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31st International Symposium on computational Geometry, SoCG 2015

作者： Agarwal, Pankaj K. Mølhave, Thomas Revsbæk, Morten Safa, Issam Wang, Yusu Yang, Jungwoo Department of Computer Science Duke University United States Scalable Algorithmics SCALGO United States MADALGO Center for Massive Data Algorithmics Aarhus University Denmark Computational Lithography Group Intel Corporation United States Department of Computer Science and Engineering Ohio State University United States

ISBN: (纸本)9783939897835

We study the problem of maintaining the contour tree T of a terrain σ, represented as a triangulated xy-monotone surface, as the heights of its vertices vary continuously with time. We characterize the combinatorial changes in T and how they relate to topological changes in. We present a kinetic data structure (KDS) for maintaining T efficiently. It maintains certificates that fail, i.e., an event occurs, only when the heights of two adjacent vertices become equal or two saddle vertices appear on the same contour. Assuming that the heights of two vertices of κ become equal only O(1) times and these instances can be computed in O(1) time, the KDS processes O(κ + n) events, where n is the number of vertices in σ and κ;is the number of events at which the combinatorial structure of T changes, and processes each event in O(log n) time. The KDS can be extended to maintain an augmented contour tree and a join/split tree.

关键词： Trees (mathematics)

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Nat Genet:单细胞分析解开结直肠癌细胞的神秘面纱

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现代生物医学进展 2017年第15期17卷 I0003-I0003页

作者： Huipeng Li, Elise T Courtois, Debarka Sengupta, Yuliana Tan Shyam Prabhakar Elise T Courtois, Yuliana Tan Paul Robson Debarka Sengupta Kok Hao Chen, Jolene Jie Lin Goh Paul Jongjoon Choi Say Li Kong, Axel M Hillmer Iain Beehuat Tan Clarinda Chua Iain Beehuat Tan Lim Kiat Hon Wah Siew Tan Mark Wong Lawrence J K Wee Iain Beehuat Tan Paul Robson Paul Robson Paul Robson Computational and Systems Biology Genome Institute of Singapore Singapore Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India Synthetic Biology Genome Institute of Singapore Singapore Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Department of Medical Oncology National Cancer Centre Singapore Singapore Department of Pathology Singapore General Hospital Singapore Department of Colorectal Surgery Singapore General Hospital Singapore Data Analytics Department Institute for Infocomm Research Singapore Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA Department of Biological Sciences National University of Singapore Singapore.

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测... 详细信息

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测序。”JAX科学家、这篇发表在Nature Genetics上的文章共同第一作者Elise Courtois说道。”我们可以根据肿瘤中的细胞组成将结直肠癌进一步分类。因为每种亚型的肿瘤病人生存率存在差别，我们的方法将为肿瘤医生提供更多的关于肿瘤预后和治疗的信息。”

关键词：单细胞分析结直肠癌癌细胞 Nat 细胞组成肿瘤病计算机技术细胞生物学

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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Author Correction: Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

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Nature genetics 2018年第12期50卷 1754页

作者： Huipeng Li Elise T Courtois Debarka Sengupta Yuliana Tan Kok Hao Chen Jolene Jie Lin Goh Say Li Kong Clarinda Chua Lim Kiat Hon Wah Siew Tan Mark Wong Igor Cima Min-Han Tan Lawrence J K Wee Axel M Hillmer Iain Beehuat Tan Paul Robson Shyam Prabhakar Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India. Synthetic Biology Genome Institute of Singapore Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. Department of Pathology Singapore General Hospital Singapore Singapore. Department of Colorectal Surgery Singapore General Hospital Singapore Singapore. Institute of Bioengineering and Nanotechnology Singapore Singapore. Data Analytics Department Institute for Infocomm Research Singapore Singapore. Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Department of Medical Oncology National Cancer Centre Singapore Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore. iain.tan.b.h@singhealth.com.sg. Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Singapore. paul.robson@***. The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA. paul.robson@***. Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA. paul.robson@***. Department of Biological Sciences National University of Singapore Singapore Singapore. paul.robson@***. Computational and Systems Biology Genome Institute of Singapore Singapore Singapore. prabhakars@gis.a-star.edu.sg.

In the version of the article published, the author list is not accurate. Igor Cima and Min-Han Tan should have been authors, appearing after Mark Wong in the author list, while Paul Jongjoon Choi should not have been listed as an author. Igor Cima and Min-Han Tan both have the affiliation Institute of Bioengineering and Nanotechnology, Singapore, Singapore, and their contributions should have been noted in the Author Contributions section as "I.C. preprocessed Primary Cell Atlas data with inputs from M.-H.T." The following description of the contribution of Paul Jongjoon Choi should not have appeared: "P.J.C. supported the smFISH experiments." In the 'RCA: global panel' section of the Online Methods, the following sentence should have appeared as the second sentence, "An expression atlas of human primary cells (the Primary Cell Atlas) was preprocessed similarly to in ref. 55," with new reference 55 (Cima, I. et al. Tumor-derived circulating endothelial cell clusters in colorectal cancer. science Transl. Med. 8, 345ra89, 2016).

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From categorical to numerical: Multiple transitive distance learning and embedding

From categorical to numerical: Multiple transitive distance ...

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SIAM International Conference on data Mining 2015, SDM 2015

作者： Zhang, Kai Wang, Qiaojun Chen, Zhengzhang Marsic, Ivan Kumar, Vipin Jiang, Guofei Zhang, Jie School of Computer Science Southwest Petroleum University Chengdu Sichuan Province610500 China Institute of Data Science and Technology Alibaba Group SeattleWA98101 United States Department of Electrical and Computer Engineering Rutger-s the State University of New Jersey NJ08854 United States NEC Laboratories America Inc. PrincetonNJ08540 United States Department of Electrical Engineering and Computer Science Northwestern University EvanstonIL60208 United States Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States Center for Computational Systems Biology Fudan University Shanghai200433 China

ISBN: (纸本)9781510811522

Categorical data are ubiquitous in real-world databases. However, due to the lack of an intrinsic proximity measure, many powerful algorithms for numerical data analysis may not work well on their categorical counterparts, making it a bottleneck in practical applications. In this paper, we propose a novel method to transform categorical data to numerical representations, so that abundant numerical learning methods can be exploited in categorical data mining. Our key idea is to learn a pairwise dissimilarity among categorical symbol-s, henceforth a continuous embedding, which can then be used for subsequent numerical treatment. There are two important criteria for learning the dissimilarities. First, it should capture the important "transitivity" which has shown to be particularly useful in measuring the proximity relation in categorical data. Second, the pairwise sample geometry arising from the learned symbol distances should be maximally consistent with prior knowledge (e.g., class labels) to obtain a good generalization performance. We achieve them through multiple transitive distance learning and embedding. Encouraging results are observed on a number of benchmark classification tasks against state-of-the-art. Copyright © SIAM.

关键词： Distance education

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Precision Medicine:What Challenges Are We Facing?

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Genomics, Proteomics & Bioinformatics 2016年第5期14卷 253-261页

作者： Yu Xue Eric-Wubbo Lameijer Kai Ye Kunlin Zhang Suhua Chang Xiaoyue Wang Jianmin Wu Ge Gao Fangqing Zhao Jian Li Chunsheng Han Shuhua Xu Jingfa Xiao Xuerui Yang Xiaomin Ying Xuegong Zhang Wei-Hua Chen Yun Liu Zhang Zhang Kun Huang Jun Yu MOE Key Lahoratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Brain ScienceHuazhong University of Science and TechnologyWuhan 430074China School of Electronic and Information Engineering.Xi'an Jiaotong University.Xi'an 710049 China CAS Key Laboratory of Mental Health Institute of PsychologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of'Medical Molecular Biology Institute of Basic Medical SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijing 100005China MOE Beijing Key Laboratory of Carcinogenesis and Translatiooal ResearchCenter for Cancer BioinformaticsPeking University Cancer Hospital&InstituteBeijing 100142China Center for Bioinformatics State Key Laboratory of Protein and Plant Gene ResearchSchool of Life SciencesPeking UniversityBeijing 100871China Beijing Institutes of Life Science.Chinese Academy of Sciences Beijing 100101China MOE Key Lahoratory of Developnlental Genes and Human Disease Institute of Life SciencesSoutheast UniversityNanjing 210096China State Key Laboratory of Stem Cell and Reproductive Biology Institute of Zoology Chinese Academy of SciencesBeijing 100101China Max Planck Independent Research Group on Population Genomics CAS-MPG Partner Institute for Computational Biology(PICB)Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China CAS Ker Laboratory of Genome Sciences and Information Chinese Academy of Sciences.Beijing 100101China MOE Key Laboratory of Bioinformatics School of Life Sciences Center for Synthetic and Systems BiologyTsinghua UniversityBeijing 100084China Computational Omics Lahoratory Center of Computational BiologyBeijing Institute of Basic Medical SciencesBeijing 100850China Bioinformatics Division TNLIST and MOE Key Laboratory for Bioinformatics Department of AutomationTsinghua UniversityBeijing 100084China Department of Bioinformatics and Systems Biology College of LifeScience and Technol

Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several n... 详细信息

关键词： PMI Precision Medicine data We

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Investigation on the influence of atomic potentials on the above threshold ionization

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Chinese Physics B 2014年第5期23卷 238-243页

作者：田原野李苏宇魏珊珊郭福明曾思良陈基根杨玉军 Institute of Atomic and Molecular Physics Jilin University Data Center for High Energy Density Physics Institute of Applied Physics and Computational Mathematics Science and Technology Computation Physics Laboratory Institute of Applied Physics and Computational Mathematics Department of Physics and Materials Engineering Taizhou University

We systematically investigate the influence of atomic potentials on the above-threshold ionization （ATI） spectra in one-dimensional （1D） cases and compare them with the three-dimensional （3D） case by numerically solving the time-dependent Schrrdinger equation. It is found that the direct ionization plateau and the rescattering plateau of the ATI spectrum in the 3D case can be well reproduced by the 1D ATI spectra calculated from the supersolid-core potential and the soft-core potential, respectively. By analyzing the factors that affect the yield of the ATI spectrum, we propose a modified-potential with which we can reproduce the overall 3D ATI spectrum. In addition, the influence of the incident laser intensities and frequencies on the ATI spectra calculated from the proposed modified potential is studied.

关键词： above threshold ionization model potential angular distribution of photoelectron

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Sustainable computational science: The Rescience initiative

arXiv

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arXiv 2017年

作者： Rougier, Nicolas P. Hinsen, Konrad Alexandre, Frédéric Arildsen, Thomas Barba, Lorena Benureau, Fabien C.Y. Titus Brown, C. de Buyl, Pierre Caglayan, Ozan Davison, Andrew P. Delsuc, Marc André Detorakis, Georgios Diem, Alexandra K. Drix, Damien Enel, Pierre Girard, Benoît Guest, Olivia Hall, Matt G. Henriques, Rafael Neto Hinaut, Xavier Jaron, Kamil S. Khamassi, Mehdi Klein, Almar Manninen, Tiina Marchesi, Pietro McGlinn, Dan Metzner, Christoph Petchey, Owen L. Plesser, Hans Ekkehard Poisot, Timothée Ram, Karthik Ram, Yoav Roesch, Etienne Rossant, Cyrille Rostami, Vahid Shifman, Aaron Stimberg, Marcel Stachelek, Joseph Stollmeier, Frank Vaggi, Federico Viejo, Guillaume Vitay, Julien Vostinar, Anya Yurchak, Roman Zito, Tiziano INRIA Bordeaux Sud-Ouest Talence France Institut des Maladies Neurodégénératives Université de Bordeaux CNRS UMR 5293 Bordeaux France LaBRI Université de Bordeaux Bordeaux INP CNRS UMR 5800 Talence France Centre de Biophysique Moléculaire CNRS UPR4301 Orléans France Synchrotron SOLEIL Division Expériences Gif sur Yvette France Department of Electronic Systems Technical Faculty of IT and Design Aalborg University Denmark Department of Mechanical and Aerospace Engineering George Washington University WashingtonDC United States Department of Population Health and Reproduction University of California Davis DavisCA United States Instituut voor Theoretische Fysica KU Leuven Belgium Le Mans France Unité de Neurosciences Information et Complexité CNRS FRE 3693 Gif sur Yvette France Institut de Génétique et de Biologie Moléculaire et Cellulaire INSERM U964 CNRS UMR 7104 Université de Strasbourg Illkirch France Department of Cognitive Sciences University of California Irvine United States Computational Engineering and Design Faculty of Engineering and the Environment University of Southampton United Kingdom Department of Computer Science Humboldt-Universität zu Berlin Friedman Brain Institute Icahn School of Medicine Mount SinaiNY United States Institut des Systèmes Intelligent et de Robotique Sorbonne Universités UPMC Univ Paris 06 CNRS Paris France Experimental Psychology University College London United Kingdom UCL Great Ormond St Institute of Child Health University College London London United Kingdom MRC Cognition and Brain Sciences Unit Cambridge United Kingdom Department of Ecology and Evolution University of Lausanne Lausanne Switzerland Independent scholar Enschede Netherlands BioMediTech Institute and Faculty of Biomedical Sciences and Engineering Tampere University of Technology Tampere Finland Swammerdam Institute for Life Sciences Center for Neuroscience Faculty of Science University of Amsterdam Amsterdam Netherlands Depart

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. Jonathan Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. Rescience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. Rescience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests. Copyright © 2017, The Authors. All rights reserved.

关键词： Open source software

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Dense matter with eXTP

arXiv

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arXiv 2018年

作者： Watts, Anna L. Yu, Wenfei Poutanen, Juri Zhang, Shu Bhattacharyya, Sudip Bogdanov, Slavko Ji, Long Patruno, Alessandro Riley, Thomas E. Bakala, Pavel Baykal, Altan Bernardini, Federico Bombaci, Ignazio Brown, Edward Cavecchi, Yuri Chakrabarty, Deepto Chenevez, Jérôme Degenaar, Nathalie Santo, Melania Del Salvo, Tiziana Di Doroshenko, Victor Falanga, Maurizio Ferdman, Robert D. Feroci, Marco Gambino, Angelo F. Ge, MingYu Greif, Svenja K. Guillot, Sebastien Gungor, Can Hartmann, Dieter H. Hebeler, Kai Heger, Alexander Homan, Jeroen Iaria, Rosario in’t Zand, Jean Kargaltsev, Oleg Kurkela, Aleksi Lai, Xiaoyu Li, Ang Li, XiangDong Li, Zhaosheng Linares, Manuel Lu, FangJun Mahmoodifar, Simin Méndez, Mariano Miller, M. Coleman Morsink, Sharon Nättilä, Joonas Possenti, Andrea Prescod-Weinstein, Chanda Qu, JinLu Riggio, Alessandro Salmi, Tuomo Sanna, Andrea Santangelo, Andrea Schatz, Hendrik Schwenk, Achim Song, LiMing Šrámková, Eva Stappers, Benjamin Stiele, Holger Strohmayer, Tod Tews, Ingo Tolos, Laura Török, Gabriel Tsang, David Urbanec, Martin Vacchi, Andrea Xu, RenXin Xu, Ypeng Zane, Silvia Zhang, Guobao Zhang, ShuangNan Zhang, Wenda Zheng, ShiJie Zhou, Xia Anton Pannekoek Institute for Astronomy University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Shanghai Astronomical Observatory Shanghai200030 China Tuorla Observatory Department of Physics and Astronomy University of Turku Väisäläntie 20 PiikkiöFIN-21500 Finland Nordita KTH Royal Institute of Technology Stockholm University Roslagstullsbacken 23 StockholmSE-10691 Sweden Institute of High Energy Physics CAS Beijing100049 China Tata Institute of Fundamental Research Mumbai400005 India Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Institut für Astronomie und Astrophysik Tübingen Universität Tübingen Sand 1 TübingenD-72076 Germany Leiden Observatory Leiden University PO Box 9513 Leiden2300 RA Netherlands Research Center for Computational Physics and Data Processing Silesian University in Opava Bezrucovo nam. 13 OpavaCZ-74601 Czech Republic Physics Department Middle East Technical University Ankara06531 Turkey INAF Osservatorio Astronomico di Roma Via Frascati 33 Monteporzio CatoneI-00078 Italy New York University Abu Dhabi PO Box 129188 Abu Dhabi United Arab Emirates Dipartimento di Fisica Enrico Fermi University of Pisa PisaI-56127 Italy INFN Italian National Institute for Nuclear Physics Pisa Section Pisa56127 Italy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Mathematical Sciences and STAG Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom MIT Kavli Institute for Astrophysics and Space Research CambridgeMA02139 United States DTU Space Technical University of Denmark Elektrovej 327-328 Kgs Lyngby2800 Denmark INAF/IASF Palermo via Ugo La Malfa 153 PalermoI-90146 Italy Universita degli Studi di Palermo Dipartimento di Fisica e Chimica via Archira 36 Palermo90123 Italy

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter;neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of science, the eXTP mission is expected to be launched in the mid 2020s. Copyright © 2018, The Authors. All rights reserved.

关键词： Pulsars

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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intensive CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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