QueryForm: A Simple Zero-shot Form Entity Query Framework

Zero-shot transfer learning for document understanding is a crucial yet under-investigated scenario to help reduce the high cost involved in annotating document entities. We present a novel query-based framework, QueryForm, that extracts entity values from form-like documents in a zero-shot fashion. QueryForm contains a dual prompting mechanism that composes both the document schema and a specific entity type into a query, which is used to prompt a Transformer model to perform a single entity extraction task. Furthermore, we propose to leverage large-scale query-entity pairs generated from form-like webpages with weak HTML annotations to pre-train QueryForm. By unifying pre-training and fine-tuning into the same query-based framework, QueryForm enables models to learn from structured documents containing various entities and layouts, leading to better generalization to target document types without the need for target-specific training data. QueryForm sets new state-of-the-art average F1 score on both the XFUND (+4.6%~10.1%) and the Payment (+3.2%~9.5%) zero-shot benchmark, with a smaller model size and no additional image input.Comment: Accepted to Findings of ACL 202

Ultralow Thermal Conductivity, Multiband Electronic Structure and High Thermoelectric Figure of Merit in TlCuSe

The entanglement of lattice thermal conductivity, electrical conductivity, and Seebeck coefficient complicates the process of optimizing thermoelectric performance in most thermoelectric materials. Semiconductors with ultralow lattice thermal conductivities and high power factors at the same time are scarce but fundamentally interesting and practically important for energy conversion. Herein, an intrinsic p-type semiconductor TlCuSe that has an intrinsically ultralow thermal conductivity (0.25 W m−1 K−1), a high power factor (11.6 µW cm−1 K−2), and a high figure of merit, ZT (1.9) at 643 K is described. The weak chemical bonds, originating from the filled antibonding orbitals p-d* within the edge-sharing CuSe4 tetrahedra and long TlSe bonds in the PbClF-type structure, in conjunction with the large atomic mass of Tl lead to an ultralow sound velocity. Strong anharmonicity, coming from Tl+ lone-pair electrons, boosts phonon–phonon scattering rates and further suppresses lattice thermal conductivity. The multiband character of the valence band structure contributing to power factor enhancement benefits from the lone-pair electrons of Tl+ as well, which modify the orbital character of the valence bands, and pushes the valence band maximum off the Γ-point, increasing the band degeneracy. The results provide new insight on the rational design of thermoelectric materials

Detecting Variability in Massive Astronomical Time-Series Data I: application of an infinite Gaussian mixture model

We present a new framework to detect various types of variable objects within massive astronomical time-series data. Assuming that the dominant population of objects is non-variable, we find outliers from this population by using a non-parametric Bayesian clustering algorithm based on an infinite GaussianMixtureModel (GMM) and the Dirichlet Process. The algorithm extracts information from a given dataset, which is described by six variability indices. The GMM uses those variability indices to recover clusters that are described by six-dimensional multivariate Gaussian distributions, allowing our approach to consider the sampling pattern of time-series data, systematic biases, the number of data points for each light curve, and photometric quality. Using the Northern Sky Variability Survey data, we test our approach and prove that the infinite GMM is useful at detecting variable objects, while providing statistical inference estimation that suppresses false detection. The proposed approach will be effective in the exploration of future surveys such as GAIA, Pan-Starrs, and LSST, which will produce massive time-series data.Comment: accepted for publication in MNRA

Microwave-induced plasma boosted microsecond-pulse glow discharge optical emission spectrometry

A microsecond-pulse (mu s-pulse) glow discharge (GD) source boosted by a microwave-induced plasma (MIP) has been developed and studied for optical emission spectrometry (OES), The excitation processes of the tandem GD source were investigated, The analytical characteristics of the GD-OES source in the presence and absence of the MIP were compared, including the operating parameters, signal-to-background ratios (S/B) and relative standard deviation (RSD), The results show that under a relatively low discharge pressure (<180 Pa), the mu s-pulse GD can couple fairly well with the MIP and emit intense analytical lines, When the GD source is operated under a pressure higher than 200 Pa, tao emission peaks appear, independent in time, for a given resonance atomic line, because sample atoms are independently structurally excited, first by the mu s-pulse GD and then by the MIP. The time interval between the tao peaks for Zn I 213.8 nm is longer than that for Cu I 324.7 nm, which is believed to be due to the faster diffusing velocity of copper atoms, When the mu s-pulse GD lamp is operated under a gas pressure higher than 220 Pa, the ion population is so high that Cu II ionic line at 224.7 nm 'becomes' two peaks because of a possible self-absorption. The results show that the supplementary nse of an MIP can eliminate the self-absorption of ionic and atomic lines, When the mu s-pulse GD source is coupled with the MTP, S/Bs are improved by a factor of more than one order of magnitude for several analytical lines. A short-term RSD of 0.2% is achieved for the 'mu s-pulse GD+MIP' configuration compared with that of 1.0% for 'mu s-pulse GD only' mode. The experimental results show that the MIP boosted mu s-pulse GD is a promising technique for solid sample and surface analysis

Reduction of liver stiffness following resolution of acute flares of chronic hepatitis B

Background: Measuring liver stiffness is becoming more popular as a non-invasive tool for assessing liver fibrosis. Aim: To assess the effect of severe hepatitis B flare on liver stiffness and determine factors that correlate with liver stiffness measurements. Methods: Twenty-nine patients with severe hepatitis B flare (ALT > 10 × upper limit of normal) were followed up for 1 year. Serial transient elastography was performed at the time of flare, 3-6, and 12 months after flare. Results: At the time of flare, the median liver stiffness was 16.8 kPa, with no patients having normal liver stiffness (<6 kPa). There was a significant decrease in liver stiffness from baseline to 3-6 months (16.8 vs. 7.9 kPa, respectively, P < 0.001), and a further smaller decline from 3-6 to 12 months (7.9 vs. 6.9 kPa, respectively, P = 0.039). By 12 months, 10 (34%) had normalized their liver stiffness. Baseline parameters which correlated with liver stiffness include bilirubin, ALT, albumin, prothrombin time and platelet levels (all P < 0.05). Conclusion: Liver stiffness was increased in patients with severe hepatitis B flares, with return to near normal levels by 6 months. Transient elastography for proper assessment of liver fibrosis should be performed at least 6 months after flare. © 2010 The Author(s).published_or_final_versionSpringer Open Choice, 31 May 201

Prenatal Detection of Aneuploidy and Imbalanced Chromosomal Arrangements by Massively Parallel Sequencing

Fetal chromosomal abnormalities are the most common reasons for invasive prenatal testing. Currently, G-band karyotyping and several molecular genetic methods have been established for diagnosis of chromosomal abnormalities. Although these testing methods are highly reliable, the major limitation remains restricted resolutions or can only achieve limited coverage on the human genome at one time. The massively parallel sequencing (MPS) technologies which can reach single base pair resolution allows detection of genome-wide intragenic deletions and duplication challenging karyotyping and microarrays as the tool for prenatal diagnosis. Here we reported a novel and robust MPS-based method to detect aneuploidy and imbalanced chromosomal arrangements in amniotic fluid (AF) samples. We sequenced 62 AF samples on Illumina GAIIx platform and with averagely 0.01× whole genome sequencing data we detected 13 samples with numerical chromosomal abnormalities by z-test. With up to 2× whole genome sequencing data we were able to detect microdeletion/microduplication (ranged from 1.4 Mb to 37.3 Mb of 5 samples from chorionic villus sampling (CVS) using SeqSeq algorithm. Our work demonstrated MPS is a robust and accurate approach to detect aneuploidy and imbalanced chromosomal arrangements in prenatal samples

Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined