MPCViT: Searching for MPC-friendly Vision Transformer with Heterogeneous Attention

Secure multi-party computation (MPC) enables computation directly on encrypted data on non-colluding untrusted servers and protects both data and model privacy in deep learning inference. However, existing neural network (NN) architectures, including Vision Transformers (ViTs), are not designed or optimized for MPC protocols and incur significant latency overhead due to the Softmax function in the multi-head attention (MHA). In this paper, we propose an MPC-friendly ViT, dubbed MPCViT, to enable accurate yet efficient ViT inference in MPC. We systematically compare different attention variants in MPC and propose a heterogeneous attention search space, which combines the high-accuracy and MPC-efficient attentions with diverse structure granularities. We further propose a simple yet effective differentiable neural architecture search (NAS) algorithm for fast ViT optimization. MPCViT significantly outperforms prior-art ViT variants in MPC. With the proposed NAS algorithm, our extensive experiments demonstrate that MPCViT achieves 7.9x and 2.8x latency reduction with better accuracy compared to Linformer and MPCFormer on the Tiny-ImageNet dataset, respectively. Further, with proper knowledge distillation (KD), MPCViT even achieves 1.9% better accuracy compared to the baseline ViT with 9.9x latency reduction on the Tiny-ImageNet dataset.Comment: 6 pages, 6 figure

Growth of Large Domain Epitaxial Graphene on the C-Face of SiC

Growth of epitaxial graphene on the C-face of SiC has been investigated. Using a confinement controlled sublimation (CCS) method, we have achieved well controlled growth and been able to observe propagation of uniform monolayer graphene. Surface patterns uncover two important aspects of the growth, i.e. carbon diffusion and stoichiometric requirement. Moreover, a new "stepdown" growth mode has been discovered. Via this mode, monolayer graphene domains can have an area of hundreds of square micrometers, while, most importantly, step bunching is avoided and the initial uniformly stepped SiC surface is preserved. The stepdown growth provides a possible route towards uniform epitaxial graphene in wafer size without compromising the initial flat surface morphology of SiC.Comment: 18 pages, 8 figure

Component attention network for multimodal dance improvisation recognition

Dance improvisation is an active research topic in the arts. Motion analysis of improvised dance can be challenging due to its unique dynamics. Data-driven dance motion analysis, including recognition and generation, is often limited to skeletal data. However, data of other modalities, such as audio, can be recorded and benefit downstream tasks. This paper explores the application and performance of multimodal fusion methods for human motion recognition in the context of dance improvisation. We propose an attention-based model, component attention network (CANet), for multimodal fusion on three levels: 1) feature fusion with CANet, 2) model fusion with CANet and graph convolutional network (GCN), and 3) late fusion with a voting strategy. We conduct thorough experiments to analyze the impact of each modality in different fusion methods and distinguish critical temporal or component features. We show that our proposed model outperforms the two baseline methods, demonstrating its potential for analyzing improvisation in dance.Comment: Accepted to 25th ACM International Conference on Multimodal Interaction (ICMI 2023

Socioeconomic status and self-rated health in China: Findings from a cross-sectional study

To investigate whether socioeconomic status is associated with the self-rated health (SRH) status among Chinese.A cross sectional study including a national sample was conducted among Chinese adults in 2008. In total, 3225 participants were selected by a multistage cluster sampling method. Both general self-rated health and time-comparative self-rated health were measured by a standardized questionnaire. Logistic regression models were used to estimate the odds ratios (ORs) (95% confidence intervals, CIs) of occupation with SRH by occupation, and adjusted for age, sex, education, area, marriage, smoking, drinking, and health status.Overall, 34.4% of study participants reported good on the general SRH (male: 35.8%; female: 32.9%) and 26.2% reported good on the time-comparative SRH (male: 27.2%; female: 25.3%). The prevalence of good general SRH varied from 28.8% to 52.8% and the prevalence of time-comparative SHR varied from 21.7% to 33.9% in different occupations. The adjusted OR (Odd Ratio) for good on the general SRH was 1.35 (95% CI: 1.20-1.52) for the occupation of civil servants, 2.23 (95% CI: 1.96-2.54) for farmers, and 1.15 (95%CI: 1.01-1.31) for businessmen. The full adjusted OR of good on the time-comparative SRH was 1.36 (95% CI: 1.17-1.58) for students and was 1.25 (95% CI: 1.10-1.42) for civil servants.In presented study, 34.4% of the participants reported good on the general SRH, and 26.2% participants reported good on the time-comparative SRH. The prevalence of good general SRH and good time-comparative SRH varied among occupations

Exploring the Nudging and Counter-Nudging Effects of Campaign Updates in Crowdfunding

Crowdfunding has emerged as a vital financing avenue for entrepreneurs to realize their ventures. With limited information availability, crowd-funders may choose to first follow the progress of interested crowdfunding campaigns, such as monitoring project updates to acquire more information for justifying investment decision, before making pledges. Although campaign updates have been touted to be a salient driver of fundraising success, the underlying mechanism for this relationship remains unclear. Subscribing to nudge theory, we strive to shed light on how update strategies, such as frequency and message length, can serve as nudges to convert project followers to actual funders. Specifically, we posit a dual-role of campaign updates whereby an over-zealous update strategy may induce a counter-nudging effect that deters prospective funders, what we labelled as ‘over-nudging’. This study advances a model to account for both the nudging and counter-nudging effects of campaign updates in crowdfunding, which could yield insights for fundraisers to optimize their update strategy and in turn, get their business off the ground

Mask the Correct Tokens: An Embarrassingly Simple Approach for Error Correction

Text error correction aims to correct the errors in text sequences such as those typed by humans or generated by speech recognition models. Previous error correction methods usually take the source (incorrect) sentence as encoder input and generate the target (correct) sentence through the decoder. Since the error rate of the incorrect sentence is usually low (e.g., 10\%), the correction model can only learn to correct on limited error tokens but trivially copy on most tokens (correct tokens), which harms the effective training of error correction. In this paper, we argue that the correct tokens should be better utilized to facilitate effective training and then propose a simple yet effective masking strategy to achieve this goal. Specifically, we randomly mask out a part of the correct tokens in the source sentence and let the model learn to not only correct the original error tokens but also predict the masked tokens based on their context information. Our method enjoys several advantages: 1) it alleviates trivial copy; 2) it leverages effective training signals from correct tokens; 3) it is a plug-and-play module and can be applied to different models and tasks. Experiments on spelling error correction and speech recognition error correction on Mandarin datasets and grammar error correction on English datasets with both autoregressive and non-autoregressive generation models show that our method improves the correction accuracy consistently.Comment: main track of EMNLP 202

Effect of route of delivery on heterologous protection against HCV induced by an adenovirus vector carrying HCV structural genes

BACKGROUND: An effective vaccine and new therapeutic methods for hepatitis C virus (HCV) are needed, and a potent HCV vaccine must induce robust and sustained cellular-mediated immunity (CMI). Research has indicated that adenoviral and vaccinia vectors may have the ability to elicit strong B and T cell immune responses to target antigens. RESULTS: A recombinant replication-defective adenovirus serotype 5 (rAd5) vector, rAd5-CE1E2, and a recombinant Tian Tan vaccinia vector, rTTV-CE1E2, were constructed to express the HCV CE1E2 gene (1-746 amino acid HCV 1b subtype). Mice were prime-immunised with rAd5-CE1E2 delivered via intramuscular injection (i.m.), intranasal injection (i.n.), or intradermal injection (i.d.) and boosted using a different combination of injection routes. CMI was evaluated via IFN-γ ELISPOT and ICS 2 weeks after immunisation, or 16 weeks after boost for long-term responses. The humoral response was analysed by ELISA. With the exception of priming by i.n. injection, a robust CMI response against multiple HCV antigens (core, E1, E2) was elicited and remained at a high level for a long period (16 weeks post-vaccination) in mice. However, i.n. priming elicited the highest anti-core antibody levels. Priming with i.d. rAd5-CE1E2 and boosting with i.d. rTTV-CE1E2 carried out simultaneously enhanced CMI and the humoral immune response, compared to the homologous rAd5-CE1E2 immune groups. All regimens demonstrated equivalent cross-protective potency in a heterologous surrogate challenge assay based on a recombinant HCV (JFH1, 2a) vaccinia virus. CONCLUSIONS: Our data suggest that a rAd5-CE1E2-based HCV vaccine would be capable of eliciting an effective immune response and cross-protection. These findings have important implications for the development of T cell-based HCV vaccine candidates

Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China.

An in-depth annotation of the newly discovered coronavirus (2019-nCoV) genome has revealed differences between 2019-nCoV and severe acute respiratory syndrome (SARS) or SARS-like coronaviruses. A systematic comparison identified 380 amino acid substitutions between these coronaviruses, which may have caused functional and pathogenic divergence of 2019-nCoV

RS4651 suppresses lung fibroblast activation via the TGF-β1/SMAD signalling pathway.

ABSTRACT Background Idiopathic pulmonary fibrosis (IPF) is a progressive disease resulting in respiratory failure with no efficient treatment options. We investigated the protective effect of RS4651 on pulmonary fibrosis in mice and the mechanism. Methods Intratracheal injection of bleomycin (BLM) was used to induce pulmonary fibrosis in mice. RS4561 was administered intraperitoneally at different doses. Histopathological changes were observed. The level of alpha-smooth muscle actin (α-SMA) were also tested. In vitro, the proliferation and migratory effects of RS4651 treatment on MRC-5 cells pre-treated with transforming growth factor (TGF-β1) were examined. RNA-sequencing was used to detect differentially expressed target genes. Then, the expression of α-SMA, pSMAD2 and SMAD7 were analysed during RS4651 treatment of MRC-5 cells with or without silencing by SMAD7 siRNA. Results Histopathological staining results showed decreased collagen deposition in RS4651 administered mice. Additionally, a lower level of α-SMA was also observed compared to the BLM group. The results of in vitro studies confirmed that RS4651 can inhibit the proliferation and migration, as well as α-SMA and pSMAD2 expression in MRC-5 cells treated with TGF-β1. RNA-sequencing data identified the target gene SMAD7. We found that RS4651 could upregulate SMAD7 expression and inhibit the proliferation and migration of MRC-5 cells via SMAD7, and RS4651 inhibition of α-SMA and pSMAD2 expression was blocked in SMAD7-siRNA MRC-5 cells. In vivo studies further confirmed that RS4651 could upregulate SMAD7 expression in BLM-induced lung fibrosis in mice. Conclusions Our data suggest that RS4651 alleviates BLM-induced pulmonary fibrosis in mice by inhibiting the TGF-β1/SMAD signalling pathway