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Minutes: Student Government Association, January 16, 2025
No full textUniversity of Minnesota Duluth. Student Government Association. (2025). Minutes: Student Government Association, January 16, 2025. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/276123
Autobiografía, dictadura y enseñanza de la literatura uruguaya del siglo XXI
No full textSosa San Martín, Gabriela. (2025). Autobiografía, dictadura y enseñanza de la literatura uruguaya del siglo XXI. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/276441
MidwestET-500: Upscaled Daily Evapotranspiration Estimates for the U.S. Midwest (2019–2024)
No full textEach contains a detailed description within attributes section.MidwestET-500 is a daily 500 m resolution evapotranspiration (ET) dataset covering the U.S. Upper Midwest (36°N–49°N, −104°W to −82°W) from 2019 to 2024. It was generated using a knowledge-guided LightGBM model trained on eddy covariance data, meteorology, and remote sensing inputs. The model integrates physically informed features, including Penman–Monteith components, and was validated via stratified GroupKFold to ensure robust generalization across space and time. MidwestET-500 shows strong agreement with OpenET ensemble data (r = 0.95) and independent Penman–Monteith estimates (r = 0.90). The dataset is released in NetCDF4 format and is intended to support applications in irrigation planning, drought monitoring, and regional water modeling. All model code and preprocessing workflows are openly available to promote reproducibility.The project was supported by LEGISLATIVE-CITIZEN COMMISSION ON MN RES (LCCMR) ENRTF 2021-266. Award: CON000000089352Rozanov , Aleksei; Subedi, Samikshya; Sharma, Vasudha; Runck, Bryan. (2025). MidwestET-500: Upscaled Daily Evapotranspiration Estimates for the U.S. Midwest (2019–2024). Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/37xe-qq18
“Do they love us? Do they hate us?”: Examining nonprofits’ perspectives on their relationships with professional sport organizations
No full textUniversity of Minnesota M.S. thesis. May 2025. Major: Kinesiology. Advisor: Dunja Antunovic. 1 computer file (PDF); v, 93 pages.Professional sport organizations are increasingly engaging in corporate social responsibility initiatives within their local communities. While literature has examined why professional sport organizations work with nonprofits, the beneficiaries of these partnerships tend to be dismissed from the literature. Even though professional sport organizations and nonprofit organizations share a reciprocal relationship, scholarship tends to solely focus on the perspectives of just the professional sport organizations. Therefore, the purpose of this study was to allow nonprofit organizations to share their experiences and perceptions based upon their relationships with professional sporting organizations, and to examine what unique benefits and challenges nonprofit organizations encounter by partnering with professional sport organizations. Drawing on the collaboration continuum, the current study accounted for the (de)evolution of relationships between nonprofit organizations and professional sport organizations over time. Semi-structured interviews were conducted with 26 nonprofit practitioners who have collaborated with professional sport organizations in the United States. Thematic analysis of each interview was conducted to find commonalities between nonprofit organizations’ perspectives. The findings indicate that while nonprofit organizations across all three stages of the collaboration continuum value their relationship with professional sport organizations, they hope that professional sport organizations adjust their utilization of their unique resources to better fit the specific needs of nonprofit organizations.Soltis, Kim. (2025). “Do they love us? Do they hate us?”: Examining nonprofits’ perspectives on their relationships with professional sport organizations. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/275837
Aligning human and AI systems: framework, algorithm design and applications in large language models
No full textUniversity of Minnesota Ph.D. dissertation. May 2025. Major: Electrical/Computer Engineering. Advisor: Mingyi Hong. 1 computer file (PDF); xi, 168 pages.Aligning artificial intelligence (AI) systems with human values is essential to unlocking their full potential while ensuring ethical and equitable outcomes. As AI systems become increasingly integrated into our lives, it is crucial that they not only perform tasks effectively but also align with human preferences and values. This alignment helps prevent harm, mitigates biases, and ensures that AI systems serve humanity responsibly. My thesis develops a comprehensive framework of inverse reinforcement learning (IRL), which focuses on learning from the demonstration dataset. For my thesis work in inverse reinforcement learning, I will discuss problem formulation, algorithm design, theoretical analysis and also application of aligning large language models with demonstration dataset through IRL. The thesis is structured into four technical chapters (Chapter 2 to Chapter 5). The second chapter addresses the theoretical foundations of AI alignment, focusing on the inverse reinforcement learning (IRL) problem. IRL seeks to infer a reward function from expert demonstrations, which can then guide an agent's behavior. We propose novel IRL algorithms capable of learning from both expert demonstrations and online interactions with the environment, providing theoretical guarantees for convergence and optimality under specific conditions.The third chapter explores the challenges of IRL in scenarios where only offline datasets are available. We identify limitations in existing IRL approaches and introduce a new method tailored for offline learning. Theoretical guarantees for this approach are established, and its effectiveness is demonstrated through experiments on various tasks. The fourth chapter discusses the connection between the proposed algorithms and existing methods in the literature, which provides a foundational understanding of the theoretical underpinnings of our work. Moreover, the fourth chapter discuss how to combine the proposed algorithms with existing methods in the literature, highlighting the potential for leveraging complementary strengths to enhance AI alignment. The fifth chapter transitions to practical applications, focusing on aligning large language models (LLMs) with inverse reinforcement learning training pipelines. We adapt the proposed IRL algorithm to train LLMs, showcasing its effectiveness through extensive experiments. Additionally, we discuss the challenges, limitations, and future directions for research in AI alignment and reinforcement learning. The thesis concludes by summarizing the key contributions and findings throughout my PhD journey, emphasizing the importance of reinforcement learning in AI alignment and the need for continued research in this area.Zeng, Siliang. (2025). Aligning human and AI systems: framework, algorithm design and applications in large language models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/275937
Minutes: Senate Committee on Academic Freedom and Tenure: April 25, 2025
No full textIn these minutes: Discussion of Unit Events and Communication Challenges; Post Tenure Review Discussion; Collegiate Personnel Plans and Long-term Appointments JustificationsUniversity of Minnesota: Senate Committee on Academic Freedom and Tenure. (2025). Minutes: Senate Committee on Academic Freedom and Tenure: April 25, 2025. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/273670
To Hunt, Fish, and Gather: Off-reservation Tribal reserved rights and the Clean Water Act
No full textThe Environmental Protection Agency published the 2024 Tribal Reserved Rights rule to ensure states consider Federal Tribes’ off-reservation rights during triennial reviews of Water Quality Standards. The rule was notable for its acknowledgment of Traditional Ecological Knowledge. Given this milestone in a complex history of state, federal, and tribal relations regarding water resource management, we were motivated to conduct a retrospective analysis of how states have historically engaged with tribes. We analyzed the last 10-15 years of triennial water quality standard reviews in the U.S. states of Michigan, Minnesota, and Wisconsin. We investigated three research questions:
1. How do states differentially engage with tribes?
2. How are tribal water quality concerns represented in state responses?
3. How has Traditional Ecological Knowledge been considered?
We found that the prioritization and recognition of Tribal concerns increased over time, according to review documents. However, treaties, off-reservation rights, Tribal subsistence use, and Traditional Ecological Knowledge were rarely mentioned. Tribal contaminant exposure was sometimes discussed, but actions were often low priority or delayed. States typically summarized concerns and did not always list authors, making it difficult to assess Tribal concerns. We found no evidence of Tribal consultation or state-engagement with Tribes holding rights outside state boundaries. Our findings affirm that the rule fills an important regulatory gap. However, it has limitations. To fulfill the intent of the rule and recognize Tribal sovereignty, we recommend: (1) building trust through transparent governance; (2) conducting state-Tribal consultation to streamline review processes; and (3) co-designing work plans for areas with reserved rights.Nichols, Rachel. (2025). To Hunt, Fish, and Gather: Off-reservation Tribal reserved rights and the Clean Water Act. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/276447
Data for 3D Printed Alumina
No full textData for the paper "3D printed alumina as a millimeter-wave optical element"
UCSB data is experimental transmission/reflection data for the alumina. HFSS is simulation data for both one and two sided alumina.Experimental and simulation data for the "3D printed alumina as a millimeter-wave optical element" paper, showcasing the transmission and reflection through the 3D printed anti-reflection piece.Lam, Rex; Cray, Scott; Dietterich, Samuel; Firth, Calvin; Hanany, Shaul; Izawa, Takumi; Koch, Jurgen; Konishi, Kuniaki; Matsumura, Tomotake; Sakurai, Haruyuki; Sakurai, Yuki; Takaku, Ryota; Yan, Andrew. (2025). Data for 3D Printed Alumina. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://hdl.handle.net/11299/276524
Episode 186: Chaos Reigns
No full textRuntime 01:04:49In "Chaos Reigns," Dr. Osterholm and Chris Dall discuss this week's ACIP meeting, the latest COVID variant data, and the current measles trends in the United States and Canada. Dr. Osterholm covers some good news about federal health agencies and answers an ID query about autism.Osterholm, Michael; Dall, Chris. (2025). Episode 186: Chaos Reigns. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/276471
Minutes: Senate Committee on Educational Policy: February 12, 2025
No full textIn these minutes: Core Curriculum; Enrollment Update; Inclusive Calendar Resolution, AI Syllabus Language Committee; Next Steps on Tutoring ResourcesUniversity of Minnesota: Senate Committee on Educational Policy. (2025). Minutes: Senate Committee on Educational Policy: February 12, 2025. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/273784