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Sampling with Prior Knowledge for High-dimensional Gravitational Wave Data Analysis

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Big Data Mining and Analytics 2022年第1期5卷 53-63页

作者： He Wang Zhoujian Cao Yue Zhou Zong-Kuan Guo zhixiang ren CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesP.O.Box 2735Beijing 100190China Department of Astronomy Beijing Normal UniversityBeijing 100875China the Department of Networked Intelligence Peng Cheng LaboratoryShenzhen 518055China

Extracting knowledge from high-dimensional data has been notoriously difficult,primarily due to the so-called"curse of dimensionality"and the complex joint distributions of these *** is a particularly profound issue for high-dimensional gravitational wave data analysis where one requires to conduct Bayesian inference and estimate joint posterior *** this study,we incorporate prior physical knowledge by sampling from desired interim distributions to develop the training ***,the more relevant regions of the high-dimensional feature space are covered by additional data points,such that the model can learn the subtle but important *** adapt the normalizing flow method to be more expressive and trainable,such that the information can be effectively extracted and represented by the transformation between the prior and target *** trained,our model only takes approximately 1 s on one V100 GPU to generate thousands of samples for probabilistic inference *** evaluation of our approach confirms the efficacy and efficiency of gravitational wave data inferences and points to a promising direction for similar *** source code,specifications,and detailed procedures are publicly accessible on GitHub.

关键词： high-dimensional data prior sampling normalizing flow gravitational wave

Taiji data challenge for exploring gravitational wave universe

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Frontiers of physics 2023年第6期18卷 93-106页

作者： zhixiang ren Tianyu Zhao Zhoujian Cao Zong-Kuan Guo Wen-Biao Han Hong-Bo Jin Yue-Liang Wu Taiji Laboratory for Gravitational Wave Universe University of Chinese Academy of Sciences(UCAS)Beijing 100049China Peng Cheng Laboratory Shenzhen 518055China Department of Astronomy Beijing Normal UniversityBeijing 100875China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUCASHangzhou 310024China CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China School of Physical Sciences UCASBeijing 100049China Shanghai Astronomical Observatory Chinese Academy of SciencesShanghai 200030China School of Astronomy and Space Science UCASBeijing 100049China International Centre for Theoretical Physics Asia-Pacific(ICTP-AP UNESCO)UCASBeijing 100190China Shanghai Frontiers Science Center for Gravitational Wave Detection Shanghai 200240China Key Laboratory of Computational Astrophysics National Astronomical ObservatoriesBeijing 100101China

The direct observation of gravitational waves(GWs)opens a new window for exploring new physics from quanta to cosmos and provides a new tool for probing the evolution of *** detection in space covers a broad spectrum ranging over more than four orders of magnitude and enables us to study rich physical and astronomical *** is a proposed space-based gravitational wave(GW)detection mission that will be launched in the *** will be exposed to numerous overlapping and persistent GW signals buried in the foreground and background,posing various data analysis *** order to empower potential scientific discoveries,the Mock Laser Interferometer Space Antenna(LISA)data challenge and the LISA data challenge(LDC)were *** LDC provides a baseline framework,the first LDC needs to be updated with more realistic simulations and adjusted detector responses for Taiji’s *** this paper,we review the scientific objectives and the roadmap for Taiji,as well as the technical difficulties in data analysis and the data generation strategy,and present the associated data *** contrast to LDC,we utilize second-order Keplerian orbit and second-generation time delay interferometry ***,we employ a new model for the extreme-mass-ratio inspiral waveform and stochastic GW background spectrum,which enables us to test general relativity and measure the non-Gaussianity of curvature ***,we present a comprehensive showcase of parameter estimation using a toy *** showcase not only demonstrates the scientific potential of the Taiji data challenge(TDC)but also serves to validate the effectiveness of the *** the first data challenge for Taiji,we aim to build an open ground for data analysis related to Taiji sources and *** details can be found on the official website(***).

关键词： gravitational wave universe evolution Taiji data challenge

Highly sensitive fluorescent sensing and photocatalytic degradation performance of two-dimensional Tb-organic network

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Journal of Rare Earths 2024年第2期42卷 303-313,I0003页

作者： Ting Gao Zhihu Ma Yixia ren zhixiang Wang Meili Zhang Xiaoli Chen Jijiang Wang Laboratory of New Energy and New Function Materials Shaanxi Key Laboratory of Chemical Reaction EngineeringCollege of Chemistry and Chemical EngineeringYan'an UniversityYan'an716000China

A novel tetra-nuclear Tb-organic network,named as [Tb_(4)(2-pyia)_(6)(HAc)_(0.5)(2,2'-bipy)(H_(2)O)_(4.5)]·2,2'-bipy·H_(2)O(1),was synthesized hydrothermally based on 5-(pyridin-2-ylmethoxy) isophthalic acid(H_(2)pyia) and 2,2'-bipyridine(2,2'-bipy) ligands,and characterized by single crystal X-ray diffraction,thermogravimetric(TG) analyses,powder X-ray diffraction(PXRD) and infrared(IR) technology.1 possesses a two-dimensional network based on the tetra-nuclear inorganic building units,and the π-πstacking interactions between the pyia^(2-) ligands and the guest 2,2'-bipy molecules play an important role in the forming of 3D supramolecular structure.1 exhibits excellent fluorescent sensing performance for Fe^(3+)(1.26×10^(-8) mol/L),Cr_(2)O_(7)^(2-)(8.1×10^(-7) mol/L),2,4,6-trinitrophenol(TNP)(2.71×10^(-8) mol/L)and tetracycline(TCT)(2.76×10^(-7) mol/L) in aqueous solution with lower detection *** sensing mechanisms of 1 were investigated by density functional theory(DFT) calculations,ultraviolet-visible(UV-Vis) diffuse reflectance spectroscopy,PXRD and fluorescent lifetime *** activated product of 1 was prepared by heating at 255℃ under constant pressure and used to photo-catalytically degrade *** 1 and the activated one have good photocatalytic degradation performance for TCT with degradation rates of 84.29% and 96.07%,*** photocatalytic mechanisms were discovered by UV-Vis diffuse reflectance spectroscopy and radical trap *** Tb-organic framework might be an excellent multifunctional fluorescent sensor and a good photocatalytic agent for TCT degradation in the future.

关键词： Tb-organic network Fluorescent sensing Photocatalytic degradation Rare earths

Oncolytic adenoviruses expressing checkpoint inhibitors for cancer therapy

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Signal Transduction and Targeted Therapy 2023年第12期8卷 5954-5969页

作者： Daoyuan Xie Yaomei Tian Die Hu Yuanda Wang Yuling Yang Bailing Zhou Rui Zhang zhixiang ren Mohan Liu Jie Xu Chunyan Dong Binyan Zhao Li Yang Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan UniversityChengdu 610041China College of Bioengineering Sichuan University of Science&EngineeringZigong 643000China Frontiers Medical Center Tianfu Jincheng LaboratoryChengdu 610212China

Despite the remarkable success of immune checkpoint inhibitors(ICIs),primary resistance to ICIs causes only subsets of patients to achieve durable responses due to the complex tumor microenvironment(TME).Oncolytic viruses(OVs)can overcome the immunosuppressive TME and promote systemic antitumor immunity in *** OVs armed with ICIs would likely have improved effectiveness as a cancer *** to the diverse immune cell landscapes among different types of tumors,we rationally and precisely generated three recombinant oncolytic adenoviruses(OAds):OAd-SIRPα-Fc,OAd-Siglec10-Fc and *** viruses were designed to locally deliver SIRPα-Fc,Siglec10-Fc or TIGIT-Fc fusion proteins recognizing CD47,CD24 or CD155,respectively,in the TME to achieve enhanced antitumor *** results suggested that OAd-SIRPα-Fc and OAd-Siglec10-Fc both showed outstanding efficacy in tumor suppression of macrophage-dominated tumors,while OAd-TIGIT-Fc showed the best antitumor immunity in CD8+T-cell-dominated ***,the recombinant OAds activated an inflammatory immune response and generated long-term antitumor *** addition,the combination of OAd-Siglec10-Fc with anti-PD-1 significantly enhanced the antitumor effect in a 4T1 tumor model by remodeling the *** summary,rationally designed OAds expressing ICIs tailored to the immune cell landscape in the TME can precisely achieve tumor-specific immunotherapy of cancer.

关键词： immunity expressing landscape

Attention-Based Deep Learning Model for Image Desaturation of SDO/AIA

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Research in Astronomy and Astrophysics 2023年第8期23卷 92-102页

作者： Xinze Zhang Long Xu zhixiang ren Xuexin Yu Jia Li State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Peng Cheng Laboratory Shenzhen 518000China Department of Automation Tsinghua UniversityBeijing 100084China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

The Atmospheric Imaging Assembly(AIA)onboard the Solar Dynamics Observatory(SDO)captures full-disk solar images in seven extreme ultraviolet wave *** a violent solar flare occurs,incoming photoflux may exceed the threshold of an optical imaging system,resulting in regional saturation/overexposure of ***,the lost signal can be partially retrieved from non-local unsaturated regions of an image according to scattering and diffraction principle,which is well consistent with the attention mechanism in deep ***,an attention augmented convolutional neural network(AANet)is proposed to perform image desaturation of SDO/AIA in this *** is built on a U-Net backbone network with partial convolution and adversarial *** addition,a lightweight attention model,namely criss-cross attention,is embedded between each two convolution layers to enhance the backbone *** results validate the superiority of the proposed AANet beyond state-of-the-arts from both quantitative and qualitative comparisons.

关键词： techniques image processing-Sun atmosphere-Sun flares

Super-resolution of Solar Magnetograms Using Deep Learning

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Research in Astronomy and Astrophysics 2022年第8期22卷 218-229页

作者： Fengping Dou Long Xu zhixiang ren Dong Zhao Xinze Zhang State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Peng Cheng National Laboratory Shenzhen 518000China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Currently,data-driven models of solar activity forecast are investigated extensively by using machine *** model training,it is highly demanded to establish a large database which may contain observations coming from different instruments with different spatio-temporal *** this paper,we employ deep learning models for super-resolution(SR)of magnetogram of Michelson Doppler Imager(MDI)in order to achieve the same spatial resolution of Helioseismic and Magnetic Imager(HMI).First,a generative adversarial network(GAN)is designed to transfer characteristics of MDI onto downscaled HMI,getting low-resolution HMI magnetogram in the same domain as ***,with the paired low-resolution and high-resolution HMI magnetograms,another GAN is trained in a supervised learning way,which consists of two streams,one is for generating high-fidelity image content,the other is explicitly optimized for generating elaborate image ***,these two streams work together to guarantee both high-fidelity and photorealistic super-resolved *** results demonstrate that the proposed method can generate super-resolved magnetograms with perceptual-pleasant visual ***,the best PSNR,LPIPS,RMSE,comparable SSIM and CC are obtained by the proposed *** source code and data set can be accessed via https://***/filterbank/SPSR.

关键词： techniques:image processing Sun:magnetic fields Sun:atmosphere

Generative pretrained transformer 4:an innovative approach to facilitate value-based healthcare

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Intelligent Medicine 2024年第1期4卷 10-15页

作者： Han Lyu zhixiang Wang Jia Li Jing Sun Xinghao Wang Pengling ren Linkun Cai Zhenchang Wang Max Wintermark Department of Radiology Capital Medical University Affiliated Beijing Friendship HospitalBeijing 100050China Department of Medical Imaging Capital Medical University Affiliated Beijing Friendship HospitalBeijing 100050China School of Biological Science and Medical Engineering Beihang UniversityBeijing 100191China Department of Neuroradiology University of Texas MD Anderson CenterHoustonTX 77030USA

Objective Appropriate medical imaging is important for value-based *** aim to evaluate the performance of generative pretrained transformer 4(GPT-4),an innovative natural language processing model,providing appropriate medical imaging automatically in different clinical *** Institutional Review Boards(IRB)approval was not required due to the use of nonidentifiable ***,we used 112 questions from the American College of Radiology(ACR)Radiology-TEACHES Program as prompts,which is an open-sourced question and answer program to guide appropriate medical *** included 69 free-text case vignettes and 43 simplified *** the performance evaluation of GPT-4 and GPT-3.5,we considered the recommendations of ACR guidelines as the gold standard,and then three radiologists analyzed the consistency of the responses from the GPT models with those of the *** set a five-score criterion for the evaluation of the consistency.A paired t-test was applied to assess the statistical significance of the *** For the performance of the GPT models in free-text case vignettes,the accuracy of GPT-4 was 92.9%,whereas the accuracy of GPT-3.5 was just 78.3%.GPT-4 can provide more appropriate suggestions to reduce the overutilization of medical imaging than GPT-3.5(t=3.429,P=0.001).For the performance of the GPT models in simplified scenarios,the accuracy of GPT-4 and GPT-3.5 was 66.5%and 60.0%,*** differences were not statistically significant(t=1.858,P=0.070).GPT-4 was characterized by longer reaction times(27.1 s in average)and extensive responses(137.1 words on average)than *** As an advanced tool for improving value-based healthcare in clinics,GPT-4 may guide appropriate medical imaging accurately and efficiently。

关键词： Generative pretrained transformer 4 model Natural language processing Medical imaging Appropriateness

BioTreasury:a community-based repository enabling indexing and rating of bioinformatics tools

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Science China(Life Sciences) 2024年第2期67卷 221-229页

作者： Qi Zhao Xin Zhou Jingxing Wu Jieyi Cai Xiaoqiong Bao Lin Tang Chaoye Wang Chunlei Liu Yukai Wang Yuyan Teng Mohan Zheng Weiping Mu zhixiang Zuo Yubin Xie Xiaotong Luo Jian ren School of Life Sciences State Key Laboratory of Oncology in South ChinaCancer CenterGuangdong Provincial Clinical Research Center for CancerSun Yat-sen UniversityGuangzhou 510060China Institute of Precision Medicine The First Affiliated HospitalSun Yat-sen UniversityGuangzhou 510080China Guangdong Institute of Gastroenterology Department of General SurgeryGuangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseasesThe Sixth Affiliated HospitalSun Yat-sen UniversityGuangzhou 510275China

The exponential growth of bioinformatics tools in recent years has posed challenges for scientists in selecting the most suitable one for their data analysis ***,to aid scientists in making informed choices,a community-based platform that indexes and rates bioinformatics tools is urgently *** this study,we introduce Bio Treasury(http://***),an integrated communitybased repository that provides an interactive platform for users and developers to share their experiences in various bioinformatics *** Treasury offers a comprehensive collection of well-indexed bioinformatics software,tools,and databases,totaling over 10,000 *** the past two years,we have continuously improved and maintained Bio Treasury,adding several exciting features,including creating structured homepages for every tool and user,a hierarchical category of bioinformatics tools and classifying tools using large language model(LLM).Bio Treasury streamlines the tool submission process with intelligent ***,Bio Treasury provides a wide range of social features,for example,enabling users to participate in interactive discussions,rate tools,build and share tool collections for the *** believe Bio Treasury can be a valuable resource and knowledge-sharing platform for the biomedical *** empowers researchers to effectively discover and evaluate bioinformatics tools,fostering collaboration and advancing bioinformatics research.

关键词： bioinformatics tools index tool database rating system large language model tool collections shari

AIPerf: Automated Machine Learning as an AI-HPC Benchmark

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Big Data Mining and Analytics 2021年第3期4卷 208-220页

作者： zhixiang ren Yongheng Liu Tianhui Shi Lei Xie Yue Zhou Jidong Zhai Youhui Zhang Yunquan Zhang Wenguang Chen Peng Cheng National Laboratory Shenzhen 518000China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Institute of Computing Technology Chinese Academy of SciencesBeijing 100086China

The plethora of complex Artificial Intelligence(AI)algorithms and available High-Performance Computing(HPC)power stimulates the expeditious development of AI components with heterogeneous ***,the need for cross-stack performance benchmarking of AI-HPC systems has rapidly *** particular,the de facto HPC benchmark,LINPACK,cannot reflect the AI computing power and input/output performance without a representative *** popular AI benchmarks,such as MLPerf,have a fixed problem size and therefore limited *** address these issues,we propose an end-to-end benchmark suite utilizing automated machine learning,which not only represents real AI scenarios,but also is auto-adaptively scalable to various scales of *** implement the algorithms in a highly parallel and flexible way to ensure the efficiency and optimization potential on diverse systems with customizable *** utilize Operations Per Second(OPS),which is measured in an analytical and systematic approach,as a major metric to quantify the AI *** perform evaluations on various systems to ensure the benchmark’s stability and scalability,from 4 nodes with 32 NVIDIA Tesla T4(56.1 Tera-OPS measured)up to 512 nodes with 4096 Huawei Ascend 910(194.53 Peta-OPS measured),and the results show near-linear weak *** a flexible workload and single metric,AIPerf can easily scale on and rank AI-HPC,providing a powerful benchmark suite for the coming supercomputing era.

关键词： High-Performance Computing(HPC) Artificial Intelligence(AI) automated machine learning