DIGITAL 357 / FTVM 366: Networked Disability Cultures Course Syllabus

Taught by David Adelman, this course presented a theoretical survey of online environments and infrastructures, covering a wide variety of networked media-from podcasts and documentary film to social media platforms and digital zines. The quarter culminated in a collaborate project that invites our class to critically and creatively reflect on local histories of access, technology, and disability culture. (note: David Adelman’s effort for this course in Winter 2024 was partially funded by the Mozilla Foundation)http://deepblue.lib.umich.edu/bitstream/2027.42/192776/1/Adelman, DIGITAL 357 FTVM 366, 2024_Redacted.pdfc4321027-eaa6-44f5-a298-a6880ec181d5Description of Adelman, DIGITAL 357 FTVM 366, 2024_Redacted.pdf : Course SyllabusSEL

Changes in adipose tissue macrophages and T cells in aging.

Adipose tissue historically was believed to be an inert tissue, functioning primarily in the storage of energy and thermal homeostasis. However, recent discoveries point toward a critical role for adipocytes in endocrine function as well as immune regulation. Excess body fat, accumulated through aging and/or a calorie-rich diet, is associated with many chronic metabolic and inflammatory diseases. Within the stromal vascular fraction of adipose tissue, macrophages and T cells accumulate with increasing tissue mass, secreting pro- or anti-inflammatory cytokines. In this review we discuss the current understanding of immune cell function in both diet-induced and age-related obesity. In both models of obesity, the classically activated, pro-inflammatory (M1) subtype takes precedence over the alternatively activated, anti-inflammatory (M2) macrophages, causing tissue necrosis and releasing pro-inflammatory cytokines like interleukin-6. Other distinct adipose tissue macrophage subtypes have been identified by surface marker expression and their functions characterized. Adipose tissue T cell recruitment to adipose tissue is also different between aging- and diet-induced obesity. Under both conditions, T cells exhibit restricted T-cell receptor diversity and produce higher levels of pro-inflammatory signals like interferon-γ and granzyme B relative to young or healthy mice. However, numbers of regulatory T cells are dramatically different between the 2 models of obesity. Taken together, these findings suggest models of age- and diet-induced obesity may be more distinct than previously thought, with many questions yet to be resolved in this multidimensional disease. © 2014 Begell House, Inc.http://deepblue.lib.umich.edu/bitstream/2027.42/193097/2/nihms516202.pdfPublished versio

Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data

Final ReportLearning Naturalistic Driving Environment CodeLearning Naturalistic Driving Environment DataFor simulation to be an effective tool for the development and testing of autonomous vehicles, the simulator must be able to produce realistic safety-critical scenarios with distribution-level accuracy. However, due to the high dimensionality of real-world driving environments and the rarity of long-tail safety-critical events, how to achieve statistical realism in simulation is a long-standing problem. In this project, we develop NeuralNDE, a deep learning-based framework to learn multi-agent interaction behavior from high-resolution vehicle trajectory data, and propose a conflict critic model and a safety mapping network to refine the generation process of safety-critical events, following real-world occurring frequencies and patterns. The results show thatNeuralNDE can achieve both accurate safety-critical driving statistics (e.g., crash rate/type/severity and near-miss statistics, etc.)and normal driving statistics (e.g., vehicle speed/distance/yielding behavior distributions, etc.), as demonstrated in the simulation of urban driving environments.U.S. Department of Transportation Office of the Assistant Secretary for Research and Technology (O-STR)http://deepblue.lib.umich.edu/bitstream/2027.42/192512/1/Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data Final Report [Accessible].pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/192512/2/Learning Naturalistic Driving Environment Code.ziphttp://deepblue.lib.umich.edu/bitstream/2027.42/192512/3/Learning Naturalistic Driving Environment Data.zipd520799f-6680-473f-9234-2ec9840d05bbDescription of Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data Final Report [Accessible].pdf : Final ReportDescription of Learning Naturalistic Driving Environment Code.zip : Learning Naturalistic Driving Environment CodeDescription of Learning Naturalistic Driving Environment Data.zip : Learning Naturalistic Driving Environment Dat

Controls on the photochemical production of hydrogen peroxide in arctic surface waters

Photochemical production of hydrogen peroxide (H2O2) from chromophoric/colored dissolved organic matter (CDOM) is a major source of H2O2 in natural waters. In a rapidly warming Arctic, H2O2 may increase due to thawing permafrost soils that are expected to export more CDOM to sunlit surface waters. At the same time, arctic surface waters are increasingly ice-free and thus exposed to sunlight for greater lengths of time during the summer. Thus, it has been hypothesized that photochemical production of H2O2 and H2O2 concentrations may increase in arctic surface waters. Testing this hypothesis requires determination of whether H2O2 production by CDOM is limited by CDOM concentration (substrate-limited) or by sunlight (light-limited). In waters with high concentrations of CDOM, H2O2 production may be limited by the sunlight reaching the water. In waters with low concentrations of CDOM, H2O2 production may be limited by CDOM concentration. This study quantified the substrate and light limitation of H2O2 production in surface waters of the Alaskan Arctic in summer 2022 and 2023. In each water, concentrations of CDOM were measured along with the apparent quantum yield of H2O2 (H2O2,λ) produced from CDOM. The H2O2,λ increased with increasing aromatic content of the CDOM. Photochemical production rates for all waters in this study were strongly limited by sunlight and limited by CDOM concentration. Photochemical production of H2O2 increased linearly with increasing sunlight and non-linearly with increasing CDOM. Thus, increasing sunlight exposure of arctic lakes (due to less ice cover) will increase H2O2 production and likely increase H2O2 concentrations. Likewise, increasing CDOM concentrations in arctic lakes due to export of CDOM from thawing permafrost soils will likely also increase H2O2 production in lake waters where H2O2 production is limited by CDOM.Master of Science (MS)Earth and Environmental SciencesUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/193115/1/Controls on the photochemical production of hydrogen peroxide in arctic surface waters.pdf9e430472-b4a9-48b3-b2d3-26f0e18b217aDescription of Controls on the photochemical production of hydrogen peroxide in arctic surface waters.pdf : Thesi

Practice trends of video laryngoscopy in pediatric anesthesia and the criteria of a difficult tracheal intubation in the context of video laryngoscopy: an international survey of pediatric anesthesiologists

http://deepblue.lib.umich.edu/bitstream/2027.42/192312/2/(2) Abstract DI SPA 2024.doc

Cereblon ligands and uses thereof

http://deepblue.lib.umich.edu/bitstream/2027.42/192158/2/WO2024015340A1_Original_document_20240124172503.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/192158/3/WO2024015340A1_Original_document_20240124172503.pd

Function-Preserving Tailored Open Partial Laryngectomy for Chondrosarcoma of the Thyroid Ala: A Case Report

http://deepblue.lib.umich.edu/bitstream/2027.42/191965/2/Function-Preserving Tailored Open Partial Laryngectomy for Chondrosarcoma of the Thyroid Ala A Case Report.pdfPublished versionDescription of Function-Preserving Tailored Open Partial Laryngectomy for Chondrosarcoma of the Thyroid Ala A Case Report.pdf : Published versio

Optimization of LoRaWAN Based IOT When Applied to Warehouse Battery Monitoring System Through Time Serial Forecasting

This dissertation proposes and studies a novel optimization scheme for LoraWAN based electric vehicle batteries monitoring system located in warehouses by utilizing techniques to optimize packet delivery and power settings. At first, based on my simulation of such a LoraWAN system, I observed and concluded that the optimized setting of such a system mainly depends on the network traffic regulated by the number of active users in the next channel access window. I therefore define the reward of the system as the multiplication of the packet delivery rate and power efficiency. A system setting consists of a traffic level and an appropriate radiation power. The optimized system setting results in maximum reward. However, the network traffic, or the number of active users in the next access window is time-varying and unknown due to the adoption of pure ALOHA protocol as well as the different packet rates and operation modes of battery LoraWAN sensors. Several factors lead to optimization of reward, including duty cycle regulation and future traffic prediction. The most effective optimization requires management of the traffic level based on criticality. A method called duty cycle management allows the lowest network traffic level with highest throughput and reward. When batteries have critical or urgent data, the specific nodes drive elevated network traffic levels for timely notification. With a large number of batteries in critical status, network traffic is at a maximum level. The goal of duty cycle management is to achieve an optimal network traffic level for different battery operating modes. Another factor in optimization is the future prediction of traffic, utilized for setting transmit power. I also examine optimizing reward with radios distributed in different zones around the collector. Also, the role of shadowing is considered in finding optimal system settings. I develop a network mechanism to survey the traffic level, power, and reward, storing the lowest power level that provides 80% of the maximum possible reward. Simulations validate the proposed scheme, which achieves the best results with an average 31% higher reward compared to competing approaches without the duty cycle management. Further chapters in this dissertation elaborate on topics related to networks of LoRaWAN radios and the optimization of their performance.PhDCollege of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/192768/1/2024_Dissertation_BT_B.pdf-1Description of 2024_Dissertation_BT_B.pdf : Dissertatio

Environmental Justice Case Study in St. Clair Township, Michigan

In St. Clair Township, Michigan, residents have filed a lawsuit against fossil fuel companies for negligence and unlawful contamination of their community. Our master's capstone team worked to support St. Clair Township residents in their fight for a healthier community in partnership with Freshwater Future and Families Reclaiming Our Environment. We sought to re-engage community members exhausted by a 40-year struggle and organize existing data detailing incidents from the 1980s to present day. These project objectives were met through hosting a community engagement event, conducting a survey to understand residents’ sentiments towards the facilities, and synthesizing records into a comprehensive timeline. The community engagement event acted as an opportunity to meet residents and learn about their concerns, shaping the survey. Survey results revealed that although almost all respondents are aware they live near these facilities, only slightly more than half had prior knowledge of the facilities before moving into their current residence. Results also showed that a majority of residents have been or are concerned about water and air quality near their homes. About 48% of respondents have or are experiencing health issues that might be correlated with the air quality near their home. Residents also described long-standing frustration with the companies and government agencies, who they feel have failed to address the pollution from these facilities. At the same time, our archival process has begun telling the four decades long story of St. Clair Township and its relationship with these local fossil fuel facilities. While still a work in progress, the timeline has begun to piece together evidence showing how residents have been and still are overlooked in the decision-making processes of these harmful facilities. The timeline has also begun teasing apart the complicated relationships between regulators and jurisdictional complexities that have perpetuated this problem for far too long. Through this report, we provide multifaceted evidence that the petrochemical facilities in St. Clair Township harm a rural frontline community’s health and quality of life and that government actors have failed to intervene. We make the case that environmental justice movements fighting petrochemical pollution must pay increased attention to previously overlooked sites within a massive geography of fossil fuel infrastructure.Master of Science (MS)School for Environment and SustainabilityUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/193035/1/Freshwater Future Rebecca Beilinson.pdfDescription of Freshwater Future Rebecca Beilinson.pdf : Master's Project Full Documen

National Poll on Healthy Aging: On Their Minds: Older Adults’ Top Health-Related Concerns

http://deepblue.lib.umich.edu/bitstream/2027.42/192983/1/0368_Top-10-Health-Concerns-Qs-050124.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/192983/4/0368_NPHA-Top-10-report_FINAL-05-02-2024.pdfDescription of 0368_Top-10-Health-Concerns-Qs-050124.pdf : Poll QuestionsSEL