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arXiv 2025年

作者： Barkaoui, K. Korth, J. Gaidos, E. Agol, E. Parviainen, H. Pozuelos, F.J. Palle, E. Narita, N. Grimm, S. Brady, M. Bean, J.L. Morello, G. Rackham, B.V. Burgasser, A.J. Van Grootel, V. Rojas-Ayala, B. Seifahrt, A. Marfil, E. Passegger, V.M. Stalport, M. Gillon, M. Collins, K.A. Shporer, A. Giacalone, S. Yalçınkaya, S. Ducrot, E. Timmermans, M. Triaud, A.H.M.J. de Wit, J. Soubkiou, A. Watkins, C.N. Aganze, C. Alonso, R. Amado, P.J. Basant, R. Baştürk, Ö. Benkhaldoun, Z. Burdanov, A. Calatayud-Borras, Y. Chouqar, J. Conti, D.M. Collins, K.I. Davoudi, F. Delrez, L. Dressing, C.D. de Leon, J. Dévora-Pajares, M. Demory, B.O. Dransfield, G. Esparza-Borges, E. Fernández-Rodriguez, G. Fukuda, I. Fukui, A. Gallardo, P.P.M. Garcia, L. Garcia, N.A. Ghachoui, M. Geraldía-González, S. Chew, Y. Gómez Maqueo González-Rodríguez, J. Günther, M.N. Hayashi, Y. Horne, K. Hooton, M.J. Hsu, C.C. Ikuta, K. Isogai, K. Jehin, E. Jenkins, J.M. Kawauchi, K. Kagetani, T. Kawai, Y. Kasper, D. Kielkopf, J.F. Klagyivik, P. Lacedelli, G. Latham, D.W. Libotte, F. Luque, R. Livingston, J.H. Mancini, L. Massey, B. Mori, M. Torres, S. Muñoz Murgas, F. Niraula, P. Orell-Miquel, J. Rapetti, David Rebolo-López, R. Ricker, G. Papini, R. Pedersen, P.P. Peláez-Torres, A. Pérez-Prieto, J.A. Poultourtzidis, E. Rodriguez, P.M. Queloz, D. Savel, A.B. Schanche, N. Sánchez-Benavente, M. Sibbald, L. Sefako, R. Sohy, S. Sota, A. Schwarz, R.P. Seager, S. Sebastian, D. Southworth, J. Stangret, M. Stefánsson, G. Stürmer, J. Srdoc, G. Thompson, S.J. Terada, Y. Vanderspek, R. Wang, G. Watanabe, N. Wilkin, F.P. Winn, J. Wells, R.D. Ziegler, C. Zúñiga-Fernández, S. Astrobiology Research Unit Université de Liège Allée du 6 Août 19C LiègeB-4000 Belgium Department of Earth Atmospheric and Planetary Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Calle Vía Láctea s/n Tenerife La Laguna38200 Spain Lund Observatory Division of Astrophysics Department of Physics Lund University Box 118 Lund22100 Sweden Department of Earth Sciences University of Hawaii at Manoa 1680 East-West Rd HonoluluHI96822 United States Institute for Astrophysics University of Vienna Türkenschanzstrasse 17 ViennaA-1180 Austria Department of Astronomy Astrobiology Program University of Washington Box 351580 SeattleWA98195 United States NExSS Virtual Planetary Laboratory University of Washington Box 351580 SeattleWA98195 United States Tenerife La LagunaE-38206 Spain Glorieta de la Astronomía s/n Granada18008 Spain INAF- Palermo Astronomical Observatory Piazza del Parlamento 1 Palermo90134 Italy Komaba Institute for Science The University of Tokyo 3-8-1 Komaba Meguro Tokyo153-8902 Japan Astrobiology Center 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Research Institute for Advanced Computer Science Universities Space Research Association WashingtonDC20024 United States Institute for Particle Physics and Astrophysics ETH Zürich OttoStern-Weg 5 Zürich8093 Switzerland Department of Astrophysics University of Zürich Winterthurerstrasse 190 Zürich8057 Switzerland Department of Astronomy & Astrophysics University of Chicago ChicagoIL United States NHFP Sagan Fellow United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States Institute Université de Liège Allée du 6 Août 19C LiègeB-4000 Belgium Instituto de Alta Investigación Universidad de Tarapacá Casilla 7D Arica Chile Gemini Observatory NSF NOIRLab 670 N. A’ohoku Place HiloHI96720 United States Departamento de

TOI-2015 is a known exoplanetary system around an M4 dwarf star, consisting of a transiting sub-Neptune planet in a 3.35-day orbital period, TOI-2015 b, accompanied by a non-transiting companion, TOI-2015 c. High-precision radial velocity measurements were taken with the MAROON-X spectrograph, and high-precision photometric data were collected, primarily using the SPECULOOS, MUSCAT, TRAPPIST and LCOGT networks. We collected 63 transit light curves and 49 different transit epochs for TOI-2015 b. We re-characterize the target star by combining optical spectra obtained by the MAROON-X, Shane/KAST and IRTF/SpeX spectrographs, Bayesian Model Averaging (BMA) and Spectral Energy Distribution (SED) analysis. The TOI-2015 host star is a K = 10.3 mag M4-type dwarf with a sub-solar metallicity of [e/H]= −0.31 ± 0.16, and an effective temperature of Teff ≈ 3200 K. Our photodynamical analysis of the system strongly favors the 5:3 mean motion resonance and in this scenario the planet b (TOI-2015 b) has an orbital period of Pb = 3.34 days, a mass of Mp = 9.02+0.32−0.36 M⊗, a radius of Rp = 3.309+0.013−0.11 R⊗, resulting in a density of ρp = 0.25±0.01 ρ⊗ = 1.40±0.06 g cm−3, indicative of a Neptune-like composition. Its transits exhibit large (> 1 hr) timing variations indicative of an outer perturber in the system. We performed a global analysis of the high-resolution radial-velocity measurements, the photometric data, and the TTVs, and inferred that TOI-2015 hosts a second planet, TOI-2015 c, in a non-transiting configuration. Our analysis places it near a 5:3 resonance with an orbital period of Pc = 5.583 days and a mass of Mp = 8.91+0.38−0.40 M⊗. The dynamical configuration of TOI-2015 b and TOI-2015 c can be used to constrain the system’s planetary formation and migration history. Based on the mass-radius composition models, TOI-2015 b is a water-rich or rocky planet with a hydrogen-helium envelope. Moreover, TOI-2015 b has a high transmission spectroscopic metric (TSM= 149), m

关键词： Stars

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Radiological characteristics of charged particle interactions in the first clay-nanoparticle dichromate gel dosimeter

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Journal of Physics: Conference Series 2013年第1期444卷

作者： M L Taylor T Maeyama N Fukunishi K L Ishikawa K Fukasaku T Furuta S Takagi S Noda R Himeno S Fukuda RMIT University/School of Applied Sciences Melbourne Australia Peter MacCallum Cancer Centre/Physical Sciences Melbourne Australia RIKEN/Nishina Centre for Accelerator-Based Science Wako Japan RIKEN/Computational Science Research Program Wako Japan The University of Tokyo/Department of Nuclear Engineering and Management Graduate School of Engineering Tokyo Japan The University of Tokyo/Photon Science Centre Graduate School of Engineering Tokyo Japan Himon'ya Hospital Department of Neurosurgery Tokyo Japan RIKEN/Advanced Centre for Computing and Communication Wako Japan The University of Tokyo/Department of Mechanical Engineering Graduate School of Engineering Tokyo Japan National Institute of Radiological Sciences / Research Centre for Charged Particle Therapy Chiba Japan

The incorporation of clay nanoparticles into gel dosimeters shows promise for significant diffusion reduction – but to what extent does the presence of the nano-clay influence charged particle interactions and, in particular, what is the impact on water equivalence? In this work, we quantify the radiological characteristics of electron, proton and carbon ion interactions in the RIKEN dichromate nanoclay gel and specifically evaluate the water equivalence over a broad energy range. Results indicate that the radiological properties are sufficiently representative of tissues that this low-diffusion gel could readily be used for validation of complex dose distributions. Electron and proton ranges are within 1 % of those in water. Mean effective atomic numbers for electron interactions in the range 10 keV – 10 GeV are within 1 % of those of water which, coupled with the similar mass density, ultimately means the overall impact on dose distributions is not great. The range of C6+ ions in the nanoclay gel is closer to that of water (< 4 %) than a common polymer gel dosimeter (< 7 %), though experimentally measured R1 values indicate an over-response at low doses.

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Exponential acceleration of macroscopic quantum tunneling in a Floquet Ising model

arXiv

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arXiv 2023年

作者： Grattan, George Barton, Brandon A. Feeney, Sean Mossi, Gianni Patnaik, Pratik Sagal, Jacob C. Carr, Lincoln D. Oganesyan, Vadim Kapit, Eliot Quantum Engineering Program Colorado School of Mines 1523 Illinois St CO Golden80401 United States Department of Computer Science Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Physics Colorado School of Mines 1523 Illinois St CO Golden80401 United States KBR Inc. 601 Jefferson St. HoustonTX77002 United States NASA Ames Research Center Moffett FieldCA94035 United States Department of Physics and Astronomy College of Staten Island CUNY Staten IslandNY10314 United States Physics program and Initiative for the Theoretical Sciences The Graduate Center CUNY New YorkNY10016 United States Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States

The exponential suppression of macroscopic quantum tunneling (MQT) in the number of elements to be reconfigured is an essential element of broken symmetry phases. Slow MQT is also a core bottleneck in quantum algorithms, such as traversing an energy landscape in optimization, and adiabatic state preparation more generally. In this work, we demonstrate the possibility to accelerate MQT through Floquet engineering with the application of a uniform, high frequency transverse drive field. Using the ferromagnetic phase of the transverse field Ising model in one and two dimensions as a prototypical example, we identify three qualitatively distinct regimes as a function of drive strength: (i) for weak drive, the system exhibits exponentially slow MQT alongside robust magnetic order, as expected;(ii) at intermediate drive strength, we find polynomial decay of rates alongside vanishing magnetic order consistent with critical or paramagnetic state;(iii) at very strong drive strengths both the tunnelling rate and time-averaged magnetic order remain finite with increasing system size. We support these claims with extensive full wavefunction and matrix-product state numerical simulations, and theoretical analysis. An experimental test of these results presents a technologically important and novel scientific question accessible on NISQ-era quantum computers. © 2023, CC BY.

关键词： Ising model

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Performance of the prototype shaftless small scale horizontal wind turbine for electricity generating from industrial exhaust air system

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IOP Conference Series: Earth and Environmental science 2020年第1期463卷

作者： Wachira Puttichaem Yuttanant Boonyongmaneerat Pakpachong Vadhanasindhu Sompong Putivisutisak Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok 10330 Thailand Metallurgy and Materials Science Research Institute (MMRI) Chulalongkorn University Bangkok 10330 Thailand Faculty of Commerce and Accountancy Chulalongkorn Business School Chulalongkorn University Bangkok 10330 Thailand Advanced Computational Fluid Dynamics Research Unit Department of Mechanical Engineering Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand

Man-made or unnatural wind from the industrial exhaust air system is an alternative wind resource for countries with natural low-speed or intermittent wind such as Thailand. It has strong and consistent wind speed when compared to the natural wind, with velocity about 5 to 10 m/s at a distance of 5 cm from the exhaust air outlet. However, some negative impacts to the exhaust air system performance was observed when a conventional wind turbine was employed. The objective of this research is to feasibility study the practicality of a prototype shaftless small scale horizontal axis wind turbine (SSHWT) to generate electricity from the exhaust air of the industrial exhaust air system. Aerodynamic, blade and generator designs were addressed in this study to maximize energy output and minimize negative impacts to the performance of the original exhaust air system. The performance of SSHWT was tested with a selected industrial fan that is widely used in industrial sections. The results showed that the SSHWT could generate electricity with less negative effect to exhaust air system performance. However, it still needs further improvements caused by the voltage output is too low. By the concept design, this innovative wind turbine is compact, thus needs only small space for installation. This SSHWT has high market potential for low wind speed countries to take advantage of unnatural wind resources which are better in terms of efficiency and economy for sustainable energy development.

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Front Cover: Design, Synthesis, and Characterization of Novel Styryl Dyes as Fluorescent Probes for Tau Aggregate Detectionin Vitroand in Cells (Chem. Asian J. 6/2024)

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Chemistry – An Asian Journal 2024年第6期19卷

作者： Withsakorn Sangsuwan Kriangsak Faikhruea Kotchakorn Supabowornsathit Don Sangsopon Praewphan Ingrungruanglert Hathaichanok Chuntakaruk Napatsaporn Nuntavanotayan Kittiporn Nakprasit Nipan Israsena Thanyada Rungrotmongkol Pitak Chuawong Tirayut Vilaivan Chanat Aonbangkhen Center of Excellence in Natural Products Chemistry (CENP) Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Department of Chemistry and Center of Excellence for Innovation in Chemistry Faculty of Science Special Research Unit for Advanced Magnetic Resonance (AMR) Kasetsart University Bangkok 10900 Thailand These authors are contributed equally. Organic Synthesis Research Unit Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Stem Cell and Cell Therapy Research Unit and Department of Pharmacology Faculty of Medicine Chulalongkorn University Bangkok 10330 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok 10330 Thailand Center of Excellence in Structural and Computational Biology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand

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EMPRESS. XI. SDSS and JWST Search for Local and z ∼ 4–5 Extremely Metal-Poor Galaxies (EMPGs): Clustering and Chemical Properties of Local EMPGs

arXiv

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arXiv 2023年

作者： Nishigaki, Moka Ouchi, Masami Nakajima, Kimihiko Ono, Yoshiaki Rauch, Michael Isobe, Yuki Harikane, Yuichi Narita, Kanako Zahedy, Fakhri Xu, Yi Yajima, Hidenobu Fukushima, Hajime Hirai, Yutaka Kim, Ji Hoon Inoue, Shigeki Kusakabe, Haruka Lee, Chien-Hsiu Nagao, Tohru Onodera, Masato Department of Astronomical Science The Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba277-8582 Japan University of Tokyo Chiba Kashiwa277-8583 Japan Observatories of the Carnegie Institution for Science 813 Santa Barbara Street PasadenaCA91101 United States Department of Physics Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Center for Computational Sciences University of Tsukuba Ten-nodai 1-1-1 Tsukuba Ibaraki305-8577 Japan Department of Physics and Astronomy University of Notre Dame 225 Nieuwland Science Hall Notre DameIN46556 United States Astronomical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Sendai Miyagi980-8578 Japan Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Center Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Faculty of Science Hokkaido University Hokkaido Sapporo060-0810 Japan Observatoire de Genève Université de Genève 51 Chemin de Pégase Versoix1290 Switzerland W. M. Keck Observatory 65-1120 Mamalahoa Hwy KamuelaHI96743 United States Research Center for Space and Cosmic Evolution Ehime University Ehime Matsuyama790-8577 Japan 650 North A’ohoku Place HiloHI96720 United States

We search for local extremely metal-poor galaxies (EMPGs), selecting photometric candidates by broadband color excess and machine-learning techniques with the SDSS photometric data. After removing stellar contaminants by shallow spectroscopy with Seimei and Nayuta telescopes, we confirm that three candidates are EMPGs with 0.05–0.1 Z☉ by deep Magellan/MagE spectroscopy for faint [Oiii]λ4363 lines. Using a statistical sample consisting of 105 spectroscopically-confirmed EMPGs taken from our study and the literature, we calculate cross-correlation function (CCF) of the EMPGs and all SDSS galaxies to quantify environments of EMPGs. Comparing another CCF of all SDSS galaxies and comparison SDSS galaxies in the same stellar mass range (107.0 − 108.4M☉), we find no significant (> 1σ) difference between these two CCFs. We also compare mass-metallicity relations (MZRs) of the EMPGs and those of galaxies at z ∼ 0–4 with a steady chemical evolution model and find that the EMPG MZR is comparable with the model prediction on average. These clustering and chemical properties of EMPGs are explained by a scenario of stochastic metal-poor gas accretion on metal-rich galaxies showing metal-poor star formation. Extending the broadband color-excess technique to a high-z EMPG search, we select 17 candidates of z ∼ 4–5 EMPGs with the deep (' 30 mag) near-infrared JWST/NIRCam images obtained by ERO and ERS programs. We find galaxy candidates with negligible [Oiii]λλ4959,5007 emission weaker than the local EMPGs and known high-z galaxies, suggesting that some of these candidates may fall in 0–0.01 Z☉, which potentially break the lowest metallicity limit known to date. Copyright © 2023, The Authors. All rights reserved.

关键词： Infrared devices

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Evolution of retrograde orbiters in an AGN disk

arXiv

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arXiv 2020年

作者： Secunda, Amy Hernandez, Betsy Goodman, Jeremy Leigh, Nathan W.C. McKernan, Barry Ford, K.E. Saavik Adorno, Jose I. Department of Astrophysics American Museum of Natural History Central Park West at 79th Street New YorkNY10024 United States Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Departamento de Astronomía Facultad de Ciencias Físicas y Matemáticas Universidad de Concepción Concepción Chile Department of Science Borough of Manhattan Community College City University of New York New YorkNY10007 United States Physics Program Graduate Center CUNY New YorkNY10016 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States NASA Goddard Space Flight Center GreenbeltMD20771 United States Department of Physics Queens College City University of New York QueensNY11367 United States

AGN disks have been proposed as promising locations for the mergers of stellar mass black hole binaries (BBHs). Much recent work has been done on this merger channel, but the majority focuses on stellar mass black holes (BHs) orbiting in the prograde direction. Little work has been done to examine the impact of retrograde orbiters (ROs) on the formation and mergers of BBHs in AGN disks. Quantifying the retrograde contribution is important, since roughly half of all orbiters should initially be on retrograde orbits when the disk forms. We perform an analytic calculation of the evolution of ROs in an AGN disk. Because this evolution could cause the orbits of ROs to cross those of prograde BBHs, we derive the collision rate between a given RO and a given BBH orbiting in the prograde direction. In the examples given here, ROs in the inner region of the disk experience a rapid decrease in the semimajor axis of their orbits while also becoming highly eccentric in less than a million years. This rapid orbital evolution could lead to extreme mass ratio inspirals detectable by the Laser Interferometer Space Antenna. The collision rates of our example ROs with prograde BBHs in the migration trap depend strongly on the volume of the inner radiation-pressure-dominated region which depends on the mass of the supermassive black hole (SMBH). Rates are lowest for larger mass SMBHs, which dominate the AGN merger channel, suggesting that merger rates for this channel may not be significantly altered by ROs. Copyright © 2020, The Authors. All rights reserved.

关键词： Black holes

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Orbital migration of interacting stellar mass black holes in disks around supermassive black holes

arXiv

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arXiv 2018年

作者： Secunda, Amy Bellovary, Jillian Low, Mordecai-Mark Mac Ford, K.E. Saavik McKernan, Barry Leigh, Nathan Lyra, Wladimir Department of Astrophysics American Museum of Natural History Central Park West at 79th Street New YorkNY10024 United States Department of Physics Queensborough Community College BaysideNY11364 United States Department of Science Borough of Manhattan Community College City University of New York New YorkNY10007 United States Physics Program Graduate Center CUNY New YorkNY10016 United States Department of Physics and Astronomy Stony Brook University Stony BrookNY11794-3800 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Physics and Astronomy California State University Northridge 18111 Nordhoff Street NorthridgeCA91330 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States

The merger rate of stellar mass black holes binaries (sBHBs) inferred by the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) suggests the need for an efficient source of sBHB formation. Active galactic nucleus (AGN) disks are a promising location for the formation of these sBHBs, as well as binaries of other compact objects, because of powerful torques exerted by the gas disk. These gas torques cause orbiting compact objects to migrate towards regions in the disk where inward and outward torques cancel, known as migration traps. We simulate the migration of stellar mass black holes (sBHs) in an analytically modeled AGN disk using an augmented N-body code that includes migration torques, a stochastic gravitational force exerted by turbulent density fluctuations in the disk, and inclination and eccentricity dampening produced by passages through the gas disk, in addition to the standard gravitational forces between objects. We find that sBHBs form rapidly in the disk as sBHs migrate towards the migration trap. These sBHBs are likely to subsequently merge on short time-scales. The process continues, leading to the build up of a population of over-massive sBHs. sBHBs that form in AGN disks could contribute significantly to the sBHB merger rate inferred by LIGO. Copyright © 2018, The Authors. All rights reserved.

关键词： Merging

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Ten quick tips for deep learning in biology

arXiv

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arXiv 2021年

作者： Lee, Benjamin D. Gitter, Anthony Greene, Casey S. Raschka, Sebastian Maguire, Finlay Titus, Alexander J. Kessler, Michael D. Lee, Alexandra J. Chevrette, Marc G. Stewart, Paul Allen Britto-Borges, Thiago Cofer, Evan M. Yu, Kun-Hsing Carmona, Juan Jose Fertig, Elana J. Kalinin, Alexandr A. Signal, Beth Lengerich, Benjamin J. Triche, Timothy J. Boca, Simina M. In-Q-Tel Labs School of Engineering and Applied Sciences Harvard University Department of Genetics Harvard Medical School United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI United States Morgridge Institute for Research MadisonWI United States Department of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine AuroraCO United States Center for Health AI University of Colorado School of Medicine AuroraCO United States Department of Statistics University of Wisconsin Madison United States Faculty of Computer Science Dalhousie University Canada University of New Hampshire Bioeconomy.XYZ United States Department of Oncology Johns Hopkins University United States Institute for Genome Sciences University of Maryland School of Medicine United States Genomics and Computational Biology Graduate Program University of Pennsylvania United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania United States Wisconsin Institute for Discovery Department of Plant Pathology University of Wisconsin-Madison United States Department of Biostatistics and Bioinformatics Moffitt Cancer Center TampaFL United States Section of Bioinformatics and Systems Cardiology Klaus Tschira Institute for Integrative Computational Cardiology University Hospital Heidelberg Germany University Hospital Heidelberg Germany Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ United States Graduate Program in Quantitative and Computational Biology Princeton University PrincetonNJ United States Department of Biomedical Informatics Harvard Medical School United States Department of Pathology Brigham and Women's Hospital United States Philips Healthcare CambridgeMA United States Philips Research

Machine learning is a modern approach to problem-solving and task automation. In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling. Artificial neural networks are a particular class of machine learning algorithms and models that evolved into what is now described as deep learning. Given the computational advances made in the last decade, deep learning can now be applied to massive data sets and in innumerable contexts. Therefore, deep learning has become its own subfield of machine learning. In the context of biological research, it has been increasingly used to derive novel insights from high-dimensional biological data. To make the biological applications of deep learning more accessible to scientists who have some experience with machine learning, we solicited input from a community of researchers with varied biological and deep learning interests. These individuals collaboratively contributed to this manuscript's writing using the GitHub version control platform and the Manubot manuscript generation toolset. The goal was to articulate a practical, accessible, and concise set of guidelines and suggestions to follow when using deep learning. In the course of our discussions, several themes became clear: the importance of understanding and applying machine learning fundamentals as a baseline for utilizing deep learning, the necessity for extensive model comparisons with careful evaluation, and the need for critical thought in interpreting results generated by deep learning, among others. © 2021, CC BY.

关键词： Learning algorithms

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Author Correction: Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes

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Nature genetics 2025年第4期57卷 1060页

作者： Alicia Huerta-Chagoya Philip Schroeder Ravi Mandla Jiang Li Lowri Morris Maheak Vora Ahmed Alkanaq Dorka Nagy Lukasz Szczerbinski Jesper G S Madsen Silvia Bonàs-Guarch Fanny Mollandin Joanne B Cole Bianca Porneala Kenneth Westerman Josephine H Li Toni I Pollin Jose C Florez Anna L Gloyn David J Carey Inês Cebola Uyenlinh L Mirshahi Alisa K Manning Aaron Leong Miriam Udler Josep M Mercader Programs in Metabolism and Medical & Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. Diabetes Unit Massachusetts General Hospital Boston MA USA. Graduate Program in Genomics and Computational Biology University of Pennsylvania Philadelphia PA USA. Department of Genomic Health Geisinger Danville PA USA. Section of Genetics and Genomics Department of Metabolism Digestion and Reproduction Imperial College London London UK. National Heart and Lung Institute Faculty of Medicine London UK. Department of Endocrinology Diabetology and Internal Medicine Medical University of Bialystok Bialystok Poland. Clinical Research Centre Medical University of Bialystok Bialystok Poland. Institute of Mathematics and Computer Science University of Southern Denmark Odense Denmark. The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard Cambridge MA USA. Department of Biochemistry and Molecular Biology University of Southern Denmark Odense Denmark. Centre for Genomic Regulation The Barcelona Institute of Science and Technology Barcelona Spain. Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas Madrid Spain. Department of Metabolism Digestion and Reproduction Imperial College London London UK. Department of Medicine Harvard Medical School Boston MA USA. Division of Endocrinology Boston Children's Hospital Boston MA USA. Department of Biomedical Informatics University of Colorado School of Medicine Aurora CO USA. Division of General Internal Medicine Massachusetts General Hospital Boston MA USA. Department of Medicine Massachusetts General Hospital Boston MA USA. University of Maryland School of Medicine Baltimore MD USA. Endocrine Division Massachusetts General Hospital Boston MA USA. Department of Pediatrics Division of Endocrinology Stanford School of Medicine Stanford

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