Tracking without Label: Unsupervised Multiple Object Tracking via Contrastive Similarity Learning

Unsupervised learning is a challenging task due to the lack of labels. Multiple Object Tracking (MOT), which inevitably suffers from mutual object interference, occlusion, etc., is even more difficult without label supervision. In this paper, we explore the latent consistency of sample features across video frames and propose an Unsupervised Contrastive Similarity Learning method, named UCSL, including three contrast modules: self-contrast, cross-contrast, and ambiguity contrast. Specifically, i) self-contrast uses intra-frame direct and inter-frame indirect contrast to obtain discriminative representations by maximizing self-similarity. ii) Cross-contrast aligns cross- and continuous-frame matching results, mitigating the persistent negative effect caused by object occlusion. And iii) ambiguity contrast matches ambiguous objects with each other to further increase the certainty of subsequent object association through an implicit manner. On existing benchmarks, our method outperforms the existing unsupervised methods using only limited help from ReID head, and even provides higher accuracy than lots of fully supervised methods

DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection

Recent years, human-object interaction (HOI) detection has achieved impressive advances. However, conventional two-stage methods are usually slow in inference. On the other hand, existing one-stage methods mainly focus on the union regions of interactions, which introduce unnecessary visual information as disturbances to HOI detection. To tackle the problems above, we propose a novel one-stage HOI detection approach DIRV in this paper, based on a new concept called interaction region for the HOI problem. Unlike previous methods, our approach concentrates on the densely sampled interaction regions across different scales for each human-object pair, so as to capture the subtle visual features that is most essential to the interaction. Moreover, in order to compensate for the detection flaws of a single interaction region, we introduce a novel voting strategy that makes full use of those overlapped interaction regions in place of conventional Non-Maximal Suppression (NMS). Extensive experiments on two popular benchmarks: V-COCO and HICO-DET show that our approach outperforms existing state-of-the-arts by a large margin with the highest inference speed and lightest network architecture. We achieved 56.1 mAP on V-COCO without addtional input. Our code is publicly available at: https://github.com/MVIG-SJTU/DIRVComment: Paper is accepted. Code available at: https://github.com/MVIG-SJTU/DIR

DecAug: Augmenting HOI Detection via Decomposition

Human-object interaction (HOI) detection requires a large amount of annotated data. Current algorithms suffer from insufficient training samples and category imbalance within datasets. To increase data efficiency, in this paper, we propose an efficient and effective data augmentation method called DecAug for HOI detection. Based on our proposed object state similarity metric, object patterns across different HOIs are shared to augment local object appearance features without changing their state. Further, we shift spatial correlation between humans and objects to other feasible configurations with the aid of a pose-guided Gaussian Mixture Model while preserving their interactions. Experiments show that our method brings up to 3.3 mAP and 1.6 mAP improvements on V-COCO and HICODET dataset for two advanced models. Specifically, interactions with fewer samples enjoy more notable improvement. Our method can be easily integrated into various HOI detection models with negligible extra computational consumption. Our code will be made publicly available

Evaluation and evolution analysis of water ecosystem service value in the yangtze river delta region based on meta-analysis

Rapid economic development, industrialization and urbanization lead to environmental pollution and damage the stability of regional ecosystems. The Yangtze River Delta region is an economically developed region in China, faces the problems of water environment pollution and water ecosystem service degradation. Reasonable assessment of water ecosystem service value (ESV) is of great significance for grasping the status of regional water ecosystem services, improving water ecological environment, and realizing regional sustainable development. This study collects 119 research literature about China, including 156 observations to establish a value transfer database; specially builds a Meta-analysis model including the variables of climate conditions, environmental pollution and environmental protection, then assesses the waters ESV in the Yangtze River Delta using the model and analyzes the changes from 2009 to 2018. The study finds that the location, population density, the area of the site, average annual precipitation, literature characteristics, landscape characteristics, wastewater discharge, environmental protection expenditure, and wastewater treatment costs can affect the water ESV significantly. Based on the meta-analysis benefit transfer model to evaluate the water ESV in Yangtze River Delta region is RMB 177,126 yuan/ hha/year and the growth rate is 27.18%. The place with the highest value per unit area is Shanghai, and the total value in Jiangsu Province is the highest. Economic development, waste water discharge and wastewater treatment costs are the main reasons for the changes and differences in the value of water ecosystem services in the Yangtze River Delta region. The contribution of this study to the field of water ESV assessment is that the meta-analysis model includes a broader set of influencing variables, including landscape, population density, climate change and environmental protection. It provides a practical reference for water ESV assessment on the local scale and a scientific basis for water area management related to the development of water area and ecological compensation, as well as promote the sustainable development of water ecosystems

Replication of a pathogenic non-coding RNA increases DNA methylation in plants associated with a bromodomain-containing viroid-binding protein.

peer reviewedViroids are plant-pathogenic molecules made up of single-stranded circular non-coding RNAs. How replicating viroids interfere with host silencing remains largely unknown. In this study, we investigated the effects of a nuclear-replicating Potato spindle tuber viroid (PSTVd) on interference with plant RNA silencing. Using transient induction of silencing in GFP transgenic Nicotiana benthamiana plants (line 16c), we found that PSTVd replication accelerated GFP silencing and increased Virp1 mRNA, which encodes bromodomain-containing viroid-binding protein 1 and is required for PSTVd replication. DNA methylation was increased in the GFP transgene promoter of PSTVd-replicating plants, indicating involvement of transcriptional gene silencing. Consistently, accelerated GFP silencing and increased DNA methylation in the of GFP transgene promoter were detected in plants transiently expressing Virp1. Virp1 mRNA was also increased upon PSTVd infection in natural host potato plants. Reduced transcript levels of certain endogenous genes were also consistent with increases in DNA methylation in related gene promoters in PSTVd-infected potato plants. Together, our data demonstrate that PSTVd replication interferes with the nuclear silencing pathway in that host plant, and this is at least partially attributable to Virp1. This study provides new insights into the plant-viroid interaction on viroid pathogenicity by subverting the plant cell silencing machinery

Metastasis of nasopharyngeal carcinoma: What we know and do not know

Nasopharyngeal carcinoma (NPC) has the highest metastatic rate among head and neck cancers, with its underlying mechanism not yet fully unveiled. High- versus low-metastasis, NPC cell lines have been established. The footpad-popliteal lymph node metastasis model and other in vivo models have been stably used to study NPC metastasis. The histological appearance and the expression of epithelial-to-mesenchymal transition (EMT) markers might be helpful in selecting high-risk NPC patients for developing post-treatment metastasis. Tested EMT markers and their protein expression levels that correlate with patient disease-free survival in large patient cohorts include E-cadherin, N-cadherin, CD44, Twist, Snail, and Cyclin D1. Epstein-Barr virus (EBV) infection can trigger NPC metastasis from multiple angles via multiple signaling pathways. High endothelial venules are commonly seen in NPC tissues, with their role in NPC metastasis requiring clarification. The molecules that promote and inhibit NPC metastasis are introduced, with a focus on cytokines SPINK6, serglycin, interleukin 8 (IL8), Wnt family member 5A (WNT5A), and chemokine C-C motif ligand 2 (CCL2). Two videos showing NPC cells with and without SPINK6 knocked down are presented. Future directions for studying NPC metastasis are also discussed

Targeting N-myristoylation for therapy of B-cell lymphomas

N-myristoyltransferases (NMTs) target many signaling proteins to membranes. Here the authors show an NMT inhibitor named PCLX-001 selectively kills lymphoma cells by shutting down their main survival signaling pathway and offers an additional treatment strategy for lymphoma patients

Combination of Chinese Herbal Medicines and Conventional Treatment versus Conventional Treatment Alone in Patients with Acute Coronary Syndrome after Percutaneous Coronary Intervention (5C Trial): An Open-Label Randomized Controlled, Multicenter Study

Aims. To evaluate the efficacy of Chinese herbal medicines (CHMs) plus conventional treatment in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI). Methods and Results. Participants (n=808) with ACS who underwent PCI from thirteen hospitals of mainland China were randomized into two groups: CHMs plus conventional treatment group (treatment group) or conventional treatment alone group (control group). All participants received conventional treatment, and participants in treatment group additionally received CHMs for six months. The primary endpoint was the composite of cardiac death, nonfatal recurrent MI, and ischemia-driven revascularization. Secondary endpoint was the composite of readmission for ACS, stroke, or congestive heart failure. The safety endpoint involved occurrence of major bleeding events. The incidence of primary endpoint was 2.7% in treatment group versus 6.2% in control group (HR, 0.43; 95% CI, 0.21 to 0.87; P=0.015). The incidence of secondary endpoint was 3.5% in treatment group versus 8.7% in control group (HR, 0.39; 95% CI, 0.21 to 0.72; P=0.002). No major bleeding events were observed in any participant. Conclusion. Treatment with CHMs plus conventional treatment further reduced the occurrence of cardiovascular events in patients with ACS after PCI without increasing risk of major bleeding