Detector-Free Structure from Motion

We propose a new structure-from-motion framework to recover accurate camera poses and point clouds from unordered images. Traditional SfM systems typically rely on the successful detection of repeatable keypoints across multiple views as the first step, which is difficult for texture-poor scenes, and poor keypoint detection may break down the whole SfM system. We propose a new detector-free SfM framework to draw benefits from the recent success of detector-free matchers to avoid the early determination of keypoints, while solving the multi-view inconsistency issue of detector-free matchers. Specifically, our framework first reconstructs a coarse SfM model from quantized detector-free matches. Then, it refines the model by a novel iterative refinement pipeline, which iterates between an attention-based multi-view matching module to refine feature tracks and a geometry refinement module to improve the reconstruction accuracy. Experiments demonstrate that the proposed framework outperforms existing detector-based SfM systems on common benchmark datasets. We also collect a texture-poor SfM dataset to demonstrate the capability of our framework to reconstruct texture-poor scenes. Based on this framework, we take $\textit{first place}$ in Image Matching Challenge 2023.Comment: Project page: https://zju3dv.github.io/DetectorFreeSfM

The influence of different metal atoms on the performance of metalloporphyrin-based sensor reaction with propanol

Density functional theory (DFT) method was carried out to investigate the molecular interaction between metalloporphyrin-based sensor and propanol. The relative energies were used to determine the most stable state of metalloporphyrin and its complexes at three different spin states for further theoretical studies. The low-spin states were found to be the most stable states for cobalt porphyrin (CoP), tin porphyrin (Sn), and zinc porphyrin (ZnP) before exposure to propanol and CoP, SnP, ZnP, iron porphyrin (FeP), ruthenium porphyrin (RuP) after exposure to propanol. The intermediate-spin state was found to be the most stable states for the other metalloporphyrins and their complexes, except for manganese porphyrin (MnP) after exposure to propanol. The calculated binding energies were shown the following order for metalloporphyrin-based sensor-binding propanol: MnP>ZnP>CoP>RuP>SnP>FeP>AgP>CuP. This calculated result may be useful for the theoretical design of metalloporphyrin-based sensor for propanol determination and perhaps other analyte

Immune checkpoints: new insights into the pathogenesis of thyroid eye disease

Thyroid eye disease (TED) is a disfiguring autoimmune disease characterized by changes in the orbital tissues and is caused by abnormal thyroid function or thyroid-related antibodies. It is the ocular manifestation of Graves’ disease. The expression of thyroid-stimulating hormone receptor (TSHR) and the insulin-like growth factor-1 receptor (IGF-1 R) on the cell membrane of orbital fibroblasts (OFs) is responsible for TED pathology. Excessive inflammation is caused when these receptors in the orbit are stimulated by autoantibodies. CD34+ fibrocytes, found in the peripheral blood and orbital tissues of patients with TED, express immune checkpoints (ICs) like MHC II, B7, and PD-L1, indicating their potential role in presenting antigens and regulating the immune response in TED pathogenesis. Immune checkpoint inhibitors (ICIs) have significantly transformed cancer treatment. However, it can also lead to the occurrence of TED in some instances, suggesting the abnormality of ICs in TED. This review will examine the overall pathogenic mechanism linked to the immune cells of TED and then discuss the latest research findings on the immunomodulatory role of ICs in the development and pathogenesis of TED. This will offer fresh perspectives on the study of pathogenesis and the identification of potential therapeutic targets

Text classification in fair competition law violations using deep learning

IntroductionEnsuring fair competition through manual review is a complex undertaking. This paper introduces the utilization of Long Short-Term Memory (LSTM) neural networks and TextCNN to establish a text classifier for classifying and reviewing normative documents.MethodsThe experimental dataset used consists of policy measure samples provided by the antitrust division of the Guangdong Market Supervision Administration. We conduct a comparative analysis of the performance of LSTM and TextCNN classification models.ResultsIn three classification experiments conducted without an enhanced experimental dataset, the LSTM classifier achieved an accuracy of 95.74%, while the TextCNN classifier achieved an accuracy of 92.7% on the test set. Conversely, in three classification experiments utilizing an enhanced experimental dataset, the LSTM classifier demonstrated an accuracy of 96.36%, and the TextCNN classifier achieved an accuracy of 96.19% on the test set.DiscussionThe experimental results highlight the effectiveness of LSTM and TextCNN in classifying and reviewing normative documents. The superior accuracy achieved with the enhanced experimental dataset underscores the potential of these models in real-world applications, particularly in tasks involving fair competition review

A density functional theory study of metalloporphyrin derivatives act as fluorescent sensor for rapid evaluation of trimethylamine

A fluorescent sensor based on metalloporphyrin was developed for trimethylamine (TMA) evaluation. Density functional theory (DFT) has been performed to investigate the design mechanism of fluorescent sensor. Fourteen metalloporphyrin (MP) models were selected to find the influence of metal atoms and substituent groups on the binding performance of fluorescent sensor. The optimized geometry structures, relative energies, mulliken charges, spin densities, and four frontier molecular orbitals together with binding energies of these fluorescent sensors were investigated. AgP sensor has the lowest relative energies before and after exposure to TMA, which make AgP sensor better than the others to go through more than one pathway. Binding energy results revealed that the metalloporphyrin sensors with different metal atoms and substituent groups cause remarkable changes in TMA binding performances. Thus, theoretical investigations can be used to extend the fluorescent sensor in to TMA related analytes in different detection requirements, and perhaps other molecule

Inflammation-Related Cytokines of Aqueous Humor in Acute Primary Angle-Closure Eyes

PURPOSE. To measure levels of various inflammation-related cytokines in the aqueous humor of patients with acute primary angle-closure (APAC) and senile cataract. METHODS. Aqueous humor samples were prospectively collected from 23 eyes (12 eyes with current APAC and 11 eyes with previous APAC) of 23 APAC patients and 15 eyes of 15 cataract patients. The levels of 15 inflammation-related cytokines in the aqueous humor of APAC and cataract subjects were measured by using the multiplex bead immunoassay technique. Data on patient demographics and preoperative intraocular pressure (IOP) were also collected for correlation analysis

Using Genome and Transcriptome Data From African-Ancestry Female Participants To Identify Putative Breast Cancer Susceptibility Genes

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3\u27 UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P \u3c 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P \u3c 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations