Digital Commons Network^™

The Enthalpy Of Formation Of Acetylenes And Aromatic Nitro Compounds For A Group Contribution Method With “Chemical Accuracy”, R. J. Meier, Paul R. Rablen

Chemistry & Biochemistry Faculty Works

In this paper we provide the Group Contribution parameters for acetylenes and aromatic nitro compounds fitting with a recently developed Group Contribution method with chemical accuracy (1 kcal/mol) for the heat of formation of organics. These additional parameters widen the applicability of the Group Contribution method. We also provide further G4 quantum calculated values as reference when no experimental data are available and compare to previously reported G4 data.

An Seir Model On Time Scales With Discrete Applications To Tuberculosis, E. Akın, G. Yeni, D. Konur, S. R. Işık, M. R. Işık

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we propose a novel dynamical model on time scales consisting of new parameters to investigate the transmission dynamics of tuberculosis (TB), one of the deadliest infectious diseases worldwide, characterized by a long latency stage. The dynamical TB model, governed by the Susceptible–Exposed–Infected–Recovered (SEIR) framework within a unified form, yields a continuous model with a non-saturated incidence rate on the real numbers and discrete models with saturated incidence rates when different time domains are chosen. We analyze the stability of the equilibrium points of both the continuous TB model on the set of real numbers and the discrete …

Evaluating The Effectiveness Of Ai Text Humanising Tools In Reducing Ai Detection In Ai-Generated Texts By Ai Detectors, Samuel Nicodemus Epaphras, Fredrick Mtenzi

Institute for Educational Development, East Africa

The use of Generative Artificial Intelligence (AI) tools, such as Gemini and ChatGPT,  is  on  the  rise,  and  it  has  revolutionised  content  generation  in professional and academic domains. However, their increasing sophistication presents challenges in distinguishing AI-generated texts from human-written ones,  raising  concerns  about  integrity,  especially  in  academic  writing.  This study   evaluated   the   effectiveness   of   three   AI   text   humanising   tools: Writesonic, QuillBot paraphraser, and WriteHuman in refining texts generated by ChatGPT and  Gemini.  The study employed  a  comparative  experimental design.  By  employing  quantitative  analysis,  the  study  compares  baseline  AI detection    rates    with    those    after    successive    humanisation    iterations. Comparison  was  also …

South Carolina Middle School Student Performance In Ela And Mathematics: The Imperative Of Assessment For Learning, Olivia S. Ochoo

South Carolina Association for Middle Level Education Journal

Despite broad access to middle school in South Carolina, recent SCReady assessment data indicate persistent literacy and numeracy achievement gaps, with so many students performing below grade level in English Language Arts (ELA) and mathematics. This article evaluated five years of state- and district-level data, highlighting steady but small gains, and explored how current assessment practices failed to fully inform instruction to accelerate learning. This paper used a mixed-methods research design, particularly a convergent parallel mixed-methods design, in which both qualitative and quantitative approaches were used to collect and analyze data. To be specific, document analysis and both open- and …

An Odd Protocol For An Agent-Based Model Of Hepatitis C Virus Transmission With Inter- And Intra-Group Structural And Behavioural Heterogeneous Syringe-Sharing Networks (5), Seun Ale, Que Nguyen Dr., John D. Kelleher Prof., Elizabeth Hunter Dr.

Reports

The model described in this ODD is an agent-based model of hepatitis C virus (HCV) transmission among people who inject drugs (PWID). The model incorporates structural heterogeneity through a three-group interaction framework and behavioural heterogeneity through group-specific syringe-sharing rates with additional intra-group variability. The syringe-sharing population in the model is divided into core, inner, and outer circle groups representing individuals with high, moderate, and low levels of syringe-sharing interaction intensity, respectively. In addition to differences in the number of daily interaction opportunities across groups, agents in each group are assigned syringe-sharing probabilities that vary at the individual level around their …

Identifying Priorities To Guide Extension Water Quality Programming In Utah, Clare Entwistle, Sarah Erwin, Stephanie Vaughn

Outcomes and Impact Quarterly

Utah State University Extension water quality faculty conducted a statewide water quality needs assessment to identify priority contaminants and resource gaps. The results found that elevated nutrient levels and sedimentation were the top concerns where additional resources would be beneficial. In addition, insufficient funding for improvements and low public engagement were identified as key challenges in addressing water quality issues. Results revealed current unmet needs with regional variation to inform Extension resource allocation and programming.

On Signifiable Computability: Part Iii: A Note On Unnameable Functions On Natural Numbers, Vladimir A. Kulyukin

Computer Science Faculty and Staff Publications

A writing system 𝔚 on an alphabet 𝒜 is a tuple (ℜ,𝔐), where ℜ is a finite set of text formation rules and 𝔐 is a finite rule application mechanism that generates texts on 𝒜. A natural writing system forms natural language texts on an alphabet such as Sanskrit on Devanagari. An artificial writing system generates formal language texts on an alphabet such as Lisp on Unicode. Let ℕ ={0,1,2,…} be the set of natural numbers. A function on natural numbers 𝑓 :ℕ^𝑘 ↦ ℕ, 0 < 𝑘 ∈ ℕ, is nameable by a writing system on an alphabet if, and only if, the system can generate a text on the alphabet that names f and no other function. We show that there exist functions on natural numbers unnameable in principle in that they cannot be named by any writing system on any alphabet. Our results imply the following computability-theoretic hierarchy of functions on natural numbers: computable ⊊ partially computable ⊊ nameable ⊊ 𝔉, where 𝔉 is the set of functions on ℕ.

Introducing The Aasspectq Framework: A New Typology For Assessing Quality, Pedagogy, Outcomes, And Learning In Micro-Credentials, Felix Quayson

Journal of Research Initiatives

Micro-credentials have gained increasing attention as a flexible and competency-based approach to bridging the gap between formal education and workforce demands. Unlike traditional qualifications and degrees, micro-credentials focus on discrete, demonstrable skills that can be rapidly developed, assessed, and recognized across industries. I proposed the Auditing, Avoidance, Specificity, Skills, Personalization, Efficiency, Competency, Technology, and Quality Assurance (AASSPECTQ) conceptual framework to examine the current state of micro-credential implementation, highlighting the tools, learning outcomes, and assessment instruments necessary for effective program design. The challenges of quality assurance, portability, and recognition that continue to limit widespread adoption were also explored. By …

In Vitro Pharmacological Evaluation Of Novel Cmpi Derivatives As Selective Positive Allosteric Modulators Of The Alpha4 Beta2 Nicotinic Acetylcholine Receptor, Josue Gaona, Nataly Sanchez, Wilder Felix, Nathalia Menegasso, Brisa Cea, Ganesh Thakur, Ayman K. Hamouda

School of Medicine Student Publications and Presentations

Nicotinic acetylcholine receptors (nAChRs) contribute to the pathogenesis of neurodegenerative diseases such as Parkinson’s disease (PD), where degeneration of dopaminergic and cholinergic neurons disrupts neurotransmission. The (α4)₃(β2)₂ nAChR subtype is expressed on affected neuronal populations and represents a promising therapeutic target. Positive allosteric modulators (PAMs) may enhance receptor function while preserving endogenous signaling. We evaluated chemical derivatives of CMPI [3-(2-chlorophenyl)-5-(5-methyl-1-(piperidin-4-yl)-1H-pyrazol-4-yl)isoxazol] as selective PAMs of (α4)₃(β2)₂ nAChRs. Two-electrode voltage-clamp recordings were performed in Xenopus laevis oocytes expressing defined receptor stoichiometries to assess potentiation and generate dose–response curves. Cytotoxicity was assessed in HEK cells using the MTT assay. Substitutions at the pyrazole …

Using Ensemble Disagreement To Stabilize Conformal Prediction Under Distribution Shift, Patrick D. Murphy

Master's Theses

Semantic segmentation of eelgrass from drone imagery is crucial for coastal habitat monitoring, restoration, and management, as these habitats continue to see rapid changes due to climate change and human influence. However, the reliability of generalizing a deployed classification model relies on both high-accuracy segmentation as well as robust uncertainty quantification that holds up when conditions change over years or locations. Conformal prediction (CP) is a method that converts a classifier's output into prediction sets with a guaranteed average coverage level for in-distribution data. However, the “vanilla” conformal score can often under-cover in hard or out-of-distribution (OOD) regions under drift. …

Neurosymbolic Counterpoint Generation, Paul D. Jarski

Master's Theses

Recent advancements in generative artificial intelligence have revolutionized music generation, yet research has predominantly focused on raw audio synthesis over music in symbolic form, i.e. a score. This thesis presents the first neurosymbolic model designed to generate imitative Renaissance counterpoint in symbolic (MIDI) format. By leveraging an autoregressive Transformer architecture, this research explores the capacity of deep learning models to manage independent voices and strict stylistic constraints.

We compare multiple data representation strategies with distinct tokenization methods. The proposed model incorporates a symbolic component that enforces fundamental contrapuntal rules. Additionally, this thesis contributes a preprocessed dataset of Renaissance polyphony, in …

Improving Gene Isoform Quantification With Miniquant., Haoran Li, Dingjie Wang, Qi Gao, Puwen Tan, Yunhao Wang, Xiaoyu Cai, Aifu Li, Yue Zhao, Andrew L Thurman, Seyed Amir Malekpour, Ying Zhang, Roberta Sala, Andrea Cipriano, Chia-Lin Wei, Vittorio Sebastiano, Chi Song, Nancy R Zhang, Kin Fai Au

Faculty Research 2026

RNA sequencing has been widely applied for gene isoform quantification, but limitations exist in quantifying isoforms of complex genes accurately, especially for short reads. Here we identify genes that are difficult to quantify accurately with short reads and illustrate the information benefit of using long reads to quantify these regions. We present miniQuant, which ranks genes with quantification errors caused by the ambiguity of read alignments and integrates the complementary strengths of long reads and short reads with optimal combination in a gene- and data-specific manner to achieve more accurate quantification. These results are supported by rigorous mathematical proofs, validated …

Meta-Analysis Of Genetic Mapping Studies In Mice Reveals Candidate Epilepsy Modifier Genes That Are Outside The Current Drug Development Landscape., Giovanna L Durante, Anna L. Tyler, Rod C Scott, Amanda E Hernan, J Matthew Mahoney

Faculty Research 2026

OBJECTIVE: Despite decades of development in anti-seizure medications, ~30% of individuals remain refractory to all treatments, and none of the existing therapies are disease modifying. Identifying targets outside the current preclinical paradigm is critically important. This study aimed to characterize the landscape of current epilepsy treatments at the level of gene interaction networks and identify novel genetic modifiers of epilepsy as potential novel therapeutic targets.

METHODS: We performed a functional network analysis to score genes based on their interactions with known epilepsy genes, and we integrated these functional scores with population genetics data and drug tractability information. In parallel, we …

Argument-Based Consistency In Toxicity Explanations Of Llms, Ramaravind K. Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, Shion Guha

Health Services and Informatics Research

The discourse around toxicity and LLMs in NLP largely revolves around detection tasks. This work shifts the focus to evaluating LLMs’ reasoning about toxicity—from their explanations that justify a stance—to enhance their trustworthiness in downstream tasks. Despite extensive research on explainability, it is not straightforward to adopt existing methods to evaluate free-form toxicity explanation due to their over-reliance on input text perturbations, among other challenges. To account for these, we propose a novel, theoretically-grounded multi-dimensional criterion, Argument-based Consistency (ArC), that measures the extent to which LLMs’ free-form toxicity explanations reflect an ideal and logical argumentation process. Based on uncertainty quantification, …

Delegation And Verification Under Ai, Lingxiao Huang, Wenyang Xiao, Nisheeth K. Vishnoi

Cowles Foundation Discussion Papers

As AI systems enter institutional workflows, workers must decide whether to delegate task execution to AI and how much effort to invest in verifying AI outputs, while institutions evaluate workers using outcome-based standards that may misalign with workers’ private costs. We model delegation and verification as the solution to a rational worker’s optimization problem, and define worker quality by evaluating an institution-centered utility (distinct from the worker’s objective) at the resulting optimal action. We formally characterize optimal worker workflows and show that AI induces phase transitions, where arbitrarily small differences in verification ability lead to sharply different behaviors. As a …

First Proof Solutions And Comments, Mohammed Abouzaid, Andrew J. Blumberg, Martin Hairer, Joe Kileel, Tamara G. Kolda, Paul D. Nelson, Daniel Spielman, Nikhil Srivastava, Rachel Ward, Shmuel Weinberger, Lauren Williams

Cowles Foundation Discussion Papers

Here we provide our solutions to the First Proof questions. We also discuss the best responses from publicly available AI systems that we were able to obtain in our experiments prior to the release of the problems on February 5, 2025. We hope this discussion will help readers with the relevant domain expertise to assess such responses.

Mainstreaming Mistrust: The Shift In Us Vaccine Policy Under The Trump Administration, Sanjin Musa, Amy Estlund, Megan A. Berman

Faculty Scholarship

Department of Health and Human Services led by Robert F. Kennedy Jr., represents a significant departure from long-standing public health norms. This commentary explores how historically marginalized anti-vaccine activism has moved into the mainstream of government oversight. Key actions driving this transition include the wholesale replacement of the Advisory Committee on Immunization Practices, the departure of senior CDC officials, and the public questioning of established childhood immunization schedules. Furthermore, the administration has ceased financial support for global health entities like the World Health Organization and Gavi, the Vaccine Alliance, while canceling funding for innovative mRNA vaccine platforms. 

These domestic policy …

Meta-Analysis Of Genetic Mapping Studies In Mice Reveals Candidate Epilepsy Modifier Genes That Are Outside The Current Drug Development Landscape., Giovanna L Durante, Anna L. Tyler, Rod C Scott, Amanda E Hernan, J Matthew Mahoney

Faculty Research 2026

OBJECTIVE: Despite decades of development in anti-seizure medications, ~30% of individuals remain refractory to all treatments, and none of the existing therapies are disease modifying. Identifying targets outside the current preclinical paradigm is critically important. This study aimed to characterize the landscape of current epilepsy treatments at the level of gene interaction networks and identify novel genetic modifiers of epilepsy as potential novel therapeutic targets.

METHODS: We performed a functional network analysis to score genes based on their interactions with known epilepsy genes, and we integrated these functional scores with population genetics data and drug tractability information. In parallel, we …

Improving Gene Isoform Quantification With Miniquant., Haoran Li, Dingjie Wang, Qi Gao, Puwen Tan, Yunhao Wang, Xiaoyu Cai, Aifu Li, Yue Zhao, Andrew L Thurman, Seyed Amir Malekpour, Ying Zhang, Roberta Sala, Andrea Cipriano, Chia-Lin Wei, Vittorio Sebastiano, Chi Song, Nancy R Zhang, Kin Fai Au

Faculty Research 2026

RNA sequencing has been widely applied for gene isoform quantification, but limitations exist in quantifying isoforms of complex genes accurately, especially for short reads. Here we identify genes that are difficult to quantify accurately with short reads and illustrate the information benefit of using long reads to quantify these regions. We present miniQuant, which ranks genes with quantification errors caused by the ambiguity of read alignments and integrates the complementary strengths of long reads and short reads with optimal combination in a gene- and data-specific manner to achieve more accurate quantification. These results are supported by rigorous mathematical proofs, validated …

College Of Natural Sciences 2025 Year-End Publication, College Of Natural Sciences

College of Natural Sciences Newsletters and Reports

Page 2 Dean's Message 
Page 3 Department Highlights 
Page 4 One Day for State 
Page 5 Ice cores reveal volcanic eruptions in 13th century 
Page 5 How do our cells interpret stress 
Page 6-7 Faculty Excellence
Page 8 New chemical biology consortium will accelerate cancer research
Page 9 SDSU to combat crop disease, biofilms in new NSF-back project 
Page 9 Science as Art Competition 
Page 10-11 Student Excellence  
Page 12 SDSU researcher developing natural alternative to synthetic dyes
Page 12 Browning Retired
Page 13 Quantum technologies through NSF-backed project
Page 13 NASA Funds CNS Development of Model
Page 14 GGS …

A Mineralogical And Geochemical Characterization Of The Amo Meteorite, Karinn Johnson '27, Kenneth Brown, Chad Byers, Thomas Grier

Annual Student Research Poster Session

Meteorites provide a wealth of information about solar system evolution, planetary formation and differentiation, and provide clues to the origins of water and life on Earth. On December 10th, 2024 (4:04 EST), a meteor fall was observed approximately 50 km west of Indianapolis, over the small town of Amo, Indiana (Hendricks County). Several pieces of the meteor ranging from about 1g to >60kg were recovered. A local Greencastle, IN resident collected a 1451.3g sample, of which a 7.5g piece was donated to DePauw University for detailed textural, mineralogical, and geochemical characterization using stereomicroscopy, scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), …

Pointwise Self-Homeomorphic Generalized Inverse Limits, Ali H. Ali, Faruq A. Mena, Robert Paul Roe

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we find uncountable families of generalized inverse sequences on intervals, where the bonding functions consist of a finite number of line segments, such that the inverse limit spaces of these sequences are pointwise self-homeomorphic continua. We give several examples of pointwise self-homeomorphic continua obtained in this manner including the dendrite D3 and a dendrite containing Dω. The dendrite D3 was obtained previously, by others, as a generalized inverse limit but the bonding function in that example contained infinitely many line segments. We show that the techniques we use on intervals can be extended to inverse limits where …

Behind The Black Box: Employer Accountability For Algorithmic Hiring Bias, Nicole Capp

The Business, Entrepreneurship & Tax Law Review

AI hiring tools are now ubiquitous in employment, promising efficiency, cost savings, and reduced human bias. Yet these systems often operate as “black boxes,” replicating or amplifying existing biases and raising significant legal concerns under Title VII of the Civil Rights Act of 1964. Even without discriminatory intent, AI trained on historical hiring data can produce disparate impacts, exposing employers to liability for outcomes they cannot fully understand or explain. Plaintiffs face steep challenges in litigating such claims, particularly in identifying specific practices, demonstrating causation, and proposing feasible alternatives. This article examines how AI perpetuates discrimination in hiring, analyzes the …

An Odd Protocol For An Agent-Based Model Of Hepatitis C Virus Transmission In A Two-Group Structural Heterogeneous Syringe-Sharing Network (M2), Seun Ale, Que Nguyen Dr., John D. Kelleher Prof., Elizabeth Hunter Dr.

Reports

The model described in this ODD is an agent-based model of hepatitis C virus (HCV) transmission among people who inject drugs (PWID). The model extended a baseline homogeneous model by incorporating structural heterogeneity via a two-group interaction framework. The syringe-sharing population in the model is divided into inner and outer circle groups representing individuals with differing levels of syringe-sharing interaction intensity. While all agents share the same syringe-sharing probability and epidemiological processes remain identical across agents, the number of daily interaction opportunities differs between the two groups. Interactions in the model are generated dynamically using proximity-based sampling at each timestep …

An Odd Protocol For An Agent-Based Model Of Hepatitis C Virus Transmission In A Three-Group Structural Heterogeneous Syringe-Sharing Network (M3), Seun Ale, Que Nguyen Dr., John D. Kelleher Prof., Elizabeth Hunter Dr.

Reports

The model described in this ODD is an agent-based model of hepatitis C virus (HCV) transmission among people who inject drugs (PWID). The model incorporates structural heterogeneity through a three-group interaction framework. The syringe-sharing population in the model is divided into core, inner, and outer circle groups representing individuals with high, moderate, and low levels of syringe-sharing interaction intensity, respectively. While the syringe-sharing rate and all epidemiological processes remain identical across agents, the number of daily interaction opportunities differs by agent grouping, capturing variation in structural position within the syringe-sharing network. Interactions are generated dynamically using proximity-based sampling at each …

Stem Day At Andrews University Engages Adventist Educators, Andrew Francis

Lake Union Herald

No abstract provided.

Financial Data Security In The Quantum Age: Evaluating The Effectiveness Of The Gramm-Leach-Bliley Act's Safeguards Rule, Shivan Moodley

North Carolina Banking Institute

No abstract provided.

The Illusion Of Causality In Llms: A Developmentally Grounded Analysis Of Semantic Scaffolding And Benchmark–Capability Mismatches, Daisuke Akiba

Publications and Research

Recent benchmarks increasingly report that large language models (LLMs) exhibit human-like causal reasoning abilities, including counterfactual inference and intervention planning. However, many such evaluations rely on domains that are heavily represented in training data and embed strong semantic cues, raising the possibility that apparent causal competence may reflect semantic pattern recombination rather than structure-sensitive causal reasoning. Drawing on human developmental theories of causal induction, this perspective argues that genuine causal understanding requires robustness to novelty and reliance on conditional structure rather than semantic familiarity. To illustrate the testability of this claim, the paper includes a pilot demonstration using synthetic causal …

Selecting Without Replacement From A Population Of Bands Of Serially Connected Objects, James E. Marengo, Dominick Banasik, Joseph Voelkel, David L. Farnsworth

Articles

The sampling procedure from a finite population of objects that are serially attached into bands is described and analyzed. One object is randomly selected and removed at a time, which results in that object’s band being broken into two bands or shortened by one object. The main result gives the probability of choosing an object that is part of a band of serially connected objects of any specified size at each stage of the selection process.

Inequality As Market Failure, Erick J. Sam

William & Mary Bill of Rights Journal

This Article explores economic, philosophical, and legal relationships between economic inequality and market failure, and it draws on these linkages to develop an innovative normative justification and alternative constitutional basis for a levy on wealth.

The Article’s central analytic result is that several general mechanisms responsible for common market failures can also systematically produce economic inequalities whenever preferences against extreme inequality are fairly widespread. Because these mechanisms satisfy both the ‘process-based’ and ‘outcome-based’ criteria of market failure, redistributive transfers designed to reduce these inequalities would be normatively justified under the widely accepted market failure theory of government action. On this …