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  • Views from the Window: Conveying Harmony Under Different Atmospheric Conditions in Camille Pissarro’s Boulevard Montmartre Series

    Type:
    Student Work
    Description/Abstract:
    The only artist to be featured at all eight Impressionist Exhibitions in Paris was Camille Pissarro. The Impressionist movement emerged during a period of rapid social change and growing industrialization with more people moving to cities. In Pissarro’s works, he specifically concentrated on the conditions of different weather and times of day to alter how he painted scenes of a city. My paper focuses on the Boulevard Montmartre series and his use of building tonal relationships and skill of lighting placement across the fourteen paintings in order to establish a harmonious composition where the day’s essence radiates off the canvas.
    Creator/Author:
    Reinhold, Emily
    Submitter:
    Emily Reinhold
    Date Uploaded:
    04/25/2023
    Date Modified:
    04/25/2023
    Date Created:
    2023-04-20
    License:
    Public Domain Mark 1.0

  • Force-displacement response of porcine meniscus under tensile-fracture behavior

    Type:
    Document
    Description/Abstract:
    This dataset details the force-displacement response of porcine meniscus under tensile-fracture behavior. Samples are cut from the anterior, middle and posterior regions of the meniscus. Each specimen geometry dimension is included.
    Creator/Author:
    Chia-Ying Lin; Kumar Vemaganti, and Long, Teng
    Submitter:
    Teng Long
    Date Uploaded:
    03/03/2023
    Date Modified:
    03/03/2023
    Date Created:
    2020-11
    License:
    Attribution 4.0 International

  • Employing Strategies to Address Implicit Racial Bias in the Home Visit Setting

    Type:
    Dataset
    Description/Abstract:
    Data from qualitative study "Employing Strategies to Address Implicit Racial Bias in the Home Visit Setting" Includes: written reflections by FM residents, resident focus group data, commitments-to-change, and 3-month follow up survey data
    Creator/Author:
    Goroncy, Anna
    Submitter:
    Anna Goroncy
    Date Uploaded:
    03/03/2023
    Date Modified:
    03/03/2023
    Date Created:
    2020-01
    License:
    Open Data Commons Attribution License (ODC-By)

  • Immersive Inclusion: Diversity and Inclusion Training Using Virtual Reality

    Type:
    Document
    Description/Abstract:
    An exploration of the use of virtual reality technology in the context of diversity and inclusion training. This manuscript describes two studies: Study 1 was longitudinal and investigated the impacts of a VR-based bias training. Cognitive and affective empathy levels and impact on behavior, attitude, and knowledge before and after the training were measured to test the hypotheses that (H1) cognitive empathy levels would increase and (H2) individuals with higher initial levels of empathy would demonstrate more pronounced changes in cognitive empathy following the training. H1 was supported but larger changes were found in affective empathy levels. H2 was also supported as individuals with higher initial empathy levels showed higher levels of cognitive empathy after the training compared to individuals with lower initial empathy levels. However, again, larger differences were found in affective empathy levels. Qualitative data revealed a lasting impact nine weeks after the training that was not present in the quantitative data. Study 2 surveyed healthcare professionals who previously participated in a VR-based DEI training that focused on social determinants of health and empathy in healthcare professionals. The purpose of this study was to gain insight into the longitudinal impacts of a VR-based DEI training by gathering qualitative data from the participants at least a year after they went through the training. The respondents reported a lasting influence from the training. Reasons for the discrepancy between the qualitative and quantitative results are discussed as are implications for organizations and future DEI training development and research.
    Creator/Author:
    Mason, Lauren
    Submitter:
    Lauren Mason
    Date Uploaded:
    02/08/2023
    Date Modified:
    02/08/2023
    Date Created:
    2022
    License:
    Attribution 4.0 International

  • Fighting Post-Tenure Fatigue: Reclaiming Your Time and Redefining Leadership

    Type:
    Document
    Description/Abstract:
    Fighting Post-Tenure Fatigue: Reclaiming Your Time and Redefining Leadership offers insights, strategies and personal examples of how the two mid-career librarians have managed to navigate academic librarianship as first-generation, BIPOC, cis-gendered women while also balancing parenthood on the road to achieving tenure. The chapter describes their bouts with post-tenure fatigue, a phenomenon familiar to many mid-career librarians. Early in their careers, academic librarians focus on fulfilling the requirements of the promotion process at their institution. These requirements often leave little room for personal fulfillment once day-to-day responsibilities and designated service requirements are met. This process can provoke feelings of stress and anxiety as they struggle to find their footing within the institution, and the larger areas of librarianship and academia. Most institutions provide a support system and other mentorship for professional growth and career development. Achieving promotion and/or tenure is an accomplishment to be celebrated and followed by a sigh of relief. However, in the days, months, and years afterward, tenured librarians can start feeling a lack of motivation, support, and career guidance. They often struggle to answer the question, “What next?” The co-authors will highlight strategies for dealing with this kind of post-tenure burnout. One strategy for mid-career librarians is to be intentional about how one wants to spend their time. Day-to-day responsibilities and leadership expectations tend to increase exponentially the longer one stays in a position. Therefore, mid-career librarians need to learn when and how to say no in some cases, in order to say yes to other possibilities. Readers will be encouraged to look beyond their core responsibilities and think about expanding their time into areas like strategizing, skill building, acting creatively, and strengthening relationships. The chapter will include questions the reader can use to reflect on how they are spending their time, as well as tips for examining and adjusting their time to align with their intentions. Another strategy for mid-career librarians is to take advantage of unexpected leadership opportunities. Rather than looking for a new position with formal leadership responsibilities, one can develop leadership skills by leading projects inside and outside of their institution. Examples include participating in initiatives with specific goals or professional service in the form of short-term committees. The chapter will include questions the reader can use to examine opportunities for new leadership roles. To illustrate these strategies, the co-authors will share their experience using the mid-career point as an inspiration to invest time into the BIPOC in LIS community. Through service on the ALA Spectrum Advisory Committee, the co-authors were able to lead projects, establish virtual networking events, support new librarians, and experience professional growth. As a result of this work, they were also introduced to new opportunities and professional relationships. This experience models how one can be more intentional about time and energy and grow leadership skills without changing jobs and moving into a leadership or management position.
    Creator/Author:
    Lam, Nia; McKinney, Michelle; West, Brandon K. (editor), and Galoozis, Elizabeth (editor)
    Submitter:
    Michelle McKinney
    Date Uploaded:
    01/24/2023
    Date Modified:
    05/16/2023
    Date Created:
    2023-01-06
    License:
    Attribution-NonCommercial-NoDerivs 4.0 International

  • Wireless Sensor Monitoring Water Use at Fixtures

    Type:
    Dataset
    Description/Abstract:
    The Dataset contains raw data that indicates the start and stop time of water flowing at fixtures in the Marian Spencer Hall Cafeteria restroom during hours of operation. The data were collected as part of an effort to develop and test a novel method of measuring flow to calculate the probability that the fixture is busy (fixture p-value). The fixture p-value is one of the parameters necessary to predict peak demand in buildings for pipe sizing purposes. There are two .csv files, a README file and a sample of the data collection template with contact information. The dataset also contains a MATLAB code written to accept data in the suggested format and estimate the fixture probability of use.
    Creator/Author:
    Choudhary, Chandrashekhar ; Omaghomi, Toju; Buchberger, Steven; Wang, Tianshuo, and Tao, Li
    Submitter:
    Toju Omaghomi
    Date Uploaded:
    12/19/2022
    Date Modified:
    12/19/2022
    Date Created:
    2022-12
    License:
    Open Data Commons Open Database License (ODbL)

  • Coherence_Evaluations - nvl_pollution.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/12/2022
    Date Modified:
    11/12/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_earth.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/12/2022
    Date Modified:
    11/12/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_climate.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/12/2022
    Date Modified:
    11/12/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_environmental.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/12/2022
    Date Modified:
    11/12/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • TV News Transcripts of Outer Space Coverage

    Type:
    Dataset
    Description/Abstract:
    Text and Metadata for 14,399 newspaper articles. Transcripts collected from Internet Archive Date Range: 2010-2022 File includes meta/data: - Unique-id (uid) - Title (incl. search term) - Date - Link (url) - Abstract - Text Text matching the following terms: - space explor* - space mission - space science - spaceship - space tour* - space transport* - spacecraft - space shuttle - outer space - astronom* - astrop* - astrona* - planet - NASA - star trek - star wars - lunar - space flight
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/12/2022
    Date Modified:
    11/12/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Newspaper coverage of Outer Space Theme

    Type:
    Dataset
    Description/Abstract:
    Text and Metadata for 9,061 newspaper articles. Newspapers included: New York Times, Wall Street Journal, & Washington Post Date Range: 2017-2022 File includes meta/data: - Unique-id (uid) - Title (incl. source paper & section name) - Date - Link (url) - Author - Text Text matching the following terms: - space explor* - space mission - space science - spaceship - space tour* - space transport* - spacecraft - space shuttle - outer space - astronom* - astrop* - astrona* - planet - NASA - star trek - star wars - lunar - space flight
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/12/2022
    Date Modified:
    11/12/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_random5k.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/05/2022
    Date Modified:
    11/11/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - pmc_environmental.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/04/2022
    Date Modified:
    11/04/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - pmc_earth.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/04/2022
    Date Modified:
    11/04/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nws_environmental.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/04/2022
    Date Modified:
    11/04/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nws_random5k.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/04/2022
    Date Modified:
    11/04/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nws_pollution.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/03/2022
    Date Modified:
    11/17/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nws_earth.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/03/2022
    Date Modified:
    11/03/2022
    Date Created:
    2022
    License:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nws_climate.csv

    Type:
    Dataset
    Description/Abstract:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creator/Author:
    McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    11/02/2022
    Date Modified:
    11/02/2022
    Date Created:
    2022
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)