分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-27 合作期刊: 《数据智能（英文）》
摘要： Knowledge graph (KG) completion aims at filling the missing facts in a KG, where a fact is typically represented as a triple in the form of (head, relation, tail). Traditional KG completion methods compel two#2;thirds of a triple provided (e.g., head and relation) to predict the remaining one. In this paper, we propose a new method that extends multi-layer recurrent neural networks (RNNs) to model triples in a KG as sequences. It obtains state-of-the-art performance on the common entity prediction task, i.e., giving head (or tail) and relation to predict the tail (or the head), using two benchmark data sets. Furthermore, the deep sequential characteristic of our method enables it to predict the relations given head (or tail) only, and even predict the whole triples. Our experiments on these two new KG completion tasks demonstrate that our method achieves superior performance compared with several alternative methods.
分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-28 合作期刊: 《数据智能（英文）》
摘要： Due to the large-scale spread of COVID-19, which has a significant impact on human health and social economy, developing effective antiviral drugs for COVID-19 is vital to saving human lives. Various biomedical associations, e.g., drug-virus and viral protein-host protein interactions, can be used for building biomedical knowledge graphs. Based on these sources, large-scale knowledge reasoning algorithms can be used to predict new links between antiviral drugs and viruses. To utilize the various heterogeneous biomedical associations, we proposed a fusion strategy to integrate the results of two tensor decomposition-based models (i.e., CP-N3 and ComplEx-N3). Sufficient experiments indicated that our method obtained high performance (MRR=0.2328). Compared with CP-N3, the mean reciprocal rank (MRR) is increased by 3.3% and compared with ComplEx-N3, the MRR is increased by 3.5%. Meanwhile, we explored the relationship between the performance and relationship types, which indicated that there is a negative correlation (PCC=0.446, P-value=2.26e-194) between the performance of triples predicted by our method and edge betweenness.
分类： 矿山工程技术 >> 矿山工程技术其他学科 提交时间： 2024-07-08
摘要： Rockburst is a phenomenon where sudden, catastrophic failure of the rock mass occurs in underground deep regions or areas with high tectonic stress during the excavation process. Rockburst disasters endanger the safety of people’s lives and property, national energy security, and social interests, so it is very important to accurately predict rockburst. Traditional rockburst prediction has not been able to find an effective prediction method, and the study of the rockburst mechanism is facing a dilemma. With the development of artificial intelligence (AI) techniques in recent years, more and more experts and scholars have begun to introduce AI techniques into the study of the rockburst mechanism. In previous research, several scholars have attempted to summarize the application of AI techniques in rockburst prediction. However, these studies either are not specifically focused on reviews of the application of AI techniques in rockburst prediction, or they do not provide a comprehensive overview. Drawing on the advantages of extensive interdisciplinary research and a deep understanding of AI techniques, this paper conducts a comprehensive review of rockburst prediction methods leveraging AI techniques. Firstly, pertinent definitions of rockburst and its associated hazards are introduced. Subsequently, the applications of both traditional prediction methods and those rooted in AI techniques for rockburst prediction are summarized, with emphasis placed on the respective advantages and disadvantages of each approach. Finally, the strengths and weaknesses of prediction methods leveraging AI are summarized, alongside forecasting future research trends to address existing challenges, while simultaneously proposing directions for improvement to advance the field and meet emerging demands effectively.
分类： 核科学技术 >> 粒子加速器 提交时间： 2023-06-18 合作期刊: 《Nuclear Science and Techniques》
摘要： In this paper, a genetic-algorithm-based artificial neural network (GAANN) model radioactivity prediction is proposed, which is verified by measuring results from Long Range Alpha Detector (LRAD). GAANN can integrate capabilities of approximation of Artificial Neural Networks (ANN) and of global optimization of Genetic Algorithms (GA) so that the hybrid model can enhance capability of generalization and prediction accuracy, theoretically. With this model, both the number of hidden nodes and connection weights matrix in ANN are optimized using genetic operation. The real data sets are applied to the introduced method and the results are discussed and compared with the traditional Back Propagation (BP) neural network, showing the feasibility and validity of the proposed approach.
分类： 化学 >> 物理化学 提交时间： 2017-11-05 合作期刊: 《结构化学》
摘要： In this work, the photovoltaic properties of BFBPD-PC61BM system as a promising high-performance organic solar cell (OSC) were theoretically investigated by means of quantum chemistry and molecular dynamics calculations coupled with the incoherent charge-hopping model. Moreover, the hole carrier mobility of BFBPD thin-film was also estimated with the aid of an amorphous cell including 100 BFBPD molecules. Results revealed that the BFBPD-PC61BM system possesses a middle-sized open-circuit voltage of 0.70 V, large short-circuit current density of 17.26 mA·cm-2, high fill factor of 0.846, and power conversion efficiency of 10%. With the Marcus model, in the BFBPD-PC61BM interface, the exciton-dissociation rate, kdis, was predicted to be 2.684×1013 s-1, which is as 3～5 orders of magnitude large as the decay (radiative and non-radiative) one (108～1010 s-1), indicating a high exciton-dissociation efficiency of 100% in the BFBPD-PC61BM interface. Furthermore, by the molecular dynamics simulation, the hole mobility of BFBPD thin-film was predicted to be as high as 1.265×10-2 cm2·V-1·s-1, which can be attributed to its dense packing in solid state.
分类： 物理学 >> 地球物理学、天文学和天体物理学 分类： 信息科学与系统科学 >> 信息科学与系统科学基础学科 提交时间： 2024-06-09
Wenlong Sun
Fengfeng Shi
Yuting Lin
Jinfeng Xu
Shaofeng He
Yongxin Lin
Guocheng Wang
Run Zhao
Pei Ma
摘要： The precise estimation of the satellite clock bias (SCB) holds considerable importance in ensuring accurate timekeeping, navigation, and positioning. This studyintroduces a novel SCB prediction approach that integrates variational mode decomposition (VMD) and long short-term memory (LSTM) network techniques, combining signal decomposition with deep learning methodologies. Initially, the raw SCB data undergoespreprocessing, followed by decomposition using the VMD method to generate multiple intrinsic mode functions (IMFs). These decomposed IMFs serve as inputs for LSTM, where several independent LSTM models are established for training and prediction purposes. Subsequently, the predicted outcomes are aggregated and reconstructed to derive the finalSCB prediction. Experimental findings demonstrate notable advancements in clock bias prediction for the spaceborne hydrogen atomic clock for BDS, with prediction accuracies of 0.048 ns, 0.204 ns and 1.397 ns for 6 hours, 3 days and 15 days, respectively. These results exhibit significant enhancements compared to both the LSTM network and the Back Propagation (BP) neural network, with improvements of 56%, 84% and 83% for the aforementioned time intervals in comparison to LSTM, and enhancements of 59%, 82% and 83% relative to the BP neural network.
分类： 核科学技术 >> 辐射物理与技术 提交时间： 2021-12-31
摘要： Controllable D-D neutron sources have a long service life, low cost, and non-radioactivity. There are favorable prospects for its application in geophysical well logging, since traditional chemical radioactive sources used for well logging pose potential threats to the safety of the human body and environment. This paper presents an improved method to measure formation density that employs a D-D neutron source. In addition, the lithological effect on the measured density was removed to better estimate the formation porosity. First, we investigated the spatial distribution of capture gamma rays through Monte Carlo simulations as well as the relationship between the ratio of capture gamma ray counts and formation density to establish theoretical support for the design of density logging tools and their corresponding data processing methods. Second, we obtained the far to near detector counts of captured gamma rays for an optimized tool structure, and then established its correlation with the density and porosity of three typical formations with pure quartz, calcite, and dolomite minerals. Third, we determined the values for correcting the densities of sandstone and dolomite with the same porosity using limestone data as the reference and established the equations for calculating the correction values, which lays a solid foundation for accurately calculating formation porosity. We observed that the capture gamma ray counts first increased then decreased and varied in different formations; this was especially observed in high-porosity formations. Under the same lithologic conditions (rock matrix), as the porosity increases, the peak value of gamma ray counts moves toward the neutron source. At different detector-source distances, the ratio of the capture gamma ray counts was well correlated with the formation density. An equation of the formation density conversion was established based on the ratio of capture gamma ray counts at the detector-source distances of 30 cm and 65 cm, and the calculated values were consistent with the true values. After correction, the formation density was highly consistent with the true value of the limestone density, and the mean absolute error was -0.013 g/cm3. The calculated porosity values were very close to the true values, and the mean relative error was 2.33%, highlighting the accuracy of the proposed method. These findings provide a new method for developing D-D neutron source logging tools and their well-log data processing methods.
分类： 生物学 >> 发育生物学 提交时间： 2017-03-31
摘要： [目的] 探索婴儿死亡率下降的历程。 [方法] 以日本和中国香港婴儿死亡率动态数列为参照系统，借鉴研究经济现象的方法，采用平均增长量、平均发展速度、平均增长速度描述分析婴儿死亡率的变化规律，分析下降历程。再通过婴儿死亡率随人均GDP变化轨迹进行验证，进一步分析191个WHO会员国2000-2013年下降规律与参照系统的符合率。按参照系统婴儿死亡率下降特征判别现阶段中国大陆婴儿死亡率所处的位置，预测未来下降历程。 [结果] 参照系统婴儿死亡率下降大致经历快速下降、缓慢下降、低水平持续状态三个阶段，婴儿死亡率随人均GDP变化轨迹与时间序列的规律相一致，191个国家下降规律与参照系统总体符合率为59.68%，快速下降、缓慢下降、低水平持续状态符合率分别为98.57%、21.62%、61.70%。中国大陆地区婴儿死亡率仍处于快速下降阶段，正向缓慢下降阶段过渡，“十四五”后期将进入低水平持续状态；城市婴儿死亡率处于缓慢下降阶段，“十二五”后期将向低水平持续状态过渡。 [结论] 婴儿死亡率下降存在着内在的变化规律，理想的下降历程值得发展中国家因地制宜地学习借鉴。在不同的发展阶段应制定、落实更有针对性的防控策略与措施。
分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-27 合作期刊: 《数据智能（英文）》
摘要： The Chinese Software Developer Network (CSDN) is one of the largest information technology communities and service platforms in China. This paper describes the user profiling for CSDN, an evaluation track of SMP Cup 2017. It contains three tasks: (1) user document keyphrase extraction, (2) user tagging and (3) user growth value prediction. In the first task, we treat keyphrase extraction as a classification problem and train a Gradient-Boosting-Decision-Tree model with comprehensive features. In the second task, to deal with class imbalance and capture the interdependency between classes, we propose a two-stage framework: (1) for each class, we train a binary classifier to model each class against all of the other classes independently; (2) we feed the output of the trained classifiers into a softmax classifier, tagging each user with multiple labels. In the third task, we propose a comprehensive architecture to predict user growth value. Our contributions in this paper are summarized as follows: (1) we extract various types of features to identify the key factors in user value growth; (2) we use the semi-supervised method and the stacking technique to extend labeled data sets and increase the generality of the trained model, resulting in an impressive performance in our experiments. In the competition, we achieved the first place out of 329 teams.
分类： 核科学技术 >> 核聚变工程技术 提交时间： 2017-10-27
摘要： Purpose – The purpose of this paper is to develop a serial redundant manipulator system applied in nuclear fusion environment. It will allow remote inspection and maintenance of plasma facing components in the vacuum vessel of fusion device without breaking down the ultra-high vacuum condition during physical experiments. Design/methodology/approach – Firstly, considering the dynamic sealing of actuators to avoid polluting the vacuum condition inside fusion reactor, the mechanical design of robot system has been introduced. The redundant manipulator system has 11 degree of freedoms in total with an identical modular design. Besides, to improve the position accuracy, an error prediction model has been built based on the experimental study and back-propagation neural network (BPNN) algorithm. Findings – Currently, the implementation of the manipulator system has been successfully finished in both atmosphere and vacuum condition. The validation of BPNN model shown an acceptable prediction accuracy (94%~98%) compared with the real measurement. Originality/value – This is a special robot system which is practically used in a nuclear fusion device in China. Its design, mechanism and error prediction strategy have great reference values to the similar robots in vacuum and temperature applications.
分类： 药物科学 >> 药物设计 提交时间： 2024-05-13
Yulong Shi
Chongwu Li
Xinben Zhang
Cheng Peng
Peng Sun
Qian Zhang
Leilei Wu
Ying Ding
Dong Xie
Zhijian Xu
Weiliang Zhu
摘要： As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1,339 patients with EGFR mutations via literature mining. On the basis of D3EGFRdb, we developed a deep learning-based prediction model, D3EGFRAI, for drug sensitivity prediction of new EGFR mutation-driven NSCLC. Model validations of D3EGFRAI showed a prediction accuracy of 0.81 and 0.85 for patients from D3EGFRdb and our hospitals, respectively. Furthermore, mutation scanning of the crucial residues inside drug-binding pockets, which may occur in the future, was performed to explore their drug sensitivity changes. D3EGFR is the first platform to achieve clinical-level drug response prediction of all approved small molecule drugs for EGFR mutation-driven lung cancer and is freely accessible at https://www.d3pharma.com/D3EGFR/index.php.
分类： 信息科学与系统科学 >> 控制科学与技术 分类： 计算机科学 >> 计算机应用技术 提交时间： 2022-04-20
摘要： Process industry is the pillar industry of national economy, particularly, the process of producing magnesia by fused magnesia furnace system is a typical category of process industry. Due to the complex smelting mechanism and changing production factors, abnormal working conditions often occur in fused magnesia furnace. The semi-molten condition is the most typical and harmful abnormal condition. In this paper, an adaptive pretraining-inference-dynamic training-validation semantic segmentation method based on industrial video is proposed for dynamic prediction of semi-molten condition of multiple fused magnesium furnaces. The experimental results show that compared with the prediction model without adaptive learning, the prediction performance of the adaptive learning model in this paper for multiple fused magnesium melting processes is significantly improved.
分类： 天文学 >> 天文学 提交时间： 2018-05-28 合作期刊: 《天文研究与技术》
摘要： This paper is aimed at separation treatment of low- and high-frequency components in polar motion forecasting and thenimproving time-series predictions. For the purpose, the empirical mode decomposition (EMD) is employed as a filter to extract low- and high-frequency signals from original pole coordinate data. The decomposition of the pole motion observations between 1986 and 2015 from the International Earth Rotation and Reference Systems Service (IERS) C04 seriesillustrates that the low-frequency fluctuations including inter-decadal, inter-annual, Chandler and annual wobbles and shorter-period high-frequency oscillationscan be separated from the observed time-series by the EMD. On the basis of separation, the least-squares (LS) extrapolation of models for annual and Chandler wobbles and for the linear trend are used for deterministic prediction of the low-frequency fluctuations, while the autoregressive (AR) technology is applied to forecasting the high-frequency oscillations plus LS fitting residuals. Pole coordinateforecasts are calculated as the sum of LS extrapolation and AR predictions (LS+AR).We have evaluated the accuracy of our long-term predictions (up to 1 year in the future) in comparison with the IERS official predictions in terms of year-by-year statistics of 5 years. It is shown that the accuracy of the LS+AR methodcan be significantly improved using a combination of the EMD and LS+AR (EMD+LS+AR). Also, the proposed prediction strategyoverall outperforms the IERS solutions. In addition, the predictions are compared with those from the Earth Orientation Parameters Prediction Comparison Campaign (EOP PCC). The comparison demonstrates that the developed schemeis a very accurate approach to predict polar motion. According to this study, it is concluded that polar motion predictions may be enhanced through separation treatment of different time-scale fluctuations and thus such processing seems to be necessary in pole coordinate prediction.
分类： 药物科学 >> 药物设计 提交时间： 2024-02-20
Jin Liu
Yike Gui
Jingxin Rao
Jingjing Sun
Gang Wang
Qun Ren
Ning Qu
Buying Niu
Zhiyi Chen
Xia Sheng
Yitian Wang
Mingyue Zheng
Xutong Li
摘要： Ensuring drug safety in the early stages of drug development is crucial to avoid costly failures in subsequent phases. However, the economic burden associated with detecting drug off-targets and potential side effects through in vitro safety screening and animal testing is substantial. Drug off-target interactions, along with the adverse drug reactions they induce, are significant factors affecting drug safety. To assess the liability of candidate drugs, we developed an artificial intelligence model for the precise prediction of compound off-target interactions, leveraging multi-task graph neural networks. The outcomes of off-target predictions can serve as representations for compounds, enabling the differentiation of drugs under various ATC codes and the classification of compound toxicity. Furthermore, the predicted off-target profiles are employed in ADR enrichment analysis, facilitating the inference of potential ADRs for a drug. Using the withdrawn drug Pergolide as an example, we elucidate the mechanisms underlying ADRs at the target level, contributing to the exploration of the potential clinical relevance of newly predicted off-target interactions. Overall, our work facilitates the early assessment of compound safety/toxicity based on off-target identification, deduces potential ADRs of drugs, and ultimately promotes the secure development of drugs.
分类： 计算机科学 >> 自然语言理解与机器翻译 提交时间： 2024-01-03
摘要： League of Legends (LoL) is a highly popular multiplayer online competitive game, featuring intricate game mechanics and team cooperation, making the prediction of match outcomes a challenging task. This study utilizes a dataset from Kaggle, comprising 9,879 ranked matches ranging from Diamond I to Master tier, to build a machine learning model predicting the ultimate winner, either the blue or red team, based on the features of the first 10 minutes of gameplay. Through steps such as data loading, preprocessing, and feature engineering, we provided effective inputs for the model. For model selection, we opted for the Logistic Regression algorithm, achieving a model accuracy of 0.7277 through data splitting and training. This accuracy robustly supports predictions of the winning side, whether blue or red. However, to further enhance model performance, we recommend exploring additional feature en#2;gineering methods, investigating alternative machine learning algorithms, and fine-tuning hyperpa#2;rameters. The introduction of deep learning models is also a promising avenue to better capture the complex relationships within the game. Through these improvements, we anticipate increasing the models predictive accuracy for future matches, offering valuable insights for game development and enhancement.
分类： 地球科学 >> 地理学 提交时间： 2019-01-17 合作期刊: 《干旱区科学》
摘要： Snowfall is one of the dominant water resources in the mountainous regions and is closely related to the development of the local ecosystem and economy. Snowfall predication plays a critical role in understanding hydrological processes and forecasting natural disasters in the Tianshan Mountains, where meteorological stations are limited. Based on climatic, geographical and topographic variables at 27 meteorological stations during the cold season (October to April) from 1980 to 2015 in the Tianshan Mountains located in Xinjiang of Northwest China, we explored the potential influence of these variables on snowfall and predicted snowfall using two methods: multiple linear regression (MLR) model (a conventional measuring method) and random forest (RF) model (a non-parametric and non-linear machine learning algorithm). We identified the primary influencing factors of snowfall by ranking the importance of eight selected predictor variables based on the relative contribution of each variable in the two models. Model simulations were compared using different performance indices and the results showed that the RF model performed better than the MLR model, with a much higher R2 value (R2=0.74; R2, coefficient of determination) and a lower bias error (RSR=0.51; RSR, the ratio of root mean square error to standard deviation of observed dataset). This indicates that the non-linear trend is more applicable for explaining the relationship between the selected predictor variables and snowfall. Relative humidity, temperature and longitude were identified as three of the most important variables influencing snowfall and snowfall prediction in both models, while elevation, aspect and latitude were of secondary importance, followed by slope and wind speed. These results will be beneficial to understand hydrological modeling and improve management and prediction of water resources in the Tianshan Mountains.
分类： 物理学 >> 核物理学 提交时间： 2024-03-07
摘要： Predicting the transition-temperature shift (TTS) induced by neutron irradiation in reactor pressure-vessel (RPV) steels is important for the evaluation and extension of nuclear power-plant lifetimes. Current prediction models may fail to properly describe the embrittlement trend curves of Chinese domestic RPV steels with relatively low Cu content. Based on the screened surveillancedata of Chinese domestic and similar international RPV steels, we have developed a new fluence-dependent model for predicting the irradiation-embrittlement trend. The fast neutron fluence (E> 1 MeV) exhibited the highest correlation coefficient with the measured TTS data; thus, it is a crucial parameter in the prediction model. The chemical composition has little relevance to the TTSresidual calculated by the fluence-dependent model. The results show that the newly developed model with a simple power-law functional form of the neutron fluence is suitable for predicting the irradiation-embrittlement trend of Chinese domestic RPVs, regardless of the effect of the chemical composition.
分类： 生物学 >> 生物物理学 提交时间： 2016-05-11
Wang, Shuihua
Li, Yang
Du, Sidan
Wang, Shuihua
Zhang, Yudong
Chen, Mengmeng
Wu, Jane
Chen, Mengmeng
Wu, Jane
Chen, Mengmeng
Zhang, Yudong
Han, Liangxiu
摘要： Identification and detection of dendritic spines in neuron images are of high interest in diagnosis and treatment of neurological and psychiatric disorders (e.g., Alzheimer's disease, Parkinson's diseases, and autism). In this paper, we have proposed a novel automatic approach using wavelet-based conditional symmetric analysis and regularized morphological shared-weight neural networks (RMSNN) for dendritic spine identification involving the following steps: backbone extraction, localization of dendritic spines, and classification. First, a new algorithm based on wavelet transform and conditional symmetric analysis has been developed to extract backbone and locate the dendrite boundary. Then, the RMSNN has been proposed to classify the spines into three predefined categories (mushroom, thin, and stubby). We have compared our proposed approach against the existing methods. The experimental result demonstrates that the proposed approach can accurately locate the dendrite and accurately classify the spines into three categories with the accuracy of 99.1% for "mushroom" spines, 97.6% for "stubby" spines, and 98.6% for "thin" spines.
分类： 地球科学 >> 大气科学 提交时间： 2023-05-30 合作期刊: 《干旱区研究》
摘要： 利用19612020年中国西北地区东部夏季降水量月平均资料、NCEP/NCAR环流再分析以及英国Hadley逐月海表温度（SST）资料，采用功率谱、合成分析、多元线性回归等，分析了西北地区东部夏季年代际、年际降水分量的主导海温模态，并利用时间尺度分离前后得到海温因子分别建立降水预测模型。结果表明：（1）西北地区东部夏季降水不仅具有30 a左右的年代际震荡周期，还具有准3 a的年际周期，其中降水的年代际分量由太平洋十年际涛动（IPO）主导，春、夏季IPO正位相时，有利于西北地区东部夏季降水处于偏多的背景；反之，处于降水偏少背景。（2）降水年际分量的主导信号来自热带印度洋、热带西太平洋和北大西洋，当春季热带印度洋呈类全区一致海温模（IOBW）负（正）位相、类北大西洋三极子（NAT）为正（负）位相及热带西太平洋为冷（暖）海温异常时，有利于夏季中高纬贝加尔湖地区出现高（低）压异常，西太平洋副热带高压偏弱（强）、偏南（北），西北地区东部降水易偏少（多）。（3）独立检验时段内，基于时间尺度分离模型的西北地区东部夏季降水年均趋势异常综合评分（Ps）、符号一致率评分（Pc）分别较原始模型提高6%、7%，具有一定的预测能力。
分类： 生物学 >> 生物物理学 提交时间： 2016-05-11
Zhu, Pingping
Zhu, Pingping
Wang, Yanying
Du, Ying
Huang, Guanling
Zhang, Geng
Yan, Xinlong
Fan, Zusen
He, Lei
摘要： Liver cancer stem cells (CSCs) harbour self-renewal and differentiation properties, accounting for chemotherapy resistance and recurrence. However, the molecular mechanisms to sustain liver CSCs remain largely unknown. In this study, based on analysis of several hepatocellular carcinoma (HCC) transcriptome datasets and our experimental data, we find that C8orf4 is weakly expressed in HCC tumours and liver CSCs. C8orf4 attenuates the self-renewal capacity of liver CSCs and tumour propagation. We show that NOTCH2 is activated in liver CSCs. C8orf4 is located in the cytoplasm of HCC tumour cells and associates with the NOTCH2 intracellular domain, which impedes the nuclear translocation of N2ICD. C8orf4 deletion causes the nuclear translocation of N2ICD that triggers the NOTCH2 signalling, which sustains the stemness of liver CSCs. Finally, NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Altogether, C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signalling.
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