Ground-to-Aerial Person Search: Benchmark Dataset and Approach

In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named G2APS, which contains 31,770 images of 260,559 annotated bounding boxes for 2,644 identities appearing in both of the UAVs and ground surveillance cameras. To our knowledge, this is the first dataset for cross-platform intelligent surveillance applications, where the UAVs could work as a powerful complement for the ground surveillance cameras. To more realistically simulate the actual cross-platform Ground-to-Aerial surveillance scenarios, the surveillance cameras are fixed about 2 meters above the ground, while the UAVs capture videos of persons at different location, with a variety of view-angles, flight attitudes and flight modes. Therefore, the dataset has the following unique characteristics: 1) drastic view-angle changes between query and gallery person images from cross-platform cameras; 2) diverse resolutions, poses and views of the person images under 9 rich real-world scenarios. On basis of the G2APS benchmark dataset, we demonstrate detailed analysis about current two-step and end-to-end person search methods, and further propose a simple yet effective knowledge distillation scheme on the head of the ReID network, which achieves state-of-the-art performances on both of the G2APS and the previous two public person search datasets, i.e., PRW and CUHK-SYSU. The dataset and source code available on \url{https://github.com/yqc123456/HKD_for_person_search}.Comment: Accepted by ACM MM 202

Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion Models

Aspect-Based Sentiment Analysis (ABSA) stands as a crucial task in predicting the sentiment polarity associated with identified aspects within text. However, a notable challenge in ABSA lies in precisely determining the aspects' boundaries (start and end indices), especially for long ones, due to users' colloquial expressions. We propose DiffusionABSA, a novel diffusion model tailored for ABSA, which extracts the aspects progressively step by step. Particularly, DiffusionABSA gradually adds noise to the aspect terms in the training process, subsequently learning a denoising process that progressively restores these terms in a reverse manner. To estimate the boundaries, we design a denoising neural network enhanced by a syntax-aware temporal attention mechanism to chronologically capture the interplay between aspects and surrounding text. Empirical evaluations conducted on eight benchmark datasets underscore the compelling advantages offered by DiffusionABSA when compared against robust baseline models. Our code is publicly available at https://github.com/Qlb6x/DiffusionABSA.Comment: Accepted to LREC-COLING 2024, submission versio

SELECTOR: Heterogeneous graph network with convolutional masked autoencoder for multimodal robust prediction of cancer survival

Accurately predicting the survival rate of cancer patients is crucial for aiding clinicians in planning appropriate treatment, reducing cancer-related medical expenses, and significantly enhancing patients' quality of life. Multimodal prediction of cancer patient survival offers a more comprehensive and precise approach. However, existing methods still grapple with challenges related to missing multimodal data and information interaction within modalities. This paper introduces SELECTOR, a heterogeneous graph-aware network based on convolutional mask encoders for robust multimodal prediction of cancer patient survival. SELECTOR comprises feature edge reconstruction, convolutional mask encoder, feature cross-fusion, and multimodal survival prediction modules. Initially, we construct a multimodal heterogeneous graph and employ the meta-path method for feature edge reconstruction, ensuring comprehensive incorporation of feature information from graph edges and effective embedding of nodes. To mitigate the impact of missing features within the modality on prediction accuracy, we devised a convolutional masked autoencoder (CMAE) to process the heterogeneous graph post-feature reconstruction. Subsequently, the feature cross-fusion module facilitates communication between modalities, ensuring that output features encompass all features of the modality and relevant information from other modalities. Extensive experiments and analysis on six cancer datasets from TCGA demonstrate that our method significantly outperforms state-of-the-art methods in both modality-missing and intra-modality information-confirmed cases. Our codes are made available at https://github.com/panliangrui/Selector.Comment: Accepted on Computers in Biology and Medicin

Role of inflammation and immunity in vascular calcification: a bibliometric and visual analysis, 2000–2022

BackgroundIn recent years, a great deal of research has been done on vascular calcification (VC), and inflammation and immunity have been displayed to play important roles in the mechanism of VC. However, to date, no comprehensive or systematic bibliometric analyses have been conducted on this topic.MethodsArticles and reviews on the roles of inflammation and immunity in VC were obtained from the Web of Science Core Collection on August 5, 2022. Four scientometric software packages—HistCite, CiteSpace, VOSviewer, and R-bibliometrix—were used for the bibliometric and knowledge mapping analyses.ResultsThe obtained 1,868 papers were published in 627 academic journals by 9,595 authors of 2,217 institutions from 69 countries. The annual number of publications showed a clear growth trend. The USA and China were the most productive countries. Karolinska Institutet, Harvard University, and the University of Washington were the most active institutions. Stenvinkel P published the most articles, whereas Demer LL received the most citations. Atherosclerosis published the most papers, while Circulation was the most highly cited journal. The largest cluster among the 22 clusters, based on the analysis of co-citations, was osteo-/chondrogenic transdifferentiation. “Vascular calcification,” “inflammation,” “chronic kidney disease,” and “expression” were the main keywords in the field. The keyword “extracellular vesicle” attracted great attention in recent years with the strongest citation burst.ConclusionsOsteo-/chondrogenic transdifferentiation is the primary research topic in this field. Extracellular vesicles are expected to become a new research focus for exploring the inflammatory and immune mechanisms of VC

Development and validation of a predictive nomogram for lower extremity deep vein thrombosis dislodgement in orthopedic patients

ObjectiveTo analyze the risk factors of lower extremity deep venous thrombosis (DVT) detachment in orthopedic patients, and to establish a risk nomogram prediction model.MethodsThe clinical data of 334 patients with orthopedic DVT admitted to the Third Hospital of Hebei Medical University from January 2020 to July 2021 were retrospectively analyzed. General statistics included gender, age, BMI, thrombus detachment, inferior vena cava filter window type, filter implantation time, medical history, trauma history, operation, use of tourniquet, thrombectomy, anesthesia mode, anesthesia grade, operative position, blood loss during operation, blood transfusion, immobilization, use of anticoagulants, thrombus side, thrombus range, D-dimer content before filter implantation and during removal of inferior vena cava filter. Logistic regression was used to perform univariate and multivariate analysis on the possible factors of thrombosis detachment, screen out independent risk factors, establish a risk nomogram prediction model by variables, and internally verify the predictability and accuracy of the model.ResultsBinary logistic regression analysis showed that Short time window filter (OR = 5.401, 95% CI = 2.338–12.478), lower extremity operation (OR = 3.565, 95% CI = 1.553–8.184), use of tourniquet (OR = 3.871, 95% CI = 1.733–8.651), non-strict immobilization (OR = 3.207, 95% CI = 1.387–7.413), non-standardized anticoagulation (OR = 4.406, 95% CI = 1.868–10.390), distal deep vein thrombosis (OR = 2.212, 95% CI = 1.047–4.671) were independent risk factors for lower extremity DVT detachment in orthopedic patients (P < 0.05). Based on these six factors, a prediction model for the risk of lower extremity DVT detachment in orthopedic patients was established, and the risk prediction ability of the model was verified. The C-index of the nomogram model was 0.870 (95% CI: 0.822–0.919). The results indicate that the risk nomogram model has good accuracy in predicting the loss of deep venous thrombosis in orthopedic patients.ConclusionThe nomogram risk prediction model based on six clinical factors, including filter window type, operation condition, tourniquet use, braking condition, anticoagulation condition, and thrombosis range, has good predictive performance

Uniform design for the optimization of Al2O3 nanofilms produced by electrophoretic deposition

Surface modification by means of nanostructures is of interest to enhance boiling heat transfer in various applications including the organic Rankine cycle (ORC). With the goal of obtaining rough and dense aluminum oxide (Al2O3) nanofilms, the optimal combination of process parameters for electrophoretic deposition (EPD) based on the uniform design (UD) method is explored in this paper. The detailed procedures for the EPD process and UD method are presented. Four main influencing conditions controlling the EPD process were identified as nanofluid concentration, deposition time, applied voltage and suspension pH. A series of tests were carried out based on the UD experimental design. A regression model and statistical analysis were applied to the results. Sensitivity analyses of the effect of the four main parameters on the roughness and deposited mass of Al2O3 films were also carried out. The results showed that Al2O3 nanofilms were deposited compactly and uniformly on the substrate. Within the range of the experiments, the preferred combination of process parameters was determined to be nanofluid concentration of 2 wt.%, deposition time of 15 min, applied voltage of 23 V and suspension pH of 3, yielding roughness and deposited mass of 520.9 nm and 161.6 × 10− 4 g/cm2, respectively. A verification experiment was carried out at these conditions and gave values of roughness and deposited mass within 8% error of the expected ones as determined from the UD approach. It is concluded that uniform design is useful for the optimization of electrophoretic deposition requiring only 7 tests compared to 49 using the orthogonal design method

Prevention of cyclophosphamide-induced immune suppression by polysaccharides from Apocynum venetum flowers via enhancing immune response, reducing oxidative stress, and regulating gut microbiota in mice

IntroductionEmerging proof suggests that Apocynum venetum flowers polysaccharide (AVFP) has immunomodulatory effects in vitro. However, the action mechanism of AVFA is still unclear in vivo. The purpose of this study is to probe into the potential mechanism of AVFA in immunosuppressed mice by investigating organ index, cytokine levels, anti-oxidative stress capacity, transcriptomics, and gut microbiota.MethodsImmunocompromised mice induced by cyclophosphamide (CTX) were divided into six groups. The enzyme-labeled method, hematoxylin and eosin, transcriptomics, and high-throughput sequencing were used to detect the regulatory effects of AVFP on immunocompromised mice and the function of AVFP on the concentration of short-chain fatty acids (SCFAs) by high-performance liquid chromatography (HPLC) analysis. The Spearman correlation analysis was used to analyze the correlation between the intestinal microbiota and biochemical indexes.ResultsThe experimental results illustrated that AVFP has protective effects against CTX-induced immunosuppression in mice by prominently increasing the organ index and levels of anti-inflammatory factors in serum in addition to enhancing the antioxidant capacity of the liver. Meanwhile, it could also signally decrease the level of pro-inflammatory cytokines in serum, the activity of transaminase in serum, and the content of free radicals in the liver, and alleviate the spleen tissue damage induced by CTX. Transcriptomics results discovered that AVFP could play a role in immune regulation by participating in the NF-κB signaling pathway and regulating the immune-related genes Bcl3, Hp, Lbp, Cebpd, Gstp2, and Lcn2. Gut microbiota results illustrated that AVFP could increase the abundance of beneficial bacteria, reduce the abundance of harmful bacteria, and regulate the metabolic function of intestinal microorganisms while dramatically improving the content of SCFAs, modulating immune responses, and improving the host metabolism. The Spearman analysis further evaluated the association between intestinal microbiota and immune-related indicators.ConclusionThese findings demonstrated that AVFP could enhance the immune effects of the immunosuppressed mice and improve the body’s ability to resist oxidative stress

5-HT recruits distinct neurocircuits to inhibit hunger-driven and non-hunger-driven feeding

Funding Information: The investigators were supported by grants from the NIH (R01DK114279, R01DK109934, and R21NS108091 to QT; R01ES027544 and R01DK111436 to ZS; R00DK107008 to PX; R01DK109194 and R56DK109194 to QW; P01DK113954, R01DK115761, R01DK117281, and R01DK125480 to YX; R01DK120858 to QT and YX; K01DK119471 to CW; and P20GM135002 to YH), USDA/CRIS (51000-064-01 S to YX and QW), American Diabetes Association (1-17-PDF-138 to YH, 7-13-JF-61 to QW, and 1-15-BS-184 to QT), American Heart Association awards (16POST27260254 to CW), the Pew Charitable Trust awards to QW (0026188), Baylor Collaborative Faculty Research Investment Program grants to QW, the Faculty Start-up grants from USDA/ ARS to QW, the Biotechnology and Biological Sciences Research Council (BB/ K001418/1 and BB/NO17838/1 to LKH), and the Medical Research Council (MC/PC/ 15077 to LKH). QW is the Pew Scholar of Biomedical Sciences and the Kavli Scholar. The anxiety tests (e.g., open-field test, light–dark test, and elevated plus maze test) were performed in the Mouse Neurobehavior Core, Baylor College of Medicine, which was supported by National Institutes of Health Grant No. P30HD024064. The Ad-iN/ WED virus was kindly provided by Dr. Martin Myers (University of Michigan). The AAV9-CBA-DIO-WGA-zsGreen virus was kindly provided by Dr. Richard Palmiter (University of Washington).Peer reviewedPublisher PD

Meta-analysis Followed by Replication Identifies Loci in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as Associated with Systemic Lupus Erythematosus in Asians

Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic involvement and ethnic differences. Susceptibility genes identified so far only explain a small portion of the genetic heritability of SLE, suggesting that many more loci are yet to be uncovered for this disease. In this study, we performed a meta-analysis of genome-wide association studies on SLE in Chinese Han populations and followed up the findings by replication in four additional Asian cohorts with a total of 5,365 cases and 10,054 corresponding controls. We identified genetic variants in or near CDKN1B, TET3, CD80, DRAM1, and ARID5B as associated with the disease. These findings point to potential roles of cell-cycle regulation, autophagy, and DNA demethylation in SLE pathogenesis. For the region involving TET3 and that involving CDKN1B, multiple independent SNPs were identified, highlighting a phenomenon that might partially explain the missing heritability of complex diseases