Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration

We propose a novel end-to-end document understanding model called SeRum (SElective Region Understanding Model) for extracting meaningful information from document images, including document analysis, retrieval, and office automation. Unlike state-of-the-art approaches that rely on multi-stage technical schemes and are computationally expensive, SeRum converts document image understanding and recognition tasks into a local decoding process of the visual tokens of interest, using a content-aware token merge module. This mechanism enables the model to pay more attention to regions of interest generated by the query decoder, improving the model's effectiveness and speeding up the decoding speed of the generative scheme. We also designed several pre-training tasks to enhance the understanding and local awareness of the model. Experimental results demonstrate that SeRum achieves state-of-the-art performance on document understanding tasks and competitive results on text spotting tasks. SeRum represents a substantial advancement towards enabling efficient and effective end-to-end document understanding.Comment: Accepted to ICCV 2023 main conferenc

Comprehensive analysis of clinical significance of stem-cell related factors in renal cell cancer

<p>Abstract</p> <p>Background</p> <p>C-MYC, LIN28, OCT4, KLF4, NANOG and SOX2 are stem cell related factors. We detected whether these factors express in renal cell carcinoma (RCC) tissues to study their correlations with the clinical and pathological characteristics.</p> <p>Methods</p> <p>The expressions of c-MYC, LIN28, SOX2, KLF4, OCT4 and NANOG in 30 RCC patients and 5 non-RCC patients were detected with quantitative real-time reverse transcription-PCR (qRT-PCR). The data were analyzed with Wilcoxon signed rank sum test and x²test.</p> <p>Results</p> <p>In RCC group, c-MYC expression was significantly higher in RCC tissues compared with normal tissues (P < 0.05). The expression levels of OCT4, KLF4, NANOG and SOX2 were significantly lower in RCC tissues compared with normal tissues (P < 0.05). LIN28 expression level was not significant. No difference was observed when it comes to clinical and pathological characteristics such as gender, age, tumor size, cTNM classification and differentiation status (P > 0.05). Also the expression levels of all above factors were not significantly changed in non-RCC group (P > 0.05).</p> <p>Conclusions</p> <p>The present analysis strongly suggests that altered expression of several stem cell related factors may play different roles in RCC. C-MYC may function as an oncogene and OCT4, KLF4, NANOG and SOX2 as tumor suppressors.</p

Drug-loaded hybrid hydrogels for sonodynamic-chemodyanmic therapy and tumor metastasis suppression

Introduction: Although various therapies have been adopted to treat cancer, metastasis of tumor cells still is a big challenge that compromises therapeutic benefits.Methods: We herein report an injectable drug-loaded hybrid hydrogel that can achieve sonodynamic therapy (SDT) and chemodyanmic therapy (CDT) combined action and suppression of tumor metastasis. This alginate (ALG)-based hydrogel (termed as AMPS) contains manganese dioxide (MnO2) nanoparticles as the CDT agents, an organic polymer as the sonosensitizer, and a SIS3 drug as metastasis inhibitor.Results: AMPS is formed via the chelation of ALG by Ca2+ in tumor microenvironment, in which MnO2 nanoparticles mediate CDT via Fenton-like reaction and the organic polymers enable SDT under ultrasound (US) irradiation by generating singlet oxygen (1O2), allowing for combinational action of CDT and SDT. In addition, SIS3 is released from AMPS hydrogels to inhibit the metastasis of tumor cells. As such, the AMPS enables a combinational action of SDT and CDT to greatly inhibit the growths of subcutaneous tumors in living mice and also completely suppress the tumor metastasis in lungs and livers.Conclusion: This study thus offers a hybrid hydrogel platform for combinational therapy and metastasis suppression simultaneously

Chirality selective magnon-phonon hybridization and magnon-induced chiral phonons in a layered zigzag antiferromagnet

Two-dimensional (2D) magnetic systems possess versatile magnetic order and can host tunable magnons carrying spin angular momenta. Recent advances show angular momentum can also be carried by lattice vibrations in the form of chiral phonons. However, the interplay between magnons and chiral phonons as well as the details of chiral phonon formation in a magnetic system are yet to be explored. Here, we report the observation of magnon-induced chiral phonons and chirality selective magnon-phonon hybridization in a layered zigzag antiferromagnet (AFM) FePSe$_3$. With a combination of magneto-infrared and magneto-Raman spectroscopy, we observe chiral magnon polarons (chiMP), the new hybridized quasiparticles, at zero magnetic field. The hybridization gap reaches 0.25~meV and survives down to the quadrilayer limit. Via first principle calculations, we uncover a coherent coupling between AFM magnons and chiral phonons with parallel angular momenta, which arises from the underlying phonon and space group symmetries. This coupling lifts the chiral phonon degeneracy and gives rise to an unusual Raman circular polarization of the chiMP branches. The observation of coherent chiral spin-lattice excitations at zero magnetic field paves the way for angular momentum-based hybrid phononic and magnonic devices

RUNX3 Mediates Suppression of Tumor Growth and Metastasis of Human CCRCC by Regulating Cyclin Related Proteins and TIMP-1

Here we presented that the expression of RUNX3 was significantly decreased in 75 cases of clear cell renal cell carcinoma (CCRCC) tissues (p<0.05). Enforced RUNX3 expression mediated 786-O cells to exhibit inhibition of growth, G1 cell-cycle arrest and metastasis in vitro, and to lost tumorigenicity in nude mouse model in vivo. RUNX3-induced growth suppression was found partially to regulate various proteins, including inhibition of cyclinD1, cyclinE, cdk2, cdk4 and p-Rb, but increase of p27Kip1, Rb and TIMP-1. Therefore, RUNX3 had the function of inhibiting the proliferative and metastatic abilities of CCRCC cells by regulating cyclins and TIMP1

An energy method for buckling behavior analysis of functionally graded carbon nanotube-reinforced composite sandwich structures

The present work aims to investigate the buckling performance of sandwich structure of functionally graded carbon nanotube-reinforced composite (FG-CNTRC). Through first-order shear deformation theory, an analytical model for the sandwich structure of FG-CNTRC was established. The governing equation for the prediction of the buckling performance of the sandwich structure of FG-CNTRC was obtained through energy method. There was analytical solution that can satisfy both boundary conditions. The theoretical model and method were verified by literature analysis, and the influence of each parameter on the buckling performance was evaluated and performed on the basis of the corroborated model. The findings can lay a solid foundation of the design and application of the sandwich structure of FG-CNTRC

Investigation of Photoelectrochemical Performance under the Piezoelectric Effect Based on Different Zinc Oxide Morphologies

Recently, the piezoelectric effect has been widely used in photoelectrochemical (PEC) water splitting, and the morphology of the piezoelectric material is a critical factor affecting the piezo-photoelectrochemical water splitting performance. Herein, we explored the mechanism of the piezo-photoelectrochemical performance of zinc oxide (ZnO) that is affected by the morphology. Firstly, three different ZnO nanostructures (nanosheets, nanorods, and nanospheres) were synthesized by the electrodeposition, hydrothermal, and sol-gel methods, respectively. Then, the measurements of PEC water splitting performance under the piezoelectric effect revealed a 3-fold increase for the ZnO nanosheets, a 1.4-fold increase for the nanorods, and a 1.2-fold increase for the nanospheres compared to no piezoelectric effect. Finally, finite element simulation showed that nanosheets generated the highest piezoelectric potential (0.6 V), followed by nanorods (0.2 V), and nanospheres the lowest (0.04 V). Thus, among the three morphologies, the ZnO nanosheets exhibited a great improvement in PEC performance under the piezoelectric effect. The great improvement is due to the non-axial vertical homogeneous growth of the ZnO nanosheets, subjecting them to the highest effective deformation stress, which enables the ZnO nanosheets to produce the highest piezoelectric potential to accelerate the carrier separation and limit the recombination of photoelectrons and holes. This work serves as a guide for developing various photoelectrodes that are used in piezo-photoelectrochemical water splitting

Direct C–H Allylation of <i>N</i>‑Acyl/Sulfonyl Tetrahydroisoquinolines and Analogues

A highly efficient direct C–H allylation reaction at the α position of <i>N</i>-acyl/sulfonyl tetrahydro­isoquinolines under mild conditions was developed. The reaction was also suitable for allylation of other protected nitrogen-containing heterocycles. Several interesting transformations of the products into valuable synthetic intermediates are featured with the successful total synthesis of (±)-crispine A

Locate Then Generate: Bridging Vision and Language with Bounding Box for Scene-Text VQA

In this paper, we propose a novel multi-modal framework for Scene Text Visual Question Answering (STVQA), which requires models to read scene text in images for question answering. Apart from text or visual objects, which could exist independently, scene text naturally links text and visual modalities together by conveying linguistic semantics while being a visual object in an image simultaneously. Different to conventional STVQA models which take the linguistic semantics and visual semantics in scene text as two separate features, in this paper, we propose a paradigm of "Locate Then Generate" (LTG), which explicitly unifies this two semantics with the spatial bounding box as a bridge connecting them. Specifically, at first, LTG locates the region in an image that may contain the answer words with an answer location module (ALM) consisting of a region proposal network and a language refinement network, both of which can transform to each other with one-to-one mapping via the scene text bounding box. Next, given the answer words selected by ALM, LTG generates a readable answer sequence with an answer generation module (AGM) based on a pre-trained language model. As a benefit of the explicit alignment of the visual and linguistic semantics, even without any scene text based pre-training tasks, LTG can boost the absolute accuracy by +6.06% and +6.92% on the TextVQA dataset and the ST-VQA dataset respectively, compared with a non-pre-training baseline. We further demonstrate that LTG effectively unifies visual and text modalities through the spatial bounding box connection, which is underappreciated in previous methods