcome the genetically determined phenotype of NOD mice. Given these results, it was concluded that the immunotherapeutic application of CpG ODN on Type 1 diabetes had clear limitations

Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks

The metabolism of organisms can be studied with comprehensive stoichiometric models of their metabolic networks. Flux balance analysis (FBA) calculates optimal metabolic performance of stoichiometric models. However, detailed biological interpretation of FBA is limited because, in general, a huge number of flux patterns give rise to the same optimal performance. The complete description of the resulting optimal solution spaces was thus far a computationally intractable problem. Here we present CoPE-FBA: Comprehensive Polyhedra Enumeration Flux Balance Analysis, a computational method that solves this problem. CoPE-FBA indicates that the thousands to millions of optimal flux patterns result from a combinatorial explosion of flux patterns in just a few metabolic sub-networks. The entire optimal solution space can now be compactly described in terms of the topology of these sub-networks. CoPE-FBA simplifies the biological interpretation of stoichiometric models of metabolism, and provides a profound understanding of metabolic flexibility in optimal states

Global Self-Organization of the Cellular Metabolic Structure

Background: Over many years, it has been assumed that enzymes work either in an isolated way, or organized in small catalytic groups. Several studies performed using "metabolic networks models'' are helping to understand the degree of functional complexity that characterizes enzymatic dynamic systems. In a previous work, we used "dissipative metabolic networks'' (DMNs) to show that enzymes can present a self-organized global functional structure, in which several sets of enzymes are always in an active state, whereas the rest of molecular catalytic sets exhibit dynamics of on-off changing states. We suggested that this kind of global metabolic dynamics might be a genuine and universal functional configuration of the cellular metabolic structure, common to all living cells. Later, a different group has shown experimentally that this kind of functional structure does, indeed, exist in several microorganisms. Methodology/Principal Findings: Here we have analyzed around 2.500.000 different DMNs in order to investigate the underlying mechanism of this dynamic global configuration. The numerical analyses that we have performed show that this global configuration is an emergent property inherent to the cellular metabolic dynamics. Concretely, we have found that the existence of a high number of enzymatic subsystems belonging to the DMNs is the fundamental element for the spontaneous emergence of a functional reactive structure characterized by a metabolic core formed by several sets of enzymes always in an active state. Conclusions/Significance: This self-organized dynamic structure seems to be an intrinsic characteristic of metabolism, common to all living cellular organisms. To better understand cellular functionality, it will be crucial to structurally characterize these enzymatic self-organized global structures.Supported by the Spanish Ministry of Science and Education Grants MTM2005-01504, MTM2004-04665, partly with FEDER funds, and by the Basque Government, Grant IT252-07