Intent-calibrated Self-training for answer selection in open-domain dialogues

Answer selection in open-domain dialogues aims to select an accurate answer from candidates. Recent success of answer selection models hinges on training with large amounts of labeled data. However, collecting large-scale labeled data is labor-intensive and time-consuming. In this paper, we introduce the predicted intent labels to calibrate answer labels in a self-training paradigm. Specifically, we propose the intent-calibrated self-training (ICAST) to improve the quality of pseudo answer labels through the intent-calibrated answer selection paradigm, in which we employ pseudo intent labels to help improve pseudo answer labels. We carry out extensive experiments on two benchmark datasets with open-domain dialogues. The experimental results show that ICAST outperforms baselines consistently with 1%, 5% and 10% labeled data. Specifically, it improves 2.06% and 1.00% of F1 score on the two datasets, compared with the strongest baseline with only 5% labeled data

Syllogistic reasoning for legal judgment analysis

Computer Systems, Imagery and Medi

Linear-Optical Implementation of Perfect Discrimination between Single-bit Unitary Operations

Discrimination of unitary operations is a fundamental quantum information processing task. Assisted with linear optical elements, we experimentally demonstrate perfect discrimination between single-bit unitary operations using two methods--sequential scheme and parallel scheme. The complexity and resource consumed in these two schemes are analyzed and compared.Comment: 10 pages, 3 figure

Coordinate-Space Hartree-Fock-Bogoliubov Description of Superfluid Fermi Systems

Properties of strongly interacting, two-component finite Fermi systems are discussed within the recently developed coordinate-space Hartree-Fock-Bogoliubov (HFB) code {\hfbax}. Two illustrative examples are presented: (i) weakly bound deformed Mg isotopes, and (ii) spin-polarized atomic condensates in a strongly deformed harmonic trap.Comment: 4 pages, 2 figures, ENAM 2008 conference proceedings (EPJA

Effect of dietary omega-3 fatty acids on castrate-resistant prostate cancer and tumor-associated macrophages.

BackgroundM2-like macrophages are associated with the pathogenesis of castrate-resistant prostate cancer (CRPC). We sought to determine if dietary omega-3 fatty acids (ω-3 FAs) delay the development and progression of CRPC and inhibit tumor-associated M2-like macrophages.MethodsMycCap cells were grown subcutaneously in immunocompetent FVB mice. Mice were castrated when tumors reached 300 mm2. To study effects of dietary ω-3 FAs on development of CRPC, ω-3 or ω-6 diets were started 2 days after castration and mice sacrificed after early regrowth of tumors. To study ω-3 FA effects on progression of CRPC, tumors were allowed to regrow after castration before starting the diets. M2 (CD206+) macrophages were isolated from allografts to examine ω-3 FA effects on macrophage function. Omega-3 fatty acid effects on androgen-deprived RAW264.7 M2 macrophages were studied by RT-qPCR and a migration/ invasion assay.ResultsThe ω-3 diet combined with castration lead to greater MycCap tumor regression (tumor volume reduction: 182.2 ± 33.6 mm3) than the ω-6 diet (tumor volume reduction: 148.3 ± 35.2; p = 0.003) and significantly delayed the time to CRPC (p = 0.006). Likewise, the ω-3 diet significantly delayed progression of established castrate-resistant MycCaP tumors (p = 0.003). The ω-3 diet (as compared to the ω-6 diet) significantly reduced tumor-associated M2-like macrophage expression of CSF-1R in the CRPC development model, and matrix metallopeptidase-9 (MMP-9) and vascular endothelial growth factor (VEGF) in the CRPC progression model. Migration of androgen-depleted RAW264.7 M2 macrophages towards MycCaP cells was reversed by addition of docosahexaenoic acid (ω-3).ConclusionsDietary omega-3 FAs (as compared to omega-6 FAs) decreased the development and progression of CRPC in an immunocompetent mouse model, and had inhibitory effects on M2-like macrophage function. Clinical trials are warranted evaluating if a fish oil-based diet can delay the time to castration resistance in men on androgen deprivation therapy, whereas further preclinical studies are warranted evaluating fish oil for more advanced CRPC

Approximate Bayesian feature selection on a large meta-dataset offers novel insights on factors that effect siRNA potency

Motivation: Short interfering RNA (siRNA)-induced RNA interference is an endogenous pathway in sequence-specific gene silencing. The potency of different siRNAs to inhibit a common target varies greatly and features affecting inhibition are of high current interest. The limited success in predicting siRNA potency being reported so far could originate in the small number and the heterogeneity of available datasets in addition to the knowledge-driven, empirical basis on which features thought to be affecting siRNA potency are often chosen. We attempt to overcome these problems by first constructing a meta-dataset of 6483 publicly available siRNAs (targeting mammalian mRNA), the largest to date, and then applying a Bayesian analysis which accommodates feature set uncertainty. A stochastic logistic regression-based algorithm is designed to explore a vast model space of 497 compositional, structural and thermodynamic features, identifying associations with siRNA potency

Formation of the ηc\eta_c in Two-Photon Collisions at LEP

The two-photon width $\Gamma_{\gamma\gamma}$ of the $\eta_c$ meson has been measured with the L3 detector at LEP. The $\eta_c$ is studied in the decay modes $\pi^+\pi^-\pi^+\pi^-$, $\pi^+\pi^-$K$^+$K$^-$, K$_s^0$K$^\pm\pi^\mp$, K$^+$K$^-\pi^{0}$, $\pi^+\pi^-\eta$, $\pi^+\pi^-\eta'$, and $\rho^+\rho^-$ using an integrated luminosity of 140 pb$^{-1}$ at $\sqrt{s} \simeq 91$ GeV and of 52 pb$^{-1}$ at $\sqrt{s} \simeq 183$ GeV. The result is $\Gamma_{\gamma\gamma}(\eta_c) = 6.9 \pm 1.7 (stat.) \pm 0.8 (sys.) \pm 2.0$(BR) keV. The $Q^2$ dependence of the $\eta_c$ cross section is studied for $Q^2 < 9$ GeV$^{2}$. It is found to be better described by a Vector Meson Dominance model form factor with a J-pole than with a $\rho$-pole. In addition, a signal of $29 \pm 11$ events is observed at the $\chi_c0$ mass. Upper limits for the two-photon widths of the $\chi_c0$, $\chi_c2$, and $\eta_c'$ are also given

Reconsideration of In-Silico siRNA Design Based on Feature Selection: A Cross-Platform Data Integration Perspective

RNA interference via exogenous short interference RNAs (siRNA) is increasingly more widely employed as a tool in gene function studies, drug target discovery and disease treatment. Currently there is a strong need for rational siRNA design to achieve more reliable and specific gene silencing; and to keep up with the increasing needs for a wider range of applications. While progress has been made in the ability to design siRNAs with specific targets, we are clearly at an infancy stage towards achieving rational design of siRNAs with high efficacy. Among the many obstacles to overcome, lack of general understanding of what sequence features of siRNAs may affect their silencing efficacy and of large-scale homogeneous data needed to carry out such association analyses represents two challenges. To address these issues, we investigated a feature-selection based in-silico siRNA design from a novel cross-platform data integration perspective. An integration analysis of 4,482 siRNAs from ten meta-datasets was conducted for ranking siRNA features, according to their possible importance to the silencing efficacy of siRNAs across heterogeneous data sources. Our ranking analysis revealed for the first time the most relevant features based on cross-platform experiments, which compares favorably with the traditional in-silico siRNA feature screening based on the small samples of individual platform data. We believe that our feature ranking analysis can offer more creditable suggestions to help improving the design of siRNA with specific silencing targets. Data and scripts are available at http://csbl.bmb.uga.edu/publications/materials/qiliu/siRNA.html