Phrase-based Topic and Sentiment Detection and Tracking Model using Incremental HDP

( YongHeng Chen ),( YaoJin Lin ),( WanLi Zuo ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.12

Sentiments can profoundly affect individual behavior as well as decision-making. Confronted with the ever-increasing amount of review information available online, it is desirable to provide an effective sentiment model to both detect and organize the available information to improve understanding, and to present the information in a more constructive way for consumers. This study developed a unified phrase-based topic and sentiment detection model, combined with a tracking model using incremental hierarchical dirichlet allocation (PTSM_IHDP). This model was proposed to discover the evolutionary trend of topic-based sentiments from online reviews. PTSM_IHDP model firstly assumed that each review document has been composed by a series of independent phrases, which can be represented as both topic information and sentiment information. PTSM_IHDP model secondly depended on an improved time-dependency non-parametric Bayesian model, integrating incremental hierarchical dirichlet allocation, to estimate the optimal number of topics by incrementally building an up-to-date model. To evaluate the effectiveness of our model, we tested our model on a collected dataset, and compared the result with the predictions of traditional models. The results demonstrate the effectiveness and advantages of our model compared to several state-of-the-art methods.

YTHDC1 inhibits cell proliferation and angiogenesis in cervical cancer by regulating m6A modification of SOCS4 mRNA

Chen Sihe,Chen Yongheng,Yu Lanting,Hu Xiangmei 대한독성 유전단백체 학회 2024 Molecular & cellular toxicology Vol.20 No.3

Background Cervical cancer (CC) is one of the most common tumors in women, with a high mortality rate. YTHDC1 has been discovered to be involved in the progression of several cancers by acting as a tumor suppressor. However, the detailed regulatory role of YTHDC1 in CC remains unclear. Our study aimed to investigate the effects of YTHDC1 on CC progression. Objectives To investigate the regulatory functions of YTHDC1 in CC. Results First, through TCGA database, YTHDC1 expression was found to be down-regulated in CC. In addition, the expression of YTHDC1 was also decreased in CC tissues and cells. Moreover, our results showed that YTHDC1 repressed cell proliferation and facilitated cell apoptosis. Additionally, YTHDC1 inhibited angiogenesis and metastasis. Further investigations revealed that YTHDC1 accelerated SOCS4 m6A modification to enhance SOCS4 expression. Finally, we identified that the suppressive effects mediated by YTHDC1 on CC progression were reversed by silencing SOCS4. Conclusion Our study for the first time showed that YTHDC1 inhibited cell proliferation and angiogenesis of cervical cancer by regulating m6A modification of SOCS4 mRNA. This finding may provide a potential therapeutic molecular target for CC. Background Cervical cancer (CC) is one of the most common tumors in women, with a high mortality rate. YTHDC1 has been discovered to be involved in the progression of several cancers by acting as a tumor suppressor. However, the detailed regulatory role of YTHDC1 in CC remains unclear. Our study aimed to investigate the effects of YTHDC1 on CC progression. Objectives To investigate the regulatory functions of YTHDC1 in CC. Results First, through TCGA database, YTHDC1 expression was found to be down-regulated in CC. In addition, the expression of YTHDC1 was also decreased in CC tissues and cells. Moreover, our results showed that YTHDC1 repressed cell proliferation and facilitated cell apoptosis. Additionally, YTHDC1 inhibited angiogenesis and metastasis. Further investigations revealed that YTHDC1 accelerated SOCS4 m6A modification to enhance SOCS4 expression. Finally, we identified that the suppressive effects mediated by YTHDC1 on CC progression were reversed by silencing SOCS4. Conclusion Our study for the first time showed that YTHDC1 inhibited cell proliferation and angiogenesis of cervical cancer by regulating m6A modification of SOCS4 mRNA. This finding may provide a potential therapeutic molecular target for CC.

Time Label Topic Model

YongHeng Chen,Wanli Zuo,kerui Chen,Yaojin lin 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.1

Most of the models not aware of these dependencies on document time stamps. Not modeling time can confound co-occurrence patters and results in exchangeability of topic problem, which is important factor to deal with when finding dynamic topic discovery. This limitation has thus motivated work on developing a generalized framework for incorporating time information into topic models. Consequently, a topic model named Topics over Time (TOT) is proposed, which introduces a time node in topic model to handle the exchangeability of topics problem. However it lacks the capability to accommodate data type of side information. In this paper, we present a generative time LDA-style topic model with a variety of side information named Time Label Topic(TLT), which can find not only how the latent low-dimensional structure of document-response pairs changes over time, but also overcome the exchangeability of topics problem. Empirical results demonstrate significant improvements accuracy of time stamp and response variable prediction, and lower perplexity of our proposed model and dominance over other models.

On-Line labeled Topic Model Based on Global and Local Topic

YongHeng Chen,Yaojin Lin,Hao Yue 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12

A large number of electronic documents are labeled using human-interpretable annotations. High-efficiency text mining on such data set requires generative model that can flexibly comprehend the significant of observed labels while simultaneously uncovering topics within unlabeled documents. This paper presents a novel and generalized on-line labeled topic model based on global and local topic (GL-OLT) tracking the time evolution of topics in a sequentially organized multi-labeled corpus. GL-OLT topic model has an incrementally update principle based on time slices by an on-line fashion, and each label has not only a set of local topics, but also has several global topics. Empirical results are presented to demonstrate significant improvements accuracy of label predictive, and lower perplexity and high performance of our proposed model when compared with other models.

Deep Image Annotation and Classification by Fusing Multi-Modal Semantic Topics

( YongHeng Chen ),( Fuquan Zhang ),( WanLi Zuo ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.1

Due to the semantic gap problem across different modalities, automatically retrieval from multimedia information still faces a main challenge. It is desirable to provide an effective joint model to bridge the gap and organize the relationships between them. In this work, we develop a deep image annotation and classification by fusing multi-modal semantic topics (DAC_mmst) model, which has the capacity for finding visual and non-visual topics by jointly modeling the image and loosely related text for deep image annotation while simultaneously learning and predicting the class label. More specifically, DAC_mmst depends on a non-parametric Bayesian model for estimating the best number of visual topics that can perfectly explain the image. To evaluate the effectiveness of our proposed algorithm, we collect a real-world dataset to conduct various experiments. The experimental results show our proposed DAC_mmst performs favorably in perplexity, image annotation and classification accuracy, comparing to several state-of-the-art methods.

Effects of dexmedetomidine on pulmonary function in patients receiving one-lung ventilation: a meta-analysis of randomized controlled trial

Yang Lin,Cai Yongheng,Dan Lin,Huang He,Chen Bing 대한마취통증의학회 2023 Korean Journal of Anesthesiology Vol.76 No.6

Background: Mechanical ventilation, particularly one-lung ventilation (OLV), can cause pulmonary dysfunction. This meta-analysis assessed the effects of dexmedetomidine on the pulmonary function of patients receiving OLV. Methods: The Embase, PubMed, MEDLINE, Cochrane Library, ClinicalTrials.gov, and Chinese Clinical Trial Registry databases were systematically searched. The primary outcome was oxygenation index (OI). Other outcomes including the incidence of postoperative complications were assessed. Results: Fourteen randomized controlled trials involving 845 patients were included in this meta-analysis. Dexmedetomidine improved the OI at 30 (mean difference [MD]: 40.49, 95% CI [10.21, 70.78]), 60 (MD: 60.86, 95% CI [35.81, 85.92]), and 90 min (MD: 55, 95% CI [34.89, 75.11]) after OLV and after surgery (MD: 28.98, 95% CI [17.94, 40.0]) and improved lung compliance 90 min after OLV (MD: 3.62, 95% CI [1.7, 5.53]). Additionally, dexmedetomidine reduced the incidence of postoperative pulmonary complications (odds ratio: 0.44, 95% CI [0.24, 0.82]) and length of hospital stay (MD: −0.99, 95% CI [−1.25, −0.73]); decreased tumor necrosis factor-α, interleukin (IL)-6, IL-8, and malondialdehyde levels; and increased superoxide dismutase levels. However, only the results for the OI and IL-6 levels were confirmed by the sensitivity and trial sequential analyses.Conclusions: Dexmedetomidine improves oxygenation in patients receiving OLV and may additionally decrease the incidence of postoperative pulmonary complications and shorten the length of hospital stay, which may be related to associated improvements in lung compliance, anti-inflammatory effects, and regulation of oxidative stress reactions. However, robust evidence is required to confirm these conclusions.

Molecular evolutionary analysis reveals Arctic-like rabies viruses evolved and dispersed independently in North and South Asia

Xin Yu,Hongwei Zhu,Yongheng Bo,Youzhi Li,Jianlong Zhang,Linlin Jiang,Guozhong Chen,Xingxiao Zhang,Yongjun Wen 대한수의학회 2021 Journal of Veterinary Science Vol.22 No.1

Background: Arctic-like (AL) lineages of rabies viruses (RABVs) remains endemic in some Arctic and Asia countries. However, their evolutionary dynamics are largely unappreciated. Objectives: We attempted to estimate the evolutionary history, geographic origin and spread of the Arctic-related RABVs. Methods: Full length or partial sequences of the N and G genes were used to infer the evolutionary aspects of AL RABVs by Bayesian evolutionary analysis. Results: The most recent common ancestor (tMRCA) of the current Arctic and AL RABVs emerged in the 1830s and evolved independently after diversification. Population demographic analysis indicated that the viruses experienced gradual growth followed by a sudden decrease in its population size from the mid-1980s to approximately 2000. Genetic flow patterns among the regions reveal a high geographic correlation in AL RABVs transmission. Discrete phylogeography suggests that the geographic origin of the AL RABVs was in east Russia in approximately the 1830s. The ancestral AL RABV then diversified and immigrated to the countries in Northeast Asia, while the viruses in South Asia were dispersed to the neighboring regions from India. The N and G genes of RABVs in both clades sustained high levels of purifying selection, and the positive selection sites were mainly found on the C-terminus of the G gene. Conclusions: The current AL RABVs circulating in South and North Asia evolved and dispersed independently.

Analysis and Benchmarking of Grid-Forming Control for Power Converters

Jianbing Yin,Junhai Wang,Lin Chen,Mingchang Wang,Hao Luo,Yongheng Yang 전력전자학회 2023 ICPE(ISPE)논문집 Vol.2023 No.-

Traditional electricity grids use large-capacity synchronous generators as power generation devices, which have the characteristics of large volume and high robustness. In recent years, the rapid development of renewable energy in alignment with the national strategy of Carbon Neutrality in China by 2060 has brought new opportunities and challenges to traditional power grids. Power electronics converters are the key to renewable energy integration to gradually replace traditional synchronous generators, leading to reduced inertia and more challenges. While being more flexible, it makes the stability of the grid worse. In view of this, various advanced control strategies have been developed in the literature. The control of grid-connected converters has been broadly divided into two groups, grid-following (GFL) and grid-forming (GFM). In this paper, the characteristics of the GEM control are benchmarked through simulations, mainly the virtual synchronous generator (VSG) control and the virtual oscillator control (VOC). The benchmarking indicates that the VSG control strategies with virtual inertia have less fluctuation in response to various disturbances and the VOC performs better in terms of dynamics.