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  • 2020-2023  (5)
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  • 1
    Publikationsdatum: 2022-02-08
    Beschreibung: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
    Format: application/pdf
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2022-05-27
    Beschreibung: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Lindell, S., & Kite-Powell, H. Meeting protein and energy needs for 10 billion people while restoring oceans. Marine Technology Society Journal, 55(3), (2021): 124–124, https://doi.org/10.4031/MTSJ.55.3.49.
    Beschreibung: Shellfish and seaweed farming provide resources, opportunities, and solutions to address a wide range of seemingly intractable global problems. Installed and managed properly, aquaculture operations can be restorative to ocean environments, counter climate change, and relieve pressure to farm sensitive terrestrial environments. For these reasons, there is growing social acceptance and political pressure for marine aquaculture expansion, and State, Federal, and International, as well as eNGO-led initiatives are underway. Now is the time to invest in multi-disciplinary science-based teams that can signpost the sustainable pathway for marine aquaculture by developing monitoring and modeling tools and protocols for measuring associated ecosystem impacts and beneficial services. The yield on that investment will be healthy food and more carbon-neutral bio-fuels grown in ways that help heal our oceans. A sustained commitment by the United States now to develop the science and technology for future ocean farms will find an enthusiastic audience in young researchers and technologist around the world, who seek better ways to improve people's lives through their science and problem solving.
    Repository-Name: Woods Hole Open Access Server
    Materialart: Article
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    Publikationsdatum: 2022-05-26
    Beschreibung: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Johnston, T. M. S., Schonau, M. C., Paluszkiewicz, T., MacKinnon, J. A., Arbic, B. K., Colin, P. L., Alford, M. H., Andres, M., Centurioni, L., Graber, H. C., Helfrich, K. R., Hormann, V., Lermusiaux, P. F. J., Musgrave, R. C., Powell, B. S., Qiu, B., Rudnick, D. L., Simmons, H. L., St Laurent, L., Terrill, E. J., Trossman, D. S., Voet, G., Wijesekera, H. W., & Zeiden, K. L. Flow Encountering Abrupt Topography (FLEAT): a multiscale observational and modeling program to understand how topography affects flows in the western North Pacific. Oceanography, 32(4), (2019): 10-21, doi: 10.5670/oceanog.2019.407.
    Beschreibung: Using a combination of models and observations, the US Office of Naval Research Flow Encountering Abrupt Topography (FLEAT) initiative examines how island chains and submerged ridges affect open ocean current systems, from the hundreds of kilometer scale of large current features to the millimeter scale of turbulence. FLEAT focuses on the western Pacific, mainly on equatorial currents that encounter steep topography near the island nation of Palau. Wake eddies and lee waves as small as 1 km were observed to form as these currents flowed around or over the steep topography. The direction and vertical structure of the incident flow varied over tidal, inertial, seasonal, and interannual timescales, with implications for downstream flow. Models incorporated tides and had grids with resolutions of hundreds of meters to enable predictions of flow transformations as waters encountered and passed around Palau’s islands. In addition to making scientific advances, FLEAT had a positive impact on the local Palauan community by bringing new technology to explore local waters, expanding the country’s scientific infrastructure, maintaining collaborations with Palauan partners, and conducting outreach activities aimed at elementary and high school students, US embassy personnel, and Palauan government officials.
    Beschreibung: We are grateful to Captains David Murline and Tom Desjardins and the crew of R/V Roger Revelle, and to the staff of the Coral Reef Research Foundation, for their help in carrying out the field program; to ONR for funding this work; and to FLEAT colleagues for their collaboration. We wish to thank the Bureau of Marine Resources, Ministry of Natural Resources, Environment and Tourism of the Palau National Government, and the Angaur, Kayangel, Koror, and Peleliu State Governments for the relevant permits to conduct this research in Palau’s waters.
    Repository-Name: Woods Hole Open Access Server
    Materialart: Article
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
    Publikationsdatum: 2022-10-26
    Beschreibung: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Belden, E. R., Kazantzis, N. K., Reddy, C. M., Kite-Powell, H., Timko, M. T., Italiani, E., & Herschbach, D. R. Thermodynamic feasibility of shipboard conversion of marine plastics to blue diesel for self-powered ocean cleanup. Proceedings of the National Academy of Sciences of the United States of America, 118(46),(2021): e2107250118, https://doi.org/10.1073/pnas.2107250118.
    Beschreibung: Collecting and removing ocean plastics can mitigate their environmental impacts; however, ocean cleanup will be a complex and energy-intensive operation that has not been fully evaluated. This work examines the thermodynamic feasibility and subsequent implications of hydrothermally converting this waste into a fuel to enable self-powered cleanup. A comprehensive probabilistic exergy analysis demonstrates that hydrothermal liquefaction has potential to generate sufficient energy to power both the process and the ship performing the cleanup. Self-powered cleanup reduces the number of roundtrips to port of a waste-laden ship, eliminating the need for fossil fuel use for most plastic concentrations. Several cleanup scenarios are modeled for the Great Pacific Garbage Patch (GPGP), corresponding to 230 t to 11,500 t of plastic removed yearly; the range corresponds to uncertainty in the surface concentration of plastics in the GPGP. Estimated cleanup times depends mainly on the number of booms that can be deployed in the GPGP without sacrificing collection efficiency. Self-powered cleanup may be a viable approach for removal of plastics from the ocean, and gaps in our understanding of GPGP characteristics should be addressed to reduce uncertainty.
    Beschreibung: The US NSF supported this work as part of its 2026 Idea Machine initiative (Chemical, Bioengineering, Environmental, and Transport Systems, EArly-concept Grants for Exploratory Research Award #2032621). E.R.B.’s contribution was funded, in part, by the NSF Graduate Research Fellowship Program under Grant No. 2038257.
    Schlagwort(e): Ocean plastic ; Hydrothermal liquefaction ; Exergy analysis ; Monte Carlo simulation
    Repository-Name: Woods Hole Open Access Server
    Materialart: Article
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
    facet.materialart.
    Unbekannt
    In:  Code4Lib Journal
    Publikationsdatum: 2022
    Beschreibung: Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) concerned with solving language tasks by modeling large amounts of textual data. Some NLP techniques use word embeddings which are semantic models where machine learning (ML) is used to learn to cluster semantically related words by learning about word co-occurrences in the original training text. Unfortunately, these models tend to reflect or even exaggerate biases that are present in the training corpus. Here we describe the Word Embedding Navigator (WEN), which is a tool for exploring word embedding models. We examine a specific potential use case for this tool: interactive discovery and neutralization of gender bias in word embedding models, and compare this human-in-the-loop approach to reducing bias in word embeddings with a debiasing post-processing technique.
    Standort Signatur Erwartet Verfügbarkeit
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