A Survey of Document-Level Information Extraction

Document-level information extraction (IE) is a crucial task in natural language processing (NLP). This paper conducts a systematic review of recent document-level IE literature. In addition, we conduct a thorough error analysis with current state-of-the-art algorithms and identify their limitations as well as the remaining challenges for the task of document-level IE. According to our findings, labeling noises, entity coreference resolution, and lack of reasoning, severely affect the performance of document-level IE. The objective of this survey paper is to provide more insights and help NLP researchers to further enhance document-level IE performance

Automated interpretation of congenital heart disease from multi-view echocardiograms

Congenital heart disease (CHD) is the most common birth defect and the leading cause of neonate death in China. Clinical diagnosis can be based on the selected 2D key-frames from five views. Limited by the availability of multi-view data, most methods have to rely on the insufficient single view analysis. This study proposes to automatically analyze the multi-view echocardiograms with a practical end-to-end framework. We collect the five-view echocardiograms video records of 1308 subjects (including normal controls, ventricular septal defect (VSD) patients and atrial septal defect (ASD) patients) with both disease labels and standard-view key-frame labels. Depthwise separable convolution-based multi-channel networks are adopted to largely reduce the network parameters. We also approach the imbalanced class problem by augmenting the positive training samples. Our 2D key-frame model can diagnose CHD or negative samples with an accuracy of 95.4\%, and in negative, VSD or ASD classification with an accuracy of 92.3\%. To further alleviate the work of key-frame selection in real-world implementation, we propose an adaptive soft attention scheme to directly explore the raw video data. Four kinds of neural aggregation methods are systematically investigated to fuse the information of an arbitrary number of frames in a video. Moreover, with a view detection module, the system can work without the view records. Our video-based model can diagnose with an accuracy of 93.9\% (binary classification), and 92.1\% (3-class classification) in a collected 2D video testing set, which does not need key-frame selection and view annotation in testing. The detailed ablation study and the interpretability analysis are provided.Comment: Published in Medical Image Analysi

A gate-programmable van der Waals metal-ferroelectric-semiconductor memory

Ferroelecticity, one of the keys to realize nonvolatile memories owing to the remanent electric polarization, has been an emerging phenomenon in the two-dimensional (2D) limit. Yet the demonstrations of van der Waals (vdW) memories using 2D ferroelectric materials as an ingredient are very limited. Especially, gate-tunable ferroelectric vdW memristive device, which holds promises in future neuromorphic applications, remains challenging. Here, we show a prototype gate-programmable memory by vertically assembling graphite, CuInP2S6, and MoS2 layers into a metal-ferroelectric-semiconductor architecture. The resulted devices exhibit two-terminal switchable electro-resistance with on-off ratios exceeding 105 and long-term retention, akin to a conventional memristor but strongly coupled to the ferroelectric characteristics of the CuInP2S6 layer. By controlling the top gate, Fermi level of MoS2 can be set inside (outside) of its band gap to quench (enable) the memristive behaviour, yielding a three-terminal gate programmable nonvolatile vdW memory. Our findings pave the way for the engineering of ferroelectric-mediated memories in future implementations of nanoelectronics

Secretory leukocyte protease inhibitor as a novel predictive biomarker in patients with diabetic kidney disease

BackgroundSecretory leukocyte protease inhibitor (SLPI) is a multifunctional protein involved in the chronic inflammatory process, implicated in the pathogenesis of diabetic kidney disease (DKD). However, its potential as a diagnostic and prognostic biomarker of DKD has yet to be evaluated. This study explored the clinical utility of SLPI in the diagnosis and prognosis of renal endpoint events in patients with DKD.MethodsA multi-center cross-sectional study comprised of 266 patients with DKD and a predictive cohort study comprised of 120 patients with stage IV DKD conducted between December 2016 and January 2022. The clinical parameters were collected for statistical analysis, a multivariate Cox proportional hazards model was used to evaluate the independent risk factors for renal endpoints.ResultsSerum SLPI levels gradually increased with DKD progression (p<0.01). A significant correlation was observed between serum SLPI levels and renal function in patients with DKD. The mean follow-up duration in this cohort study was 2.32 ± 1.30 years. Multivariate Cox regression analysis showed SLPI levels≥51.61ng/mL (HR=2.95, 95% CI[1.55, 5.60], p<0.01), 24h urinary protein levels≥3500 mg/24h (HR=3.02, 95% CI[1.66, 5.52], p<0.01), Alb levels<30g/l (HR=2.19, 95% CI[1.12, 4.28], p<0.05), HGB levels<13g/dl (HR=3.18, 95% CI[1.49, 6.80], p<0.01), and urea levels≥7.1 mmol/L (HR=8.27, 95% CI[1.96, 34.93], p<0.01) were the independent risk factors for renal endpoint events in DKD patients.ConclusionsSerum SLPI levels increased with DKD progression and were associated with clinical parameters of DKD. Moreover, elevated SLPI levels showed potential prognostic value for renal endpoint events in individuals with DKD. These findings validate the results of previous studies on SLPI in patients with DKD and provide new insights into the role of SLPI as a biomarker for the diagnosis and prognosis of DKD that require validation

Probing the fractional quantum Hall phases in valley-layer locked bilayer MoS2_{2}

Semiconducting transition-metal dichalcogenides (TMDs) exhibit high mobility, strong spin-orbit coupling, and large effective masses, which simultaneously leads to a rich wealth of Landau quantizations and inherently strong electronic interactions. However, in spite of their extensively explored Landau levels (LL) structure, probing electron correlations in the fractionally filled LL regime has not been possible due to the difficulty of reaching the quantum limit. Here, we report evidence for fractional quantum Hall (FQH) states at filling fractions 4/5 and 2/5 in the lowest LL of bilayer MoS$_{2}$, manifested in fractionally quantized transverse conductance plateaus accompanied by longitudinal resistance minima. We further show that the observed FQH states sensitively depend on the dielectric and gate screening of the Coulomb interactions. Our findings establish a new FQH experimental platform which are a scarce resource: an intrinsic semiconducting high mobility electron gas, whose electronic interactions in the FQH regime are in principle tunable by Coulomb-screening engineering, and as such, could be the missing link between atomically thin graphene and semiconducting quantum wells.Comment: 10 pages, 4 figure

Room temperature 2D ferromagnetism in few-layered 1TT-CrTe2_{2}

Spin-related electronics using two dimensional (2D) van der Waals (vdW) materials as a platform are believed to hold great promise for revolutionizing the next generation spintronics. Although many emerging new phenomena have been unravelled in 2D electronic systems with spin long-range orderings, the scarcely reported room temperature magnetic vdW material has thus far hindered the related applications. Here, we show that intrinsic ferromagnetically aligned spin polarization can hold up to 316 K in a metallic phase of 1$T$-CrTe$_{2}$ in the few-layer limit. This room temperature 2D long range spin interaction may be beneficial from an itinerant enhancement. Spin transport measurements indicate an in-plane room temperature negative anisotropic magnetoresistance (AMR) in few-layered CrTe$_{2}$, but a sign change in the AMR at lower temperature, with -0.6$\%$ at 300 K and +5$\%$ at 10 K, respectively. This behavior may originate from the specific spin polarized band structure of CrTe$_{2}$. Our findings provide insights into magnetism in few-layered CrTe$_{2}$, suggesting potential for future room temperature spintronic applications of such 2D vdW magnets.Comment: 9 Pages, 4 Figure

Heterogeneous Institutional Stock Ownership and Firms' Dividend Policies

Agent theory suggests that cash dividends can reduce information asymmetry, but high dividends might harm the company's investment and its growth potential, resulting in less capital gain. This study confirms the positive relationship between institutional investors’ shareholding and firms’ dividend payouts in the Chinese market. Through vector autoregression, we find that institutional investors influence firms to pay more dividends during the period from 2003 to 2021. We also find that not all Institutions are dividend seeker, especially in the absence of capital gains tax in China's capital market, the institutions that are more professional with better research ability focus on capital gain and their shareholdings will not impact the firm’s dividend. While other institutions like banks, insurance companies, and trusts may suffer higher agency cost, and tend to require more dividends from firms. The results confirm the exit theories like agency theory, catering theory, and signal hypothesis from the perspective of heterogeneous institutions. Considering that China has a large number of state-owned enterprises that can be used to verify the agency theory or catering theory in dividend payout policies, we further test the relationship on state-owned firms and private-owned firms. We find that the relationship between heterogeneous institutional investors and firms’ dividend policies only exists in those private-owned firms, because those state-owned firms’ executives and ownership are both governments