61 research outputs found
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
Removal of Methyl Parathion from Artificial Off-Gas Using a Bioreactor Containing a Constructed Microbial Consortium
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
Recommended from our members
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
Biological technologies for the removal of sulfur containing compounds from waste streams: bioreactors and microbial characteristics
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
- …