8413 research outputs found
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Reinforcement and Stabilization of Ripios Dumps Platforms Using Leached Ripios Fill and Geocells
No full textThis paper was presented at the Heap Leach Solutions Conference, October 19-21, 2025, Sparks, Nevada.In large-scale mining operations, ensuring the stability of roads and working platforms is a major challenge due to the mechanical behavior of leaching ripios, which is often used as a construction material. This study presents the application of geocells as a reinforcement solution to enhance the load-bearing capacity and stability of infrastructure built over leaching ripios. The proposed methodology offers a cost-effective and technically feasible alternative to traditional soil stabilization methods, reducing resource consumption and execution time. Geocells, have proven to be highly effective in geotechnical engineering by confining granular materials and improving their mechanical properties. Originally developed by the US Army Corps of Engineers in the 1980s, geocells provide structural integrity by increasing shear resistance, reducing lateral displacement, and distributing loads more efficiently. The implementation of this technology aims to address the limitations of leaching ripios, which exhibits high moisture content, fine particle fractions, and low undrained shear strength. The research involved the execution of a field trial where geocells were deployed over leaching ripios, filled with material, and compacted to form stable working platforms. Instrumentation, including pressure cells and laser displacement measurement, was used to monitor stress distribution and deformation behavior. The construction process consisted of geocell installation, filling, compaction, and load verification using a Bulldozer D9 to assess bearing capacity under operational conditions. Results demonstrate that geocell reinforcement significantly enhances the performance of leaching ripios by reducing settlement and increasing structural stability. Saturated and highly deformable areas adjacent to the reinforced sections exhibited noticeable differences in load-bearing capacity, confirming the effectiveness of geocells in mitigating excessive deformation. This study concludes that the use of geocells as a reinforcement system for leaching ripios is a practical and sustainable solution for mining infrastructure. The approach minimizes material replacement costs, optimizes resource utilization, and enhances operational safety. Future research should focus on optimizing design parameters and expanding its application to other geotechnical challenges in the mining industry
Advancing Vegetation Monitoring Strategies in Arid Ecosystems Using Unmanned Aircraft Systems
No full textArid ecosystems present unique challenges for environmental monitoring using remotely sensed data because vegetation communities in drylands are often sparsely distributed and have heterogeneous species and soil composition. Unmanned Aircraft Systems (UAS) offer centimeter-scale spatial resolution and flexible deployment that can better address the scale of these communities. This work explores two complementary approaches for integrating UAS into scalable and adaptable vegetation monitoring strategies in arid ecosystems. Chapter 1 evaluated the potential of high-resolution, multispectral UAS imagery to classify perennial vegetation cover in the Mojave Desert and upscaled those estimates to coarser resolution, freely accessible satellite data using Random Forest modeling. Chapter 2 investigated an alternative to traditional photogrammetric workflows by treating individual aerial images as independent sampling units. These approaches together illustrate how UAS can bridge the gap between fine-scale and landscape-scale vegetation monitoring, enabling flexible, scalable workflows that adapt to management priorities and the ecological context within arid ecosystems
Advancing UAV-Based Remote Sensing and Machine Learning for Ecological Monitoring, Habitat Disturbance Detection, and Forensic Science in Arid Landscapes
No full textThe advances in unmanned aerial vehicle (UAV) technologies have the potential to revolutionize remote sensing. By integrating high-resolution low-altitude remote sensing data captured via UAVs with sophisticated machine learning algorithms, researchers can now analyze habitat disturbances, vegetation cover, and even the detection of threatened and endangered species with unprecedented precision. This synergy not only facilitates assessments of vegetation cover and health but also enhances the detection of anthropogenic impacts such as land degradation caused by off-highway vehicle (OHV) activity. Furthermore, these advancements hold significant promise for forensic science applications to assist in search and recovery, cold-case investigations, and disaster response. The deployment of UAV-based systems equipped with multispectral capabilities allows for comprehensive spatial analysis that can substantially improve management decisions and reduce workloads. We deployed multiple drone and camera systems at study sites within the arid deserts of the western United States to demonstrate low-cost, user-defined, scientific, and civil applications. In chapter one we use a UAV-based multispectral camera to classify vegetation with a goal of detecting individual plants of the endangered Peirson’s milkvetch (Astragalus magdalenae var. peirsonii) (PMV) within the Algodones Dunes, California. In chapter two, we use UAV imagery and innovative computer vision analyses to detect OHV tracks that disrupt fragile dune ecosystems; such modeling is crucial for understanding human impact on arid biomes and informing management practices. Finally, chapter three focuses on forensic applications, as we apply multi-spectral analyses via a UAV collection platform to detect surface skeletal remains in the Great Basin Desert—illustrating how low-cost aerial methods can serve multifaceted purposes in both conservation efforts and forensic investigations amid desert environments.
Our American deserts have often been ignored or simply perceived as obstacles enroute to more hospitable regions in riparian zones or along the coast, however, modern improvements in living conditions and immense growth in urban populations have increased interaction between humans and the desert landscapes of the west. Many more people enjoy the benefits of living and working in the American deserts than ever before, and this contact continues to place a heavy burden on fragile ecosystems that include many endemic species unique to the Sonoran, Mojave, and Great Basin Deserts. Our research, focused on arid landscapes, emphasizes the challenges unique to our deserts which require specific remote sensing solutions. Many of the desert locations in this study are hampered by direct access and the difficult nature of the rugged terrain creating a need for continuing development in drone technology to facilitate research in these regions. Reduced levels of moisture and high heat levels in summer require distinct remote sensing solutions as well as opportunities to conduct research not typical in other regions, such as our skeletal surface remains detection. Finally, the deserts decades-to-centuries long recovery cycle from fire, ground clearing, and disturbance heightens the growing awareness of the threat to these fragile ecosystems and the need for continuing research. Each project in this dissertation underscores both an interactive and automated approach to studying desert landscapes through user-oriented technologies tailored in the pursuit of advancing conservation and scientific efforts within arid landscapes
2023 Nevada High School Youth Risk Behavior Survey (YRBS): Urban, Rural, and Frontier Special Report
No full textCenters for Disease Control and Prevention, Nevada Division of Public and Behavioral Healt
Pattern Reversal Chromatic VEPs like Onsets, are unaffected by Attentional Demand
No full textAttention has been shown to modulate the visual evoked potential (VEP) recorded to reversing achromatic patterns. However, the chromatic onset VEP appears to be robust to attentional shifts. Functional magnetic resonance imaging (fMRI) responses to both chromatic and achromatic reversing patterns are also affected by attention. Resolution and comparison of these results is problematic due to differences in presentation mode, stimulus parameters, and the source of the response. Here, we report the results of experiments using comparable perceptual contrasts, pattern reversals, and a co-extensive and highly demanding multiple object tracking (MOT) task while exploring the effects of attentional modulation across both the chromatic (L - M) and (S - (L + M)) and the achromatic visual pathways. Our findings indicate that although achromatic VEPs are modulated by attention, chromatic VEPs are more robust to attentional modulation, even when using comparable stimulus presentation modes and in the presence of a highly demanding distractor task. In addition, we found that the majority of the modulation appears to be from a relative decrease in response due to the distractor task rather than a relative increase in response during heightened attention to the stimulus
Enhancing Flexibility, Operation, and Control in Modern Electricity Grids Through Robust Data-Driven Methods
No full textThe modern electric grid faces numerous challenges, including aging infrastructure, increasing demand, managing more frequent extreme weather events due to extreme climate events, and integrating renewable energy sources to promote infrastructure decarbonization. Furthermore, the growing digitalization of power systems has heightened vulnerability to security threats, complicating operational and planning processes. These changes, shaped by economic, technological, environmental, and political factors, have transformed the traditional grid into a smart grid with more complex power flows and system requirements, making reliable operation, monitoring, and control considerably more challenging. Traditional grid management techniques have become increasingly complex and require improvement to handle the growing interdependency between the grid and other infrastructure, such as cyber, and the increasing uncertainties resulting from variable renewable generation. Leveraging data-driven methodologies, such as machine learning and artificial intelligence, presents promising solutions to assist traditional grid monitoring and control platforms by analyzing complex interactions and behaviors among the grid and other systems. Data-driven approaches offer real-time management capabilities and effective forecasting tools, ensuring the smooth operation and control of energy and electricity systems. Furthermore, as grid-edge resources like distributed energy sources and flexible demand continue to grow, the urgency for increased grid flexibility to handle supply and demand fluctuations has intensified. These resources are inherently flexible, as they can be strategically monitored and controlled to shift electricity generation and consumption, providing ancillary services during peak periods. When managed effectively, flexible resources can offer critical grid services, such as day-ahead generation dispatch and peak load management, improving grid reliability and resilience. This dissertation proposes utilizing machine learning and artificial intelligence to enhance energy systems' operation, monitoring, and control. Given the vast amount of data available in today’s grid and the advancements in computing, these technologies present innovative solutions. Intelligent sensors, like smart meters, produce a wealth of data that facilitates advanced grid monitoring. Machine learning can identify hidden patterns and anomalies within extensive datasets, providing computational efficiency and scalability that surpass traditional methods. These techniques enable near-real-time solutions, enhancing grid reliability and resilience. Also, this dissertation proposes quantifying and coordinating the flexibility of grid-edge resources, evaluating the energy flexibility these resources can offer for grid services from a pricing perspective. In this quantification, grid network constraints are considered, as they are essential to the grid's operation and can significantly affect the reliability and efficiency of the overall energy system. These constraints represent the limitations in the grid’s physical and operational characteristics, influencing energy production, transmission, and consumption. Various customer types and their consumption patterns are examined to assess how quickly and to what degree customers can modify their consumption in response to energy savings incentives or signals. In summary, this dissertation explores leveraging data-driven methods to enhance grid operation, monitoring, and control. It also proposes quantifying and optimizing grid-edge resource flexibility for grid services while considering network constraints and customer consumption patterns
Engineering TIMP-Based Inhibitors with Minimal and Light-Controlled Designs to Modulate MMPs
No full textMatrix metalloproteinases (MMPs) are key mediators of extracellular matrix remodeling and are implicated in a wide range of pathological conditions, including cancer, neurodegenerative diseases, and cardiovascular disorders. Tissue inhibitors of metalloproteinases (TIMPs), particularly TIMP-1, serve as endogenous regulators of MMP activity but face limitations in therapeutic applications due to their size, broad specificity, and lack of spatiotemporal control. This dissertation presents three complementary engineering strategies to overcome these challenges and advance the development of TIMP-based inhibitors with enhanced precision and functionality.In the first approach, minimal TIMP variants were engineered by recombining sequences from all four human TIMPs using DNA shuffling and screening the resulting libraries with yeast surface display and FACS. Several minimal inhibitors as short as 20 amino acids were identified with nanomolar binding affinities (Kd) and picomolar inhibition constants (Ki) toward MMP-3 and MMP-9. These compact variants retained critical inhibitory motifs, including the CXC motif, and demonstrated potency comparable to the full N-terminal domain of TIMP-1, highlighting their potential as modular therapeutic scaffolds.
The second strategy focused on reversible light-controlled inhibition by fusing the photoswitchable fluorescent protein Dronpa145N to TIMP-1. Two fusion orientations were constructed—N-TIMP-1-Dronpa145N and Dronpa145N-N-TIMP-1—and evaluated using structural modeling, flow cytometry, and inhibition assays. Only the N-terminal Dronpa145N fusion enabled light-dependent modulation of MMP-3 inhibition, with cyan light triggering dissociation of tetrameric Dronpa and restoring access to the TIMP domain. These findings emphasize the critical role of fusion orientation and steric architecture in designing optogenetic protein inhibitors.
In the third approach, irreversible light-triggered activation was achieved using PhoCl, a photocleavable fluorescent protein. TIMP-1 was fused to PhoCl through SpyTag/SpyCatcher domains to create a light-sensitive steric cage. Upon violet light exposure, PhoCl underwent photocleavage, releasing the inhibitory domain and restoring TIMP-1 activity. Functional assays and AlphaFold3 modeling confirmed that only the cleaved N-TIMP-1-SpyTag configuration adopted an accessible conformation for MMP-3 binding and inhibition, with a significant decrease in Ki post-cleavage. This system demonstrated precise optical control over protease inhibition and underscored the importance of domain accessibility in functional recovery.
Together, these studies establish a versatile platform for the design of minimal and optogenetically regulated TIMP-based inhibitors, enabling dynamic, light-responsive control of MMP activity. This work lays the foundation for next-generation therapeutics targeting protease-driven pathologies with improved specificity, modularity, and precision
Effect of Vegetation Structure on Evapotranspiration and the Prediction of Evapotranspiration
No full textUnderstanding how vegetation structure controls evapotranspiration is important for predicting how changing climate conditions may influence hydrologic balances in different ecosystems. However, evaluating this topic across diverse ecosystems is often made difficult by the observational challenges associated with great spatiotemporal variability. The work in this dissertation utilizes unique network- and manually-collected ground-based field datasets and remotely sensed data at different spatial and temporal scales to evaluate how varying vegetation structures interact with components of evapotranspiration (ET). The components of ET studied here include canopy rainfall interception loss and storage across diverse forested ecosystems, and transpiration and soil evaporation in semi-arid shrublands. For interception loss, using data from 2073 storms across 22 forested sites, we found storm gross-precipitation depth was the most important variable for predicting the amount of interception loss. We also found that vegetation structure variables, while more important for predicting the percent than the amount of interception losses, had inconsistent relationships with interception losses across sites, suggesting that statistical models with vegetation structure metrics may not be best for predicting interception losses at broad spatial scales.
For canopy storage, using data from 648 storms across 15 forested sites, we found storage values did not vary considerably across sites, and found no consistent, strong relationship across sites between storage variation and the remotely sensed vegetation structure metrics we evaluated. These results suggest the common modeling convention of scaling storage with vegetation metrics is not more appropriate than assuming storage to be constant across forested sites.
For evapotranspiration in semi-arid shrublands, using data from micrometeorology stations at seven paired burned and control plots around the Great Basin, we found dry-season evapotranspiration was 15-77% lower and soil volumetric water content at soil depths ≥35 cm in the control plots was 16-70% of that of the burned plots. These results suggest fire-induced change in vegetation structure led to reduced soil water use and lower evapotranspiration.
Each of the topics in this work fall within the larger challenge in the field of hydrology of reconciling the difference in scales between what we can directly measure at individual sites and smalls scales, and the larger-scale prediction and modeling of water fluxes
Nanosecond Electric Pulses in Neuromodulation: A Journey from Isolated Adrenal Chromaffin Cells to Murine Tissue Slices
No full textNeuromodulation using nanosecond electric pulses (NEP) represents an emerging frontier in biomedical research, offering unparalleled precision for targeting cellular structures and modulating physiological processes. This dissertation explores the novel application of NEPs in adrenal chromaffin cells (ACC), focusing on transgenic murine models and transitioning from cellular studies to tissue-level investigations. Building upon foundational work in bovine ACC, we have developed innovative methodologies to stimulate and characterize responses in murine systems, advancing both the scientific understanding and technical applications of NEP-evoked responses.In isolated murine ACC, NEPs reliably elicited transient, reproducible responses with high signal-to-noise ratios, demonstrating their capacity to activate chromaffin cells without inducing sustained cellular damage using 5 ns pulses. These experiments revealed the characteristics of transgenic murine ACC activity in comparison to previous bovine ACC discoveries as being similar, reproducible, and reliable, serving as a crucial stepping stone toward more complex biological contexts. Expanding on these findings, we transitioned to functional imaging and stimulation studies in freshly prepared murine adrenal tissue slices. Within this intact tissue architecture, NEPs were shown to directly activate ACC, marking a pivotal advance in demonstrating their efficacy beyond simplified cellular models. These studies highlight the transient nature of NEP-evoked responses, providing insight into the physiological relevance of this approach of which more investigations are still required.
The foundational work presented in this dissertation bridges the gap between in vitro studies and ex vivo applications, emphasizing the translational potential of NEPs for neuromodulatory research. By building on techniques initially developed in bovine ACC studies, this research demonstrates the versatility and adaptability of NEPs as a tool for probing adrenal physiology. Furthermore, these findings establish a robust platform for future studies investigating adrenal medulla-cortex cross-talk, stress response modulation, and the eventual translation of NEP neuromodulation to in vivo models with potential for remote stimulation of ACC. This work underscores the promise of NEPs not only for advancing our understanding of adrenal physiology but also for their broader implications in therapeutic and neuromodulatory applications
Ctrl+Alt+Desire: A Mixed-Methods Assessment of Masculinity and Sexism in Online Narratives Documenting Commercial Sex Experiences in Nevada’s Legal and Illegal Commercial Sex Industry
No full textDespite the illegality of commercial sex work in most of the United States, the Internet has become a key tool for facilitating transactions between sex buyers and sex workers. Moreover, online communities, enabled by the Internet, provide a platform for sex buyers to exchange explicit details about their experiences, including prices paid, services received, and satisfaction with services received. Such communities present a unique opportunity to study the social-psychological processes influencing commercial sex buying – an area with limited existing empirical research. While existing research has delineated variations among sex buyers, such as diverse motives and dimensions of masculinity, there remains a scarcity of studies delving into how the identified masculinity "typologies" might influence sex buying and related behaviors. Further, even though there is recognition that ideals of masculinity are related to beliefs about and expectations of women, none of the same studies have examined how sexism might be connected to masculinity in sex-buying behaviors. Lastly, few studies have applied the concept of cost-benefit analyses to commercial sex-buying behaviors. Accordingly, this study aimed to explore whether previously identified masculinity typologies were evident within narratives posted in online commercial sex communities. This study also aimed to identify sexist ideals within the same narratives. Additionally, the study aimed to elucidate the connection between different practices of masculinity and expressions of sexist ideals and language, as well as satisfaction with commercial sex experiences. Lastly, the study aimed to explore sex buyers’ adherence to commercial sex laws in Nevada based on their masculinity typology.
This dissertation utilized the theories of masculinity, sexism, and social exchange theory to examine sex buyers' behaviors. More specifically, it explored how these frameworks collectively influence participation in the commercial sex industry, focusing on gender expression, gender inequality, and individual decision-making processes. By uniquely combining these theories, the research aimed to explain how masculine ideologies and sexist beliefs impact the rationalization of purchasing sex and the chosen location in which the sex is purchased. This novel approach aimed to provide insights into the social-psychological processes that enable participation in the commercial sex industry.
The study employed a mixed-methods approach using qualitative and quantitative content analysis and chi-square analysis. I adopted a non-participatory observer role (i.e., lurking) in two online communities where sex buyers discuss their commercial sex experiences. One community was focused on legal commercial sex (e.g., brothels), and the other community was focused on illegal commercial sex (e.g., street-based prostitution, Asian-massage parlors, etc.). From each community, I collected posts in which users reviewed and rated their commercial sex experiences that occurred in Nevada.
An analysis of 354 commercial sex reviews found expressions of masculinity and sexism, and exhibited a pattern between masculinity and sexism. Additionally, the study found patterns between masculinity, sexism, and satisfaction with commercial sex experiences. The study also found a pattern between masculinity and sectors of commercial sex, such that johns expressing elements of certain masculinity typologies appeared to be drawn to specific sectors of commercial sex. Lastly, the study found that descriptions – tone, vulgarity, and focus – of commercial sex experience differed significantly by sector of commercial sex. The findings of this study provide insight into the social-psychological processes that might influence sex-buying behavior, which has implications for prevention and intervention programs and the safety of providers