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PERFORMANCE OF A PRIORITIZED ON-BOARD BASEBAND SWITCH FOR A MULTISERVICE MULTIBEAM SATELLITE

INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS 1994年第3期12卷 283-297页

作者： BOHM, S ELHAKEEM, AK HACHICHA, M Department of Electrical and Computer Engineering Concordia University 1455 De Maisonneuve Blvd. West Montreal H3A 1M8 Canada Was born in Montreal Canada on 14 September 1966. He received the B. Eng. degree in electrical engineering from Concordia University Montreal Canada in 1989. He is at present completing the M.A.Sc. degree in electrical engineering at Concordia University. (S'75–S'79–M'79–SM'86) received the Ph.D. degree from Southern Methodist University Dallas TX in 1979. He spent the next two years working as a Visiting Professor in Egypt after which he moved to Ottawa Canada in 1982. He assumed teaching and research positions in Carleton and Manitoba Univerities and later moved to Concordia University Montreal Canada in 1983 where he is now a Professor in the Electrical and Computer Engineering Department. He has published numerous papers in IEEE and international journals in the areas of spread spectrum and networking. He is a well-known expert in these areas and serves as a consultant to many companies. His current research interests include wide-band metropolitan networks switching architectures and performance of on-board multibeam satellites acquisitionless CDMA networks code distribution and orthogonalization of CDMA signals responsive congestion control for ATM-based networks ARQ techniques and investigation of the novel SUGAR CDMA systems in fading channels. Dr. Elhakeem is a Senior Member of the Canadian Electrical Engineering Society and Armed Forces Association. He has chaired numerous technical sessions in IEEE Conferences was the Technical Program Chairman for IEEE Montech 1986 Montreal Canada. Dr. Elhakeem is the key guest editor of theIEEE Journal of Selected Areas in Communicationsfor the May June issues 1993 covering CDMA networks. Advanced Technology & Networks VISTAR Telecommunications Inc. Ottawa Ontario K1G 3J4 Canada An Associate Director of Advanced Technology & Networks Group VISTAR Telecommunications Inc. Ottawa Canada. He is also an Adjunct Pr

In this paper, we study the performance of a prioritized on-board baseband switch in conjunction with a multibeam satellite handling integrated services. The services considered for the analysis include voice, video, file transfer and interactive data. The prioritized switch uses both input and output buffering, switch speed-up as well as a two-phase head-of-line resolution algorithm, in order to reduce the buffer loss while maintaining acceptable user delays. The minimum required buffer capacity and switch speed-up for each service in a prioritized environment are found under uniform traffic conditions. It is shown that under uniform traffic conditions, only minimal buffering and switch speed-up are needed even for the lowest priority users. The performance dependence on the switch size is also substantially reduced with head of line resolution and buffering even in a prioritized environment.

关键词： SWITCH ON-BOARD BASEBAND MULTIBEAM PRIORITIZED HEAD-OF-LINE UNIFORM LOAD SPEED-UP

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Abstracts and Workshops 7th National Spinal Cord Injury Conference November 9-11, 2017 Fallsview Casino Resort Niagara Falls, Ontario, Canada Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2017年第6期40卷 813-869页

作者： [Anonymous] a NET Team Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. fo Neural Engineering and Therapeutic Team Lyndhurst Centre Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. c Rick Hansen Institute Vancouver BC Canada. ev Rick Hansen Institute Vancouver BC Canada. fc Stan Cassidy Hospital University of New Brunswick Fredericton NB Canada. fd Dalhousie University Halifax NS Canada. e University of Saskatchewan Saskatoon SK Canada. aa University of Calgary Calgary AB Canada. y Dalhousie University Halifax NS Canada. fa Health Sciences Centre Winnipeg MB Canada. fb University of Manitoba Winnipeg MB Canada. h University of Alberta Edmonton AB Canada. i Universite Laval Quebe c City QC Canada. bd Rick Hansen Institute Vancouver BC Canada. fz Clinician Investigator Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto. v University of Toront o Toronto ON Canada. n Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada. o Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. ga Clinical Scientist Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Physical Therapy University of Toronto. dx Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. fm Lawson Health Research Institute London ON Canada. r Parkwood Institute London ON Canada. bi Parkwood Institute London ON Canada. s University of British Columbia Vancouver BC Canada. t Simon Fraser University Burnaby BC Canada. u DeltaQuest Foundation Concord MA USA. z Institut national d'excellence en santé et en services sociaux (INESSS) Quebec City QC Ca

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Retraction notice to "A deep learning approach based on graphs to detect plantation lines" [Heliyon Volume 10, Issue 11, 15 June 2024, e31730]

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Heliyon 2024年第23期10卷 e40689页

作者： Diogo Nunes Gonçalves José Marcato Junior Mauro Dos Santos de Arruda Vanessa Jordão Marcato Fernandes Ana Paula Marques Ramos Danielle Elis Garcia Furuya Lucas Prado Osco Hongjie He Lucio André de Castro Jorge Jonathan Li Farid Melgani Hemerson Pistori Wesley Nunes Gonçalves Faculty of Computer Science Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Engineering Architecture and Urbanism and Geography Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Agricultural Sciences Federal University of Grande Dourados Av. Costa e Silva Dourados 79070-900 MS Brazil. Faculty of Science and Technology São Paulo State University (UNESP) R. Roberto Simonsen 305 Presidente Prudente 19060-900 SP Brazil. Program of Environment and Regional Developement University of Western São Paulo Raposo Tavares km 572 Presidente Prudente 19067-175 SP Brazil. Department of Geography and Environmental Management University of Waterloo Waterloo ON N2L 3G1 Canada. National Research Center of Development of Agricultural Instrumentation Brazilian Agricultural Research Agency (EMBRAPA) 13560-970 R. XV de Novembro 1452 São Carlos SP Brazil. Department of Information Engineering and Computer Science University of Trento Trento 38122 Italy. INOVISAO Dom Bosco Catholic University Avenida Tamandaré 6000 Campo Grande 79117-900 MS Brazil.

[This retracts the article DOI: 10.1016/***.2024.e31730.].

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A deep learning approach based on graphs to detect plantation lines

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Heliyon 2024年第11期10卷 e31730页

Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the Knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no

关键词： Aerial imagery Convolutional neural networks Object detection Remote sensing UAV

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Genome-wide analyses identify 30 loci associated with obsessive–compulsive disorder

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Nature Genetics 2025年 1-13页

作者： Strom, Nora I. Gerring, Zachary F. Galimberti, Marco Yu, Dongmei Halvorsen, Matthew W. Abdellaoui, Abdel Rodriguez-Fontenla, Cristina Sealock, Julia M. Bigdeli, Tim Coleman, Jonathan R. Mahjani, Behrang Thorp, Jackson G. Bey, Katharina Burton, Christie L. Luykx, Jurjen J. Zai, Gwyneth Alemany, Silvia Andre, Christine Askland, Kathleen D. Bäckman, Julia Banaj, Nerisa Barlassina, Cristina Nissen, Judith Becker Bienvenu, O. Joseph Black, Donald Bloch, Michael H. Børte, Sigrid Bosch, Rosa Breen, Michael Brennan, Brian P. Brentani, Helena Buxbaum, Joseph D. Bybjerg-Grauholm, Jonas Byrne, Enda M. Cabana-Dominguez, Judit Camarena, Beatriz Camarena, Adrian Cappi, Carolina Carracedo, Angel Casas, Miguel Cavallini, Maria Cristina Ciullo, Valentina Cook, Edwin H. Crosby, Jesse Cullen, Bernadette A. De Schipper, Elles J. Delorme, Richard Djurovic, Srdjan Elias, Jason A. Estivill, Xavier Falkenstein, Martha J. Fundin, Bengt T. Garner, Lauryn Gironda, Christina Goes, Fernando S. Grados, Marco A. Grove, Jakob Guo, Wei Haavik, Jan Hagen, Kristen Harrington, Kelly Havdahl, Alexandra Höffler, Kira D. Hounie, Ana G. Hucks, Donald Hultman, Christina Janecka, Magdalena Jenike, Eric Karlsson, Elinor K. Kelley, Kara Klawohn, Julia Krasnow, Janice E. Krebs, Kristi Lange, Christoph Lanzagorta, Nuria Levey, Daniel Lindblad-Toh, Kerstin Macciardi, Fabio Maher, Brion Mathes, Brittany McArthur, Evonne McGregor, Nathaniel McLaughlin, Nicole C. Meier, Sandra Miguel, Euripedes C. Mulhern, Maureen Nestadt, Paul S. Nurmi, Erika L. O’Connell, Kevin S. Osiecki, Lisa Ousdal, Olga Therese Palviainen, Teemu Pedersen, Nancy L. Piras, Federica Potluri, Sriramya Rabionet, Raquel Ramirez, Alfredo Rauch, Scott Reichenberg, Abraham Riddle, Mark A. Ripke, Stephan Rosário, Maria C. Sampaio, Aline S. Schiele, Miriam A. Skogholt, Anne Heidi Sloofman, Laura G. Smit, Jan Artigas, María Soler Thomas, Laurent F. Tifft, Eric Vallada, Homero van Kirk, Nathanial Veenstra-VanderWeele, Jeremy Vulink, Nienke N. Walker, Christopher P. Wang, Ying Wendland, Jens R. Winsvold Department of Psychology Humboldt-Universität zu Berlin Berlin Germany Department of Psychiatric Phenomics and Genomics (IPPG) Ludwig-Maximilians University Munich Munich Germany Centre for Psychiatry Research Department of Clinical Neuroscience Karolinska Institutet and Stockholm Health Services Region Stockholm Stockholm Sweden Department of Biomedicine Aarhus University Aarhus Denmark University Hospital of Psychiatry and Psychotherapy University of Bern Bern Switzerland Department of Mental Health and Neuroscience Translational Neurogenomics QIMR Berghofer Medical Research Institute Brisbane QLD Australia Department of Population Health and Immunity Healthy Development and Ageing Walter and Eliza Hall Institute of Medical Research Melbourne VIC Australia Department of Psychiatry Human Genetics Yale University New Haven CT United States VA Connecticut Healthcare System West Haven CT United States Department of Center for Genomic Medicine Psychiatric and Neurodevelopmental Genetics Unit Massachusetts General Hospital Boston MA United States Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA United States Department of Genetics University of North Carolina at Chapel Hill Chapel Hill NC United States Department of Psychiatry Amsterdam University Medical Centers University of Amsterdam Amsterdam Netherlands Center for Research in Molecular Medicine and Chronic Diseases (CiMUS) Genomics and Bioinformatics University of Santiago de Compostela Santiago de Compostela Spain Grupo de Medicina Xenómica Genetics Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS) Santiago de Compostela Spain Vanderbilt Genetics Institute Vanderbilt University Nashville TN United States Department of Psychiatry and Behavioral Sciences SUNY Downstate Health Sciences University Brooklyn NY United States VA NY Harbor Healthcare System Brooklyn NY United States Social Genetic and Developmental Psychiatry Centre Insti

Obsessive–compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D₁ and D₂ type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index. © The Author(s) 2025.

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The Hyper-Kamiokande experiment - snowmass LOI

arXiv

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arXiv 2020年

作者： Abe, K. Adrich, P. Aihara, H. Akutsu, R. Alekseev, I. Ali, A. Ameli, F. Anthony, L.H.V. Araya, A. Asaoka, Y. Aushev, V. Bandac, I. Barbi, M. Barr, G. Batkiewicz-Kwasniak, M. Bellato, M. Berardi, V. Bernard, L. Bernardini, E. Berns, L. Bhadra, S. Bian, J. Blanchet, A. Blondel, A. Boiano, A. Bolognesi, S. Bonavera, L. Borjabad, S. Boschi, T. Bose, D. Boyd, S.B. Bozza, C. Bravar, A. Bronner, C. Bubak, A. Buchowicz, A. Avanzini, M. Buizza Cafagna, F.S. Calabria, N.F. Calvo-Mozota, J.M. Cao, S. Catanesi, M.G. Chakraborty, S. Choi, J.H. Choubey, S. Cicerchia, M. Coleman, J. Collazuol, G. Cuen-Rochin, S. Danilov, M. Fuente, E. De la de Perio, P. de Rosa, G. Dealtry, T. Densham, C.J. Dergacheva, A. Deshmukh, N. Devi, M.M. Di Lodovico, F. Di Meo, P. Di Palma, I. Doyle, T.A. Drakopoulou, E. Drapier, O. Dumarchez, J. Eklund, L. El Hedri, S. Ellis, J. Emery, S. Esmaili, A. Fedotov, S. Feng, J. Fernández-Martinez, E. Ferrario, P. Ferrazzi, B. Finch, A. Finley, C. Fiorillo, G. Fitton, M. Friend, M. Fujii, Y. Fukuda, Y. Galinski, G. Gao, J. Garde, C. Garfagnini, A. Garode, S. Gialanella, L. Giganti, C. Gomez-Cadenas, J.J. Gonin, M. González-Nuevo, J. Gorin, A. Gornea, R. Gramegna, F. Grassi, M. Grella, G. Guigue, M. Hadley, D.R. Harada, M. Hartz, M. Hassani, S. Hastings, N.C. Hayato, Y. Hiraide, K. Hoshina, K. Hultqvist, K. Iacob, F. Ichikawa, A.K. Ibnsalih, W. Idrissi Ikeda, M. Inomoto, M. Ioannisian, A. Ishida, T. Ishidoshiro, K. Ishino, H. Ishitsuka, M. Ito, H. Ito, S. Itow, Y. Iwamoto, K. Izumi, N. Izumiyama, S. Jakkapu, M. Jamieson, B. Jang, J.S. Jo, H.S. Jonsson, P. Joo, K.K. Kajita, T. Kakuno, H. Kameda, J. Kano, Y. Karlen, D. Kataoka, Y. Kato, A. Katori, T. Kazarian, N. Khabibullin, M. Khotjantsev, A. Kikawa, T. Kim, J.Y. Kim, S.B. King, S. Kinoshita, T. Kisiel, J. Klekotko, A. Kobayashi, T. Koerich, L. Kolev, N. Konaka, A. Kormos, L.L. Koshio, Y. Kotsar, Y. Kouzakov, K.A. Kowalik, K.L. AGH University of Science and Technology Faculty of Computer Science Electronics and Telecommunications Krakow Poland British Columbia Institute of Technology Physics Department BurnabyBC Canada Università della Campania"L. Vanvitelli" INFN Sezione di Napoli Napoli Italy Carleton University Department of Physics OttawaON Canada University of California Irvine Department of Physics and Astronomy IrvineCA United States Charles University IPNP FMF Prague Czech Republic Chonnam National University Department of Physics Gwangju Korea Republic of Dongshin University Laboratory for High Energy Physics Naju Korea Republic of Donostia International Physics Center Ikerbasque Foundation Basque Country Spain Ecole Polytechnique IN2P3-CNRS Laboratoire Leprince-Ringuet Palaiseau France University of Edinburgh School of Physics and Astronomy Edinburgh United Kingdom ETH Zurich Institute for Particle and Astroparticle Physics Zurich Switzerland University of Geneva Section de Physique DPNC Geneva Switzerland GIST College Gwangju Institute of Science and Technology Gwangju Korea Republic of University of Glasgow School of Physics and Astronomy Glasgow United Kingdom Universidad de Guadalajara CUCEA IT.Ph.D. program GuadalajaraJal Mexico Universidad de Guadalajara CUCEI Departamento de Fisica GuadalajaraJal Mexico H. Niewodniczá nski Institute of Nuclear Physics PAN Cracow Poland Imperial College London Department of Physics London United Kingdom Indian Institute of Technology Guwahati Guwahati India Indian Institute of Technology Jodhpur Department of Physics Karwar Rajasthan India Indian Institute of Technology Kharagpur Department of Physics Kharagpur India INFN Gruppo Collegato di Salerno Fisciano Italy INFN Laboratori Nazionali di Legnaro LegnaroPD Italy INFN Sezione di Bari Università e Politecnico di Bari Bari Italy INFN Sezione di Napoli Università Federico II di Napoli Dipartimento di Fisica Napoli Italy INFN Sezione di Napoli Nap

Hyper-Kamiokande is the next generation underground water Cherenkov detector that builds on the highly successful Super-Kamiokande experiment. The detector which has an 8.4 times larger effective volume than its predecessor will be located along the T2K neutrino beamline and utilize an upgraded J-PARC beam with 2.6 times beam power. Hyper-K’s low energy threshold combined with the very large fiducial volume make the detector unique, that is expected to acquire an unprecedented exposure of 3.8 Mton·year over a period of 20 years of operation. Hyper-Kamiokande combines an extremely diverse science program including nucleon decays, long-baseline neutrino oscillations, atmospheric neutrinos, and neutrinos from astrophysical origins. The scientific scope of this program is highly complementary to liquid-argon detectors for example in sensitivity to nucleon decay channels or supernova detection modes. Hyper-Kamiokande construction has started in early 2020 and the experiment is expected to start operations in 2027. The Hyper-Kamiokande collaboration is presently being formed amongst groups from 19 countries including the United States, whose community has a long history of making significant contributions to the neutrino physics program in Japan. US physicists have played leading roles in the Kamiokande, Super-Kamiokande, EGADS, K2K, and T2K programs. Copyright © 2020, The Authors. All rights reserved.

关键词： Atomic physics

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

arXiv

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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

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Creation and analysis of biochemical constraint-based models: The COBRA Toolbox v3.0

arXiv

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arXiv 2017年

作者： Heirendt, Laurent Arreckx, Sylvain Pfau, Thomas Mendoza, Sebastián N. Richelle, Anne Heinken, Almut Haraldsdóttir, Hulda S. Wachowiak, Jacek Keating, Sarah M. Vlasov, Vanja Magnusdóttir, Stefania Ng, Chiam Yu Preciat, German Žagare, Alise Chan, Siu H.J. Aurich, Maike K. Clancy, Catherine M. Modamio, Jennifer Sauls, John T. Noronha, Alberto Bordbar, Aarash Cousins, Benjamin El Assal, Diana C. Valcarcel, Luis V. Apaolaza, Iñigo Ghaderi, Susan Ahookhosh, Masoud Guebila, Marouen Ben Kostromins, Andrejs Sompairac, Nicolas Le, Hoai M. Ma, Ding Sun, Yuekai Wang, Lin Yurkovich, James T. Oliveira, Miguel A.P. Vuong, Phan T. El Assal, Lemmer P. Kuperstein, Inna Zinovyev, Andrei Scott Hinton, H. Bryant, William A. Aragón Artacho, Francisco J. Planes, Francisco J. Stalidzans, Egils Maass, Alejandro Vempala, Santosh Hucka, Michael Saunders, Michael A. Maranas, Costas D. Lewis, Nathan E. Sauter, Thomas Palsson, Bernhard Ø. Thiele, Ines Fleming, Ronan M.T. Luxembourg Centre for Systems Biomedicine University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg Life Sciences Research Unit University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg University of Chile Blanco Encalada 2085 Santiago Chile Department of Pediatrics University of California San Diego School of Medicine San DiegoCA92093 United States Hinxton CambridgeCB10 1SD United Kingdom Department of Chemical Engineering Pennsylvania State University University University ParkPA16802 United States Department of Physics University of California San Diego 9500 Gilman Dr. San DiegoCA92093 United States Bioinformatics and Systems Biology Program University of California San Diego San DiegoCA United States Sinopia Biosciences San DiegoCA United States School of Computer Science Algorithms and Randomness Center Georgia Institute of Technology AtlantaGA United States Biomedical Engineering and Sciences Department TECNUN University of Navarra Paseo de Manuel Lardizabal 13 San Sebastian20018 Spain Institute of Microbiology and Biotechnology University of Latvia Jelgavas iela 1 RigaLV-1004 Latvia Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States Bioengineering Department University of California San Diego San DiegoCA United States Utah State University Research Foundation 1695 North Research Park Way North LoganUT84341 United States Centre for Integrative Systems Biology and Bioinformatics Department of Life Sciences Imperial College London London United Kingdom Department of Mathematics University of Alicante Spain California Institute of Technology Computing and Mathematical Sciences MC 305-16 1200 E. California Blvd. PasadenaCA91125 United States Mathomics Center for Mathematical Modeling University of Chile Beauchef 851 Santiago Chile Novo Nordisk Foundation Center for Biosustainability University of California San Diego San DiegoCA92093 Uni

COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Data integration

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A molecular single-cell lung atlas of lethal COVID-19 (vol 595, pg 114, 2021)

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NATURE 2021年第7882期598卷 E2-E2页

作者： Melms, Johannes C. Biermann, Jana Huang, Huachao Wang, Yiping Nair, Ajay Tagore, Somnath Katsyv, Igor Rendeiro, Andre F. Amin, Amit Dipak Schapiro, Denis Frangieh, Chris J. Luoma, Adrienne M. Filliol, Aveline Fang, Yinshan Ravichandran, Hiranmayi Clausi, Mariano G. Alba, George A. Rogava, Meri Chen, Sean W. Ho, Patricia Montoro, Daniel T. Kornberg, Adam E. Han, Arnold S. Bakhoum, Mathieu F. Anandasabapathy, Niroshana Suarez-Farinas, Mayte Bakhoum, Samuel F. Bram, Yaron Borczuk, Alain Guo, Xinzheng V. Lefkowitch, Jay H. Marboe, Charles Lagana, Stephen M. Del Portillo, Armando Tsai, Emily J. Zorn, Emmanuel Markowitz, Glen S. Schwabe, Robert F. Schwartz, Robert E. Elemento, Olivier Saqi, Anjali Hibshoosh, Hanina Que, Jianwen Izar, Benjamin Department of Medicine Division of Hematology/Oncology Columbia University Irving Medical Center New York NY USA Columbia Center for Translational Immunology Columbia University Irving Medical Center New York NY USA Herbert Irving Comprehensive Cancer Center Columbia University Irving Medical Center New York NY USA Program for Mathematical Genomics Columbia University New York NY USA Columbia Center for Human Development Columbia University Irving Medical Center New York NY USA Division of Digestive and Liver Diseases Columbia University Irving Medical Center New York NY USA Department of Medicine Columbia University Irving Medical Center New York NY USA Institute of Human Nutrition Columbia University New York NY USA Department of Systems Biology Columbia University Irving Medical Center New York NY USA Department of Pathology and Cell Biology Columbia University Irving Medical Center New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Caryl and Israel Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA WorldQuant Initiative for Quantitative Prediction Weill Cornell Medicine New York NY USA Department of Physiology and Biophysics Weill Cornell Medical College New York NY USA Department of Dermatology Weill Cornell Medical College New York NY USA Meyer Cancer Center Weill Cornell Medical College New York NY USA Laboratory of Systems Pharmacology Harvard Medical School Boston MA USA Klarman Cell Observatory Broad Institute of MIT and Harvard Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Cancer Immunology and Virology Dana-Farber Cancer Center Boston MA USA Human Immune Monitoring Core Columbia University Irving Medical Center New York NY USA Department of Medicine Division of Pulmonary and Critical Care Massachusetts General Hospital Boston MA USA Cell Circu

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Reporting of Hospital Facility on Smartphone

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Journal of Physics: Conference Series 2021年第1期1807卷

作者： Jack Febrian Rusdi Sazilah Salam Nur Azman Abu Budi Sunaryo Nova Agustina Harya Gusdevi Hermansah Ari Hadhiwibowo Tuty Heryati Richki Hardi Rohmat Taufiq Muhammad Taher Jufri Ignatius Sudarsono Eko Wahyu Utomo Frans Richard Kodong Puteri Fannya Informatics Engineering Sekolah Tinggi Teknologi Bandung Bandung Indonesia. Information and Communication Technology Faculty Universiti Teknikal Malaysia Melaka Melaka Malaysia. Department of Electrical Engineering Andalas University Padang Indonesia. Rumah Sakit Umum Daerah Majalaya Kabupaten Bandung Majalaya Indonesia. Informatics Engineering Computer Science Faculty Universitas Mulya Balikpapan Indonesia. Department of Informatics Engineering Engineering Faculty University Muhammadiyah of Tangerang Tangerang 15117 Indonesia Program Studi Sistem Informasi Fakultas Teknik dan Sistem Informasi Universitas Yapis Papua Civil Engineering Department Engineering Faculty Universitas Langlangbuana Bandung Bandung Indonesia. Department of Informatics Engineering UPN 'Veteran' Yogyakarta Yogyakarta Indonesia. Department of Medical Record and Health Information Faculty of Health Universitas Esa Unggul Jakarta Indonesia.

In the context of achieving Good Corporate Governance (GCG) in hospitals, among others, it is carried out with control and supervision, including in the case of hospital facility maintenance installations. Besides that, the hospital needs to improve its services. The asset reporting system is one of the high needs in this field, so it requires a solution that can deal with existing problems. Unfortunately, the current reporting system so far is more likely to be conventional, such as by telephone. This study proposes a new solution to the hospital facility maintenance reporting process, namely by utilising smartphone-based applications that directly connected to the server. So, the information distributed to the competent parties. This solution can speed up the reporting process and actions. Also, save the historical equipment that is available from each service room — the results of this study used as a hospital facility maintenance reporting system.

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