Digital Commons Network^™

Isolation Of Bovine Milk-Derived Exosomes Via A Polyester Capillary- Channeled Polymer (C-Cp) Fiber Stationary Phase, Jerisa Pimentel, Carolina Mata, R. Kenneth Marcus

Chemistry Summer Research Program

No abstract provided.

Competency-Based Personnel Selection Oklahoma - Key Findings, Quality Improvement Center For Workforce Development

Other QIC-WD Products

Background

The QIC-WD began working with Oklahoma Human Services (OKDHS) in 2017. At that time OKDHS had an average turnover rate of 25% among Child Welfare Specialist (CWS) I and IIs. Agency leaders expressed a desire to better understand turnover rates with an eye toward increasing the retention of more competent performers. A thorough needs assessment led to the decision to design and implement a competency-based personnel selection intervention to address inconsistencies in hiring and better identify candidates with the desired competencies to be hired as a CWS. The evaluation was designed to include an implementation evaluation; a validation …

Improved Logical Reasoning Of Language Models Via Differentiable Symbolic Programming, Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric Xing

Machine Learning Faculty Publications

Pre-trained large language models (LMs) struggle to perform logical reasoning reliably despite advances in scale and compositionality. In this work, we tackle this challenge through the lens of symbolic programming. We propose DSR-LM, a Differentiable Symbolic Reasoning framework where pre-trained LMs govern the perception of factual knowledge, and a symbolic module performs deductive reasoning. In contrast to works that rely on hand-crafted logic rules, our differentiable symbolic reasoning framework efficiently learns weighted rules and applies semantic loss to further improve LMs. DSR-LM is scalable, interpretable, and allows easy integration of prior knowledge, thereby supporting extensive symbolic programming to robustly derive …

Bertnet: Harvesting Knowledge Graphs With Arbitrary Relations From Pretrained Language Models, Shibo Hao, Bowen Tan, Kaiwen Tang, Bin Ni, Xiyan Shao, Hengzhe Zhang, Eric P. Xing, Zhiting Hu

Machine Learning Faculty Publications

It is crucial to automatically construct knowledge graphs (KGs) of diverse new relations to support knowledge discovery and broad applications. Previous KG construction methods, based on either crowdsourcing or text mining, are often limited to a small predefined set of relations due to manual cost or restrictions in text corpus. Recent research proposed to use pretrained language models (LMs) as implicit knowledge bases that accept knowledge queries with prompts. Yet, the implicit knowledge lacks many desirable properties of a full-scale symbolic KG, such as easy access, navigation, editing, and quality assurance. In this paper, we propose a new approach of …

Phase-Aware Adversarial Defense For Improving Adversarial Robustness, Dawei Zhou, Nannan Wang, Heng Yang, Xinbo Gao, Tongliang Liu

Machine Learning Faculty Publications

Deep neural networks have been found to be vulnerable to adversarial noise. Recent works show that exploring the impact of adversarial noise on intrinsic components of data can help improve adversarial robustness. However, the pattern closely related to human perception has not been deeply studied. In this paper, inspired by the cognitive science, we investigate the interference of adversarial noise from the perspective of image phase, and find ordinarily-trained models lack enough robustness against phase-level perturbations. Motivated by this, we propose a joint adversarial defense method: a phase-level adversarial training mechanism to enhance the adversarial robustness on the phase pattern; …

High-Probability Bounds For Stochastic Optimization And Variational Inequalities: The Case Of Unbounded Variance, Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel Dvurechensky, Alexander Gasnikov, Peter Richtárik

Machine Learning Faculty Publications

During recent years the interest of optimization and machine learning communities in high-probability convergence of stochastic optimization methods has been growing. One of the main reasons for this is that high-probability complexity bounds are more accurate and less studied than in-expectation ones. However, SOTA high-probability non-asymptotic convergence results are derived under strong assumptions such as the boundedness of the gradient noise variance or of the objective's gradient itself. In this paper, we propose several algorithms with high-probability convergence results under less restrictive assumptions. In particular, we derive new high-probability convergence results under the assumption that the gradient/operator noise has bounded …

Analysis Of Predictive Performance And Reliability Of Classifiers For Quality Assessment Of Medical Evidence Revealed Important Variation By Medical Area, Simon Šuster, Timothy Baldwin, Karin Verspoor

Natural Language Processing Faculty Publications

Objectives: A major obstacle in deployment of models for automated quality assessment is their reliability. To analyze their calibration and selective classification performance. Study Design and Setting: We examine two systems for assessing the quality of medical evidence, EvidenceGRADEr and RobotReviewer, both developed from Cochrane Database of Systematic Reviews (CDSR) to measure strength of bodies of evidence and risk of bias (RoB) of individual studies, respectively. We report their calibration error and Brier scores, present their reliability diagrams, and analyze the risk–coverage trade-off in selective classification. Results: The models are reasonably well calibrated on most quality criteria (expected calibration error …

Bertastic At Semeval-2023 Task 3: Fine-Tuning Pretrained Multilingual Transformers – Does Order Matter?, Tarek Mahmoud, Preslav Nakov

Natural Language Processing Faculty Publications

The naïve approach for fine-tuning pretrained deep learning models on downstream tasks involves feeding them mini-batches of randomly sampled data. In this paper, we propose a more elaborate method for fine-tuning Pretrained Multilingual Transformers (PMTs) on multilingual data. Inspired by the success of curriculum learning approaches, we investigate the significance of fine-tuning PMTs on multilingual data in a sequential fashion language by language. Unlike the curriculum learning paradigm where the model is presented with increasingly complex examples, we do not adopt a notion of “easy” and “hard” samples. Instead, our experiments draw insight from psychological findings on how the human …

Conformal Prediction For Federated Uncertainty Quantification Under Label Shift, Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov

Machine Learning Faculty Publications

Federated Learning (FL) is a machine learning framework where many clients collaboratively train models while keeping the training data decentralized. Despite recent advances in FL, the uncertainty quantification topic (UQ) remains partially addressed. Among UQ methods, conformal prediction (CP) approaches provides distribution-free guarantees under minimal assumptions. We develop a new federated conformal prediction method based on quantile regression and take into account privacy constraints. This method takes advantage of importance weighting to effectively address the label shift between agents and provides theoretical guarantees for both valid coverage of the prediction sets and differential privacy. Extensive experimental studies demonstrate that this …

Interprofessional Collaboration At The Pacific Speech, Hearing, And Language Center, Ashlyn Emberley

Occupational Therapy Student Capstones

No abstract provided.

Creating The Pathway To Participation In Adaptive Recreation, Katie White

Occupational Therapy Student Capstones

No abstract provided.

A Holistic Approach To Resources For The Military And Veteran Student Center, Simrandeep Singh

Occupational Therapy Student Capstones

No abstract provided.

Enhancing Lifelong Learning & Wellness Programs For Older Adults, Hannah Gantuangco

Occupational Therapy Student Capstones

No abstract provided.

Uncovering The Spatio-Temporal Impact Of The Covid-19 Pandemic On Shared E-Scooter Usage: A Spatial Panel Model, Farzana Mehzabin Tuli, Arna Nishita Nithila, Suman Mitra

Civil Engineering Faculty Publications and Presentations

This study examines the spatio-temporal effects of the COVID-19 pandemic on shared e-scooter usage by leveraging two years (2019 and 2020) of daily shared micromobility data from Austin, Texas. We employed a series of random effects spatial-autoregressive model with a spatially autocorrelated error (SAC) to examine the differences and similarities in determinants of e-scooter usage during regular and pandemic periods and to identify factors contributing to the changes in e-scooter use during the Pandemic. Model results provided strong evidence of spatial autocorrelation in the e-scooter trip data and found a spatial negative spillover effect in the 2020 model. The key …

Ukraine’S Supreme Court: Born Amid Crisis, Now Under Siege, Sergii Koziakov, David Collins

Judicature International

No abstract provided.

The ‘Temple Of The Holy Spirit’ & Christian Identity: Old Testament Echoes In 1 Corinthians, Sr. Amata Christi Lippert O.P.

Theology Graduate Theses

No abstract provided.

A Fault In Democracy: The Disenfranchisement Of Voters, Kylie Cooper, Razan Elsir

Library Award for Outstanding Undergraduate Research

Our project is focused on why there is variation in felon disenfranchisement policy among states. After selecting five different states (New York, Mississippi, Virginia, North Carolina, and Vermont) with various policies, we tested them against our different hypotheses: demographics (age, education level, and the number of people incarcerated), partisanship, and race. We expected race to be a strong factor, meaning that as diversity of the state increased the strictness of its felon disenfranchisement policy would increase. We expected to see a similar correlation with partisanship, that the more Republican-leaning states would have stricter policies. Additionally, we believed that age, education, …

Swing With Me, Daniel Kyle

IPS/BAS 495 Undergraduate Capstone Projects

This is my Capstone Project for IPS introducing my business plan for Swing with Me, a country swing dance business me and my girlfriend Chelsea are going to start here in Ontario!

Capstone 2023: The Bond Of Learning, Mckinzee D. Goodwin

IPS/BAS 495 Undergraduate Capstone Projects

The learning that is done between the ages of 2-5 years old provides for lifelong learning. Basic knowledge of the alphabet, numbers, and colors used to be expected before a child steps foot into the public school setting, however as time has passed children have been increasingly behind in those steps. A recent study found that for every ten children that arrive at kindergarten each fall only four of them are prepared. Those six who are not prepared struggle in a continuous catch-up cycle (Livingstone, 2015). My capstone project was to show others who might be worried about the readiness …

A Statistical Framework For Automating Resonance Detection: Modelling Pion Proton Collision Activity, Shahnaz Abdul Hameed

2023 REYES Proceedings

In this paper, we analyze π− − p elastic collision data from the Particle Data Group (PDG), by creating a general framework to study resonance activity: automating peak detection, extrapolating, parametrizing thresholds, filtering resonances and further comparing and extracting characteristics, to identify Delta (Δ) baryons. We then analyse experimental Energy vs Phase-Shift (δ) data for the collision π+ +π− → π− +π+, model the T matrix from a curve fitted polynomial representation of the K⁻¹ matrix, simulate its Riemann sheets and analyse it to identify the characteristics of ρ⁰(770) meson, as well as estimate their uncertainties. …

Invited Review: Adrenocortical Function In Avian And Non-Avian Reptiles: Insights From Dispersed Adrenocortical Cells., Rocco V. Carsia, Patrick J. Mcilroy, Henry B John-Alder

Rowan-Virtua School of Osteopathic Medicine Departmental Research

Herein we review our work involving dispersed adrenocortical cells from several lizard species: the Eastern Fence Lizard (Sceloporus undulatus), Yarrow's Spiny Lizard (Sceloporus jarrovii), Striped Plateau Lizard (Sceloporus virgatus) and the Yucatán Banded Gecko (Coleonyx elegans). Early work demonstrated changes in steroidogenic function of adrenocortical cells derived from adult S. undulatus associated with seasonal interactions with sex. However, new information suggests that both sexes operate within the same steroidogenic budget over season. The observed sex effect was further explored in orchiectomized and ovariectomized lizards, some supported with exogenous testosterone. Overall, a suppressive effect of testosterone was evident, especially in cells …

Why The West Should Help China Reduce Unrecognized And Preventable Covid-19 Deaths, George A. Gellert

Journal of Health Ethics

In an era marked by a ruinous war between a democratic state and a totalitarian regime, political volatility, rightward looking isolationism and nationalism, and heightened competition and disputes between China and the West, it is perhaps difficult to discern why the West should supply China with COVID-19 vaccines and therapeutics, as well as epidemiological assistance in order to mitigate a potentially unrecognized COVID-19 crisis in that nation. This commentary considers three arguments against Western and international indifference to the plight of China as it transitions to COVID-19 endemicity.

How To Best Retrain A Neural Network If We Added One More Input Variable, Saeid Tizpaz-Niari, Vladik Kreinovich

Departmental Technical Reports (CS)

Often, once we have trained a neural network to estimate the value of a quantity y based on the available values of inputs x1, ..., xn, we learn to measure the values of an additional quantity that have some influence on y. In such situations, it is desirable to re-train the neural network, so that it will be able to take this extra value into account. A straightforward idea is to add a new input to the first layer and to update all the weights based on the patterns that include the values of the new input. The problem with …

Topological Explanation Of Why Complex Numbers Are Needed In Quantum Physics, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

In quantum computing, we only use states in which all amplitudes are real numbers. So why do we need complex numbers with non-zero imaginary part in quantum physics in general? In this paper, we provide a simple topological explanation for this need, explanation based on the Second Law of Thermodynamics.

Effects Of Preservation By Ethanol On Δ13C And Δ15N Of Three Tissues Of The Critically Endangered European Eel Anguilla Anguilla, Rose M. Boardman, Adrian C. Pinder, Adam T. Piper, Roberts C Gutmann, Rosalind M. Wright, John Robert Britton

More Faculty of Science and Engineering Research

The temporal effects of ethanol preservation on the δ13C and δ15N values of tissues excised from European eel Anguilla anguilla were assessed. Preservation significantly enriched 13C values of fin and mucus but not dorsal muscle. The 13C enrichment occurred in the initial 15 days of preservation and was independent of initial eel mass. Tissue preservation effects on δ15N values were negligible. These tissue-specific isotopic shifts should be considered when ethanol-preserved eel samples are used.

The Appropriateness Of Outlier Exclusion Approaches Depends On The Expected Contamination: Commentary On André (2022), Daniel Villanova

Marketing Faculty Publications and Presentations

In a recent article, André (2022) addressed the decision to exclude outliers using a threshold across conditions or within conditions and offered a clear recommendation to avoid within-conditions exclusions because of the possibility for large false-positive inflation. In this commentary, I note that André’s simulations did not include the situation for which within-conditions exclusion has previously been recommended—when across-conditions exclusion would exacerbate selection bias. Examining test performance in this situation confirms the recommendation for within-conditions exclusion in such a circumstance. Critically, the suitability of exclusion criteria must be considered in relationship to assumptions about data-generating mechanisms.

Playing The Long Game: The Role Of International Courts And Tribunals In The Russo-Ukrainian War, Paul W. Grimm, Kim Scheppele, Paul Stephan, Harold Hongju Koh, Oleksandra Matviichuk

Judicature International

No abstract provided.

On The Blow Up Criterion For The 3d Nematic Liquid Crystal Flows Involving The Second Eigenvalue Of The Deformation Tensor, Ines Ben Omrane

Applied Mathematics & Information Sciences

In this paper, we study the blow up criterion of the smooth solutions to the three-dimensional incompressible nematic liquid crystal flows in terms of $\lambda _{2}^{+}$ in the multiplier space $\dot{X}_{1}$ and $\nabla d$ in $BMO$. It is shown that the solution $(u,d)$ can be extended beyond $t=T$ if 􏰖 T  􏰇􏰇 λ + ( · , t ) 􏰇􏰇 2 2   2 X ̇ 1 + ∥ ∇ d ( · , t ) ∥ B M O  d t < ∞ . 0 ln(e+∥∇u(·,t)∥X ̇1) ln(e+∥∇d(·,t)∥BMO)

Duality In A Class Of Vector Ko ̈ The-Orlicz Spaces, Mohamed Ahmed Sidaty

Applied Mathematics & Information Sciences

We deal with a complete normed space $E$, a scalar sequence space $\lambda$, and an Orlicz mapping $M$ to introduce and study some properties of the spaces $\lambda_M\{E\}$ of all $E-$valued sequences that are absolutely $(\lambda, M)$-summable. Denote by $\lambda_M\{E\}_{r}$ the subspace of $\lambda_M\{E\}$ whose elements are AK-sequences. We describe the continuous linear forms on this space in term of $E^*-$valued sequences that are absolutely $(\lambda^*, N)$-summable, where $N$ is the Orlicz mapping complement of $M$.

Spectrum Of A Perturbed Harmonic Oscillator, K. Dosmagulova, B. Kanguzhin, Z. Fazullin

Applied Mathematics & Information Sciences

In this article the spectrum of a perturbed harmonic oscillator is calculated. New correctly solvable boundary value problems are used for the corresponding harmonic oscillator on a two-dimensional punctured sphere. The eigenfunctions of the harmonic oscillator are studied in detail and a set of elements from the obtained functionals is introduced.