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Baseball Blues, Song Lyrics, 1978
Get PDFLyrics for Baseball Blues, a song written by Bill Gessner in April 1978. The song regards a dream he had while napping in his favorite chair while listening to a game. The lyrics are typed, with hand written revisions. One sheet of paper, which was a photocopy from the book Private Screenings.https://commons.und.edu/gessner-lyrics/1009/thumbnail.jp
Concept Application Of Active Magnetic Bearing Technology For Offshore Horizontal Axis Wind Turbines
Get PDFWind energy continues to lead the global transition to renewable power, driven by its minimal environmental impact and high scalability. Offshore wind farms benefit from stronger and consistent wind resources. However, these advantages are tempered by challenges related to installation, maintenance, and drivetrain reliability. Conventional bearings, which support the drivetrain system, are prone to wear related failures due to lubrication breakdown and mechanical fatigue from continuous loading. This study explores the integration of Active Magnetic Bearings as an alternative to conventional bearings in offshore Horizontal Axis Wind Turbines. Using advanced engineering simulation tools, the main driveshaft of a 130 MW wind turbine was remodeled and optimized to facilitate the integration of magnetic bearings. Also, a bench test using scaled wind turbine models was conducted to examine the performance characteristics of both bearing systems. Simulation results show that shaft weight and input current characteristics significantly affect the geometric features and magnetic field properties of the AMB system respectively. The bench test findings indicate that wind turbines using conventional bearings achieve higher power output and efficiency when the shaft mass is increased, due to enhanced rotational inertia and reduced friction effects provided by smaller-sized bearings, particularly when coupled with an optimized blade pitch angle. In contrast, turbines supported by magnetic bearings demonstrated superior performance when the shaft was optimized for reduced weight, highlighting the latter system’s efficiency under low-load conditions. Overall, the results emphasize the performance trade-offs between bearing types and underscore the potential of AMBs in enhancing turbine compactness and efficiency, especially in offshore or spatially constrained environments. While real-time control and scalability remain areas for further development, this study provides a strong foundation for future innovations in magnetic bearing integration for wind energy systems
The Ability Of The Millon Pre-Adolescent Clinical Inventory (M-PACI) To Distinguish Between ADHD And Non-ADHD Clinical Groups
Get PDFThe M-PACI is a personality scale based on Millon’s biosocial personality theory designed to measure emerging personality patterns in pre-adolescents (9-12 years old). There is minimal published research on this inventory, particularly in clinical contexts. For this study, we used a data set collected at a Midwestern private practice clinic where children are assessed for ADHD and learning disabilities. This study looks at how those diagnosed with ADHD differ in emerging personality patterns and current clinical signs scales compared to those in a clinical sample who have not been diagnosed with ADHD. Some studies have shown differences between children diagnosed with ADHD versus non-ADHD groups. Our hypothesis was that those in the ADHD would score significantly higher on the unruly, attention deficits, disruptive behaviors, and anxiety/fears scales. Our study found no significant differences between the ADHD and non-ADHD group on these scales. Additionally, post hoc tests revealed no significant differences between ADHD and non-ADHD groups on other personality and clinical symptoms scales. Limitations may include an underpowered study due to low participant numbers
Integrating Cognitive And Visual Scanning Strategies In Flight Instruction: Effects On Student Pilots’ Learning During Approach And Landing
No full textThis interdisciplinary study employed a convergent parallel mixed-methods design to advance innovation in aviation education by incorporating eye tracking technology with enhanced performance traceability through visual modeling and comparative feedback. Specifically, the study investigated student pilots’ scanning behavior, cognitive strategies, and proficiency development on a normal approach and landing task by modeling flight instructors’ cognitive behavior. The first research phase revealed statistically significant differences in scanning ratios between 10 flight instructors and 10 student pilots along with substantial performance variation. The result showed that student pilots exhibited excessive outside fixation, often failing to monitor or respond to energy management in a timely manner. In the second research phase, a separate cohort of 10 student pilots took part in a structured training intervention—comprising three training modules—designed to model flight instructors’ scanning behavior and gain an understanding of cognitive awareness. Post-intervention analysis shows student pilots exhibited a significant reduction in excessive outside fixation and alignment toward flight instructors’ scanning ratios along with performance improvements per ACS standards for the Private Pilot airplane. Thematic analysis of student pilots’ interviews across the training modules highlighted the value of technology-assisted learning for enhancing conceptual clarity and self-assessment and for reducing teaching ambiguity with a deliberate, cognitively engaged learning style by bridging the instructional gap beyond the traditional training method.Keywords: education, aviation, technology-assisted learning, eye tracking, scanning technique, cognitive behavior, teaching methodology, flight instruction, approach and landing
A Stochastic Framework For Hosting Capacity Analysis Of Residential Distribution Systems With Solar Photovoltaic And Electric Vehicle Adoption
No full textThe rise of distributed generation and the electrification of transportation are driving fundamental changes in the electric grid. The growing adoption of electric vehicles and solar rooftops introduces significant uncertainty in demand patterns, posing new challenges for the operation of distribution systems. Residential distribution systems are particularly vulnerable to the impacts of residential solar photovoltaics (PV) generation and electric vehicle charging, as they introduce significant variability and localized stress on the grid. To ensure reliable and efficient operation, utilities must account for the long-term growth of these technologies in their planning processes. While substantial progress has been made in assessing hosting capacity for community and utility-scale solar PVs, the effects of widespread residential solar PV and electric vehicle (EV) adoption on distribution system performance remain largely underexplored. This gap exists due to the absence of computational models that link distribution system operations with the underlying factors driving individual-level adoption of electric vehicles and rooftop solar PVs. The challenge lies in capturing uncertainty on two fronts: the adoption of distributed energy resources and electric vehicles, and the variability of solar-based generation and EV charging demand, as they depend on climate conditions and user behavior.
This dissertation explores the key socio-economic, perception and geographical factors driving EV and residential solar PV adoption in the US. Household traits and perception-based variables emerge as important indicators of potential electric vehicle and rooftop PV adoption. While multiple vehicles, homeownership, higher household income, gas prices, and winter temperatures drive EV adoption in both rural and urban areas, urban EV adoption is particularly higher among households with young or no children. In contrast, rural households with very high incomes, technological awareness, and high concerns about fuel cost are more likely to adopt EVs.
Social interaction or peer influence emerged as the strongest driver of residential PV adoption. It implies that peer influence plays an important role along with financial and technological factors in driving PV adoption. Similar to EV adoption, homeownership, moderate income, and higher education are common characteristics of PV adopters. Potential adopters are invested in PV systems’ ability to reduce energy costs, provide backup power, and benefit the environment, whereas non-adopters often view solar as politically driven and express low trust in installers. However, both EV and PV adoption are not uniform across the US. Therefore, the adoption datasets are typically imbalanced, with relatively few adopter records compared to non-adopters. To address this issue, this dissertation work introduces an ensemble learning approach to improve estimation accuracy and the reliability of adoption projection.
Assessing the hosting capacity of distribution systems requires the development of a detailed simulation model with the grid topology and variations in load demand. In this dissertation research, a distribution system model of a rural feeder is constructed using utility-provided network and consumer demand data. The model reflects typical demand patterns, with weekdays exhibiting morning and evening peaks. A stochastic hosting capacity analysis technique is developed in this dissertation that captures the impact of uncertain residential solar PV and EV adoption along with EV charging load and PV generation by assigning probability distributions to key input variables. The development process involves deriving adoption patterns from ensemble classification model outputs, while regional travel behavior, charging preferences, and weather conditions are used to build multiple EV charging and solar generation profiles. Each stochastic scenario simulates a unique set of conditions under operational constraints, and the outcomes are compared to evaluate how changes in these parameters influence hosting capacity across the distribution system. A regression analysis is further conducted to identify the relationship between adoption-related factors and the load and generation hosting capacity of the distribution grid.
The results indicate that reverse power flow and overvoltage are the primary constraints for PV hosting capacity, whereas load hosting capacity is limited by either thermal loading or undervoltage issues. Single-phase sections farther from the substation are more vulnerable to undervoltage issues due to high EV charging loads. The regression analysis implies hosting capacity of three-phase sections is directly influenced by feeder-level PV and EV adoption rates, whereas the hosting capacity of single-phase sections distant from the substation depends on local PV and EV adoption rates and charging parameters. Finally, this comprehensive approach enables a more realistic and data-driven evaluation of hosting capacity, taking into account the complex and uncertain nature of future distributed generation and electric vehicle integration in distribution systems
Preparing Rural Interstates For Connected And Autonomous Vehicles: A Legislative And Microsimulation Study Of I-29 In North Dakota
No full textRural interstate corridors in the Upper Great Plains face distinctive challenges to the deployment of Connected and Autonomous Vehicles (CAVs), including limited broadband-enabled traffic control, sparse roadside infrastructure, severe winter weather, and fragmented legislation. Although these corridors carry a substantial share of lane miles and freight traffic, they are underrepresented in CAV research despite higher crash rates and more severe operational disruptions than urban networks. These conditions create a pressing need to examine both institutional readiness and the operational impacts of CAV adoption. This study follows a two-part methodology. First, it conducts a legislative and policy review of all fifty states to identify gaps in safety standards, liability provisions, cybersecurity protections, and rural deployment readiness, with a focused comparison of the Upper Great Plains that highlights further deficiencies in cross-border data sharing, freight platooning policies, and permitting practices. Second, it develops a microsimulation of the I-29 corridor between Fargo and Grand Forks, North Dakota, using traffic and geometric data from NDDOT. Five CAV penetration scenarios (20, 40, 60, 80, and 100 percent) were evaluated under two driver behavior frameworks: the internal Wiedemann 99 model with CoEXist Cautious, Normal, and Aggressive profiles, and an external Intelligent Driver Model (IDM) implemented through a C++ dynamic link library. Performance measures included delay, stops, speed, and safety conflicts using the Surrogate Safety Assessment Model (SSAM). The findings reveal wide variation in CAV legislation across the United States, with rural states showing critical gaps in permitting consistency, liability rules, and broadband-based traffic management. Recommended actions include harmonized permitting, standardized liability provisions, and targeted infrastructure investment. Simulation outcomes confirm that higher CAV penetration improves mobility and safety, with the external IDM model achieving the strongest gains. Under the 100 percent IDM scenario, rear-end conflicts decreased by 79.96 percent, lane-change conflicts by 67.16 percent, and overall conflicts by 76.67 percent, while the internal model achieved a 60.86 percent reduction at full adoption. These results provide policymakers, transportation agencies, and industry partners with evidence-based guidance for advancing safe and sustainable CAV deployment on rural interstate corridors
Of Birds And Beef: Expanding The Knowledge Of Rotational Grazing Systems On Grassland Bird Productivity In North Dakota
No full textCattle grazing is one of the main economic contributors driving grassland ecosystem existence across the landscape. Cattle grazing can impact a variety of aspects of grassland ecosystems functions, including which wildlife species use them and in what ways. Given the drastic declines in grassland passerines, it is especially important to understand how different grazing practices affect critical population metrics such as reproductive success, clutch size, and number of fledglings. There is a wealth of research on grassland passerine reproductive in response to grazing systems throughout North America; however, most of the existing literature studies more traditional, longer rotational (LR) grazing practices with few studies in North Dakota and limited information on high intensity, short duration (HISD). In HISD systems, higher cattle densities, smaller paddock sizes, shorter durations in paddocks and longer rest periods are common characteristics that could impact habitat selection and reproductive success by birds. Moreover, because working landscapes rely on the ranchers who employ such practices, there is a need to understand how the values, intents, and motivations may influence ranchers towards different grazing practices that ultimately impact the wildlife using the grasslands. In this study, we investigated passerine use and reproductive success across 4 HISD and 4 LR sites in North Dakota during May to August from 2021 – 2023. In addition, we used semi-structured interviews to conduct a qualitative analysis of ranchers to determine the values, intents, and motivations that may set apart HISD from LR grazing practices. We found no difference in daily nest survival in passerine guilds (ground, suspended, and canopy nesting passerines) between the two grazing practices, despite differences in cattle density, duration in paddock, and paddock size. Further, we found less than 2% of all the nests in our study period over the three years were trampled, which was opposite of our initial hypotheses that increased cattle densities in smaller paddocks would have resulted in greater trampling rates. In HISD sites, we observed greater parasitism rates from Brown-headed Cowbirds (Molothrus ater), which resulted in increased daily nest survival and nest survival estimates but lower host clutch sizes and fledging success from host species compared to those metrics on LR sites. From area transect surveys conducted twice each summer, we found similar species composition with slightly more species in HISD sites than LR sites. Of note, Chestnut-collared Longspurs (Calcarius ornatus) were more numerous on LR sites compared to HISD sites. When examining vegetation characteristics between the LR and HISD sites, we found the two grazing practices ultimately had the same utilization across plots after grazing had occurred, and this likely shaped our limited differences in bird reproduction and bird use. Generally, it appeared that although ranchers were grazing in different ways, they were ultimately grazing to similar vegetation outcomes and that cattle densities were not as intense on the HISD as assumed would be the case from rancher discussions during site selection. Further, HISD ranchers in North Dakota may have intense rotations but not necessarily intense grazing outcomes. Finally, from our interviews we found that regardless of grazing practices, ranchers share a lot of values and motivations that guide their way of life. These included strong values associated with forage/grass production, a focus on their families, and the autonomy that the ranching way of life brought to them. They were frequently motivated in succession planning in their multi-generational operations. Differences were observed in intents such as HISD ranchers intended to build better resiliency in their forage/grass production through increased rest periods, which helped them battle drought. Comparatively, LR ranchers intended to ranch more simply, and not have to worry about the increased labor or costs associated with intensive grazing management like increased fencing or water availability. Future research should continue to examine vegetation outcomes to better understand specific bird species responses since grazing practices may not be reflective of the actual habitat characteristics on the landscape. In addition, surveys on average stocking rates and perceived “grazing practices” that ranchers use would help to characterize the overall grazing intensity common across the North Dakota landscape. Ultimately, by working to partner with ranchers to produce specific deliverables could be a more effective manner for conservation delivery through embracing the knowledge that exists in working landscapes
Improvement Of Lithium-Ion Battery’s Fast Charging Capability Through Anode Design And Charging Algorithm: A Modeling And Experimental Investigation
No full textSilicon monoxide (SiO)-graphite composite anodes have emerged as promising candidates for next-generation lithium-ion batteries (LIBs) due to their high energy density and favorable electrochemical behavior. However, the heterogeneous nature of composite electrodes characterized by multiple particle sizes, nonlinear reaction kinetics, and intricate transport pathways poses challenges in predicting and optimizing their lithiation performance. This dissertation investigates these challenges through three integrated research studies employing computational modeling, electrode engineering, and fast charging of LIBs at subzero temperatures.
In the first part of this work, a SiO-graphite composite electrode is systematically analyzed to understand the effects of SiO proportion, C-rate, and particle size on electrochemical performance. A physics model developed in COMSOL Multiphysics 6.1 reveals that electrodes with higher SiO content exhibit improved rate capability due to enhanced charge storage capacity. While a relatively uniform state of charge (SOC) distribution is observed at low C-rates, significant SOC heterogeneity develops between graphite and SiO particles at high C-rates. An optimized particle size for both materials is proposed to narrow this SOC gap, enabling a half-cell with 30.27 wt.% SiO to deliver 432 mAh/g at 2C, with an approximately 9% deviation between simulation and experiment.
The second part of this work explores engineered electrode architectures to mitigate transport limitations during high-rate operation. At a coating thickness of 55 μm, this design improves capacity by approximately 2% (440 mAh/g) compared to randomly distributed particles, and further optimization increases the capacity to 475 mAh/g.
The final part of the dissertation addresses fast charging under subzero environmental conditions, where electrolyte conductivity and ion mobility are severely reduced. A lithium cobalt oxide (LCO)/graphite full cell is modeled using the Python Battery Mathematical Modeling (PyBaMM) framework to develop an optimized multi-stage charging protocol for operation at 258.15 K.The proposed strategy integrates (1) pulse charge-discharge preheating, (2) constant-current charging, and (3) constant-voltage charging. Pulse currents are used to increase the cell temperature while maintaining a capacity protection ratio to avoid over-discharge. The optimized protocol successfully raises the cell temperature from 258.15 K to 278.15 K within approximately 6.7 minutes, enabling safe and efficient subsequent fast charging
Data-Driven Evalutation And Optimization Of Fishbone Well Configurations For Geothermal Energy Recovery In The Red River Formation, Cedar Creek Anticline
No full textThis thesis evaluates the geothermal potential of the Red River C interval at the Cedar Creek Anticline and develops a workflow for screening fishbone multilateral designs in a heterogeneous carbonate reservoir. Regional heat-flow and depth maps delineated Cedar Creek as a thermally favorable site and the lower dolomite as the primary reservoir target, supporting construction of a 3D Petrel model that captured the five-member C-interval architecture, petrophysical properties, and temperature field. A multi-stage Particle Swarm Optimization and fast-marching framework used this model to generate and rank fishbone injector–producer configurations, and a line-source approximation combined with a fixed-efficiency Organic Rankine Cycle representation yielded first-order estimates of reservoir heat uptake and annual net electric energy of approximately 100 MWh for the highest-ranked injector–producer pair
How Does Music Therapy Affect Pain Management and Emotional Health in Pediatric Cancer Patients?
Get PDFThis paper explores the effectiveness of music therapy as a non-pharmacological intervention for pediatric cancer patients. It highlights how music therapy can reduce pain, anxiety, and depression, while also improving emotional well-being and coping skills during treatment