Illinois Mathematics and Science Academy
Illinois Mathematics and Science Academy: DigitalCommons@IMSANot a member yet
9795 research outputs found
Sort by
Dynamic Spectrum Access (DSA) Algorithms for Spatio-Temporal, Opportunistic Spectrum Sharing in 6G Networks with Heterogeneous Wireless Devices
No full textAs highlighted in the National Spectrum Strategy, Dynamic Spectrum Access (DSA) is key for enabling 6G networks to meet the growing demand for spectrum from various, heterogeneous emerging applications. In this study, we consider heterogeneous wireless networks with multiple 6G base stations (BSs) and limited frequency bands available for transmission. Each BS is given a geographical location, a coverage area, and a bandwidth requirement. To avoid interference, we impose that BSs with overlapping coverage must use distinct frequency bands. We address the problem of efficiently allocating contiguous frequency bands to BSs as they stochastically enter/exit the network over time. We develop and evaluate three bandwidth allocation strategies—continual recoloring, non-recoloring, and partial-periodic recoloring—and five different DSA algorithms that prioritize BSs based on different features. Through extensive spatiotemporal, Monte Carlo-based simulations, we test all combinations of these approaches across several metrics, including feasibility, bandwidth usage, recoloring overhead, and frequency disruption, to gain insight into their performance trade-offs. Our findings indicate that partial-periodic recoloring strategies, paired with higher-degree DSA algorithms, offer an ideal balance between spectrum utilization efficiency and minimal frequency disruption, particularly under increasingly stochastic arrival patterns–directly informing DSA implementation in real-world 6G deployments where network traffic continuously evolves
Computational Screening and Identification of Novel Cell-penetrating Peptides for Effective Drug Delivery
No full textEffectively delivering anti-cancer drugs remains a significant challenge in oncology due to their non-specific distribution and harmful side effects. Cellpenetrating peptides (CPPs) offer a promising solution by enabling the targeted transport of therapeutic agents, such as proteins, nucleic acids, and small molecules, directly into cancer cells. Bacterial-derived peptides have shown unique stability and penetration efficiency, making them strong candidates for further development. However, challenges such as low stability in the bloodstream and off-target effects limit their clinical potential. To address these issues, we used a computational screening approach and selected 59 candidates. We refined our selection to five promising peptides through further computational analysis based on their predicted ability to interact with cell membranes. These five peptides were chemically synthesized and tested in human cancer cells. Our computational and experimental approaches identified novel CPPs that can efficiently penetrate human cancer cells
Carbon Fiber Instrument Crafting
No full textThis experiment seeks to determine whether carbon fiber is a viable alternative to brass or wood in woodwind construction. The benefits of using carbon fiber include weight reduction, rigidity, and price reduction when mass-produced, resulting in affordable instruments for the underprivileged. Furthermore, the material\u27s resilience means it will not corrode like metal, making it more resistant to dents, and less likely to need costly repairs. The primary downside and reason that this is the first saxophone of its kind is that carbon fiber does not shape or tune like its brass or wood counterparts. However, we successfully constructed a carbon-fiber saxophone bell. And, while that may not look impressive, it indicates the endless possibility for carbon-fiber work on the rest of the instrument. Following the lead of the University of Illinois’ FSAE team, we prepped a mold for the carbon fiber using insulation foam. Then, carbon fiber gets applied to the mold and autoclaved to harden. Post autoclave, excess resin and fiber are filed off of the horn, also forming the tone hole that is strategically placed during the molding process. The result is a full-sized tenor saxophone bell
Analysis on Lepton Cuts for Doubly Charged Higgs Boson
No full textIn data analysis, selection cuts play an important role in filtering out background data while keeping the needed signal. Cuts improve the statistical significance of the measurements by retaining mostly the desired information. In this study, an analysis was conducted to understand which selection cuts were the most effective for the doubly charged Higgs boson search. The analysis was run on muons and electrons, and compared the original working cuts to a machine- learning-based multivariate analysis cut. Both cuts were tested with loose, medium, and tight leptons. The test concluded that the original cuts were the most efficient for electrons while the multivariate analysis was more efficient for muons
Computational Optimization of Small Molecule Medication Efficacy for COVID-19
No full textThe COVID-19 pandemic has highlighted limitations in different aspects of current vaccines, including reduced immunity and reduced protection against new strains of COVID. These issues highlight the need for better vaccine designs that offer longer-lasting and broader protection. Our project uses Computer Aided Drug Design (CADD) to enhance vaccine effectiveness by improving molecular binding affinity and structural stability. By targeting the SARS-CoV-2 spike protein, CADD techniques available in SeeSar, such as molecular docking and simulations can identify structural modifications that could strengthen vaccine-protein interactions. Virtual screening allows us to test multiple molecular variations efficiently, later selecting the most promising candidates for further study. By applying these techniques to strengthen vaccine efficacy, it may reduce the frequency of vaccine booster doses and lower the risk of post-COVID conditions
Antihypertensive Capabilities of Gallic Acid–Derived Esters
No full textHypertension is the most predominant risk factor for the onset of cardiovascular disease in the world and is one of the largest causes of mortality worldwide. Current treatments for the condition vary significantly due to individual circumstances, with severe cases often involving the usage of careful dosages of custom combinations of medicines to minimize unintended effects. Thus, great priority is given to discovering novel economical antihypertensive treatments with minimal adverse effects.
Morus Alba, a tree cultivated for thousands of years in Asia, has recently gained traction as a potential source of medicinal compounds due to its usage in traditional medicines and rich polyphenol content. One major bioactive substance present in Morus Alba is 3,4,5- trihydroxybenzoic acid or gallic acid, which has demonstrated potential antihypertensive capabilities, such as in the inhibition of the renin-angiotensin system.
This research aims to investigate the antihypertensive capabilities of gallic-acid based molecules through computational docking with the protein structure of the angiotensin-converting enzyme in the program SeeSAR, which has generated several potential angiotensin-inhibiting esters. Another set of laboratory procedures created and explored several pathways to synthesize and purify the discovered medicines. Results are to be presented
Solar Flares: Investigating the Link Between Metallicity and Stellar Activity
No full textThis study investigates the correlation between the frequency of solar flares and a star’smetallicity. It is known that metallicity affects convection in a star, and the mass of the star, the rotation rate of the star, and the convection in a star all affect the activity of a star. The activity of a star is defined by how many and how large the stellar flares and coronal mass ejections are. Therefore, a relationship should be able to be measured between the stellar flare frequency and metallicity (Saders et al.). Multiple data sets could be analyzed and used to explore this relationship, currently, this study focuses on Kepler data sets. The process involved sorting and filtering data by cross-referencing each data set with a previous study (Yang et al.
Improvement of Localization of Radiation-Resistant Tumor Areas with MesoporousSilicon Nanotube-Based Intracellular Electron Paramagnetic Resonance pO2 Imaging
No full textHypoxic tumors consist of areas that have reduced oxygen levels in the tissue due to insufficient blood flow or poor vascularization. As a result, the tumor becomes more aggressive, spreading to other parts of the body, and being harder to treat with chemotherapy or radiation. Determining the oxygenation at the time of diagnosis will enable more effective treatment planning and therapeutic effect. Electron Paramagnetic Resonance Imaging (EPRI) with a sensor to measure oxygen was utilized to assess tumor oxygenation in vivo. The triarylmethyl (trityl) radical is good for measuring oxygen. However, it faced challenges from high dosage requirements, a short half-life, and poor intracellular permeability. The goal of this study is to develop mesoporous silica nanoparticles (MSNs) as carriers, which allows for an effective targeted delivery of the trityl radicals without being destroyed by dilution or environment. The synthesis of such a nanoplatform for tumor targeting was performed without losing oxygen- sensing capacity due to self-relaxation or broadening effects. The results indicated a high sensitivity to oxygen within the partial oxygen pressure range between 0 and 155 mmHg. MSN- trityl showed the best intracellular oxygen mapping in both in-vitro and in-vivo studies. MSN- trityl provides high-value oxygenation information for in-situ diagnostic imaging in potentialclinical applications
Rapamycin Nanoparticles for the Treatment of Lymphangioleiomyomatosis
No full textLymphangioleiomyomatosis (LAM) is a rare, progressive lung disease primarily affecting women of childbearing age. Characterized by bi-allelic mutations in TSC1 or TSC2, LAM leads to elevated mTORC1 activity, resulting in pulmonary tumor nodules and reduced lung function. One possible method of treatment is the rapamycin drug which works through the inhibition of the mTOR. However, while rapamycin therapy slows tumor progression, it does not eliminate LAM cells, leaving lung transplantation as the only definitive treatment. To counter this, an innovative immunotherapy approach was tested through the application of nanoparticle rapamycin and the introduction of an antigen receptor (CAR). This was done through patient-derived xenograft (PDX) model, preserving the LAM microenvironment. These tissues were treated with rapamycin, nanoparticle rapamycin, or CAR CCR2 and then frozen into explants which were then sectioned for further analysis. These tissues were stained with different protein markers like gp100 and Ps6 and then imaged to quantify the effectiveness of each treatment. Immunotherapies show efficacy in PDX models as rapamycin models were 43% more effective than control. This work has broader implications for treating benign tumors and other rare diseases, ultimately striving for a curative, precision-based immunotherapy for LAM
A Comparative Study of Quantum Programming Languages: Programmability and Computational Efficiency
No full textQuantum computing is rapidly becoming of increasing importance as they become more powerful and accessible. With computers surpassing the 1,000-qubit threshold and quantum chips like Google’s Willow gaining traction, these devices are pushing the boundaries of what was once impossible. However, as with any computer, these devices are only as effective as the platform used to control them. From here emerges quantum programming and the quantum programming languages behind them. This study attempts to compare the features, ease of use, and efficiency of various quantum programming languages including Qunity, Qiskit, and Q#. These quantum programming languages take vastly different approaches to achieve the same task: effective control over quantum processes. This study will undertake the complicated task of comparing completely different quantum programming methods. These standalone languages have different structures and platforms, with their base languages ranging from the common Python to the niche OCaml. The work in this study aims to establish a comprehensive guide to the uses and advantages to various quantumprogramming languages