Illinois Mathematics and Science Academy
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Quantum Information Processing for Computational Linguistics on Small Ethical Texts (SETS) and Tamil Adjectives and Proverbs (TAP)
No full textThe objective is to propose an information processing model using quantum computing for computational linguistics on Small Ethical Texts (SETS) with Tamil Adjectives and proverbs (TAP). This model utilizes the Bobcat parser, a part of the Lambeq library, to parse the given SETS and map them into Combinatory Categorial Grammar (CCG) structures. Then apply Quantum Natural Language Processing (QNLP) to convert CCG structures into quantum circuits. The challenge in applying QNLP during Tamil grammar parsing is that the Bobcat parser parses only the English texts since it was pretrained on an English corpus. Since it incorrectly classifies grammar, it is necessary to apply NLP tools like SpaCy from MIT and Stanza from Stanford for Tamil SETS to tokenize and lemmatize. Stanza was pretrained on a corpus of Universal Dependencies that include Tamil syntactic annotations. Stanza uses dependency parsing whereas the Bobcat parser uses CCG parsing, necessitating a python class to be created for conversion. As a first level processing output, the program creates relevant string diagrams for the SETS’ syntactic relationships. The next step is to proceed with the string diagram and convert it into an accurate quantum circuit to analyze the semantic relationships between the Tamil linguistic entities
Signal Processing and Classification Techniques of Surface Electromyography to Understand Muscle Atrophy Due to Aging Presenter
No full textSignal analysis is a key field in engineering with diverse applications, from wireless technology to medical diagnostics. Medical applications focus on analyzing physiological signals for diagnosis, treatment, and research. Electromyography (EMG) is one such technique, used to improve diagnostic and therapeutic care. This study investigates the acquisition, analysis, decomposition, and interpretation of bio-signals obtained from surface EMG (sEMG). By analyzing sEMG signals from sensors, the research explores the impact of aging on muscle information processing, coding, and transmission. Data is collected using Vernier EKG three- lead sensors, along with measurements of Grip Strength, Angle Flexion, Strength (force), and sEMG from two distinct EKG sensors per test. Techniques like Fast Fourier Transform (FFT), Averaging, Root Mean Squared (RMS), Peak Amplitude Values, and Filtering are applied using MATLAB to quantify the signals. Preliminary findings indicate that muscle atrophy becomes more prominent with age, especially in the 40-50 year group, showing a 15% decrease in RMS values of sEMG frequencies. This comparison helps distinguish muscle atrophy due to aging from other factors and relates the findings to motor neuron activity and muscle fiber contraction. In conclusion, signal analysis facilitates the interpretation of sEMG data, bridging the gap between signal processing and biological applications
Intramembranous Bone Regeneration After Marrow Ablation in Heterozygotes
No full textIntramembranous bone regeneration is an essential process for skeletal repair involving the direct differentiation of mesenchymal cells into osteoblasts. This study examines the formation of osteoblasts after marrow ablation surgery, a controlled injury model, to build understanding of intramembranous bone regeneration in haplotype mice, and how genetic variation may influence regenerative capabilities. Following surgery, femur samples were collected, frozen in optimal cutting temperature (OCT) compound, sectioned, mounted on slides, and stained using histological techniques before being analyzed under a microscope to assess osteoblast formation. Results are ongoing and will be based on microscopic observations. This research will provide insight into the capabilities of intramembranous bone regeneration in heterozygotes, potentially advancing regenerative medicine and orthopedi treatment
Identification of effects of Matricaria chamomilla essential oil against bacteria
No full textModern medicine has been seen to cause a development of resistance after time of usage, this ineffectiveness causes stronger doses and the need for a change in antibiotics. Due to this problem, the development of more antibiotics has become crucial despite its difficult process to create and execute. Natural products have been noted to have much less resistance development over time from their usage despite dating back to ancient times. This project aims to test the antibacterial properties that are contained in the natural product of Matricaria Recutita through the creation of essential oil from ground-dried chamomile and the comparison to the store-bought counterpart compared to the current antibiotic treatment to identify the effectiveness in bacteria and its comparison to modern antibacterial medicine. Then testing the minimum inhibitory concentration to identify to what intensity this treatment must be used. The results will allow the possibility of natural products to be incorporated into modern medicine to fight bacteria
Implications of Singing and Listening to Music on Working Memory
No full textMusic is known to improve focus and memory, yet different brain regions are activated when listening to music versus singing. For example, singing uniquely engages the frontal and parietal systems, closely linked with thinking and problem-solving. However, singing also requires certain motor skills and is considerably more cognitively taxing than simply listening to music. Despite the differences in brain activation, the benefits of singing to memory remain poorly understood. This project aims to understand the distinct roles of listening to music and singing in two cognitive processes - attention and memory - and how music may be advantageous. Participants were assigned to one of three groups (n=90): no music, listening to a song, or singing along with a song. The song used for this study was “Here Comes the Sun” by the Beatles, commonly associated with positive valence. From there, analyses were conducted to examine the effect of music listening on memory and focus. The results of this study have immense potential to highlight music-based therapies as a tool for those with poor working memory, and the power of music in improving well-being
A Reinforcement Learning Approach to Quadrotor Stability in Windy Conditions
No full textUnmanned Aerial Vehicles, particularly quadrotors, have diverse applications in logistics, agriculture, surveillance, and search and rescue. However, quadrotor stability is highly sensitive to variable environmental conditions, such as wind. The Proportional-Integral-Derivative (PID) controller, the traditional control method for quadrotors, performs well in stable conditions but faces difficulties when tasked with maintaining drone attitude in more turbulent environments. Additionally, existing reinforcement learning (RL)-based research on quadrotor stability has primarily focused on simulated environments with low wind speeds and unrealistic wind dynamics, limiting its practical applicability. In this work, reinforcement learning is applied to the problem of quadrotor stabilization to improve performance in varying wind disturbances of different directions and intensities. Specifically, we employ a Deep Q-Network (DQN) trained using a Computational Fluid Dynamics (CFD)-based wind model and compare its performance against the traditional PID controller. The study leverages the Gym reinforcement learning library, Gazebo simulation software, and PX4 flight control to define a custom wind environment and train a quadrotor agent. Our results demonstrate the potential of this reinforcement learning approach in enhancing quadrotor stability in dynamic wind conditions
Prototyping and Testing the Screw-propelled Multi-terrain Amphibious RoboT (SMART)
No full textThe Screw-propelled Multi-terrain Amphibious RoboT (SMART) is a screw-propelled vehicle designed to navigate the diverse Arctic landscape. It uses one or more pairs of helical drives (Archimedes’ screws) for movement, offering Screw (moving longitudinally) and Crab-crawl (moving laterally) locomotion for traveling on land. SMART will be able to explore extreme terrains such as icy landscapes, deep water, or remote Arctic regions, and collect data and perform tasks without risking human lives. As space exploration starts to become a larger priority, it is important to be able to develop rovers and robots that can traverse on the surface of planets and moons. SMART’s adaptability makes it suitable for extraplanetary exploration particularly on the diverse Martian terrain and on the icy crust and oceans located under the surface on Europa. The robot can also aid in monitoring natural resources in remote areas. The prototype was first modeled on Fusion360, a CAD software, and went through multiple iterations where different screw models and blade heights were used to determine the optimal dimensions. To analyze the stability, the RPM values (Revolutions per Minute) are collected to see which motor speed is more desirable on different terrains in terms of robot functionality, adaptability, and efficiency
Investigating the Effects of Light Exposure on Sleep in Young Adults
No full textSleep health is an important determinant of general well-being, however many young adults have irregular sleep patterns due to environmental and behavioral influences. This study looks at the association between light exposure and sleep quality, specifically among undergraduate students at Northwestern University. In the first phase of survey distribution, 92 participants evaluated their sleep patterns, chronotype, and overall sleep health using recognized sleep tools such as the Munich Chronotype Questionnaire (MCTQ), the Reduced Unit Sleep Assessment Tool (RU-SATED), and the Pittsburgh Sleep Quality Index (PSQI). A selection of subjects with various sleep patterns were chosen to wear actigraphy watches, which enable for objective monitoring of sleep duration, timing, and light exposure. We wanted to see how light settings affected circadian cycles and sleep efficiency by combining subjective self-reports with objective actigraphy data. The study sheds light on the potential significance of light exposure in sleep health, guiding future interventions to improve sleep hygiene among young individuals. Our findings add to the expanding amount of research on circadian rhythms and may aid in the development of individualized recommendations for optimizing light exposure to promote healthy sleep patterns
Kinematic and Velocity Modeling of Serial Manipulators
No full textThis study explores the kinematic modeling of robotic serial manipulators. It covers forward and inverse kinematics and introduces the Denavit–Hartenberg convention for 3D manipulators, along with loop closure equations. The work further examines velocity and inverse velocity kinematics and employs interpolation techniques for smooth trajectory planning. A modeling framework for typical serial robots is presented, with simulations validating the influence of joint configurations and actuator dynamics on performance. Finally, the study discusses current applications and practical uses of these modeling techniques
Top-Antitop Background Minimization To Improve Doubly Charged Higgs Boson Detection Sensitivity
No full textThe doubly charged Higgs boson is a particle predicted by various theoretical models such as the left-right symmetric Model. Using data from the CMS detector at the LHC in collaboration with Fermilab, we reconstruct signal events while making cuts to minimize background detection. The Higgs Boson is predicted to have a decay that results in two same-sign leptons. In order to minimize background from decays that produce similar decay results, we look to create optimal cuts on top-antitop decays which also result in di-lepton same-charge production if such cuts exist. This will help us narrow down possible signals while omitting background from consideration in order to improve our doubly charged Higgs boson signal detection sensitivity