cometadata/test-preprints-extracted-funding huggingface dataset:
(supported by NSF grant DMS-1440140) during which some of this work was completed. This research was conducted during the period J.P. served as a Clay Research Fellow and was partially supported by a Packard Fellowship and by the National Science Foundation under the Alan T. Waterman Award, Grant No. 1747553. V.S. was supported by a Villum Investigator grant, a Danish National Research Foundation chair, a Novo Nordisk start package, NSF CAREER grant DMS-1654545, and the Simons-CRM scholar-in-residence program.
S.G. was partially supported by NSF grant DMS-1907635, and would also like to thank the Mathematical Sciences Research Institute for its hospitality during a visit in Spring 2018
This work was in part supported by the German Research Foundation (Deutsche Forschungsgemeinschaft) through Grants No. HU1874/3-2 and No. LA965/6-2 awarded as part of the DFG-Forschergruppe FOR 1548 'Geometry and Physics of Spatial Random Systems.' DY's work was supported by INSPIRE Faculty Award from DST and CPDA from the Indian Statistical Institute. This project was initiated during DY's visit to the Institute of Stochastics, Karlsruhe Institute of Technology and DY wishes to thank the institute for hosting him. DY would like to thank Rapha¨ el Lachi` eze-Rey for his comments on an earlier draft and Subhroshekhar Ghosh and Manjunath Krishnapur for discussions on higher-dimensional examples of rigid point processes. The authors are thankful to the two anonymous referees for their comments leading to an improved presentation.
T. Ketseoglou is with the Electrical and Computer Engineering Department, California State Polytechnic University, Pomona, California (e-mail: tketseoglou@cpp.edu). E. Ayanoglu is with the Center for Pervasive Communications and Computing, Department of Electrical Engineering and Computer Science, University of California, Irvine (e-mail: ayanoglu@uci.edu). This work was partially supported by NSF grant 1547155.
This work was supported by TIN2014-57251-P and TIN2017-89517-P, by the Spanish 'Ministerio de Econom´ ıa y Competitividad' and by 'Fondo Europeo de Desarrollo Regional' (FEDER) under Project TEC2015-69496-R and the Project BigDaP-TOOLS - Ayudas Fundacion BBVA a Equipos de Investigacion Cient´ ıfica 2016.
The work is partly supported by the Danish ForskEL and EUDP programmes through the Energy Collective project (grant no. 2016-1-12530), and by the EU Interreg programme through the Smart City Accelerator project (grant no. 20200999). The post-doctoral grant of Tiago Soares was financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the Portuguese funding agency, FCT - Funda¸ c˜ ao para a Ciˆ encia e a Tecnologia, within project ESGRIDS - Desenvolvimento Sustentavel da Rede Eletrica Inteligente/SAICTPAC/0004/2015-POCI-01-0145-FEDER-016434. The icons used in Figures 1, 2, 3. 4 and 5 were designed by Freepik, Nikita Golubev, Pixel Perfect, Vectors Market, Pixel Buddha, Becris from Flaticon 38 .
Wei Chen is supported by the National Natural Science Foundation of China(11771379), the Natural Science Foundation of Jiangsu Province(BK20161326), and the Jiangsu Government Scholarship for Overseas Studies(JS-2017-228). The research of R. Han is supported in part by grant from the US National Science Foundation, DMS-1800689. The research of M. T. Lacey is supported in part by grant from the US National Science Foundation, DMS-1600693, and the Australian Research Council ARC DP160100153.
This work is supported by the National Natural Science Foundation of China (No. 61772170, 61472115), the National Key Research and Development Program of China (No. 2017YFB0803301) and the Fundamental Research Funds for the Central Universities (No. JZ2017YYPY0234). This work is also supported by the National Research Foundation, Prime Ministers Office, Singapore under its IRC@Singapore Funding Initiative. The authors would like to thank the anonymous reviewers for their reviewing efforts and valuable comments.
We thank Zongquan Zhou , Zhiyuan Zhou, Xiao Liu, Zhaodi Liu for beneficial discussion for experiment, and Andrew White for careful reading of the manuscript. This work was supported by the National Natural Science Foundation of China (Grant Numbers 61490711, 61327901, 11734015, 11804330, 11874345, 11821404, 11774335, 11704371), the National Key Research and Development Program of China (Grants Number 2017YFA0304100), Anhui Initiative in Quantum Information Technologies (AHY070000), Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01X121), Key Research Program of Frontier Sciences, CAS (No. QYZDY-SSWSLH003), the National Youth Top Talent Support Program of National High level Personnel of Special Support Program, the Fundamental Research Funds for the Central Universities (Grants Number WK2030020019). JR is supported by a Westpac Research Fellowship and Australian Research Council Centre of Excellence for Engineered Quantum Systems (EQUS, CE170100009).
This research was funded by the Army Research Office grant number ARO-W911NF-151-0239. The developed computational framework uses the following open source libraries: Deal.ii [ABD + 17], P4est [BWG11], MUMPS [ADKL01], and PetSc [BAA + 17]. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE) [TCD + 14], which is supported by National Science Foundation grant number ACI-1548562. We gratefully acknowledge the Pittsburgh Supercomputing Center [NLRS15], and Jorge Vin˜ als and the Minnesota Supercomputing Institute (URL: http://www.msi.umn.edu) for providing computing resources that contributed to the research results reported within this paper.
We thank Massimo Inguscio for continuous support, the members of the LENS electronic workshop for discussions and Claudio Calosso for discussions and a critical reading of the manuscript. This work was supported by the ERC-Starting Grant PlusOne (grant agreement no. 639242), the SIR grant ULTRACOLDPLUS (grant code RBSI14GNS2), the FARE grant UltraCrystals (grant code R165JHRWR3), and the the European Metrology Programme for Innovation and Research (EMPIR) project 17FUN07 (CC4C). This project has received funding from the EMPIR programme co-financed by the Participating States and from the European Unions Horizon 2020 research and innovation programme.
Cristian Rusu is with the Faculty of Automatic Control and Computer Science, University Politehnica of Bucharest, Romania (email: cristian.rusu@acse.pub.ro). This work was supported by the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number PN-III-P1-1.1-TE-2019-1843, within PNCDI III. Demo source code https://github.com/cristian-rusu-research/multiplication-free-transform
We are grateful to V. Fock, M. Gekhtman, A. Izosimov, B. Khesin, S. MorierGenoud, V. Ovsienko, M. Shapiro, and Yu. Suris for stimulating discussions. Part of this material is based upon work supported by the National Science Foundation under grant DMS-1439786 while the authors were in residence at the Institute for Computational and Experimental Research in Mathematics in Providence, RI, during the Collaborate@ICERM program in summer of 2017. II was supported by the Swiss National Science Foundation grant 200021 169391. ST was supported by NSF grant DMS-1510055. Part of this material is based upon work supported by the National Science Foundation under Grant DMS-1440140 while ST was in residence at the Mathematical Sciences Research Institute in Berkeley, California, during the Fall 2018 semester. DF is grateful to MPIM Bonn for its invariable hospitality.
Acknowledgements. The authors wish to thank A. Aviles for valuable discussions on the topic of this paper. A.J. Guirao was supported by projects MTM2017-83262C2-1-P (AEI/FEDER, UE) and 19368/PI/14 (Fundacion Seneca). G. Mart´ ınezCervantes and J. Rodr´ ıguez were supported by projects MTM2014-54182-P and MTM2017-86182-P (AEI/FEDER, UE) and 19275/PI/14 (Fundacion Seneca).
The work reported here was supported in part by Guangdong Provincial Key Laboratory (Grant No. 2019B121203002), the JSPS Grantin-Aid for Scientific Research (A) No.17H01280, (B) No. 16KT0017, and Kayamori Foundation of Informational Science Advancement. Masahito Hayashi is with Shenzhen Institute for Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China, Guangdong Provincial Key Laboratory of Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China, Shenzhen Key Laboratory of Quantum Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China, and the Graduate School of Mathematics, Nagoya University, Nagoya, 464-8602, Japan (email:hayashi@sustech.edu.cn).
A.M.D. and S.P.M. were supported from ARO grant W911NF1810334. Additional financial support from the National Science Foundation, EPCN 1935389 &amp; CPS 1646229, and from a graduate fellowship from the University of Florida Informatics Institute is gratefully acknowledged.
I.K. was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the 'First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant,' project number 1034.
This work was partially supported by Ericsson Innovation Center in Brazil. Additional support is provided by CNPq (Conselho Nacional de Desenvolvimento Cient´ ıfico e Tecnologico) grant numbers 310317/2013-4 and 310930/2016-2, by grants from Comunidad de Madrid through project TAPIR-CM (S2018/TCS4496), and by the University of Alcala through project CCGP2017-EXP/001 and the 'Formacion del Profesorado Universitario (FPU)' program.
This work was supported by, or in part by, the Army Research Laboratory and the Army Research Office under grant number W911NF-15-1-0577, the Cooperative Agreement Number W911NF-18-2-0066, and the National Science Foundation under grant number DGE-1258507. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
The work was partially supported by the Korean-Russian bilateral project. The first author was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B05048450). The second and the third authors were partially supported by the Russian Foundation for Basic Research (grants 18-01-00420 and 18-501-51021). The results given in Sections 5 and 6 are supported by the Laboratory of Topology and Dynamics, Novosibirsk State University (contract no. 14.Y26.31.0025 with the Ministry of Education and Science of the Russian Federation).
The first author would also like to thank the Laboratoire de mathematiques Jean Leray at the Universite de Nantes for the hospitality and the financial support in the framework of the program DefiMaths during his visit in August and September 2018. Moreover, the first author wishes to thank Henning Krause and the BIREP group at Bielefeld University for the hospitality and the financial support during his visit in October and November 2018 when large portions of the paper were written.
- 5.4. Coalescence of Nematic Tactoids. Finally, the Landau - de Gennes model can also be used to simulate the reverse situation when positive nematic tactoids nucleate in the isotropic phase, then grow and coalesce to form the nematic phase with embedded topological defects (cf. [2]). In Fig. 8 the simulations were conducted subject to Neumann boundary data on ∂ω and assuming that ω has radius 1 / 2, while α = 0 . 01. Three circular tactoids of different orientations were assumed to be present at the time t = 0; in the course of the simulation, tactoids merged generating a single degree -1 / 2 defect. This situation closely resembles the original Kibble's model of strings formed in early universe through coalescence of domains with different 'phase' [29]. 6. Acknowledgements. DG acknowledges the support from DMREF NSF DMS-1729538. OL acknowledges the support from DMREF NSF DMS-1729509. PS acknowledges the support from the Simons Collaboration grant 585520.
The work at Princeton was supported by the ARO MURI on Topological Insulators, grant W911NF1210461. W.X. at LSU was supported by a Beckman Young Investigator award. X.G. at LSU is supported by the National Science Foundation under NSF-OIA-1832967. H.B.C. acknowledges support of US DOE BES Early Career Award KC0402010 under Contract DE-AC05-00OR22725. This research used resources at the High Flux Isotope Reactor, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory. This research also used resources of the National Synchrotron Light Source II, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Brookhaven National Laboratory under Contract No. DESC0012704. IP thanks J. Jiang, E. Vescovo, and K. Kaznatcheev for their help with setting up the experiment at the 21-ID-1 (ESM-ARPES) beamline. T.-R.C. was supported from Young Scholar Fellowship Program by Ministry of Science and Technology (MOST) in Taiwan, under MOST Grant for the Columbus Program MOST107-2636-M-006-004, National Cheng Kung University, Taiwan, and National Center for Theoretical Sciences (NCTS), Taiwan. W.X. and X.G. thank D. Vineyard for helping with electron paramagnetic resonance measurement.
The work was supported by the National Key R&amp;D Program of China (Grant No. 2018YFB0407601), the Foundation of National Key Laboratory (Grant No. 2018SSFNKLSMT-04), the Natural Science Foundation of China (Grant Nos. 51472199, 11534015, 51602244, and 51802248), the Key R&amp;D Program of Shaanxi Province (Grant No. 2018GY-109), the National 111 Project of China (B14040), and the Fundamental Research Funds for the Central Universities (xjj2018207).
This work at University of Texas at Dallas is supported by US Air Force Office of Scientific Research Grant No. FA9550-15-1-0236, FA9550-19-1-0037, and the startup funds from University of Texas at Dallas. The work at AFRL was also supported by an AFOSR grant (LRIR 18RQCOR100) and a grant from the National Research Council. SK and MJK acknowledges the support from Louis Beecherl, Jr. endowed funds.
Acknowledgements We gratefully acknowledge the support of DARPA under Nos. FA87501720095 (D3M) and FA86501827865 (SDH), NIH under Nos. N000141712266 (Mobilize), 1U01CA190214, and 1U01CA187947, NSF under Nos. CCF1763315 (Beyond Sparsity) and CCF1563078 (Volume to Velocity), ONRunder No. N000141712266 (Unifying Weak Supervision),the National Library of Medicine under No. R01LM01296601, the Stanford Child Health Research Institute under No. UL1-TR001085, the Stanford Human-Centered Artificial Intelligence Seed Grant, the Moore Foundation, NXP, Xilinx, LETI-CEA, Intel, Google, NEC, Toshiba, TSMC, ARM, Hitachi, BASF, Accenture, Ericsson, Qualcomm, Analog Devices, the Okawa Foundation, American Family Insurance, and members of the Stanford DAWN project: Intel, Microsoft, Teradata, Facebook, Google, Ant Financial, NEC, SAP, and VMWare. J.D. was supported by the Intelligence Community Postdoctoral Fellowship, A.R. was supported by the Stanford Interdisciplinary Graduate Fellowship, and H.S. was supported by an RSNA Research Fellow Grant from the Radiological Society of North America and the NIH No. T32-CA009695 (Stanford Cancer Imaging Training Program). The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views, policies, or endorsements, either expressed or implied, of DARPA, NIH, ONR, or the U.S. Government.
Acknowledgements. We are happy to thank Peter Haskell for interesting email correspondence. We thank Marco Manetti, Kieran O'Grady, Luca Migliorini and Shoji Yokura for useful information related to the Baum-Fulton-MacPherson class. The first author wishes to thank Stefano Urbinati and Ernesto Mistretta for helpful discussions. Part of this work was done during visits of the first author to Sapienza Universit` a di Roma; the financial support of Sapienza is gratefully acknowledged. The first author wishes also to thank the university of Padova for financial support. Finally this work was partially performed within the framework of the LABEX MILYON (ANR-10-LABX0070) of Universite de Lyon, within the program 'Investissements d'Avenir' (ANR-11-IDEX-0007) operated by the French National Research Agency (ANR).
Acknowledgements Thanks to Fei Sha for valuable discussions. This research is partially supported by the NSFC (61773198, 61751306, 61632004), NSFC-NRF Joint Research Project under Grant 61861146001, NSF Awards IIS-1513966/ 1632803/1833137, CCF-1139148, DARPA Award#: FA875018-2-0117, DARPA-D3M - Award UCB-00009528, Google Research Awards, gifts from Facebook and Netflix, and ARO# W911NF-12-1-0241 and W911NF-15-1-0484.
Marta D'Elia was supported by Sandia National Laboratories (SNL), SNL is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energys National Nuclear Security Administration contract number de-na0003525. Specifically, this work was supported through the Sandia National Laboratories Laboratory-directed Research and Development (LDRD) program. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. SAND Number: SAND2019-6287. The research of Xiaochuan Tian is supported in part by the U.S. NSF grant DMS-1819233. Yue Yu is supported by the U.S. NSF grant DMS-1620434 and the Lehigh faculty research grant.
This work was supported by the Fundamental Research Funds for the Central Universities at Huazhong University of Science and Technology Grant No. 2019kfyXJJS193, the National Natural Science Foundation of China Grant No. 11775221, the National Magnetic Confinement Fusion Science Program of China Grant No. 2015GB101004, and U.S. Department of Energy Grant Nos. DE-FG02-86ER53218 and de-sc0018001. This research used the com-
This work was supported in part by the National Science Foundation under Award ECCS-1802319 and the Key R&amp;D Project of China 2016YFB0901900. Y. Lan is with Ministry of Education Key Lab for Intelligent Networks and Network Security, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, China. Y. Lan is also with the Department of ECE, The University of Texas at Austin, Austin, TX 78705, USA. E-mail: ylan@sei.xjtu.edu.cn
This material is based upon work supported by the National Science Foundation under Grant No. CHE-1652960 to T.E.M. and Grant No. CHE-1464904 to D.B.A. T.E.M. also acknowledges support from the Camille Dreyfus Teacher-Scholar Awards Program. T.M. is grateful for financial support by the DFG (MO 3177/1-1). We thank Ondrej Marsalek, Andrés MontoyaCastillo and Yuezhi Mao for useful discussions.
Acknowledgements GB was supported by research grants NSF MCB1330728 and NIH P01GM55876-14A1. GB and LM were also supported through a grant from the Research Corporation for Scientific Advancement. This project was supported with computational resources from the National Science Foundation XSEDE program through allocation NSFMCB110149, a local cluster funded by nsf-dbi1126052, the Rutgers University Office of Advanced Research Computing (OARC) and the Rutgers Discovery Informatics Institute (RDI2), which is supported by Rutgers and the State of New Jersey. We are grateful to Dr. Jerˆ ome Henin for his helpful suggestions throughout this study.
Conflict of interest: The authors declare that they have no conflict of interest. This research was supported in part by the National Science Foundation, the National Institutes of Health, and the Research Corporation for Scientific Advancement.
Acknowledgments: LB acknowledges support by VILLUM FONDEN via the QMATH Centre of Excellence (grant no. 10059) during his stay at University of Copenhagen and by the WWTF research project 'Variational Modeling of Carbon Nanostructures' (no. MA14-009) at University of Vienna. LDL is a member of the INdAM-GNAMPA group and wishes to thank the Scuola Internazionale di Studi Superiori Avanzati where she worked in the early stage of this project. MP is supported by the Fondecyt Iniciacion grant number 11170264 entitled 'Sharp asymptotics for large particle systems and topological singularities'.
This work has been supported by Deutscher Akademischer Austauschdienst (DAAD) and Ministry of Science and Education of the Republic of Croatia (MSE) via project Random TimeChange and Jump Processes . Financial support through the Alexander von Humboldt Foundation and Croatian Science Foundation under projects 8958 and 4197 (for N. Sandrić), and the Austrian Science Fund (FWF) under project P31889-N35 and Croatian Science Foundation under project 4197 (for S. Šebek) is gratefully acknowledged.
We would like to acknowledge Dr Zhongyang Xing for her help in the interpretation of our microrheology data. I. D. S. thanks EPSRC (grant no. 1805384) for financial support. T. C. and D.L. acknowledge support by National Natural Science Foundation of China (NNSFC, 21534007 and 21821001). A. C. and E. E. thank the Winton Program for Sustainable Physics. J. Y. and R. L. acknowledge help from Cambridge Trust and China Scholarship Council (CSC). C. N. acknowledges the Maudslay-Butler Research Fellowship at Pembroke College, Cambridge, for financial support.
§ Email: irmde@dtu.dk. Partially supported by the Austrian Science Fund (FWF): W1230, by the collaborative DACH project Arrangements and Drawings as FWF project I 3340-N35, and by the Independent Research Fund Denmark grant 2020-2023 (9131-00044B) 'Dynamic Network Analysis'.
‖ Email: bvogt@ist.tugraz.at. Partially supported by Austrian Science Fund within the collaborative DACH project Arrangements and Drawings as FWF project I 3340-N35.
† Email: alanmarcelo.arroyoguevara@ist.ac.at. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skglyph[suppress] lodowska-Curie grant agreement No 754411.
‡ Email: f.m.klute@uu.nl. Supported by the Netherlands Organisation for Scientific Research (NWO) under project no. 612.001.651 and by the Austrian Science Fund (FWF): J-4510.
∗∗ Email: tilo.wiedera@uos.de. Supported by the German Research Foundation (DFG) grant CH 897/2-2.
This work is partially supported by the National Key R&amp;D Program of China (2020YFB1313503), the National Natural Science Foundation of China (Nos. 61922019, 61672125, 61733002, 61432003, 61632019, 11971220), Shenzhen Science and Technology Program (No. RCYX20200714114700072), the Stable Support Plan Program of Shenzhen Natural Science Fund (No. 20200925152128002), Guangdong Basic and Applied Basic Research Foundation 2019A1515011152, and the Fundamental Research Funds for the Central Universities.