cometadata/test-preprints-extracted-funding huggingface dataset:
This work was supported by the U.S. Department of Homeland Security under Grant Award 2017-ST-061-QA0001 and 17STQAC00001-03-03, and the National Science Foundation Program on Fairness in AI in collaboration with Amazon under award No. 1939725. 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 U.S. Department of Homeland Security.
Argonne National Laboratory's contribution is based upon work supported by Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. Z. Liu was supported by the Advanced Scientific Computing Research program of U.S. Department of Energy. The data generated and/or analysed during the current study are not publicly available for legal/ethical reasons but are available from the corresponding author on reasonable request.
✩ This work was supported by the DFG RTG 2236 'UnRAVeL', and the ERC Advanced Grant 787914 'FRAPPANT', and by NSF grants 1545126 (VeHICaL) and 1646208, by the DARPA Assured Autonomy program, by Berkeley Deep Drive, and by Toyota under the iCyPhy center. Most work was done while the first author was with RWTH Aachen University. ∗ Corresponding author
MED acknowledges support by a visiting fellowship from the Ecole Nationale Superieure de Lyon, Universite de Lyon. DF and RW acknowledge support from the French National Program of High Energy (PNHE). The simulation was performed with the EPOCH code financed by the grant EP/P02212X/1 on resources provided by the French supercomputing facilities GENCI through the grant A0070406960 and on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the HPC2N (Ume˚ a).
Funding: This publication was made possible through the support of a grant from the Army Research Office (proposal 77111-PH-II). This research was also supported by the Allen Discovery Center program through The Paul G. Allen Frontiers Group (12171). Author contributions: S.M., E.J.M., and E.H. conceived the ideas and wrote the article. S.M. and E.J.M. created the code. E.J.M. made the figures and did the analyses. Competing interests: The authors declare no competing interests.
Acknowledgments: This material is based upon work supported by the Defense Health Agency and U.S. Strategic Command under Contract No. FA4600-12-D-9000 and Contract No. FA4600-18-D-9001, and in part by the National Institutes of Health, grant #R35GM119770, and by the Layman seed grant by University of Nebraska Foundation. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Defense Health Agency, U.S. Strategic Command, or 55th Contracting Squadron. Similarly, the opinions or assertions contained herein are the private views of the authors and are not necessarily those of the Uniformed Services University of the Health Sciences, or the Department of Defense. The mention of specific therapeutic agents does not constitute endorsement by the U.S. Department of Defense, and trade names are used only for the purpose of clarification.
This work was supported by Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP) grant funded by the Korea government(MSIT) (No. 2018-11-1864, Scalable Spectrum Sharing for Beyond 5G Communication), a grant from R&amp;D Program of the Korea Railroad Research Institute, Republic of Korea, and in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2019R1G1A1100123). (Corresponding author: Seung-Woo Ko.)
This research was performed when S.G. held a position at the California Institute of Technology. The work was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-12-2-0022. 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 computations presented here were conducted on the Caltech High Performance Cluster partially supported by a grant from the Gordon and Betty Moore Foundation, and the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562.
We would like to thank Anton Pichler, Thomas Schaper and three anonymous reviewers for helpful comments on the script. The icons in Figures 9 and 10 are made by Freepik, Eucalyp, fjstudio, Those Icons, Pixel perfect, Kiranshastry, Becris, Smashicons, Prosymbols and Good Ware from www.flaticon.com. This work was supported by NWO (Dutch Research Council) grant nr. 452-13-010
Science user facility, was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. J.R.P., R.K.S., and A.X.G. acknowledge support from the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences, and Engineering Division under award number DESC0019297. The electrostatic photoelectron analyzer for HAXPES measurements was acquired through an Army Research Office DURIP grant (Grant No. W911NF-18-1-0251). This research used resources of the Advanced Light Source, a U.S. DOE Office of Science User Facility under contract no. DE-AC02-05CH11231.
Work at Drexel was supported by the National Science Foundation (Grant No. CMMI1562223). Thin film synthesis utilized deposition instrumentation acquired through an Army Research Office DURIP grant (Grant No. W911NF-14-1-0493). Y.S. and J.M.R. were supported by NSF (Grant No. DMR-2011208). Calculations were performed using the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation (NSF) Grant No. ACI-1548562, and the Center for Nanoscale Materials, an Office of
Partially supported by the Spanish Ministry of Science and Innovation, through the 'Severo Ochoa Programme for Centres of Excellence in R&amp;D' (SEV-2015-0554 and CEX2019-000904-S), and grant MTM201681048-P. The first author is partially supported by MICINN under grant PID2019-109339GB-C31. The second author is partially supported by MICINN under grant BES-2017-080578. The second and third authors are partially supported by MICINN under grants PID2019-109339GA-C32 and EUR2020-112265.
MLF acknowledges partial support by INdAM-GNCS and the Spanish grant MTM2016-75465-P.
NG acknowledges that his research was supported by funds from the Italian MUR (Ministero dell'Universit` a e della Ricerca) within the PRIN 2017 Project 'Discontinuous dynamical systems: theory, numerics and applications' and by the INdAM Research group GNCS (Gruppo Nazionale di Calcolo Scientifico).
Acknowledgments -This work is initiated at KITP and YY, TLH, FP are supported in part by the National Science Foundation under Grant No. NSF PHY- 1748958(KITP) during the Topological Quantum Matter program. TLH thanks the US National Science Foundation (NSF) MRSEC program under NSF Award Number DMR-1720633 (SuperSEED) and the award DMR 1351895-CAR for support.FP acknowledges the support of the DFG Research Unit FOR 1807 through grants no. PO 1370/2-1, TRR80, and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy EXC-2111-390814868.
The author is a Ph.D. student funded by Formation à la Recherche dans l'Industrie et dans l'Agriculture ( FRIA ) as part of Fonds de la Recherche Scientifique - FNRS .
The main aims of this paper were reached during a research visit at the University of Cape Town , which was funded by the Concours des bourses de voyage 2018 awarded by the Fédération Wallonie-Bruxelles . I am very grateful to George Janelidze for our weekly conversations and lunches on the UCT campus. His request for the definition of a commutator and his encouragements and advice for the completion of the main results of my Ph.D. project during my stay in South-Africa had a significant influence on the outcomes of my research. Let me add many thanks to my supervisors Tim Van der Linden and Marino Gran for their support, advice, contributions and careful proofreading of this work.
This work was supported by the Scheme for Promotion of Academic and Research Collaboration (SPARC/20182019/P309/SL), Ministry of Education, India. M.K. acknowledges the support from JSPS KAKENHI Grant No. 19K03859, the collaborative research programs 2020, Information Initiative Center at Hokkaido University and the COREnet program at the RCNP, Osaka University. M.D. acknowledges a doctoral research fellowship from the Ministry of Education, India.
M. Soltani was with the Department of Electrical and Computer Engineering, University of Idaho, Moscow, Idaho, USA, e-mail: solt8821@vandals.uidaho.edu, and Z. Rezki is with the Department of Electrical and Computer Engineering, University of California Santa Cruz, CA, USA, e-mail:zrezki@ucsc.edu. This work has been supported by the King Abdullah University of Science and Technology (KAUST), under a competitive research grant (CRG) OSR-2016-CRG5-2958-01.
DW, MBG, and JQ are supported by a grant from the US National Cancer Institute (NCI), R35CA220523; MBG and JQ are further supported by NCI grant U24CA231846. KG is supported by a grant from the US National Heart, Lung, and Blood Institute (NHLBI), K25HL133599. JP is supported by a grant from the US National Heart, Lung and Blood Institute, K25HL140186. JJY is supported by grant from the NCI: R01CA199064, CA193650 and U24CA211000.
The Authors acknowledge financial support of the NFFA infrastructure under Project ID 517. Computational resources were provided by the INDACO Platform for High Performance Computing at the Universit` a degli Studi di Milano http://www.indaco.unimi.it , and by CINECA through the supercomputing grant project HP10C3S9Z0. EP, TS and TT acknowledges JSPS, Ministero Affare Esteri, MEXT and CNR Short Mobility program for funding.
Manuscript received Apr. 1, 2020. Revised July 18, 2020, Nov. 19, 2020. Accepted Jan. 2, 2021. This work is supported in part by NSFC (#61874066, #61720106013), in part by The National Key Research and Development Program of China (2019YFA0706100, 2018YFA0701500), in part by Key Laboratory of Artificial Intelligence, Ministry of Education, and in part by The Beijing Innovation Center for Future Chips. Corresponding author: X. Li.
presented at ScL. Wordlines (WL and WLB) and bitlines (BL and BLB) could be set to GND to make corresponding rows and columns inactive so as to support a smaller network. Large networks may also be supported by matrix splitting with several smaller CiM macros, as discussed in [23].
J. E.-L. was supported by a Carroll L. Wilson Award and the MIT International Science and Technology Initiatives (MISTI). H. P. was supported by FONDECYT Regular grant 1190442.
The first author was supported by a Carroll L. Wilson Award and the MIT International Science and Technology Initiatives (MISTI) during an academic visit to Pontificia Universidad Catolica de Chile. The second author was supported by FONDECYT Regular grant 1190442.
The authors acknowledge L. Biferale and G. Koutsou. This project has received funding from the European Union Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement No. 765048. We also acknowledge support from the project 'Detailed Simulation of Red blood Cell Dynamics accounting for membRane viscoElastic propertieS' (SorCeReS, CUP No. E84I19002470005) financed by the University of Rome 'Tor Vergata' ('Beyond Borders 2019' call).
This research is supported by National Research Foundation of Korea (2019R1A2C4070663 and 2019M3E4A1080391). S. Jung, J. Kim, and J.-H. Kim are corresponding authors.
processing is utilized that is supported by mlagents , thus parallel accelerated training computation is realized. For the DRL training, learning iteration is set to 3 , 000 K and detailed hardware/software specification is summarized in Table I.
- *This work was partially supported by BK21 FOUR and Korea Ministry of Land, Infrastructure and Transport 362 (MOLIT) as 'Innovative Talent Education Program for Smart City'. - † J. Jeon, E. Lee, D. Choi, and ∗ H. Myung are with Urban Robotics Laboratory, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea {zinuok, sungwook87, eungchang_mason, duckyu, hmyung}@kaist.ac.kr - † S. Jung is with Autonomous IoT Research Center, Korea Electronics Technology Institute (KETI), Seongnam 13509, Republic of Korea {sungwook87}@keti.re.kr
This research was funded in part by JPMorgan Chase &amp; Co. Any views or opinions expressed herein are solely those of the authors listed, and may differ from the views and opinions expressed by JPMorgan Chase &amp; Co. or its affiliates. This material is not a product of the Research Department of J.P. Morgan Securities LLC. This material should not be construed as an individual recommendation for any particular client and is not intended as a recommendation of particular securities, financial instruments or strategies for a particular client. This material does not constitute a solicitation or offer in any jurisdiction.
This work has been supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M17), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).
This work was supported by the Arizona State University start-up funds and in part as part of ULTRA, an Energy Frontier Research Center funded by the U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), under Award # DE-SC0021230 (GW-BSE high-throughput simulations). In addition, Singh acknowledges support by the NSF DMR-grant NSF-DMR #1906030. The authors acknowledge the San Diego Supercomputer Center under the NSF-XSEDE Award No. DMR150006 and the Research Computing at Arizona State University for providing HPC resources. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
We acknowledge the partial financial support by the U.S. Department of Energy (Office of Basic Energy Sciences) under Award No. DE-SC0019215. We thank Prof. Ronald G. Reifenberger for fruitful discussions. We express our gratitude to the Center for Nanoscale Materials for the help with the STM tip preparation (use of the Center for Nanoscale Materials, an Office of Science user facility, was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357).
Acknowledgements: We would like to thank Prof. Udayan B. Darji for helpful comments on an earlier version of this text. We would also like to show our deep appreciation for the careful review and interesting suggestions given by the anonymous referee, which include among others, lemma 2.6 and its proof, Corollary 2.7, example 2.13 and question 4.3. M.B.A. was supported by CAPES. R.V. was partially supported by CNPq.
A.M. and A.S. acknowledge financial support from the Semiconductor Research Corporation (SRC), IMPACT nCore Center, Task no. 2966.012. M.K. and M.H. acknowledge financial support by the ÅForsk Foundation (18461). W.T. and M.H. acknowledge financial support by the Swedish Energy Agency (Energimyndigheten 484891). Authors acknowledge Alessandro Enrico at KTH for help with laser patterning, Tyler James Quill at Stanford University for help with ANN simulations, and Toni Moore and Alex Blagojebic for their help at University of Connecticut with MAX phase synthesis. A.V.M. acknowledges Sina Shahbazmohamadi for providing access to chemical laboratories at innovation partnership building (IPB) of the University of Connecticut for part of this project.
The majority of the data represented here was supported by the National Institutes of Health and the National Science Foundation, currently through NIH R01 AG053330 and R01 AG053308, as well as R01 HD088558, P01 AG031719, and NSF IOS 1456832. We also thank Duke University, Princeton University, and the University of Notre Dame for financial and logistical support. For assistance and cooperation in Kenya, we are grateful to the Kenya Wildlife Service (KWS), University of Nairobi, Institute of Primate Research (IPR), National Museums of Kenya, National Environment Management Authority, and National Commission for Science, Technology, and Innovation (NACOSTI). We also thank the members of the Amboseli-Longido pastoralist communities, and the Enduimet Wildlife Management Area for their cooperation and assistance in the field. Particular thanks go to the Amboseli Baboon Project long-term field team (R.S. Mututua, S. Sayialel, J.K. Warutere, Siodi, I.L.), and to T. Wango and V. Oudu for their untiring assistance in Nairobi. The baboon project database, Babase, is expertly managed by N. Learn and J. Gordon. Database design and programming are provided by K. Pinc. This research was approved by the IACUC at Duke University, University of Notre Dame, and Princeton University and adhered to all the laws and guidelines of Kenya. For a complete set of acknowledgments of funding sources, logistical assistance, and data collection and management, please visit http://amboselibaboons.nd.edu/acknowledgements/ .
This work has received financial support from Ministerio de Economía y Competitividad (Spain) under projects No. MAT2016-80762-R, PID2019-104150RB-100 and PGC2018-097789-B-I00, Xunta de Galicia (Centro singular de investigación de Galicia accreditation 2016-2019, ED431G/09), the European Union (European Regional Development Fund-ERDF) and the European Commission through the Horizon H2020 funding by H2020-MSCA-RISE-2016Project No. 734187 -SPICOLOST. E.L. is a Serra Húnter Fellow (Generalitat de Catalunya). E.L. acknowledges the funding received from the European Union's Horizon 2020 research and innovation program through the Marie Skłodowska -Curie Actions: Individual Fellowship-Global Fellowship (Ref. MSCA-IF-GF-708129). D.B. acknowledges financial support from MINECO (Spain) through an FPI fellowship (BES-2017-079688). The work at Cornell was supported by the Army Research Office under grant W911NF-16-1-0315. H.P. acknowledges support from the National Science Foundation [Platform for the Accelerated Realization, Analysis, and Discovery of Interface Materials (PARADIM)] under Cooperative Agreement No. DMR-1539918.
We thank J. Watchorn (UToronto) for helpful comments regarding this manuscript. STEM images were taken at the Ontario Center for the Characterization of Advanced Materials (OCCAM) at the University of Toronto. This work was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant (06441). P.Z.C. was supported by the NSERC Vanier Canada Graduate Scholarship. A.J.C. was supported by the Ontario Graduate Scholarship. F.X.G. was supported by the NSERC Senior Industrial Research Chair program.
§ The work of the fourth author was partially supported by the distinguished Edurad ˇ Cech visiting program at the Institute of Mathematics of the Academy of Sciences of the Czech Republic.
∗ S.K. has been supported by the Czech Science Foundation (GA ˇ CR) project GA19-04243S within RVO:67985840. † The work of Y-S.K. was supported by the National Research Foundation of Korea (NRF2020R1F1A1A01049805) ‡ ˇ S. N. has been supported by the Czech Science Foundation (GA ˇ CR) project GA19-04243S. The Institute of Mathematics, CAS is supported by RVO:67985840.
Funding: Jonas Kusch, Graham Alldredge and Martin Frank were supported by the German Research Foundation (DFG). Martin Frank was supported under grant FR 2841/6-1 and Graham Alldredge under AL 2030/1-1. Jonas Kusch was funded under Project-ID 258734477 - SFB 1173. Furthermore, Jonas Kusch would like to thank the German Academic Exchange Service (DAAD) for funding his research visit at the University of Notre Dame as well as the University of Notre Dame for hosting his stay during which large portions of this work were conducted.
We thank S. Hüttner for valuable discussions. This work was supported by the Bavarian State Ministry of Science and the Arts through the Collaborative Research Network Solar Technologies go Hybrid (SolTech), the Elite Network Bavaria, and the German Research Foundation (DFG) through SFB840 B7, and through computational resources provided by the Bavarian Polymer Institute (BPI). R.-I. Biega acknowledges support by the DFG program GRK1640.
The authors would like to thank Jeffrey C. Lagarias and the anonymous referee for their comments and literature suggestions. A.K. was partially supported by SNSF (project no. PP00P2-170560) and Russian Federation Government (grant no. 075-15-2019-1926). A.T. was partially supported by RFBR and SC RA (project no. 20-51-05010). Also, A.T. would like to thank the University of Neuchâtel for its hospitality in May 2021.
This work was supported by the National Natural Science Foundation of China (Grants No. 62025507, No. 11934019, No. 11721404, and No. 11874419), the Key-Area Research and Development Program of Guangdong Province (Grant No.2018B030329001), and the Strategic Priority Research Program (Grant No. XDB28000000), the Instrument Developing Project (Grant No. YJKYYQ20180036) and the Interdisciplinary Innovation Team of the Chinese Academy of Science.
D. Jha is funded by the PRIVATON project (#263248) which is funded by Research Council of Norway (RCN). S. Ali is supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). Our experiments were performed on the Experimental Infrastructure for Exploration of Exascale Computing (eX3) system, which is financially supported by RCN under contract 270053. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.
Acknowledgements. XD is supported by NSF DMS-2107729. YO is supported by NSF DMS-2042109. RZ is supported by the NSF grant DMS-1856541, DMS1926686 and by the Ky Fan and Yu-Fen Fan Endowment Fund at the Institute for Advanced Study. We would like to thank Tuomas Orponen for pointing us to the example of Davies-Fast [4] and Alex Iosevich for helpful discussions over the course of the project. We are also grateful to the anonymous referee whose suggestions have greatly improved the accuracy and exposition of the article.
Acknowledgements Y. Gao is supported by the Start-up fund from The Hong Kong Polytechnic University. T. K. Wong is partially supported by the HKU Seed Fund for Basic Research under the project code 201702159009, the Start-up Allowance for Croucher Award Recipients, and Hong Kong General Research Fund (GRF) grant 'Solving Generic Mean Field Type Problems: Interplay between Partial Differential Equations and Stochastic Analysis' with project number 17306420.
This paper was recommended for publication by Editor Abderrahmane Kheddar upon evaluation of the Associate Editor and Reviewers' comments. This work was supported in part by National Natural Science Foundation of China under Grant No. 62073159 and Grant No. 62003155, in part by the Shenzhen Science and Technology Program under Grant No. JCYJ20200109141601708, and in part by the Science, Technology and Innovation Commission of Shenzhen Municipality under grant no. ZDSYS20200811143601004. (Corresponding author: Wei Zhang.)