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  1. Article: COVID-19 related TV news and stock returns: Evidence from major US TV stations.

    Möller, Rouven / Reichmann, Doron

    The Quarterly review of economics and finance : journal of the Midwest Economics Association

    2022  Volume 87, Page(s) 95–109

    Abstract: We investigate a novel dataset of more than half a million 15 seconds transcribed audio snippets containing COVID-19 mentions from major US TV stations throughout 2020. Using the Latent Dirichlet Allocation (LDA), an unsupervised machine learning ... ...

    Abstract We investigate a novel dataset of more than half a million 15 seconds transcribed audio snippets containing COVID-19 mentions from major US TV stations throughout 2020. Using the Latent Dirichlet Allocation (LDA), an unsupervised machine learning algorithm, we identify seven COVID-19 related topics discussed in US TV news. We find that several topics identified by the LDA predict significant and economically meaningful market reactions in the next day, even after controlling for the general TV tone derived from a field-specific COVID-19 tone dictionary. Our results suggest that COVID-19 related TV content had nonnegligible effects on financial markets during the pandemic.
    Language English
    Publishing date 2022-12-05
    Publishing country United States
    Document type News
    ISSN 1062-9769
    ISSN 1062-9769
    DOI 10.1016/j.qref.2022.11.007
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Automatic and Online Pollen Monitoring.

    Oteros, Jose / Pusch, Gudrun / Weichenmeier, Ingrid / Heimann, Ulrich / Möller, Rouven / Röseler, Stefani / Traidl-Hoffmann, Claudia / Schmidt-Weber, Carsten / Buters, Jeroen T M

    International archives of allergy and immunology

    2015  Volume 167, Issue 3, Page(s) 158–166

    Abstract: Background: Pollen are monitored in Europe by a network of about 400 pollen traps, all operated manually. To date, automated pollen monitoring has only been feasible in areas with limited variability in pollen species. There is a need for rapid ... ...

    Abstract Background: Pollen are monitored in Europe by a network of about 400 pollen traps, all operated manually. To date, automated pollen monitoring has only been feasible in areas with limited variability in pollen species. There is a need for rapid reporting of airborne pollen as well as for alleviating the workload of manual operation. We report our experience with a fully automated, image recognition-based pollen monitoring system, BAA500.
    Methods: The BAA500 sampled ambient air intermittently with a 3-stage virtual impactor at 60 m3/h in Munich, Germany. Pollen is deposited on a sticky surface that was regularly moved to a microscope equipped with a CCD camera. Images of the pollen were constructed and compared with a library of known samples. A Hirst-type pollen trap was operated simultaneously.
    Results: Over 480,000 particles sampled with the BAA500 were both manually and automatically identified, of which about 46,000 were pollen. Of the automatically reported pollen, 93.3% were correctly recognized. However, compared with manual identification, 27.8% of the captured pollen were missing in the automatic report, with most reported as unknown pollen. Salix pollen grains were not identified satisfactorily. The daily pollen concentrations reported by a Hirst-type pollen trap and the BAA500 were highly correlated (r = 0.98).
    Conclusions: The BAA500 is a functional automated pollen counter. Its software can be upgraded, and so we expected its performance to improve upon training. Automated pollen counting has great potential for workload reduction and rapid online pollen reporting.
    MeSH term(s) Air Pollutants/analysis ; Air Pollutants/immunology ; Allergens/analysis ; Allergens/immunology ; Automation ; Environmental Monitoring/instrumentation ; Environmental Monitoring/methods ; Germany ; Humans ; Pollen/anatomy & histology ; Pollen/immunology ; Reproducibility of Results
    Chemical Substances Air Pollutants ; Allergens
    Language English
    Publishing date 2015
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1108932-5
    ISSN 1423-0097 ; 1018-2438
    ISSN (online) 1423-0097
    ISSN 1018-2438
    DOI 10.1159/000436968
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Uh III Zs.155: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  3. Article: Automatic and Online Pollen Monitoring

    Oteros, Jose / Pusch, Gudrun / Weichenmeier, Ingrid / Heimann, Ulrich / Möller, Rouven / Röseler, Stefani / Traidl-Hoffmann, Claudia / Schmidt-Weber, Carsten / Buters, Jeroen T.M.

    International Archives of Allergy and Immunology

    2015  Volume 167, Issue 3, Page(s) 158–166

    Abstract: Background: Pollen are monitored in Europe by a network of about 400 pollen traps, all operated manually. To date, automated pollen monitoring has only been feasible in areas with limited variability in pollen species. There is a need for rapid reporting ...

    Institution ZAUM, Center of Allergy & Environment, Helmholtz Zentrum München UNIKA-T, Klinikum rechts der Isar, Technische Universität München, Munich Department of Dermatology, Universitätsklinikum Aachen, Aachen Helmut Hund GmbH, Wetzlar, and Outpatient Clinic for Environmental Medicine, Klinikum Augsburg, Augsburg, Germany CK-CARE, Christine Kühne Center for Allergy Research and Education, Davos, Switzerland
    Abstract Background: Pollen are monitored in Europe by a network of about 400 pollen traps, all operated manually. To date, automated pollen monitoring has only been feasible in areas with limited variability in pollen species. There is a need for rapid reporting of airborne pollen as well as for alleviating the workload of manual operation. We report our experience with a fully automated, image recognition-based pollen monitoring system, BAA500. Methods: The BAA500 sampled ambient air intermittently with a 3-stage virtual impactor at 60 m3/h in Munich, Germany. Pollen is deposited on a sticky surface that was regularly moved to a microscope equipped with a CCD camera. Images of the pollen were constructed and compared with a library of known samples. A Hirst-type pollen trap was operated simultaneously. Results: Over 480,000 particles sampled with the BAA500 were both manually and automatically identified, of which about 46,000 were pollen. Of the automatically reported pollen, 93.3% were correctly recognized. However, compared with manual identification, 27.8% of the captured pollen were missing in the automatic report, with most reported as unknown pollen. Salix pollen grains were not identified satisfactorily. The daily pollen concentrations reported by a Hirst-type pollen trap and the BAA500 were highly correlated (r = 0.98). Conclusions: The BAA500 is a functional automated pollen counter. Its software can be upgraded, and so we expected its performance to improve upon training. Automated pollen counting has great potential for workload reduction and rapid online pollen reporting.
    Keywords Aerobiology ; Pollen ; Air quality ; Automation ; Environmental monitoring
    Language English
    Publishing date 2015-08-19
    Publisher S. Karger AG
    Publishing place Basel, Switzerland
    Document type Article
    Note Original Paper
    ZDB-ID 1108932-5
    ISSN 1423-0097 ; 1018-2438
    ISSN (online) 1423-0097
    ISSN 1018-2438
    DOI 10.1159/000436968
    Database Karger publisher's database

    Full text online

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Uh III Zs.155: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

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