17179 research outputs found
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Discrimination Experiences, Resilience, Ethnocultural Empathy, and Support for Policies Helping Marginalized Groups: A Moderated Mediation Analysis
No full textActs of compassion and empathy towards someone in need are small gestures, but they serve as foundational behaviors for cultivating a society of greater understanding and harmony. Research has shown that a high level of empathy, which involves placing oneself in another person’s shoes on a mental and emotional level, is associated with enhanced prosocial reasoning, behaviors, and attitudes. The notion of showing empathy through prosocial behavior to individuals of different cultures has been further explored and referred to as ethnocultural empathy in the literature; however, ethnocultural empathy and prosociality are rarely examined in tandem. This study seeks to gain a better understanding of ethnocultural empathy and whether it may provide insight into the relationship between discrimination experiences and prosocial support for policies that benefit marginalized groups. Participants, 384 adult students recruited from introductory psychology courses at Texas State University, completed an online Qualtrics survey that included measures assessing personal experiences with discrimination, resilience, ethnocultural empathy, and prosocial policy support. Moderated mediation analyses revealed that greater discrimination experiences were associated with greater ethnocultural empathy, which was associated with greater support for policies supporting marginalized groups (including religious minorities, sexual or gender minorities, disabled persons, and homeless individuals) and greater support for Black-targeted affirmative action policies. Resilience did not moderate this relationship between experienced discrimination and policy support. Further, parallel mediation analyses revealed that the effects of experiences with discrimination on stigmatized group policy support were mediated by empathic concern and by awareness of racial/ethnic mistreatment, whereas the effects of discrimination experiences on support for affirmative action policies were mediated by empathic concern and by empathic perspective taking. These findings suggest that one’s experiences with discrimination may lead to the development of greater ethnocultural empathy and positively manifest in prosocial support for policies aimed at helping marginalized groups, including affirmative action policies.Psycholog
Enhancing Middle School Teachers' TPACK and Dispositions Toward Using Geospatial Technologies in Social Studies Classrooms through a Professional Development on Virtual Field Trip Technology
No full textUtilizing geospatial technology (GST) in the classroom is a significant teaching tool for enhancing middle school social studies and geography education. However, many teachers struggle to integrate GST due to a lack of knowledge and professional development. In Mississippi, middle school teachers receive minimal if any training on GST, despite its potential to enrich their Technological Pedagogical and Content Knowledge (TPACK). One promising GST tool is the virtual field trip (VFT), an interactive 3-D platform for teaching spatial and geographic concepts. This dissertation study began with a five-day professional development tailored for understanding and utilizing VFT specifically for middle school social studies and geography teachers in Oxford, Mississippi. The study utilized a mixed-method approach, incorporating a pre- and post- disposition survey, participant-created VFT lesson plans, and semi-structured interviews to evaluate the impact of the professional development program on teachers' TPACK and their dispositions towards using VFT technology as an instructional tool. The study found that participation in the professional development program significantly enhanced participants’ dispositions and TPACK related to the use of VFT. Participants demonstrated a strong understanding of curriculum standards, effective instructional strategies, and the integration of geography content and pedagogy when incorporating VFT technology into their lessons. The findings also revealed the potential of VFT to enrich existing lessons, inspire new ones, and engage diverse learners through dynamic and interactive activities. Based on these results, the researcher recommends conducting further studies to explore the impact of professional development on middle school social studies and geography teachers’ dispositions and TPACK for using VFT technology.Geography and Environmental Studie
Exploring the Effectiveness of Embedding a Course-Based Undergraduate Research Experience in a Science Content Course for Pre-Service Elementary Teachers
No full textElementary classrooms often devote limited time to science instruction, which places added importance on how Pre-Service Elementary Teachers (PSETs) capitalize that time. Because elementary teachers often serve as children’s first formal guides into science, PSETs own encounters with science during teacher preparation are especially consequential. Many PSETs enter teacher education programs with little prior research experience and mixed confidence in doing science, which may influence whether and how they later teach it. Course-based Undergraduate Research Experiences (CUREs) offer one way to embed authentic research within existing coursework, yet most CURE research has focused on science majors rather than future elementary teachers. This exploratory study examined whether participation in a semester-long water-quality CURE embedded in a required general science laboratory was associated with changes in PSETs’ science identity and motivation to learn science.
My study took place one semester at a Hispanic-Serving, high-research university in the Southern United States. I adapted and refined two instruments for this population: a 22-item science identity instrument aligned with Recognition, Competence, Performance, and Interest factors, and a 22-item modified Motivated Strategies for Learning Questionnaire (MSLQ) including Intrinsic and Extrinsic Goal Orientation, Task Value, Control of Learning Beliefs, and Self-efficacy for Learning as factors. Using pre-course data, I established factor structures with exploratory factor analysis (EFA) and documented strong internal reliability for all subscales. Both instruments were administered at the beginning and end of the semester. After data cleaning, matched samples were n = 144 (science identity) and n = 167 (motivation). Since the data violated normality assumptions, I used non-parametric method i.e. Wilcoxon signed-rank tests for analysis and calculated effect sizes (r).
Science Identity scores were significantly higher at the end of the course, with a medium overall effect (r ≈ -0.31, p < .001). Performance (r = -0.37), Recognition (r = -0.29), and Interest (r = -0.25) increased significantly, whereas Competence showed a non-significant change (r = -0.09). Overall Motivation to Learn Science did not change significantly, but Self-efficacy for Learning showed a small-to-medium increase (r = -0.17), while other motivational factors remained stable. These patterns suggest that a single semester of CURE-based coursework may support PSETs’ sense of belonging, engagement, and confidence in doing science, even if deeper shifts in perceived competence and broader motivational orientations may require more sustained and coordinated experiences. Taken together, the findings indicate that integrating CUREs into teacher preparation is feasible and may offer a promising avenue for helping future elementary teachers feel more comfortable and capable using their limited science instructional time in rich, inquiry-oriented ways.Biolog
Examining the Connection between Guam's Seasonal Rainfall and the El-Nino Southern Oscillation 1950-2023
No full textGuam has seen an increase in water demand resulting in a need for imports of fresh water. Annual rainfall is impacted by both tropical cyclones and interannual climate variability. This interannual variability is represented by the El Nino Southern Oscillation (ENSO). Different phases of ENSO may produce deviations from the expected precipitation pattern. Knowledge of this deviation, may assist planners in compensating for changes in water supply.
This study will analyze monthly precipitation values from 1950 thru 2023 on Guam in comparison to the ENSO phase. Data will be aggregated into the four seasons to identify ENSO phase impacts on seasonal precipitation. Descriptive and inferential techniques, particularly ANOVA will be employed. In addition, a phase lag of one season will also be tested for its impact on precipitation. It is anticipated that results of the analysis will identify seasons of higher or lower precipitation depending on the current and possibly previous season ENSO phase.Geography and Environmental Studie
Oral history interview: Teddy Newell
No full textEdited and unedited transcript files (.pdf) and edited and unedited video files available with closed captioning.Oral history interview with Kimberly Green about her father Teddy Newell. She shares about his life, service, and legacy
From triads to tools: A comprehensive review of the expanding roles of G-triplex structures
No full textInterest in non-canonical DNA structures continues to grow, in part fueled by the recent discovery of a new structure, G-triplex DNA. Originally proposed as folding intermediates for G-quadruplex DNA, G-triplex DNA has more recently been shown to form from truncated G-quadruplex sequence oligonucleotides and other, specifically designed sequences. In this review, we provide the first, comprehensive survey of G-triplex DNA and RNA, covering the literature up to 2024. We include reports of G-triplex DNA from bulk solution and single-molecule approaches, the structural characterization of G-triplex DNA, and the breadth of oligonucleotide sequences that have been reported to form these structures. The formation of G-triplex RNA structures is also reviewed. The evolving understanding of sequence and environmental effects on G-triplex formation are presented together with challenges due to structural polymorphism and competing formation of multimeric G-quadruplex structures. Hints of the biological relevance of G-triplexes are provided by reports of protein recognition of these structures and their effects on DNA replication in vitro. Interaction of G-triplex DNA with a variety of ligands has been reported, although the search for selective ligands that can distinguish G-triplex from G-quadruplex is on-going. The vast majority of publications in the area have focused on the utilization of G-triplex in biosensing applications, which has shown some advantages compared to G-quadruplex-based systems. These results highlight the potential utility of G-triplex structures in a variety of domains and show its promise in applications in biotechnology, medicine, and research.Chemistry and BiochemistryMaterials Science, Engineering, and Commercializatio
A High-Performance Hybrid Transformer–LSTM–XGBoost Model for sEMG-Based Fatigue Detection in Simulated Roofing Postures
No full textWithin the hazardous construction industry, roofers represent one of the most at-risk workforces, with high fatalities and injury rates largely driven by Work-Related Musculoskeletal Disorders (WMSDs). The primary precursor to these disorders is muscle fatigue, yet its objective assessment remains a significant challenge for implementing proactive safety management. To address this gap, this study details the implementation and validation of an AI-driven predictive analytics framework for automated fatigue detection using surface electromyography (sEMG) signals. Data was collected as participants (novice roofers) performed strenuous, simulated roofing tasks involving sustained standing, stooping, and kneeling postures. A key innovation is a data-driven labeling methodology using Weak Monotonicity (WM) trend analysis to automate the generation of objective labels. After a feature selection process yielded seven significant features, an evaluation of standard models confirmed that their classification performance was highly posture-dependent, motivating a more robust, hybrid solution. The framework culminates in a high-performance hybrid machine learning model. This architecture synergistically combines a Transformer–LSTM network for deep feature extraction with an XGBoost classifier. The model outperformed all standalone approaches, achieving over 82% accuracy across all postures with consistently strong fatigue F1-scores (0.77–0.78). The entire framework was validated using a stringent Leave-One-Subject-Out (LOSO) cross-validation protocol to ensure subject-independent generalizability. This research provides a validated component for AI-enhanced safety management systems. Future work should prioritize field validation with professional workers to translate this framework into practical, real-world ergonomic monitoring systems.Engineering Technolog
Mechanical and Seismic Performance of Extraterrestrial Geopolymers for Lunar and Martian 3D-Printing Applications
No full textThis study investigates the 3D-printability and seismic resilience of geopolymer mixtures made from lunar and Martian regolith simulants. Three simulants, LHS-1, LSP-2, and MGS-1C, were assessed for their ability to form 3D-printable geopolymers under varying liquid-to-solid ratios (0.2–0.4) and silica moduli (1.0–2.0). The printability of each formulation was evaluated through extrudability, buildability, and shape retention, while compressive strength was measured after 14-day oven curing. A shake-table test was also conducted to examine the performance of manually printed models under sustained vibrations. Results showed that LSP-2 mixtures demonstrated poor printability due to coarse particle distribution and long curing times. LHS-1 performed better but exhibited inconsistent behavior across batches, which was linked to differences in particle size confirmed via SEM imaging. Finer particles (LHS-1-2) promoted higher compressive strength and improved printability, though shape retention remained limited in several mixtures. In contrast, MGS-1C simulant consistently produced pastes with excellent printability and favorable mechanical properties due to its hydrated clay content, which contributed to thixotropic behavior and enhanced setting. Among all tested combinations, the MGS-1C mixture with a liquid-to-solid ratio of 0.4 and a silica modulus of 2.0 achieved the best overall performance, demonstrating the highest compressive strength (5.91 MPa) and full structural stability during seismic simulations. Efflorescence and setting behavior were also tracked and correlated with silica content. These findings suggest that Martian simulants may offer more reliable performance for additive construction in extraterrestrial environments. The results emphasize the critical role of mix design and particle refinement in optimizing geopolymer-based construction materials for space applications.Engineerin
Semantics-Driven 3D Scene Retrieval via Joint Loss Deep Learning
No full textThree-dimensional (3D) scene model retrieval has emerged as a novel and challenging area within content-based 3D model retrieval research. It plays an increasingly critical role in various domains, such as video games, film production, and immersive technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), where automated generation of 3D content is highly desirable. Despite their potential, the existing 3D scene retrieval techniques often overlook the rich semantic relationships among objects and between objects and their surrounding scenes. To address this gap, we introduce a comprehensive scene semantic tree that systematically encodes learned object occurrence probabilities within each scene category, capturing essential semantic information. Building upon this structure, we propose a novel semantics-driven image-based 3D scene retrieval method. The experimental evaluations show that the proposed approach effectively models scene semantics, enables more accurate similarity assessments between 3D scenes, and achieves substantial performance improvements. All the experimental results, along with the associated code and datasets, are available on the project website.Computer Scienc
Factors of Individuals that Sustained Weight Loss after Discontinuing a GLP-1 RA [paper]
No full textGlucagon-like peptide-1 receptor agonists (GLP-1) have been shown to be effective for weight loss; however, weight regain after discontinuation is common. This systematic review aimed to review characteristics that lead to sustained weight loss after discontinuing a GLP-1. A systematic search was conducted in Medline, CINHL, and Web of Science. Data extraction was performed using a PRISMA flow diagram. Five studies were included in the final analysis. Risks of bias and validity were assessed using a rapid critical appraisal tool. Three themes were found among the five articles. Themes included including exercise during GLP-1 use and continue post treatment to sustain weight loss, diet after GLP-1 use to sustain weight loss, and being in a group with social support can yield to better adherence. The systematic review demonstrates that weight regain after GLP-1 discontinuation is common but there are factors that have been found to prevent it. Diet, exercise, and social support can help maintain weight loss after stopping GLP-1. The findings emphasize the need for implementing a long-term treatment strategy to maintain weight loss that includes diet and exercise. More research on the discontinuation process is needed.Nursin