pushshift.io的 10 大竞争对手

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zenodo.org

Amiridis, V.1, Marinou, E.1, Hostetler, C.2, Koopman, R.3, Cecil, D., J.4, Moisseev, D.5, Tackett, J.2, Gross, S.6, Baars, H.7, Redemann, J.8, Marenco, F.9, Baldini, L.10, Tanelli, S.11, Fielding, M.12, Janisková, M.12, Tanaka, T.13, O’Connor, E.14, Fjæraa, A., M.15, and the ACPPV consortium 16   1Institute of Astronomy, Astrophysics, Space Applications & Remote Sensing (IAASARS), National Observatory of Athens (NOA), 15236 Athens, Greece 2NASA Langley Research Center, Hampton, United States 3European Space Research and Technology, European Space Agency (ESA/ESTEC), Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands 4NASA Marshall Space Flight Center, Earth Science Branch, 320 Sparkman Dr NW, AL 35805, Huntsville, United States 5Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, Finland 6Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Weßling 82234, Germany 7Leibniz Institute for Tropospheric Research (TROPOS), Permoserstraße 15, 04318 Leipzig, Germany 8School of Meteorology, University of Oklahoma, Norman, Oklahoma, United States 9The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus 10National Research Council, Insitute of Atmospheric Science and Climate (CNR-ISAC), Via Fosso del Cavaliere, 100, 00133, Roma, Italy 11Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States 12European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom 13Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Tsukuba, Ibaraki 305-8505, Japan 14Finnish Meteorological Institute, Climate Research Programme, Erik Palménin aukio 1, FI-00560, Helsinki, Finland 15Climate and Research Institute NILU, P.O. Box 100, 2027 Kjeller, Norway 16 57 institutes, universities, and space agencies   Aerosols, clouds, precipitation, and the processes governing their interactions are the grand challenges for cu

academictorrents.com

# BOLT Chinese SMS/Chat | Item Name: | BOLT Chinese SMS/Chat | |—-|—-| | Author(s): | Song Chen, Dana Fore, Stephanie Strassel, Haejoong Lee, Jonathan Wright | | LDC Catalog No.: | LDC2018T15 | | ISBN: | 1-58563-847-1 | | ISLRN: | 269-619-825-584-0 | | DOI: | | | Release Date: | June 15, 2018 | | Member Year(s): | 2018 | | DCMI Type(s): | Text | | Data Source(s): | text chat conversations | | Project(s): | BOLT | | Application(s): | machine translation | | Language(s): | Mandarin Chinese | | Language ID(s): | cmn | | Citation: | Chen, Song, et al. BOLT Chinese SMS/Chat LDC2018T15. Web Download. Philadelphia: Linguistic Data Consortium, 2018. | ### Introduction BOLT Chinese SMS/Chat was developed by the Linguistic Data Consortium (LDC) and consists of naturally-occurring Short Message Service (SMS) and Chat (CHT) data collected through data donations and live collection involving native speakers of Chinese. The corpus contains 14,877 conver, Info Hash: 02a77d9684f25ed8d86c19b2dc2be1554aa14719

arxiv.org

A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory. In this study, we test karma in an online experiment in which human subjects repeatedly compete for a resource with time-varying and stochastic individual preferences or urgency to acquire the resource. We confirm that karma has significant and sustained welfare benefits even in a population with no prior training. We identify mechanism usage in contexts with sporadic high urgency, more so than with frequent moderate urgency, and implemented as a simple (binary) karma bidding scheme as particularly effective for welfare improvements: relatively larger aggregate efficiency gains are realized that are (almost) Pareto superior. These findings provide guidance for further testing and for future implementation plans of such mechanisms in the real world.

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