检索结果-内蒙古大学图书馆

SciOps: Achieving Productivity and reliability in data-Intensive research

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Johnson, Erik C. Nguyen, Thinh T. dichter, Benjamin K. Zappulla, Frank Kosma, Montgomery Gunalan, Kabilar Halchenko, Yaroslav O. Neufeld, Shay Q. ratan, Kristen Edwards, Nicholas J. ressl, Susanne Heilbronner, Sarah r. Schirner, Michael ritter, Petra Wester, Brock Ghosh, Satrajit Martone, Maryann E. Pestilli, Franco Yatsenko, dimitri Research and Exploratory Development Department Johns Hopkins University Applied Physics Laboratory LaurelMD United States DataJoint Inc. HoustonTX United States CatalystNeuro BeniciaCA United States Digital R&D Creation Center Pfizer Inc. United States McGovern Institute for Brain Research Massachusetts Institute of Technology CambridgeMA United States Center for Open Neuroscience Department of Psychological and Brain Sciences Dartmouth College New Hampshire United States Inscopix a Bruker company Mountain ViewCA United States Santa CruzCA United States Happy Potato Inc. IssaquahWA United States Department of Neuroscience University of Texas at Austin AustinTX United States Neurosurgery Baylor College of Medicine HoustonTX United States Charité – Universitätsmedizin Berlin Berlin Germany Department of Neurology with Experimental Neurology Charité Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin Humboldt Universität zu Berlin Berlin Germany Bernstein Focus State Dependencies of Learning Bernstein Center for Computational Neuroscience Berlin Germany Einstein Center for Neuroscience Berlin Berlin Germany Einstein Center Digital Future Berlin Germany Department of Otolaryngology Harvard Medical School BostonMA United States Department of Neurosciences University of California La Jolla San DiegoCA United States Department of Psychology University of Texas Austin AustinTX United States

Scientists are increasingly leveraging advances in instruments, automation, and collaborative tools to scale up their experiments and research goals, leading to new bursts of discovery. Various scientific disciplines, including neuroscience, have adopted key technologies to enhance collaboration, reproducibility, and automation. drawing inspiration from advancements in the software industry, we present a roadmap to enhance the reliability and scalability of scientific operations for diverse research teams tackling large and complex projects. We introduce a five-level Capability Maturity Model describing the principles of rigorous scientific operations in projects ranging from small-scale exploratory studies to large-scale, multi-disciplinary research endeavors. Achieving higher levels of operational maturity necessitates the adoption of new, technology-enabled methodologies, which we refer to as "SciOps." This concept is derived from the devOps methodologies that have revolutionized the software industry. SciOps involves digital research environments that seamlessly integrate computational, automation, and AI-driven efforts throughout the research cycle—from experimental design and data collection to analysis and dissemination, ultimately leading to closed-loop discovery. This maturity model offers a framework for assessing and improving operational practices in multidisciplinary research teams, guiding them towards greater efficiency and effectiveness in scientific inquiry. © 2023, CC BY.

关键词： Artificial intelligence

Correction to: Streaming active learning strategies for real-life credit detection: assessment and visualization

学校读者我要写书评

暂无评论

International Journal of data Science and Analytics 2018年第4期5卷 301-302页

作者： Fabrizio Carcillo Yann-Aël Le Borgne Olivier Caelen Gianluca Bontempi Machine Learning Group Computer Science Department Faculty of Sciences Université Libre de Bruxelles (ULB) Brussels Belgium R&D Worldline Brussels Belgium

A line was misplaced in Table 1. The correct Table 1 is given below.

关键词：

Probing Ultra-late reionization: direct Measurements of the Mean Free Path over 5 < z < 6

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Zhu, Yongda Becker, George d. Christenson, Holly M. d’Aloisio, Anson Bosman, Sarah E.I. Bakx, Tom d’Odorico, Valentina Bischetti, Manuela Cain, Christopher davies, Frederick B. davies, rebecca L. Eilers, Anna-Christina Fan, Xiaohui Gaikwad, Prakash Haehnelt, Martin G. Keating, Laura C. Kulkarni, Girish Lai, Samuel Ma, Hai-Xia Mesinger, Andrei Qin, Yuxiang Satyavolu, Sindhu Takeuchi, Tsutomu T. Umehata, Hideki Yang, Jinyi Department of Physics & Astronomy University of California RiversideCA92521 United States Max-Planck-Institut für Astronomie Königstuhl 17 HeidelbergD-69117 Germany Institute for Theoretical Physics Heidelberg University Philosophenweg 12 HeidelbergD-69120 Germany Department of Space Earth and Environment Chalmers University of Technology Onsala Space Observatory Onsala439 92 Sweden Division of Particle and Astrophysical Science Nagoya University Furo-cho Chikusa-ku Nagoya464-8602 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan INAF-Osservatorio Astronomico di Trieste Via Tiepolo 11 TriesteI-34143 Italy Scuola Normale Superiore Piazza dei Cavalieri 7 PisaI-56126 Italy IFPU-Institute for Fundamental Physics of the Universe via Beirut 2 TriesteI-34151 Italy Dipartimento di Fisica Sezione di Astronomia Universitá di Tri- este via Tiepolo 11 Trieste34143 Italy Centre for Astrophysics and Supercomputing Swinburne University of Technology HawthornVIC3122 Australia Australia MIT Kavli Institute for Astrophysics and Space Research 77 Massachusetts Avenue CambridgeMA02139 United States Steward Observatory University of Arizona 933 N Cherry Ave TucsonAZ85721 United States Kavli Institute for Cosmology Institute of Astronomy Madingley Road CambridgeCB3 0HA United Kingdom Institute for Astronomy University of Edinburgh Blackford Hill EdinburghEH9 3HJ United Kingdom Tata Institute of Fundamental Research Homi Bhabha Road Mumbai400005 India Research School of Astronomy and Astrophysics Australian National University CanberraACT2611 Australia School of Physics University of Melbourne ParkvilleVIC3010 Australia The Research Center for Statistical Machine Learning The Institute of Statistical Mathematics 10-3 Midori-cho Tachikawa Tokyo190-8562 Japan Institute for Advanced Research Nagoya University Furocho Chikusa Nagoya464-8602 Japan Department of Physics Graduate School of Science Na

The mean free path of ionizing photons, λmfp, is a critical parameter for modeling the intergalactic medium (IGM) both during and after reionization. We present direct measurements of λmfp from QSO spectra over the redshift range 5 mfp = 9.33+2−1.0680, 5.40+1−1.4740, 3.31−+21.7434, and 0.81+0−0.7348 pMpc at z = 5.08, 5.31, 5.65, and 5.93, respectively. Our results demonstrate that λmfp increases steadily and rapidly with time over 5 mfp deviates significantly from predictions based on a fully ionized and relaxed IGM as late as z = 5.3. By comparing our results to model predictions and indirect λmfp constraints based on IGM Lyα opacity, we find that the λmfp evolution is consistent with scenarios wherein the IGM is still undergoing reionization and/or retains large fluctuations in the ionizing UV background well below redshift six. © 2023, CC BY.

关键词： Galaxies

Pd-1 suppresses the maintenance of cell couples between cytotoxic T cells and target tumor cells within the tumor

学校读者我要写书评

暂无评论

SCIENCE SIGNALING 2020年第649期13卷 eaau4518页

作者： Ambler, rachel Edmunds, Grace L. Tan, Sin Lih Cirillo, Silvia Pernes, Jane, I ruan, Xiongtao Huete-Carrasco, Jorge Wong, Carissa C. W. Lu, Jiahe Ward, Juma Toti, Giulia Hedges, Alan J. dovedi, Simon J. Murphy, robert F. Morgan, david J. Wulfing, Christoph Univ Bristol Sch Cellular & Mol Med Bristol BS8 1TD Avon England Carnegie Mellon Univ Sch Comp Sci Computat Biol Dept Pittsburgh PA 15213 USA AstraZeneca R&D Oncol Granta Pk Cambridge CB21 6GH England Carnegie Mellon Univ Dept Biol Sci Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Biomed Engn Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Machine Learning Pittsburgh PA 15213 USA Albert Ludwig Univ Freiburg Freiburg Inst Adv Studies D-79104 Freiburg Germany Albert Ludwig Univ Freiburg Fac Biol D-79104 Freiburg Germany Francis Crick Inst London NW1 1AT England

The killing of tumor cells by Cd8(+) T cells is suppressed by the tumor microenvironment, and increased expression of inhibitory receptors, including programmed cell death protein-1 (Pd-1), is associated with tumor-mediated suppression of T cells. To find cellular defects triggered by tumor exposure and associated Pd-1 signaling, we established an ex vivo imaging approach to investigate the response of antigen-specific, activated effector Cd8(+) tumor-infiltrating lymphocytes (TILs) after interaction with target tumor cells. Although TIL-tumor cell couples readily formed, couple stability deteriorated within minutes. This was associated with impaired F-actin clearing from the center of the cellular interface, reduced Ca2+ signaling, increased TIL locomotion, and impaired tumor cell killing. The interaction of Cd8(+) T lymphocytes with tumor cell spheroids in vitro induced a similar phenotype, supporting a critical role of direct T cell-tumor cell contact. diminished engagement of Pd-1 within the tumor, but not acute ex vivo blockade, partially restored cell couple maintenance and killing. Pd-1 thus contributes to the suppression of TIL function by inducing a state of impaired subcellular organization.

关键词：

Streaming active learning strategies for real-life credit card fraud detection: Assessment and visualization

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Carcillo, Fabrizio Le Borgne, Yann-Aël Caelen, Olivier Bontempi, Gianluca Machine Learning Group Computer Science Department Faculty of Sciences ULB Université Libre de Bruxelles Brussels Belgium R&D Worldline Brussels Belgium

Credit card fraud detection is a very challenging problem because of the specific nature of transaction data and the labeling process. The transaction data is peculiar because they are obtained in a streaming fashion, they are strongly imbalanced and prone to non-stationarity. The labeling is the outcome of an active learning process, as every day human investigators contact only a small number of cardholders (associated to the riskiest transactions) and obtain the class (fraud or genuine) of the related transactions. An adequate selection of the set of cardholders is therefore crucial for an efficient fraud detection process. In this paper, we present a number of active learning strategies and we investigate their fraud detection accuracies. We compare different criteria (supervised, semi-supervised and unsupervised) to query unlabeled transactions. Finally, we highlight the existence of an exploitation/exploration trade-off for active learning in the context of fraud detection, which has so far been overlooked in the literature. Copyright © 2018, The Authors. All rights reserved.

关键词： Crime

Multi-phase black-hole feedback and a bright [CII] halo in a Lo-BAL quasar at z ∼ 6.6

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Bischetti, Manuela Choi, Hyunseop Fiore, Fabrizio Feruglio, Chiara Carniani, Stefano d’Odorico, Valentina Bañados, Eduardo Chen, Huanqing decarli, roberto Gallerani, Simona Hlavacek-Larrondo, Julie Lai, Samuel Leighly, Karen M. Mazzucchelli, Chiara Perreault-Levasseur, Laurence Tripodi, roberta Walter, Fabian Wang, Feige Yang, Jinyi Zanchettin, Maria Vittoria Zhu, Yongda Dipartimento di Fisica Universitá di Trieste Sezione di Astronomia Via G.B. Tiepolo 11 TriesteI-34131 Italy INAF - Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI–34131 Italy Département de Physique Université de Montréal Succ. Centre-Ville MontréalQCH3C 3J7 Canada Mila - Quebec Artificial Intelligence Institute MontréalQC Canada IFPU - Institut for fundamental physics of the Universe Via Beirut 2 Trieste34014 Italy Scuola Normale Superiore Piazza dei Cavalieri 7 PisaI-56126 Italy Max Planck Institut für Astronomie Königstuhl 17 HeidelbergD-69117 Germany Canadian Institute for Theoretical Astrophysics University of Toronto 60 St George St TorontoONM5R 2M8 Canada INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna via Gobetti 93/3 BolognaI-40129 Italy Research School of Astronomy and Astrophysics Australian National University CanberraACT2611 Australia Homer L. Dodge Department of Physics and Astronomy The University of Oklahoma 440 W. Brooks St. NormanOK73019 United States Núcleo de Astronomía de la Facultad de Ingeniería Universidad Diego Portales Av. Ejército Libertador 441 Santiago Chile Ciela - Montreal Institute for Astrophysical Data Analysis and Machine Learning Montréal Canada Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States University of Ljubljana FMF Jadranska 19 1000 Slovenia Steward Observatory University of Arizona 933 N Cherry Avenue TucsonAZ85721 United States SISSA Via Bonomea 265 Trieste34136 Italy Department of Physics & Astronomy University of California RiversideCA92521 United States

Although the mass growth of supermassive black holes during the Epoch of reionisation is expected to play a role in shaping the concurrent growth of their host-galaxies, observational evidence of feedback at z6 is still sparse. We perform the first multi-scale and multi-phase characterisation of black-hole driven outflows in the z ∼ 6.6 quasar J0923+0402 and assess how these winds impact the cold gas reservoir. We employ the SimBAL spectral synthesis to fit broad absorption line (BAL) features and find a powerful ionized outflow on 210 pc scale, with a kinetic power ∼ 2 − 100% of the quasar luminosity. ALMA observations of [CII] emission allow us to study the morphology and kinematics of the cold gas. We detect high-velocity [CII] emission, likely associated with a cold neutral outflow at ∼ 0.5−2 kpc scale in the host-galaxy, and a bright extended [CII] halo with a size of ∼ 15 kpc. For the first time at such an early epoch, we accurately constrain the outflow energetics in both the ionized and the atomic neutral gas phases. We find such energetics to be consistent with expectations for an efficient feedback mechanism, and both ejective and preventative feedback modes are likely at play. The scales and energetics of the ionized and atomic outflows suggest that they might be associated with different quasar accretion episodes. The results of this work indicate that strong black hole feedback is occurring in quasars at z 6 and is likely responsible for shaping the properties of the cold gas reservoir up to circum-galactic scales. © 2024, CC BY.

关键词： Galaxies

Benchmarking CrISPr on-target sgrNA design

学校读者我要写书评

暂无评论

BrIEFINGS IN BIOINFOrMATICS 2018年第4期19卷 721-724页

作者： Yan, Jifang Chuai, Guohui Zhou, Chi Zhu, Chenyu Yang, Jing Zhang, Chao Gu, Feng Xu, Han Wei, Jia Liu, Qi Tongji Univ Sch Life Sci Bioinformat Shanghai Peoples R China Tongji Univ Sch Life Sci Machine Learning & Biol Data Min Shanghai Peoples R China Tongji Univ Sch Life Sci Algorithm Design Shanghai Peoples R China Tongji Univ Sch Life Sci Shanghai Peoples R China Wenzhou Med Univ Eye Hosp Sch Ophthalmol & Optometry Wenzhou Peoples R China Harvard Sch Publ Hlth Dana Farber Canc Inst Boston MA USA AstraZeneca R&D Informat Shanghai Peoples R China Fujian Agr & Forestry Univ Coll Comp & Informat Sci Fuzhou Fujian Peoples R China Tongji Univ Bioinformat Dept Shanghai Peoples R China

CrISPr (Clustered regularly Interspaced Short Palindromic repeats)-based gene editing has been widely implemented in various cell types and organisms. A major challenge in the effective application of the CrISPr system is the need to design highly efficient single-guide rNA (sgrNA) with minimal off-target cleavage. Several tools are available for sgrNA design, while limited tools were compared. In our opinion, benchmarking the performance of the available tools and indicating their applicable scenarios are important issues. Moreover, whether the reported sgrNA design rules are reproducible across different sgrNA libraries, cell types and organisms remains unclear. In our study, a systematic and unbiased benchmark of the sgrNA predicting efficacy was performed on nine representative on-target design tools, based on six benchmark data sets covering five different cell types. The benchmark study presented here provides novel quantitative insights into the available CrISPr tools.

关键词： gene editing CrISPr sgrNA benchmark

dalek - A deep-learning based emulator for tardis

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Kerzendorf, Wolfgang E. Vogl, Christian Buchner, Johannes Contardo, Gabriella Williamson, Marc van der Smagt, Patrick Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Str. 1 GarchingD-85741 Germany Max-Planck-Institut für extraterrestrische Physik Giessenbachstrasse 1 Garching bei München85748 Germany Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Physics New York University New YorkNY10003 United States Machine Learning Research Lab Volkswagen AG Munich Germany Faculty of Informatics Eötvös Loránd University Budapest Hungary

Supernova spectral time series contain a wealth of information about the progenitor and explosion process of these energetic events. The modeling of these data requires the exploration of very high dimensional posterior probabilities with expensive radiative transfer codes. Even modest parametrizations of supernovae contain more than ten parameters and a detailed exploration demands at least several million function evaluations. Physically realistic models require at least tens of CPU minutes per evaluation putting a detailed reconstruction of the explosion out of reach of traditional methodology. The advent of widely available libraries for the training of neural networks combined with their ability to approximate almost arbitrary functions with high precision allows for a new approach to this problem. Instead of evaluating the radiative transfer model itself, one can build a neural network proxy trained on the simulations but evaluating orders of magnitude faster. Such a framework is called an emulator or surrogate model. In this work, we present an emulator for the tardis supernova radiative transfer code applied to Type Ia supernova spectra. We show that we can train an emulator for this problem given a modest training set of a hundred thousand spectra (easily calculable on modern supercomputers). The results show an accuracy on the percent level (that are dominated by the Monte Carlo nature of tardis and not the emulator) with a speedup of several orders of magnitude. This method has a much broader set of applications and is not limited to the presented problem. Copyright © 2020, The Authors. All rights reserved.

关键词： Supernovae

Cost-effective CFd for vortex shedding from a trailing edge of hydraulic turbine blade

学校读者我要写书评

暂无评论

IOP Conference Series. Earth and Environmental Science 2019年第7期240卷

作者： Kurosawa, Sadao Nakazono, Masahiko Hydraulic Machinery Group Rotating Machine Technology R&D Department Power and Industrial Systems R&D Center Research & Development Div. Toshiba Corporation 20-1 Kansei-cho Tsurumi-ku Yokohama 230-0034 Japan

This paper describes the method for analysing the vortex from a trailing edge of the blade with high accuracy using CFd. As for the analysis method, rANS and LES hybrid model, which is a combination of rANS with a low calculation load and LES with a high calculation load, was used on understanding the turbine-scale phenomenon with a relatively low calculation load. As for the first step its application as a turbine runner, we conducted the case study in which the blade model was fixed in a uniform and we confirmed that the present CFd could be predicted the vortex shedding phenomena, such as power spectra of velocity fluctuations, wake fluctuation, vortex shedding pattern and hydraulic force acting on the blade etc.

关键词：