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arXiv 2021年

作者： David, Etienne Serouart, Mario Smith, Daniel Madec, Simon Velumani, Kaaviya Liu, Shouyang Wang, Xu Pinto, Francisco Shafiee, Shahameh Tahir, Izzat S.A. Tsujimoto, Hisashi Nasuda, Shuhei Zheng, Bangyou Kichgessner, Norbert Aasen, Helge Hund, Andreas Sadhegi-Tehran, Pouria Nagasawa, Koichi Ishikawa, Goro Dandrifosse, Sébastien Carlier, Alexis Dumont, Benjamin Mercatoris, Benoit Evers, Byron Kuroki, Ken Wang, Haozhou Ishii, Masanori Badhon, Minhajul A. Pozniak, Curtis LeBauer, David Shaner Lillemo, Morten Poland, Jesse Chapman, Scott de Solan, Benoit Baret, Frédéric Stavness, Ian Guo, Wei Arvalis Institut du végétal 3 Rue Joseph et Marie Hackin Paris75116 France UMR1114 EMMAH INRAE Centre PACA Bâtiment Climat Domaine Saint-Paul 228 Route de l’Aérodrome CS 40509 Avignon Cedex84914 France School of Food and Agricultural Sciences The University of Queensland GattonQLD4343 Australia Hiphen SAS Agroparc Bâtiment Technicité 120 rue Jean Dausset Avignon84140 France Plant Phenomics Research Center Nanjing Agricultural University Nanjing China Wheat Genetics Resource Center Dep. of Plant Pathology Kansas State Univ. 4024 Throckmorton Plant Sciences Center ManhattanKS United States Mexico D.F. Mexico Norwegian University of Life Sciences Faculty of Biosciences P.O. Box 5003 ÅsNO-1432 Norway Agricultural Research Corporation Wheat Research Program P.O. Box 126 Wad Medani Sudan Arid Land Research Center Tottori University Tottori680-0001 Japan Laboratories of Plant Genetics and Plant Breeding Graduate School of Agriculture Kyoto University Japan CSIRO Agriculture and Food Queensland Biosciences Precinct 306 Carmody Road St LuciaQLD4067 Australia Institute of Agricultural Sciences ETH Zurich Universitätstrasse 2 Zurich8092 Switzerland Plant Sciences Department Rothamsted Research Harpenden United Kingdom Institute of Crop Science National Agriculture and Food Research Organization Japan Hokkaido Agricultural Research Center National Agriculture and Food Research Organization Japan Biosystems Dynamics and Exchanges TERRA Teaching and Research Center Gembloux Agro-Bio Tech University of Liège Gembloux5030 Belgium Plant Sciences TERRA Teaching and Research Center Gembloux Agro-Bio Tech University of Liège Gembloux5030 Belgium Graduate School of Agricultural and Life Sciences The University of Tokyo 1-1-1 Midori-cho Nishitokyo City Tokyo Japan Department of Computer Science University of Saskatchewan Canada Department of Plant Sciences University of Saskatchewan Canada College of Agriculture and Life Sciences University o

The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4,700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD has successfully attracted attention from both the computer vision and agricultural science communities. From this first experience in 2020, a few avenues for improvements have been identified, especially from the perspective of data size, head diversity and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and augmented by adding 1,722 images from 5 additional countries, allowing for 81,553 additional wheat heads to be added. We now release a new version of the Global Wheat Head Detection (GWHD) dataset in 2021, which is bigger, more diverse, and less noisy than the 2020 version. The GWHD 2021 is now publicly available at http://***/ and a new data challenge has been organized on AIcrowd to make use of this updated dataset. © 2021, CC BY.

关键词： Object detection

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A simple standard for sharing ontological mappings (SSSOM)

arXiv

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arXiv 2021年

作者： Matentzoglu, Nicolas Balhoff, James P. Bello, Susan M. Bizon, Chris Brush, Matthew Callahan, Tiffany J. Chute, Christopher G. Duncan, William D. Evelo, Chris T. Gabriel, Davera Graybeal, John Gray, Alasdair Gyori, Benjamin M. Haendel, Melissa Harmse, Henriette Harris, Nomi L. Harrow, Ian Hegde, Harshad Hoyt, Amelia L. Hoyt, Charles T. Jiao, Dazhi Jiménez-Ruiz, Ernesto Jupp, Simon Kim, Hyeongsik Koehler, Sebastian Liener, Thomas Long, Qinqin Malone, James McLaughlin, James A. McMurry, Julie A. Moxon, Sierra Munoz-Torres, Monica C. Osumi-Sutherland, David Overton, James A. Peters, Bjoern Putman, Tim Queralt-Rosinach, Núria Shefchek, Kent Solbrig, Harold Thessen, Anne Tudorache, Tania Vasilevsky, Nicole Wagner, Alex H. Mungall, Christopher J. Semanticly Ltd. LondonWC2H 9JQ United Kingdom RENCI University of North Carolina Chapel HillNC27517 United States The Jackson Laboratory Bar HarborME04609 United States University of Colorado Anschutz Medical Campus AuroraCO80217 United States Johns Hopkins University BaltimoreMD21210 United States Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Maastricht University Netherlands Stanford University StanfordCA94305 United States Department of Computer Science Heriot-Watt University Edinburgh United Kingdom Harvard Medical School BostonMA02115 United States Hinxton United Kingdom Pistoia Alliance Inc United States Beth Israel Deaconess Medical Center BostonMA United States City University of London United Kingdom University of Oslo Norway SciBite Limited Bio Data Innovation Centre Wellcome Genome Campus Hinxton Saffron Walden CB10 1DR United Kingdom Robert Bosch LLC Ada Health GmbH Leiden University Medical Center Leiden Netherlands BenchSci 25 York St Suite 1100 TorontoONM5J 2V5 Canada Knocean Inc. TorontoON Canada La Jolla Institute for Immunology 9420 Athena Circle La Jolla CA92037 United States The Steve and Cindy Rasmussen Institute for Genomic Medicine Nationwide Children's Hospital ColumbusOH43205 United States The Ohio State University College of Medicine ColumbusOH43210 United States

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. © 2021, CC0.

关键词： Mapping

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computer Vision Problems in Plant Phenotyping, CVPPP 2017: Introduction to the CVPPP 2017 Workshop Papers

Computer Vision Problems in Plant Phenotyping, CVPPP 2017: I...

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International Conference on computer Vision Workshops (ICCV Workshops)

作者： H. Scharr T. Pridmore S. A. Tsaftaris Institute of Bio- and Geosciences (IBG) IBG-2: Plant Sciences Forschungszentrum Jülich Germany School of Computer Science University of Nottingham UK School of Engineering University of Edinburgh Edinburgh UK

Plant phenotyping is the identification of effects on the phenotype (i.e., the plant appearance and behavior) as a result of genotype differences (i.e., differences in the genetic code) and the environment. Previously, the process of taking phenotypic measurements has been laborious, costly, and time consuming. In recent years, non-invasive, image-based methods have become more common. These images are recorded by a range of capture devices from small embedded camera systems to multi-million Euro smart-greenhouses, at scales ranging from microscopic images of cells, to entire fields captured by UAV imaging. These images needs to be analyzed in a high throughput, robust, and accurate manner.

关键词： Conferences computer vision Three-dimensional displays Machine vision Image analysis Machine learning Geology

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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Scalable photonic reinforcement learning by time-division multiplexing of laser chaos

arXiv

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arXiv 2018年

作者： Naruse, Makoto Mihana, Takatomo Hori, Hirokazu Saigo, Hayato Okamura, Kazuya Hasegawa, Mikio Uchida, Atsushi Network System Research Institute National Institute of Information and Communications Technology 4-2-1 Nukui-kita Koganei Tokyo184-8795 Japan Department of Information and Computer Sciences Saitama University 255 Shimo-Okubo Sakura-ku Saitama Saitama338-8570 Japan Interdisciplinary Graduate School University of Yamanashi Takeda Kofu Yamanashi400-8510 Japan Nagahama Institute of Bio-Science and Technology 1266 Tamura Nagahama Shiga526-0829 Japan Graduate School of Informatics Nagoya University Furo Chikusa Nagoya Aichi464-8601 Japan Department of Electrical Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika Tokyo125-8585 Japan

Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes a crucial element of artificial intelligence. In our previous work, we experimentally demonstrated that the ultrafast chaotic oscillatory dynamics of lasers can be used to solve the two-armed bandit problem efficiently, which requires decision making concerning a class of difficult trade-offs called the exploration?exploitation dilemma. However, only two selections were employed in that research;thus, the scalability of the laser-chaos-based reinforcement learning should be clarified. In this study, we demonstrated a scalable, pipelined principle of resolving the multi-armed bandit problem by introducing time-division multiplexing of chaotically oscillated ultrafast time-series. The experimental demonstrations in which bandit problems with up to 64 arms were successfully solved are presented in this report. Detailed analyses are also provided that include performance comparisons among laser chaos signals generated in different physical conditions, which coincide with the diffusivity inherent in the time series. This study paves the way for ultrafast reinforcement learning by taking advantage of the ultrahigh bandwidths of light wave and practical enabling technologies. Copyright © 2018, The Authors. All rights reserved.

关键词： Time series

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Empirical Analysis of A Tree-based Efficient Non-dominated Sorting Approach for Many-Objective Optimization

Empirical Analysis of A Tree-based Efficient Non-dominated S...

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IEEE Symposium Series on Computational Intelligence

作者： Xingyi Zhang Ye Tian Ran Cheng Yaochu Jin Institute of Bio-inspired Intelligence and Mining Knowledge School of Computer Science and Technology Anhui University Hefei 230039 China School of Computer Science University of Birmingham B15 2TT United Kingdom Department of Computer Science University of Surrey Guildford GU2 7XH United Kingdom

ISBN: (纸本)9781509042418

Non-dominated sorting has been widely adopted in evolutionary multi-objective optimization. Many approaches to non-dominated sorting have been proposed to improve its computational efficiency, but unfortunately, most of them still suffer from high computational cost, especially when the number of objectives becomes large. A tree-based efficient non-dominated sorting approach, termed T-ENS, has been recently developed by us for many-objective optimization, where a tree structure is adopted to represent solutions, such that the non-dominance relationship between solutions can be easily inferred from the position of the solutions in the tree, thereby considerably reducing the number of comparisons between solutions belonging to the same non-dominated front. To validate the computational efficiency of T-ENS, this paper provides a detailed empirical analysis by comparing T-ENS with the state-of-the-art approaches, in particular when the number of objectives is larger than three and the population size becomes large. Empirical results indicate that the T-ENS is well suited for evolutionary many-objective optimization and large-scale multi-objective optimization, where either the number of objectives or the population size is large.

关键词： structure adopted represent

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Corrigendum to "Dissecting the genetic heterogeneity of gastric cancer"

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EbioMedicine 2023年 94卷 104709页

作者： Timo Hess Carlo Maj Jan Gehlen Oleg Borisov Stephan L Haas Ines Gockel Michael Vieth Guillaume Piessen Hakan Alakus Yogesh Vashist Carina Pereira Michael Knapp Vitalia Schüller Alexander Quaas Heike I Grabsch Jessica Trautmann Ewa Malecka-Wojciesko Anna Mokrowiecka Jan Speller Andreas Mayr Julia Schröder Axel M Hillmer Dominik Heider Florian Lordick Ángeles Pérez-Aísa Rafael Campo Jesús Espinel Fernando Geijo Concha Thomson Luis Bujanda Federico Sopeña Ángel Lanas María Pellisé Claudia Pauligk Thorsten Oliver Goetze Carolin Zelck Julian Reingruber Emadeldin Hassanin Peter Elbe Sandra Alsabeah Mats Lindblad Magnus Nilsson Nicole Kreuser René Thieme Francesca Tavano Roberta Pastorino Dario Arzani Roberto Persiani Jin-On Jung Henrik Nienhüser Katja Ott Ralf R Schumann Oliver Kumpf Susen Burock Volker Arndt Anna Jakubowska Małgorzta Ławniczak Victor Moreno Vicente Martín Manolis Kogevinas Marina Pollán Justyna Dąbrowska Antonio Salas Olivier Cussenot Anne Boland-Auge Delphine Daian Jean-Francois Deleuze Erika Salvi Maris Teder-Laving Gianluca Tomasello Margherita Ratti Chiara Senti Valli De Re Agostino Steffan Arnulf H Hölscher Katharina Messerle Christiane Josephine Bruns Armands Sīviņš Inga Bogdanova Jurgita Skieceviciene Justina Arstikyte Markus Moehler Hauke Lang Peter P Grimminger Martin Kruschewski Nikolaos Vassos Claus Schildberg Philipp Lingohr Karsten Ridwelski Hans Lippert Nadine Fricker Peter Krawitz Per Hoffmann Markus M Nöthen Lothar Veits Jakob R Izbicki Adrianna Mostowska Federico Martinón-Torres Daniele Cusi Rolf Adolfsson Geraldine Cancel-Tassin Aksana Höblinger Ernst Rodermann Monika Ludwig Gisela Keller Andres Metspalu Hermann Brenner Joerg Heller Markus Neef Michael Schepke Franz Ludwig Dumoulin Lutz Hamann Renato Cannizzaro Michele Ghidini Dominik Plaßmann Michael Geppert Peter Malfertheiner Olivier Glehen Tomasz Skoczylas Marek Majewski Jan Lubiński Orazio Palmieri Stefania Boccia Anna Latiano Nuria Aragones Thomas Schmidt Mário Dinis-Ribeiro Rui Medeiros Salah-Eddin Al-Batran Mārcis Leja Juozas Institute of Human Genetics University of Marburg Marburg Germany Institute of Human Genetics University of Bonn School of Medicine & University Hospital Bonn Bonn Germany. Institute for Genomic Statistics and Bioinformatics Medical Faculty University of Bonn Bonn Germany. Institute of Human Genetics University of Marburg Marburg Germany. Department of Upper GI Diseases Karolinska University Hospital and Unit of Gastroenterology and Rheumatology Karolinska Institutet Stockholm Sweden. Department of Visceral Transplant Thoracic and Vascular Surgery University Hospital Leipzig Leipzig Germany. Institute for Pathology Friedrich-Alexander-University Erlangen-Nuernberg Klinikum Bayreuth Bayreuth Germany. Department of Digestive and Oncological Surgery Claude Huriez Hospital CHU Lille Lille France. Department of General Visceral Cancer and Transplant Surgery University of Cologne Cologne Germany. Department of General Visceral and Thoracic Surgery University Medical Center Hamburg-Eppendorf University of Hamburg Hamburg Germany Centre for Surgical Oncology Medias Klinikum Burghausen Burghausen Germany. Molecular Oncology and Viral Pathology Group IPO Porto Research Center (CI-IPOP) Portuguese Institute of Oncology of Porto (IPO Porto) 4200-072 Porto Portugal Porto Comprehensive Cancer Center & RISE @ CI-IPO University of Porto 4200-450 Porto Portugal. Institute of Medical Biometrics Informatics and Epidemiology (IMBIE) Medical Faculty University of Bonn Bonn Germany. Institute of Pathology University Hospital Cologne Medical Faculty University of Cologne Germany. Department of Pathology GROW School for Oncology and Developmental Biology Maastricht University Medical Center Maastricht the Netherlands Pathology and Data Analytics Leeds Institute of Medical Research at St James's University of Leeds Leeds United Kingdom. Department of Digestive Tract Diseases Medical University of Lodz Lodz Poland. Department of Mathematics and Computer Science Unive

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Emerging giant resonant exciton induced by Ta substitution in anatase TiO2: A tunable correlation effect

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Physical Review B 2016年第20期93卷 205118-205118页

作者： Z. Yong P. E. Trevisanutto L. Chiodo I. Santoso A. R. Barman T. C. Asmara S. Dhar A. Kotlov A. Terentjevs F. Della Sala V. Olevano M. Rübhausen T. Venkatesan A. Rusydi NUSNNI-NanoCore National University of Singapore Singapore 117576 Singapore Synchrotron Light Source National University of Singapore 5 Research Link Singapore 117603 Singapore Department of Physics National University of Singapore Singapore 117542 Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Centre for Advanced 2D Materials and Graphene Research Centre National University of Singapore Singapore 117546 Unit of Nonlinear Physics and Mathematical Modeling Department of Engineering Università Campus Bio-Medico di Roma Via Álvaro del Portillo 21 00128 Rome Italy Center for Life Nano Science @Sapienza Istituto Italiano di Tecnologia Viale Regina Elena 291 00161 Rome Italy Department of physics School of Natural Sciences Shiv Nadar University Gautam Buddha Nagar P.O. NH-91 Uttar Pradesh 201314 India Photon Science at DESY Notkestraße 85 D-22607 Hamburg Germany Istituto Nanoscienze-CNR Euromediterranean Center for Nanomaterial Modelling and Technology (ECMT) Via per Arnesano 73100 Lecce Italy Center for Biomolecular Nanotechnologies @UNILE Istituto Italiano di Tecnologia Via Barsanti I-73010 Arnesano Italy CNRS Institut Néel Grenoble France Institute of Nanostructure and Solid State Physics Jungiusstrasse 11 University of Hamburg D-20355 Hamburg Germany Center for Free-Electron Laser Science Advanced Study Group of the University of Hamburg Luruper Chaussee 149 D-22761 Hamburg Germany

Titanium dioxide (TiO2) has rich physical properties with potential implications for both fundamental physics and new applications. To date, the main focus of applied research is to tune its optical properties, which is usually done via doping and/or nanoengineering. However, understanding the role of d electrons in materials and possible functionalization of d-electron properties are still major challenges. Herewith, within a combination of an innovative experimental technique, high-energy optical conductivity, and state-of-the-art ab initio electronic structure calculations, we report an emerging, novel resonant exciton in the deep ultraviolet region of the optical response. The resonant exciton evolves upon low-concentration Ta substitution in anatase TiO2 films. It is surprisingly robust and related to strong electron-electron and electron-hole interactions. The d- and f-orbital localization, due to Ta substitution, plays an unexpected role, activating strong electronic correlations and dominating the optical response under photoexcitation. Our results shed light on a new optical phenomenon in anatase TiO2 films and on the possibility of tuning electronic properties by Ta substitution.

关键词： Excitons Optical conductivity Ab initio calculations

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