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  • FIRE SERVICE LAW Supplement - Leadership Lessons in Law & American History

    Type:
    Document
    Description/Abstract:
    Modules to educate Officers in Officer I, II, III and Officer IV classes.
    Creator/Author:
    Bennett, Lawrence
    Submitter:
    Lawrence Bennett
    Date Uploaded:
    08/18/2020
    Date Modified:
    02/02/2026
    Date Created:
    2020-08
    License:
    Attribution-NonCommercial 4.0 International

  • Interdisciplinary Studies - Fire Service, Legal Issues & American History

    Type:
    Document
    Description/Abstract:
    American History text to be used in A&S Interdisciplinary Studies online courses.
    Creator/Author:
    Bennett, Lawrence
    Submitter:
    Lawrence Bennett
    Date Uploaded:
    10/24/2022
    Date Modified:
    02/02/2026
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • EMS LAW - LEGAL LESSONS LEARNED (3rd Edition)

    Type:
    Document
    Description/Abstract:
    Case summaries involving EMS cases.
    Creator/Author:
    Bennett, Lawrence
    Submitter:
    Lawrence Bennett
    Date Uploaded:
    07/10/2020
    Date Modified:
    01/29/2026
    Date Created:
    2020-07
    License:
    Attribution-NonCommercial 4.0 International

  • FIRE & EMS LAW - RECENT CASE SUMMARIES

    Type:
    Document
    Description/Abstract:
    Monthly newsletter for Fire and EMS.
    Creator/Author:
    Bennett, Lawrence
    Submitter:
    Lawrence Bennett
    Date Uploaded:
    11/02/2020
    Date Modified:
    01/29/2026
    Date Created:
    2020-11
    License:
    Attribution 4.0 International

  • Gas streetlights in Boston, Massachusetts

    Type:
    Document
    Description/Abstract:
    This historic document indicates the location of natural gas streetlights in the city of Boston, Massachusetts.
    Creator/Author:
    Townsend-Small, Amy
    Submitter:
    Amy Townsend-Small
    Date Uploaded:
    01/26/2026
    Date Modified:
    01/26/2026
    Date Created:
    1985-08-27
    License:
    Public Domain Mark 1.0

  • Boston gas streetlights

    User Collection
    Type:
    Collection
    Description/Abstract:
    Methane emissions and other environmental and historical information about natural gas streetlights in Boston, Massachusetts
    Creator/Author:
    Townsend-Small, Amy
    Submitter:
    Amy Townsend-Small
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)
    0Collections
    0Works

  • Artificial Intelligence Presentation University of Cincinnati

    Type:
    Generic Work
    Description/Abstract:
    This is the slide deck for the DTS Hands On Training.
    Creator/Author:
    Scherz, Thomas
    Submitter:
    Thomas Scherz
    Date Uploaded:
    01/13/2026
    Date Modified:
    01/13/2026
    Date Created:
    January 12, 2026
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • FIRE & EMS LAW – RECENT CURRENT EVENTS

    Type:
    Document
    Description/Abstract:
    CHAPTERS 1- 18: Supplement to Prof. Larry Bennett’s textbook, FIRE SERVICE LAW (SECOND EDITION), Jan. 2017:  http://www.waveland.com/browse.php?t=708 SEE ALSO RECENT PUBLISHED COURT DECISIONS [NOV. 2018-PRESENT] FOR 18 CHAPTERS: From Prof. Bennett’s Fire & EMS Law monthly newsletters [send him e-mail if wish to receive]  https://scholar.uc.edu/concern/documents/n870zs553?locale=en
    Creator/Author:
    Bennett, Lawrence
    Submitter:
    Lawrence Bennett
    Date Uploaded:
    07/27/2021
    Date Modified:
    01/11/2026
    Date Created:
    2021-07
    License:
    Attribution 4.0 International

  • Changing Support for Ukraine among the European Union (EU) Members after the Full-Scale Russian Invasion

    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. ENERGO: EU energy dependence on Russia as estimated 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). CNG_MIL -- change of net support for the financing of the purchase and supply of military equipment to Ukraine, Spring 2022-Spring 2025 CNG_FIN -- change of net support for the financing of support for Ukraine, Spring 2022-Spring 2025 CNG_HUM -- change of net support for providing humanitarian support for the people affected by the war, Spring 2022-Spring 2025 CNG_REF -- change of net support for welcoming in the EU people fleeing the war, Spring 2022-Spring 2025 AVCHNG: Difference in average change of the military, economic, humanitarian and refugee support for Ukraine Spring 2022-Spring 2025. 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) RENERGO1: 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) --------------- NB: File: "Dataset_UkrTime2yr.csv" contains data for the public support during the first two years (24 months) since the whole scale invasion of Ukraine, Spring 2022-Spring 2024 File"Dataset_UkrTime3yr.csv" contains data for the public support during the first three years (36 months) since the whole scale invasion of Ukraine, Spring 2022-Spring 2025
    Creator/Author:
    Ivanov, Ivan
    Submitter:
    Ivan Ivanov
    Date Uploaded:
    04/27/2025
    Date Modified:
    12/30/2025
    Date Created:
    5-01-2024
    License:
    All rights reserved

  • Advancements in automated nuclei segmentation for histopathology using you only look once-driven approaches

    Type:
    Article
    Description/Abstract:
    Histopathology image analysis plays a pivotal role in disease diagnosis and treatment planning, relying heavily on accurate nuclei segmentation for extracting vital cellular information. In recent years, artificial intelligence (AI) and in particular deep learning models have been applied successfully in solving computational pathology image analysis tasks. The You Only Look Once (YOLO) object detection framework, which is based on a convolutional neural network (CNN) architecture has gained traction across various domains for its real-time processing capabilities. This systematic review aims to comprehensively explore and evaluate the advancements, challenges, and applications of YOLO-based methodologies in nuclei segmentation within the domain of histopathological images. The review encompasses a structured analysis of recent literature, focusing on the utilization of YOLO variants for nuclei segmentation. Key methodologies, training strategies, dataset specifics, and performance metrics are evaluated to elucidate the strengths and limitations of YOLO in this context. Additionally, the review highlights the unique characteristics of YOLO that enable efficient object detection and delineation of nuclei structures, offering a comparative analysis against traditional segmentation approaches. This systematic review underscores the promising outcomes achieved through YOLO-based architectures, emphasizing their potential for accurate and rapid nuclei segmentation. Furthermore, it identifies persistent challenges such as handling variances in nuclei appearances, optimizing model architectures for histopathological images, and improving generalization across diverse datasets. Insights derived from this review can provide a foundation for future research directions and enhancements in nuclei segmentation methodologies using YOLO within histopathology, fostering advancements in disease diagnosis and biomedical research.
    Creator/Author:
    Debsarkar, Shyam
    Submitter:
    Shyam Debsarkar
    Date Uploaded:
    12/28/2025
    Date Modified:
    12/28/2025
    Date Created:
    March 25, 2025
    License:
    All rights reserved