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37th International Cosmic Ray Conference, ICRC 2021

作者： Saito, T. Delgado, C. Blanch, O. Artero, M. Barrio, J.A. Cassol, F. Diaz, C. Hadasch, D. Hoffmann, D. Houles, J. Inome, Y. Iori, M. Jouvin, L. Kerszberg, D. Kobayashi, Y. Kubo, H. Martinez, G. Mazin, D. Moretti, E. Nakamori, T. Nozaki, S. Oka, T. Okumura, A. Palatiello, M. Polo, M. Prast, J. Sakurai, S. Sunada, Y. Takahashi, M. Takeishi, R. Tejedor, L.A. Yamamoto, T. Yoshida, T. Abe, H. Aguasca, A. Agudo, I. Antonelli, L.A. Aramo, C. Armstrong, T. Asano, K. Ashkar, H. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Batkovic, I. Becerra González, J. Bernardos, M.I. Berti, A. Biederbeck, N. Bigongiari, C. Bonnoli, G. Bordas, P. Bose, D. Bulgarelli, A. Burelli, I. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Cerruti, M. Chai, Y. Cheng, K. Chikawa, M. Chytka, L. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. De Angelis, A. de Bony de Lavergne, M. Deleglise, G. Delgado Mengual, J. della Volpe, D. Depaoli, D. Di Pierro, F. Di Venere, L. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Elsässer, D. Emery, G. Escudero, J. Fiasson, A. Foffano, L. Fonseca, M.V. Freixas Coromina, L. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Green, D. Grespan, P. Gunji, S. Hackfeld, J. Hahn, A. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Horns, D. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Inada, T. Ishio, K. Iwamura, Y. Jacquemont, M. Jimenez Martinez, I. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kong, A. Kushida, J. Lamanna, G. Lamastra, A. Le Flour, T. Longo, F. López-Coto, R. López-Moya, M. López-Oramas, A. Luque-Escamilla, P.L. Majumdar, P. Makariev, M. Mandat, D. Manganaro, M. Mannheim, K. Mariotti, M. Marquez, P. Marsella, G. Martí, J. Martinez, O. Martínez, M. Marusevec, P. Mas, A. Maurin, G. Mestre Guillen, E. Micanovic, S. Miceli, D. Miener, T. Miranda, J.M. ICRR Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan CIEMAT Avda. Complutense 40 Madrid28040 Spain The Barcelona Institute of Science and Technology Bellaterra Campus UAB Barcelona08193 Spain EMFTEL Department IPARCOS Universidad Complutense de Madrid Madrid28040 Spain Aix-Marseille Université CNRS IN2P3 CPPM 163 Avenue de Luminy MarseilleCedex 09 13288 France INFN Sezione di Roma La Sapienza P.le Aldo Moro 2 Roma00185 Italy Division of Physics and Astronomy Graduate School of Science Kyoto University Sakyo-ku Kyoto606-8502 Japan Department of Physics Yamagata University Yamagata990-8560 Japan ISEE Nagoya University Chikusa-ku Nagoya464-8602 Japan Graduate School of Science and Engineering Saitama University 255 Simo-Ohkubo Sakura-ku Saitama338-8570 Japan CNRS Laboratoire d'Annecy de Physique des Particules IN2P3 Univ. Grenoble Alpes Univ. Savoie Mont Blanc Annecy74000 France Department of Physics Konan University Hyogo Kobe658-8501 Japan Faculty of Science Ibaraki University Ibaraki Mito310-8512 Japan Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain Instituto de Astrofísica de Andalucía CSIC Spain INAF - Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy IRFU CEA Université Paris-Saclay France Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil INFN Sezione di Padova Università degli Studi di Padova Italy Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain Max-Planck-Institut für Physik Germany Department of Physics TU Dortmund University Germany Saha Institute of Nuclear Physics India INFN Sezione di Trieste Università degli Studi di Udine Italy INFN Sezio

The first Large Size Telescope (LST-1) of the Cherenkov Telescope Array has been operational since October 2018 at La Palma, Spain. We report on the results obtained during the camera commissioning. The noise level of the readout is determined as a 0.2 p.e. level. The gain of PMTs are well equalized within 2% variation, using the calibration flash system. The effect of the night sky background on the signal readout noise as well as the PMT gain estimation are also well evaluated. Trigger thresholds are optimized for the lowest possible gamma-ray energy threshold and the trigger distribution synchronization has been achieved within 1 ns precision. Automatic rate control realizes the stable observation with 1.5% rate variation over 3 hours. The performance of the novel DAQ system demonstrates a less than 10% dead time for 15 kHz trigger rate even with sophisticated online data correction. © 2022 Sissa Medialab Srl. All rights reserved.

关键词： Cameras

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory

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Nature Communications 2025年第1期16卷 1-10页

作者： Rajendran, Suraj Xu, Zhenxing Pan, Weishen Zang, Chengxi Siempos, Ilias Torres, Lisa Xu, Jie Bian, Jiang Schenck, Edward J. Wang, Fei Tri-Institutional Computational Biology & Medicine Program Cornell University Cornell NY United States Division of Health Informatics Department of Population Health Sciences Weill Cornell Medicine New York NY United States Division of Pulmonary and Critical Care Medicine Department of Medicine New York-Presbyterian Hospital-Weill Cornell Medical Center Weill Cornell Medicine New York NY United States First Department of Critical Care Medicine and Pulmonary Services Evangelismos Hospital National and Kapodistrian University of Athens Medical School Athens Greece Department of Health Outcomes and Biomedical Informatics College of Medicine University of Florida Gainesville FL United States Department of Biostatistics and Health Data Science School of Medicine Indiana University Indianapolis IN United States Regenstrief Institute Indianapolis IN United States

Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, including septic shock, pneumonia and the acute respiratory distress syndrome (ARDS). The risk and benefit of corticosteroids are not fully defined using the construct of organ dysfunction duration. This retrospective multicenter, proof-of-concept study aimed to evaluate the association between usage of corticosteroids and mortality of patients with sepsis, pneumonia and ARDS by emulating a target trial framework stratified by predicted organ dysfunction trajectory. The study employed a two staged machine learning (ML) methodology to first subphenotype based on organ dysfunction trajectory then predict this defined trajectory. Once patients were classified by predicted trajectory we conducted a target trial emulation. Our analysis revealed that the association between corticosteroid use and 28-day mortality varied by predicted trajectory and between *** findings suggest that matching treatment strategies to empirically observed pathobiology may offer a more nuanced understanding of corticosteroid utility. © The Author(s) 2025.

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SI-spreading-based network embedding in static and temporal networks

arXiv

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arXiv 2020年

作者： Zhan, Xiu-Xiu Li, Ziyu Masuda, Naoki Holme, Petter Wang, Huijuan Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands Department of Mathematics University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8503 Japan

Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a similarity comparison task. Nodes with similar embedding vectors are more likely to be connected. Classic network embedding algorithms are random-walk-based. They sample trajectory paths via random walks and generate node pairs from the trajectory paths. The node pair set is further used as the input for a Skip-Gram model, a representative language model that embeds nodes (which are regarded as words) into vectors. In the present study, we propose to replace random walk processes by a spreading process, namely the susceptible-infected (SI) model, to sample paths. Specifically, we propose two SI-spreading-based algorithms, SINE and TSINE, to embed static and temporal networks, respectively. The performance of our algorithms is evaluated by the missing link prediction task in comparison with state-of-the-art static and temporal network embedding algorithms. Results show that SINE and TSINE outperform the baselines across all six empirical datasets. We further find that the performance of SINE is mostly better than TSINE, suggesting that temporal information does not necessarily improve the embedding for missing link prediction. Moreover, we study the effect of the sampling size, quantified as the total length of the trajectory paths, on the performance of the embedding algorithms. The better performance of SINE and TSINE requires a smaller sampling size in comparison with the baseline algorithms. Hence, SI-spreading-based embedding tends to be more applicable to large-scale networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Network embeddings

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Variational Benchmarks for Quantum Many-Body Problems

arXiv

引用

arXiv 2023年

作者： Wu, Dian Rossi, Riccardo Vicentini, Filippo Astrakhantsev, Nikita Becca, Federico Cao, Xiaodong Carrasquilla, Juan Ferrari, Francesco Georges, Antoine Hibat-Allah, Mohamed Imada, Masatoshi Läuchli, Andreas M. Mazzola, Guglielmo Mezzacapo, Antonio Millis, Andrew Moreno, Javier Robledo Neupert, Titus Nomura, Yusuke Nys, Jannes Parcollet, Olivier Pohle, Rico Romero, Imelda Schmid, Michael Silvester, J. Maxwell Sorella, Sandro Tocchio, Luca F. Wang, Lei White, Steven R. Wietek, Alexander Yang, Qi Yang, Yiqi Zhang, Shiwei Carleo, Giuseppe LausanneCH-1015 Switzerland LausanneCH-1015 Switzerland ParisF-75005 France CPHT CNRS École Polytechnique Institut Polytechnique de Paris PalaiseauF-91128 France Collège de France Université PSL ParisF-75005 France Department of Physics University of Zurich ZurichCH-8057 Switzerland Dipartimento di Fisica Università di Trieste TriesteI-34151 Italy Center for Computational Quantum Physics Flatiron Institute New YorkNY10010 United States Vector Institute MaRS Centre TorontoONM5G 1M1 Canada Institute for Theoretical Physics ETH Zürich ZurichCH-8093 Switzerland Institut für Theoretische Physik Goethe-Universität Frankfurt am Main60438 Germany Department of Quantum Matter Physics Université de Genève GenevaCH-1211 Switzerland Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Department of Applied Mathematics University of Waterloo WaterlooONN2L 3G1 Canada Toyota Physical and Chemical Research Institute Aichi Nagakute480-1192 Japan Waseda Research Institute for Science and Engineering Waseda University Shinjuku-ku Tokyo169-8555 Japan Physics Division Sophia University Chiyoda-ku Tokyo102-8554 Japan Department of Applied Physics University of Tokyo Bunkyo-ku Tokyo113-8656 Japan Laboratory for Theoretical and Computational Physics Paul Scherrer Institute VilligenCH-5232 Switzerland Institute for Computational Science University of Zurich ZurichCH-8057 Switzerland IBM Quantum T. J. Watson Research Center Yorktown HeightsNY10598 United States Department of Physics Columbia University New YorkNY10027 United States Center for Quantum Phenomena Department of Physics New York University New YorkNY10003 United States Department of Applied Physics and Physico-Informatics Keio University Kohoku-ku Yokohama223-8522 Japan Institute for Materials Research Tohoku University Aoba-ku Sendai980-8577 Japan Université Pa

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this work, we introduce a metric of variational accuracy, the V-score, obtained from the variational energy and its variance. We provide an extensive curated dataset of variational calculations of many-body quantum systems, identifying cases where state-of-the-art numerical approaches show limited accuracy, and future algorithms or computational platforms, such as quantum computing, could provide improved accuracy. The V-score can be used as a metric to assess the progress of quantum variational methods toward a quantum advantage for ground-state problems, especially in regimes where classical verifiability is impossible. Copyright © 2023, The Authors. All rights reserved.

关键词： Ground state

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MRT discrete boltzmann modeling of multicomponent mixture with nonequilibrium effects

arXiv

引用

arXiv 2020年

作者： Lin, Chuandong Luo, Kai H. Xu, Aiguo Gan, Yanbiao Lai, Huilin Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen University Zhuhai519082 China Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Energy and Power Engineering Tsinghua University Beijing100084 China Department of Mechanical Engineering University College London Torrington Place LondonWC1E 7JE United Kingdom Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics P. O. Box 8009-26 Beijing100088 China State Key Laboratory of Explosion Science and Technology Beijing Institute of Technology Beijing100081 China Center for Applied Physics and Technology MOE Key Center for High Energy Density Physics Simulations College of Engineering Peking University Beijing100871 China North China Institute of Aerospace Engineering Langfang065000 China College of Mathematics and Informatics FJKLMAA Fujian Normal University Fuzhou350007 China

A multiple-relaxation-time discrete Boltzmann model (DBM) is proposed for multicomponent mixtures, where compressible, hydrodynamic, and thermodynamic nonequilibrium effects are taken into account. It allows the specific heat ratio and the Prandtl number to be adjustable, and is suitable for both low and high speed fluid flows. From the physical side, besides being consistent with the multicomponent Navier-Stokes equations, Fick's law and Stefan-Maxwell diffusion equation in the hydrodynamic limit, the DBM provides more kinetic information about the nonequilibrium effects. The physical capability of DBM to describe the nonequilibrium flows, beyond the Navier-Stokes representation, enables the study of the entropy production mechanism in complex flows, especially in multicomponent mixtures. Moreover, the current kinetic model is employed to investigate the compressible nonequilibrium Kelvin-Helmholtz instability (KHI). It is found that, in the dynamic KHI process, the mixing degree and fluid flow are similar for cases with various thermal conductivity and initial temperature configurations. Physically, both heat conduction and temperature exert slight influences on the formation and evolution of the KHI. Copyright © 2020, The Authors. All rights reserved.

关键词： Heat conduction

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Detecting anomalous citation groups in journal networks

arXiv

引用

arXiv 2020年

作者： Kojaku, Sadamori Livan, Giacomo Masuda, Naoki Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Computer Science University College London LondonWC1E 6EA United Kingdom Systemic Risk Centre London School of Economics and Political Science LondonWC2A 2AE United Kingdom Department of Mathematics University at Buffalo State University of New York BuffaloNY United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-2900 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact factors leads some journals to artificially boost impact factors through the coordinated effort of a "citation cartel" of journals. "Citation cartel" behavior has become increasingly common in recent years, with several instances being reported. Here, we propose an algorithm—-named CIDRE—to detect anomalous groups of journals that exchange citations at excessively high rates when compared against a null model that accounts for scientific communities and journal size. CIDRE detects more than half of the journals suspended from Journal Citation Reports due to anomalous citation behavior in the year of suspension or in advance. Furthermore, CIDRE detects many new anomalous groups, where the impact factors of the member journals are lifted substantially higher by the citations from other member journals. We describe a number of such examples in detail and discuss the implications of our findings with regard to the current academic climate. Copyright © 2020, The Authors. All rights reserved.

关键词： Publishing

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The SCUBA-2 Large eXtragalactic Survey: 850 μm map, catalogue and the bright-end number counts of the XMM-LSS field

arXiv

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arXiv 2023年

作者： Garratt, T.K. Geach, J.E. Tamura, Y. Coppin, K.E.K. Franco, M. Ao, Y. Chen, C.-C. Cheng, C. Clements, D.L. Dai, Y.S. Dannerbauer, H. Greve, T.R. Hatsukade, B. Hwang, H.S. Jiang, L. Kohno, K. Koprowski, M.P. Michalowski, M.J. Sawicki, M. Scott, D. Shim, H. Takeuchi, T.T. Wang, W.-H. Xue, Y.Q. Yang, C. Centre for Astrophysics Research University of Hertfordshire HatfieldAL10 9AB United Kingdom Division of Particle and Astrophysical Science Nagoya University Aichi Nagoya464-8602 Japan Purple Mountain Observatory Key Laboratory for Radio Astronomy Chinese Academy of Sciences 10 Yuanhua Road Nanjing210023 China School of Astronomy and Space Science University of Science and Technology of China Anhui Hefei230026 China Academia Sinica Institute of Astronomy and Astrophysics No. 1 Section 4 Roosevelt Road Taipei10617 Taiwan Chinese Academy of Sciences South America Center for Astronomy National Astronomical Observatories CAS Beijing100101 China Imperial College London Blackett Lab Prince Consort Road LondonSW7 2AZ United Kingdom National Astronomical Observatories Chinese Academy of Sciences 20A Datun RoadChaoyang District Beijing100101 China Tenerife La LagunaE-38205 Spain Universidad de La Laguna Dpto. Astrofísica Tenerife La LagunaE-38206 Spain National Space Institute DTU Space Technical University of Denmark Elektrovej 327 Kgs. LyngbyDK-2800 Denmark Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom Institute of Astronomy Graduate School of Science The University of Tokyo 2-21-1 Osawa Tokyo Mitaka181-0015 Japan Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Center Astronomy Program Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Kavli Institute for Astronomy and Astrophysics Peking University No. 5 Yiheyuan Road Haidian District Beijing100871 China Institute of Astronomy Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziadzka 5 Torun87-100 Poland Astronomical Observatory Institute Faculty of Physics Adam Mickiewicz University ul. Sloneczna 36 Poznań60-286 Poland Department of Astronomy and P

We present 850 μm imaging of the XMM-LSS field observed for 170 hours as part of the James Clerk Maxwell Telescope SCUBA-2 Large eXtragalactic Survey (S2LXS). S2LXS XMM-LSS maps an area of 9 deg2, reaching a moderate depth of 1σ 4 mJy beam−1. This is the largest contiguous area of extragalactic sky mapped by JCMT at 850 μm to date. The wide area of the S2LXS XMM-LSS survey allows us to probe the ultra-bright (S850μm & 15 mJy), yet rare submillimetre population. We present the S2LXS XMM-LSS catalogue, which comprises 40 sources detected at >5σ significance, with deboosted flux densities in the range of 7 mJy to 48 mJy. We robustly measure the bright-end of the 850 μm number counts at flux densities >7 mJy, reducing the Poisson errors compared to existing measurements. The S2LXS XMM-LSS observed number counts show the characteristic upturn at bright fluxes, expected to be motivated by local sources of submillimetre emission and high-redshift strongly lensed galaxies. We find that the observed 850 μm number counts are best reproduced by model predictions that include either strong lensing or source blending from a 15 arcsec beam, indicating that both may make an important contribution to the observed over-abundance of bright single dish 850 μm selected sources. We make the S2LXS XMM-LSS 850 μm map and >5σ catalogue presented here publicly available. Copyright © 2023, The Authors. All rights reserved.

关键词： Blending

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An Information Theory Approach on Deciding Spectroscopic Follow Ups

arXiv

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arXiv 2019年

作者： Astudillo, Javiera Protopapas, Pavlos Pichara, Karim Huijse, Pablo Computer Science Department School of Engineering Pontificia Universidad Católica de Chile Institute for Applied Computational Science Harvard University CambridgeMA United States Millennium Institute of Astrophysics Chile Informatics Institute Universidad Austral de Chile Valdivia Chile

Classification and characterization of variable phenomena and transient phenomena are critical for astrophysics and cosmology. These objects are commonly studied using photometric time series or spectroscopic data. Given that many ongoing and future surveys are in time-domain and given that adding spectra provide further insights but requires more observational resources, it would be valuable to know which objects should we prioritize to have spectrum in addition to time series. We propose a methodology in a probabilistic setting that determines a-priory which objects are worth taking spectrum to obtain better insights, where we focus insight as the type of the object \(classification\). Objects for which we query its spectrum are reclassified using their full spectrum information. We first train two classifiers, one that uses photometric data and another that uses photometric and spectroscopic data together. Then for each photometric object we estimate the probability of each possible spectrum outcome. We combine these models in various probabilistic frameworks \(strategies\) which are used to guide the selection of follow up observations. The best strategy depends on the intended use, whether it is getting more confidence or accuracy. For a given number of candidate objects \(127, equal to 5% of the dataset\) for taking spectra, we improve 37% class prediction accuracy as opposed to 20% of a non-naive \(non-random\) best base-line strategy. Our approach provides a general framework for follow-up strategies and can be extended beyond classification and to include other forms of follow-ups beyond spectroscopy. Copyright © 2019, The Authors. All rights reserved.

关键词： Spectroscopic analysis

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Stable isotope analysis of western Lake Superior predatory fishes, part two: prey source contributions

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Journal of Great Lakes Research 2025年

作者： Jessica Hanson Morgann Gordon Nick Peterson Ryan Lepak Cory Goldsworthy Valerie Brady Thomas Hrabik Joel Hoffman University of Minnesota Duluth Swenson College of Science and Engineering Integrated Biological Sciences Master’s Program 1035 Kirby Drive Duluth MN 55812 USA Oak Ridge Associated Universities U.S. EPA Office of Research and Development Center for Computational Toxicology and Exposure Great Lakes Toxicology and Ecology Division 6201 Congdon Blvd Duluth MN 55804 USA Minnesota Department of Natural Resources Lake Superior Areas Fisheries 5351 North Shore Drive Duluth MN 55804 USA U.S. Environmental Protection Agency Center for Computational Toxicology and Exposure Great Lakes Toxicology and Ecology Division 6201 Congdon Blvd. Duluth MN 55804 USA Natural Resources Research Institute 5013 Miller Trunk Hwy Hermantown MN 55811 USA University of Minnesota Duluth Swenson College of Science and Engineering 1035 Kirby Drive Duluth MN 55812 USA

Niche partitioning of time, space, or resources facilitates the coexistence of competitor species. The Lake Superior food web includes several piscivores that are important to fisheries, including native lake trout ( Salvelinus namaycush, both lean and siscowet morphotypes) and walleye ( Sander vitreus ), and introduced Chinook salmon ( Oncorhynchus tshawytscha ), coho salmon ( Oncorhynchus kisutch ), pink salmon ( Oncorhynchus gorbuscha ), brown trout ( Salmo trutta ), and rainbow trout ( Oncorhynchus mykiss ). Here we quantify specific prey source contributions to these predators in the western arm of Lake Superior using dual stable isotope mixing models based on carbon and nitrogen stable isotope ratios. For each species, three mixing models were constructed to examine predator size effect: one with all fish sampled, one with the 10 smallest fish sampled, and one with the 10 largest fish sampled. We found that native and introduced species had distinct diets from one another; siscowet lake trout primarily relied on burbot ( Lota lota ) and invasive rainbow smelt ( Osmerus mordax ), native lean lake trout and walleye both relied on invasive rainbow smelt, and introduced salmonids relied on native invertebrates Mysis diluviana and Diporeia spp. Additionally, siscowet lake trout, lean lake trout, Chinook salmon, and coho salmon exhibited size-based shifts in prey contributions. The low piscivory in introduced salmonids and high reliance of native predators on invasive rainbow smelt is likely due to low abundance of cisco ( Coregonus artedi ). Our study reveals complex, potentially adaptive responses of both native and introduced nearshore predators to both native and invasive prey resources in Lake Superior.

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