Plasma, a fluid consisting of highly charged particles, is the single most abundant state of matter in the universe, yet our understanding of its properties remains incomplete. One common method of generating plasma is by inducing a large voltage difference between two charged electrodes in a low-pressure environment, referred to as direct current (DC) plasma. Understanding the relationship between plasma temperature and spectral line intensity as a function of external parameters, such as voltage, pressure, and position, is crucial to optimizing plasma-based processes. This study analyzes these dependencies systematically to help build a further understanding of the spatially dependent properties of DC plasmas. We extract electron temperature from spectroscopic measurements by analyzing line intensities assuming a Maxwell-Boltzmann electron energy distribution. The intensity of spectral lines is related to electron energy via the Boltzmann factor, allowing for temperature determination through a logarithmic plot of intensity ratios versus upper energy levels. By varying voltage and pressure, we identified trends in intensity and temperature, providing insights into plasma behavior. Our results suggest that higher discharge voltages correspond to an increase in electron temperatures, indicating a direct relationship between voltage and temperature. These results provide a greater understanding of plasma-based processes, paving a path toward greater efficiency in applications such as semiconductor manufacturing, surface treatment, and materials processing.

Our brains have evolved to navigate survival and respond to danger, but trauma dysregulates these systems, causing the brain to misinterpret everyday experiences as threats. This dysregulation results in hypervigilance, which can manifest as panic attacks, dissociation, and other debilitating symptoms. Current treatment options for trauma often focus on symptom management, overlooking the physiological impacts of trauma. These treatments can be expensive, inaccessible, and may have side effects. This literature review examines holistic, non-pharmaceutical, neuroplasticity-based (NPNB) approaches, such as breathwork, nutrition, exercise, and sleep, to challenge traditional methods and advocate for integrating holistic interventions into mainstream trauma care, emphasizing accessibility and autonomy for trauma survivors. As we explore the increasing need for mental health care, we look at the interplay between psychological trauma and physical health by exploring the mind-body connection and trauma-induced inflammation. Additionally, this exploration aims to understand how these treatments can reshape neural pathways, improve emotional regulation, and enhance psychological and physiological well-being. It also examines potential paradigm shifts in trauma care and advocates for increased accessibility to alternative treatments, particularly for individuals who cannot access conventional therapies. We expect to find that NPNB treatments are underutilized in the treatment of trauma and, if expanded upon, would have the potential to improve accessibility, reduce or eliminate side effects, and help survivors regain a sense of autonomy.

Extreme operating temperatures in rocket engines severely degrades their lifespan, function and reusability. One mitigating approach to help cool rocket engines and extend their lifespans is called Regenerative Cooling, which has been a method actively used in liquid rocket engines (LREs) since 1923. The cooling system utilizes many narrow coolant channels to draw heat away from the liquid propellant near the rocket nozzle. However, experimental research on these channels is rarely done as they are very small and a single channel is difficult to manufacture for basic research testing thereby causing many researchers to look to non-experimentally tested CFD (Computational Fluid Dynamics) simulations to perform their studies. Our experiment aims to fill the gap between simulation and practical testing by testing scaled up models with V-shaped ribs based on a study done by Zhang et al. These scaled up models would allow for more easily obtainable thermal distribution, stress, and pressure data while also being simpler and cheaper to manufacture. We believe our data could offer an alternative to non-tested CFD simulation data and, as access to experimental data increases, result in the expansion of this area of research.

Speech technology is often evaluated under idealized conditions that privilege certain speaker profiles: native English speakers in optimal acoustic environments. This approach overlooks the reality that English, as a global lingua franca, is spoken by billions of non-native speakers. Similarly, speakers with speech disorders face potential exclusion. Accurate phonemic transcription is crucial both for analyzing speech patterns in post-stroke aphasia and Computer-Assisted Pronunciation Training (CAPT). We evaluate automatic phonemic transcription under realistic conditions, including varied noise levels, L2 accents, and speech variations. We find that standard models perform suboptimal under realistic conditions, and that applying vocabulary refinement and data augmentation improves error rates by 12-28 percentage points. To demonstrate the viability of our phonemic transcription models, we develop Machine Aided Pronunciation Learning via Entertainment (MAPLE). MAPLE maintains real-time performance on consumer devices, demonstrating the practical applicability of robust socioculturally-aware phonemic transcription in educational environments.

Welcome all young and old to the future of movie magic! 2D animation remains a powerful storytelling medium, yet its resource-intensive nature has made it increasingly rare in today’s industry. What if we could change that? What if artificial intelligence (A.I) can work with, rather than against artists, making 2D animation more accessible? Could a small studio implement this and revive this beloved genre? Join international award-winning filmmaker G Alvarado as we explore cutting-edge image generation and video interpolation A.I models. Along with an enhanced 2D animation pipeline that preserves artistic integrity using customly trained models. Early findings suggest that this can significantly reduce production time, transforming what once took years into mere months. Come all far and near to see our research results in action and peek behind the curtain. For once you do, you will find through science comes art, and through innovation, a new era of storytelling begins!

Exoplanetary studies suggest that massive outer planets, such as Jupiter in our Solar System, play a crucial role in shielding inner planets from excessive asteroid bombardment, thereby contributing to long-term orbital stability. The Kepler-11 system is a tightly packed configuration of six planets that lacks a known massive outer planet protector. In this project I investigated the stability of Kepler-11 planets under varying levels of asteroid impact modeled using a combination of n-body simulations in 10,000-year segments, Monte Carlo methods, and statistical extrapolation. These results were then further extrapolated using Poisson statistics to estimate the system’s long-term evolution over millions of years. I ran simulations as the system is currently known and with a Jupiter-like planet to assess its role in deflecting or capturing incoming objects. Preliminary findings suggest that in the absence of a massive outer planet, asteroid impacts on the inner planets increase significantly, leading to cumulative orbital drift and potential long-term destabilization. These results highlight the importance of massive planets in preserving planetary system stability and suggest the possible existence of an undetected distant massive planet or a densely packed outer system that has maintained Kepler-11’s current planetary configuration.

The collection of underwater sounds for anomaly detection can contain white noise, making it challenging to analyze data. This project’s goal was to improve the process of analyzing data and detection in the presence of white noise. The project focused on the detection of the fin whale’s twenty hertz down sweep call. The call is visually recognizable on the spectrogram, a tool that visualizes audio using shape and color over time as a static image. The project used detection output from the publicly available WhaleTracks software as a comparison to the method presented herein. I focused on tuning a part of the detection process to better detect fin whale calls in a noisy environment. We focused on studying changes in the Python script find_peaks function’s prominence parameter in a normalized signal. The prominence parameter is a variable responsible for characterizing the sensitivity of the detector. Lower values of the prominence parameter increase the sensitivity of the detector and higher numbers lower the sensitivity. My research analyzed how changes in the prominence parameter would affect the detection of fin whale calls. Using a Google Colab notebook, I modified a set of code that took in data, processed the data into a readable form for the machine, detected peaks in the twenty hertz range, and then printed the data in the form of several graphs readable for the human eye. Based on the time frames used for evaluation, we concluded that the best value for the prominence parameter for all environmental conditions was three. In the future, this prominence parameter should instead be made dynamic, changing depending on the amount of sound energy present in the audio data.

Regenerative braking is a well-tested and ubiquitous technology currently used in electric and hybrid vehicles. It recovers electrical energy while stopping or slowing a vehicle rather than simply wasting the energy as heat losses. However, another much-less studied source of untapped energy also exists in vehicle suspension systems, where shock absorbers also dissipate kinetic energy as heat. This study investigates the practicality of regenerative shock absorbers for transforming oscillatory motion (vehicle bouncing) into recoverable electrical energy. In our study, a motor-driven oscillation system simulates vehicle-like suspension movements in controlled experiments. We have created an experimental regenerative electric shock design that uses oscillatory linear actuation of a series of magnets passing through a series of coils to convert mechanical energy into recoverable electrical energy. We have examined the electrical current, voltage and power characteristics and are able to quantify energy-recapture efficiency over broad operating conditions ranging from single-frequency vibrational modes to more complicated and realistic pulse (sudden impact) conditions. Our findings advance knowledge of the feasibility of using regenerative suspension systems to charge auxiliary electronics or augment vehicle power and identify an alternate method of energy recapture for the automobile industry that maximizes vehicle efficiency without sacrificing ride enjoyment.

In recent years, soft end-effector prototypes for agricultural harvesting applications have seen a rise in research and development from numerous sources. Soft robot manipulators in agriculture are necessary because of delicate produce requiring a wide area of force application to reduce bruising, as opposed to small points of contact through rigid gripper materials. Novel designs for delicate and clustered fruits and berries such as blackberries, strawberries, and blueberries are of highest demand. This is because of their small size, fragility, and the narrow windows of fruit harvest due to ripeness. These limitations for berries and vine plants necessitate the use of manual labor as opposed to assisted labor for harvesting other fruits and vegetables like apples and pears, and full harvest automation of other fruits and grains like corn and wheat. As novel proof-of-concept designs describe solutions to these limitations, sensing mechanisms for control loop compensation such as visual and tactile are required to control the parameters required when harvesting fruits. These parameters of surface roughness, overall ripeness, blemishes, etc. require thorough and precise sensing capabilities to reduce fruit waste and resulting costs. The purpose of this paper is to discuss the state of novel agricultural end-effector prototypes for harvesting non-automated produce. This review describes the materials and methods of actuation for end-effectors of small, difficult to automate, and/or delicate agricultural needs with focus on sensing methods, variability and scalability to differently sized produce, and cost-effectiveness. End-effector design prototype and case study research papers are used to produce conclusions through analyzing qualitative data and subjective results. Design improvements, future considerations, and gaps in research are covered to aid the advancement of the most promising prospective designs and potential innovation.