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Effects of Training and Self-Monitoring on Paraeducators\u27 Use of Behavior Specific Praise
No full textParaeducators support students with disabilities in special education classrooms but often receive limited training in effective behavior support strategies. This study examined whether training combined with self-monitoring increased paraeducators’ use of positive, specific praise and reduced the use of reprimands during instruction. Paraeducators were trained to use and track their own praise while working with students. Results showed increased use of positive praise and decreased reprimands following the intervention. These findings suggest that brief, low-cost training and self-monitoring can improve paraeducator instructional practices and support positive classroom environments for students with disabilities
Characterizing Metabolic Flux of Plant Secondary Metabolites From Diverse Animal-Source Foods to Humans
No full textThere is a popular saying: “You are what you eat.” But does this also mean, “You are what your food eats”? This dissertation explores that question by examining how farming practices shape the nutritional quality of meat—and what, if anything, those differences mean for the people who consume it. While modern livestock production and nutrition research often emphasize protein and fat, this work tests the idea that animals function as biological mediators, linking soil and plant conditions to human diets through the chemical composition of meat and milk. To evaluate this hypothesis, we tracked health-relevant plant compounds— phytonutrients—across the soil–plant–animal–human continuum through five complementary studies. First, a comprehensive review of scientific literature found that ruminants (such as cows and goats) do not simply accumulate plant compounds; they can bio-transform plant material into distinct antioxidants detectable in meat and milk, supporting the view that animal foods participate in a broader phytochemical ecology. Next, we analyzed beef produced under grass-fed and grain-based finishing systems, spanning local research sites and a large North American survey of more than 100 operations. Across these datasets, production system was associated with consistent nutritional differences: grass-fed beef contained higher concentrations of antioxidant-related compounds, including vitamin E, β-carotene, and multiple plant-derived phenolics, whereas grain-fed beef tended to be higher in several B-vitamins. These results indicate that what cattle eat leaves measurable “metabolic fingerprints” in the food they produce. To place these findings in an evolutionary context, we compared domesticated livestock products to a reference benchmark—wild game species such as elk, deer, and nilgai. Because wild herbivores forage from highly diverse plant communities, their tissues exhibited substantially greater phytochemical richness (ranging from 260 to 1030%-fold higher concentrations) and more unique metabolite profiles than feedlot-finished meat, highlighting the extent to which dietary simplification in production systems can dilute bioactive food compounds. Finally, we asked whether food-level differences translate into measurable changes in humans. In a controlled randomized crossover trial, participants consumed diets sourced from either regenerative or conventional agricultural systems for six weeks. Regenerative foods generally contained higher concentrations across multiple phytonutrient classes, but the human response was selective: plant-derived markers increased, whereas other compounds (including carotenoids) appeared more tightly regulated and did not shift rapidly over the study period. Importantly, a whole-food dietary pattern improved several health-related markers regardless of production system, underscoring that overall diet quality remains a major driver of health outcomes. Together, these studies demonstrate that agricultural management can meaningfully reshape the bioactive chemistry of animal foods. Meat from diverse, pasture-based systems may offer a nutritional “bonus” in specific compounds, but the translation to human biology is nuanced—suggesting that improving both agricultural practices and overall dietary patterns will be most important for advancing public health
Pest Management for Utah Cut Flower Production: Insects and Their Relatives
Get PDFPest management is important in cut flower production, marketability, and farm profitability. This fact sheet focuses on animal pests (insects, arthropods, mollusks, and vertebrates), not diseases or weeds, and has two parts. Part 1 applies Integrated Pest Management (IPM): using preventive techniques, pest thresholds, and best management practices with pests in cut flower crop production. Part 2 highlights the top 10 common pests of cut flowers in Utah and their management
Compilation of a Nationwide River Image Dataset for Identifying River Channels and River Rapids via Deep Learning
No full textRemote sensing enables large-scale, image-based assessments of river dynamics, offering new opportunities for hydrological monitoring. We present a publicly available dataset consisting of 281,024 satellite and aerial images of U.S. rivers, constructed using an Application Programming Interface (API) and the U.S. Geological Survey’s National Hydrography Dataset. The dataset includes images, primary keys, and ancillary geospatial information. We use a manually labeled subset of the images to train models for detecting rapids, defined as areas where high velocity and turbulence lead to a wavy, rough, or even broken water surface visible in the imagery. To demonstrate the utility of this dataset, we develop an image segmentation model to identify rivers within images. This model achieved a mean test intersection-over-union () of 0.57, with performance rising to an actual of 0.89 on the subset of predictions with high confidence (predicted \u3e 0.9). Following this initial segmentation of river channels within the images, we trained several convolutional neural network (CNN) architectures to classify the presence or absence of rapids. Our selected model reached an accuracy and F1 score of 0.93, indicating strong performance for the classification of rapids that could support consistent, efficient inventory and monitoring of rapids. These data provide new resources for recreation planning, habitat assessment, and discharge estimation. Overall, the dataset and tools offer a foundation for scalable, automated identification of geomorphic features to support riverine science and resource management
Design of a Low-Power Magneto-Inductive Magnetometer
No full textMeasuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better predict and understand space weather events that impact our everyday technology while advancing the development of power-efficient space instrumentation
Constraint-Aware Metaheuristic Optimization for Experimental Design
No full textDesigning experiments becomes much more challenging when many variables and strict constraints are involved, as is common in modern science and engineering. This thesis introduces a new computational and mathematical framework that efficiently searches for optimal experiments in complex, high-dimensional spaces where traditional methods fail. By combining geometric techniques with flexible optimization algorithms like particle swarm optimization, our methods handle difficult constraints while scaling to real-world problems. Built in the high-performance Julia programming language and released as open-source software, this work bridges advanced theory with practical tools, offering researchers a powerful and accessible way to design better experiments under realistic conditions
Aerodynamic Parameter Estimation for a Scaled F-16: A Simulation-Based Sensitivity Analysis
No full textThe physical motion of an aircraft is determined by the resulting forces and moments acting on the aircraft. These forces and moments can be defined as a mathematical equation where the control deflections, rotation rates, and orientation of the aircraft are multiplied by individual constants and summed together to define the entire force or moment. This method results in a highly accurate model that defines the motion of the aircraft at low angles of attack and sideslip. Initial calculations of the aerodynamic model are created based on analytical estimations based on the physical properties of the aircraft. Additional refinement of the model is achieved in flight testing. During flight tests, the physical states of the aircraft, such as orientation, translational motion, and rotational motion, are recorded as well as the input commands for the aircraft. An analysis of the input commands and the output states provides the necessary data to define the aerodynamic model of the aircraft. This method of defining the motion of an object based on the input commands and the output states is called system identification. The aerodynamic model resulting from the system identification method is highly dependent on the accuracy of the input and output parameters as this is the only available information in the process. This high dependence demands a robust method to analyze and manage the error that is inherent in measurements. Most research in the area of error analysis in system identification focuses on removal or management of error. This research analyzes how much effect individual sensor error and assumptions have on the resulting aerodynamic model. This research identifies a robust maneuver input that provides sufficient measurement data for the system identification method. A best-case scenario will be tested in a simulation environment to determine what accuracy is possible with the specific maneuver case. The simulation environment provides direct control of introduced errors and assumptions, providing a platform to test the influence of each error and assumption on the resulting aerodynamic model. The results show that model assumptions need to be carefully analyzed to understand the effect on the resulting aerodynamic model. The assumption that the velocity of the aircraft can be simplified to be the forward velocity, which is the velocity measured by the pitot tube, is an erroneous assumption and highly corrupts the result. The second result that introduced significant error is using the commanded control inputs instead of the actual physical position of the control surfaces. This analysis shows the need to accurately measure or estimate the full velocity vector and the true control surface deflections. The results can provide practical guidance for designing a successful flight test, helping engineers determine what sensors are necessary and which assumptions must be avoided to build a flight test platform that can successfully find the aerodynamic model through system identification
Vines in the Landscape: Virginia Creeper
No full textVirginia creeper (Parthenocissus quinquefolia) is a vigorous and aggressive deciduous vine in the grape family (Vitaceae), known for its rapid growth, dense foliage, and striking fall color. Some landscapers consider this plant a nuisance because of its aggressive growth, potential damage to weak structures, and difficulty in removing, but others love it for its potential for erosion control, rapid coverage, fall color, and as a bird and pollinator habitat
Effects of Beaver Dams on Components of Riverscape Health and Biodiversity in the Great Basin
No full textNetworks of rivers and their floodplains (i.e., low-lying areas adjacent to rivers and streams that could plausibly flood) have been degraded, reducing the availability of freshwater and habitat for people and wildlife. Therefore, land managers are pursuing cost-effective restoration strategies, including partnering with beavers (Castor canadensis), to promote the health of these ecosystems and associated benefits. However, our understanding of beaver-mediated restoration benefits remains incomplete. Here, we compared locations along streams with and without beaver dams to measure the benefits of beavers in the Great Basin of the Western United States. We measured the effects of beaver dams on i) stream depths and depth variability, interactions between the stream and surrounding floodplains, and water movement as ecosystem health indicators; and ii) number of unique species, diversity, and activity levels for various fish, bat, and bird taxa as biodiversity indicators. We further investigated how the benefits of beavers varied by dam status (i.e., actively maintained or abandoned), and across valley settings, from steep and narrow valleys to low-gradient and wide valleys. Our results showed deeper and more variable stream habitats, stronger connections between streams and floodplains, and slower-moving water in stream segments with beaver dams than in segments without. Importantly, we found that the benefits of beaver activity are influenced by valley setting and that many benefits persisted even after dam abandonment. Although we found little difference in biodiversity indicators, the benefits of beaver dams to other components of ecosystem health likely contribute to diverse habitats that benefit biodiversity beyond individual stream segments. As interest in nature-based restoration grows, understanding the variable effects that beavers have on ecosystem processes within and across regions can inform the feasibility, potential effectiveness, and benefits of beaver-mediated ecosystem health restoration