UTSA Runner Research Press (Univ. of Texas at San Antonio)
Not a member yet
6846 research outputs found
Sort by
Los Tejanos: The Ranching Experience, Life & Work
No full textBased on Texas Essential Knowledge & Skills, Kindergarten through Third GradeLos Tejanos: The Ranching Experience explores the legacy of ranching from a unique cultural perspective and offers students a glimpse into what life was like for people working and thriving on Texas ranches. This resource guide provides students with hands-on learning activities that give them the opportunity to engage with the past, where they will refine critical thinking skills while learning about the value of work as an aspect of Tejano culture. The contents of this guide are based on Art, Social Studies, and English Language Arts and Reading TEKS for grades K through 3
Finite Element Analysis of Strain-Mediated Direct Magnetoelectric Coupling in Multiferroic Nanocomposites for Material Jetting Fabrication of Tunable Devices
No full textMagnetoelectric composites enable strain-mediated coupling between magnetic and electric fields, supporting applications in sensors, actuators, and tunable devices. This study presents a finite element modeling framework for simulating the direct magnetoelectric effect in core–shell and layered nanocomposites fabricated by material jetting (inkjet printing). The model incorporates nonlinear magnetostrictive behavior of cobalt ferrite nanoparticles and size-dependent piezoelectric properties of barium titanate, allowing efficient simulation of complex interfacial strain transfer. Results show a strong dependence of coupling on field orientation, particle arrangement, and interfacial geometry. Simulations of printed droplet geometries, including coffee ring droplet morphologies, reveal enhanced performance through increased surface area and directional alignment. These findings highlight the potential of material jetting for customizable, high-performance magnetoelectric devices and provide a foundation for simulation-guided design.Electrical and Computer Engineerin
Forskolin Loaded Lipid Coated Mesoporous Silica Nanoparticles Modulates Fat Thermogenesis and Impedes Weight Gain
No full textObesity is an ever-increasing health crisis in the US and can lead to various illnesses such as type 2 diabetes, hypertension, and stroke, yet many therapeutic treatments prove to be ineffective due to the lack of bioavailability at the physiological target site. We have successfully designed a liposome coated mesoporous silica nanoparticle (LCMSN) delivery system for forskolin (FSK), a water insoluble cAMP activator that has been used to increase thermogenic activity in adipose tissue.
Briefly, dissolved FSK were mixed with liposome components and dried into a film. Dendritic mesoporous silica nanoparticles (MSN) were synthesized and loaded with FSK, which was then suspended in PBS, and fused with liposome film through electrostatic interactions to form LCMSN-FSK. The hydrodynamic size was measured to be ~140 nm, with a low PDI (<0.1), and a negatively charged surface (ζ=-28mV). The FSK loading percentages were 11% and 30% respectively, when liposomes were prepared with 10% or 25% FSK.
Human adipose stem cells were differentiated to mature adipocytes and used to evaluate treatment efficacy. Cytotoxicity assays show no detectable toxicity (20-1000 ug/ml media). The uptake of fluorescently labeled LCMSN in adipocytes was evaluated using flow cytometry at different time points (3-48h) demonstrating maximum uptake at 24 h post treatment. Cell internalization was confirmed using 3D confocal microscopy images. Adipocytes treated with LCMSN-FSK resulted in an increase in UCP1 and Cox7A1 gene expression when compared to FSK or LCMSN alone. Furthermore, glucose uptake and lipolysis were also significantly elevated, demonstrating increased metabolic functional outcomes. For in vivo analysis, LCMSN-FSK was subcutaneously injected in inguinal white adipose tissue (iWAT). Biodistribution imaging using KINO Spectral Imaging system was performed in obese and non-obese mice. Retention of fluorescently labelled LCMSN-FSK was observed even until 48h post injection, while accumulation in heart, lung, liver, and kidney was not detected. Increase in lipolytic function and expression of UCP1 at the protein (WB) and gene (RT-PCR) levels were also detected. In conclusion, we have optimized a nanoparticle delivery system that is taken up by adipocytes, and effectively delivered forskolin to adipose tissue in mice which resulted in an increase in thermogenic activities.Biomedical and Chemical Engineerin
Does Cognitive Ability Moderate Relations Between Cognitive Biases and Cognitive Reflection?
No full textThis study examined how cognitive ability and cognitive reflection affect susceptibility to two cognitive biases, Framing and Anchoring. Based on Intelligence Compensation Theory and dual-process models of reasoning, it was hypothesized that cognitive ability (based on SAT scores) would moderate relations between cognitive reflection and the Framing bias, exhibiting a compensatory effect, but not the Anchoring bias. Contrary to expectations, no significant main or moderation effects were found for the Framing bias. However, cognitive reflection was a significant negative predictor of the Anchoring bias, indicating that more reflection was associated with less bias, and cognitive ability became a non-significant predictor of Anchoring when reflection was accounted for. In addition, a positive relation of cognitive reflection with response times for both Framing and Anchoring was found, indicating that more reflection was associated with longer response times, suggesting more deliberation. The findings suggest that cognitive reflection may protect against certain cognitive biases, such as Anchoring, beyond cognitive ability. Future research should examine how cognitive reflection, cognitive ability, and related dispositions (e.g., need for cognition) can reduce cognitive challenges, including logical fallacies and cognitive distortions.Psycholog
Premium Resources lesson plan list
No full textIncludes a list of ITC-created lesson plans, showing the lesson plan summary, intended grade levels, and subjects covered in each plan
Advancing Secure and Efficient Edge Intelligence Over Mobile Edge Networks
Get PDFThe rapid proliferation of edge devices such as smartphones, IoT sensors, and autonomous systems has led to a massive volume of data being generated at the network edge. Meanwhile, large language models (LLMs) have demonstrated remarkable capabilities across diverse applications, including question answering, text generation, and reasoning. Integrating the intelligence of LLMs with the distributed data available at the edge promises transformative potential for edge intelligence. However, deploying such large models in federated learning (FL) settings introduces critical challenges related to communication efficiency, system heterogeneity, privacy leakage, and robustness against adversarial attacks. To address these challenges, this dissertation develops a suite of secure and resource-efficient federated learning frameworks tailored for LLM fine-tuning on edge devices. First, we propose a federated adaptive fine-tuning framework with heterogeneous quantization and Low-Rank Adaptation (LoRA) to significantly reduce training latency and memory consumption while maintaining model performance on resource-constrained devices. Next, we design differentially private federated optimization algorithms that provide rigorous privacy guarantees without compromising model utility, leveraging techniques such as partial model aggregation and sharpness-aware minimization to mitigate the adverse effects of differential privacy noise. Furthermore, we develop robust and personalized federated training methods that enhance resistance to backdoor attacks and model manipulation through personalized sharpness-aware optimization. Finally, we extend our study to cooperative federated edge learning, which coordinates multiple edge servers to improve scalability, energy efficiency, and convergence speed in heterogeneous and bandwidth-limited environments. Comprehensive theoretical analyses and extensive experiments on benchmark datasets demonstrate that the proposed methods achieve superior trade-offs between privacy, robustness, and efficiency compared with state-of-the-art FL frameworks, paving the way toward secure and scalable large-model learning at the edge.Electrical and Computer Engineerin
Sexual Orientation and Social Isolation from Early Adulthood to Early Midlife
Get PDFAlthough social isolation is a critical public health issue, there is a gap in understanding how it varies by sexual orientation. Using minority stress, minority strength, and life course perspectives, this study investigates how social isolation trajectories differ by sexual orientation from ages 18 to 42 using longitudinal data from the National Longitudinal Study of Adolescent to Adult Health (2001–2018, N = 30,250 observations). Results from growth curve models reveal that sexual minority respondents experience higher levels of isolation than heterosexual respondents from early adulthood to early midlife. Specifically, respondents who identify as lesbian, gay, or bisexual report the highest levels of social isolation; completely heterosexual respondents have the lowest levels; and mostly heterosexual respondents fall in between. Notably, mostly heterosexual respondents experience a more rapid increase in isolation than the other two groups. Analyses conducted separately by sex and each dimension of social isolation reveal important nuances.Health and Social Behavio
Cultural Values Impact on Personal Identity Development and Commitment Among Latino Immigrant Adolescents
Get PDFIdentity development is a complex process for adolescents, as they seek to answer the question, “Who are you?” within different sociocultural environments (Vignoles, 2014). For immigrant Latino adolescents, identity development becomes complicated by external factors are incorporated, such as cultural pressures and expectations, which can impact adolescents' personal beliefs, goals, and attitudes (Schwartz et al., 2016; Vignoles, 2014). While the goal is for adolescents to develop a well-established identity, cultural values and expectations could potentially limit an adolescent’s desire to explore opportunities related to identity development, resulting in identity confusion or a loss of direction (Schwartz, 2001). A lack of a well-established identity has been found to have negative implications for adolescents' adjustment and prosocial functioning development and mental health, such as depression (Schwartz et al., 2017). Factors which are thought to play a key role in the development of positive personal identity development in Latino youth, such as endorsement of Latino cultural values (Meca et al., 2017). This is specifically prevalent among Immigrant Latino adolescents, as they are tasked with making sense of their native culture and the culture of their new environment (Schwartz et al., 2016). This thesis examined the role that cultural values, specifically the separate dimensions of collectivism, individualism, and familism, play in the development of personal identity. The data utilized was from a longitudinal study with a sample that consisted of 302 (53% boys; Mage 14.51 years at baseline; SD .88 years) recently immigrated Latino adolescents from Los Angeles and Miami. The findings indicated that immigrant Latino adolescents who abide by vertical collectivism values are likely to be in cycle 1 of identity formation of Exploration in Breadth and Commitment Making. Additionally, our findings found no significance between dimensions of familism and personal identity development. The results of this study provide insight into identity development among Immigrant adolescents and to understand the impact of these external factors, guiding intervention and preventive efforts for positive identity development (Meca et al., 2023).Health, Community and Polic
Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment
Get PDFWorldwide energy demand is increasing exponentially, presenting significant challenges for existing power generation systems to meet this demand. Enhancing energy efficiency has become critical for reducing consumption and addressing the ongoing environmental crisis. Consequently, there is a need for smart control systems that optimize system costs and improve efficiency. Because of the introduction of smart grids, customers can now participate in demand-side management and integrate renewable energy sources (RESs). Electricity consumption during peak hours often leads to increased grid demand and higher costs. However, the integration of RESs enables consumers to operate appliances during peak hours, thereby reducing reliance on grid power. Therefore, residential load management seeks to reduce power peaks and electrical energy costs. In home energy management systems (HEMS), appliance scheduling is crucial because it continually monitors appliance usage, ensuring that energy supply and demand are balanced. This research aims to optimize power usage by reducing peak loads and electricity costs through the integration of RESs, such as solar or photovoltaic (PV) systems, while considering grid limitations, PV capacity, appliance ON/OFF schedules, and time-of-use tariffs. A genetic algorithm (GA) based optimization technique was employed to evaluate the performance of a HEMS and validated with particle swarm optimization (PSO) technique under identical initial conditions for each appliance and their corresponding energy pricing over different periods. The results show that GA achieved a 48% cost reduction compared to PSO, with significant peak load reduction and improved energy optimization when integrated with PV systems. GA also demonstrated better appliance scheduling, with appliances in the “ON” state for 82% of the time, compared to 52% with PSO.Electrical and Computer Engineerin
Integration of conventional and renewable energy resources using artificial bee colony based combined emission and economic dispatch
Get PDFReliable and cost-effective electricity generation has been a significant problem for many years. Economic dispatch (ED) techniques have been widely used for efficient power production at minimal cost. However, conventional ED techniques have been studied considering only traditional power plants. With the depletion of fossil fuels and rising environmental concerns, many countries are shifting toward maximizing the share of renewable energy resources in their energy mix. The dispatch strategies should consider both conventional and renewable energy systems to align with this transition. Therefore, in this study, the ED of a system comprising 13 photovoltaic (PV) plants and 10 thermal generators is optimized using the binary artificial bee colony technique within a combined economic and emission dispatch (CEED) framework. Only selected expenditures, fuel and emission charges for thermal units, and the per-unit expense of PV power are considered. Moreover, both full solar radiation and reduced radiation conditions, simulating cloudy weather, are included in the CEED framework. The results demonstrate that the proposed algorithm gives satisfactory outputs, capping the PV share to 25% to maintain grid stability and leverage renewable energy benefits. Furthermore, the proposed algorithm is compared with particle swarm optimization (PSO) within the CEED framework. The comparative analysis depicts that the proposed algorithm reports less computational time than PSO.Electrical and Computer Engineerin