An Effective Deployment of Contrastive Learning in Multi-label Text Classification

The effectiveness of contrastive learning technology in natural language processing tasks is yet to be explored and analyzed. How to construct positive and negative samples correctly and reasonably is the core challenge of contrastive learning. It is even harder to discover contrastive objects in multi-label text classification tasks. There are very few contrastive losses proposed previously. In this paper, we investigate the problem from a different angle by proposing five novel contrastive losses for multi-label text classification tasks. These are Strict Contrastive Loss (SCL), Intra-label Contrastive Loss (ICL), Jaccard Similarity Contrastive Loss (JSCL), Jaccard Similarity Probability Contrastive Loss (JSPCL), and Stepwise Label Contrastive Loss (SLCL). We explore the effectiveness of contrastive learning for multi-label text classification tasks by the employment of these novel losses and provide a set of baseline models for deploying contrastive learning techniques on specific tasks. We further perform an interpretable analysis of our approach to show how different components of contrastive learning losses play their roles. The experimental results show that our proposed contrastive losses can bring improvement to multi-label text classification tasks. Our work also explores how contrastive learning should be adapted for multi-label text classification tasks.Comment: Accepted by ACL-Findings 2023, 13 page

Efficient Three-stage Auction Schemes for Cloudlets Deployment in Wireless Access Network

Cloudlet deployment and resource allocation for mobile users (MUs) have been extensively studied in existing works for computation resource scarcity. However, most of them failed to jointly consider the two techniques together, and the selfishness of cloudlet and access point (AP) are ignored. Inspired by the group-buying mechanism, this paper proposes three-stage auction schemes by combining cloudlet placement and resource assignment, to improve the social welfare subject to the economic properties. We first divide all MUs into some small groups according to the associated APs. Then the MUs in same group can trade with cloudlets in a group-buying way through the APs. Finally, the MUs pay for the cloudlets if they are the winners in the auction scheme. We prove that our auction schemes can work in polynomial time. We also provide the proofs for economic properties in theory. For the purpose of performance comparison, we compare the proposed schemes with HAF, which is a centralized cloudlet placement scheme without auction. Numerical results confirm the correctness and efficiency of the proposed schemes.Comment: 22 pages,12 figures, Accepted by Wireless Network

Co3O4 Nanocrystals on Graphene as a Synergistic Catalyst for Oxygen Reduction Reaction

Catalysts for oxygen reduction and evolution reactions are at the heart of key renewable energy technologies including fuel cells and water splitting. Despite tremendous efforts, developing oxygen electrode catalysts with high activity at low costs remains a grand challenge. Here, we report a hybrid material of Co3O4 nanocrystals grown on reduced graphene oxide (GO) as a high-performance bi-functional catalyst for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). While Co3O4 or graphene oxide alone has little catalytic activity, their hybrid exhibits an unexpected, surprisingly high ORR activity that is further enhanced by nitrogen-doping of graphene. The Co3O4/N-doped graphene hybrid exhibits similar catalytic activity but superior stability to Pt in alkaline solutions. The same hybrid is also highly active for OER, making it a high performance non-precious metal based bi-catalyst for both ORR and OER. The unusual catalytic activity arises from synergetic chemical coupling effects between Co3O4 and graphene.Comment: published in Nature Material

Mapping the Binding between the Tetraspanin Molecule (Sjc23) of Schistosoma japonicum and Human Non-Immune IgG

BACKGROUND: Schistosomal parasites can establish parasitization in a human host for decades; evasion of host immunorecognition including surface masking by acquisition of host serum components is one of the strategies explored by the parasites. Parasite molecules anchored on the membrane are the main elements in the interaction. Sjc23, a member of the tetraspanin (TSP) family of Schistosoma japonicum, was previously found to be highly immunogenic and regarded as a vaccine candidate against schistosomiasis. However, studies indicated that immunization with Sjc23 generated rapid antibody responses which were less protective than that with other antigens. The biological function of this membrane-anchored molecule has not been defined after decades of vaccination studies. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we explored affinity pull-down and peptide competition assays to investigate the potential binding between Sjc23 molecule and human non-immune IgG. We determined that Sjc23 could bind human non-immune IgG and the binding was through the interaction of the large extra-cellular domain (LED) of Sjc23 (named Sjc23-LED) with the Fc domain of human IgG. Sjc23 had no affinity to other immunoglobulin types. Affinity precipitation (pull-down assay) in the presence of overlapping peptides further pinpointed to a 9-amino acid motif within Sjc23-LED that mediated the binding to human IgG. CONCLUSION AND SIGNIFICANCE: S. japonicum parasites cloak themselves through interaction with human non-immune IgG, and a member of the tetraspanin family, Sjc23, mediated the acquisition of human IgG via the interaction of a motif of 9 amino acids with the Fc domain of the IgG molecule. The consequence of this interaction will likely benefit parasitism of S. japonicum by evasion of host immune recognition or immunoresponses. This is the first report that an epitope of schistosomal ligand and its immunoglobulin receptor are defined, which provides further evidence of immune evasion strategy adopted by S. japonicum