Physical Sciences and Mathematics Commons^™

Terry Riley's "In C" For Mobile Ensemble, David B. Wetzel, Griffin Moe, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

This workshop presents a mobile-friendly Web Audio application for a “technology ensemble play-along” of Terry Riley’s 1964 composition In C. Attendees will join in a reading of In C using available web-enabled devices as musical instruments. We hope to demonstrate an accessible music-technology experience that relies on face-to-face interaction within a shared space. In this all-electronic implementation, no special musical or technical expertise is required.

Accepted for presentation and publication at WAC 2024.

Emoji Use In Social Media Posts: Relationships With Personality Traits And Word Usage, Shelia Kennison, Kameryn Fritz, Maria Andrea Hurtado Morales, Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

Prior research has demonstrated relationships between personality traits of social media users and the language used in their posts. Few studies have examined whether there are relationships between personality traits of users and how they use emojis in their social media posts. Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, which depict faces with expressions, objects, animals, and activities. We conducted a study with two samples (n = 76 and n = 245) in which we examined how emoji use on X (formerly Twitter) related to users’ personality traits and language use …

Biochemical And Structural Analysis Of The Bacterial Enzyme Succinyl-Diaminopimelate Desuccinylase (Dape) From Acinetobacter Baumannii, Emma H. Kelley, George Minasov, Katherine Konczak, Ludmilla Shuvalova, Joseph S. Brunzelle, Shantanu Shukla, Megan Beulke, Teerana Thabthimthong, Ken W. Olsen, Nicole L. Inniss, Karla Jf Satchell, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

There is an urgent need for new antibiotics given the rise of antibiotic resistance, and succinyl-diaminopimelate desuccinylase (DapE, E.C. 3.5.1.18) has emerged as a promising bacterial enzyme target. DapE from Haemophilus influenzae (HiDapE) has been studied and inhibitors identified, but it is essential to explore DapE from different species to assess selective versus broad-spectrum therapeutics. We have determined the structure of DapE from the ESKAPE pathogen Acinetobacter baumannii (AbDapE) and studied inhibition by known inhibitors of HiDapE. AbDapE is inhibited by captopril and sulfate comparable to HiDapE, but AbDapE was not significantly …

Cyclobutanone Inhibitors Of Diaminopimelate Desuccinylase (Dape) As Potential New Antibiotics, Thahani Shifna Habeeb Mohammad, Emma H. Kelley, Cory T. Reidl Dr., Katherine Konczak, Megan Beulke, Janielle Javier, Ken W. Olsen, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

Based on our previous success in using cyclobutanone derivatives as enzyme inhibitors, we have designed and prepared a 37-member library of α-aminocyclobutanone amides and sulfonamides, screened for inhibition of the bacterial enzyme diaminopimelate desuccinylase (DapE), which is a promising antibiotic target, and identified several inhibitors with micromolar inhibitory potency. Molecular docking suggests binding of the deprotonated hydrate of the strained cyclobutanone, and thermal shift analysis with the most potent inhibitor (3y, IC50 = 23.1 µM) enabled determination of a Ki value of 10.2 +/− 0.26 µM and observed two separate Tm values for H. influenzae DapE (HiDapE).

Conventions, Definitions, Identities, And Other Useful Formulae, Robert A. Mcnees Iv

Physics: Faculty Publications and Other Works

As the name suggests, these notes contain a summary of important conventions, definitions, identities, and various formulas that I often refer to. They may prove useful for researchers working in General Relativity, Supergravity, String Theory, Cosmology, and related areas.

Actionpoint: An App To Combat Cyberbullying By Strengthening Parent-Teen Relationships, Maddie Juarez, Natali Barragan, Deborah Hall, George K. Thiruvathukal, Yasin Silva

Computer Science: Faculty Publications and Other Works

No abstract provided.

Neutrino Self-Interactions: A White Paper, Jeffrey M. Berryman, Nikita Blinov, Vedran Brdar, Thejs Brinckmann, Mauricio Bustamante, Francis-Yan Cyr-Racine, Anirban Das, André De Gouvêa, Peter B. Denton, P.S. Bhupal Dev, Bhaskar Dutta, Ivan Esteban, Damiano Fiorillo, Martina Gerbino, Subhajit Ghosh, Tathagata Ghosh, Evan Grohs, Tao Han, Steen Hannestad, Matheus Hostert, Patrick Huber, Jeffrey Hyde, Kevin J. Kelly, Felix Kling, Zhen Liu, Massimiliano Lattanzi, Marilena Loverde, Sujata Pandey, Ninetta Saviano, Manibrata Sen, Ian M. Shoemaker, Walter Tangarife, Yongchao Zhang, Yue Zhang

Physics: Faculty Publications and Other Works

Neutrinos are the Standard Model (SM) particles which we understand the least, often due to how weakly they interact with the other SM particles. Beyond this, very little is known about interactions among the neutrinos, i.e., their self-interactions. The SM predicts neutrino self-interactions at a level beyond any current experimental capabilities, leaving open the possibility for beyond-the-SM interactions across many energy scales. In this white paper, we review the current knowledge of neutrino self-interactions from a vast array of probes, from cosmology, to astrophysics, to the laboratory. We also discuss theoretical motivations for such self-interactions, including neutrino masses and possible …

Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep Learning (DL) methods have shown substantial efficacy in computer vision (CV) and natural language processing (NLP). Despite their proficiency, the inconsistency in input data distributions can compromise prediction reliability. This study mitigates this issue by introducing uncertainty evaluations in DL models, thereby enhancing dependability through a distribution of predictions. Our focus lies on the Vision Transformer (ViT), a DL model that harmonizes both local and global behavior. We conduct extensive experiments on the ImageNet-1K dataset, a vast resource with over a million images across 1,000 categories. ViTs, while competitive, are vulnerable to adversarial attacks, making uncertainty estimation crucial for …

Optimized Uncertainty Estimation For Vision Transformers: Enhancing Adversarial Robustness And Performance Using Selective Classification, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep Learning models often exhibit undue confidence when encountering out-of-distribution (OOD) inputs, misclassifying with high confidence. The ideal outcome, in these cases, would be an "I do not know" verdict. We enhance the trustworthiness of our models through selective classification, allowing the model to abstain from making predictions when facing uncertainty. Rather than a singular prediction, the model offers a prediction distribution, enabling users to gauge the model’s trustworthiness and determine the need for human intervention. We assess uncertainty in two baseline models: a Convolutional Neural Network (CNN) and a Vision Transformer (ViT). By leveraging these uncertainty values, we minimize …

Peatmoss: Mining Pre-Trained Models In Open-Source Software, Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajiv Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis

Computer Science: Faculty Publications and Other Works

Developing and training deep learning models is expensive, so software engineers have begun to reuse pre-trained deep learning models (PTMs) and fine-tune them for downstream tasks. Despite the widespread use of PTMs, we know little about the corresponding software engineering behaviors and challenges. To enable the study of software engineering with PTMs, we present the PeaTMOSS dataset: Pre-Trained Models in Open-Source Software. PeaTMOSS has three parts: a snapshot of (1) 281,638 PTMs, (2) 27,270 open-source software repositories that use PTMs, and (3) a mapping between PTMs and the projects that use them. We challenge PeaTMOSS miners to discover software engineering …

Fermion Pair Radiation From Accelerating Classical Systems, Margarita Gavrilova, Mitrajyoti Ghosh, Yuval Grossman, Walter Tangarife, Tien-Hsueh Tsai

Physics: Faculty Publications and Other Works

Accelerating classical systems that couple to a fermion-antifermion pair at the microscopic level can radiate pairs of fermions and lose energy in the process. In this work, we derive the generalization of the Larmor formula for fermion pair radiation. We focus on the case of a point-like classical source in an elliptical orbit that emits fermions through vector and scalar mediators. Ultra-light fermion emission from such systems becomes relevant when the mass of the mediator is larger than the frequency of the periodic motion. This enables us to probe regions of the parameter space that are inaccessible in on-shell bosonic …

Design And Synthesis Of N-Succinyl-L,L-2.6-Diaminopimelic Acid Desuccinylase Inhibitors As Potential Novel Antibiotics, Thomas Dipuma

Master's Theses

N-Succinyl-L,L-2,6-Diaminopimelic Acid Desuccinylase (DapE) is a bacterial enzyme located in the lysine biosynthetic pathway of all Gram-negative and most Gram-positive species of bacteria including the notorious ESKAPE pathogens, or pathogenic strains of bacteria that have developed significant levels of resistance to currently available antibiotics. As a means to combat this challenge of growing antimicrobial resistance, we have identified the bacterial enzyme DapE as a conserved, novel enzymate target within these resistant bacterial strains,as DapE is responsible for the production of m-DAP and lysine which are ultimately employed in bacterial cell wall synthesis. The overall aim of this research is to …

Finite Charges From The Bulk Action, Robert Mcnees, Céline Zwikel

Physics: Faculty Publications and Other Works

Constructing charges in the covariant phase space formalism often leads to formally divergent expressions, even when the fields satisfy physically acceptable fall-off conditions. These expressions can be rendered finite by corner ambiguities in the definition of the presymplectic potential, which in some cases may be motivated by arguments involving boundary Lagrangians. We show that the necessary corner terms are already present in the variation of the bulk action and can be extracted in a straightforward way. Once these corner terms are included in the presymplectic potential, charges derived from an associated codimension-2 form are automatically finite. We illustrate the procedure …

A Critical Inter-Subunit Interaction For The Transmission Of The Allosteric Signal In The Agrobacterium Tumefaciens Adp-Glucose Pyrophosphorylase, Hiral Patel, Gabriela Martinez-Ramirez Ms., Emily Dobrzynski, Alberto A. Iglesias, Dali Liu, Miguel Ballicora

Chemistry: Faculty Publications and Other Works

ADP-glucose pyrophosphorylase is a key regulatory enzyme involved in starch and glycogen synthesis in plants and bacteria, respectively. It has been hypothesized that inter-subunit communications are important for the allosteric effect in this enzyme. However, no specific interactions have been identified as part of the regulatory signal. The enzyme from Agrobacterium tumefaciens is a homotetramer allosterically regulated by fructose 6-phosphate and pyruvate. Three pairs of distinct subunit-subunit interfaces are present. Here we focus on an interface that features two symmetrical interactions between Arg11 and Asp141 from one subunit with residues Asp141 and Arg11 of the neighbor subunit, respectively. Previously, scanning …

Exploring The Genotypic And Phenotypic Differences Distinguishing Lactobacillus Jensenii And Lactobacillus Mulieris, Adriana Ene, Swarnali Banerjee, Alan J. Wolfe, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii are dominant species of the urogenital microbiota. Prior studies suggest that these Lactobacillus species play a significant role in the urobiome of healthy females. In our prior genomic analysis of all publicly available L. jensenii and Lactobacillus mulieris genomes at the time (n = 43), we identified genes unique to these two closely related species. This motivated our further exploration here into their genotypic differences as well as into their phenotypic differences. First, we expanded genome sequence representatives of both species to 61 strains, including publicly available …

Exploring The Genotypic And Phenotypic Differences Distinguishing Lactobacillus Jensenii And Lactobacillus Mulieris, Adriana Ene, Swarnali Banerjee, Alan J. Wolfe, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

Lactobacillus crispatus, Lactobacillus gasseri, Lactobacillus iners, and Lactobacillus jensenii are dominant species of the urogenital microbiota. Prior studies suggest that these Lactobacillus species play a significant role in the urobiome of healthy females. In our prior genomic analysis of all publicly available L. jensenii and Lactobacillus mulieris genomes at the time (n = 43), we identified genes unique to these two closely related species. This motivated our further exploration here into their genotypic differences as well as into their phenotypic differences. First, we expanded genome sequence representatives of both species to 61 strains, including publicly available …

Tree-Based Unidirectional Neural Networks For Low-Power Computer Vision, Abhinav Goel, Caleb Tung, Nick Eliopoulos, Amy Wang, Jamie C. Davis, George K. Thiruvathukal, Yung-Hisang Lu

Computer Science: Faculty Publications and Other Works

This article describes the novel Tree-based Unidirectional Neural Network (TRUNK) architecture. This architecture improves computer vision efficiency by using a hierarchy of multiple shallow Convolutional Neural Networks (CNNs), instead of a single very deep CNN. We demonstrate this architecture’s versatility in performing different computer vision tasks efficiently on embedded devices. Across various computer vision tasks, the TRUNK architecture consumes 65% less energy and requires 50% less memory than representative low-power CNN architectures, e.g., MobileNet v2, when deployed on the NVIDIA Jetson Nano.

Assessing The Impact Of A Csforall Research-Practice Partnership Using The Prosper Framework: A Case Study Of The Chicago Alliance For Equity In Computer Science (Cafécs), Erin Henrick, Steven Mcgee, Ronald I. Greenberg, Dale Reed, Don Yanek, Lucia Dettori, Haley Williamson

Computer Science: Faculty Publications and Other Works

The Chicago Alliance for Equity in Computer Science (CAFÉCS) Research Practice Partnership (RPP) has been working for more than a decade towards their mission to engage in research and development that enables Chicago Public Schools (CPS) to ensure that all students in Chicago participate in engaging, relevant, and rigorous computing experiences, increase opportunities for all students to pursue computing pathways and prepare all students for the future of work. The partnership engaged in an iterative design process to develop a framework for understanding the areas of RPP impact on a district. This paper applies the PROSPER framework to the CAFÉCS …

Carborane-Containing Hydroxamate Mmp Ligands For The Treatment Of Tumors Using Boron Neutron Capture Therapy (Bnct): Efficacy Without Tumor Cell Entry, Sebastian Flieger, Mao Takagaki, Natsuko Kondo, Marlon Lutz Jr., Yash Gupta, Hiroki Ueda, Yoshinori Sakurai, Graham Moran, Prakasha Kempaiah, Narayan Hosmane, Minoru Suzuki, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

New carborane-bearing hydroxamate matrix metalloproteinase (MMP) ligands have been synthesized for boron neutron capture therapy (BNCT) with nanomolar potency against MMP-2, -9 and -13. New analogs are based on MMP inhibitor CGS-23023A, and two previously reported MMP ligands 1 (B1) and 2 (B2) were studied in vitro for BNCT activity. The boronated MMP ligands 1 and 2 showed high in vitro tumoricidal effects in an in vitro BNCT assay, exhibiting IC₅₀ values for 1 and 2 of 2.04 × 10⁻² mg/mL and 2.67 × 10⁻² mg/mL, respectively. The relative killing effect of 1 to L-boronophenylalanine (BPA) is …

Conversations With Chatgpt About C Programming: An Ongoing Study, James C. Davis, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

AI (Artificial Intelligence) Generative Models have attracted great attention in recent years. Generative models can be used to create new articles, visual arts, music composition, even computer programs from English specifications. Among all generative models, ChatGPT is becoming one of the most well-known since its public announcement in November 2022. GPT means {\it Generative Pre-trained Transformer}. ChatGPT is an online program that can interact with human users in text formats and is able to answer questions in many topics, including computer programming. Many computer programmers, including students and professionals, are considering the use of ChatGPT as an aid. The quality …

In Silico Binding Of 2-Aminocyclobutanones To Sars-Cov-2 Nsp13 Helicase And Demonstration Of Antiviral Activity, Thahani S. Habeeb Mohammad, Yash Gupta, Cory T. Reidl, Vlad Nicolaescu, Haley Gula, Ravi Durvasula, Prakasha Kempaiah, Daniel P. Becker Ph.D.

Chemistry: Faculty Publications and Other Works

The landscape of viral strains and lineages of SARS-CoV-2 keeps changing and is currently dominated by Delta and Omicron variants. Members of the latest Omicron variants, including BA.1, are showing a high level of immune evasion, and Omicron has become a prominent variant circulating globally. In our search for versatile medicinal chemistry scaffolds, we prepared a library of substituted α-aminocyclobutanones from an α-aminocyclobutanone synthon (11). We performed an in silico screen of this actual chemical library as well as other virtual 2-aminocyclobutanone analogs against seven SARS-CoV-2 nonstructural proteins to identify potential drug leads against SARS-CoV-2, and more broadly against coronavirus …

Observing Human Mobility Internationally During Covid-19, Shane Allcroft, Mohammed Metwaly, Zachery Berg, Isha Ghodgaonkar, Fischer Bordwell, Xinxin Zhao, Xinglei Liu, Jiahao Xu, Subhankar Chakraborty, Vishnu Banna, Akhil Chinnakotla, Abhinav Goel, Caleb Tung, Gore Kao, Wei Zakharov, David A. Shoham, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

This article analyzes visual data captured from five countries and three U.S. states to evaluate the effectiveness of lockdown policies for reducing the spread of COVID-19. The main challenge is the scale: nearly six million images are analyzed to observe how people respond to the policy changes.

Neutrino Forces In Neutrino Backgrounds, Mitrajyoti Ghosh, Yuval Grossman, Walter Tangarife, Xun-Jie Xu, Bingrong Yu

Physics: Faculty Publications and Other Works

The Standard Model predicts a long-range force, proportional to G² F /r⁵, between fermions due to the exchange of a pair of neutrinos. This quantum force is feeble and has not been observed yet. In this paper, we compute this force in the presence of neutrino backgrounds, both for isotropic and directional background neutrinos. We find that for the case of directional background the force can have a 1/r dependence and it can be significantly enhanced compared to the vacuum case. In particular, background effects caused by reactor, solar, and supernova neutrinos enhance the force by many …

When Plaquing Is Not Possible: Computational Methods For Detecting Induced Phages, Taylor Miller-Ensminger, Genevieve Johnson, Swarnali Banerjee, Catherine Putonti

Mathematics and Statistics: Faculty Publications and Other Works

High-throughput sequencing of microbial communities has uncovered a large, diverse population of phages. Frequently, phages found are integrated into their bacterial host genome. Distinguishing between phages in their integrated (lysogenic) and unintegrated (lytic) stage can provide insight into how phages shape bacterial communities. Here we present the Prophage Induction Estimator (PIE) to identify induced phages in genomic and metagenomic sequences. PIE takes raw sequencing reads and phage sequence predictions, performs read quality control, read assembly, and calculation of phage and non-phage sequence abundance and completeness. The distribution of abundances for non-phage sequences is used to predict induced phages with statistical …

Poster: Userland Containers For Mobile Systems, Isaac Ahlgren, Victor Rakotondranoro, Yasin N. Silva, Eric Chan-Tin, George K. Thiruvathukal, Neil Klingensmith

Computer Science: Faculty Publications and Other Works

Mobile platforms are not rising to their potential as ubiquitous computers, in large part because of the constraints we impose on their apps in the name of security. Mobile operating systems have long struggled with the challenge of isolating untrusted apps. In pursuit of a secure runtime environment, Android and iOS isolate apps inside a gulag of platform-imposed programming languages and runtime libraries, leaving few design decisions to the application developers. These thick layers of custom software eschew app portability and maintainability, as development teams must continually tweak their apps to support modifications to the OS's runtime libraries. Nonstandard and …

Filling In The Gaps: A Multiple Imputation Approach To Estimating Aging Curves In Baseball, Quang Nguyen, Gregory J. Matthews

Mathematics and Statistics: Faculty Publications and Other Works

In sports, an aging curve depicts the relationship between average performance and age in athletes' careers. This paper investigates the aging curves for offensive players in the Major League Baseball. We study this problem in a missing data context and account for different types of dropouts of baseball players during their careers. In particular, the performance metric associated with the missing seasons is imputed using a multiple imputation model for multilevel data, and the aging curves are constructed based on the imputed datasets. We first perform a simulation study to evaluate the effects of different dropout mechanisms on the estimation …

Snapshot Metrics Are Not Enough: Analyzing Software Repositories With Longitudinal Metrics, Nicholas Synovic, Matt Hyattt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Software metrics capture information about software development processes and products. These metrics support decision-making, e.g., in team management or dependency selection. However, existing metrics tools measure only a snapshot of a software project. Little attention has been given to enabling engineers to reason about metric trends over time -- longitudinal metrics that give insight about process, not just product. In this work, we present PRiME (PRocess MEtrics), a tool for computing and visualizing process metrics. The currently-supported metrics include productivity, issue density, issue spoilage, and bus factor. We illustrate the value of longitudinal data and conclude with a research agenda. …

Evolution Of Winning Solutions In The 2021 Low-Power Computer Vision Challenge, Xiao Hu, Ziteng Jiao, Ayden Kocher, Zhenyu Wu, Junjie Liu, James C. Davis, George K. Thiruvathukal, Yung-Hsiang Lu

Computer Science: Faculty Publications and Other Works

Mobile and embedded devices are becoming ubiquitous. Applications such as rescue with autonomous robots and event analysis on traffic cameras rely on devices with limited power supply and computational sources. Thus, the demand for efficient computer vision algorithms increases. Since 2015, we have organized the IEEE Low-Power Computer Vision Challenge to advance the state of the art in low-power computer vision. We describe the competition organizing details including the challenge design, the reference solution, the dataset, the referee system, and the evolution of the solutions from two winning teams. We examine the winning teams’ development patterns and design decisions, focusing …

Creating Data From Unstructured Text With Context Rule Assisted Machine Learning (Craml), Stephen Meisenbacher, Peter Norlander

School of Business: Faculty Publications and Other Works

Popular approaches to building data from unstructured text come with limitations, such as scalability, interpretability, replicability, and real-world applicability. These can be overcome with Context Rule Assisted Machine Learning (CRAML), a method and no-code suite of software tools that builds structured, labeled datasets which are accurate and reproducible. CRAML enables domain experts to access uncommon constructs within a document corpus in a low-resource, transparent, and flexible manner. CRAML produces document-level datasets for quantitative research and makes qualitative classification schemes scalable over large volumes of text. We demonstrate that the method is useful for bibliographic analysis, transparent analysis of proprietary data, …

College Teaching And Ai, Leo Irakliotis

Computer Science: Faculty Publications and Other Works

Artificial Intelligence will reshape the way we assess student learning in ways that no one has prepared us for.