检索结果-内蒙古大学图书馆

research on 3D Printing layered Algorithm based on FDM technology

Journal of Physics: Conference Series 2021年第1期1798卷

作者： Hongwei Jia Wei Xu East China University of Technology Economic Development Zone Guanglan Avenue 418 Nanchang330013 China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System Economic Development Zone Guanglan Avenue 418 Nanchang330013 China

Fused deposition forming (FDM) is the most mature 3D printing technology, which has been widely used in many fields of our daily life, science and technology, and economic *** the molding process of the model, how to choose the appropriate layering method has become the key point to improve the precision and efficiency of 3D printing. Based on adaptive layered algorithm was studied, using three-dimensional modeling software of entity modeling, the introduction of the z axis curve contour curve is determined, and then segment, find out each section contour tangent to the curve, calculated the contour tangent with the model the Angle between the positive direction, an analysis model of layer thickness;The lamination thickness of the model is calculated by using probability statistics, summation superposition and other mathematical *** has proved that the adaptive layering method is clear in process and simple in calculation, which reduces the workload of layering to a certain extent and improves the precision and efficiency of 3D printing molding.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Visualization research of STL Model Based on OpenGL technology

引用

Journal of Physics: Conference Series 2020年第1期1437卷

作者： Wei Xu Hongwei Jia East China University of Technology Economic Development Zone Guanglan Avenue 418 Nanchang330013 China Jiangxi Engineering Technology Research Center of Nuclear Geoscience Data Science and System Economic Development Zone Guanglan Avenue 418 Nanchang330013 China

With the OpenGL visualization as the background, some important attributes in the OpenGL application data table are processed by using the STL model visualization method. According to the advantages and disadvantages of OpenGL technology, it is rationally optimized. According to the computer display mode, the scale of visual graphics is designed. The OpenGL visualization data and the OpenGL STL model visualization method are reasonably combined, and the corresponding human-computer interaction technology is applied, which allows the user to customize the data according to the task goals.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Theoretical Quantification of Secondary Electron Emission from Silicon

SSRN

引用

SSRN 2023年

作者： Khan, Muhammad Saadat Shakoor Mao, Shifeng Zou, Yanbo Lu, Dabao Da, Bo Li, Yonggang Ding, Zejun Department of Physics University of Science and Technology of China Anhui Hefei230026 China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Anhui Hefei230026 China Department of Nuclear Science and Engineering University of Science and Technology of China Anhui Hefei230026 China School of Physics and Electronic Engineering Xinjiang Normal University Xinjiang Urumchi830054 China Microscope Science and Technology Limited Anhui Hefei230093 China Research and Services Division of Materials Data and Integrated System National Institute for Materials Science 1-1 Namiki Ibaraki Tsukuba305-0044 Japan Research Center for Advanced Measurement and Characterization National Institute for Materials Science 1-2-1 Sengen Ibaraki Tsukuba305-0047 Japan Key Laboratory of Materials Physics Insititute of Solid State Physics Chinese Academy of Sciences Anhui Hefei230031 China

Though intensive experimental studies have been carried out on electron emission properties in past decades, the reliable data from accurate experimental measurements for clean and smooth surfaces are still quite limited. In this work, we have performed a comprehensive Monte Carlo simulation of electron emission yields, the secondary electron yield (SEY,δ), backscattered electron coefficient (BSC,η) and total electron yield (TEY,σ=δ+η), from silicon and the uncertainty quantification of the theoretical calculation results for the first time. The considered uncertainty factors in the physical modelling include work function data, optical energy loss function data, dielectric function models for electron inelastic scattering and the scattering potentials for electron elastic scattering. The calculation results show that δ is significantly influenced by the work function while the dielectric function model has a slight effect. Elastic scattering potential and energy loss function affects both δ and η. Our simulatedσ η data agree with most of the experimental measurements while the simulated mean σ data are well below most of the experimental data. The experimental σ data measured by Goto lie within the uncertainty range of our simulation results. This work has provided sufficient ground for the necessity of building a theoretical database of electron emission yield. © 2023, The Authors. All rights reserved.

关键词： Silicon

来源：评论

学校读者我要写书评

暂无评论

Ultrahigh-pressure form of SiO2 glass with dense pyrite-type crystalline homology

引用

Physical Review B 2019年第4期99卷 045153-045153页

作者： M. Murakami S. Kohara N. Kitamura J. Akola H. Inoue A. Hirata Y. Hiraoka Y. Onodera I. Obayashi J. Kalikka N. Hirao T. Musso A. S. Foster Y. Idemoto O. Sakata Y. Ohishi Department of Earth Sciences ETH Zürich Zürich 8092 Switzerland Department of Earth and Planetary Materials Science Tohoku University Sendai 980-8578 Japan Research Center for Advanced Measurement and Characterization National Institute for Materials Science (NIMS) Hyogo 679-5148 Japan Center for Materials research by Information Integration (CMI2) Research and Services Division of Materials Data and Integrated System (MaDIS) NIMS Ibaraki 305-0047 Japan Research and Utilization Division Japan Synchrotron Radiation Research Institute Hyogo 679-5198 Japan School of Materials Science Japan Advanced Institute of Science and Technology Ishikawa 923-1211 Japan PRESTO Japan Science and Technology Agency Tokyo 102-0076 Japan Department of Pure and Applied Chemistry Faculty of Science and Technology Tokyo University of Science Chiba 278-8510 Japan Department of Physics Tampere University of Technology FI-33101 Tampere Finland Department of Physics Norwegian University of Science and Technology NO-7481 Trondheim Norway Institute of Industrial Science The University of Tokyo Tokyo 153-8505 Japan Graduate School of Fundamental Science and Engineering Waseda University Tokyo 169-8555 Japan Kagami Memorial Research Institute for Materials Science and Technology Waseda University Tokyo 169-0051 Japan Mathematics for Advanced Materials-OIL AIST Sendai 980-8577 Japan WPI Advanced Institute for Materials Research Tohoku University Sendai 980-8577 Japan Kyoto University Institute for Advanced Study Kyoto University Kyoto 606-8501 Japan Center for Advanced Intelligence Project RIKEN Tokyo 103-0027 Japan Institute for Integrated Radiation and Nuclear Science Kyoto University Osaka 590-0494 Japan Department of Applied Physics Aalto University FI-00076 Aalto Finland Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kanazawa 920-1192 Japan

High-pressure synthesis of denser glass has been a longstanding interest in condensed-matter physics and materials science because of its potentially broad industrial application. Nevertheless, understanding its nature under extreme pressures has yet to be clarified due to experimental and theoretical challenges. Here we reveal the formation of OSi4 tetraclusters associated with that of SiO7 polyhedra in SiO2 glass under ultrahigh pressures to 200 gigapascal confirmed both experimentally and theoretically. Persistent homology analyses with molecular dynamics simulations found increased packing fraction of atoms whose topological diagram at ultrahigh pressures is similar to a pyrite-type crystalline phase, although the formation of tetraclusters is prohibited in the crystalline phase. This critical difference would be caused by the potential structural tolerance in the glass for distortion of oxygen clusters. Furthermore, an expanded electronic band gap demonstrates that chemical bonds survive at ultrahigh pressure. This opens up the synthesis of topologically disordered dense oxide glasses.

关键词： Chemical bonding Density of states Electronic structure Phase transitions Pressure effects Specific phase transitions Structural properties Topological phase transition Topological phases of matter Density functional theory Molecular dynamics Wannier function methods X-ray diffraction X-ray powder diffraction

来源：评论

学校读者我要写书评

暂无评论

Correlation-aware Cross-modal Attention Network for Fashion Compatibility Modeling in UGC systems

引用

ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Kai Cui Shenghao Liu Wei Feng Xianjun Deng Liangbin Gao Minmin Cheng Hongwei Lu Laurence T. Yang Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China China Nuclear Power Operation Technology Corporation Ltd. China

Empowered by the continuous integration of social multimedia and artificial intelligence, the application scenarios of information retrieval (IR) progressively tend to be diversified and personalized. Currently, User-Generated Content (UGC) systems have great potential to handle the interactions between large-scale users and massive media contents. As an emerging multimedia IR, Fashion Compatibility Modeling (FCM) aims to predict the matching degree of each given outfit and provide complementary item recommendation for user queries. Although existing studies attempt to explore the FCM task from a multimodal perspective with promising progress, they still fail to fully leverage the interactions between multimodal information or ignore the item-item contextual connectivities of intra-outfit. In this paper, a novel fashion compatibility modeling scheme is proposed based on Correlation-aware Cross-modal Attention Network. To better tackle these issues, our work mainly focuses on enhancing comprehensive multimodal representations of fashion items by integrating the cross-modal collaborative contents and uncovering the contextual correlations. Since the multimodal information of fashion items can deliver various semantic clues from multiple aspects, a modality-driven collaborative learning module is presented to explicitly model the interactions of modal consistency and complementarity via a co-attention mechanism. Considering the rich connections among numerous items in each outfit as contextual cues, a correlation-aware information aggregation module is further designed to adaptively capture significant intra-correlations of item-item for characterizing the content-aware outfit representations. Experiments conducted on two real-world fashion datasets demonstrate the superiority of our approach over state-of-the-art methods.

关键词： User-Generated Contents fashion intelligent analysis complementary compatibility modeling multimodal representation learning correlation-aware integration strategy

来源：评论

学校读者我要写书评

暂无评论

INTRODUCTION

引用

Bulletin of the American Meteorological Society 2024年第8期105卷 S1-S11页

作者： Boyer, T. Blunden, J. Dunn, R.J.H. NOAA/NESDIS National Centers for Environmental Information Silver Spring Maryland NOAA/NESDIS National Centers for Environmental Information Asheville North Carolina Met Office Hadley Centre Exeter United Kingdom European Centre for Medium-Range Weather Forecasts Reading United Kingdom University of Maryland College Park Maryland Scripps Institution of Oceanography University of California San Diego La Jolla California NOAA/NWS National Centers for Environmental Prediction Climate Prediction Center College Park Maryland Brandenburg University of Technology (BTU) Cottbus-Senftenberg Germany Servicio Meteorológico Nacional Buenos Aires Argentina NOAA/OAR Physical Sciences Laboratory Boulder Colorado European Centre for Medium-Range Weather Forecasts Bonn Germany Center for Geophysical Research and School of Physics University of Costa Rica San José Costa Rica Department of Meteorology and National Centre for Earth Observation University of Reading Reading United Kingdom Centro Nacional de Monitoramento e Alertas de Desastres Naturais CEMADEN São Paulo Brazil Université Grenoble Alpes Institut des Géosciences de l’Environnement IRD CNRS Grenoble INP Grenoble France Hampton University Hampton Virginia Seychelles Meteorological Authority Mahe Seychelles Section for Glaciers Ice and Snow Norwegian Water Resources and Energy Directorate Oslo Norway National Research Institute for Agriculture Food and Environment (INRAE) CARRTEL Université Savoie Mont Blanc Thonon les Bains France Graduate School of Agriculture Osaka Metropolitan University Sakai Japan Science Faculty Universidad Nacional de Colombia Bogotá Colombia University of Bremen Bremen Germany NOAA Global Monitoring Laboratory Boulder Colorado Servicio Nacional de Meteorología e Hidrología del Perú Lima Perú Centro de Investigaciones sobre Desertificación – Spanish National Research Council (CSIC-UV-GVA) Valencia Spain Hydro-Climate Extremes Lab (H-CEL) Ghent University Ghent Belgium Department o

In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. A

关键词：

来源：评论

学校读者我要写书评

暂无评论

New evaluations of heavy nuclide data for JENDL-3.3

引用

Journal of nuclear science and technology 2002年 39卷 108-111页

作者： Kawano, Toshihiko Matsunobu, Hiroyuki Murata, Toru Zukeran, Atsushi Nakajima, Yutaka Kawai, Masayoshi Yoshida, Tadashi Ohsawa, Takaaki Shibata, Keiichi Nakagawa, Tsuneo Iwamoto, Osamu Baba, Mamoru Ishikawa, Makoto Department of Advanced Energy Engineering Science Kyushu University Kasuga 816-8580 6-1 Kasuga-kouen Japan Data Engineering Inc. Fujisawa 251-0038 5-13-21 Matsu-ga-oka Japan AITEL Corporation Tokyo 105-1106 1-5-9 Shiba Japan Power and Industrial System R and D Laboratory Hitachi 319-1221 Hitachi Ltd. 7-2-1 Omika Japan Research Organization for Information Science and Technology Tokai-mura 319-1106 Ibaraki Japan High Energy Accelerator Research Organization Tsukuba 305-0801 Oho Japan Faculty of Engineering Musashi Institute of Technology Tokyo 158-8557 1-28-1 Tamatsutsumi Japan Department of Nuclear Engineering Kinki University Higashi-Osaka 577-8502 Kowakae Japan Japan Atomic Energy Research Institute Tokai-mura 319-1195 Ibaraki Japan Cyclotron and Radioisotope Center Tohoku University Sendai 980-8578 Aoba-ku Japan Japan Nuclear Cycle Development Institute O-arai-machi 311-1393 Ibaraki Japan

New evaluations of nuclear data for Uranium, Plutonium, and Thorium isotopes which are essential for applications to nuclear technology were carried out for the Japanese Evaluated nuclear data Library, JENDL-3.3. The objectives of the current release of JENDL were to fix several problems which have been reported for the previous version, to improve the accuracy of the data, and to evaluate covariances for the important nuclides. Quantities in JENDL-3.2 were extensively re-evaluated or replaced by more reliable values. The heavy nuclide data in JENDL-3.3 were validated with several benchmark tests, and it was reported that the current release gave a good prediction of criticalities. © 2014 Atomic Energy Society of Japan.

关键词： Covariance Cross section Direct/semidirect capture Evaluation JENDL-3.3 Neutron Plutonium Prompt fission neutron spectrum Simultaneous evaluation Thorium Uranium

来源：评论

学校读者我要写书评

暂无评论

Analysis of more than 400,000 women provides case-control evidence for BRCA1 and BRCA2 variant classification

引用

Nature Communications 2025年第1期16卷 1-18页

作者： Maria Zanti Denise G. O’Mahony Kristia Yiangou Kyriaki Michailidou Michael T. Parsons Amanda B. Spurdle Leila Dorling Joe Dennis Marc Naven Antonis C. Antoniou Manjeet K. Bolla Qin Wang Douglas F. Easton Nicholas J. Boddicker Wenan Chen Chunling Hu Steven N. Hart Fergus J. Couch Thomas U. Ahearn Jonine D. Figueroa Montserrat García-Closas Christine B. Ambrosone Song Yao Irene L. Andrulis Gord Glendon Paul L. Auer Caroline Baynes Don M. Conroy Alison M. Dunning Craig Luccarini Clara Bodelon James M. Hodge Alpa V. Patel Lauren R. Teras Natalia V. Bogdanova Stig E. Bojesen Kristen D. Brantley Nicola J. Camp Archie Campbell Jose E. Castelao Melissa H. Cessna Jenny Chang-Claude Fei Chen Christopher A. Haiman Georgia Chenevix-Trench Kamila Czene Arcangela De Nicolo Susan M. Domchek Katherine L. Nathanson Thilo Dörk A. Heather Eliassen D. Gareth Evans Peter A. Fasching Henrik Flyger Manuela Gago-Dominguez Anna González-Neira Rocio Nuñez-Torres Felix Grassmann Andreas Hadjisavvas Mihalis I. Panayiotidis Ute Hamann Muhammad U. Rashid Diana Torres Mikael B. A. Hartman Weang-Kee Ho Reiner Hoppe Sacha J. Howell Anna Jakubowska Elza K. Khusnutdinova Yon-Dschun Ko Peter Kraft Vessela N. Kristensen James V. Lacey Jingmei Li Geok Hoon Lim Veronique Kiak-Mien Tan Sara Lindström Artitaya Lophatananon Kenneth Muir Arto Mannermaa Maria Elena Martinez Dimitrios Mavroudis Roger L. Milne Melissa C. Southey Nadia Obi Janet E. Olson Celine M. Vachon Julie R. Palmer Gary R. Zirpoli Paul D. P. Pharoah Eric C. Polley Kathryn J. Ruddy Siddhartha Yadav Emmanouil Saloustros Elinor J. Sawyer Marjanka K. Schmidt Soo Hwang Teo Amy Trentham-Dietz Thérèse Truong Jeffrey N. Weitzel Melissa S. Cline Peter Devilee Sean V. Tavtigian David E. Goldgar Biostatistics Unit The Cyprus Institute of Neurology & Genetics Nicosia Cyprus Department of Medical Genetics Oslo University Hospital Oslo Norway Population Health Program QIMR Berghofer Medical Research Institute Brisbane Queensland Australia Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care University of Cambridge Cambridge UK Centre for Cancer Genetic Epidemiology Department of Oncology University of Cambridge Cambridge UK Department of Quantitative Health Sciences Division of Computational Biology Mayo Clinic Rochester MN USA Department of Laboratory Medicine and Pathology Mayo Clinic Rochester MN USA Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Department of Health and Human Services Bethesda MD USA Usher Institute of Population Health Sciences and Informatics The University of Edinburgh Edinburgh UK Cancer Research UK Edinburgh Centre The University of Edinburgh Edinburgh UK Department of Cancer Prevention and Control Roswell Park Comprehensive Cancer Institute Buffalo NY USA Fred A. Litwin Center for Cancer Genetics Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Toronto Ontario Canada Department of Molecular Genetics University of Toronto Toronto Ontario Canada Division of Biostatistics Data Science Institute and Cancer Center Medical College of Wisconsin Milwaukee WI USA Department of Population Science American Cancer Society Atlanta GA USA Radiation Oncology Research Unit Hannover Medical School Hannover Germany Copenhagen General Population Study Herlev and Gentofte Hospital Copenhagen University Hospital Herlev Denmark Department of Clinical Biochemistry Herlev and Gentofte Hospital Copenhagen University Hospital Herlev Denmark Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Internal Medicine and Hu

Clinical genetic testing identifies variants causal for hereditary cancer, information that is used for risk assessment and clinical management. Unfortunately, some variants identified are of uncertain clinical significance (VUS), complicating patient management. Case-control data is one evidence type used to classify VUS. As an initiative of the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) Analytical Working Group we analyze germline sequencing data ofBRCA1andBRCA2from 96,691 female breast cancer cases and 302,116 controls from three studies: the BRIDGES study of the Breast Cancer Association Consortium, the Cancer Risk Estimates Related to Susceptibility consortium, and the UK Biobank. We observe 11,207BRCA1andBRCA2variants, with 6909 being coding, covering 23.4% ofBRCA1andBRCA2VUS in ClinVar and 19.2% of ClinVar curated (likely) benign or pathogenic variants. Case-control likelihood ratio (ccLR) evidence is highly consistent with ClinVar assertions for (likely) benign or pathogenic variants; exhibiting 99.1% sensitivity and 95.3% specificity forBRCA1and 93.3% sensitivity and 86.6% specificity forBRCA2. This approach provides case-control evidence for 787 unclassified variants; these include 579 with strong or moderate benign evidence and 10 with strong pathogenic evidence for which ccLR evidence is sufficient to alter clinical classification.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

arXiv

引用

arXiv 2018年

作者： Maier-Hein, Lena Eisenmann, Matthias Reinke, Annika Onogur, Sinan Stankovic, Marko Scholz, Patrick Arbel, Tal Bogunovic, Hrvoje Bradley, Andrew P. Carass, Aaron Carolin Feldmann Frangi, Alejandro F. Ful, Peter M. van Ginneken, Bram Hanbury, Allan Honauer, Katrin Kozubek, Michal Landman, Bennett A. Marz, Keno Maier, Oskar Maier-Hein, Klaus Menze, Bjoern H. Müller, Henning Neher, Peter F. Niessen, Wiro Rajpoot, Nasir Sharp, Gregory C. Sirinukunwattana, Korsuk Speidel, Stefanie Stock, Christian Stoyanov, Danail Taha, Abdel Aziz van der Sommen, Fons Wang, Ching-Wei Weber, Marc-André Zheng, Guoyan Jannin, Pierre Kopp-Schneider, Annette Heidelberg Germany Centre for Intelligent Machines McGill University MontrealQC Canada Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna Vienna Austria Science and Engineering Faculty Queensland University of Technology BrisbaneQLD Australia Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore United States CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine University of Sheffield Sheffield United Kingdom Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center Nijmegen Netherlands Institute of Information Systems Engineering TU Wien Vienna Austria Heidelberg University Heidelberg Germany Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Electrical Engineering Vanderbilt University NashvilleTN United States Institute of Medical Informatics Universität zu Lübeck Lübeck Germany Heidelberg Germany Institute for Advanced Studies Department of Informatics Technical University of Munich Munich Germany Information System Institute HES-SO Sierre Switzerland Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC Rotterdam Netherlands Department of Computer Science University of Warwick Coventry United Kingdom Department of Radiation Oncology Massachusetts General Hospital BostonMA United States Institute of Biomedical Engineering University of Oxford Oxford United Kingdom National Center for Tumor Diseases Dresden Dresden Germany Heidelberg Germany Department of Computer Science University College London London United Kingdom Data Science Studio Research Studios Austria FG Vienna Austria Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands AIExplore NTUST Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering National Ta

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Quality control

来源：评论

学校读者我要写书评

暂无评论

A global multiproxy database for temperature reconstructions of the Common Era

引用

Scientific data 2017年第1期4卷 170088-170120页

作者： Emile-Geay, Julien McKay, Nicholas P. Kaufman, Darrell S. Von Gunten, Lucien Wang, Jianghao Anchukaitis, Kevin J. Abram, Nerilie J. Addison, Jason A. Curran, Mark A.J. Evans, Michael N. Henley, Benjamin J. Hao, Zhixin Martrat, Belen McGregor, Helen V. Neukom, Raphael Pederson, Gregory T. Stenni, Barbara Thirumalai, Kaustubh Werner, Johannes P. Xu, Chenxi Divine, Dmitry V. Dixon, Bronwyn C. Gergis, Joelle Mundo, Ignacio A. Nakatsuka, Takeshi Phipps, Steven J. Routson, Cody C. Steig, Eric J. Tierney, Jessica E. Tyler, Jonathan J. Allen, Kathryn J. Bertler, Nancy A.N. Björklund, Jesper Chase, Brian M. Chen, Min-Te Cook, Ed De Jong, Rixt DeLong, Kristine L. Dixon, Daniel A. Ekaykin, Alexey A. Ersek, Vasile Filipsson, Helena L. Francus, Pierre Freund, Mandy B. Frezzotti, Massimo Gaire, Narayan P. Gajewski, Konrad Ge, Quansheng Goosse, Hugues Gornostaeva, Anastasia Grosjean, Martin Horiuchi, Kazuho Hormes, Anne Husum, Katrine Isaksson, Elisabeth Kandasamy, Selvaraj Kawamura, Kenji Kilbourne, K. Halimeda Koç, Nalan Leduc, Guillaume Linderholm, Hans W. Lorrey, Andrew M. Mikhalenko, Vladimir Mortyn, P. Graham Motoyama, Hideaki Moy, Andrew D. Mulvaney, Robert Munz, Philipp M. Nash, David J. Oerter, Hans Opel, Thomas Orsi, Anais J. Ovchinnikov, Dmitriy V. Porter, Trevor J. Roop, Heidi A. Saenger, Casey Sano, Masaki Sauchyn, David Saunders, Krystyna M. Seidenkrantz, Marit-Solveig Severi, Mirko Shao, Xuemei Sicre, Marie-Alexandrine Sigl, Michael Sinclair, Kate St George, Scott St Jacques, Jeannine-Marie Thamban, Meloth Thapa, Udya Kuwar Thomas, Elizabeth R. Turney, Chris Uemura, Ryu Viau, Andre E. Vladimirova, Diana O. Wahl, Eugene R. White, James W.C. Yu, Zicheng Zinke, Jens Department of Earth Sciences Center for Applied Mathematical Sciences University of Southern California Los Angeles 90089 CA United States School of Earth Sciences and Environmental Sustainability Northern Arizona University Flagstaff 86001 AZ United States PAGES International Project Office Bern 3012 Switzerland Mathworks Inc. Natick 01760 MA United States School of Geography and Development Laboratory of Tree Ring Research University of Arizona Tucson 85721 AZ United States Research School of Earth Sciences ARC Centre of Excellence for Climate System Science Australian National University Canberra 2601 ACT Australia U.S. Geological Survey Menlo Park 94025 CA United States Australian Antarctic Division Kingston 7050 TAS Australia Antarctic Climate and Ecosystems CRC University of Tasmania Hobart 7050 TAS Australia Department of Geology and Earth System Science Interdisciplinary Center University of Maryland College Park 20742 MD United States School of Earth Sciences University of Melbourne Melbourne 3010 VIC Australia Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China Department of Environmental Chemistry Institute of Environmental Assessment and Water Research Spanish Council for Scientific Research Barcelona 08034 Spain Department of Earth Sciences University of Cambridge Cambridge CB2 3EQ United Kingdom School of Earth and Environmental Sciences University of Wollongong Wollongong 2522 NSW Australia Oeschger Centre for Climate Change Research Institute of Geography University of Bern Bern 3012 Switzerland U.S. Geological Survey Northern Rocky Mountain Science Center Bozeman 59715 MT United States Department of Environmental Sciences Informatics and Statistics Ca' Foscari University of Venice Venice 30170 Italy Institute for Geophysics Jackson School of Geosciences University of Texas at Austin Austin 78758 TX United States Department for Earth Science Bje

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850-2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo data (LiPD) format, including serializations in Matlab, R and Python.

关键词：

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：