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Aerodynamic Analysis and Wind Tunnel Testing of the Quadfoil UAV
No full textThis study presents the aerodynamic evaluation of the Quadfoil UAV, a novel quadrotor configuration featuring a central lifting body in the form of an airfoil to enhance forward-flight efficiency. Flight tests conducted by Virginia Tech demonstrated a 25% increase in endurance and a 31.6% improvement in range compared to conventional quadcopters, validating the aerodynamic benefits of this design. To further investigate its performance, a dynamically adjustable angle of attack (AoA) model support system was developed for wind tunnel testing, enabling precise replication of in-flight conditions. The support system, controlled via LabVIEW, dynamically adjusts AoA based on real-time tilt sensor feedback, facilitating aerodynamic analysis across various speeds. Wind tunnel experiments included the identification of trim conditions, where lift equals weight, and where total drag and pitching moments are minimized, as well as pitch sweeps without propellers, flow visualization, and power consumption measurements. The results not only validate the Quadfoil’s enhanced aerodynamic efficiency but also provide critical data on AoA, motor RPS, and power requirements, essential for refining flight control laws. These findings further establish the Quadfoil as a suitable solution for energy-efficient, long-range missions
The Effects of Sleep on an Athlete’s Average Timed-Tandem Gait Test
No full textBackground: Sleep plays an essential role in athletic performance and injury recovery. Research has demonstrated that less sleep may result in adverse effects such as weakened cardiorespiratory fitness and psychomotor skills. Evidence suggests that athletes who get less than 8 hours of sleep are more likely to sustain an injury. Sleep is also important for the body during recovery. The timed-tandem gait test assesses dynamic postural control and is part of the Sport Concussion Assessment Tool 6 (SCAT 6). Athletes perform the time-tandem gait test for baseline concussion testing and following a suspected concussion.
Purpose: To evaluate the impact of athletes’ sleep habits on average timed-tandem gait performance.
Methods: Participants consisted of 368 athletes on Old Dominion University’s collegiate teams. This study was conducted during annual baseline concussion testing. Participants performed the timed-tandem gait test. The test consists of walking without shoes using an alternate heel-to-toe gait along a 3-meter strip of tape, going down and back as quickly as possible. Each participant performed 3 trials and the average time across all the trials was calculated. In addition, participants completed a 16-question Athlete Sleep Screening Questionnaire (ASSQ) assessing sleep habits. Lower scores indicate better sleeping habits and higher scores indicate potentially severe sleep disorders. Based on performance, participants were grouped into four groups: normal (0-4), mild (5-7), moderate (8-10), and severe (11-17). Data was analyzed using a one-way between subjects analysis of variance (ANOVA).
Results: Out of the 368 participants, 141 scored in the normal sleep group, 152 in the mild sleep group, 55 in the moderate sleep group, and 20 in the severe sleep group. No significant differences were found between sleep groups on the timed tandem gait performance (p = 0.459).
Conclusions: The results from this study demonstrate that an athlete’s sleeping habits are not directly related to how they score on the timed-tandem gait test. It can be concluded that athletes who have poor sleeping habits may still perform quicker than athletes with better sleeping habits
A Multi-Compartment Computational Model of Dendritic Spine Plasticity and Network Hyperexcitability in Epileptogenesis
No full textBackground: Epileptogenesis is characterized by a progressive increase in network excitability and synchronization, often accompanied by structural remodeling of dendritic spines and alterations in synaptic connectivity. Experimental evidence suggests that calcium-mediated spine plasticity plays a critical role in modulating synaptic strength and neuronal excitability. However, the mechanistic relationship between spine dynamics, synaptic plasticity, and emergent epileptiform activity remains incompletely understood. Computational modeling offers a powerful framework to explore how dendritic spine remodeling influences network-level hyperexcitability and the transition from physiological to pathological activity states.
Methods: We developed a multi-scale computational model integrating multi-compartment neurons with Hodgkin–Huxley (HH) membrane dynamics, calcium-dependent dendritic spine plasticity, and conductance-based synapses. Our hybrid network consists of detailed neurons (including soma, active dendrites, and spines) and point neurons, connected via a spatially constrained connectivity rule with distance-dependent synaptic strength.
Each detailed neuron incorporates HH sodium and potassium currents, along with a persistent sodium current and a voltage-gated calcium current that directly modulate intracellular calcium concentration]. Spine plasticity is governed by a calcium-dependent rule, where spine neck resistance and head capacitance evolve dynamically based on local calcium levels, reflecting activity-dependent synaptic remodeling. Synaptic interactions are conductance-based and follow a biexponential decay model.
To induce epileptiform activity, we introduced a transient kindling current injection (5 µA/cm² from 300 to 700 ms) to a subset of neurons, simulating an external perturbation that drives hyperexcitability. The model was simulated for 2000 ms using an adaptive ordinary differential equation solver, and key metrics—including firing rates, network synchrony (pairwise spike-time correlation), and spine parameter evolution—were computed and analyzed.
Results:
Increased excitability and synchrony during kindling: The transient current injection resulted in a 2.5× increase in network firing rate, with activity spreading from directly stimulated neurons to the broader network. The network synchrony index rose from baseline (0.04) to a peak of 0.32 during kindling, indicating emergent synchronization.
Calcium-driven spine remodeling: In neurons exhibiting sustained high-frequency spiking, intracellular calcium exceeded plasticity thresholds (0.1 µM), leading to a reduction in neck resistance (~10% decrease) and an increase in head capacitance (~15% increase), suggesting synaptic potentiation.
Persistent post-kindling activity: Following the cessation of kindling, firing rates remained elevated (1.7× above baseline), and network synchrony declined only partially, suggesting that transient perturbations can induce long-lasting changes in synaptic structure and excitability.
Conclusion: Our results suggest that dendritic spine plasticity plays a causal role in shaping network excitability, where calcium-mediated structural modifications reinforce synaptic potentiation and facilitate the transition to hyperexcitable states. These findings support the hypothesis that dendritic spine morphology is not merely a passive correlate of epileptogenesis but an active driver of synaptic reorganization and emergent pathological activity. This model provides a computational framework for exploring targeted interventions that modulate dendritic spine plasticity to restore normal network function and mitigate seizure susceptibility. Future work will explore the role of inhibitory synapses, short-term synaptic dynamics, and larger-scale network effects
Improving Normalizing Flow Models with MCMC-Based Correction on the Ackley Function
No full textNormalizing Flows (NFs) are widely used for density estimation and generative modeling due to their ability to learn complex distributions through invertible transformations. However, their accuracy is often limited by imperfect training, insufficient expressivity, and mode collapse, particularly when modeling multimodal or rugged landscapes such as the Ackley function. In this work, we propose a Markov Chain Monte Carlo (MCMC)-based correction framework to refine the learned distribution of a trained Normalizing Flow. By first training an NF model on samples from the Ackley function, we apply MCMC as a post-processing step to correct discrepancies and improve the fidelity of the generated samples. Our approach ensures better approximation of the target distribution by mitigating biases introduced during training and enhancing sample diversity. We evaluate the effectiveness of this method through quantitative comparisons of likelihood estimation, convergence properties, and error reduction. The results demonstrate that incorporating MCMC correction significantly improves the accuracy and robustness of Normalizing Flow models, making them more reliable for applications in complex, high-dimensional optimization and density estimation tasks
Associations of Different Types of Physical Activity and Sedentary Behavior with Self-Rated Health in Children and Adolescents: A Systematic Review of Research from 2010 to 2024
Get PDFSelf-rated health (SRH) is one of the common measures to evaluate individuals’ overall health. Many studies have explored the associations between different types of physical activity (PA), sedentary behavior (SB), and SRH in children and adolescents. These studies report inconsistent findings and sometimes highlight gender differences. This systematic review aims to synthesize findings to provide a comprehensive evaluation of these associations
Sex-Dependent Changes in Risk-Taking Predisposition of Rats Following Space Radiation Exposure
Get PDFThe Artemis missions will establish a sustainable human presence on the Moon, serving as a crucial steppingstone for future Mars exploration. Astronauts on these ambitious missions will have to successfully complete complex tasks, which will frequently involve rapid and effective decision making under unfamiliar or high-pressure conditions. Exposure to low doses of space radiation (SR) can impair key executive functions critical to decision making. This study examined the effects of exposure to 10 cGy of Galactic Cosmic Ray simulated radiation (GCRsim) on decision-making performance in male and female rats with a naturally low predisposition for risk-taking (RTP) prior to exposure. Rats were assessed at monthly intervals following SR exposure and the RTP performance contrasted with that observed during the prescreening process. Exposure to 10 cGy of GCRsim impaired decision making in both male and female rats, with sex-dependent outcomes. By 30 days after SR exposure, female rats became more risk-prone, making less profitable decisions, while male rats retained their decision-making strategies but took significantly longer to make selections. However, continued practice in the RTP tasks appeared to reduce/reverse these performance deficits. This study has expanded our understanding of the range of cognitive processes impacted by SR to include decision making
Rural Families\u27 At-Home STEM Tinkering Stimulates Creativity, Self-Expression, and Social-Emotional Engagement
Get PDFIntroduction: Informal STEM learning experiences include visits to museums, zoos, and aquariums as well as experiments and other activities performed at home. Family involvement in these experiences has been linked to increased student interest and participation in STEM fields; yet, scant research has been conducted on at-home STEM.
Methods: This descriptive case study investigated the tinkering experiences of nine rural middle school students and their families who participated in a series of interactive, at-home activities. The overarching research question was, in what ways do families engage in at-home STEM interventions? Data analyses of at-home audio recordings were guided by the Learning Dimensions of Making & Tinkering framework. Follow-up interviews with families about their informal STEM experiences were a secondary data source used to contextualize family dynamics.
Results: Overall, families who engaged in at-home STEM activities were most likely to demonstrate Social & Emotional Engagement (e.g., Collaborating and Working in Teams) and Creativity & Self-Expression (e.g., Expressing Joy and Delight), and were least likely to exhibit Initiative & Intentionality. Engagement patterns differed based on family (dynamics and backgrounds), family participant group type (number of parents and children in groups), and the STEM activity. Rich descriptions and vignettes illustrate the moment-to-moment experiences of families as they engaged in at-home STEM together. Additional evidence was gleaned through family interviews. Families valued their time together and tinkered in ways that stimulated their self-expression, creativity, and social and emotional skills.
Discussion: Recommendations for professional developers include attention to the order of activity difficulty, length of time required, inclusion of conceptual material, and allowing time for failure and risk-taking. Researcher recommendations suggest ways to streamline the data collection and analyses to ease the resources required to study other populations of interest
34 - Applying Computational Methods for Simulating Quaternary States of Proteins.
No full textProteins are composed of amino acids bonded together to create a polypeptide chain, which acts as an essential part of all biological systems. The protein folding problem has been investigated for over fifty years and has evolved into three separate problems. One of those is the protein structure prediction problem, which involves computational methodology. Understanding precise protein structures will lead to a better understanding of how proteins function and, conversely, how mutations can lead to disease states. Predicting protein structures can also accelerate drug discovery research and lead to important scientific and medical advances. AlphaFold is a groundbreaking artificial intelligence program recently developed by Google’s DeepMind team to predict protein structures. AlphaFold uses neural networks and deep learning-based algorithms to predict protein structures given an amino acid sequence as input. The first aim of this research study was to gain expertise in using AlphaFold to predict known protein structures using a test set we constructed. This laid the foundation for all subsequent studies. The second aim, which is underway, expands this computational approach to predict the three-dimensional structure of human alpha-synuclein, which is proposed to consist of a multimeric state. Knowing the native structure will also facilitate the characterization of the protein function, which is not well understood. This aim also involves extending the application and present capabilities of AlphaFold. The initial experimental results indicate that alpha-synuclein can form a tetramer, and further analysis reveals the presence of stabilizing hydrophobic interactions
36 - Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings
Get PDFTitle: Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings
Authors: Lee Logan, Sean Baker, Dominik Soos, Jian Wu
The spread of scientific information and research beyond the confines of academic institutions plays a central role in how the public understands and trusts modern sciences. Social media has become an essential means of dissemination for scholarly news, papers, and other forms of engagement. This research aims to explore how scientific research is disseminated over social media to understand its role as a bridge between peer-reviewed research and the public\u27s overall understanding. To support the research we created a data collection pipeline that utilizes focused web scraping to collect the metadata of research articles from mainstream digital library portals and associated news from prominent science news outlets. The scraper extracts embedded links from search engine result pages that point to the related scientific papers. After cleaning and normalizing the data, the pipeline retrieves the relevant metadata through the OpenAlex API and their appearance on Twitter (now X.com), a popular social media website for research paper dissemination. We have built a structured dataset containing the metadata of 693 peer-reviewed papers published from 1952 and 2024. This dataset provides a foundation for the analysis of the potential discrepancies of the dissemination between scientific papers and science news using a homogeneous sample. Ultimately this research hopes to contribute to the understanding of whether social media provides a more effective vehicle in boosting the dissemination of scientific discoveries, and how this boosting effect(if it exists) has been changed over time. Our preliminary findings show that the average number of tweets per paper fluctuates around 128 between 2012 and 2022, with 2021 emerging as a significant outlier. This spike suggests unusually high user engagement with scientific papers, presumably due to heightened public interest in scientific discourse during the Covid-19 pandemic. We also found that the average number of tweets/paper is in general below 100 before 2012 (with 2010 an outlier), indicating relatively low user engagement with scientific paper on Twitter during those years
Dihadron Aziumuthal Correlations in Deep-Inelastic Scattering Off Nuclear Targets
Get PDFWe measured the nuclear dependence of the di-pion azimuthal correlation function in deep-inelastic scattering (DIS) using the CEBAF Large Acceptance Spectrometer and a 5 GeV electron beam. As the nuclear-target size increases, transitioning from deuterium to carbon, iron, and lead, the correlation function broadens monotonically. Its shape exhibits a significant dependence on kinematics, including the transverse momentum of the pions and the difference in their rapidity. None of the various Monte Carlo event generators we evaluated could fully replicate the observed correlation functions and nuclear effects throughout the entire phase space. As the first study of its kind in DIS experiments, this research provides an important baseline for enhancing our understanding of the interplay between the nuclear medium and the hadronization process in these reactions