Robust Table Detection and Structure Recognition from Heterogeneous Document Images

We introduce a new table detection and structure recognition approach named RobusTabNet to detect the boundaries of tables and reconstruct the cellular structure of each table from heterogeneous document images. For table detection, we propose to use CornerNet as a new region proposal network to generate higher quality table proposals for Faster R-CNN, which has significantly improved the localization accuracy of Faster R-CNN for table detection. Consequently, our table detection approach achieves state-of-the-art performance on three public table detection benchmarks, namely cTDaR TrackA, PubLayNet and IIIT-AR-13K, by only using a lightweight ResNet-18 backbone network. Furthermore, we propose a new split-and-merge based table structure recognition approach, in which a novel spatial CNN based separation line prediction module is proposed to split each detected table into a grid of cells, and a Grid CNN based cell merging module is applied to recover the spanning cells. As the spatial CNN module can effectively propagate contextual information across the whole table image, our table structure recognizer can robustly recognize tables with large blank spaces and geometrically distorted (even curved) tables. Thanks to these two techniques, our table structure recognition approach achieves state-of-the-art performance on three public benchmarks, including SciTSR, PubTabNet and cTDaR TrackB2-Modern. Moreover, we have further demonstrated the advantages of our approach in recognizing tables with complex structures, large blank spaces, as well as geometrically distorted or even curved shapes on a more challenging in-house dataset.Comment: Accepted by Pattern Recognition on 27 Aug. 202

Joint Layout Analysis, Character Detection and Recognition for Historical Document Digitization

In this paper, we propose an end-to-end trainable framework for restoring historical documents content that follows the correct reading order. In this framework, two branches named character branch and layout branch are added behind the feature extraction network. The character branch localizes individual characters in a document image and recognizes them simultaneously. Then we adopt a post-processing method to group them into text lines. The layout branch based on fully convolutional network outputs a binary mask. We then use Hough transform for line detection on the binary mask and combine character results with the layout information to restore document content. These two branches can be trained in parallel and are easy to train. Furthermore, we propose a re-score mechanism to minimize recognition error. Experiment results on the extended Chinese historical document MTHv2 dataset demonstrate the effectiveness of the proposed framework.Comment: 6 pages, 6 figure

GridFormer: Towards Accurate Table Structure Recognition via Grid Prediction

All tables can be represented as grids. Based on this observation, we propose GridFormer, a novel approach for interpreting unconstrained table structures by predicting the vertex and edge of a grid. First, we propose a flexible table representation in the form of an MXN grid. In this representation, the vertexes and edges of the grid store the localization and adjacency information of the table. Then, we introduce a DETR-style table structure recognizer to efficiently predict this multi-objective information of the grid in a single shot. Specifically, given a set of learned row and column queries, the recognizer directly outputs the vertexes and edges information of the corresponding rows and columns. Extensive experiments on five challenging benchmarks which include wired, wireless, multi-merge-cell, oriented, and distorted tables demonstrate the competitive performance of our model over other methods.Comment: ACMMM202

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network

Deep sparse networks are widely investigated as a neural network architecture for prediction tasks with high-dimensional sparse features, with which feature interaction selection is a critical component. While previous methods primarily focus on how to search feature interaction in a coarse-grained space, less attention has been given to a finer granularity. In this work, we introduce a hybrid-grained feature interaction selection approach that targets both feature field and feature value for deep sparse networks. To explore such expansive space, we propose a decomposed space which is calculated on the fly. We then develop a selection algorithm called OptFeature, which efficiently selects the feature interaction from both the feature field and the feature value simultaneously. Results from experiments on three large real-world benchmark datasets demonstrate that OptFeature performs well in terms of accuracy and efficiency. Additional studies support the feasibility of our method.Comment: NeurIPS 2023 poste

Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy

<p>Abstract</p> <p>Background</p> <p>Proteomics may help us better understand the changes of multiple proteins involved in oncogenesis and progression of prostate cancer(PCa) and identify more diagnostic and prognostic biomarkers. The aim of this study was to screen biomarkers of PCa by the proteomics analysis using isobaric tags for relative and absolute quantification(iTRAQ).</p> <p>Methods</p> <p>The patients undergoing prostate biopsies were classified into 3 groups according to pathological results: benign prostate hyperplasia (BPH, n = 20), PCa(n = 20) and BPH with local prostatic intraepithelial neoplasm(PIN, n = 10). Then, all the specimens from these patients were analyzed by iTRAQ and two-dimensional liquid chromatography-tandem mass spectrometry (2DLC-MS/MS). The Gene Ontology(GO) function and the transcription regulation networks of the differentially expressed were analyzed by MetaCore software. Western blotting and Immunohistochemical staining were used to analyze the interesting proteins.</p> <p>Result</p> <p>A total of 760 proteins were identified from 13787 distinct peptides, including two common proteins that enjoy clinical application: prostate specific antigen (PSA) and prostatic acid phosphatase(PAP). Proteins that expressed differentially between PCa and BPH group were further analyzed. Compared with BPH, 20 proteins were significantly differentially up-regulated (>1.5-fold) while 26 were significantly down-regulated in PCa(<0.66-fold). In term of GO database, the differentially expressed proteins were divided into 3 categories: cellular component(CC), molecular function (MF) and biological process(BP). The top 5 transcription regulation networks of the differentially expressed proteins were initiated through activation of SP1, p53, YY1, androgen receptor(AR) and c-Myc The overexpression of periostin in PCa was verified by western blotting and immunohistochemical staining.</p> <p>Conclusion</p> <p>Our study indicates that the iTRAQ technology is a new strategy for global proteomics analysis of the tissues of PCa. A significant up-regulation of periostin in PCa compared to BPH may provide clues for not only a promising biomarker for the prognosis of PCa but also a potential target for therapeutical intervention.</p

Effects of parenteral nutrition of ω-3 polyunsaturated fatty acid, arginine and glutamine on cellular immune status of patients following liver cancer surgery

Purpose: To study the effects of parenteral nutrition (TPN), ω-3  polyunsaturated fatty acid (PUFA), Larginine (Arg), and glutamine on cellular immunity of patients who have done the liver cancer (LC) surgery.Methods: Seventy-five (75) LC patients were randomly divided into 5  groups (A - E; 15 cases each), group A, B, C, D and E, in which patients were treated with TPN, TPN + fish oil, TPN + Arg, TPN + glutamine, and TPN + ω-3 PUFA + Arg + glutamine, respectively. Before and after surgery, CD3 +, CD4 + and CD8 + were measured by antibody-sensitized erythrocyte rosette test, and IL-6, IL-10 and TNF-a were assayed with double-antibody sandwich enzyme-linked immunoassay (DAS-ELISA). IgA and IgM were measured nephelometrically.Results: The levels of CD3 +, CD4 + and CD8 + in group A showed no  obvious change after surgery (p &gt; 0.05). However, CD3 + and CD4 +  increased in groups B, C and D, while CD8 + decreased in group E (p &lt; 0.05). IL-6 in group E was lower than that in any of the other four groups (p &lt; 0.05). IL-10 in group A was lower than that in groups B, C and D, but lower than in group E (p &lt; 0.05). The levels of TNF-a in groups B and C were lower than those in group A, but higher than that in group E (p &lt; 0.05) but lower than in group D. IgA in group E was higher than in the other groups (p &lt; 0.05), while IgM level in group E was lower than in groups A, B and C (p &lt; 0.05).Conclusion: Immunosuppressive status and cellular immunity of patients  after liver cancer surgery may be improved by a combination therapy of TPN, ω-3 PUFAs, Arg and glutamine.Keywords: Polyunsaturated fatty acid, Arginine, Glutamine, Parenteral nutrition, Hepatoma, Cellular immunit

A frustrated quantum spin-{\boldmath s} model on the Union Jack lattice with spins {\boldmath s>1/2}

The zero-temperature phase diagrams of a two-dimensional frustrated quantum antiferromagnetic system, namely the Union Jack model, are studied using the coupled cluster method (CCM) for the two cases when the lattice spins have spin quantum number $s=1$ and $s=3/2$. The system is defined on a square lattice and the spins interact via isotropic Heisenberg interactions such that all nearest-neighbour (NN) exchange bonds are present with identical strength $J_{1}>0$, and only half of the next-nearest-neighbour (NNN) exchange bonds are present with identical strength $J_{2} \equiv \kappa J_{1} > 0$. The bonds are arranged such that on the $2 \times 2$ unit cell they form the pattern of the Union Jack flag. Clearly, the NN bonds by themselves (viz., with $J_{2}=0$) produce an antiferromagnetic N\'{e}el-ordered phase, but as the relative strength $\kappa$ of the frustrating NNN bonds is increased a phase transition occurs in the classical case ($s \rightarrow \infty$) at $\kappa^{\rm cl}_{c}=0.5$ to a canted ferrimagnetic phase. In the quantum cases considered here we also find strong evidence for a corresponding phase transition between a N\'{e}el-ordered phase and a quantum canted ferrimagnetic phase at a critical coupling $\kappa_{c_{1}}=0.580 \pm 0.015$ for $s=1$ and $\kappa_{c_{1}}=0.545 \pm 0.015$ for $s=3/2$. In both cases the ground-state energy $E$ and its first derivative $dE/d\kappa$ seem continuous, thus providing a typical scenario of a second-order phase transition at $\kappa=\kappa_{c_{1}}$, although the order parameter for the transition (viz., the average ground-state on-site magnetization) does not go to zero there on either side of the transition.Comment: 1

Frustrated 3-Dimensional Quantum Spin Liquid in CuHpCl

Inelastic neutron scattering measurements are reported for the quantum antiferromagnetic material Cu_2(C_5H_12N_2)_2Cl_4 (CuHpCl). The magnetic excitation spectrum forms a band extending from 0.9 meV to 1.4 meV. The spectrum contains two modes that disperse throughout the a-c plane of the monoclinic unit cell with less dispersion along the unique b-axis. Simple arguments based on the measured dispersion relations and the crystal structure show that a spin ladder model is inappropriate for describing CuHpCl. Instead, it is proposed that hydrogen bond mediated exchange interactions between the bi-nuclear molecular units yield a three-dimensional interacting spin system with a recurrent triangular motif similar to the Shastry-Sutherland Model (SSM). Model independent analysis based on the first moment sum rule shows that at least four distinct spin pairs are strongly correlated and that two of these, including the dimer bond of the corresponding SSM, are magnetically frustrated. These results show that CuHpCl should be classified as a frustration induced three dimensional quantum spin liquid.Comment: 13 pages, 17 figures (Color) ReSubmitted to Phys. Rev. B 9/21/2001 resubmission has new content email comments to [email protected] or [email protected]

Using force spectroscopy analysis to improve the properties of the hairpin probe

The sensitivity of hairpin-probe-based fluorescence resonance energy transfer (FRET) analysis was sequence-dependent in detecting single base mismatches with different positions and identities. In this paper, the relationship between the sequence-dependent effect and the discrimination sensitivity of a single base mismatch was systematically investigated by fluorescence analysis and force spectroscopy analysis. The same hairpin probe was used. The uneven fluorescence analysis sensitivity was obviously influenced by the guanine-cytosine (GC) contents as well as the location of the mismatched base. However, we found that force spectroscopy analysis distinguished itself, displaying a high and even sensitivity in detecting differently mismatched targets. This could therefore be an alternative and novel way to minimize the sequence-dependent effect of the hairpin probe. The advantage offered by force spectroscopy analysis could mainly be attributed to the percentage of rupture force reduction, which could be directly and dramatically influenced by the percentage of secondary structure disruption contributed by each mismatched base pair, regardless of its location and identity. This yes-or-no detection mechanism should both contribute to a comprehensive understanding of the sensitivity source of different mutation analyses and extend the application range of hairpin probes