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  • Data to accompany “Monarch butterflies (Danaus plexippus) only use magnetic cues for migratory directionality with orientation re-calibrated by coldness”

    Type:
    Dataset
    Description/Abstract:
    Data on orientation angle for fall migratory monarch butterflies exposed to experimental magnetic conditions north of, at, and south of their overwintering sites in Mexico. Additional orientation data for butterflies consistently exposed to either fall-like or colder temperatures.
    Creator/Author:
    Matter, Stephen F.
    Submitter:
    Stephen F. Matter
    Date Uploaded:
    05/21/2025
    Date Modified:
    05/21/2025
    Date Created:
    2024
    License:
    Attribution-NonCommercial-ShareAlike 4.0 International

  • Varieties of International Cyber Strategies (VoICS): Text Analysis of National Cybersecurity Documents

    Type:
    Dataset
    Description/Abstract:
    Varieties of International Cyber Strategies (VoICS): Text Analysis of National Cybersecurity Documents is a project that compares and contrasts the three main approaches to conceptualize national cybersecurity strategies (NSS): deterrence, norm-based approach (NBA) and cyber persistence engagement (CPE). Scholars and policymakers have initially conceptualized NSS in terms of deterrence or NBA. More recent academic research has demonstrated that these frameworks are inadequate for cyber space. As a result, Cyber Persistence Engagement (CPE) emerged as a third option. The first version (1.0) of the VoICS database on National Cybersecurity Strategies focuses on nations in Europe and North America and includes a total of 77 NCS of the states in the North Atlantic Area—NATO allies, EU members and Switzerland—released from 2003 until the end of 2023. It consists of 27 variables, including country and strategy identifiers, EU and NATO membership, their respective accession dates, and total length of the documents. VoICS include eighteen variables representing different measures of relative and absolute weights of the three NSS types—deterrence, NBA and CPE. The text analysis is based on official NSS documents provided by the NATO Cooperative Cyber Defence Centre of Excellence library (2024) and ENISA’s interactive map for National Cyber Security Strategies (2023). Both sources rely on voluntary submission from the member states. Unfortunately, some official documents were not available or accessible or were not listed at all. Authors have used various sources and contacts with a variety of cyber attachés in Brussels to determine if any additional strategies were released and to obtain the missing documents. The 18 text analysis variables compare and contrast the extent to which different NCS are associated with a specific strategy. They represent different frequency scores based either on words, phrases, or words and phrases combined. These calculations are associated with either deterrence, NBA, or CPE in each strategy. The authors have generated respective vocabularies for the three strategic ideas through which each of these approaches are operationalized. We have conducted a text analysis using WordStat text analysis software by Provialis ( https://provalisresearch.com/products/content-analysis-software/). A detailed codebook for NSS Dataset 1.0 along with a NSS Dictionary 1.0 have been included in this collection/ repository. The process of generating vocabulary associated with the three cybersecurity approaches involved several steps. First, upon reviewing the literature, the authors generated independently a list of words and phrases associated with each type of cybersecurity strategy. Second, the authors compared their lists to determine the degree of overlap in vocabulary. Those words and phrases that included in at least two different lists were reviewed and, if there was consensus, were incorporated in the dictionary. Finally, words and phrases which were identified in only one of lists were once again reviewed and, in case there was a consensus among the authors, these were also included in the dictionary. Third, the three vocabularies were updated on several instances when it was unanimously agreed that these words or phrases should be included in the analysis.
    Creator/Author:
    Millard, Matthew; Kovac, Igor, and Ivanov, Ivan Dinev
    Submitter:
    Ivan Ivanov
    Date Uploaded:
    05/12/2025
    Date Modified:
    05/12/2025
    Date Created:
    2025-04-18
    License:
    All rights reserved

  • Changing Support among European Union (EU) Members for the War in Ukraine

    Type:
    Dataset
    Description/Abstract:
    This is a dataset generated as a part of a research project studying the changing support among European Union (EU) members for the war in Ukraine. The dataset contains a number of conditions (variables) used to conduct fuzzy-set qualitative comparative analysis (fsQCA) to test five critical conditions that have shaped the change in public opinion that include economic growth, democratic rule, distance from the front lines, level of energy dependence from Russia and trust in social media. These conditions (or variables) include: Num: Case number in the row MEMBR: EU member state two or three-letter abbreviation WEALTH: GDP per capita in Euro (measured in purchasing power parties) as reported by Eurostat GROWTH: GDP growth in volume based on seasonally adjusted data by Eurostat DEMOCR: the overall score for each EU member’s democracy index for 2022. Data have been drawn from the Economist Intelligence Unit (EIU) 2022 report DISTAN: an average distance (in thousand kilometers) from the geographic center point of the national capital of each EU member-state to the south-western and north-eastern tips of the frontline of the war in Ukraine. I have accepted that the western tip of the frontline is Kinburnsʹka Kosa National Park (Geographic Coordinates: 46°34’37”N 31°30’44”E) and the eastern tip of the frontline is at the village of Topoli in Kharkiv Oblast (Geographic Coordinates: 49°57’52″N, 37°54′31″E). TRADE: volume of trade with Russia per capita in thousand of US Dollars. ENERGY: EU energy dependence on Russia as estmated by the European Commission (from 0 to 100 percent) for 2020. Source: Eurostat. GOVTR: Net trust in national government (difference between the sum of fully trust and partially trust responses and fully distrust and partially distrust responses). MEDIATR: Net trust in social media (difference between the sum of fully trust and partially trust responses and fully distrust and partially distrust responses). ECONSAN: Difference in support for economic sanctions on Russia, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with economic sanctions and partially disagree and totally disagree with sanctions responses). EQUIPS: Difference in support for financial support for providing military equipment for Ukraine, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with financial support for equipment and partially disagree and totally disagree with support for equipment). HUMSAN: Difference in support for humanitarian support for Ukrainians fleeing the war, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with humanitarian support for Ukrainians and partially disagree and totally disagree with humanitarian support for Ukrainians). REFUG: Difference in support for welcoming Ukrainian refugees, Spring 2022-Spring 2024 (difference between the sum of tend to agree and totally agree with welcoming Ukrainian and partially disagree and totally disagree with welcoming Ukrainian refugees). AVCHNG: Difference in average change of the support for Ukraine and economic sanctions on Russia, Spring 2022-Spring 2024. WEALTH1: Calibrated score for national wealth (see paper for details) GROWT1: Calibrated score for economic growth (see paper for details) DEMOCR1: Calibrated score for democracy (see paper for details) DISTAN1: Calibrated score for distance (see paper for details) TRADE1: Calibrated score for trade (see paper for details) RENERG1: Calibrated score for energy dependence (see paper for details) GOVTR1: Calibrated score for trust in governance (see paper for details) RMEDIATR1: Calibrated score for trust in social media (see paper for details) ECONSAN1: Calibrated score for support for economic sanctions on Russia (see paper for details, calibration the same as AVCHNG3) MDIASAN1: Calibrated score for media sanctions on Russia (see paper for details, calibration the same as AVCHNG3) AVCHNG3: Calibrated score for average change/ decline for public opinion (see paper for details)
    Creator/Author:
    Ivanov, Ivan
    Submitter:
    Ivan Ivanov
    Date Uploaded:
    04/27/2025
    Date Modified:
    04/27/2025
    Date Created:
    5-01-2024
    License:
    All rights reserved

  • ecology-and-evolution-2025-data

    Type:
    Dataset
    Description/Abstract:
    Raw data for: Siers, S.R., Mungaray, J.-C., Kastner, M. & Jayne, B.C. (2025) Hard to swallow: scaling relationships between the size of avian prey and the overall size and maximal gape of brown treesnakes. Ecology and Evolution (in revision). (BCJ corresponding author)
    Creator/Author:
    Jayne, Bruce
    Submitter:
    Bruce Jayne
    Date Uploaded:
    04/02/2025
    Date Modified:
    04/02/2025
    Date Created:
    2025-04-02
    License:
    Open Data Commons Attribution License (ODC-By)

  • Monarch butterflies (Danaus plexippus) only use magnetic cues for migratory directionality with orientation re-calibrated by coldness - data file

    Type:
    Dataset
    Description/Abstract:
    Data of monarchs subjected to righting response orientation trials under different artificial magnetic fields pre- and post-overwintering cold treatment.
    Creator/Author:
    Shively-Moore, Samuel
    Submitter:
    Samuel Shively-Moore
    Date Uploaded:
    03/25/2025
    Date Modified:
    05/21/2025
    License:
    Attribution-NonCommercial 4.0 International

  • methane emissions from natural gas streetlights in Cincinnati, Ohio

    Type:
    Dataset
    Description/Abstract:
    Methane emissions from natural gas streetlights. Measurements were made by Dr. Amy Townsend-Small and her students.
    Creator/Author:
    Townsend-Small, Amy
    Submitter:
    Amy Townsend-Small
    Date Uploaded:
    11/20/2024
    Date Modified:
    11/20/2024
    Date Created:
    2024-11-20
    License:
    Public Domain Mark 1.0

  • locations of natural gas streetlights in Cincinnati

    Type:
    Dataset
    Description/Abstract:
    Locations of natural gas streetlights in Cincinnati, Ohio
    Creator/Author:
    Townsend-Small, Amy
    Submitter:
    Amy Townsend-Small
    Date Uploaded:
    11/20/2024
    Date Modified:
    11/20/2024
    Date Created:
    2024-11-20
    License:
    Public Domain Mark 1.0

  • Goff MS Thesis Data and Code Chapter 1

    Type:
    Dataset
    Description/Abstract:
    Data and code for analysis of thermal constraints on flight for butterflies
    Creator/Author:
    Goff, Jennifer and Matter, Stephen F.
    Submitter:
    Stephen F. Matter
    Date Uploaded:
    09/01/2024
    Date Modified:
    09/01/2024
    Date Created:
    2024-6
    License:
    Attribution-NonCommercial 4.0 International

  • Senior Project, Book

    Type:
    Document
    Description/Abstract:
    Forest settings can provide emotional and physical stimulation that can effectively calm the nervous system and regulate responses to the effects of trauma. By exposing a population to a nearby temperate forest, measures can be made regarding the overall reaction to being in the presence of a forest specific environment. It is expected that the response to the experiences of forest engagement and exposure will present positive and increase the overall well-being of participants.
    Creator/Author:
    Adams, Margaret
    Submitter:
    Margaret Adams
    Date Uploaded:
    04/04/2024
    Date Modified:
    04/04/2024
    Date Created:
    04/4/2024
    License:
    All rights reserved

  • Modelling sex roles in animals using life-history traits and population characteristics

    Type:
    Student Work
    Description/Abstract:
    Code for modelling sex roles in animals using life-history traits and population characteristics.
    Creator/Author:
    Samuel, Justine
    Submitter:
    Justine Samuel
    Date Uploaded:
    11/07/2023
    Date Modified:
    11/07/2023
    License:
    All rights reserved