Illinois Mathematics and Science Academy
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Analyzing localized heating in Deep Brain Stimulation leads under radiofrequency exposure
No full textMRI is widely used in medical diagnostics due to its superior tissue contrast. However, patients with active implantable medical devices (AIMDs), such as deep brain stimulation (DBS) systems, face risks during MRI. DBS is an AIMD commonly used for neurological conditions, and many patients require MRI scans. During MRI, radiofrequency (RF) field energy can couple with the conductive DBS lead, increasing the specific absorption rate (SAR) of RF energy in surrounding tissues. This interaction may cause localized heating at the electrode tip, posing a safety concern. Heating depends on the shape, orientation, and length of the leads, and configuring the extracranial portion of DBS leads into concentric loops near the lead insertion point has been shown to reduce heating. In this study, realistic lead trajectories with and without loops were modeled to assess their impact on RF heating by minimizing exposure to the maximum tangential electric field. Using the validated transfer function of a commercially available Boston Scientific DBS system, tangential electric fields calculated in ANSYS HFSS along the lead trajectories were used to predict RF heating at the electrode tip. This work highlights the importance of optimizing DBS trajectories to significantly reduce RF heating and enhance patient safety
Reengineering Penicillin to Combat MRSA to resemble Ceftaroline through Chemical Synthesis
No full textMRSA (Methicillin-Resistant Staphylococcus aureus) is a strain of bacteria resistant to many common antibiotics, such as methicillin and penicillin. It is a common cause of severe infections, including pneumonia and sepsis.
Antibiotics like Ceftaroline have shown significant efficacy against MRSA. However, their high costs and limited accessibility make them less viable for underserved populations. In contrast, while widely available and cost-effective, penicillin remains ineffective against MRSA due to many bacteria evolving resistance mechanisms. This disparity underscores the urgent need for a solution that upholds clinical effectiveness and is economically accessible, especially in resource-limited environments like underfunded communities.
Our study focuses on bridging the issue of antibiotic resistance by reengineering penicillin to combat MRSA. Through chemical synthesis, we aim to modify the R1-side chain of penicillin to resemble ceftaroline, a potent but pricey drug proven to be effective against the MRSA bacterium. By leveraging this structural modification, we strive to produce an effective compound against MRSA that is accessible to populations worldwide due to lower costs. As antibiotic resistance poses substantial challenges, this research could pave the way for a more equitable and efficient approach to combating MRSA infections
Analyzing the t tbar Background of the Doubly Charged Higgs Boson
No full textThe Standard Model is the current basis of particle physics, providing a basic set of particles and interactions. Since its introduction, researchers have been attempting to discover new particles to prove an extended set of theories. One of these particles is the doubly charged Higgs boson. If found, the Doubly Charged Higgs would have many implications for other areas of particle physics such as the existence of a right-handed neutrino.
One important background process for the doubly charged Higgs search involves t and tbar, has a signal of 2 leptons and two neutrinos, but it shows as 4 leptons, the same signal as the doubly charged Higgs. This creates the potential for a cut to reduce background. We also must understand where the two leptons come from in this background. We will analyze the t and tbar background to find why four leptons are being detected, which will lead to background cuts to aid in our search for the Doubly Charged Higgs
Developing a User-friendly System for Home-based Monitoring of Arm Use after Stroke
No full textStroke rehabilitation faces challenges in providing real-time care outside clinical settings, as they require in-person supervision and lack personalized monitoring of continuous progression in stroke rehabilitation. Recent advances in wearable sensors (e.g., inertial measurement unit (IMU), electromyography (EMG)) offer avenues to longitudinally track arm use in the real-world setting, e.g. during activities of daily living at home. However, challenges remain in translating such technology mainly due to practical barriers in transferring the technical knowledge and skills required for operating the sensor/device to acquire data. The main objective of this project was to develop a user-friendly system that consists of: 1) “easy-to-don and-doff” wearable sensors, 2) “easy-to-use” graphical user interface (GUI) for data acquisition, and 3) “on-the-go” receiver unit for reliable wireless connection. To this end, we used Myo Armband (Thalmic Labs, CANADA), which is a consumer-grade bracelet sensor capable of capturing IMU data and EMG signals to assess movement and muscle activity that communicates via bluetooth. We developed a Python-based GUI that collects and displays real-time data visualization for the two Myo Armbands on the upper arm and forearm. This system has enabled real-time monitoring, reliable tracking, and scalable rehabilitation, enhancing accessibility, engagement, and recovery outcome
Developing IIR Filters for NICU Active Noise Cancellation Incubator
No full textWhen infants are fresh out of the womb their ears are extremely sensitive to even the quietest of noises. The infant\u27s hearing is volatile in the loud hospital environment due to the sounds produced by the medical machinery which could potentially cause long term hearing damage. To reduce the noise heard by the infants we improved upon an existing active noise cancelling incubator. By using An infinite impulse response (IIR) filter to record frequencies in the time domain we can create noises with an opposite amplitude of unwanted noise around the baby\u27s ear using a 2x2x2 system consisting of input microphones, speakers, and error microphones. When this noise is played by a speaker towards the baby\u27s ear it will destructively interfere with the noises approaching the baby’s ear and reduce the amount of total sound the baby will hear. In order to set up this IIR filter we need to set up a working active noise cancellation incubator by updating the hardware and software to more modern components
Implementing Machine Learning Techniques for Optimizing Atomic Layer Deposition in Thin Films Growth
No full textPerfecting the development of materials synthesis conditions in nanotechnology remains a significant challenge, particularly in atomic layer deposition (ALD), a versatile process used in the development of semiconductors. ALD involves repeated dosing and purging steps with chemical material and requires incredible precision. Optimizing time intervals for dosing and purging steps is essential to avoid incomplete surface coverage or poor-quality deposition. To accomplish this, good growth must be maximized while minimizing unwanted reactions at the atomic level and overall time for the ALD process. This study utilizes machine learning techniques to accelerate the optimization of ALD processes by developing a Gaussian Process-based (GP) algorithm trained across 100 simulated reaction environments. These simulations mimic real-world experimental conditions, enabling the model to predict optimal deposition parameters efficiently and accurately. To validate the approach, the trained model is tested in an experimental ALD setup equipped with in-situ characterization techniques that provide real-time feedback, allowing the model to tune the reaction. By eliminating human intervention, this work creates a completely autonomous platform for self-optimizing materials synthesis. This framework can extend to alternative deposition techniques such as plug-flow, fluidized bed, and spatial ALD, paving the way for broader applications in thin film development
Quantitative Analysis of Biomarkers Using G-Quadruplex-Hemin as a Catalase Enzyme
No full textNucleic acid biomarkers are useful tools that can give diagnoses, indicate prognosis, and monitor the effectiveness of therapy in various diseases. The quantitative analysis of oligonucleotides provides direct evidence that aids in treatment planning and therapy for these conditions, but current methodologies of analysis are costly due to calibration and require high- end laboratory equipment. To bypass these shortcomings, our experiment utilizes stoichiometry and the G-quadruplex-hemin complex, which can be engineered to follow a target-probe binding model that catalyzes hydrogen peroxide decomposition based on the amount of the target oligonucleotide sequence in the solution. Oxygen gas is released during the decomposition reaction, forming bubbles in the solution. The results can be interpreted from the quantity of bubbles present in the solution with a higher amount of bubbles signaling a higher presence of the nucleic acid biomarker, a cost-effective and widely applicable method of quantitative analysis. Further experiments are underway in order to finetune this model and produce a significant difference in bubble production between controls and samples containing oligonucleotides. Various factors such as buffer types, presence of surfactants, and concentration of reactants can be adjusted to improve the system
Repurposing Disease-Associated Inhibitors to Disrupt Thioredoxin Reductase in Cryptosporidium parvum
No full textCryptosporidiosis is a severe diarrheal disease caused by the protozoan parasite Cryptosporidium, posing a significant health risk to immunocompromised individuals and young children in low-resource settings. Current treatment options are limited, underscoring the urgent need for novel therapeutics. This project investigates thioredoxin reductase (CpTrxR), an essential enzyme in Cryptosporidium\u27s redox homeostasis, as a potential drug target. We evaluated a panel of 20 inhibitors, previously shown to exhibit activity against diseases such as malaria, schistosomiasis, and cancer, for their efficacy against CpTrxR. Using a combination of biochemical assays, computational modeling, and structural analysis, we assessed each inhibitor’s potency and binding characteristics. While several compounds demonstrated measurable inhibition of CpTrxR, their IC₅₀ values were not sufficiently low to suggest strong potential as therapeutic candidates
Exploring the Performance of a Micro-Gap Thermionic Energy Converter
No full textThermionic energy conversion (TEC) is a unique method of transforming energy, providing a direct exchange of excess heat to usable power with no moving parts or harmful byproducts. TEC has impressive potential for waste heat recovery, clean energy generation, and even enhancement of existing clean energy technologies such as solar or nuclear energy. While TEC has received substantial interest from the scientific community, specifically micro/nanoscale TECs, studies on TEC are limited to computational investigations, with very few experimental studies. These limitations are due to the harsh conditions required for testing TEC: thermal gradients as large as 1000 K between the electrodes while maintaining gap distances as small as 500nm. In this study, we develop an experimental platform to test micro/nanoscale TEC and analyze the effects of various materials, temperature differences, and gap distances. This experiment enables extensive studies of TEC—realizing many of the theoretical predictions proposed in previous literature—and allows for a more precise understanding of charge transport at the micro/nanoscale, a vital step for understanding how TEC can be advanced further
Designing IMSA\u27s Al Future: Human centered Al and Ethics Intern
No full textThe focus Of IMSA Al Center for Al Human Centered Al and Ethics is advancing responsible artificial intelligence development and encouraging ethical considerations and conversations in education, research, and institutional policy.
To do this, we focused on curriculum development. We designed and implemented an Al Ethics course, workshops, and interessions such as Teaching and Learning in the Age Of Generative Al, Writing to Make Generative Al Useful (Prompt Engineering), and Independent Al Lab Projects. We also expanded on the LE Il Reviews ChatGPT project where students engaged in critical evaluation Of large language models to enhance their Al literacy skills. Additionally, three Al-focused computer science courses with a focus on ethics were developed for AY 2025-2026.
This year\u27s community engagement included quarterly Al and ethics programs and Al Bytes discussions on Al in Education, Politics, and Economics, Ethics of DeepSeek, and Copyright and Consent in Generative Al. The second annual Al Book Read was based around Co-intelligence by Ethan Mollick.
With a $30,000 grant, the Center acquired Al development tools, robotics kits, Al glasses, and Khanmigo Al for ethical Al education. ChatGPT for Teams was introduced to engage faculty in responsible Al use.
Our department was able to help students develop an awareness Of ethics in Al. We hope to continue this with policy development and community conversations focused on Al ethics