Visual Named Entity Linking: A New Dataset and A Baseline

Visual Entity Linking (VEL) is a task to link regions of images with their corresponding entities in Knowledge Bases (KBs), which is beneficial for many computer vision tasks such as image retrieval, image caption, and visual question answering. While existing tasks in VEL either rely on textual data to complement a multi-modal linking or only link objects with general entities, which fails to perform named entity linking on large amounts of image data. In this paper, we consider a purely Visual-based Named Entity Linking (VNEL) task, where the input only consists of an image. The task is to identify objects of interest (i.e., visual entity mentions) in images and link them to corresponding named entities in KBs. Since each entity often contains rich visual and textual information in KBs, we thus propose three different sub-tasks, i.e., visual to visual entity linking (V2VEL), visual to textual entity linking (V2TEL), and visual to visual-textual entity linking (V2VTEL). In addition, we present a high-quality human-annotated visual person linking dataset, named WIKIPerson. Based on WIKIPerson, we establish a series of baseline algorithms for the solution of each sub-task, and conduct experiments to verify the quality of proposed datasets and the effectiveness of baseline methods. We envision this work to be helpful for soliciting more works regarding VNEL in the future. The codes and datasets are publicly available at https://github.com/ict-bigdatalab/VNEL.Comment: 13 pages, 11 figures, published to EMNLP 2022(findings

Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network

Graphs consisting of vocal nodes ("the vocal minority") and silent nodes ("the silent majority"), namely VS-Graph, are ubiquitous in the real world. The vocal nodes tend to have abundant features and labels. In contrast, silent nodes only have incomplete features and rare labels, e.g., the description and political tendency of politicians (vocal) are abundant while not for ordinary people (silent) on the twitter's social network. Predicting the silent majority remains a crucial yet challenging problem. However, most existing message-passing based GNNs assume that all nodes belong to the same domain, without considering the missing features and distribution-shift between domains, leading to poor ability to deal with VS-Graph. To combat the above challenges, we propose Knowledge Transferable Graph Neural Network (KT-GNN), which models distribution shifts during message passing and representation learning by transferring knowledge from vocal nodes to silent nodes. Specifically, we design the domain-adapted "feature completion and message passing mechanism" for node representation learning while preserving domain difference. And a knowledge transferable classifier based on KL-divergence is followed. Comprehensive experiments on real-world scenarios (i.e., company financial risk assessment and political elections) demonstrate the superior performance of our method. Our source code has been open sourced.Comment: Paper was accepted by WWW202

Robust Recommender System: A Survey and Future Directions

With the rapid growth of information, recommender systems have become integral for providing personalized suggestions and overcoming information overload. However, their practical deployment often encounters "dirty" data, where noise or malicious information can lead to abnormal recommendations. Research on improving recommender systems' robustness against such dirty data has thus gained significant attention. This survey provides a comprehensive review of recent work on recommender systems' robustness. We first present a taxonomy to organize current techniques for withstanding malicious attacks and natural noise. We then explore state-of-the-art methods in each category, including fraudster detection, adversarial training, certifiable robust training against malicious attacks, and regularization, purification, self-supervised learning against natural noise. Additionally, we summarize evaluation metrics and common datasets used to assess robustness. We discuss robustness across varying recommendation scenarios and its interplay with other properties like accuracy, interpretability, privacy, and fairness. Finally, we delve into open issues and future research directions in this emerging field. Our goal is to equip readers with a holistic understanding of robust recommender systems and spotlight pathways for future research and development

Synthesis and Antioxidant Activity of Cationic 1,2,3-Triazole Functionalized Starch Derivatives

In this study, starch was chemically modified to improve its antioxidant activity. Five novel cationic 1,2,3-triazole functionalized starch derivatives were synthesized by using "click" reaction and N-alkylation. A convenient method for pre-azidation of starch was developed. The structures of the derivatives were analyzed using FTIR and H-1 NMR. The radicals scavenging abilities of the derivatives against hydroxyl radicals, DPPH radicals, and superoxide radicals were tested in vitro in order to evaluate their antioxidant activity. Results revealed that all the cationic starch derivatives (2a-2e), as well as the precursor starch derivatives (1a-1e), had significantly improved antioxidant activity compared to native starch. In particular, the scavenging ability of the derivatives against superoxide radicals was extremely strong. The improved antioxidant activity benefited from the enhanced solubility and the added positive charges. The biocompatibility of the cationic derivatives was confirmed by the low hemolytic rate (<2%). The obtained derivatives in this study have great potential as antioxidant materials that can be applied in the fields of food and biomedicine

Identification of Human ABAD Inhibitors for Rescuing Aβ-Mediated Mitochondrial Dysfunction

Amyloid beta (Aβ) binding alcohol dehydrogenase (ABAD) is a cellular cofactor for promoting (Aβ)-mediated mitochondrial and neuronal dysfunction, and cognitive decline in transgenic Alzheimer's disease (AD) mouse models. Targeting mitochondrial ABAD may represent a novel therapeutic strategy against AD. Here, we report the biological activity of small molecule ABAD inhibitors. Using in vitro surface plasmon resonance (SPR) studies, we synthesized compounds with strong binding affinities for ABAD. Further, these ABAD inhibitors (ABAD-4a and 4b) reduced ABAD enzyme activity and administration of phosphonate derivatives of ABAD inhibitors antagonized calcium-mediated mitochondrial swelling. Importantly, these compounds also abolished Aβ-induced mitochondrial dysfunction as shown by increased cytochrome c oxidase and adenosine-5′-triphosphate levels, suggesting protective mitochondrial function effects of these synthesized compounds. Thus, these compounds are potential candidates for further pharmacologic development to target ABAD to improve mitochondrial function

Mitochondrial Uncoupling Inhibits p53 Mitochondrial Translocation in TPA-Challenged Skin Epidermal JB6 Cells

The tumor suppressor p53 is known to be able to trigger apoptosis in response to DNA damage, oncogene activation, and certain chemotherapeutic drugs. In addition to its transcriptional activation, a fraction of p53 translocates to mitochondria at the very early stage of apoptosis, which eventually contributes to the loss of mitochondrial membrane potential, generation of reactive oxygen species (ROS), cytochrome c release, and caspase activation. However, the mitochondrial events that affect p53 translocation are still unclear. Since mitochondrial uncoupling has been suggested to contribute to cancer development, herein, we studied whether p53 mitochondrial translocation and subsequent apoptosis were affected by mitochondrial uncoupling using chemical protonophores, and further verified the results using a siRNA approach in murine skin epidermal JB6 cells. Our results showed that mitochondrial uncoupling blocked p53 mitochondrial translocation induced by 12-O-tetradecanoylphorbol 13-acetate (TPA), a known tumor promoter to induce p53-mediated apoptosis in skin carcinogenesis. This blocking effect, in turn, led to preservation of mitochondrial functions, and eventually suppression of caspase activity and apoptosis. Moreover, uncoupling protein 2 (UCP2), a potential suppressor of ROS in mitochondria, is important for TPA-induced cell transformation in JB6 cells. UCP2 knock down cells showed enhanced p53 mitochondrial translocation, and were less prone to form colonies in soft agar after TPA treatment. Altogether, our data suggest that mitochondrial uncoupling may serve as an important regulator of p53 mitochondrial translocation and p53-mediated apoptosis during early tumor promotion. Therefore, targeting mitochondrial uncoupling may be considered as a novel treatment strategy for cancer

The Herpesvirus Associated Ubiquitin Specific Protease, USP7, Is a Negative Regulator of PML Proteins and PML Nuclear Bodies

The PML tumor suppressor is the founding component of the multiprotein nuclear structures known as PML nuclear bodies (PML-NBs), which control several cellular functions including apoptosis and antiviral effects. The ubiquitin specific protease USP7 (also called HAUSP) is known to associate with PML-NBs and to be a tight binding partner of two herpesvirus proteins that disrupt PML NBs. Here we investigated whether USP7 itself regulates PML-NBs. Silencing of USP7 was found to increase the number of PML-NBs, to increase the levels of PML protein and to inhibit PML polyubiquitylation in nasopharyngeal carcinoma cells. This effect of USP7 was independent of p53 as PML loss was observed in p53-null cells. PML-NBs disruption was induced by USP7 overexpression independently of its catalytic activity and was induced by either of the protein interaction domains of USP7, each of which localized to PML-NBs. USP7 also disrupted NBs formed from some single PML isoforms, most notably isoforms I and IV. CK2α and RNF4, which are known regulators of PML, were dispensable for USP7-associated PML-NB disruption. The results are consistent with a novel model of PML regulation where a deubiquitylase disrupts PML-NBs through recruitment of another cellular protein(s) to PML NBs, independently of its catalytic activity

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples