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The Weapon Focus Effect On Memory For Male And Female Perpetrators
Get PDFPrevious research on the weapon focus effect suggests that weapon presence causes reduced memory accuracy for perpetrator details due to weapons being surprising and unexpected. The unusualness hypothesis suggests that a stronger weapon focus effect should occur when the perpetrator defies typical gender stereotypes, such as a woman holding a gun. The current study sought to examine how the weapon focus effect impacts eyewitness memory for male and female perpetrators, specifically exploring the magnitude of the effect on female perpetrators. The current study further investigated whether the own gender bias attenuates the weapon focus effect on memory for female perpetrators. Participants viewed one of four stimulus videos depicting a simulated home invasion, where the critical object was either a phone (neutral) or a handgun (weapon) and the perpetrator was either male or female. Participants then completed a brief filler task and a memory questionnaire. While the typical effect of unusualness based on object type was found, there were no significant main effects or interactions. Explanations for why this may have happened are outlined, as well as implications for future research
Domain Adapted Signal Classification For Simulated And Real-World Signals
Get PDFSignal classification models based on deep neural networks are trained on a set of data either simulated or over-the-air that are restricted to specific channel environments, varying distortion conditions such as SNR offsets. The consequence are models that unexpectedly do not do well in scenarios when the feature distribution between domains are too large such as when simulated models are deployed in real world environments. In this regard, we propose signal classification framework leveraging Domain-Adversarial Neural Networks to address SNR variability for simulated data Unsupervised Domain Adaptation frameworks for simulated to real world signals. Our first approach employs domain adversarial learning techniques to align feature distributions across different SNR levels, mitigating domain shifts and enhancing modulation recognition robustness. Extensive experiments demonstrate significant improvements in classification accuracy compared to existing techniques, highlighting the potential of domain adversarial methods in overcoming domain discrepancies in signal classification. The second approach using unsupervised adaptation techniques based on adversarial learning, distance and stochasticity are used to counteract such feature distribution differences in order to bridge the generalization gap towards a targeted real-world domain. Many adaptation methods are analyzed in contrast to the baseline approach where isolated experiments cross-SNR and SNR-matched alongside true domain adaptation are evaluated
White Paper For Faculty Professional Development In Establishing, Addressing, And Informing, To Promote Mental Wellness For Health Careers Students
Get PDFThis research utilized a qualitative case study to explore the need for faculty professional development in the health careers division at a public non-profit California community college, specifically Porterville College. Literature suggests that mental health is a crucial topic to address in contemporary higher education. College students, in general, are facing a notable deterioration in their overall mental well-being, accompanied by an increase in mental disorders. Furthermore, students in health careers programs frequently encounter even more intense stress and psychological challenges, stemming from their constant exposure to high-pressure, emotionally charged situations, and vicarious trauma. Although literature emphasizes the critical need to explore mental health in higher education, there is a marked deficit in faculty professional development related to student mental health necessities. The findings of this study suggest that there is a demand for faculty to establish a rapport and environment that is conducive to student mental wellbeing, address the mental health needs of the students, and inform students about available mental health resources. This study concludes with a white paper to guide professional development for Porterville College Health Careers faculty
Geothermal Sweep Efficiency Enhancement Potential Analysis Using Geological Modeling And Numerical Simulation On Unconventional Deadwood Formation
Get PDFThis study investigates the potential to enhance geothermal sweep efficiency in the fractured, low-permeability Deadwood Formation using a cellulose-based biopolymer and gel treatment. A geological model was developed using well log and structural data from four wells in the Williston Basin and subsequently upscaled into a numerical reservoir simulation in CMG/STARS. Laboratory core-flooding experiments on Deadwood samples were used to calibrate gel behavior under high-temperature (160 °C) and high-salinity (17% TDS) reservoir conditions.Simulation results indicate that a short-duration gel treatment—equivalent to 0.03 pore volumes over one year—can significantly reduce channeling through high-conductivity fractures. The reduction in channeling improves thermal conformance and extends the heat retention capacity of the reservoir. Unlike water injection alone, gel-treated scenarios increased heat recovery by approximately 20%, with lower thermal breakthroughs and improved temperature stability, particularly at 2–5 GPM injection rates. Two horizontal well patterns were evaluated, both yielding favorable economics. The best pattern achieved a Net Present Value (NPV) of over 16/MWh, indicating strong commercial viability. This work presents one of the first demonstrations of conformance control using biopolymer gels in unconventional geothermal systems. The results support targeted gel treatments as an effective strategy for improving sweep efficiency and economic returns in fractured geothermal reservoirs, particularly those transitioning from hydrocarbon production to renewable heat extraction
Seismic Design And Ductility Evaluation Of Concrete-Filled Thin-Walled Steel Tubular Columns Modeling As Bridge Piers
Get PDFAccurate numerical modeling is essential for evaluating the seismic performance and load-bearing behavior of partially concrete-filled thin-walled steel tubular columns, particularly those used as bridge piers under complex seismic conditions. This study investigates the performance of such columns enhanced with embedded energy-dissipating shell plates and/or partial concrete infill, subjected to unidirectional and bidirectional seismic loading. A validated finite element model (FEM), developed in ABAQUS and incorporating geometric and material nonlinearities—including the modified Two-Surface Model (2SM)—was employed to simulate cyclic behavior and predict structural response.The model was benchmarked against experimental results and used to analyze a broad range of parameters, including width-to-thickness ratio, infill height, slenderness ratio, shell plate properties, and axial compression ratio. The simulations captured key seismic response indicators such as damage modes, hysteresis behavior, stiffness and strength degradation, and energy dissipation, while also evaluating post-buckling and interaction effects of local and flexural buckling. Findings reveal that partially filling the steel tube—optimally around 50% of the column height—substantially improves strength, ductility, and post-buckling stability, with diminishing returns beyond this threshold. Embedded shell plates and internal stiffeners further enhance performance, increasing ductility by up to 30% and strength by 12%. A novel rocking mechanism with a central cable was also shown to reduce local buckling and improve energy dissipation capacity. Based on the extensive numerical analysis, practical design equations were proposed for use by structural engineers, with recommended design parameters of 0.20 ≤ Rf ≤ 0.5, 0.2 ≤ λ ≤ 0.5, and P/Py ≤ 0.2. These equations provide a reliable foundation for the seismic design and construction of efficient, ductile, and resilient bridge piers
Experimental And Numerical Modeling For CO2 Utilization In Enhanced Oil Recovery And Associated Storage In Unconventional Reservoirs
No full textUnconventional reservoirs, such as the Bakken and Three Forks formations, present significant challenges due to their ultra-low permeability and complex fracture networks, which limit primary oil recovery to less than 10%. To enhance hydrocarbon extraction while simultaneously facilitating carbon dioxide (CO₂) storage, this study investigates the mechanisms governing CO₂ Huff-n-Puff (HnP) and associated storage under various operational conditions. A comprehensive approach integrating experimental analysis, numerical simulations, multiphase flow modeling, and geochemical interactions is employed to optimize CO₂-EOR and storage strategies. The experimental phase focuses on evaluating the performance of different injected gases (CO₂, ethane, and propane) in the Upper Three Forks (UTF) and Middle Three Forks (MTF) formations. A series of experiments are applied under different constraints. The parameters that are examined include the effect of soaking time at immiscible and miscible conditions, the effect of fluid state (vapor, supercritical), injection pressure, selected gases (CO2, ethane, and propane), target formations (Upper Three Forks (UTF) and Middle Three Forks (MTF)), and the effect of pore size distribution on the recovery factor. During the Huff-n-Puff process, the Nuclear Magnetic Resonance (NMR) technique was used to analyze the microscopic oil production and the micro residual oil distribution before and after CO2 injection. NMR measurements reveal that soaking time plays a pivotal role in mobilizing oil from diverse pore structures, particularly under or near the minimum miscibility pressure (MMP), while higher injection pressures above the MMP attenuate the benefits of soaking. Moreover, propane demonstrates the highest recovery factor at low pressures, followed by ethane and CO₂, though the performance of lighter gases improves significantly at higher pressures. Additionally, the physical properties of the rocks can undergo significant alteration during the CO2 injection and soaking stage. While the interaction between brine, rock, and CO₂ has been widely studied, there is limited understanding of how the buffering capacity of carbonate-rich and silicate-rich rocks influences these interactions and alters pore-scale properties, fluid flow, brine chemistry, and mineralogical composition under the complex mineralogy of Bakken rocks. To address this problem, we present an experimental investigation on how supercritical CO2 (Sc-CO2) influences mineralogy, fluid flow, pore structure, and brine chemistry in carbonate-rich and silicate-rich samples from the Bakken Formations. Carbonate-rich rocks display notable dissolution of calcite and a concomitant reduction in acidity that favors clay stability, whereas silicate-rich samples exhibit pronounced clay dissolution and subsequent quartz precipitation. Extended soaking times (up to 30 days) prove essential for the penetration of CO₂ into micropores, although precipitation of salt crystals in macropores diminishes fluid mobility in both rock types, most notably in formations with lower buffering capacity. Although horizontal drilling and multistage hydraulic fracture (HF) have significantly increased the primary production, field data also indicate substantial well interference arising from HF overlaps (HFO) in the multi-well pad (MWP). During the CO2 Huff-n-Puff (HnP) process, poor conformance management can lead to early CO2 breakthrough, causing injected CO2 to promptly migrate to adjacent wells without effectively contacting the designated HnP well. Moreover, gas relative permeability hysteresis, which depends on alternating drainage (injection) and imbibition (production) under varied complex HF interference can redistribute the CO2 mobilization, hence, impacting oil recovery and CO₂ trapping mechanism. Simultaneously, geochemical interactions among CO₂, brine, and rock can alter reservoir properties, and injectivity, potentially complicating interference patterns. This study develops a 3D field geological model for the Bakken formation using conventional logs and petrophysical analysis. A compositional simulation was subsequently performed on a MWP (4 wells) for history matching. Following that, three HFO Schemas (low, medium, and high) were conducted to investigate the impact of injection rate and offset well operations on well interference under varying degrees of overlap. Gas hysteresis was integrated using Land’s trapping function to assess the influence of hysteresis-induced trapping on the efficiency of MWP interference performance. Additionally, Henry\u27s law for CO2 solubility in brine was coupled with aqueous and mineral reactions, providing an in-depth perspective on reactive transport effects on porosity, permeability, and the overall CO2-EOR and storage effectiveness in complex HF networks. The results indicate that the multi-well pad study highlights how partial closure of offset wells increases average reservoir pressure, improves CO₂ solubility in oil, and enhances the efficiency of both oil recovery and CO₂ storage. Relative permeability hysteresis aids in creating residual gas saturation, improving overall storage, yet can reduce injectivity near the Huff-n-Puff well. Furthermore, geochemical reactions, including calcite dissolution, affect reservoir properties such as porosity and permeability, thus influencing both CO₂ migration and oil recovery. The findings of this study contribute to optimizing gas injection strategies for unconventional reservoirs by identifying the most effective injection parameters and enhancing the understanding of gas-oil-rock interactions. The research provides a systematic framework for improving CO₂-EOR efficiency while maximizing CO₂ storage potential, supporting both economic hydrocarbon recovery and long-term carbon management initiatives. The insights gained will aid in developing more effective CO₂ injection designs, minimizing early gas breakthroughs, and advancing sustainable energy practices in the Bakken Formation development
Forceful Functors: A Categorical Approach To Constraint Monitoring In Machine Learning Models
Get PDFOften times in machine learning there are several heuristic choices that one makes during model selection, training, and validation. These choices include the type of training used, the width and depth of the model, type activation function and many more. These choices are general rules of thumb and best practices when creating a machine learning algorithm to achieve acceptable results. For example, in the case of image processing, this may mean determining whether or not a given image contains a tumor. Decisions made during the design process create several variations of machine learning algorithms, all with various properties with pros and cons. Things like, how many layers the network has, what activation function you are using, or what error function is used to update parameters are examples of theses decisions one needs to make while specify a machine learning algorithm. This thesis explores the use of category theory to document the structure, and provide a language to describe, the changes hyperparameters have in machine learning algorithms.
A specific case of using category theory to capture how regularization changes the structure of machine learning models is given. Then a brief inventory of various hyperparameters such as network width and activation functions are given with their potential categorical constructions are outlined. The resulting categorification of various hyperparameters show that using category theory is a valid way to specify model constraints at the beginning of an ML design process and subsequently track said constraints to the final implementation of the model
Effects of NSAIDs on Bone Healing Time in Orthopedic Patients
Get PDFUse of NSAIDs in adults recovering from orthopedic injury or surgery has been found to be largely inconclusive when it comes to determining significance in delay of bone healing. The purpose of this review is to determine whether use of NSAIDs is detrimental to bone healing after orthopedic injury or surgery. A literature review was performed using electronic databases PubMed and SportsDiscus from May to July of 2024. There were fifteen studies that met final inclusion criteria. Research overwhelmingly acknowledged that selective COX-2 inhibitors are not recommended in a post injury or post operative state. However, when it comes to non-selective COX inhibitors, there is no definitive answer. Future research should focus on larger sample sizes, more randomized controlled trials, use of more in vivo/ in vitro study models and effects of specific NSAIDs. Investigations should also include all ages, genders, and races. The focus of initial research should be placed on otherwise healthy individuals with no known medical conditions. Subsequent studies should compare initial outcomes against individuals with the most common comorbidities and continue to grow the population outwardhttps://commons.und.edu/pas-grad-posters/1328/thumbnail.jp
Efficacy of Low-dose Naltrexone Compared to Gabapentinoids in Fibromyalgia
Get PDF• . This literature review evaluates the efficacy, safety, and tolerability of low-dose naltrexone (LDN) compared to gabapentinoids, including gabapentin and pregabalin, in the management of fibromyalgia symptoms. • Pilot studies on LDN highlighted its potential anti-inflammatory benefits and its ability to reduce pain severity and improve quality of life, with minimal side effects. Gabapentinoids demonstrated dose-dependent efficacy in pain reduction and sleep quality improvement but had adverse effects, including dizziness and sedation, which may limit their tolerability. • The findings underscore the need for more extensive, long-term research to confirm the therapeutic potential of LDN and refine the clinical use of gabapentinoids in fibromyalgia management.https://commons.und.edu/pas-grad-posters/1326/thumbnail.jp
Cyril P. O\u27Neil
No full textPhotograph taken of Cyril P. O.Neil at an unknown date. Cyril P. O\u27Neil was the mayor of Grand Forks from 1972 until 1980.https://commons.und.edu/gf-city-photos/1246/thumbnail.jp