Conversational question answering: a survey

Published online: 6 September 2022Question answering (QA) systems provide a way of querying the information available in various formats including, but not limited to, unstructured and structured data in natural languages. It constitutes a considerable part of conversational artificial intelligence (AI) which has led to the introduction of a special research topic on conversational question answering (CQA), wherein a system is required to understand the given context and then engages in multi-turn QA to satisfy a user’s information needs. While the focus of most of the existing research work is subjected to single-turn QA, the field of multi-turn QA has recently grasped attention and prominence owing to the availability of large-scale, multi-turn QA datasets and the development of pre-trained language models. With a good amount of models and research papers adding to the literature every year recently, there is a dire need of arranging and presenting the related work in a unified manner to streamline future research. This survey is an effort to present a comprehensive review of the state-of-the-art research trends of CQA primarily based on reviewed papers over the recent years. Our findings show that there has been a trend shift from single-turn to multi-turn QA which empowers the field of Conversational AI from different perspectives. This survey is intended to provide an epitome for the research community with the hope of laying a strong foundation for the field of CQA.Munazza Zaib, Wei Emma Zhang, Quan Z. Sheng, Adnan Mahmood, Yang Zhan

Growth, immunity and ammonia excretion of albino and normal Apostichopus japonicus (Selenka) feeding with various experimental diets

An experiment was conducted to evaluate the effects of six experimental diets on growth performance, ammonia excretion and immunity of albino and normal Apostichopus japonicus. A factorial design was used, the factors being type of diets (six levels) and colour of A. japonicus (two levels). A total of 30 randomly selected albino A. japonicus were housed in each (60 × 50 × 30 cm3) of 18 blue plastic aquaria to form six groups in triplicate, and the same set-up was used for the normal A. japonicus. Each group of animals was fed with one of the six experimental diets. Apparent dry matter digestibility (ADMD) and apparent crude protein digestibility (ACPD) were analysed using acid-insoluble ash (AIA) content method. At the end of the experiment, all A. japonicus were harvested and weighed to calculate growth parameters. After weighing, six individuals from each aquarium were randomly sampled for immune indices. Results indicated that all growth parameters of A. japonicus increased with decreasing nutrient content in their diets (p < .01), whereas an opposite result was observed in case of the ammonia-nitrogen production by A. japonicus. Normal A. japonicus grew better (p < .01) and produced lower (p < .01) quantity of ammonia nitrogen compared to the albino A. japonicus. Immunity particularly superoxide dismutase and lysozyme activities was higher (p < .05) in normal compared to albino A. japonicus. Considering all measured variables, D1 (diet containing crude protein, crude lipid, carbohydrate and crude ash 51.8, 8.7, 231.3, 708.2 g/kg, respectively) was the best diet among all experimental diets. More research is still needed to optimize nutrients in the diet of A. japonicus, as this study does not provide information about critical threshold level of nutrients in diets. Until then, diet D1 can be recommended for A. japonicus aquaculture

CupMar: A deep learning model for personalized news recommendation based on contextual user-profile and multi-aspect article representation

OnlinePublIn modern days, making recommendation for news articles poses a great challenge due to vast amount of online information. However, providing personalized recommendations from news articles, which are the sources of condense textual information is not a trivial task. A recommendation system needs to understand both the textual information of a news article, and the user contexts in terms of long-term and temporary preferences via the user’s historic records. Unfortunately, many existing methods do not possess the capability to meet such need. In this work, we propose a neural deep news recommendation model called CupMar, that not only is able to learn the user-profile representation in different contexts, but also is able to leverage the multi-aspects properties of a news article to provide accurate, personalized news recommendations to users. The main components of our CupMar approach include the News Encoder and the User-Profile Encoder. Specifically, the News Encoder uses multiple properties such as news category, knowledge entity, title and body content with advanced neural network layers to derive informative news representation, while the User-Profile Encoder looks through a user’s browsed news, infers both of her long-term and recent preference contexts to encode a user representation, and finds the most relevant candidate news for her. We evaluate our CupMar model with extensive experiments on the popular Microsoft News Dataset (MIND), and demonstrate the strong performance of our approach.Dai Hoang Tran, Quan Z. Sheng, Wei Emma Zhang, Nguyen H. Tran, Nguyen Lu Dang Kho

The accuracy of prenatal diagnosis of selective fetal growth restriction with second trimester Doppler ultrasound in monochorionic diamniotic twin pregnancies

Background Selective fetal restriction growth (sFGR) is one of the common diseases of monochorionic diamniotic (MCDA) twin pregnancies, resulting in many adverse outcomes. At present, second trimester ultrasonography is widely used in the prenatal diagnosis of sFGR, but the diagnostic effectiveness is still uncertain. The aim of this study is to assess the diagnostic accuracy of second trimester Doppler ultrasound measurements for sFGR. Methods A retrospective study included 280 pregnant women (118 with and 162 without sFGR) with MCDA pregnancies was conducted in the fetal medicine center from Leiden University Medical Center from January 2008 to December 2013. The women participating had already undergone an ultrasound examination in the second trimester. The postnatal criteria of sFGR was a single birth weight (BW) = 25% between two twins, while the BW of the smaller twin = 25%, UA pulsatility index (PI) of the smaller fetus > 95th percentile). According to the diagnosis of sFGR after birth, we evaluate diagnostic effectiveness of Doppler ultrasound in the second trimester for sFGR. Results Of these 280 participants, the mean age was 32.06 +/- 4.76 years. About 43.9% of pregnant women were primiparas. The ability of second trimester Doppler ultrasound to accurately diagnosed sFGR is 75.4%, missed diagnosis rate and the misdiagnosis rate were 24.6% and 10.5% respectively. The ROC curve indicated that the combination of AC discordance, EFW discordance, and small fetal UA blood flow was the best diagnostic indicator of sFGR in MCDA pregnancy with the AUC was 0.882 (95%CI, 0.839-0.926). Conclusions Second trimester Doppler and ultrasound measurements is an effective method for early prenatal diagnosis of sFGR. The combined indicator of AC discordance, EFW discordance, and the small fetal UA blood flow reaches highest diagnostic value.Developmen

Predicting secondary organic aerosol phase state and viscosity and its effect on multiphase chemistry in a regional-scale air quality model

Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acidcatalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (Tg), oxygen to carbon (O V C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4% of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported 70% in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 102 1012 Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity < 102 Pa s. Phase separation while in a liquid phase state, i.e., liquid liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution

Α-Pinene-Derived organic coatings on acidic sulfate aerosol impacts secondary organic aerosol formation from isoprene in a box model

Fine particulate matter (PM2.5) is known to have an adverse impact on public health and is an important climate forcer. Secondary organic aerosol (SOA) contributes up to 80% of PM2.5 worldwide and multiphase reactions are an important pathway to form SOA. Aerosol-phase state is thought to influence the reactive uptake of gas-phase precursors to aerosol particles by altering diffusion rates within particles. Current air quality models do not include the impact of diffusion-limiting organic coatings on SOA formation. This work examines how α-pinene-derived organic coatings change the predicted formation of SOA from the acid-catalyzed multiphase reactions of isoprene epoxydiols (IEPOX). A box model, with inputs provided from field measurements taken at the Look Rock (LRK) site in Great Smokey Mountains National Park during the 2013 Southern Oxidant and Aerosol Study (SOAS), was modified to incorporate the latest laboratory-based kinetic data accounting for organic coating influences. Including an organic coating influence reduced the modeled reactive uptake when relative humidity was in the 55–80% range, with predicted IEPOX-derived SOA being reduced by up to 33%. Only sensitivity cases with a large increase in Henry's Law values of an order of magnitude or more or in particle reaction rates resulted in the large statistically significant differences form base model performance. These results suggest an organic coating layer could have an impact on IEPOX-derived SOA formation and warrant consideration in regional and global scale models

Physics of Solar Prominences: I - Spectral Diagnostics and Non-LTE Modelling

This review paper outlines background information and covers recent advances made via the analysis of spectra and images of prominence plasma and the increased sophistication of non-LTE (ie when there is a departure from Local Thermodynamic Equilibrium) radiative transfer models. We first describe the spectral inversion techniques that have been used to infer the plasma parameters important for the general properties of the prominence plasma in both its cool core and the hotter prominence-corona transition region. We also review studies devoted to the observation of bulk motions of the prominence plasma and to the determination of prominence mass. However, a simple inversion of spectroscopic data usually fails when the lines become optically thick at certain wavelengths. Therefore, complex non-LTE models become necessary. We thus present the basics of non-LTE radiative transfer theory and the associated multi-level radiative transfer problems. The main results of one- and two-dimensional models of the prominences and their fine-structures are presented. We then discuss the energy balance in various prominence models. Finally, we outline the outstanding observational and theoretical questions, and the directions for future progress in our understanding of solar prominences.Comment: 96 pages, 37 figures, Space Science Reviews. Some figures may have a better resolution in the published version. New version reflects minor changes brought after proof editin

Detector Description and Performance for the First Coincidence Observations between LIGO and GEO

For 17 days in August and September 2002, the LIGO and GEO interferometer gravitational wave detectors were operated in coincidence to produce their first data for scientific analysis. Although the detectors were still far from their design sensitivity levels, the data can be used to place better upper limits on the flux of gravitational waves incident on the earth than previous direct measurements. This paper describes the instruments and the data in some detail, as a companion to analysis papers based on the first data.Comment: 41 pages, 9 figures 17 Sept 03: author list amended, minor editorial change

Measurement of the p-pbar -> Wgamma + X cross section at sqrt(s) = 1.96 TeV and WWgamma anomalous coupling limits

The WWgamma triple gauge boson coupling parameters are studied using p-pbar -> l nu gamma + X (l = e,mu) events at sqrt(s) = 1.96 TeV. The data were collected with the DO detector from an integrated luminosity of 162 pb^{-1} delivered by the Fermilab Tevatron Collider. The cross section times branching fraction for p-pbar -> W(gamma) + X -> l nu gamma + X with E_T^{gamma} > 8 GeV and Delta R_{l gamma} > 0.7 is 14.8 +/- 1.6 (stat) +/- 1.0 (syst) +/- 1.0 (lum) pb. The one-dimensional 95% confidence level limits on anomalous couplings are -0.88 < Delta kappa_{gamma} < 0.96 and -0.20 < lambda_{gamma} < 0.20.Comment: Submitted to Phys. Rev. D Rapid Communication

Measurement of the ttbar Production Cross Section in ppbar Collisions at sqrt{s} = 1.96 TeV using Kinematic Characteristics of Lepton + Jets Events

We present a measurement of the top quark pair ttbar production cross section in ppbar collisions at a center-of-mass energy of 1.96 TeV using 230 pb**{-1} of data collected by the DO detector at the Fermilab Tevatron Collider. We select events with one charged lepton (electron or muon), large missing transverse energy, and at least four jets, and extract the ttbar content of the sample based on the kinematic characteristics of the events. For a top quark mass of 175 GeV, we measure sigma(ttbar) = 6.7 {+1.4-1.3} (stat) {+1.6- 1.1} (syst) +/-0.4 (lumi) pb, in good agreement with the standard model prediction.Comment: submitted to Phys.Rev.Let