Variational Deep Semantic Hashing for Text Documents

As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

Information decomposition of symbolic sequences

We developed a non-parametric method of Information Decomposition (ID) of a content of any symbolical sequence. The method is based on the calculation of Shannon mutual information between analyzed and artificial symbolical sequences, and allows the revealing of latent periodicity in any symbolical sequence. We show the stability of the ID method in the case of a large number of random letter changes in an analyzed symbolic sequence. We demonstrate the possibilities of the method, analyzing both poems, and DNA and protein sequences. In DNA and protein sequences we show the existence of many DNA and amino acid sequences with different types and lengths of latent periodicity. The possible origin of latent periodicity for different symbolical sequences is discussed.Comment: 18 pages, 8 figure

The red tail of carbon stars in the LMC: Models meet 2MASS and DENIS observations

Carbon stars are known to exhibit systematically redder near-infrared colours with respect to M-type stars. In the near-infrared colour-magnitude diagrams provided by the 2MASS and DENIS surveys, the LMC C-type stars draw a striking red tail, well separated from the sequences of O-rich giants. So far, this conspicuous feature has been absent from any set of available isochrones, even the few existing ones that include the TP-AGB evolution of low- and intermediate-mass stars. To investigate such issue we simulate the complete 2MASS Ks vs.(J-Ks) data towards the LMC by means of a population synthesis approach, that relies on extended libraries of published stellar evolutionary tracks, including the TP-AGB phase. The simulations provide quite a detailed description of the several vertical fingers and inclined sequences seen in 2MASS data, due to both Galactic foreground and LMC O-rich stars. Instead, as mentioned, the red tail of C-stars sets a major difficulty: we find that TP-AGB models with solar-scaled molecular opacities, the usual assumption of existing AGB calculations, do not succeed in reproducing this feature. Our tests indicate that the main reason for this failure should not be ascribed to empirical Teff - (J-K) transformations for C-type stars. Instead, the discrepancy is simply removed by adopting new evolutionary models that account for the changes in molecular opacities as AGB stars get enriched in carbon via the third dredge-up (Marigo 2002). In fact, simulations that adopt these models are able to reproduce, for the first time, the red tail of C-stars in near-infrared CMDs. Finally, we point out that these simulations also provide useful indications about the efficiency of the third dredge-up process, and the pulsation modes of long-period variables.Comment: To appear in A&A. 14 pages, better if printed in colour. A version with high-resolution figures may be found in http://pleiadi.pd.astro.i

On the critical nature of plastic flow: one and two dimensional models

Steady state plastic flows have been compared to developed turbulence because the two phenomena share the inherent complexity of particle trajectories, the scale free spatial patterns and the power law statistics of fluctuations. The origin of the apparently chaotic and at the same time highly correlated microscopic response in plasticity remains hidden behind conventional engineering models which are based on smooth fitting functions. To regain access to fluctuations, we study in this paper a minimal mesoscopic model whose goal is to elucidate the origin of scale free behavior in plasticity. We limit our description to fcc type crystals and leave out both temperature and rate effects. We provide simple illustrations of the fact that complexity in rate independent athermal plastic flows is due to marginal stability of the underlying elastic system. Our conclusions are based on a reduction of an over-damped visco-elasticity problem for a system with a rugged elastic energy landscape to an integer valued automaton. We start with an overdamped one dimensional model and show that it reproduces the main macroscopic phenomenology of rate independent plastic behavior but falls short of generating self similar structure of fluctuations. We then provide evidence that a two dimensional model is already adequate for describing power law statistics of avalanches and fractal character of dislocation patterning. In addition to capturing experimentally measured critical exponents, the proposed minimal model shows finite size scaling collapse and generates realistic shape functions in the scaling laws.Comment: 72 pages, 40 Figures, International Journal of Engineering Science for the special issue in honor of Victor Berdichevsky, 201

Minimax Current Density Coil Design

'Coil design' is an inverse problem in which arrangements of wire are designed to generate a prescribed magnetic field when energized with electric current. The design of gradient and shim coils for magnetic resonance imaging (MRI) are important examples of coil design. The magnetic fields that these coils generate are usually required to be both strong and accurate. Other electromagnetic properties of the coils, such as inductance, may be considered in the design process, which becomes an optimization problem. The maximum current density is additionally optimized in this work and the resultant coils are investigated for performance and practicality. Coils with minimax current density were found to exhibit maximally spread wires and may help disperse localized regions of Joule heating. They also produce the highest possible magnetic field strength per unit current for any given surface and wire size. Three different flavours of boundary element method that employ different basis functions (triangular elements with uniform current, cylindrical elements with sinusoidal current and conic section elements with sinusoidal-uniform current) were used with this approach to illustrate its generality.Comment: 24 pages, 6 figures, 2 tables. To appear in Journal of Physics D: Applied Physic

Resonant tunneling through ultrasmall quantum dots: zero-bias anomalies, magnetic field dependence, and boson-assisted transport

We study resonant tunneling through a single-level quantum dot in the presence of strong Coulomb repulsion beyond the perturbative regime. The level is either spin-degenerate or can be split by a magnetic field. We, furthermore, discuss the influence of a bosonic environment. Using a real-time diagrammatic formulation we calculate transition rates, the spectral density and the nonlinear $I-V$ characteristic. The spectral density shows a multiplet of Kondo peaks split by the transport voltage and the boson frequencies, and shifted by the magnetic field. This leads to zero-bias anomalies in the differential conductance, which agree well with recent experimental results for the electron transport through single-charge traps. Furthermore, we predict that the sign of the zero-bias anomaly depends on the level position relative to the Fermi level of the leads.Comment: 27 pages, latex, 21 figures, submitted to Phys. Rev.

Rapid neurogenesis through transcriptional activation in human stem cells

Advances in cellular reprogramming and stem cell differentiation now enable ex vivo studies of human neuronal differentiation. However, it remains challenging to elucidate the underlying regulatory programs because differentiation protocols are laborious and often result in low neuron yields. Here, we overexpressed two Neurogenin transcription factors in human-induced pluripotent stem cells and obtained neurons with bipolar morphology in 4 days, at greater than 90% purity. The high purity enabled mRNA and microRNA expression profiling during neurogenesis, thus revealing the genetic programs involved in the rapid transition from stem cell to neuron. The resulting cells exhibited transcriptional, morphological and functional signatures of differentiated neurons, with greatest transcriptional similarity to prenatal human brain samples. Our analysis revealed a network of key transcription factors and microRNAs that promoted loss of pluripotency and rapid neurogenesis via progenitor states. Perturbations of key transcription factors affected homogeneity and phenotypic properties of the resulting neurons, suggesting that a systems-level view of the molecular biology of differentiation may guide subsequent manipulation of human stem cells to rapidly obtain diverse neuronal types

Driving chronicity in rheumatoid arthritis: perpetuating role of myeloid cells

Acute inflammation is a complex and tightly regulated homeostatic process that includes leukocyte migration from the vasculature into tissues to eliminate the pathogen/injury, followed by a pro-resolving response promoting tissue repair. However, if inflammation is uncontrolled as in chronic diseases such as Rheumatoid Arthritis (RA) it leads to tissue damage and disability. Synovial tissue inflammation in RA patients is maintained by sustained activation of multiple inflammatory positive-feedback regulatory pathways in a variety of cells including myeloid cells. In this review, we will highlight recent evidence uncovering biological mechanisms contributing to the aberrant activation of myeloid cells that contributes to perpetuation of inflammation in RA, and discuss emerging data on anti-inflammatory mediators contributing to sustained remission that may inform a novel category of therapeutic targets

Quantum dynamics in strong fluctuating fields

A large number of multifaceted quantum transport processes in molecular systems and physical nanosystems can be treated in terms of quantum relaxation processes which couple to one or several fluctuating environments. A thermal equilibrium environment can conveniently be modelled by a thermal bath of harmonic oscillators. An archetype situation provides a two-state dissipative quantum dynamics, commonly known under the label of a spin-boson dynamics. An interesting and nontrivial physical situation emerges, however, when the quantum dynamics evolves far away from thermal equilibrium. This occurs, for example, when a charge transferring medium possesses nonequilibrium degrees of freedom, or when a strong time-dependent control field is applied externally. Accordingly, certain parameters of underlying quantum subsystem acquire stochastic character. Herein, we review the general theoretical framework which is based on the method of projector operators, yielding the quantum master equations for systems that are exposed to strong external fields. This allows one to investigate on a common basis the influence of nonequilibrium fluctuations and periodic electrical fields on quantum transport processes. Most importantly, such strong fluctuating fields induce a whole variety of nonlinear and nonequilibrium phenomena. A characteristic feature of such dynamics is the absence of thermal (quantum) detailed balance.Comment: review article, Advances in Physics (2005), in pres

A Cryogenic Silicon Interferometer for Gravitational-wave Detection

The detection of gravitational waves from compact binary mergers by LIGO has opened the era of gravitational wave astronomy, revealing a previously hidden side of the cosmos. To maximize the reach of the existing LIGO observatory facilities, we have designed a new instrument that will have 5 times the range of Advanced LIGO, or greater than 100 times the event rate. Observations with this new instrument will make possible dramatic steps toward understanding the physics of the nearby universe, as well as observing the universe out to cosmological distances by the detection of binary black hole coalescences. This article presents the instrument design and a quantitative analysis of the anticipated noise floor