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The Non-Orientable Four-Genus of Ten-Crossing Knots
No full textWe perform a detailed and complete computation of the non-orientable smooth 4-genus gamma4 for all 165 prime knots with crossing number equal to ten. Prior to this work, this important knot invariant was only known for knots with up to 9 crossings, and our work substantially expands on this body of knowledge. Our results have been published in the peer-reviewed Journal of Knot Theory and its Ramifications, and have been entered into the online database of knot invariants for low-crossing knots - KnotInto
Seismic Analysis and Isolation Strategies for Spent Fuel Dry Storage Cask Systems
No full textThis dissertation presents a thorough and insightful investigation into the long-term seismic safety of spent nuclear fuel dry storage casks (DSCs) and their internal fuel components. It underscores the critical need for robust containment of radioactive materials over extended operational periods to prevent damage and mitigate any potential releases. Based on a comprehensive review of existing literature, the study reveals that the global seismic responses of DSCs-such as sliding, rocking, and accelerations-have been extensively examined, while the localized response of fuel assemblies remains insufficiently explored. Since fuel rods, guide tubes, and other internal components significantly influence overall DSC safety, a deeper understanding of these localized behaviors is essential. To address these knowledge gaps, and to complement recent experimental efforts led by the Department of Energy, the dissertation proposes a versatile numerical framework for seismic analysis and response evaluation of DSCs. This framework integrates high-fidelity and simplified models, and a two-step modeling approach, enabling a wide spectrum of analysis objectives while reducing computational costs. The methodology captures both the global response of DSCs and the localized behavior of fuel assemblies, offering a holistic perspective on their seismic performance. Moreover, it achieves a remarkable reduction—exceeding 70\%—in computational expenses without compromising key dynamic features such as peak accelerations and localized stress distributions. Through evaluations under extreme seismic conditions reflecting various site conditions, the structural integrity of fuel assembly components is further confirmed, with responses remaining below yield limits. The dissertation also explores a meta-material-based seismic isolation strategy. By employing a ``meta-foundation” composed of alternating rubber and concrete layers, the research demonstrates the efficiency of frequency band gaps in filtering and attenuating seismic waves. When applied to multi-story structures, this meta-foundation reduces story accelerations and inter-story drifts by up to 95.1\% and 97.9\%, respectively, compared to conventional concrete foundations. In a novel extension of this concept, the dissertation investigates the effectiveness of meta-foundations for DSCs, showing that system accelerations can be diminished by as much as 95.3\% with careful design. This significant decrease in inertial forces also suggests significant reduction in the dynamic response of the fuel assemblies stored within the cask considerably, which must be further investigated in future investigations
Nevada State Climate Office Drought Report July 2025
No full textThis report was created by the Nevada State Climate Office to provide a statewide drought summary for July 2025
Researching with Library Search - Instructor Version
No full textThis scavenger hunt is designed to familiarize students with UNR libraries’ “Library Search,” an aggregating platform that pulls from databases, physical collections, digital materials, and more. This activity does not address databases or journal
Two-Level Solution Collection System: A Case History
No full textThis paper was presented at the Heap Leach Solutions Conference, October 19-21, 2025, Sparks, Nevada.Expanding leach pads is a common practice, where the liner system is extended, and ore is stacked against the existing heap. This case history presents an approach to overcoming unfavorable ground conditions by creating a two-level solution collection system and using a numerical seepage model to evaluate its performance. A heap leach expansion adjacent to an existing heap leach facility (HLF) was identified as the preferred site, with ore stacked in the expansion area and extending over the existing heap, with pregnant solution collected and conveyed through the existing infrastructure. The expansion site incorporated an independent solution collection system in the newly lined pad area to improve solution recovery. The existing HLF was constructed in multiple phases, with each expansion built upgradient, allowing leachate to be collected via gravity to the existing pregnant pond. The expansion site was located next to the most recent phase. The initial grading plan directed pregnant solution to a proposed expansion pregnant pond to accelerate mineral recovery, rather than relying on the longer existing collection system, which posed risks of prolonged travel time and potential losses through perforated pipes. The topography of the expansion pad area presented a challenge, as a portion of the site was in a depression sloping toward the existing pad, making independent solution collection difficult. One option considered was placing fill in the depression to modify the flow direction before placing the liner system. However, this approach had high capital costs and would reduce ore capacity by approximately 232,000 tonnes. To maximize ore stacking capacity while ensuring effective solution collection, a two-level solution collection system was designed and implemented. The lower-level system ensures environmental compliance and conveys solution to existing infrastructure, while the upper-level system is installed once the ore reaches a suitable elevation. The second-level collection system, placed directly on the prepared ore surface, consists only of perforated solution collection pipes without a geomembrane. It captures most of the leachate from additional ore lifts placed above it, with the remaining solution collected by the lower-level system. A numerical model, calibrated using both transient and steady-state flow conditions, was developed to evaluate system performance. When field-measured ore and overliner parameters were used, results showed a strong correlation with actual measured solution flow rates. Field data confirmed that 90.9% of the solution is captured by the second-level system and conveyed directly to the expansion pregnant pond, reaching it within 12 days from the start of irrigation. The remaining 9.1% is captured by the lower-level system. This case history illustrates that a set of solution collection pipes installed in intermediate lifts, without a geomembrane, can effectively collect most of the leachate solution. This approach mitigates unfavorable grading conditions without requiring extensive earthworks. The two-level solution collection system has performed as intended, accelerating mineral recovery and providing an efficient alternative to traditional heap leach pad designs
Spatiotemporal Modeling for Wildlife Demographic Analysis: Bridging Analysis to Waterfowl Conservation
No full textExamining variation in ecological systems is critical to understanding the fundamental demographic processes (e.g. reproduction, survival, growth, and dispersal) that govern populations and manage them in an increasingly altered world. Population dynamics often respond to environmental alterations, such as habitat fragmentation, climate variability, and resource changes, as individuals cope with shifting stressors. I demonstrate the use of spatially explicit models to estimate demographic rates and their relationships to environmental conditions in a highly variable system. In doing so, I clarify the changing spatial nature of this system and highlight conservation issues for midcontinent mallard populations. My second chapter serves as a guide to using spatially explicit models in population ecology. In a comprehensive literature review, I discuss spatial autocorrelation in demographic models and show how spatial models can mitigate this problem while leading to a greater ecological understanding of different systems. With three examples, I estimate spatial variation in survival and show how spatial models contribute to population ecology by reducing autocorrelation in residuals, smoothing and interpolating data, and providing insight into the spatial dynamics of ecological processes. In my third chapter, I use a conditional autoregressive model to estimate survival and harvest mortality from 1974 to 2023 of female and male mallards at the adult and juvenile age stages. Specifically, I studied populations in the Prairie Pothole Region (PPR) of the northern Great Plains. This area has seen dramatic and widespread landscape changes in recent decades with the change of agricultural patterns and climate. These spatial and temporal gradients of land use, combined with natural heterogeneity on the landscape, allow us to see how changing environmental conditions affect broad-scale population dynamics. Results showed substantial variation across time and space for survival and harvest mortality for all age and sex classes. Juvenile survival had a positive relationship with environmental conditions associated with higher recruitment, while adult survival had a negative relationship with the same variables. In the same vein, adult survival increased with habitats associated with lower recruitment rates, while juvenile survival decreased. These results also suggested a worrying trend: both adult and juvenile females exhibited declining survival probabilities throughout the time series. My fourth chapter was driven by these findings. Changes in sex-specific survival rates can lead to changes in population sex ratios and lead to substantial shifts in population structure. These changes in survival rates can result from sex-specific environmental effects on males and females, often via reproductive investments and risk. I estimated the relationships between sex-specific survival differences and environmental factors in mallard breeding grounds in the PPR. I found a rapid increase in survival differences, with males surviving at increasingly higher rates than females at the adult and juvenile age stages. Environmental covariates associated with higher quality breeding habitats were correlated with increases in sex-specific survival differences. These trends, resulting from land use and climate change in the region, could result in declining midcontinent mallard populations. Together, these results indicate a population that is responding to an extremely variable environment across time and space. The use of spatially explicit models in this research shows the spatial nature of mallard population dynamics, as well as where and how conservationists can target resources towards this population
The role of recombinant human laminin-111 in adhesion-signaling and glycosylation in laminin-⍺2 deficient muscle
No full textLAMA2-related congenital muscular dystrophy (LAMA2-CMD) is a rare and severe neuromuscular disease characterized by progressive muscular degeneration. LAMA2-CMD is caused by mutations in LAMA2 which encodes for the laminin-α2 protein. Loss of laminin-α2 results in the absence of laminin-211/221, an extracellular matrix protein essential for anchoring skeletal muscle cells to the basal lamina. LAMA2-CMD patients experience profound muscle weakness from birth, demyelinating neuropathy, and muscle atrophy starting from a very young age. Currently there is no effective treatment nor cure, therefore there is an urgent unmet medical need to develop therapeutics for LAMA2-CMD. Spatial proteomics analysis of LAMA2-CMD patient biopsies revealed altered biological processes including protein aggregation, oxidative stress, and dysregulated glycolysis. In the LAMA2-CMD mouse model, the dyW, spatial proteomics showed similar altered proteins and dysregulated pathways to LAMA2-CMD patients. Including downregulation of MAPK and Akt signaling. After treatment with recombinant human laminin-111 (rhLAM-111), the differentially expressed proteins were restored to wild-type levels. Immunofluorescence also showed that rhLAM-111 could restore altered localization of the laminin adhesion complexes to the sarcolemma and led us to explore the glycan composition of the dyW and other dystrophic mouse models utilizing different types of lectins. These results suggest that laminin-deficient muscle experiences dysfunctional Golgi complex organization influenced by integrin-α7 binding. Altogether, these findings highlight novel mechanistic insights into laminin’s role in regulating many integral biological pathways and the therapeutic potential of rhLAM-111 for mitigating disease progression in LAMA2-CMD
Quantifying Correlated Variables and Determining Signal Phase Reservice Rate Models from Multiple Linear Regression Using Historical Signal Controller Data
No full textSignal phase reservice is a technique that operates in coordination under advanced controller settings that help mitigate unreasonable delays at side streets when the green dwells on the main street. Despite its potential benefits, evaluating the effectiveness of phase reservice remains challenging due to its reliance on in-field observation, which is time-consuming and labor-intensive. Its current implementation also depends heavily on local expertise and engineering judgment. As a result, the practical impact of this technique often remains unclear. This study introduces a data-driven approach to evaluate phase reservice using historical controller data from eight intersections in the Reno-Sparks region. Data from Cubic Trafficware’s ATMS, including Split History, Timeline Split History, and Occupancy Reports for March 2025, were analyzed to identify instances of phase reservice and the corresponding traffic conditions. Through a regression analysis, the data can confirm engineers’ initial assumptions and create a guideline to implement phase reservice in coordinated intersections. A linear regression analysis was conducted to investigate the relationship between reservice rate and four variables: coordinated occupancy rate, non-coordinated occupancy rate, number of phases, and average cycle length. The analysis found significant correlations for all variables except coordinated occupancy rate. A multiple linear regression model incorporating all four variables yielded a residual standard error of 0.2236 and an adjusted R² of 0.4697. By plotting the actual vs estimated reservice rates, it was deemed that creating an accurate model was infeasible with current data. To address this, a regression decision tree was developed, achieving a cross-validation error of 0.397 with seven splits. This model is a more practical tool that can be used by engineers to help facilitate decision making in addition to engineering judgment. Future research should explore more diverse intersections and advanced modeling techniques to further enhance predictive performance
Advancing Rockfall Hazard Assessment through Data-Driven Modelling Based on Laboratory-Scale Experiments
No full textUnderstanding the dynamics of rockfalls is critical for predicting hazards and mitigating risks in both natural and engineered environments. This research investigates the relationship between rock shape, release angle, and rockfall behavior, combining experimental analysis with machine learning (ML) modeling to address the complexities of rockfall mechanics. Laboratory experiments were conducted to analyze the behavior of three distinct rock shapes—ellipsoidal, octahedral, and spherical—dropped from a pendulum arm at two specific release angles (15° and 30°) onto a horizontal concrete surface. Motion data captured from dual camera angles were analyzed to evaluate key parameters, including the coefficient of restitution (COR), translational and angular velocity, runout distance, and trajectory dispersion. The results highlighted significant variations in behavior based on shape, with non-spherical rocks, particularly ellipsoidal and octahedral forms, exhibiting erratic trajectories, greater lateral dispersion, and wider variability in COR compared to spherical counterparts. These findings underscore the critical influence of shape and impact conditions on rockfall dynamics, emphasizing the need for nuanced hazard prediction models.
To extend these insights, ML techniques were employed to predict rockfall parameters using the experimental data. Three models—K-Nearest Neighbors (KNN), perceptron, and deep neural networks (DNNs)—were evaluated for their ability to handle the nonlinear and irregular patterns inherent in rockfall behavior. While perceptron models struggled with the complexity of the data and DNNs faced challenges with overfitting and interpretability, KNN emerged as the most effective approach. By leveraging localized, instance-based predictions, KNN demonstrated robust accuracy and adaptability, effectively modeling the dynamics across diverse shapes and release angles.
Furthermore, the study compares the predictive performance of the KNN model with RocFall, a physics-based software widely used for rockfall simulations. This comparison provides insights into the strengths and limitations of both approaches, highlighting the potential for ML to complement traditional physics-based models by offering data-driven adaptability and improved predictive capabilities for specific rockfall scenarios.
The research presents a comprehensive framework for understanding and predicting rockfall behavior, combining experimental insights with an interpretable ML approach. The findings improve the predictive capabilities of hazard models and provide practical tools for safety management in mining and civil engineering. By addressing the challenges of complex physical interactions and high-dimensional datasets, the approach enhances risk assessment and mitigation strategies
“We deserve to be seen, heard, and included in recovery spaces:” A content analysis informing the improvement of treatment for alcohol use for sexually diverse individuals
No full textObjectives: Excessive alcohol use is a public health concern that results in hundreds of billions of dollars in economic costs each year and leads to increased risk for disease, premature death, and other physical and mental health concerns. Sexually diverse individuals (SD; e.g., lesbian, gay, bisexual, queer) represent a community disproportionately impacted by alcohol use disorder (AUD) and alcohol-related problems. Though SD individuals utilize alcohol-related treatment services at a higher rate than the general population, the number of SD individuals with AUDs who seek treatment is low compared to the number of SD individuals with AUDs who do not seek treatment. Thus, current alcohol use treatment programs may not adequately engage or meet the needs of SD individuals. This study seeks to better understand treatment barriers SD individuals face in alcohol-related treatment that may be contributing to low treatment utilization, highlight ways of improving treatment for SD individuals experiencing AUD, and disseminating the findings to provide additional resources and increased knowledge for service providers who work with this community. Methods: A sample of 11 adults 18 years or older who identify as SD (e.g., lesbian, gay, bisexual, queer) and who are currently receiving, or have received (within a one-year timeframe) alcohol use treatment for AUD were recruited for this study. Semi-structured interviews were conducted, transcribed, and a conventional content analysis approach was used to interpret data.
Results: Findings from conventional content analysis indicated participants felt their sexuality played a major role in their alcohol use (e.g., identity suppression and exploration, community drinking norms). Additionally, participants emphasized the importance of creating and maintaining an inclusive and affirming environment, including mind/body/spirit components to treatment (e.g., body work, spirit-based programming), having competent and friendly staff (e.g., trauma-informed staff, increased training on working with community), and including a diverse selection of treatment and recovery models. Finally, all participants shared positive perceptions of incorporating aspects of harm reduction into treatment.
Conclusions: These recommendations should be taken into consideration when discussing treatment improvements, program policies, and program structure. It should be a priority to ensure that SD individuals feel safe, understood, validated, and are receiving the most effective treatment possible when entering programs