Neural Generative Question Answering

This paper presents an end-to-end neural network model, named Neural Generative Question Answering (GENQA), that can generate answers to simple factoid questions, based on the facts in a knowledge-base. More specifically, the model is built on the encoder-decoder framework for sequence-to-sequence learning, while equipped with the ability to enquire the knowledge-base, and is trained on a corpus of question-answer pairs, with their associated triples in the knowledge-base. Empirical study shows the proposed model can effectively deal with the variations of questions and answers, and generate right and natural answers by referring to the facts in the knowledge-base. The experiment on question answering demonstrates that the proposed model can outperform an embedding-based QA model as well as a neural dialogue model trained on the same data.Comment: Accepted by IJCAI 201

Enhanced bias stress stability of a-InGaZnO thin film transistors by inserting an ultra-thin interfacial InGaZnO:N layer

Amorphous indium-gallium-zinc oxide (a-IGZO) thin film transistors (TFTs) having an ultra-thin nitrogenated a-IGZO (a-IGZO:N) layer sandwiched at the channel/gate dielectric interface are fabricated. It is found that the device shows enhanced bias stress stability with significantly reduced threshold voltage drift under positive gate bias stress. Based on x-ray photoelectron spectroscopy measurement, the concentration of oxygen vacancies within the a-IGZO:N layer is suppressed due to the formation of N-Ga bonds. Meanwhile, low frequency noise analysis indicates that the average trap density near the channel/dielectric interface continuously drops as the nitrogen content within the a-IGZO:N layer increases. The improved interface quality upon nitrogen doping agrees with the enhanced bias stress stability of the a-IGZO TFTs.This work was supported in part by the State Key Program for Basic Research of China under Grant Nos. 2010CB327504, 2011CB922100, and 2011CB301900; in part by the National Natural Science Foundation of China under Grant Nos. 60936004 and 11104130; in part by the Natural Science Foundation of Jiangsu Province under Grant Nos. BK2011556 and BK2011050; and in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions

Productivity Formulae of an Infinite-conductivity Hydraulically Fractured Well Producing at Constant Wellbore Pressure Based on Numerical Solutions of a Weakly Singular Integral Equation of the First Kind

In order to increase productivity, it is important to study the performance of a hydraulically fractured well producing at constant wellbore pressure. This paper constructs a new productivity formula, which is obtained by solving a weakly singular integral equation of the first kind, for an infinite-conductivity hydraulically fractured well producing at constant pressure. And the two key components of this paper are a weakly singular integral equation of the first kind and a steady-state productivity formula. A new midrectangle algorithm and a Galerkin method are presented in order to solve the weakly singular integral equation. The numerical results of these two methods are in accordance with each other. And then the solutions of the weakly singular integral equation are utilized for the productivity formula of hydraulic fractured wells producing at constant pressure, which provide fast analytical tools to evaluate production performance of infinite-conductivity fractured wells. The paper also shows equipotential threads, which are generated from the numerical results, with different fluid potential values. These threads can be approximately taken as a family of ellipses whose focuses are the two endpoints of the fracture, which is in accordance with the regular assumption in Kuchuk and Brigham, 1979

QAOA with fewer qubits: a coupling framework to solve larger-scale Max-Cut problem

Maximum cut (Max-Cut) problem is one of the most important combinatorial optimization problems because of its various applications in real life, and recently Quantum Approximate Optimization Algorithm (QAOA) has been widely employed to solve it. However, as the size of the problem increases, the number of qubits required will become larger. With the aim of saving qubits, we propose a coupling framework for designing QAOA circuits to solve larger-scale Max-Cut problem. This framework relies on a classical algorithm that approximately solves a certain variant of Max-Cut, and we derive an approximation guarantee theoretically, assuming the approximation ratio of the classical algorithm and QAOA. Furthermore we design a heuristic approach that fits in our framework and perform sufficient numerical experiments, where we solve Max-Cut on various $24$-vertex Erd\H{o}s-R\'enyi graphs. Our framework only consumes $18$ qubits and achieves $0.9950$ approximation ratio on average, which outperforms the previous methods showing $0.9778$ (quantum algorithm using the same number of qubits) and $0.9643$ (classical algorithm). The experimental results indicate our well-designed quantum-classical coupling framework gives satisfactory approximation ratio while reduces the qubit cost, which sheds light on more potential computing power of NISQ devices

High Accuracy Combination Method For Solving the Systems of Nonlinear Volterra Integral and Integro-differential Equations with Weakly Singular Kernels of the Second Kind

This paper presents a high accuracy combination algorithm for solving the systems of nonlinear Volterra integral and integro-differential equations with weakly singular kernels of the second kind. Two quadrature algorithms for solving the systems are discussed, which possess high accuracy order and the asymptotic expansion of the errors. By means of combination algorithm, we may obtain a numerical solution with higher accuracy order than the original two quadrature algorithms. Moreover an a posteriori error estimation for the algorithm is derived. Both of the theory and the numerical examples show that the algorithm is effective and saves storage capacity and computational cost

Productivity Formulae of an Infinite-Conductivity Hydraulically Fractured Well Producing at Constant Wellbore Pressure Based on Numerical Solutions of a Weakly Singular Integral Equation of the First Kind

In order to increase productivity, it is important to study the performance of a hydraulically fractured well producing at constant wellbore pressure. This paper constructs a new productivity formula, which is obtained by solving a weakly singular integral equation of the first kind, for an infinite-conductivity hydraulically fractured well producing at constant pressure. And the two key components of this paper are a weakly singular integral equation of the first kind and a steady-state productivity formula. A new midrectangle algorithm and a Galerkin method are presented in order to solve the weakly singular integral equation. The numerical results of these two methods are in accordance with each other. And then the solutions of the weakly singular integral equation are utilized for the productivity formula of hydraulic fractured wells producing at constant pressure, which provide fast analytical tools to evaluate production performance of infinite-conductivity fractured wells. The paper also shows equipotential threads, which are generated from the numerical results, with different fluid potential values. These threads can be approximately taken as a family of ellipses whose focuses are the two endpoints of the fracture, which is in accordance with the regular assumption in Kuchuk and Brigham, 1979

Contrast-free detection of myocardial fibrosis in hypertrophic cardiomyopathy patients with diffusion-weighted cardiovascular magnetic resonance.

BackgroundsPrevious studies have shown that diffusion-weighted cardiovascular magnetic resonance (DW-CMR) is highly sensitive to replacement fibrosis of chronic myocardial infarction. Despite this sensitivity to myocardial infarction, DW-CMR has not been established as a method to detect diffuse myocardial fibrosis. We propose the application of a recently developed DW-CMR technique to detect diffuse myocardial fibrosis in hypertrophic cardiomyopathy (HCM) patients and compare its performance with established CMR techniques.MethodsHCM patients (N = 23) were recruited and scanned with the following protocol: standard morphological localizers, DW-CMR, extracellular volume (ECV) CMR, and late gadolinium enhanced (LGE) imaging for reference. Apparent diffusion coefficient (ADC) and ECV maps were segmented into 6 American Heart Association (AHA) segments. Positive regions for myocardial fibrosis were defined as: ADC > 2.0 μm(2)/ms and ECV > 30%. Fibrotic and non-fibrotic mean ADC and ECV values were compared as well as ADC-derived and ECV-derived fibrosis burden. In addition, fibrosis regional detection was compared between ADC and ECV calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) using ECV as the gold-standard reference.ResultsADC (2.4 ± 0.2 μm(2)/ms) of fibrotic regions (ADC > 2.0 μm(2)/ms) was significantly (p < 0.01) higher than ADC (1.5 ± 0.2 μm(2)/ms) of non-fibrotic regions. Similarly, ECV (35 ± 4%) of fibrotic regions (ECV > 30%) was significantly (p < 0.01) higher than ECV (26 ± 2%) of non-fibrotic regions. In fibrotic regions defined by ECV, ADC (2.2 ± 0.3 μm(2)/ms) was again significantly (p < 0.05) higher than ADC (1.6 ± 0.3 μm(2)/ms) of non-fibrotic regions. In fibrotic regions defined by ADC criterion, ECV (34 ± 5%) was significantly (p < 0.01) higher than ECV (28 ± 3%) in non-fibrotic regions. ADC-derived and ECV-derived fibrosis burdens were in substantial agreement (intra-class correlation = 0.83). Regional detection between ADC and ECV of diffuse fibrosis yielded substantial agreement (κ = 0.66) with high sensitivity, specificity, PPV, NPV, and accuracy (0.80, 0.85, 0.81, 0.85, and 0.83, respectively).ConclusionDW-CMR is sensitive to diffuse myocardial fibrosis and is capable of characterizing the extent of fibrosis in HCM patients

Nitric Oxide Activates Intradomain Disulfide Bond Formation in the Kinase Loop of Akt1/PKBα after Burn Injury

Severe burn injury is an acute inflammatory state with massive alterations in gene expression and levels of growth factors, cytokines and free radicals. During the catabolic processes, changes in insulin sensitivity and skeletal muscle wasting (unintended loss of 5–15% of lean body mass) are observed clinically. Here, we reveal a novel molecular mechanism of Akt1/protein kinase Bα (Akt1/PKBα) regulated via cross-talking between dephosphorylation of Thr308 and S-nitrosylation of Cys296 post severe burn injury, which were characterized using nano-LC interfaced with tandem quadrupole time-of-fight mass spectrometry (Q-TOF)micro tandem mass spectrometry in both in vitro and in vivo studies. For the in vitro studies, Akt1/PKBα was S-nitrosylated with S-nitrosoglutathione and derivatized by three methods. The derivatives were isolated by SDS-PAGE, trypsinized and analyzed by the tandem MS. For the in vivo studies, Akt1/PKBα in muscle lysates from burned rats was immuno-precipitated, derivatized with HPDP-Biotin and analyzed as above. The studies demonstrated that the NO free radical reacts with the free thiol of Cys296 to produce a Cys296-SNO intermediate which accelerates interaction with Cys310 to form Cys296-Cys310 in the kinase loop. MS/MS sequence analysis indicated that the dipeptide, linked via Cys296-Cys310, underwent dephosphorylation at Thr308. These effects were not observed in lysates from sham animals. As a result of this dual effect of burn injury, the loose conformation that is slightly stabilized by the Lys297-Thr308 salt bridge may be replaced by a more rigid structure which may block substrate access. Together with the findings of our previous report concerning mild IRS-1 integrity changes post burn, it is reasonable to conclude that the impaired Akt1/PKBα has a major impact on FOXO3 subcellular distribution and activities