Digital Commons Network^™

Cloud-Managed System For Distributing Audio Content To Point-Of-Sale Devices, Ramprasad S, Gulmohar Khan, Ankul Batra, Gajen Agrawal, Malay Singh, Saurabh Mimani, Ajay Prasad, Venu Annamraju, Sailendra Bathi

Defensive Publications Series

The utility for merchants of point-of-sale (POS) audio devices can be expanded beyond announcing transaction details. A cloud-managed system can facilitate the creation and distribution of custom audio content to these devices. For example, a user can input text through a client application, which can be sent to a cloud backend. The backend can use services, such as generative artificial intelligence for content refinement and a text-to-speech engine, to generate an audio file. The backend can then orchestrate the distribution of the audio file and an associated playback schedule to one or more endpoint audio devices. This system can expand …

Dissecting The Efficacy And Immunogenicity Of Tlr7 Agonist–Antibody Conjugates Through The Lens Of Fc Effector Function, Conjugation Strategies, And Linker Cleavability, Siteng Fang, Samantha R. Benjamin, Lina Wu, Mohammad Asikur Rahman, Kayla K. Elder, Victor T. Ojo, Tao Zhang, Tracy A. Brooks, L. Nathan Tumey

Pharmacy Faculty Scholarship

The advent of immuno-oncology therapeutics has given rise to antibody-drug conjugates (ADC) designed to selectively activate pattern recognition receptors such as Toll-Like Receptors (TLRs). In contrast to classical ADC technology, these Immune Stimulating Antibody Conjugates (ISACs) are widely reported to rely on Fcγ-mediated uptake and noncleavable linkers. Herein, we systematically study the impact of Fc effector function, linker cleavability, and conjugation strategy on the efficacy and immunogenicity of a series of TLR7 agonist-based ISACs. We demonstrate that the combination of FcγR-ablation and incorporation of a cleavable linker results in increased stimulation of myeloid cells, enhanced efficacy, and improved tolerability as …

Innovation Curse: The Wastefulness Of Technologies Believed To Mitigate Climate Change, Minh Hoang Nguyen, Valoree Gagnon, Thanh Tu Tran, Thi Mai Anh Tran

Michigan Tech Publications

Technological innovations are increasingly promoted as solutions to climate change. However, many innovations, including Carbon Capture and Storage, bioplastics, and glacier geo-engineering, suffer significant limitations from high costs, speculative efficacy, and adverse ecological consequences. Using Granular Interaction Thinking Theory (GITT), a transdisciplinary framework grounded in information theory, quantum mechanics, and mindsponge theory, in this study, we explain how such technological innovations become systemically favored despite their flaws. We introduce the concept of the “innovation curse,” which arises when institutional and cognitive filtering systems, operating under high informational entropy, default to familiar but ineffective techno-solutions while marginalizing Indigenous and Local Knowledges …

A Detailed Investigation Into Word-Order In The Modification Of Pronouns, Kelli Hesseltine, Joseph C. M. Davis

Publications and Research

This study builds upon Hesseltine and Davis ([2020]. “The Communicative Function of Adjective-Noun Order in English.” WORD 66 (3): 166–193. https://doi.org/10.1080/00437956.2020.1793499), which examines word order in modification in English and proposes the Assertion of Characterization hypothesis. To communicate an assertion of an entity’s traits, speakers employ two different meanings: weaker, signaled by the order AB as in long (A) hair (B), and stronger, signaled by BA as in hair (B) long (A). The attribution of the characterization is thus made less or more assertively. This work focuses on examples where the characterized entity, the B, is a form traditionally …

Mark Munsell Named Distinguished Fellow Of Artificial Intelligence, Lindenwood University

Archived Lindenwood Press Releases

No abstract provided.

Deconstructing The Black Box: An Explainability Analysis Of Deep Learning Architectures In Cytopathology, Chase A. Garrett

Master's Theses or Doctor of Nursing Practice

Deep learning shows strong potential in medical-image analysis, yet adoption in cyptopathology remains limited. Cytopathology could benefit from deep learning applications by improving diagnostic efficiency and accuracy. However deep learning comes with a notorious “black box” that keeps the models from being transparent and trustworthy for widespread clinical adoption. We conducted a comprehensive and comparative analysis of several deep learning architectures for multi-class classification of acute leukemia types, ALL, AML, and normal healthy cells from peripheral blood smear images. The models in this research include a Vision Transformer (ViT) and a diverse selection of Convolutional Neural Network (CNN) models. The …

Characterization Of Antiretroviral Therapy (Art) Adherence Phenotypes And Psychosocial Symptom Clusters Among Black/African American (Aa) And Hispanic/Latine Adolescents And Young Adults (Ayas) With Hiv In The Adherence Connection For Counseling, Education, And Support (Access-Ii) Trial, Ann-Margaret Navarra, Taehoon Ha, Eva Liang, Maurade Gormley, David R. Garcia, Jason Fletcher, Lloyd A. Goldsamt, Michael G. Rosenberg, Karin Hasegawa, Jie Yang

School of Nursing Faculty Publications

Antiretroviral therapy (ART) adherence behavior is heterogeneous among adolescents and young adults (AYAs) with HIV and influenced by individual and interpersonal psychosocial factors. The primary objective of this study is to characterize ART adherence phenotypes and psychosocial symptom clusters, as related to ART adherence and HIV viral load suppression. This analysis included 60 AYAs with HIV enrolled in an ART adherence support clinical trial. Self-reported ART adherence at baseline, 12-weeks, and 24-weeks was used to define four ART adherence phenotypes: consistently high adherence (YY), early-only adherence (YN), late-only adherence (NY), and consistently low adherence (NN). Symptom clusters were empirically derived …

Flow Control Tactics For Photovoltaic Modules: Coherent Structure And Heat Shedding Amplification, Sarah Elizabeth Smith

Dissertations and Theses

Solar photovoltaic systems have become the fastest growing renewable technology in the last several years. However, large-scale systems are at the mercy of their external environments, where extreme heating and wind-flung debris impact their efficiency and useable life. The work in this dissertation presents studies aimed to both understand and mitigate for these effects by identifying the underlying physics which govern them. Exploring flow control as a tactic to combat environmental heating, collective work discusses the role of turbulent fluid dynamics within large-scale systems as pertains to convective heat transfer, turbulent structure formation, and particle-laden environments. Wind tunnel experiments on …

Advanced Deep Neural Network Architectures For 3d Gait Assessment From Video In The Early Detection Of Alzheimers Disease, Abhishek Singh Kushwaha

Electronic Theses and Dissertations 2020 - Present

This thesis presents an advanced deep learning framework for markerless 3D gait assessment using monocular video, aimed at the early detection of Alzheimer’s disease (AD). Recognizing gait abnormalities as potential preclinical biomarkers, the study leverages video-based human pose estimation to derive detailed spatiotemporal gait parameters without the need for specialized laboratory equipment. The proposed system adapts the MeTRAbs (Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation) architecture to reconstruct metric-scale 3D human joint coordinates from RGB video recordings. A complete processing pipeline is developed to extract stride length, cadence, stance and swing phases, and gait variability, validated against the …

Node-Attributed Spatial Graph Partitioning: A Kullback-Leibler Divergence Based Approach, Valentin Nechita

Electronic Theses and Dissertations 2020 - Present

This thesis presents a novel approach to node-attributed spatial graph partitioning (NSGP) that addresses limitations in existing homogeneity measures. We introduce a Kullback-Leibler (KL) divergence-based formulation we name KLD that measures attribute similarity by comparing each node’s distribution to its subgraph centroid, providing a computationally efficient method of measuring homogeneity. Integrated within a multilevel graph partitioning framework and Fiduccia-Mattheyses refinement, our approach achieves approximately 90% runtime reduction compared to the baseline Clustering and Local Refinement (CLR) algorithm while maintaining comparable partition quality. Applied to COVID-19 infection data combined with American Community Survey demographics across U.S. FIPS codes, KLD successfully identifies …

Archaeology As Alternative Prison Education, Jayne Price Dr, Caroline Pudney Dr

Journal of Prison Education Research

This paper presents the educational focused outcomes of a set of workshops entitled 'Introduction to Archaeology’ that were delivered within a prison. The workshops were delivered as part of a project that seeks to explore the pro-social benefits and social capital (i.e. social and structural aspects that support positive identity formation) that could be developed through engagement with archaeology, specifically for those within the criminal justice system. The workshops offered a bespoke, alternative, educational offering within an adult male prison in Wales. It was designed and delivered by an archaeologist who has an established background in the field, especially in …

Healthlitpro™: Development Of An Ai Driven Audit & Feedback Tool For Organizational Health Literacy, Carol J. Howe, Yunhe Feng, Song Fu, Donger Chen, Lindsey Patton

2025

RESEARCH

Purpose: Organizational Health Literacy (OHL) refers to the ability of healthcare institutions to support patients and families to access, understand, and use health information. Nurses play a key role in OHL using evidence-based health literacy practices (i.e. plain language, teach-back, open-ended questions, chunking information, and three to five key points) when educating patient families. Yet, implementation is challenging. Audit and Feedback (A&F) is an implementation strategy for promoting fidelity to health literacy practices. Conventionally requiring expert human evaluations that are costly, labor-intensive, and difficult to scale.

Methods: HealthLit was trained using a dataset of simulated nurse-patient education …

Development And Applications Of A Health Equity Summary Score Using The Medical Expenditure Panel Survey, Ronald R. Sanchez

Dissertations and Theses

Despite sustained national efforts, disparities in healthcare delivery persist among racial and ethnic minorities, low-income individuals, and socially at-risk populations. Monitoring modifiable aspects of care delivery, such as the structures and processes that health systems can directly improve, is a key strategy for addressing these gaps. However, most measures evaluate modifiable aspects of care delivery separately, limiting understanding of how improvements in one domain reinforce the other and how their combined effect influences equitable care.

This dissertation addresses this gap by combining patient experience and clinical quality, two modifiable aspects of care that captures how patients interact with the health …

High-Throughput Screens Identify Genotype-Specific Therapeutics For Channelopathies, Christian L. Egly, Alex Shen, Tri Q. Do, Carlos Tellet Cabiya, Paxton A. Ritschel, Suah Woo, Matthew Ku, Brian P. Delisle, Brett M. Kroncke, Björn C. Knollmann

Physiology Faculty Publications

Genetic diseases such as ion channelopathies substantially burden human health. Existing treatments are limited and not genotype specific. Here, we report a 2-step high-throughput approach to rapidly identify drug candidates for repurposing as genotype-specific therapy. We first screened 1,680 medicines using a thallium-flux trafficking assay against Kv11.1 gene variants causing long QT syndrome (LQTS), an ion channelopathy associated with fatal cardiac arrhythmia. We identified evacetrapib as a suitable drug candidate that improves membrane trafficking and activates channels. We then used deep mutational scanning to prospectively identify all Kv11.1 missense variants in an LQTS hotspot region responsive to treatment with evacetrapib. …

Tesla's Forced Middleman: Why Modernization In The Automobile Industry Requires Louisiana To Revise Its Direct Sales Law, John Brainard

Louisiana Law Review

No abstract provided.

Diffog: Differentiable Policy Trajectory Optimization With Generalizability, Zhengtong Xu, Zichen Miao, Qiang Qiu, Zhe Zhang, Yu She

School of Industrial Engineering Faculty Publications

Imitation-learning-based visuomotor policies excel at manipulation tasks but often produce suboptimal action trajectories compared to model-based methods. Directly mapping camera data to actions via neural networks can result in jerky motions and difficulties in meeting critical constraints, compromising safety and robustness in real-world deployment. For tasks that require high robustness or strict adherence to constraints, ensuring trajectory quality is crucial. However, the lack of interpretability in neural networks makes it challenging to generate constraint-compliant actions in a controlled manner. This article introduces differentiable policy trajectory optimization with generalizability (DiffOG), a learning-based trajectory optimization framework designed to enhance visuomotor policies. By …

On Iterative Method For The Solution Of Non-Linear Equations Using Anti-Lobatto Four Point Quadrature Rule, Tusar Singh, Dwiti Krushna Behera

Baghdad Science Journal

By harnessing the classic anti-Lobatto four-point quadrature rule of degree of precision three, the order of convergence of the Newton-Raphson method has been profoundly enhanced. This newly developed iterative scheme reveals a remarkable order of convergence, reaching three and far surpassing the original Newton-Raphson method. It operates as a two-step iterative method that elevates Newton’s approach by integrating the quadrature rule. A theorem related to this innovative iterative method has been formulated, confirming that its order of convergence is indeed three. In the numerical computation section, insightful scenarios demonstrate the remarkable numerical efficiency of the new method. Through the power …

Efficient Face Mask Recognition Model Based On Deep Learning And Multi-Machine Learning Classifiers, Hassenien Ali Hussein, Firas Muneam Bachay, Saffa Jasim Mosa, Mohammed Hasan Abdulameer

Baghdad Science Journal

Safety in chemical and biological laboratories requires face masks. Nevertheless, the masked face images present obstacles to accommodate the wide pose variations, low resolution, changes in size and incomplete cropping, and varying emotive expressions, making feature extraction and recognition robust difficult. To decern between faces with proper, improper, and no facemask, Deep Learning (the use of Convolutional Neural Networks (CNNs)) and classifiers such as SoftMax, Support Vector Machines (SVM) and K-Nearest Neighbors (KNN) were used. The methodology utilized the 2075 AR face images that contain various resolutions, orientations, and occlusions. The paper develops a Deep Learning-based model utilizing CNNs and …

Transformer Network On Global Self-Attention Mechanism For Brain Tumor Segmentation, Ammar Awni Abbas Baghdadi, Mohammed Al-Mukhtar, Ammar S Al-Zubaidi

Baghdad Science Journal

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as …

Next Word Prediction In Social Media Texts For Punjabi-English Bilingual Users With Sequential Cnn-Bilstm, Gurpreet Singh, C P Kamboj

Baghdad Science Journal

Preparing a collection of Punjabi-English social media text and creating a next word prediction system for Punjabi users are the main goals of this study. As the Gurmukhi script has a large character set, typing in Punjabi takes a lot of time. That is the reason behind using the Roman script for communication on social media platforms like WhatsApp, Facebook, and Twitter by many Punjabi users. For such users, we have proposed a sequential CNN-BiLSTM architecture to provide suggestions to improve typing speed and make communication convenient. In our proposed model, we used 128 filters and a kernel size of …

Enhancing Secrecy Rate For Cognitive Radio Based On 5g Communication Systems, Mohammed Kadim Shaybeth Al-Jorani, Hakem Beitollahi

Baghdad Science Journal

The non-orthogonal multiple accesses (NOMA) together with Cognitive radio network (CRN) are critical frameworks in the 5G remote transmission framework. Nonetheless, the framework is an outstanding method for the cognitive clients to get a telecommunication from the interference signals in different info numerous yield (MIMO)- NOMA-relied cognitive radio network. For here project, a modern beamforming strategy is introduced for getting a data trade inside similar units as well as adjoining units about every tempering client. The intervention is brought about through a blemished range detecting of the optional clients (SUs). The SUs is expected to get to the essential communication …

Black On Black Sounds: Music, Migration, And The ‘Nu-K Blak’ Identity Formation In Early 21st Century Britain, Monique Charles

Sociology Faculty Articles and Research

Examining literature on the under researched areas of Afrobeats and African migration to Britain, this article identifies significant internal shifts in the ethnic diversity of Black Britain —i.e., from Caribbean (predominantly Jamaican) to West African (Nigerian, Ghanaian) (ONS 2011). Interpreting literature and applying to the British context, it highlights how Afrobeats reshapes Blackness in Britain, particularly the incorporation of desirable Africanness through Afrobeats music. It argues that demographic and musical shifts in Britain result in a renegotiation of the Caribbean and US dominant 20th century Black Britishness — ‘UK Blak’ identity (as identified by Bradley 2013, Gilroy 1993 & Palmer …

Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud

Faculty Articles

Hybrid energy storage systems (HESS) integrating batteries and supercapacitors offer a promising solution to overcome the limitations of battery-only architectures in electric vehicles (EVs). By leveraging the high energy density of batteries and the high power density of supercapacitors, HESS can enhance power delivery, improve energy efficiency, and extend battery lifespan. The effectiveness of HESS, however, is largely determined by the energy management system (EMS) that coordinates power flow under dynamic driving conditions. Unlike existing reviews, this work addresses common gaps in the literature, including the lack of industrial energy storage component examples, limited coverage of recently developed EMS strategies, …

Stiefel Md Anderson Oropharynx Cancer (Mda-Opc) Cohort: A Single-Institution, Prospective Longitudinal Outcomes Study, Amy Moreno, Ariana J Sahli, Faye Johnson, Xiaowen Sun, Carly Barbon, Waree Rinsurongkawong, Wenye Song, Flavie M Luciani, Han Liang, Jun Li, Wei Liu, J Jack Lee, S J Frank, Stephen Lai, Clifton Fuller, Katherine Hutcheson

Faculty, Staff and Student Publications

Purpose: The MD Anderson Oropharynx Cancer (MDA-OPC) cohort is a unique single-institution, prospective longitudinal cancer cohort. The cohort aims to enhance the therapeutic index of OPC management by supporting data needs for independent investigators to conduct rigorous observational studies examining exposures and factors associated with acute and late toxicities, cancer progression, recurrence, new malignancies and quality of life in OPC survivors.

Participants: A total of 1811 patients with OPC with a minimum follow-up of 6 months have been consented to our prospective registry between 18 March 2015 and 29 December 2023. Clinical and treatment (Tx) data are available on all …

Mycobacterium Chelonae Outbreak Investigation At A Quaternary Pediatric Hospital Following The Opening Of A Leed-Certified Critical Care Tower: Where Does Water Sustainability Intersect With Infection Control?, Andrea L Ankrum, Silvia M Caceres, Michael Torsell, Elaine Epperson, Vinicius Calado Nogueira De Moura, Jennifer J Gilick, Michael Strong, Qingyun Liu, Matthew J Strand, Rachel N Wilsey, Jennifer R Honda, Jane E Gross, Felicia A Scaggs-Huang

Faculty, Staff and Student Publications

Objective: Investigate the increased incidence of Mycobacterium chelonae positive respiratory cultures in hospitalized patients.

Design: Apply the Healthcare-Associated Links in Transmission of Nontuberculous Mycobacteria (HALT NTM) toolkit to an outbreak investigation of M. chelonae.

Setting: Quaternary-care pediatric hospital and medical center in the United States with a recently opened LEED-certified critical care tower.

Patients: Adult and pediatric patients with M. chelonae positive respiratory cultures between June 2022 and January 2024.

Methods: An epidemiological investigation involving clinical and laboratory practices, water management, building construction and renovation projects. Environmental sampling of air vents, water sources and endoscope reprocessing equipment was performed. M. …

Naphthalimide-Based Type-I Nano-Photosensitizers For Enhanced Antitumor Photodynamic Therapy: H2s Synergistically Regulates Pet And Self-Assembly, Huiyu Niu, Songnan Wang, Yang Liu, Nana Ma, Shuaiwei Cheng, Beidou Feng, Hyunsun Jeong, Yonggang Yang, Ge Wang, Tony D James, Juyoung Yoon, Jonathan L Sessler, Hua Zhang

Faculty, Staff and Student Publications

Photodynamic therapy (PDT) relies on a combination of light and photosensitizers (PSs) to achieve local control over cancerous lesions. However, it is subject to limitations, including tumor hypoxia, low tumor targeting, off‐target phototoxicity, and always‐on fluorescence. Here, we propose a design strategy for activated nano‐PSs (N‐PSs) to simultaneously overcome the limitations of PDT, wherein photoinduced electron transfer (PeT) is coupled with an endogenous H2S‐regulated self‐association process to promote Type‐I photochemical reactions. Using theoretical calculations, spectral analysis, and microscopic imaging, we verified the generation of self‐assembly and occurrence of PeT. And it was also shown that H2S could synergistically inhibit the …

The Global Hypophosphatasia Registry: Lessons Learned From A Decade Of Real-World Data., Priya S. Kishnani, Lothar Seefried, Keiichi Ozono, Gabriel Ángel Martos-Moreno, Cheryl Rockman-Greenberg, Deborah Fowler, Luke K. Burke, William R. Mowrey, Eric T. Rush, Peter R. Ebeling, Wolfgang Högler, Agnès Linglart, Shona Fang, Anna Petryk, Kathryn M. Dahir

Manuscripts, Articles, Book Chapters and Other Papers

INTRODUCTION: Hypophosphatasia (HPP) is an inherited, metabolic, rare disease characterized by a high level of clinical heterogeneity. In response to this robust heterogeneity, the Global HPP Registry was formed to characterize the types of manifestations that patients may experience, as well as to compile information on genetic underpinnings of the disease, overall impact on patient quality of life, and safety and effectiveness of enzyme replacement therapy. The objective of this review was to synthesize key learnings gained from the Global HPP Registry, which is now in its tenth year of enrolling patients.

METHODS: Registry data were analyzed to provide up-to-date …

Modified Artificial Neural Networks In Stochastic Differential Equations To Estimate The Occurrence Rate Of A New Process For Software Reliability Growth Modelling, Adel Sufyan Hussain, Zedan Zubair Mashikhin, Noora Taha Abduirazzaq

Baghdad Science Journal

This paper aims to utilize modified artificial neural networks under stochastic differential equations to improve the estimation of occurrence rates on models towards the growth of software reliability through such models. There has never been a time when reliable assessment methods have been more important as software systems grow ever more sophisticated. This study covers the risks arising from software bugs, security weaknesses, and the need to meet legal requirements. The authors use a new method that combines artificial intelligence techniques with classical reliability models to achieve their goal of a more efficient computational tool for predicting software reliability. It …

Regulating Privacy Policies On Digital Platforms, Michele Bisceglia, Alessandro Bonatti, Fiona Scott Morton

Cowles Foundation Discussion Papers

We study how privacy regulation affects menu pricing by a monopolist platform that collects and monetizes personal data. Consumers differ in privacy valuation and sophistication: naive users ignore privacy losses, while sophisticated users internalize them. The platform designs prices and data collection options to screen users. Without regulation, privacy allocations are distorted and naive users are exploited. Regulation through privacy-protecting defaults can create a market for information by inducing payments for data; hard caps on data collection protect naive users but may restrict efficient data trade.

South Carolina Reemployment Services And Eligibility Assessments (Resea) Randomized Controlled Trial Design Report, Gabrielle Pepin, Ethan Jenkins, Christopher J. O'Leary, Aaron Sojourner

Upjohn Institute Technical Reports

No abstract provided.