Bioculture Journal
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Fire Regimes: Rhetoric and the Local Climate Politics of Wildfire
No full textThesis (Ph.D.)--University of Washington, 2024Fire history, topography, climate, and vegetation make up a fire regime: an ecological tool usedto determine a general pattern of wildfire in a particular ecosystem over time. By situating
clashes between local politics and federal and state projects to scale policies regulating fire
regimes, this project looks at how the ecological is impacted by the rhetorical through public
debate. Here, I look at the role of science in mediating, further aggravating, and sometimes
creating some understanding in relations between the state and locals around wildfire through
definitions. First, I demonstrate how definitional rhetoric was instrumental in the United States
Forest Service gaining control over the management of our nation’s forests. I then move 100
years in the future to the Oregon Labor Day Fires of 2020 where public officials (mis)used
definitional rhetoric to rhetorically maneuver political arson rumors while evacuating residents.
Lastly, I analyze the controversial Oregon Wildfire Risk Map created in the aftermath of the
2020 fires, showing how the public contested the state’s definition of “risk” and how scientists
and public officials recovered the map by using the more scientifically specific definition of
“hazard.” Together, I weave together a story of how tensions between the government and local
residents came to shape and be shaped by wildfires in the American West
Uncovering the mechanistic basis of intracellular Raf inhibitor sensitivity reveals synergistic cotreatment strategies
No full textThesis (Ph.D.)--University of Washington, 2024Raf kinases are crucial effectors in the Ras-Raf-Mek-Erk signaling pathway, making them important targets for the development of cancer therapeutics. This study investigates the variable potency of DFG-out-stabilizing Raf inhibitors in mutant KRas-expressing cell lines. We demonstrate that inhibitor potency correlates with basal Raf activity, with more active Raf being more susceptible to inhibition. We further show that DFG-out-stabilizing inhibitors disrupt high-affinity Raf-Mek interactions, promoting the formation of inhibited Raf dimers. Furthermore, we identify cobimetinib as a Mek inhibitor that uniquely sensitizes Raf to DFG-out inhibitors by disrupting autoinhibited Raf-Mek complexes. Building on this insight, we developed cobimetinib analogs with enhanced sensitization properties. Our findings provide a mechanistic framework for understanding the cellular determinants of DFG-out-stabilizing inhibitor sensitivity and offer strategies for optimizing synergistic Raf-Mek inhibitor combinations
Effects of Spinal Cord Stimulation on Neuromechanics of Gait for Children with Cerebral Palsy
No full textThesis (Ph.D.)--University of Washington, 2024Cerebral palsy (CP) is one of the largest causes of motor disability in children. Due to an injury in the central nervous system around the time of birth, children with CP have altered motor control and function that affects their movement. Common interventions to support mobility in children with CP often target secondary complications such as bone deformities, muscle contracture, and spasticity. Interventions are needed that can non-invasively support mobility in children with CP while targeting the underlying nervous system injury. Expertise in engineering, biomechanics, neuroscience, and rehabilitation can help to design and evaluate novel interventions for children with CP. This dissertation investigates how three novel interventions: spinal stimulation, interval treadmill training, and exoskeletons impact movement for children with CP.Transcutaneous spinal cord stimulation (tSCS) is a novel technique for modulating neural activity. Previous research suggests that tSCS can boost sensory feedback as it enters the spinal cord and may be effective for improving motor output when applied during rehabilitation. The evidence thus far for how tSCS may impact movement for children with CP is minimal but suggests that tSCS may improve whole-body motor function and coordination of muscle activity, even after one session of use. We enrolled four children with CP in a pilot study where they received 24 sessions each of short-burst interval treadmill training (SBLTT) only and SBLTT with tSCS. We found that tSCS+SBLTT reduced spasticity while maintaining walking function and reducing self-reported fatigue more than SBLTT only. However, we are continuing to understand the underlying neural and biomechanical changes that drive these functional improvements, as well as more about how these changes translate to community mobility.
Increased sensory information from tSCS+SBLTT may change how the body controls movement. Understanding the biomechanical changes with tSCS+SBLTT can elucidate the mechanisms driving functional improvements. In the same study of four children with CP, we quantified changes in muscle activity and joint kinematics. We found that participants walked in a more upright posture, with more knee and hip extension, after tSCS+SBLTT. Muscle co-contraction was also reduced, primarily in the thigh. Participants also had a reduction in motor control complexity after SBLTT only, but not after tSCS+SBLTT, despite reductions in spasticity. These results suggest that tSCS+SBLTT may improve coordination of movement and lead to more energy efficient walking patterns in children with CP.
One challenge when implementing novel rehabilitation techniques is tracking individual progress. Understanding why and how someone’s walking changes with rehabilitation is important for determining the best method for reaching their movement goals. This can be challenging to quantify due to the natural variability in movement, nonlinear rehabilitation progression, and additional factors that can mask change. We developed a causal modeling and machine learning paradigm to measure the direct effect of SBLTT on step length in children with CP. Using a virtual dataset, we validated that this paradigm can accurately capture nonlinear changes in step length with simulated training data. We then applied the causal modeling and machine learning paradigm to show that three of four children with CP improved step length with SBLTT, even after controlling for changes like treadmill speed and incline. This framework can be used to track individual therapy progression and determine how an intervention is affecting an individual's movement, remaining accurate even when there is high variability in the data.
Another aspect of translating novel techniques into rehabilitative care is understanding how they affect muscle fatigue during training. Overexertion of muscles that causes fatigue can limit motor learning of new tasks. Children with CP fatigue faster than peers, making fatigue an important consideration when developing rehabilitation programs. We quantified how tSCS and a resistive ankle exoskeleton, designed to increase muscle engagement, affected fatigue in nine children with CP. Each participant did 20-minutes of walking on separate days with no devices, tSCS only, bilateral resistive ankle exoskeletons (Exo), and tSCS+Exo. We found that the Exo session had the greatest rate of fatigue within the first 5-minutes of training, while there was an increase in muscle engagement with minimal signs of fatigue during the tSCS+Exo training. These findings suggest that the resistive exoskeleton may be more fatiguing on muscles, but that tSCS reduces the rate of fatigue. The use of these tools together may be beneficial for optimizing engagement in rehabilitation programs while supporting neuroplasticity.
This dissertation contributes to the fields of mechanical engineering, rehabilitation engineering, and neuroscience through a detailed investigation into how novel rehabilitation strategies affect movement for children with CP. We employ methods across these fields to comprehensively deepen our understanding of human movement and evaluating individual responses to rehabilitation. This work will support future translation of novel, non-invasive rehabilitation strategies into clinical care with tools to support how we can optimize and personalize their implementation
Deep learning frameworks for modeling how neural circuits learn
No full textThesis (Ph.D.)--University of Washington, 2024The brain's prowess in learning and adapting remains an enigma, particularly in its approach to the 'temporal credit assignment' problem. How do neural circuits determine which specific states and connections contribute to future outcomes, and subsequently adjust these for enhanced learning? My thesis addresses this by combining insights from the latest large-scale neuroscience data and recent deep learning theoretical tools. The first two projects introduce novel learning rules inspired by the Allen Institute's transcriptomics data, which revealed widespread and intricate cell-type-specific interactions among neuromodulatory molecules. This rule enables neurons to propagate credit information efficiently, enhancing learning performance beyond that of biologically plausible predecessors. Extensive computational experiments confirm the significant role of local neuromodulatory signals in learning, offering new perspectives on neural information processing. My third project assesses the generalization capabilities of bio-plausible learning rules through the lens of deep learning theory, particularly focusing on the curvature of the loss landscape via the loss’ Hessian eigenspectrum. Our findings reveal that these rules often settle in high-curvature regions of the loss landscape, indicating suboptimal generalization. This analysis led to a mathematical theorem linking synaptic weight update dynamics to landscape curvature, proposing neuromodulator-driven adjustments as a potential enhancement for learning rule performance. Given how initial conditions can greatly influence a system’s future trajectory, the fourth project delves into the impact of initial connectivity structures on learning dynamics in neural circuits. By examining various connectivity patterns derived from neuroscience data, including recent electron microscopy data, we analyze how these structures influence learning regimes, implicating metabolic costs and risks of catastrophic forgetting. Our findings suggest that high-rank initializations utilize pre-existing high-dimensional input expansion to facilitate input decoding, leading to minimal changes post-training and increasing the propensity for lazy learning. These specific initializations thus predispose networks toward certain learning behaviors, critically affecting their ability to adapt and generalize
Sources of Bias in Naturalistic Decision Making Under Risk
No full textThesis (Ph.D.)--University of Washington, 2024Severe weather situations such as tornadoes and droughts require people to take protective action even when the probability of the severe weather is low because the consequence of not protecting is very serious. In naturalistic decision experiments based on these situations, people are risk-seeking such that they often do not take protective actions when it is economically rational to do so. This project studied this phenomenon from a signal detection theory perspective. A random likelihood model was introduced to estimate the subjective criterion which is the likelihood above which one takes protection actions. This model separates the subjective criterion from subjective likelihood, which is participants’ perception of the probability of the weather event. Three experiments manipulated the gain-loss framing and the economically rational criterion (the criterion based on expected value theory) to examine their effect on the subjective criterion. When the gain-loss framing was manipulated, the subjective criterion was higher in a loss frame than a gain frame. When the economically rational criterion was manipulated, the subjective criterion was between the economically rational criterion and the center of the possible likelihood range (50%). Neither manipulation affected subjective likelihood. In addition, participants showed an overestimation in subjective likelihood in all conditions. The shifted subjective criterion overcame this overestimation and resulted in risk-seeking decisions in some conditions. Thus, the random likelihood model analysis suggests that shift of the subjective criterion is the source of risk-seeking decisions in naturalistic decision tasks. Potential interventions are discussed with the aim to improve the placement of the subjective criterion
Mapping the Chinese Community of Western Washington
No full textThesis (Master's)--University of Washington, 2024The Chinese community is one of the oldest and most established communities on the West Coast in addition to one of the most influential communities in founding current day Washington state’s landscape, economy, and historical businesses. In Western Washington, the Chinese community is largely concentrated in the Seattle area, but originated with immigrants who settled all across the Pacific Northwest in the mid-late 19th century. This project enhances the awareness of the Chinese community in Western Washington within the Eastside Heritage Center, highlighting this community’s experiences while moving through the history of the region. The map I created highlights notable locations relevant to the history of the Chinese community in Western Washington and provides visitors with an expansive and comprehensive view of the community’s historical and continued impacts in the region, allowing visitors to discover the influence and history of this community through historic neighborhoods, businesses, and key individuals. The map is available in a digital file and physical copies can be picked up at the Eastside Heritage Center
Community-based agricultural revitalization in Ngringo Village, Jaten Subdistrict, Karanganyar Regency
No full textBackground: Development involves conscious efforts and activities aimed at achieving positive change within a community. It requires the participation of all societal layers, with the government acting as a facilitator and guide. The government and the community must work harmoniously to achieve the desired goals. National agricultural development often focuses on villages close to municipalities, benefiting from hierarchical governance and advanced rural agricultural practices. This development can progress with political support, as outlined in Law Number 6 of 2014 on Villages, which aims to improve welfare, enhance human resources, and reduce rural poverty through sustainable management of local resources and the environment. This study aims to understand the potential and issues facing Ngringo Village, analyze the structural transformations, examine the institutional changes, assess the technology transfer, and identify a suitable agricultural development model. Methods: The research employs qualitative methods, including field observations, interviews with key informants, and analysis of secondary data from relevant literature and official documents. Findings: The results indicate that Ngringo Village has significant potential due to its strategic location and developed infrastructure. However, challenges such as reduced agricultural land and a shift in economic activities from agriculture to industrial sectors are evident. Institutional support through local farmer groups and technology adoption has been crucial in addressing some of these challenges. Conclusion: In conclusion, while Ngringo Village faces challenges due to rapid structural changes and urbanization, the village has managed to sustain its agricultural practices through effective institutional support and technology transfer. The study suggests that a location-based development model, considering both agricultural and non-agricultural factors, is essential for the sustainable development of Ngringo Village. Novelty/Originality of this study: This study produces a location-based agricultural development model that considers both agricultural and non-agricultural factors, providing practical guidance for local governments in planning sustainable development in villages facing rapid urbanization, such as Ngringo Village
Bakteri dalam proses produksi gas metana dari tumpukan sampah organik: Kajian pustaka
No full textMethane gas is a gas that occurs naturally on earth and is formed in piles of rubbish due to the large number of bacteria that nest in it. This article aims to discuss the formation of methane gas originating from piles of organic waste. The type of research method in this article uses a comparative method of journals and articles from within the country and abroad. Based on the results of the study, it was found that there is methane gas formed from piles of organic waste that undergoes an anaerobic decomposition process and there are several bacteria that play a role in the process of forming methane gas, such asEnterobacter, Pseudomonas, Bacillus, Streptomyces and Streptococcus which is the most dominant bacteria in organic waste
Baku mutu kualitas air muara sungai di kawasan Pura Petitenget dan upaya pengendaliannya
No full textThe main objective of this research is to analyze the quality standards for the quality of flowing water and river estuaries in the Petitenget Temple Area and efforts to control pollution or reduce the quality standards for flowing and river estuary water in the Petitenget Temple Area. The research was conducted from December 2018 to April 2019 in the river that flows into Petitenget Beach by taking four sampling points. The quality of water quality standards is measured using the water quality standards of Bali Governor Regulation No. 16 of 2016 concerning Environmental Quality Standards and Standard Criteria for Environmental Damage. The results of the research found that the quality of the water quality standards in the Petitenget Temple area had experienced pollution, namely the parameters of turbidity, chemical oxygen demand (COD), biological oxygen demand (BOD5), phosphate (PO4-P), total ammonia (NH3-N), fecal coliform, and total coliform. Efforts that can be made to overcome pollution in Loloan waters and river estuaries in Petitenget are the creation of Waste Management Regulations through the 4R (Reuse, Reduce, Recycle, Replace) pattern, limiting the use of chemical fertilizers and pesticides, creating waste storage and processing (septic tanks), and involving traditional villages (based on traditional villages) as well as environmental law enforcement
Empowering Womens MSMEs for economic independence based on local wisdom
No full textBackground: The aim of this research is to analyze the empowerment of women in MSMEs for Economic Independence Based on Local Wisdom. Method: The type of research is analytical survey research. This type of data uses qualitative data. Data sources consist of primary data and secondary data. Data collection techniques using interviews, documentation studies, and observations. The data analysis technique uses descriptive methods with a qualitative approach. Findings: Based on the results of the analysis and discussion, empowerment of the existence of female MSME actors, members of the Jempiring Women's Farmers Group (KWT), Badung Regency, uses the local wisdom of Tri Hita Karana. Conclusion: This is considered capable of increasing economic independence to help family finances with education costs, able to help carry out home renovations and repairs, and able to improve the health of all family members because family finances are already good. Novelty/Originality of this article: The novelty of this research lies in the empowerment model of women's MSMEs that integrates the principles of local wisdom Tri Hita Karana with a modern economic approach. This model combines entrepreneurship training, strengthening social networks, and preserving local cultural values to create a sustainable and competitive MSME ecosystem while maintaining cultural identity