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Effects of Mating System and Adaptedness on the Evolution of Fitness and Mtdna Copy Number in Mitonuclear Mismatched C. Elegans
No full textMetabolic functioning in nearly all eukaryotes relies on molecular machinery dual-encoded by mitochondrial DNA (mtDNA) and nuclear DNA (nDNA) genomes. The two genomes have sustained an extraordinary degree of cooperation across evolutionary time, preserving the capacity for indispensable processes including oxidative phosphorylation and ATP production, which in turn influence many fitness-related traits. How this cooperation is maintained when one member of the pair is debilitated by deleterious mutation is poorly understood, as is the influence of mutation location (mtDNA or nDNA), mating system, or the potentially compensatory effects of mtDNA copy number changes on the process. We asked whether and to what extent populations experiencing mitonuclear mismatch can recover ancestral levels of fitness by allowing C. elegans nematodes containing either mitochondrial or nuclear mutations of electron transport chain (ETC) genes to evolve under three mating systems-facultatively outcrossing (wildtype), obligately selfing, and obligately outcrossing-for 60 generations. In alignment with evolutionary theory, we observed an inverse relationship between the magnitude of fitness recovery and the ancestral fitness level of strains with the latter outweighing any effect of mating system. We interpret these findings in light of previously reported male frequency evolution in the same mutant lines. The relationship between the amount of fitness evolution and change in mtDNA copy number was influenced by strains\u27 ETC mutant background and its interaction with mating system. To our knowledge, this work provides the first direct test of the effects of reproductive mode and evolution under mitonuclear mismatch on the population dynamics of mtDNA genomes
Bringing DEI to Nature Education: a Community Based, Culturally Specific Approach
No full textHanna Dornhofer and Kesia Tosh expand on the topic, Bringing DEI to nature education: a community based, culturally specific approach. during a lunch and learn presentation.
Since 2022, Beaverton Black People’s Union (BBPU) and the Tualatin Hills Nature Center at Tualatin Hills Park & Recreation District (THPRD) have partnered to offer the annual Black & Green Fellowship, a paid four-day experience for Black high school students in the Beaverton area. The Fellowship empowers youth to take up space and gain comfort in nature by building a relationship with a park site and building community with each other. Sessions are led by professional facilitators and subject matter experts on topics associated with nature and mental health. We focus on increasing students’ understanding of the connection between nature and mental health, offering techniques for nature-based self-care and wellness and providing take-home tools to integrate self-care into their lives. We would like to share the results of this partnership program, entering its fourth year, including both successes and lessons learned. This program gives insight into the creation of culturally specific programming using a community-led model. Additionally, the Black & Green Fellowship Program has led to a deeper, more trusting relationship with the BBPU, and is currently resulting in new program ideas and events planned for 2025 and beyond, illustrating an example of how community-based equity and inclusion work can succee
Coli@fire2024: Findings of Word-Level Code-Mixed Language Identification in Dravidian Languages
No full textCode-mixing, a linguistic phenomenon where multiple languages are blended within a single text, has become increasingly prevalent in multilingual societies, particularly in digital communication. The CoLI-Dravidian shared task, organized as part of Forum for Information Retrieval and Evaluation (FIRE) 2024, aimed to address these challenges by inviting researchers to develop models capable of classifying words in code-mixed texts involving Dravidian languages — Tamil, Kannada, Malayalam, and Tulu - interwoven with English. The task presents significant challenges due to the complexity of linguistic structures, mixed-language tokens, and dialectal variations, especially in low-resource languages like those in the Dravidian family. The participating teams employed various methodologies, including traditional Machine Learning (ML), Deep Learning (DL), and transformer-based models, to tackle these challenges. This paper presents important findings of the task, baselines, and an overview of the submitted methodologies. The top-performing models achieved macro F1 scores ranging from 0.7656 for Tamil to 0.9293 for Kannada, demonstrating the capability of advanced computational techniques to process these complex multilingual texts effectively
Urban Heterogeneity Drives Dissolved Organic Matter Sources, Transport, and Transformation from Local to Macro Scales
No full textUrbanization reshapes dissolved organic matter (DOM) sources, transport, and transformations through changes in vegetation, hydrology, and management of waste and water. Yet the impacts of urbanization on DOM are variable within and among cities. Predicting heterogeneous responses to urbanization is challenged by diverse human activities and underlying biophysical variation along stream networks. Using data from the 486 largest urban areas in the continental United States and seven focal cities, we identified macro and local scale urban gradients in social, built, and biophysical factors that are expected to shape DOM. We used these gradients and the literature to develop hypotheses about heterogeneity in DOM quantity and quality within and among cities. Interactions among landscape and infrastructure attributes across spatial and temporal scales result in heterogeneous responses in DOM. Characterizing and quantifying these inconsistent responses to urbanization in contrasting settings may help to better understand heterogeneity and identify generalities among urban watersheds
The Lake
No full textThe Lake is a novella-length fictional work in lyrical and fragmented prose that explores themes of small town origination, belief, hypersensitivity, alienation, and inheritance. In a village surrounded by forest, two sensorially gifted children from different families negotiate the growing magnitude of what they perceive. This narrative incorporates elements of magical realism, shared and shifting perspective, sound, landscape, and time
Hydrosocial Ocean Commons: Offshore Wind Energy in Oregon
No full textThe ocean has been culturally and legally conceptualized as a commons, a space of subsistence inherited by all. Enclosure or privatization creates overlapping jurisdictions of ocean space. The ocean is also the world\u27s most significant carbon capture, absorbing billions of tons of anthropogenic carbon dioxide since the Industrial Revolution. Now, the ocean offers an additional opportunity to decarbonize energy production and reduce greenhouse gas emissions through \u27new frontiers\u27 of offshore wind technology; however, this potential is entangled within neoliberalism. Offshore wind is entering a fragmented legal landscape where the social-legal process of ocean jurisdiction remains contested. As the new frontier of renewable energy moves offshore, society needs strategies to create comprehensive policies that encompasses the social-ecological systems of the ocean, including renewable energy. This thesis builds on theoretical foundations of political ecology, legal geography, energy and water justice, and common property theory to ask the following research questions: What are competing ideas and narratives of ocean space in relation to Oregon offshore wind energy development? What are the legal geographic dimensions of offshore wind energy development in Oregon? How can these results be analyzed through processes of enclosure and commons? Through spatial conceptualization of the commons, enclosure, and scale, this critical human geography research analyzes qualitative data on offshore wind energy development processes and policies, as well as the social and legal dimensions of ocean waters. The goal of this thesis is to invite potential paths forward for renewable energy transitions through deeper understanding of ideas and expectations for protecting ocean, atmospheric, and energy commons as Oregon stakeholders and Tribes struggle not solely for clean electrons, but for democratic processes toward energy justice
Alignment of Perceptual Similarity Metrics with Human Perception
No full textPerceptual similarity metrics are used for quantitatively evaluating the similarity between two images as it would appear to human perception. These metrics aim to mimic the human visual system, providing a more accurate assessment of visual similarity. Such visual assessments are considered to be more advanced than simple pixel-wise comparisons such as ℓp norm distances. Thus, a human-like assessment of visual similarity, makes the metrics valuable for applications in image compression, restoration, and enhancement, where evaluating perceptual quality is crucial. Perceptual similarity metrics have progressively become more correlated with human judgments on perceptual similarity; however, despite recent advances, the addition of an imperceptible distortion can still compromise these metrics. This dissertation investigates how the magnitude of specific perturbations applied to visual stimuli affects the responses of low-level perceptual similarity metrics, with the goal of determining how imperceptible distortions impact the reliability of these metrics.
We begin by investigating the robustness of perceptual similarity metrics against an imperceptible geometrical distortion that can occasionally occur during image acquisition and preprocessing. Existing perceptual similarity metrics assume an image and its reference are well aligned. As a result, these metrics are often sensitive to a small alignment error that is imperceptible to the human eyes. In this dissertation, we first study the effect of small misalignment, specifically a small shift between the input and reference image, on existing metrics, and accordingly develops a shift-tolerant similarity metric. We build upon LPIPS, a widely used learned perceptual similarity metric, and explores architectural design considerations to make it robust against imperceptible misalignment. Specifically, we study a wide spectrum of neural network elements, such as anti-aliasing filtering, pooling, striding, padding, and skip connection, and discuss their roles in making a robust metric. Based on our studies, we develop a new deep neural network-based perceptual similarity metric. Our experiments show that our metric is tolerant to imperceptible shifts while being consistent with the human similarity judgment.
We further extend our investigation by systematically evaluating the robustness of these metrics to imperceptible adversarial perturbations. We call these perturbations adversarial, as they are deliberately crafted by an attacker with malicious intent. Following the two-alternative forced-choice experimental design with two distorted images and one reference image, we perturb the distorted image closer to the reference via an adversarial attack until the metric flips its judgment. We first show that all metrics in our study are susceptible to perturbations generated via common adversarial attacks such as FGSM, PGD, and the One-pixel attack. Next, we attack the widely adopted LPIPS metric using spatial-transformation-based adversarial perturbations (stAdv) in a white-box setting to craft adversarial examples that can effectively transfer to other similarity metrics in a black-box setting. We also combine the spatial attack stAdv with PGD (ℓ∞-bounded) attack to increase transferability and use these adversarial examples to benchmark the robustness of both traditional and recently developed metrics. Our benchmark provides a good starting point for discussion and further research on the robustness of metrics to imperceptible adversarial perturbations.
Continuing our line of investigation, we examine the accuracy and robustness of leveraging vision encoders from large foundation models as the backbone for perceptual similarity metrics. Deep-learning based approaches to measuring perceptual similarity, the perceptual similarity score between a distorted image and a reference image is typically computed as a distance measure between features extracted from a pretrained CNN or more recently, a Transformer network. Often, these intermediate features require further fine-tuning or processing with additional neural network layers to align the final similarity scores with human judgments. So far, most perceptual similarity metrics and quality assessment models based on foundation models have primarily relied on the final layer or the embedding for the similarity and quality score estimation. In contrast, this work explores the potential of utilizing the intermediate features of these foundation models, which have largely been unexplored so far in the design of low-level perceptual similarity metrics. We demonstrate that for the low-level perceptual similarity task the intermediate features are comparatively more effective than embeddings as backbone features. Moreover, without requiring any training, these metrics can outperform both traditional and state-of-the-art learned metrics by using distance measures between the intermediate features
Communities of Practice: Aging, Emergency Management, and Churches in Rural Clackamas County, Oregon
No full textAs the population of the United States ages, questions arise of how to best care for older adults in daily life and emergency situations. This research looks at the daily activities of churches to see how they affect everyday and emergency care practices. As a collaboration with Clackamas County government, I researched the relationship between churches and care through participant observation and interviews during the summer of 2024 to understand congregations’ support for older members, the role of church congregations in emergency management, and the implications of the decline in religious participation alongside aging in the United States. I found that congregations create networks of assistance and communication that could help emergency management and senior social services. I explore the relationship between belief and action in one congregation, and then interpret the implications of church-related benefits in an increasingly irreligious context. I end with suggestions for how governments can appropriately make use of these findings
Postsurgical Pain, Psychosocial Functioning, and Cannabis Use Among Adolescents and Young Adults Undergoing Gender Affirming Surgery
No full textPurpose: Little is known about transgender and gender expansive (TGE) adolescents and young adults (AYAs) pain and psychosocial experiences in the acute postsurgical period following gender-affirming surgery (GAS). This study describes pain symptomatology and psychosocial functioning within 1 month after GAS among TGE AYAs, examines immediate postsurgical associations of cannabis use with pain symptomatology, pain catastrophizing, and psychosocial functioning, and explores pain persistence, cannabis use, and psychosocial functioning in a subgroup of individuals 6 months after surgery.
Methods: AYAs (N = 64) underwent GAS at a large academic medical center in the Pacific Northwest between March 2019 and June 2023. Participants reported on pain intensity, pain interference, pain catastrophizing, anxiety, depression, and cannabis use. Independent and paired-samples t-tests examined differences by age, past 30-day cannabis use, and from the postsurgical period to 6-month follow-up.
Results: Participants reported acute and persistent pain following GAS. Younger age was associated with improved pain interference in the postoperative stage. Reports of past 30-day cannabis use were high in this sample, and cannabis use was associated with higher pain interference, anxiety, and depression.
Conclusion: This study is the first to assess AYA pain functioning, mental health, and cannabis use following GAS within 1 month of surgery and at 6 months. Findings suggest that 6 months after GAS is a postsurgical adjustment phase, necessitating more supportive perioperative and psychosocial resources, including attention to substance use, during this crucial window
2025 Commencement School of Business Ceremony Video
No full textVideo presentation of the PSU School of Business Commencement ceremony, held June 14, 2025, at the Viking Pavilion at Portland State University.
This ceremony honors both undergraduate and graduate students in the School of Business.https://pdxscholar.library.pdx.edu/commencement_2020s/1014/thumbnail.jp