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

Synthesis and investigation of deoxyribonucleic acid/locked nucleic acid chimeric molecular beacons

To take full advantage of locked nucleic acid (LNA) based molecular beacons (LNA-MBs) for a variety of applications including analysis of complex samples and intracellular monitoring, we have systematically synthesized a series of DNA/LNA chimeric MBs and studied the effect of DNA/LNA ratio in MBs on their thermodynamics, hybridization kinetics, protein binding affinity and enzymatic resistance. It was found that the LNA bases in a MB stem sequence had a significant effect on the stability of the hair-pin structure. The hybridization rates of LNA-MBs were significantly improved by lowering the DNA/LNA ratio in the probe, and most significantly, by having a shared-stem design for the LNA-MB to prevent sticky-end pairing. It was found that only MB sequences with DNA/LNA alternating bases or all LNA bases were able to resist nonspecific protein binding and DNase I digestion. Additional results showed that a sequence consisting of a DNA stretch less than three bases between LNA bases was able to block RNase H function. This study suggested that a shared-stem MB with a 4 base-pair stem and alternating DNA/LNA bases is desirable for intracellular applications as it ensures reasonable hybridization rates, reduces protein binding and resists nuclease degradation for both target and probes. These findings have implications on the design of LNA molecular probes for intracellular monitoring application, disease diagnosis and basic biological studies

UniVIE: A Unified Label Space Approach to Visual Information Extraction from Form-like Documents

Existing methods for Visual Information Extraction (VIE) from form-like documents typically fragment the process into separate subtasks, such as key information extraction, key-value pair extraction, and choice group extraction. However, these approaches often overlook the hierarchical structure of form documents, including hierarchical key-value pairs and hierarchical choice groups. To address these limitations, we present a new perspective, reframing VIE as a relation prediction problem and unifying labels of different tasks into a single label space. This unified approach allows for the definition of various relation types and effectively tackles hierarchical relationships in form-like documents. In line with this perspective, we present UniVIE, a unified model that addresses the VIE problem comprehensively. UniVIE functions using a coarse-to-fine strategy. It initially generates tree proposals through a tree proposal network, which are subsequently refined into hierarchical trees by a relation decoder module. To enhance the relation prediction capabilities of UniVIE, we incorporate two novel tree constraints into the relation decoder: a tree attention mask and a tree level embedding. Extensive experimental evaluations on both our in-house dataset HierForms and a publicly available dataset SIBR, substantiate that our method achieves state-of-the-art results, underscoring the effectiveness and potential of our unified approach in advancing the field of VIE

Selective Solar Harvesting Windows for Full‐Spectrum Utilization

Smart windows can selectively regulate excess solar radiation to reduce heating and cooling energy consumption in the built environment. However, the inevitable dissipation of ultraviolet and near-infrared into waste heat results in inefficient solar utilization. Herein, a dual-band selective solar harvesting (SSH) window is developed to realize full-spectrum utilization. A transparent photovoltaic, converting ultraviolet into electricity, and a transparent solar absorber, converting near-infrared into thermal energy, are integrated and coupled with a ventilation system to extract heat for indoor use. Compared with common transparent photovoltaics, the SSH window increases solar harvesting efficiency up to threefold while maintaining a considerable visible transmittance. Simulations suggest that the SSH window, besides generating electricity, delivers energy savings by over 30% higher than common smart windows. This is the first integration of transparent photovoltaic and transparent solar absorber into a window, which may open up a new avenue for the development of energy-efficient buildings

High performance interrogation by a composite-double-probe-pulse for ultra-weak FBG array

We propose and experimentally demonstrate a technique using a composite-double-probe-pulse (CDPP) to eliminate the effect of polarization fading for phase-sensitive optical time-domain reflectometry (Φ-OTDR) based on ultra-weak FBG (UWFBG) array. The CDPP is composed of two optical pulses whose spatial interval is equal to twice the spatial interval of adjacent UWFBGs in the UWFBG array. One optical pulse is a long optical pulse, and the other optical pulse is composed of two continuous short optical pulses, whose polarization states are orthogonal to each other. The width of the short pulse is equal to half of the width of the normal pulse and their frequencies are different from the long pulse. By using such a method to perform the sensing for the UWFBG array, distributed quantitative measurement can be realized with only direct detection scheme and the influence of polarization fading in the demodulation of signal is thoroughly eliminated

Chinese Medicines Improve Perimenopausal Symptoms Induced by Surgery, Chemoradiotherapy, or Endocrine Treatment for Breast Cancer

The application of surgery, chemoradiotherapy, and endocrine treatment successfully increases survival rates of breast cancer patients. However, perimenopausal symptoms, the main side effects of these treatments, often afflict patients and reduce their quality of life. Perimenopausal symptoms include vasomotor symptoms, sleep problems, arthromuscular symptoms, and osteoporosis. Currently, there are no satisfactory treatments for perimenopausal symptoms that result from these treatments. Therefore, alternative and complementary therapies including herbal medicines represented by Chinese medicines (CMs), acupuncture, massage, and psychotherapy are increasingly being expected and explored. In this paper, we review the effects and potentials of several CM formulae, along with some active ingredients or fractions from CMs, Chinese herbal extracts, and other herbal medicines, which have drawn attention for improving perimenopausal symptoms in breast cancer patients. We also elaborate their possible mechanisms. Moreover, further studies for evaluation of standardized clinical efficacy should be scientifically well-designed and continuously performed to investigate the efficacy and mechanisms of CMs for perimenopausal symptoms due to breast cancer therapy. The safety and value of estrogen-containing CMs for breast cancer should also be clarified