检索结果-内蒙古大学图书馆

SUBCELLULAR TO TISSUE SCALE MODELING OF ISCHEMIA AND SPREADING DEPOLARIZATION

IBRO Neuroscience Reports 2023年 15卷 S792-S792页

作者： Adam Newton Craig Kelley Amy Guo Joy Wang Sydney Zink Marcello Distasio Robert A Mcdougal William Lytton SUNY Downstate Health Sciences University Physiology And Pharamcology New York United States of America SUNY Downstate Health Sciences University Program In Biomedical Engineering New York United States of America Yale School of Public Health Health Informatics Program NEW HAVEN United States of America Yale School of Medicine Department Of Pathology NEW HAVEN United States of America Yale University Department Of Biostatistics NEW HAVEN United States of America Yale University Center For Medical Informatics NEW HAVEN United States of America Yale University Program In Computational Biology And Bioinformatic NEW HAVEN United States of America Yale University Wu Tsai Institute NEW HAVEN United States of America SUNY Downstate Health Sciences University Department Of Neurology New York United States of America Kings County Hospital Center Department Of Neurology New York United States of America SUNY Downstate Health Sciences University The Robert F. Furchgott Center Neural And Behavioral Science New York United States of America

来源：评论

学校读者我要写书评

暂无评论

The cell surface marker CD36 selectively identifies matured,mitochondria-rich hPSC-cardiomyocytes

引用

细胞研究（英文版） 2020年第7期30卷 626-629页

作者： Ellen Ngar-Yun Poon Xiao-ling Luo Sarah E.Webb Bin Yan Rui Zhao Stanley Chun Ming Wu Yong Yang Peng Zhang Huajun Bai Jiaofang Shao Ching Man Chan Godfrey Chi-Fung Chan Suk Ying Tsang Rebekah L.Gundry Huang-Tian Yang Kenneth R.Boheler Department of Medicine and Therapeutics and Centre for Cardiovascular Genomics and Medicine The Chinese University of Hong Kong (CUHK) HKSAR China CAS Key Laboratory of Tissue Microenvironment and Tumor Laboratory of Molecular CardiologyShanghai Institute of Nutrition and Health University of Chinese Academy of Sciences (CAS) CAS Shanghai China Division of Life Science and State Key Laboratory of Molecular Neuroscience The Hong Kong University of Science and Technology HKSAR China Department of Computer Science The University of Hong Kong (HKU) HKSAR China Intervention and Cell Therapy Center Peking University Shenzhen Hospital Shenzhen China School of Life Sciences CUHK HKSAR China Department of Paediatrics and Adolescent Medicine HKU HKSAR China School of Biomedical Sciences HKU HKSAR China SUSTech Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology (SUSTech) Shenzhen China Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical University Nanjing Jiangsu China State Key Laboratory of Agrobiotechnology CUHK HKSAR China Department of Biochemistry and Center for Biomedical Mass Spectrometry Research Medical College of Wisconsin Milwaukee WIUSA CardiOmics Program Center for Heart and Vascular Research Division of Cardiovascular Medicine and Department of Cellular and Integrative Physiology University of Nebraska Medical Center Omaha NE USA Institute for Stem Cell and Regeneration Medicine CASBeijing China Division of Cardiology Department of Medicineand Department of Biomedical Engineering The Johns Hopkins University Baltimore MD USA

Dear Editor,Human pluripotent stem cell (hPSC)-derived cardiomyocytes (CMs) are of significant translational value to in vitro studies of human cardiac development, drug and cardiotoxicity testing and cardiac disease *** of hPSCs to CMs,however, yields mixed cultures of atrial-, ventricular-, and pacemaker-like cells as well as non-CMs in variable proportions.1

关键词：

来源：评论

学校读者我要写书评

暂无评论

CsPb(I_(x)Br_(1-x))_(3) solar cells

引用

science Bulletin 2019年第20期64卷 1532-1539页

作者： Xue Jia Chuantian Zuo Shuxia Tao Kuan Sun Yixin Zhao Shangfeng Yang Ming Cheng Mingkui Wang Yongbo Yuan Junliang Yang Feng Gao Guichuan Xing Zhanhua Wei Lijun Zhang Hin-Lap Yip Mingzhen Liu Qing Shen Longwei Yin Liyuan Han Shengzhong Liu Lianzhou Wang Jingshan Luo Hairen Tan Zhiwen Jin Liming Ding Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing100190China University of Chinese Academy of Sciences Beijing100049China CSIRO Manufacturing Bag10Clayton SouthVictoria3169Australia Center for Computational Energy Research Department of Applied PhysicsEindhoven University of Technology5600MB EindhovenThe Netherlands MOE Key Laboratory of Low-grade Energy Utilization Technologies and Systems Chongqing UniversityChongqing400044China School of Environmental Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Department of Materials Science and Engineering University of Science and Technology of ChinaHefei230026China Institute for Energy Research Jiangsu UniversityZhenjiang212013China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China School of Physics and Electronics Central South UniversityChangsha410083China Department of Physics Chemistry and BiologyLinkoping UniversitySE-58183 LinkopingSweden Institute of Applied Physics and Materials Engineering University of MacaoMacao999078China College of Materials Science&Engineering Huaqiao UniversityXiamen361021China College of Materials Science and Engineering Jilin UniversityChangchun130012China State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou510640China Center for Applied Chemistry School of Materials and EnergyUniversity of Electronic Science and Technology of ChinaChengdu611731China Faculty of Informatics and Engineering The University of Electro-CommunicationsTokyo182-8585Japan School of Materials Science and Engineering Shandong UniversityJinan250061China State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai200240China Shaanxi Key Laboratory for Advanced Energy Devices Shaanxi Normal UniversityXi’an710119China

Owing to its nice performance, low cost, and simple solution-processing, organic-inorganic hybrid perovskite solar cell(PSC) becomes a promising candidate for next-generation high-efficiency solar *** power conversion efficiency(PCE) has boosted from 3.8% to 25.2% over the past ten years. Despite the rapid progress in PCE, the device stability is a key issue that impedes the commercialization of PSCs. Recently, all-inorganic cesium lead halide perovskites have attracted much attention due to their better stability compared with their organic-inorganic counterpart. In this progress report, we summarize the properties of CsPb(IxBr1-x)3 and their applications in solar cells. The current challenges and corresponding solutions are discussed. Finally, we share our perspectives on CsPb(IxBr1-x)3 solar cells and outline possible directions to further improve the device performance.

关键词： Perovskite solar cells Cesium lead halide perovskites Power conversion efficiency Stability

来源：评论

学校读者我要写书评

暂无评论

EMPRESS. IX. Extremely Metal-Poor Galaxies are Very Gas-Rich Dispersion-Dominated Systems: Will JWST Witness Gaseous Turbulent High-z Primordial Galaxies?

arXiv

引用

arXiv 2022年

作者： Isobe, Yuki Ouchi, Masami Nakajima, Kimihiko Ozaki, Shinobu Bouché, Nicolas F. Wise, John H. Xu, Yi Emsellem, Eric Kusakabe, Haruka Hattori, Takashi Nagao, Tohru Chiaki, Gen Fukushima, Hajime Harikane, Yuichi Hayashi, Kohei Hirai, Yutaka Kim, Ji Hoon Maseda, Michael V. Nagamine, Kentaro Shibuya, Takatoshi Sugahara, Yuma Yajima, Hidenobu Aoyama, Shohei Fujimoto, Seiji Fukushima, Keita Hatano, Shun Inoue, Akio K. Ishigaki, Tsuyoshi Kawasaki, Masahiro Kojima, Takashi Komiyama, Yutaka Koyama, Shuhei Koyama, Yusei Lee, Chien-Hsiu Matsumoto, Akinori Mawatari, Ken Moriya, Takashi J. Motohara, Kentaro Murai, Kai Nishigaki, Moka Onodera, Masato Ono, Yoshiaki Rauch, Michael Saito, Tomoki Sasaki, Rin Suzuki, Akihiro Takeuchi, Tsutomu T. Umeda, Hiroya Umemura, Masayuki Watanabe, Kuria Yabe, Kiyoto Zhang, Yechi Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8582 Japan Department of Physics Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan University of Tokyo Chiba Kashiwa277-8583 Japan Univ Lyon Univ Lyon1 ENS de Lyon CNRS Centre de Recherche Astrophysique de Lyon UMR5574 Saint-Genis-LavalF-69230 France Center for Relativistic Astrophysics School of Physics Georgia Institute of Technology AtlantaGA30332 United States Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan European Southern Observatory Karl-Schwarzschild-Straße 2 Garching85748 Germany Observatoire de Genéve Université de Genéve 51 Ch. des Maillettes Versoix1290 Switzerland 650 North A'ohoku Place HiloHI96720 United States Research Center for Space and Cosmic Evolution Ehime University Bunkyo-cho 2-5 Ehime Matsuyama790-8577 Japan Center for Computational Sciences University of Tsukuba Ten-nodai 1-1-1 Tsukuba Ibaraki305-8577 Japan Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom National Institute of Technology Ichinoseki College Hagisho Ichinoseki021-8511 Japan Astronomical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Miyagi Sendai980-8578 Japan Department of Physics and Astronomy University of Notre Dame 225 Nieuwland Science Hall Notre DameIN46556 United States 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 Department of Astronomy University of Wisconsin-Madison 475 N. Charter Street MadisonWI53706 United States Theoretical Astrophysics Department of Earth & Space S

We present kinematics of 6 local extremely metal-poor galaxies (EMPGs) with low metallicities (0.016 − 0.098 Z☉) and low stellar masses (104.7 − 107.6M☉). Taking deep medium-high resolution (R ∼ 7500) integral-field spectra with 8.2-m Subaru, we resolve the small inner velocity gradients and dispersions of the EMPGs with Hα emission. Carefully masking out sub-structures originated by inflow and/or outflow, we fit 3-dimensional disk models to the observed Hα flux, velocity, and velocity-dispersion maps. All the EMPGs show rotational velocities (vrot) of 5-23 km s−1 smaller than the velocity dispersions (σ0) of 17-31 km s−1, indicating dispersion-dominated (vrot/σ0 = 0.29−0.80 gas 0.9 − 1.0. Comparing our results with other Hα kinematics studies, we find that vrot/σ0 decreases and fgas increases with decreasing metallicity, decreasing stellar mass, and increasing specific star-formation rate. We also find that simulated high-z (z ∼ 7) forming galaxies have gas fractions and dynamics similar to the observed EMPGs. Our EMPG observations and the simulations suggest that primordial galaxies are gas-rich dispersion-dominated systems, which would be identified by the forthcoming James Webb Space Telescope (JWST) observations at z ∼ 7. Copyright © 2022, The Authors. All rights reserved.

关键词： Galaxies

来源：评论

学校读者我要写书评

暂无评论

Coastal water quality prediction based on machine learning with feature interpretation and Spatio-temporal analysis

arXiv

引用

arXiv 2021年

作者： Grbčić, Luka Družeta, Siniša Mauša, Goran Lipić, Tomislav Lušić, Darija Vukić Alvir, Marta Lučin, Ivana Sikirica, Ante Davidović, Davor Travaš, Vanja Kalafatović, Daniela Pikelj, Kristina Fajković, Hana Holjević, Toni Kranjčević, Lado Department of Fluid Mechanics and Computational Engineering Faculty of Engineering University of Rijeka Vukovarska 58 Rijeka51000 Croatia Department of Computer Engineering Faculty of Engineering University of Rijeka Vukovarska 58 Rijeka51000 Croatia Center for Advanced Computing and Modelling University of Rijeka Radmile Matejčić 2 Rijeka51000 Croatia Department of Hydrotechnics and Geotechnics Faculty of Civil Engineering University of Rijeka Radmile Matejčić 3 Rijeka51000 Croatia Department of Environmental Health Faculty of Medicine University of Rijeka Braće Branchetta 20/1 Rijeka51000 Croatia Department of Environmental Health Teaching Institute of Public Health of Primorje-Gorski Kotar County Krešimirova 52a Rijeka51000 Croatia Department of Biotechnology University of Rijeka Radmile Matejčić 2 Rijeka51000 Croatia Laboratory for Machine Learning and Knowledge Representations Rudjer Boskovic Institute Biljenička cesta 54 Zagreb10000 Croatia Center for Informatics and Computing Ruđer Bošković Institute Biljenička cesta 54 Zagreb10000 Croatia Department of Geology Faculty of Science University of Zagreb Horvatovac 102a Zagreb10000 Croatia

Coastal water quality management is a public health concern, as poor coastal water quality can potentially harbor pathogens that are dangerous to human health. Tourism-oriented countries need to actively monitor the condition of coastal water at tourist popular sites during the summer season. In this study, routine monitoring data of Escherichia Coli and enterococci across 15 public beaches in the city of Rijeka, Croatia, were used to build machine learning models for predicting their levels based on environmental parameters as well as to investigate their dynamics and relationships with environmental stressors. Gradient Boosting algorithms (Catboost, Xgboost), Random Forests, Support Vector Regression and Artificial Neural Networks were trained with routine monitoring measurements from all sampling sites and used to predict E. Coli and enterococci values based on environmental features. The evaluation of stability and generalizability with 10-fold cross validation analysis of the machine learning models, showed that the Catboost algorithm performed best with R2 values of 0.71 and 0.68 for predicting E. Coli and enterococci, respectively, compared to other evaluated ML algorithms including Xgboost, Random Forests, Support Vector Regression and Artificial Neural Networks. We also use the SHapley Additive exPlanations technique to identify and interpret which features have the most predictive power. The results show that site salinity measured is the most important feature for forecasting both E. Coli and enterococci levels. Finally, the spatial and temporal predictive accuracy of both ML models were examined at sites with the historically lowest coastal water quality. The spatial *** and enterococci models achieved strong R2 values of 0.85 and 0.83, while the temporal models achieved R2 values of 0.74 and 0.67. The temporal model also achieved moderate R2 values of 0.44 and 0.46 at a site with historically high coastal water quality. © 2021, CC BY-NC-ND.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to "Novel model of multiple sclerosis induced by EBV-like virus generate a unique B cell population" [Journal of Neuroimmunology volume 394 (2024) 578408]

引用

Journal of neuroimmunology 2025年 404卷 578625页

作者： J L Deffenbaugh K-J Jung S P Murphy Y Liu C N Rau C Petersen-Cherubini P L Collins D Chung A E Lovett-Racke Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA. Department of Computer Science and Engineering The Ohio State University USA. Department of Microbial Infection & Immunity The Ohio State University Wexner Medical Center USA Neuroscience Graduate Program The Ohio State University USA. Department of Biomedical Informatics The Ohio State University Wexner Medical Center USA Pelotonia Institute for Immuno-Oncology The Ohio State University Wexner Medical Center USA. Department of Neuroscience The Ohio State University Wexner Medical Center USA. Electronic address: amylovettracke@***.

来源：评论

学校读者我要写书评

暂无评论

Expanding the computational Toolbox for Single-Particle Cryo-Electron Microscopy

引用

Microscopy and Microanalysis 2019年第S2期25卷 2686-2687页

作者： Alberto Bartesaghi Department of Computer Science Trinity College of Arts & Sciences Department of Biochemistry Duke University School of Medicine Department of Electrical and Computer Engineering Pratt School of Engineering Duke Institute for Brain Sciences Computational Biology and Bioinformatics Program Duke University Durham NC USA.

来源：评论

学校读者我要写书评

暂无评论

Metrics Reloaded: Recommendations for image analysis validation

arXiv

引用

arXiv 2022年

作者： Maier-Hein, Lena Reinke, Annika Godau, Patrick Tizabi, Minu D. Buettner, Florian Christodoulou, Evangelia Glocker, Ben Isensee, Fabian Kleesiek, Jens Kozubek, Michal Reyes, Mauricio Riegler, Michael A. Wiesenfarth, Manuel Emre Kavur, A. Sudre, Carole H. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Rädsch, Tim Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Jorge Cardoso, M. Cheplygina, Veronika Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian Ginneken, Bram Van Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kofler, Florian Kopp-Schneider, Annette Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rajpoot, Nasir Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Smeden, Maarten Van Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben Van Varoquaux, Gaël Jäger, Paul F. Heidelberg Division of Intelligent Medical Systems and HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt-Marburg Germany Heidelberg Goethe University Frankfurt Germany Department of Medicine Goethe University Frankfurt Germany Department of Informatics Frankfurt Cancer Insititute Germany Department of Computing Imperial College London London United Kingdom Heidelberg Division of Medical Image Computing and HI Applied Computer Vision Lab Germany Institute for AI in Medicine University Medicine Essen Essen Germany Centre for Biomedical Image Analysis Faculty of Informatics Masaryk University Brno Czech Republic ARTORG Center for Biomedical Engineering Research University of Bern Bern Switzerland Department of Radiation Oncology University Hospital Bern University of Bern Bern Switzerland Simula Metropolitan Center for Digital Engineering Oslo Norway UiT The Arctic University of Norway Romsø Norway Heidelberg Division of Biostatistics Germany Heidelberg Division of Intelligent Medical Systems Division of Medical Image Computing HI Applied Computer Vision Lab Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Heidelberg Division of Medical Image Computing Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, we created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. It was developed by a large international consortium in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint – a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. Its applicability is demonstrated for various biomedical use cases. © 2022, CC BY.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Cascaded cross-module residual learning towards lightweight end-to-end speech coding

arXiv

引用

arXiv 2019年

作者： Zhen, Kai Sung, Jongmo Lee, Mi Suk Beack, Seungkwon Kim, Minje Indiana University School of Informatics Computing and Engineering BloomingtonIN United States Indiana University Cognitive Science Program BloomingtonIN United States Electronics and Telecommunications Research Institute Daejeon Korea Republic of

Speech codecs learn compact representations of speech signals to facilitate data transmission. Many recent deep neural network (DNN) based end-to-end speech codecs achieve low bitrates and high perceptual quality at the cost of model complexity. We propose a cross-module residual learning (CMRL) pipeline as a module carrier with each module reconstructing the residual from its preceding modules. CMRL differs from other DNN-based speech codecs, in that rather than modeling speech compression problem in a single large neural network, it optimizes a series of less-complicated modules in a two-phase training scheme. The proposed method shows better objective performance than AMR-WB and the state-of-the-art DNNbased speech codec with a similar network architecture. As an end-to-end model, it takes raw PCM signals as an input, but is also compatible with linear predictive coding (LPC), showing better subjective quality at high bitrates than AMR-WB and OPUS. The gain is achieved by using only 0.9 million trainable parameters, a significantly less complex architecture than the other DNN-based codecs in the literature. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

TOI-2458 b: A mini-Neptune consistent with in situ hot Jupiter formation

arXiv

引用

arXiv 2024年

作者： Šubjak, Jan Gandolfi, Davide Goffo, Elisa Rapetti, David Jankowski, Dawid Mizuki, Toshiyuki Dai, Fei Serrano, Luisa M. Wilson, Thomas G. Goździewski, Krzysztof Nowak, Grzegorz Jenkins, Jon M. Twicken, Joseph D. Winn, Joshua N. Bieryla, Allyson Ciardi, David R. Cochran, William D. Collins, Karen A. Deeg, Hans J. Garcia, Rafael A. Guenther, Eike W. Hatzes, Artie P. Kabath, Petr Korth, Judith Latham, David W. Livingston, John H. Lund, Michael B. Mathur, Savita Narita, Norio Orell-Miquel, Jaume Palle, Enric Persson, Carina M. Redfield, Seth Schwarz, Richard P. Watanabe, David Ziegler, Carl Astronomical Institute Czech Academy of Sciences Fričova 298 Ondřejov251 65 Czech Republic Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Dipartimento di Fisica Universita degli Studi di Torino via Pietro Giuria 1 TorinoI-10125 Italy Thuringer Landessternwarte Tautenburg Sternwarte 5 Tautenburg07778 Germany NASA Ames Research Center Moffett FieldCA94035 United States Research Institute for Advanced Computer Science Universities Space Research Association WashingtonDC20024 United States Institute of Astronomy Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziadzka 5 Toruń87-100 Poland Astrobiology Center of NINS 2-21-1 Osawa Mitaka Tokyo181-8588 Japan National Astronomical Observatory of Japan 2-21-2 Osawa Mitaka Tokyo181-8588 Japan Institute for Astronomy University of Hawai'i 2680 Woodlawn Drive HonoluluHI96822 United States Department of Physics University of Warwick Gibbet Hill Road CoventryCV4 7AL United Kingdom SETI Institute Mountain ViewCA94043 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States NASA Exoplanet Science Institute-Caltech/IPAC PasadenaCA91125 United States McDonald Observatory The University of Texas AustinTX United States Center for Planetary Systems Habitability The University of Texas AustinTX United States C. Via Lactea S/N Tenerife La LagunaE-38205 Spain Dept. de Astrofisica Tenerife La LagunaE-38206 Spain Universite Paris-Saclay Universite Paris Cite CEA CNRS AIM Gif-sur-Yvette91191 France Lund Observatory Division of Astrophysics Department of Physics Lund University Box 118 Lund22100 Sweden Astronomical Science Program Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Komaba Institute for Science The University of Tokyo 3-8-1 Komaba Meguro Tokyo153-8902 Japan Chalmers University of Technology Departmen

We report on the discovery and spectroscopic confirmation of TOI-2458 b, a transiting mini-Neptune around an F-type star leaving the mainsequence with a mass of M*= 1.05 ± 0.03Mo, a radius of R*= 1.31 ± 0.03 Ro, an effective temperature of Teff = 6005 ± 50 K, and a metallicity of -0.10 ± 0.05 dex. By combining TESS photometry with high-resolution spectra acquired with the HARPS spectrograph, we found that the transiting planet has an orbital period of ∼3.74 days, a mass of Mp = 13.31±0.99M⊕ and a radius of Rp = 2.83±0.20 R⊕. The host star TOI-2458 shows a short activity cycle of ∼54 days revealed in the HARPS S-index and Hα times series. We took the opportunity to investigate other F stars showing activity cycle periods comparable to that of TOI-2458 and found that they have shorter rotation periods than would be expected based on the gyrochronology predictions. In addition, we determined TOI-2458's stellar inclination angle to be i*= 10.6+13.3 -10.6 degrees. We discuss that both phenomena (fast stellar rotation and planet orbit inclination) could be explained by in situ formation of a hot Jupiter interior to TOI-2458 b. It is plausible that this hot Jupiter was recently engulfed by the star. Analysis of HARPS spectra has identified the presence of another planet with a period of P = 16.55 ± 0.06 days and a minimum mass of Mp sin i = 10.22 ± 1.90M⊕. Using dynamical stability analysis, we constrained the mass of this planet to the range Mc (10, 25)M⊕. © 2024, CC BY.

关键词： Stars

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：