University of Illinois at Chicago
University of Illinois at Chicago: UIC INDIGO (INtellectual property in DIGital form available online in an Open environment)Not a member yet
21439 research outputs found
Sort by
Social Dimensions of Heat-Related Injury Prevention Among Migrant Farmworkers
No full textThis conference presentation from the 34th International Congress on Occupational Health presents results from a heat safety intervention study with migrant farmworkers in Florida.</p
The Relationship Between Domain-General Auditory Processing and Second/Additional Language Acquisition
No full textDomain-general auditory processing (DGAP), the ability to perceive and recall sound features (Mueller et al., 2012), is linked to disparities in L2/A phonological and speech learning. While evidence suggests its role in L2/A proficiency and grammar learning (e.g., Saito et al., 2022), other domains remain underexplored.Intermediate L2/A Spanish learners completed four auditory discrimination tests (duration, rise-time, pitch, formant; Kachlicka et al., 2019), an elicited imitation task (EIT), and a standardized test (DELE) to assess proficiency. A grammaticality judgment task (GJT) measured grammatical knowledge on phrase structure (PS), subject-verb (SV), and noun-phrase agreement (AGn, AGg). ERP responses during the GJT examined (morpho)syntactic processing.Preliminary analyses (N=13) showed variation in auditory processing, with lower scores indicating better abilities. Participants performed at intermediate levels for proficiency (EIT: M=75.69, SD=23.43; DELE: M=20.60, SD=3.59) and the GJT (PS: M=0.799, SD=0.172; SV: M=0.797, SD=0.147; AGn: M=0.794, SD=0.175; AGg: M=0.64, SD=0.15). Correlation analyses showed small-to-medium negative associations between spectral processing and proficiency (EIT: r=-0.339; DELE: r=-0.348), and grammatical knowledge (PS: r=-0.445; SV: r=-0.339; AGn: r=-0.40; AGg: r=-0.356). Similar associations emerged between temporal processing and grammatical knowledge (SV: r=-0.255; AGg: r=-0.564). ERP analyses showed P600_PS and P600_SV effects for spectral processing, and P600_AGn and P600_AGg effects for temporal processing. Participants showed a P600 trend for number agreement (PS: M=0.33, SD=5.00; SV: M=0.60, SD=3.55; AGn: M=1.28, SD=2.52). Two medium negative correlations were found for spectral processing (r=0.49) and three small-to-medium negative for temporal processing (r=0.48).</p
Simultaneous Power-Gating, Scheduling, and Binding in High-Level Synthesis with Lookahead Based Formation of Power Islands
No full textNo description supplied</p
Integrating Behavior and Conservation: Behavioral Ecology as a Management Tool
No full textMy research utilizes behavioral ecology as a management tool for species in zoos and in the wild. Each dissertation chapter explores a different application for using animal behavior to assess management concerns, evaluate protocols, and minimize adverse effects. Chapter one addresses low reproductive success in two zoo-housed passerine species, blue-gray tanagers (Thraupis episcopus) and red-capped cardinals (Paroaria gularis). I evaluated and compared two breeding management protocols: pedigree-based pairing and female mate-choice. I found that pairing method did not impact reproductive success, but that the opportunity to engage in mate-choice led to greater welfare for the individual expressing preference. For monogamous species, incorporating both sexes’ mate preference may be more beneficial, improving welfare and mating success. Next, I utilized behavioral indicators of patch use to evaluate the impact of visitor proximity on Bennett’s wallabies’(Notamacropus rufogriseus) perception of their walk-through exhibit. I identified key features within areas of preference and aversion and provided recommendations for how managers can amend underutilized areas to increase space use. In my last two chapters, I shift my application of behavioral ecology to the management of two free-ranging ‘pest’ species, the swamp wallaby (Wallabia bicolor) in Australia and the Eastern gray squirrel (Sciurus carolinensis) in the USA, whose close-proximity to humans and damages inflicted by foraging, can lead to direct conflict. I applied behavior-based management aimed at modifying each species foraging behavior by manipulating a food item’s value (perceived or actual). I then utilized behavioral indicators of patch use to evaluate the efficacy of each potential feeding deterrent. For wallabies, I found that a phantom decoy (a food item that is present, but inaccessible) shifted their short-term food preference, but the effect diminished over time suggesting that decoys are unlikely to be an effective tool for manipulating wallabies’ long-term foraging decisions. For squirrels, I found that peppermint and chili pepper oils were most effective at reducing seed consumption, indicating that these two plant compounds have the greatest potential as squirrel feeding deterrents. The results from these two chapters demonstrate that patch use serves as a successful tool for quantifying short- and long-term effectiveness of potential feeding deterrents
Looking across Infrastructure’s Lifecycle: Understanding Challenges to Provide Services in Alaska
No full textThe provision of critical infrastructure systems (CISs) in Alaska is uniquely challenging due to the extreme climate, workforce limitations, and remoteness of communities. While many of these challenges span lifecycle phases and CISs, most literature examines systems in isolation and without considering the entire project lifecycle. This thesis addresses this gap by analyzing CIS challenges throughout the planning, design, construction, use, and disposal phases. Focusing on six key infrastructure sectors—transportation, water and wastewater, solid waste, energy, communication, and public health, this work is based on insights from 19 semi-structured interviews with 22 stakeholders involved in providing CISs in Alaska. A hybrid qualitative approach combining deductive and inductive techniques was used to identify emergent themes. The findings reveal significant obstacles that impact infrastructure functionality, resilience, and service delivery in Alaska. High construction and maintenance costs, limited funding, and complex grant processes make infrastructure management difficult. In addition, many CISs face a shortage of skilled labor, particularly in remote areas, while coordination problems between agencies and stakeholders slow down decision making throughout the project lifecycle. Findings highlight that many challenges are common across systems, suggesting that lessons from one CIS can inform the management of other systems
Nonpositively Curved Manifolds of Small Volume
No full textThis thesis contributes a novel theorem in the mathematical literature of collapsing manifolds. We prove that for compact manifolds of nonpositive sectional curvature bounded below, with uniformly bounded diameter, and containing no local Euclidean factors, there is a uniform lower bound on volume. This lower volume bound only depends on the dimension of the manifolds and the uniform bound on diameter, and represents an obstruction to collapsing. The theorem is analogous to previous results in collapsing manifolds, in particular, a theorem of Kazhdan and Margulis on the minimal volume of locally symmetric spaces
Machine Learning for Space Signal Processing
No full textThe rapidly expanding volume and complexity of data in space systems pose significant challenges to traditional signal processing methods, necessitating innovative approaches that can efficiently adapt to these demands. This thesis explores the transformative role of machine learning in enhancing signal recovery for space signal processing, addressing critical challenges with computationally efficient and scalable solutions.
We begin by examining clustering algorithms tailored for large datasets, a cornerstone of modern data analysis. Two novel variants—2-Hard and 2-Soft clustering—are introduced to improve computational efficiency and adaptability, including extensions designed for scenarios with incomplete knowledge. These clustering methods are further demonstrated in practical space systems, where they enhance forward error correction processes, showcasing their utility in real-world applications.
Building on this foundation, we turn to the problem of phase retrieval, a key task in space signal recovery, e.g., in space telescope image formation. We propose a deep unfolded phase retrieval (UPR) framework, blending machine learning with model-based techniques to optimize both encoding and decoding processes. Our framework not only improves computational dynamics but also achieves superior performance compared to traditional algorithms, as demonstrated by extensive empirical evaluations.
Lastly, we explore the emerging frontier of quantum compressive sensing (QCS), integrating classical machine learning principles with quantum computing methodologies to advance signal recovery techniques. Using practical datasets such as LIDAR, we evaluate the robustness of the proposed QCS framework under both ideal and quantum noise conditions. The results highlight the potential of QCS for data recovery and its promising outlook in reshaping the landscape of space signal processing
The Cell-Autonomous Role of Caveolin-1 in Adult Hippocampal Neurogenesis
No full textThe mechanisms governing adult hippocampal neurogenesis (AHN) remain incompletely understood, despite its crucial roles in learning and memory. Identifying the signals that regulate AHN has significant implications for brain function and therapeutic strategies. Here, we demonstrate that Caveolin-1 (Cav-1), a protein highly enriched in endothelial cells and a key component of caveolae, cell autonomously regulates AHN. Conditional deletion of Cav-1 in adult neural progenitor cells enhanced neurogenesis and improved contextual discrimination performance in mice. Proteomic analysis revealed that Cav-1 influences mitochondrial pathways in neural progenitor cells. Notably, Cav-1 localized to mitochondria and regulated mitochondrial morphology, an outcome of fission-fusion dynamics—a critical process in neurogenesis. These findings identify Cav-1 as a novel regulator of AHN and underscore its impact on cognitive function
Investigating the Role of Bile Acid Homeostasis in Multiple Sclerosis
No full textMultiple Sclerosis (MS) is a severe neurodegenerative disease characterized by demyelination and immune cell infiltration in the central nervous system (CNS). The pathophysiology of MS is multifactorial, and gut dysbiosis has recently been identified as a contributing factor. To this end, bile acids are detergent-like compounds that are synthesized in the liver and modified in the intestine. While their primary physiological function is to aid in lipid emulsification, recent studies have shown that bile acids act as signaling molecules in a number of peripheral tissues, including the brain. However, it has not been established how the size and composition of the bile acid pool modulate the neuroinflammatory response in neurodegenerative diseases such as MS. Therefore, we utilized primary mouse astrocyte cultures to determine how bile acid treatment affected the cytokine-induced inflammatory response. Chenodeoxycholic acid (CDCA) and its conjugated form (TCDCA) elicited a modest anti-inflammatory effect in cytokine-treated astrocytes. For in vivo studies, our lab utilized the experimental autoimmune encephalomyelitis (EAE) mouse model of MS to examine how altering the bile acid pool modulated onset and progression of disease. The overproduction of bile acids via overexpression of CYP7A1 exacerbated EAE disease severity. In contrast, depletion of the bile acid pool via 2% Cholestyramine feeding significantly reduced disease clinical score, histological damage, and markers of astrocyte activation. Elaboration on these studies could lead to novel therapeutic approaches in the treatment of MS
The Hidden Architects of Regional Power: How RIGOs Shape Governance, Influence, and Collaboration
No full textThis dissertation explores how Regional Intergovernmental Organizations (RIGOs) influence interlocal collaboration and shape governance power structures in the United States. RIGOs have gained prominence as institutional mechanisms to address complex regional challenges, but questions remain about their effectiveness and equity in governance. This study adopts a two-essay format to address these gaps using rigorous empirical approaches.
The first essay uses the Augmented Synthetic Control Method (ASCM) to assess the causal impact of RIGO formation on interlocal collaboration in Iowa. By analyzing longitudinal data from a newly established RIGO in 2007, the study evaluates changes in the frequency, complexity, and diversity of interlocal agreements across treated and comparison counties. Findings show that RIGOs significantly enhance collaboration, particularly by increasing the number and sustainability of interlocal agreements. However, the effects are heterogeneous and often delayed, depending on local context and administrative capacity.
The second essay investigates power allocation within RIGOs by introducing the Governance Representation Disparity Index (GRDI), a novel metric capturing the misalignment between a county’s voting power and its population or economic status. Using a national sample of 182 RIGOs spanning 1,232 counties, this study finds that while population size is a primary driver of voting power, institutional rules often modify this relationship, sometimes amplifying or constraining the influence of smaller or wealthier jurisdictions. These disparities raise critical concerns about representational equity and governance legitimacy.
The final chapter synthesizes findings and proposes a broader empirical framework for RIGO research, encouraging inclusion of multiple RIGOs per region, recognition of single-function entities, and the application of advanced quantitative methods. Overall, this dissertation contributes new insights into the causal impact and institutional dynamics of RIGOs, offering both theoretical advancement and practical guidance for regional governance design
Data sources:
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇