A Survey of Natural Language Generation

This paper offers a comprehensive review of the research on Natural Language Generation (NLG) over the past two decades, especially in relation to data-to-text generation and text-to-text generation deep learning methods, as well as new applications of NLG technology. This survey aims to (a) give the latest synthesis of deep learning research on the NLG core tasks, as well as the architectures adopted in the field; (b) detail meticulously and comprehensively various NLG tasks and datasets, and draw attention to the challenges in NLG evaluation, focusing on different evaluation methods and their relationships; (c) highlight some future emphasis and relatively recent research issues that arise due to the increasing synergy between NLG and other artificial intelligence areas, such as computer vision, text and computational creativity.Comment: Accepted by ACM Computing Survey (CSUR) 202

Optimal suppression strategy for capacitor voltage ripples of hybrid MMCs under unbalanced grid voltages

Submodule (SM) capacitor voltage ripples in modular multilevel converters (MMCs) can be suppressed by harmonic injection strategy, which can reduce the volume and cost of MMCs. The existing methods using the dual harmonic injection strategy for hybrid MMCs only consider steady-state conditions. Harmonic injection strategies for unbalanced grid voltage conditions only use single harmonic injection and can be applied for single-phase faults. To address the above issues, this paper proposes an optimal dual harmonic injection of second-order harmonic current and third-order harmonic voltage strategy for hybrid MMCs. Firstly, the mathematical model of MMC under unbalanced grid voltages is established. Then the ripple characteristics of SM capacitor voltage are analyzed to reveal the relationship between the capacitor voltage and the arm power ripples. Based on the developed instantaneous arm power model, optimal harmonic injection parameters are calculated. A hybrid MMC simulation model is built in PSCAD/EMTDC to verify the effectiveness of the proposed strategy. The results show the excellent performance of the proposed strategy in suppressing the voltage ripples under unbalanced voltage conditions

Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization

Existing methods for CWS usually rely on a large number of labeled sentences to train word segmentation models, which are expensive and time-consuming to annotate. Luckily, the unlabeled data is usually easy to collect and many high-quality Chinese lexicons are off-the-shelf, both of which can provide useful information for CWS. In this paper, we propose a neural approach for Chinese word segmentation which can exploit both lexicon and unlabeled data. Our approach is based on a variant of posterior regularization algorithm, and the unlabeled data and lexicon are incorporated into model training as indirect supervision by regularizing the prediction space of CWS models. Extensive experiments on multiple benchmark datasets in both in-domain and cross-domain scenarios validate the effectiveness of our approach.Comment: 7 pages, 11 figures, accepted by the 2019 World Wide Web Conference (WWW '19

Kyphoplasty for thoracic and lumbar fractures with an intravertebral vacuum phenomenon in ankylosing spondylitis patients

BackgroundIntravertebral vacuum phenomenon (IVP) is a special sign after vertebral fractures, which is common in patients with ankylosing spondylitis (AS) and may indicate pseudarthrosis and bone nonunion that lead to spinal instability. The objective of this study is to evaluate the efficacy and safety of kyphoplasty (KP) in treating such types of vertebral fractures with AS.MethodsSixteen patients with AS suffering from thoracic or lumbar fractures with IVP received KP from 2015 to 2020 and were monitored for more than 1 year. The visual analog scale (VAS) score was used to evaluate back pain relief. The Oswestry Disability Index (ODI) questionnaire was used to assess the improvement of the patients' living quality. The anterior and middle vertebral height restoration ratio (AVH, MVH) and the kyphotic angle (KA) were used to evaluate the radiographic results.ResultsThe mean follow-up period was 20.8 months (12–28 months). The VAS and ODI significantly reduced at 3 days, 3 months after surgery, and at the last follow-up compared with the preoperative outcomes (p < 0.05). The AVH and MVH were significantly increased compared with the preoperative outcomes (p < 0.05). There was a significant correction in the KA between pre- and postoperative assessments (p < 0.05). Asymptomatic intradiscal polymethylmethacrylate (PMMA) cement leakage was found in two patients.ConclusionsFor thoracic or lumbar fractures with IVP in AS patients, KP may be safe and effective, which achieves pain relief and satisfying functional improvement, restores the anterior and middle height, and corrects the kyphotic angle of the fractured vertebra

Leaf structural traits vary with plant size in even-aged stands of Sapindus mukorossi

Sapindus mukorossi Gaertn., an important oleaginous woody plant, has garnered increasing research attention owing to its potential as a source of renewable energy (biodiesel). Leaf structural traits are closely related to plant size, and they affect the fruit yield and oil quality. However, plant size factors that predominantly contribute to leaf structural traits remain unknown. Therefore, the purpose of this study was to understand the associations between leaf structural traits and plant size factors in even-aged stands of S. mukorossi. Results showed that leaf length (LL) and leaf area (LA) markedly increased with the increasing diameter at breast height (DBH) and tree height (TH), although other leaf structural traits did not show noticeable changes. Difference in slopes also indicated that the degree of effect of plant size factors on leaf structural traits was in the order of TH > DBH. Leaf structural traits showed no systematic variation with crown width (CW). LA was significantly positively correlated with LL, leaf width (LW), LL/LW, and leaf thickness (LT) and was significantly but negatively correlated with leaf tissue density (LTD) and leaf dry mass content (LDMC). Specific leaf area showed a significantly negative correlation with LT, LDMC, and LTD. LTD showed a significantly positive correlation with LDMC, but a negative correlation with LT. The results were critical to understand the variability of leaf structural traits with plant size, can provide a theoretical foundation for further study in the relationship between leaf structural traits and fruit yield, and regulate leaf traits through artificial management measures to promote plant growth and fruit yield

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level