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Fei Li

Publications and source records attributed to Fei Li.

At least 145 records · Page 8Linked to original sources
arXiv2023

PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation

Pathologic myopia (PM) is a common blinding retinal degeneration suffered by highly myopic population. Early screening of this condition can reduce the damage caused by the associated fundus lesions and therefore prevent vision loss. Automated diagnostic tools based on artificial intelligence methods can benefit this process by aiding clinicians to identify disease signs or to screen mass populations using color fundus photographs as inputs. This paper provides insights about PALM, our open fundus imaging dataset for pathological myopia recognition and anatomical structure annotation. Our databases comprises 1200 images with associated labels for the pathologic myopia category and manual annotations of the optic disc, the position of the fovea and delineations of lesions such as patchy retinal atrophy (including peripapillary atrophy) and retinal detachment. In addition, this paper elaborates on other details such as the labeling process used to construct the database, the quality and characteristics of the samples and provides other relevant usage notes.

eess.IV↗
arXiv2023

LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model

Universally modeling all typical information extraction tasks (UIE) with one generative language model (GLM) has revealed great potential by the latest study, where various IE predictions are unified into a linearized hierarchical expression under a GLM. Syntactic structure information, a type of effective feature which has been extensively utilized in IE community, should also be beneficial to UIE. In this work, we propose a novel structure-aware GLM, fully unleashing the power of syntactic knowledge for UIE. A heterogeneous structure inductor is explored to unsupervisedly induce rich heterogeneous structural representations by post-training an existing GLM. In particular, a structural broadcaster is devised to compact various latent trees into explicit high-order forests, helping to guide a better generation during decoding. We finally introduce a task-oriented structure fine-tuning mechanism, further adjusting the learned structures to most coincide with the end-task's need. Over 12 IE benchmarks across 7 tasks our system shows significant improvements over the baseline UIE system. Further in-depth analyses show that our GLM learns rich task-adaptive structural bias that greatly resolves the UIE crux, the long-range dependence issue and boundary identifying. Source codes are open at https://github.com/ChocoWu/LasUIE.

cs.CL↗
arXiv2023

The ALMA Survey of 70 μm Dark High-mass Clumps in Early Stages (ASHES). VIII. Dynamics of Embedded Dense Cores

We present the dynamical properties of 294 cores embedded in twelve IRDCs observed as part of the ASHES Survey. Protostellar cores have higher gas masses, surface densities, column densities, and volume densities than prestellar cores, indicating core mass growth from the prestellar to the protostellar phase. We find that ~80% of cores with virial parameter ($α$) measurements are gravitationally bound ($α$< 2). We also find an anti-correlation between the mass and the virial parameter of cores, with massive cores having on average lower virial parameters. Protostellar cores are more gravitationally bound than prestellar cores, with an average virial parameter of 1.2 and 1.5, respectively. The observed non-thermal velocity dispersion (from N$_{2}$D$^{+}$ or DCO$^{+}$) is consistent with simulations in which turbulence is continuously injected, whereas the core-to-core velocity dispersion is neither in agreement with driven nor decaying turbulence simulations. We find no significant increment in the line velocity dispersion from prestellar to protostellar cores, suggesting that dense gas within the core traced by these deuterated molecules is not yet severely affected by turbulence injected from outflow activity at the early evolutionary stages traced in ASHES. The most massive cores are strongly self-gravitating and have greater surface density, Mach number, and velocity dispersion than cores with lower masses. Dense cores have not significant velocity shifts relative to their low-density envelopes, suggesting that dense cores are co-moving with their envelopes. We conclude that the observed core properties are more in line with predictions of ``clump-fed" scenarios rather than with ``core-fed" scenarios.

astro-ph.GA↗
arXiv2023

Accurate simulation of direct laser acceleration in a laser wakefield accelerator

In a laser wakefield accelerator (LWFA), an intense laser pulse excites a plasma wave that traps and accelerates electrons to relativistic energies. When the pulse overlaps the accelerated electrons, it can enhance the energy gain through direct laser acceleration (DLA) by resonantly driving the betatron oscillations of the electrons in the plasma wave. The particle-in-cell (PIC) algorithm, although often the tool of choice to study DLA, contains inherent errors due to numerical dispersion and the time staggering of the electric and magnetic fields. Further, conventional PIC implementations cannot reliably disentangle the fields of the plasma wave and laser pulse, which obscures interpretation of the dominant acceleration mechanism. Here, a customized field solver that reduces errors from both numerical dispersion and time staggering is used in conjunction with a field decomposition into azimuthal modes to perform PIC simulations of DLA in an LWFA. Comparisons with traditional PIC methods, model equations, and experimental data show improved accuracy with the customized solver and convergence with an order-of-magnitude fewer cells. The azimuthal-mode decomposition reveals that the most energetic electrons receive comparable energy from DLA and LWFA.

physics.plasm-ph↗
arXiv2023

Dialogue State Distillation Network with Inter-slot Contrastive Learning for Dialogue State Tracking

In task-oriented dialogue systems, Dialogue State Tracking (DST) aims to extract users' intentions from the dialogue history. Currently, most existing approaches suffer from error propagation and are unable to dynamically select relevant information when utilizing previous dialogue states. Moreover, the relations between the updates of different slots provide vital clues for DST. However, the existing approaches rely only on predefined graphs to indirectly capture the relations. In this paper, we propose a Dialogue State Distillation Network (DSDN) to utilize relevant information of previous dialogue states and migrate the gap of utilization between training and testing. Thus, it can dynamically exploit previous dialogue states and avoid introducing error propagation simultaneously. Further, we propose an inter-slot contrastive learning loss to effectively capture the slot co-update relations from dialogue context. Experiments are conducted on the widely used MultiWOZ 2.0 and MultiWOZ 2.1 datasets. The experimental results show that our proposed model achieves the state-of-the-art performance for DST.

cs.CL↗
arXiv2023

Implementation and performances of the IPbus protocol for the JUNO Large-PMT readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. Thanks to the tight requirements on its optical and radio-purity properties, it will be able to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range from tens of keV to hundreds of MeV. A key requirement for the success of the experiment is an unprecedented 3% energy resolution, guaranteed by its large active mass (20 kton) and the use of more than 20,000 20-inch photo-multiplier tubes (PMTs) acquired by high-speed, high-resolution sampling electronics located very close to the PMTs. As the Front-End and Read-Out electronics is expected to continuously run underwater for 30 years, a reliable readout acquisition system capable of handling the timestamped data stream coming from the Large-PMTs and permitting to simultaneously monitor and operate remotely the inaccessible electronics had to be developed. In this contribution, the firmware and hardware implementation of the IPbus based readout protocol will be presented, together with the performances measured on final modules during the mass production of the electronics.

physics.ins-det↗
arXiv2023

Superconductivity in Li8Au electride

Located at crystal voids, interstitial anion electrons (IAEs) have diverse topologies, which may be tuned to achieve new properties. Elucidating the role of IAEs in electron-phonon coupling (EPC), and using it to design new electride superconductors, leads to the current prediction of superconducting Li8Au at high pressure. We suggest that the occurence of high-temperature superconductivity in electrides requires high-symmetry structures with hydrogen-like cages, an electron acceptor element to balance charges, and isolated IAEs coupled with medium-frequency vibrations. The uniquely designed Li8Au electride has a NaCl-type (B1) lattice, with atomic Au and cubic Li8 cages as bases. Isolated IAEs are formed at the cage centers, with extra charges taken up by Au. These octahedrally coordinated IAEs have a p-orbital-like attribute and are strongly coupled with atomic vibrations in the Li8 cages. The strong EPC in Li8Au results in a calculated Tc of 73.1 K at 250 GPa, which is the highest Tc reported to date for all the electrides. A slight substitutional Pt doping can enhance the Tc of Li8Au to exceed liquid nitrogen temperature.

cond-mat.supr-con↗
arXiv2023

Lithospheric loading model for large impact basin where mantle plug presents

Lithosphere is an outer rigid part of the terrestrial body, usually consisting of the crust and part of the mantle. Characterizing the physical properties of the lithosphere is critical in investigating its evolution. By modeling mass-related loads within the lithosphere, physical parameters such as the elastic thickness of the lithosphere can be inferred from gravity and topography data. In the impact basin region, however, the low topography-gravity correlation and the sharp change in admittance from negative to positive within a narrow spheric harmonic degree make this model inapplicable. In this work, we incorporated mantle uplift structures commonly formed in impact basin regions into the lithospheric loading model. The crustal-mantle boundary of this mantle uplift structure is inferred from the global crustal thickness model. The gravity anomaly of the deflected lithosphere is calculated at the surface and crustal-mantle boundary, then the theoretical gravity admittance and correlation can be compared with the observed data. We sampled parameters using this mantle loading model at Argyre and Isidis basin on Mars with a novel crustal thickness model from the InSight mission. Our work suggests that proper modelling of the impact-induced load is critical to understanding the physical properties of the planetary lithosphere in the basin region.

astro-ph.EP↗
arXiv2023

Mass testing of the JUNO experiment 20-inch PMTs readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose, large size, liquid scintillator experiment under construction in China. JUNO will perform leading measurements detecting neutrinos from different sources (reactor, terrestrial and astrophysical neutrinos) covering a wide energy range (from 200 keV to several GeV). This paper focuses on the design and development of a test protocol for the 20-inch PMT underwater readout electronics, performed in parallel to the mass production line. In a time period of about ten months, a total number of 6950 electronic boards were tested with an acceptance yield of 99.1%.

physics.ins-det↗
arXiv2022

REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screening

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge -- Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application.

eess.IV↗
arXiv2022

GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges

Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarkers to indicate glaucoma suspected. Clinically, it is often recommended to take both of the screenings for a more accurate and reliable diagnosis. However, although numerous algorithms are proposed based on fundus images or OCT volumes in computer-aided diagnosis, there are still few methods leveraging both of the modalities for the glaucoma assessment. Inspired by the success of Retinal Fundus Glaucoma Challenge (REFUGE) we held previously, we set up the Glaucoma grAding from Multi-Modality imAges (GAMMA) Challenge to encourage the development of fundus \& OCT-based glaucoma grading. The primary task of the challenge is to grade glaucoma from both the 2D fundus images and 3D OCT scanning volumes. As part of GAMMA, we have publicly released a glaucoma annotated dataset with both 2D fundus color photography and 3D OCT volumes, which is the first multi-modality dataset for glaucoma grading. In addition, an evaluation framework is also established to evaluate the performance of the submitted methods. During the challenge, 1272 results were submitted, and finally, top-10 teams were selected to the final stage. We analysis their results and summarize their methods in the paper. Since all these teams submitted their source code in the challenge, a detailed ablation study is also conducted to verify the effectiveness of the particular modules proposed. We find many of the proposed techniques are practical for the clinical diagnosis of glaucoma. As the first in-depth study of fundus \& OCT multi-modality glaucoma grading, we believe the GAMMA Challenge will be an essential starting point for future research.

cs.CV↗
arXiv2022

Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery

Self-supervised representation learning (SSL) on biomedical networks provides new opportunities for drug discovery. However, how to effectively combine multiple SSL models is still challenging and has been rarely explored. Therefore, we propose multi-task joint strategies of self-supervised representation learning on biomedical networks for drug discovery, named MSSL2drug. We design six basic SSL tasks inspired by various modality features including structures, semantics, and attributes in heterogeneous biomedical networks. Importantly, fifteen combinations of multiple tasks are evaluated by a graph attention-based multi-task adversarial learning framework in two drug discovery scenarios. The results suggest two important findings. (1) Combinations of multimodal tasks achieve the best performance compared to other multi-task joint models. (2) The local-global combination models yield higher performance than random two-task combinations when there are the same size of modalities. Therefore, we conjecture that the multimodal and local-global combination strategies can be treated as the guideline of multi-task SSL for drug discovery.

cs.LG↗
arXiv2022

Validation and integration tests of the JUNO 20-inch PMTs readout electronics

The Jiangmen Underground Neutrino Observatory (JUNO) is a large neutrino detector currently under construction in China. JUNO will be able to study the neutrino mass ordering and to perform leading measurements detecting terrestrial and astrophysical neutrinos in a wide energy range, spanning from 200 keV to several GeV. Given the ambitious physics goals of JUNO, the electronic system has to meet specific tight requirements, and a thorough characterization is required. The present paper describes the tests performed on the readout modules to measure their performances.

physics.ins-det↗
arXiv2022

TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags

So far, discontinuous named entity recognition (NER) has received increasing research attention and many related methods have surged such as hypergraph-based methods, span-based methods, and sequence-to-sequence (Seq2Seq) methods, etc. However, these methods more or less suffer from some problems such as decoding ambiguity and efficiency, which limit their performance. Recently, grid-tagging methods, which benefit from the flexible design of tagging systems and model architectures, have shown superiority to adapt for various information extraction tasks. In this paper, we follow the line of such methods and propose a competitive grid-tagging model for discontinuous NER. We call our model TOE because we incorporate two kinds of Tag-Oriented Enhancement mechanisms into a state-of-the-art (SOTA) grid-tagging model that casts the NER problem into word-word relationship prediction. First, we design a Tag Representation Embedding Module (TREM) to force our model to consider not only word-word relationships but also word-tag and tag-tag relationships. Concretely, we construct tag representations and embed them into TREM, so that TREM can treat tag and word representations as queries/keys/values and utilize self-attention to model their relationships. On the other hand, motivated by the Next-Neighboring-Word (NNW) and Tail-Head-Word (THW) tags in the SOTA model, we add two new symmetric tags, namely Previous-Neighboring-Word (PNW) and Head-Tail-Word (HTW), to model more fine-grained word-word relationships and alleviate error propagation from tag prediction. In the experiments of three benchmark datasets, namely CADEC, ShARe13 and ShARe14, our TOE model pushes the SOTA results by about 0.83%, 0.05% and 0.66% in F1, demonstrating its effectiveness.

cs.CL↗
arXiv2022

Entity-centered Cross-document Relation Extraction

Relation Extraction (RE) is a fundamental task of information extraction, which has attracted a large amount of research attention. Previous studies focus on extracting the relations within a sentence or document, while currently researchers begin to explore cross-document RE. However, current cross-document RE methods directly utilize text snippets surrounding target entities in multiple given documents, which brings considerable noisy and non-relevant sentences. Moreover, they utilize all the text paths in a document bag in a coarse-grained way, without considering the connections between these text paths.In this paper, we aim to address both of these shortages and push the state-of-the-art for cross-document RE. First, we focus on input construction for our RE model and propose an entity-based document-context filter to retain useful information in the given documents by using the bridge entities in the text paths. Second, we propose a cross-document RE model based on cross-path entity relation attention, which allow the entity relations across text paths to interact with each other. We compare our cross-document RE method with the state-of-the-art methods in the dataset CodRED. Our method outperforms them by at least 10% in F1, thus demonstrating its effectiveness.

cs.CL↗
arXiv2022

Impact of LHC probes of SUSY and recent measurement of $(g-2)_μ$ on $\mathbb{Z}_3$-NMSSM

It is well known that excessively heavy supersymmetric particles (sparticles) are disfavored to explain the $(g-2)_μ$ anomaly, but some people overlook that moderately light sparticles are also disfavored by the LHC probes of supersymmetry. We take the Next-to-Minimal Supersymmetric Standard Model as an example to emphasize the latter point. It is found that, if the theory is required to explain the anomaly at $2σ$ level and meanwhile keep consistent with the LHC results, the following lower bounds may be set: $\tan β\gtrsim 20$, $|M_1| \gtrsim 275~{\rm GeV}$, $M_2 \gtrsim 300~{\rm GeV}$, $μ\gtrsim 460~{\rm GeV}$, $m_{\tildeμ_L} \gtrsim 310~{\rm GeV}$, and $m_{\tildeμ_R} \gtrsim 350~{\rm GeV}$, where $M_1$ and $M_2$ denote gaugino masses, $μ$ represents the Higgsino mass, and $m_{\tildeμ_L}$ and $m_{\tildeμ_R}$ are the mass of Smuons with $L$ and $R$ denoting their dominant chiral component. This observation has significant impacts on dark matter (DM) physics, e.g., the popular $Z$- and Higgs-funnel regions have been excluded, and the Bino-dominated neutralino DM has to co-annihilate with the Wino-dominated electroweakinos (in most cases) and/or Smuons (in few cases) to obtain the correct density. It is also inferred that these conclusions should apply to the Minimal Supersymmetric Standard Model since the underlying physics for the bounds are the same.

hep-ph↗
arXiv2022

The ALMA Survey of 70 $μ\rm m$ Dark High-mass Clumps in Early Stages (ASHES). VII: Chemistry of Embedded Dense Cores

We present a study of chemistry toward 294 dense cores in 12 molecular clumps using the data obtained from the ALMA Survey of 70 $μ\rm m$ dark High-mass clumps in Early Stages (ASHES). We identified 97 protostellar cores and 197 prestellar core candidates based on the detection of outflows and molecular transitions of high upper energy levels ($E_{u}/k > 45$ K). The detection rate of the N$_{2}$D$^{+}$ emission toward the protostellar cores is 38%, which is higher than 9% for the prestellar cores, indicating that N$_{2}$D$^{+}$ does not exclusively trace prestellar cores. The detection rates of the DCO$^{+}$ emission are 35% for the prestellar cores and 49% for the protostellar cores, which are higher than those of N$_{2}$D$^{+}$, implying that DCO$^{+}$ appears more frequently than N$_{2}$D$^{+}$ in both prestellar and protostellar cores. Both N$_{2}$D$^{+}$ and DCO$^{+}$ abundances appear to decrease from the prestellar to protostellar stage. The DCN, C$_{2}$D and $^{13}$CS emission lines are rarely seen in the dense cores of early evolutionary phases. The detection rate of the H$_{2}$CO emission toward dense cores is 52%, three times higher than that of CH$_{3}$OH (17%). In addition, the H$_{2}$CO detection rate, abundance, line intensities, and line widths increase with the core evolutionary status, suggesting that the H$_{2}$CO line emission is sensitive to protostellar activity.

astro-ph.GA↗