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Opportunities to Improve Heap Leaching Operations
No full textThis paper was presented at the Heap Leach Solutions Conference, October 19-21, 2025, Sparks, Nevada.The Heap Leaching operation during the last 40 years of my experience had a good evolution from operation point of view and technology implementation. However, in some cases the metal recoveries are lower than project design and target for several reasons. This paper has the intention to share the real examples where we improve the gold and copper recoveries in Heap Leaching with the biggest and smaller plant operations in Chile, Peru and Argentina, management important parameter how: application rate, irrigation network design, surface preparation, chart organization, etc
16S Microbial Profiling of Two Heaps in Southern Arizona Reveals Depth-Based Differences in Genus Distribution
No full textThis paper was presented at the Heap Leach Solutions Conference, October 19-21, 2025, Sparks, Nevada.Microbes colonizing mineral surfaces in leach systems can drive oxidation and reduction (redox) reactions with potential to both catalyse or impede leach chemistry according to environmental and electrochemical contexts. Leach pads comprise complex ecosystems of microbes with dimensional differences in temperature, irrigation, oxygen saturation, and nutrient or metal dissolution. These multidimensional environmental factors differentially impact the growth of certain microbes, which can in turn change microenvironments, and ultimately impact leaching kinetics. Therefore, surveying dimensional differences in native ore microbiomes is critical to optimizing hydrometallurgical operations. This study used 16S sequencing to survey 106 samples ranging from 30-700 feet (ft.) from 13 boreholes from two Southern Arizona sites: Site (A) and Site (B). This study identified depth-based differences in taxonomy and microbial substrate utilization with hydrometallurgical implications in both heaps. Shallow intervals (300 ft deep) contained thermophilic genera Geobacillus and Thermus. In both sites A and B, obligately aerobic microbes were identified in samples 0-635 ft. deep. Obligately aerobic microbes were absent from samples deriving from intervals 640 - 700 ft. deep. Anaerobic microbes were present at samples as shallow as ~275 ft. deep in A. These depth-based differences in oxygen consumption may reflect localized microenvironments in the heap with less oxygen saturation. In A and B, samples across all depths contained ecosystems with diverse substrate utilization featuring interspersed autotrophic, mixotrophic and heterotrophic communities. Tolerance for higher temperatures increased with depth wherein mesophilic microbes being more abundant above 200 ft. deep and thermophiles were abundant below 200 ft. deep
Three-dimensional wildland fuel mapping with remote sensing and machine learning
No full textThe 21st century has seen a global increase in fire size and severity, including the western United States. Historically loaded forests, changing precipitation patterns, and lengthening fire seasons place a significant strain on land management and firefighting capacity. Fire behavior is a fine scaled process affected by climate, weather, topography, and fuel. The amount and arrangement of fuels are of particular interest because they can be directly controlled by managers to manage present-day fire risk and influence future response to fire. Existing fuel maps have a coarse resolution that limits their utility to understand fire behavior. In this dissertation, I address this research gap by using airborne and terrestrial LiDAR (ALS, TLS; respectively) and machine learning to make fine scaled predictions of fuels beneath the canopy. In my first chapter I use a gradient boosting regressor to boost the signal of ALS at the surface floor by using the ALS signal itself as features. I demonstrate that this method does a better job of detecting changes in surface fuels after two forest fires compared to ALS alone. In my second chapter I use a generative deep learning model to reduce fine-scale occlusion in ALS point clouds, leading to better measurement of vegetation beneath the canopy. In my third chapter, I compare this method with ALS to examine changes in fuel loading before and after a forest fire. I also examine how these changes influence management by comparing differences in common fuel metrics. I found that the use of machine learning and deep learning can significantly improve the capabilities of ALS beneath the forest canopy
The Impact of Type II Protein Kinase A Subcellular Mislocalization on Stress Hormone Production
No full textSustainable Approaches to Enhance Water Productivity in Cucumis melo
No full textDrought poses one of the biggest threats to horticultural production by reducing plant growth, photosynthetic efficiency, and yield. Sustainable strategies such as grafting, deficit irrigation, and an improved understanding of plant-water relations offer potential solutions to enhance crop water productivity (CWP). This study conducted at the University of Nevada, Reno, evaluates three sustainable approaches to increase CWP in melons (Cucumis melo L.) under high desert conditions: (1) the effect of melon grafting on yield using squash hybrid rootstocks, (2) determining the physiological transition from water-consumptive to water-conservative (impaired photosynthetic activity) in the water potential curve (predawn and midday water potential relationship) in response to progressive drought stress of grafted and ungrafted melons, and (3) the impact of two-levels of consistent deficit irrigation regimes, moderate (70% of full irrigation ) and severe (50% of full irrigation), on melon’s physiology, yield, and CWP. Results showed (1) no significant yield advantage of grafting melons onto squash hybrid rootstocks, with outcomes highly dependent on environmental factors (i.e., location and seasonal weather). (2) A Piecewise linear regression model best conceptualized the water potential curve, effectively predicting the transition from water-consumptive to water-conservative behavior at -0.72 MPa of predawn water potential under field condition. The water potential curve may offer a valuable tool for irrigation scheduling and the breeding of drought tolerant crops. (3) Moderate deficit irrigation maintained yields comparable to full irrigation, while saving approximately 25% of water and increasing CWP. Integrating plant physiological modeling and deficit irrigation could be used to enhance drought resilience and CWP in melons and potentially other horticultural crops
Impact of Lens Angle and Nozzle Geometry on Aerodynamic Focusing: A Numerical Study
No full textStraight-edge thin plate orifices (90° half angle) are used as the focusing elements in most aerodynamic lenses. They are simple to fabricate and have fewer boundary layer effects as compared to other geometries such as capillaries, converging nozzles, and diverging nozzles. The focusing performance of these other geometries has not been systematically evaluated. This study used computational fluid dynamics (CFD) simulations and Lagrangian particle tracking to investigate aerodynamic focusing of converging and diverging orifices with half angles ranging from 30° to 150° at two Reynolds numbers (50 and 100) and three Mach numbers (0.03, 0.1, and 0.3). The results show that the optimal Stokes number (Sto) for near-axis particles have small differences between the straight-edge orifice and the converging or diverging orifices, indicating small changes in focusing behavior for different lens geometries. This study also investigated the effects of varying dimensions of the exit nozzle on particle terminal trajectories into the vacuum chamber. The nozzle has a cylindrical constriction upstream of the exit orifice. Several nozzle radial aspect ratios and lengths of the constriction were simulated in a two-dimensional axisymmetric domain. The nozzle geometry that generates the least divergent particle path in the vacuum chamber as well as geometry that maintains the highest transmission efficiency for particles in the size range of 10 nm – 10 μm is identified
The Invisible Landscape: Statistical Characterization and Simulation of Large-Scale Outdoor Odor Plumes
No full textThis thesis addresses fundamental challenges in chemical plume tracking and odor source localization across large outdoor scales, with applications in environmental monitoring, disaster response, and public safety. Utilizing extensive field data collected from diverse environments such as the Black Rock Desert and Whittell Forest, I demonstrate that integrating statistical features of odor encounters over time enables accurate source distance estimation, with achievable median errors of 3-8 meters. This work reveals the importance of using a memory and highlights the most relevant statistics that could be used to localize the source. It also reveals that high temporal resolution sensing (at least 20 Hz) is essential for extracting useful distance information from odor signals.The thesis also introduces COSMOS (Configurable Odor Simulation Model Over Scalable Spaces), a novel probabilistic data driven simulation framework that combines empirical data with adaptive state transitions based on historical experience of odor encounters and autoregressive modeling to realistically reproduce the odor experiences of an agent moving through complex plumes across large spatial scales while maintaining computational efficiency. Comprehensive validation confirms the framework's ability to accurately replicate key statistical features of natural odor plumes, making it a valuable tool for developing and evaluating odor-tracking algorithms.
Finally, a ROS-based simulation environment incorporating quadrotor and wind dynamics extends these insights to aerial vehicle applications. Together, these three complementary components—empirical distance estimation, data-driven odor experience simulation, and real-time simulation in a physics enabled robotics simulator (Gazebo-ROS) that can be directly translated to a real system—establish a comprehensive pathway toward developing autonomous outdoor plume-tracking robots for real-world deployment. The thesis concludes by identifying promising directions for future research, including multi-modal sensing integration, enhancements to the COSMOS framework, and swarm-based approaches to odor source localization
Examining Influential Factors on the success of Project Management in Education: A Content Analysis
No full textThere has been an amplified demand for project management skills in the workforce and with the ever-evolving technology, the importance of project management in education has become increasingly evident. Project management is a complex discipline, and educators know that every project is assigned limited resources, but they must identify and define the critical path to success so that the project is completed on time and within budget and renders results that meet the expectations of the diverse stakeholders. As educational institutions increasingly navigate change, reform, and digital transformation, the demand for strategic, principle-centered project management approaches is more pressing than ever. Also, the growing integration of artificial intelligence introduces both new opportunities and complexities into project management in education. Based on contingency theory, the Technology Acceptance Model (TAM), and Agile methodology, this study investigated the key project management principles that contributed to success of project management cases in education indicated by its value, and it identified the principles that had most influence on the project value. The study utilized a correlational research design and quantitative content analysis method. Data was collected from studies in project management in education conducted between 2010 and April, 2025. The literature yielded 4,312 publications. After careful screening, 104 articles were included in this study. Data analysis was conducted using logistic regression and Chi-Square tests. The result from the logistic regression shows that five of the principles are significant predictors of the success of a project.
Findings affirm that project management, rooted in strategic leadership, systems awareness, and responsiveness to complexity is critical to navigating the challenges facing modern educational institutions. The study contributes a practical and theoretical framework for fostering adaptive project cultures that align with institutional goals and stakeholder needs. The study concluded with a discussion of practical implications and recommendations for future research
Developing Free Radical Initiated Peptide Sequencing towards the Analysis of Complex Mixtures
No full textProteomics characterization of complex samples is often employed to determine protein conformation and functions. Tandem mass spectrometry (MS/MS) is one of the predominate techniques for providing information on the amino acid sequence and the site of protein post-translational modification, where free radical initiated peptide sequencing (FRIPS) is an example. However, with unwanted neutral losses, complex mixture analysis can be challenging because ion abundance can be shuttled away from sequence-informative fragment ions, leading to decreased ion abundance and reduced sequence coverage. To be employed in more complex systems and proteomics workflows, the efficiency of sequence ion generation must be improved for multiply charged ions, which are frequently generated in proteomics workflows. This dissertation presents the development of radical-driven MS/MS (FRIPS) for improved peptide characterization towards the analysis of complex mixture. There have been different forms of radical-driven tandem mass spectrometry (MS/MS) techniques ranging from UV photodissociation of photolabile radical precursor (UVPD), UV photoexcitation of peptide cations (UVPE), among others. However, the radical-based method employed for this dissertation often displays distinctive benefits such as low cost (requires no extra instrumentation), unique thermal stability, and ability to examine singly and even negatively charged peptides when compared with electron-based techniques. By considering peptide radical ion fragmentation of specific PTMs, FRIPS MS/MS has often been seen as one of the most efficient techniques, able to couple to a proteomic setup without difficulty. Although several studies deal with the analysis of FRIPS-MS, few research reports the application of the para-FRIPS tag for peptide characterization. Importantly, no research has reported using negative mode collision induced dissociation-trapped ion mobility spectrometry (CIDtims) coupled with FRIPS-MS for peptides and phosphorylated peptide analysis. The para-TEMPO-FRIPS reagent allows for electron delocalization and steric protection during the reaction. The work carried out in this dissertation is expected to open new research horizons, particularly in the analysis of complex mixtures, including post-translational modification, protein pharmaceutical development, biological, and physiological processes. In addition, through this peptide backbone dissociation technique, the gas-phase digest of large PTMs-containing peptides can be examined.
In chapter 2, we demonstrate that free radical initiated peptide sequencing (FRIPS) as a radical-driven technique improves the performance of positive-ion mode peptide characterization. This is done through the comparison of the dissociation behavior of the ortho- and para-FRIPS tags. These tags are chemical reagents that when conjugated to a peptide/protein, can facilely degrades into radicals upon activation. Results from this chapter reveal that compared to the commonly utilized ortho-FRIPS tag, the para counterpart overcomes high abundance of neutral losses, increase sequence coverage, and can be a promising tool in FRIPS-MS workflow.
In FRIPS-MS, all product ions can be generated, so the complexity of FRIPS fragmentation requires the use of high-resolution mass spectrometers which are often slow. Our hypothesis is that ion mobility spectrometry (IMS) could be an alternative method for deconvoluting these spectra on a high-throughput mass spectrometer. In chapter 3, we investigate the utility of ion mobility spectrometry-mass spectrometry (IMS-MS) to assist in para-TEMPO-Bz FRIPS-based fragmentation by increasing the Δ6 direct current (DC) voltage and controlling the pressure within a trapped ion mobility spectrometry (TIMS) device. We demonstrate that a recently developed method from our group, collision induced dissociation-trapped ion mobility spectrometry “CIDtims” can initiate the homolytic cleavage of the FRIPS precursor. We then examine if the resultant ion mobility separation results in additional assignments of product ions and improved sequence coverage. We demonstrate that activation within the TIMS device promotes robust radical initiation and fragmentation of peptide cations. The generated product ions are mobility separated, enabling facile assignment and increased sequence coverage.
PTMS can be labile in positive mode analyses and efficient localization of them may require negative-mode analyses although our technique “CIDtims” has not been tested in negative mode. In chapter 4, we demonstrate that activation within the TIMS device can be further extended in the negative ion mode. Here, IMS activation was employed prior to the collisional activation step, enabling the radical initiation in doubly protonated and deprotonated peptides and in phosphorylated peptide anions within a trapped-ion mobility spectrometry device. This process does indeed promote robust radical initiation of deprotonated peptide. Generated radical species are subjected to isolation by the quadrupole and further activated in the collision cell. In negative mode, this two-step activation enables increased sequence coverage of examined peptides. Promisingly, the ion-mobility-assisted fragmentation technique can be developed as a new pseudo-MS3 workflow for applying FRIPS-based PTMs proteomics in negative mode.
From the studies described in this dissertation, in the future, we will examine the ability of this TOF-based FRIPS workflow to annotate the location of labile post-translational modifications. We will also investigate whether the “CIDtims” can be coupled with liquid chromatographic separations and utilize this FRIPS-LC workflow to annotate post-translational modification in complex mixtures
A Language Convergence Meaning Divergence Perspective on Toxic Relationships
No full textThis study uses the Language Convergence, Meaning Divergence Theory and the sensitizing concepts of toxic, domestic violence, and perception as reality to analyze how
individuals on Reddit define toxic relationships and domestic violence. This study
utilized taxonomic analysis to find the semantic relationships individuals associate with
the terms toxic and abuse, which revealed the five semantic relationships of attribution,
strict inclusion, cause, effect, and rationale. The study revealed a clear overlap, or
convergence, of semantic relationships for toxic and abuse regarding behaviors, harms,
and causes. Additionally, divergences were found within how individuals defined abuse
regarding substance use and the generational cycle of abuse. This study outlines
implications for the findings and directions for future studies