检索结果-内蒙古大学图书馆

SMAD7 and SERPINE1 as novel dynamic network biomarkers detect and regulate the tipping point of TGF-beta induced EMT

学校读者我要写书评

暂无评论

science Bulletin 2020年第10期65卷 842-853,M0004页

作者： Zhonglin Jiang Lina Lu Yuwei Liu Si Zhang Shuxian Li Guanyu Wang Peng Wang Luonan Chen Key Laboratory of Systems Biology Center for Excellence in Molecular Cell ScienceInstitute of Biochemistry and Cell BiologyShanghai Institutes for Biological SciencesChinese Academy of SciencesUniversity of Chinese Academy of SciencesShanghai 200031China Bio-med Big Data Center Key Laboratory of Computational BiologyCAS-MPG Partner Institute of Computational BiologyShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China Institute of Biomedical Sciences and School of Life Sciences East China Normal UniversityShanghai 200241China Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China School of Life Science and Technology ShanghaiTech UniversityShanghai 201210China Guangdong Provincial Key Laboratory of Cell Microenviroment and Disease Research Guangdong Provincial Key Laboratory of Computational Science and Material DesignDepartment of BiologySouthern University of Science and TechnologyShenzhen 518055China Laboratory of Systems Biology Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 200031China

Epithelial–mesenchymal transition(EMT) is a complex nonlinear biological process that plays essential roles in fundamental biological processes such as embryogenesis, wounding healing, tissue regeneration,and cancer metastasis. A hallmark of EMT is the switch-like behavior during state transition, which is characteristic of phase transitions. Hence, detecting the tipping point just before mesenchymal state transition is critical for understanding molecular mechanism of EMT. Through dynamic network biomarkers(DNB) model, a DNB group with 37 genes was identified which can provide the early-warning signals of EMT. Particularly, we found that two DNB genes, i.e., SMAD7 and SERPINE1 promoted EMT by switching their regulatory network which was further validated by biological experiments. Survival analyses revealed that SMAD7 and SERPINE1 as DNB genes further acted as prognostic biomarkers for lung adenocarcinoma.

关键词： Dynamic network biomarker Tipping point Epithelial–mesenchymal transition Bistability Quantitative real-time PCR

Full-Duplex ISCC for Low-Altitude networks: Resource Allocation and Coordinated Beamforming

学校读者我要写书评

暂无评论

arXiv 2025年

作者： Chen, Yiyang Liu, Wenchao Zhang, Xuhui Ren, Jinke Xing, Huijun Wang, Shuqiang Shen, Yanyan Southern University of Science and Technology Guangdong518055 China Guangdong518055 China Shenzhen Future Network of Intelligence Institute the School of Science and Engineering Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom SIAT CAS Guangdong518055 China Shenzhen University of Advanced Technology Guangdong518055 China

This paper investigates an integrated sensing, communication, and computing system deployed over low-altitude networks for enabling applications within the low-altitude economy. In the considered system, a full-duplex enabled unmanned aerial vehicle (UAV) is dispatched in the airspace, functioning as a UAV-enabled low-altitude platform (ULAP). The ULAP is capable of achieving simultaneous information transmission, target sensing, and mobile edge computing services. To reduce the overall energy consumption of the system while meeting the sensing beampattern threshold and user computation requirements, we formulate an energy consumption minimization problem by jointly optimizing the task allocation, computation resource allocation, transmit beamforming, and receive beamforming. Since the problem is non-convex and involves highly coupled variables, we propose an efficient algorithm based on alternation optimization, which decomposes the original problem into tractable convex subproblems. Moreover, we analyze the convergence and complexity of the proposed algorithm. Numerical results demonstrate that the proposed scheme saves up to 54.12% energy consumption performance compared to the benchmark schemes. Copyright © 2025, The Authors. All rights reserved.

关键词： Signaling

Role of left-hand cut contributions on pole extractions from lattice data: case study for Tcc(3875)+

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Du, Meng-Lin Filin, Arseniy Baru, Vadim Dong, Xiang-Kun Epelbaum, Evgeny Guo, Feng-Kun Hanhart, Christoph Nefediev, Alexey Nieves, Juan Wang, Qian School of Physics University of Electronic Science and Technology of China Chengdu611731 China Institut für Theoretische Physik II Ruhr-Universität Bochum BochumD-44780 Germany CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing100190 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China Peng Huanwu Collaborative Center for Research and Education Beihang University Beijing100191 China Institute for Advanced Simulation Institut für Kernphysik Jülich Center for Hadron Physics Forschungszentrum Jülich JülichD-52425 Germany Jozef Stefan Institute Jamova 39 Ljubljana1000 Slovenia CeFEMA Center of Physics and Engineering of Advanced Materials Instituto Superior Técnico Avenida Rovisco Pais 1 Lisboa1049-001 Portugal Institutos de Investigación de Paterna Apartado 22085 Valencia46071 Spain Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China

We discuss recent lattice data for the Tcc(3875)+ state to stress, for the first time, a potentially strong impact of left-hand cuts from the one-pion exchange on the pole extraction for near-threshold exotic states. In particular, if the left-hand cut is located close to the two-particle threshold, which happens naturally in the DD∗ system for the pion mass exceeding its physical value, the effective-range expansion is valid only in a very limited energy range up to the cut and as such is of little use to reliably extract the poles. Then, an accurate extraction of the pole locations requires the one-pion exchange to be implemented explicitly into the scattering amplitudes. Our findings are general and potentially relevant for a wide class of hadronic near-threshold states. © 2023, CC BY.

关键词： Poles

HAS-QA: Hierarchical answer spans model for open-domain question answering

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Pang, Liang Lan, Yanyan Guo, Jiafeng Xu, Jun Su, Lixin Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Department of Statistics University of California Berkeley

This paper is concerned with open-domain question answering (i.e., OpenQA). Recently, some works have viewed this problem as a reading comprehension (RC) task, and directly applied successful RC models to it. However, the performances of such models are not so good as that in the RC task. In our opinion, the perspective of RC ignores three characteristics in OpenQA task: 1) many paragraphs without the answer span are included in the data collection;2) multiple answer spans may exist within one given paragraph;3) the end position of an answer span is dependent with the start position. In this paper, we first propose a new probabilistic formulation of OpenQA, based on a three-level hierarchical structure, i.e., the question level, the paragraph level and the answer span level. Then a Hierarchical Answer Spans Model (HAS-QA) is designed to capture each probability. HAS-QA has the ability to tackle the above three problems, and experiments on public OpenQA datasets show that it significantly outperforms traditional RC baselines and recent OpenQA baselines. Copyright © 2019, The Authors. All rights reserved.

关键词：

Design of Target Behavior Intelligent Analysis System Based on Distributed computing

学校读者我要写书评

暂无评论

Design of Target Behavior Intelligent Analysis System Based ...

Signal, Information and data Processing (ICSIDP), IEEE International Conference on

作者： Xinlong Pan Xueqi Cheng Libo Yao Zhenqiu Zhu Biao Ding Tiantian Tang Minbo Li Chuanhui Liu CAS Key Laboratory of Network Data Science & Technology Inistitute of Computing Technology Beijing China Institute of Information Fusion Naval Aviation University Yantai China School of Software Fudan University Shanghai China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Through the fusion processing of target data obtained by radar, electronic reconnaissance, space reconnaissance, technical reconnaissance and civil cooperative system in early warning and surveillance system, multidimensional target data including explicit state information such as target attributes, type, position, speed and course could be obtained. The latent potential information, such as regular behavior, intention and threat degree, need to be mastered by human intelligence and experience analysis. It is urgent to use big data mining technology to realize intelligent analysis of target behavior. Based on the analysis of big data related technologies, this paper designs an intelligent target behavior analysis system based on distributed computing, which provides theoretical and technical support for intelligent upgrading of intelligence processing systems and command decision systems.

关键词：

Constraining ultralight vector dark matter with the Parkes Pulsar Timing Array second data release

学校读者我要写书评

暂无评论

Physical Review D 2022年第8期106卷 L081101-L081101页

作者： Yu-Mei Wu Zu-Cheng Chen Qing-Guo Huang Xingjiang Zhu N. D. Ramesh Bhat Yi Feng George Hobbs Richard N. Manchester Christopher J. Russell R. M. Shannon School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou 310024 China School of Physical Sciences University of Chinese Academy of Sciences No. 19A Yuquan Road Beijing 100049 China CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing 100190 China Department of Astronomy Beijing Normal University Beijing 100875 China Advanced Institute of Natural Sciences Beijing Normal University Zhuhai 519087 China International Centre for Radio Astronomy Research Curtin University Bentley Western Australia 6102 Australia Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou 311100 China Australia Telescope National Facility CSIRO Astronomy and Space Science P.O. Box 76 Epping New South Wales 1710 Australia CSIRO Scientific Computing Australian Technology Park Locked Bag 9013 Alexandria New South Wales 1435 Australia Centre for Astrophysics and Supercomputing Swinburne University of Technology Hawthorn Victoria 3122 Australia Australian Research Council Centre of Excellence in Gravitational Wave Discovery (OzGrav)

Composed of ultralight bosons, fuzzy dark matter provides an intriguing solution to challenges that the standard cold dark matter model encounters on subgalactic scales. The ultralight dark matter with mass m∼10−23 eV will induce a periodic oscillation in gravitational potentials with a frequency in the nanohertz band, leading to observable effects in the arrival times of radio pulses from pulsars. Unlike scalar dark matter, pulsar timing signals induced by the vector dark matter are dependent on the oscillation direction of the vector fields. In this work, we search for ultralight vector dark matter in the mass range of [2×10−24,2×10−22] eV through its gravitational effect in the Parkes Pulsar Timing Array (PPTA) second data release. Since no statistically significant detection is made, we place 95% upper limits on the local dark matter density as ρVF≲5 GeV/cm3 for m≲10−23 eV. As no preferred direction is found for the vector dark matter, these constraints are comparable to those given by the scalar dark matter search with an earlier 12-year dataset of PPTA.

关键词： Dark matter Gravitational waves

MatchZoo: A Learning, Practicing, and Developing System for Neural Text Matching

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Guo, Jiafeng Fan, Yixing Ji, Xiang Cheng, Xueqi University of Chinese Academy of Sciences Beijing China CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China Beijing Institute of Technology University Beijing China

Text matching is the core problem in many natural language processing (NLP) tasks, such as information retrieval, question answering, and conversation. Recently, deep leaning technology has been widely adopted for text matching, making neural text matching a new and active research domain. With a large number of neural matching models emerging rapidly, it becomes more and more difficult for researchers, especially those newcomers, to learn and understand these new models. Moreover, it is usually difficult to try these models due to the tedious data pre-processing, complicated parameter configuration, and massive optimization tricks, not to mention the unavailability of public codes sometimes. Finally, for researchers who want to develop new models, it is also not an easy task to implement a neural text matching model from scratch, and to compare with a bunch of existing models. In this paper, therefore, we present a novel system, namely MatchZoo, to facilitate the learning, practicing and designing of neural text matching models. The system consists of a powerful matching library and a user-friendly and interactive studio, which can help researchers: 1) to learn state-of-the-art neural text matching models systematically, 2) to train, test and apply these models with simple configurable steps;and 3) to develop their own models with rich APIs and assistance. Copyright © 2019, The Authors. All rights reserved.

关键词： Natural language processing systems

Transferring knowledge distillation for multilingual social event detection

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

SetRank: Learning a permutation-invariant ranking model for information retrieval

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Pang, Liang Xu, Jun Ai, Qingyao Lan, Yanyan Cheng, Xueqi Wen, Jirong CAS Key Lab of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China Renmin University of China Beijing China University of Utah United States

In learning-to-rank for information retrieval, a ranking model is automatically learned from the data and then utilized to rank the sets of retrieved documents. Therefore, an ideal ranking model would be a mapping from a document set to a permutation on the set, and should satisfy two critical requirements: (1) it should have the ability to model cross-document interactions so as to capture local context information in a query;(2) it should be permutation-invariant, which means that any permutation of the inputted documents would not change the output ranking. Previous studies on learning-to-rank either design uni-variate scoring functions that score each document separately, and thus failed to model the cross-document interactions;or construct multivariate scoring functions that score documents sequentially, which inevitably sacrifice the permutation invariance requirement. In this paper, we propose a neural learning-to-rank model called SetRank which directly learns a permutation-invariant ranking model defined on document sets of any size. SetRank employs a stack of (induced) multi-head self attention blocks as its key component for learning the embeddings for all of the retrieved documents jointly. The self-attention mechanism not only helps SetRank to capture the local context information from cross-document interactions, but also to learn permutation-equivariant representations for the inputted documents, which therefore achieving a permutation-invariant ranking model. Experimental results on three large scale benchmarks showed that the SetRank significantly outperformed the baselines include the traditional learning-to-rank models and state-of-the-art Neural IR models. Copyright © 2019, The Authors. All rights reserved.

关键词： Information retrieval