Digital Commons Network^™

Ion-Dna Interactions As A Key Determinant Of Uracil Dna Glycosylase Activity., Sharon N Greenwood, Alexis N Dispensa, Matthew Wang, Justin R Bauer, Timothy D Vaden, Zhiwei Liu, Brian P Weiser

Rowan-Virtua School of Osteopathic Medicine Departmental Research

Because of their ubiquitous presence, ions interact with numerous macromolecules in the cell and affect critical biological processes. Here, we discuss how cations including Mg²⁺ alter the enzymatic activity of a DNA glycosylase by tuning its affinity for DNA. The response of uracil DNA glycosylase (UNG2) to Mg²⁺ ions in solution is biphasic and paradoxical, where low concentrations of the ion stimulate the enzyme, but high concentrations inhibit the enzyme. We analyzed this phenomenon by modeling experimental data with a statistical framework that we empirically derived to understand molecular systems that display biphasic behaviors. Parameters from our statistical …

Ciccolella, Peg Oral History Interview, Margaret E. Ciccolella, Gene Pearson

Emeriti Society Oral History Collection

Peg Ciccolella (1985-2024) Professor of Health and Exercise Science.

Health and Exercise Science program development and change, Pacific Legal Scholars program development, chairing of and involvement in Pacific committees, chairing of health and exercise science department, the law and application to health sciences, research and publishing at Pacific, WASC accreditation, change and application of Title IX.

Functionalizing Polyethersulfone Membranes: Using Nmr To Avoid Pitfalls When Using Uv-Induced Polymerization To 'Graft From' Surfaces, Priyanka Suresh, Megan M. Sibley, Amy C. Che, Christine E. Duval

Faculty Scholarship

For nearly 30 years, UV-induced free radical polymerization has been used to modify the surface chemistry of polyethersulfone (PES) membranes, films, and coatings. The initial mechanism for the grafting process was introduced in the 1990s and supported without direct evidence of covalent bond formation. Since then, claims of ‘grafting from’ membranes in the literature rely on similar evidence using a combination of gravimetry, attenuated total reflectance infrared spectroscopy, contact angle goniometry, water sorption, and/or water permeance. While these techniques provide evidence of the presence of a polymer coating, they do not provide direct evidence of covalent bond formation between the …

Effect Of Anesthesia And Diurnal Variation On Chronic Vagus Nerve Activity In Rats, Bhanu P. Kotamraju, Grant A. Mccallum, Dominique M. Durand

Faculty Scholarship

The vagus nerve, serving as a pivotal link between the brain and vital organs, regulates crucial physiological functions. It plays a central role in maintaining homeostasis within the body and must dynamically adapt to changing conditions such as anesthesia or sleep. While vagal tone, typically estimated indirectly from heart rate variability, has been extensively studied, direct measurement of vagal activity during sleep and anesthesia remains unreported to date. Recent technological advancements have facilitated the recording of vagus nerve activity in freely moving rodents using small, highly flexible carbon nanotube yarns. Consequently, it is now feasible to directly investigate vagal activity …

Research On Grey-Box Modeling Method Of Digital Twins For Cantilever Structure, Wenjia Zhang, Heming Zhang

Journal of System Simulation

Abstract: The construction of accurate and highly real-time digital twin models in complex industrial setting presents several challenges. Traditional model construction approaches based only on mechanism or data show certain limitations. Therefore, this study is based on the idea of grey-box modeling, taking the cantilever structure within a boom-type roadheader as the object, and proposes a novel modeling approach that combines the characteristics of the mechanism model and introduces a self-attention mechanism. This method performs grayscale transformation on the original input and splices it with physical features to achieve organic fusion of mechanism information, which not only enhances the expressiveness …

An Extended Image Features Based Uncalibrated Visual Servoing Method, Shuzhen Zhang, Yukun Cheng, Yangbo Liu, Fusheng Zha

Journal of System Simulation

Abstract: Aiming at the traditional uncalibrated visual servo relying on the estimation of image Jacobi matrix and the coupling of the motion of each degree of freedom of the camera, on the basis of imagebased uncalibrated visual servo, an extended image features based uncalibrated visual servo method is proposed. By analyzing the relationship between image features and camera frames change in the visual servoing process, the visual servoing process in the image space is decomposed into four basic processes: translation, stretching, rotation and scaling; by analyzing the changing of image features in the visual servoing process, extended image features are …

A Modeling And Simulation Method For Firepower Intelligent Decision-Making Of Directed Energy System Basedon Joint Dqn, Changhong Qu, Junjie Wang, Kun Wang, Qingyong Cui, Jiangyang Chen, Xinpeng Wang

Journal of System Simulation

Abstract: In order to solve the problem of dynamically addressing firepower intelligent decision-making in anti-UAV cluster combat using a directed energy system, a deep reinforcement learning model is established. Based on the high multi-agent state and action space dimensions of this model, a modeling and simulation method of firepower intelligent decision-making of directed energy system based on joint deep Q network (DQN) is proposed. The state space is constructed from the state of directed energy system, UAV cluster and the directed energy system deployment area. The joint mechanism is used to share the state information of each equipment and the …

Histone Methyltransferase Ash1l Primes Metastases And Metabolic Reprogramming Of Macrophages In The Bone Niche, Chenling Meng, Kevin Lin, Wei Shi, Hongqi Teng, Xinhai Wan, Anna Debruine, Yin Wang, Xin Liang, Javier Leo, Feiyu Chen, Qianlin Gu, Jie Zhang, Vivien Van, Kiersten L Maldonado, Boyi Gan, Li Ma, Yue Lu, Di Zhao

Faculty, Staff and Student Publications

Bone metastasis is a major cause of cancer death; however, the epigenetic determinants driving this process remain elusive. Here, we report that histone methyltransferase ASH1L is genetically amplified and is required for bone metastasis in men with prostate cancer. ASH1L rewires histone methylations and cooperates with HIF-1α to induce pro-metastatic transcriptome in invading cancer cells, resulting in monocyte differentiation into lipid-associated macrophage (LA-TAM) and enhancing their pro-tumoral phenotype in the metastatic bone niche. We identified IGF-2 as a direct target of ASH1L/HIF-1α and mediates LA-TAMs' differentiation and phenotypic changes by reprogramming oxidative phosphorylation. Pharmacologic inhibition of the ASH1L-HIF-1α-macrophages axis elicits …

Ultimate Limit State Reliability-Based Approach Life Prediction Of An Existing Frame Structure Under Seismic Hazard In Indonesia, Wira Herucakra, Luh Putri Adnyani

Journal of Materials Exploration and Findings

Life assessment integrated with Structural Integrity Management (SIM) has been implemented in the oil and gas industry for the past decade to maintain the integrity and safety of an in-service structure used to support hydrocarbon exploration, production, and processing activity. Current structural life assessment, as ruled by the American Petroleum Institute (API), uses a fatigue-based approach for offshore structures subjected to wave loading. As the general principle of SIM is not limited to offshore structures, this study offers an alternative life assessment method for onshore structures, especially steel frame structures subjected to earthquake loads. Reliability analysis, combined with the effect …

Structural Analysis Of Biochar Derived From Pruning Residues Gasification, Iván Calderón-Gutiérrez, Michell Ortiz, Farid Chejne, Mauricio Cotte, Juan-Carlos Maya, Carlos-Mario Ceballos

Bio-Char IV

Please click Additional Files below to see the full abstract

Linking Bacterial Adsorption To Local Biochar Morphology And Production Conditions By X-Ray Nanotomography, Meredith Barr, Daniel Yazdanipour, Francesco Iacoviello, Rhodri Jervis

Bio-Char IV

Please click Additional Files below to see the full abstract

Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif

Electrical Engineering

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)-based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure …

Adaptive Multi-Scale Feature Pyramid Network For Occlusion Pedestrian Detection, Huaping Zhou, Tao Wu, Kelei Sun

Journal of System Simulation

Abstract: To address the issue of current pedestrian detectors, which struggle to extract complete features in occlusion-heavy environments and consequently have low detection accuracy. A novel adaptive multiscale feature pyramid network is proposed. A multi-scale feature enhancement module (MFEM) is developed. It captures the visible area of pedestrians at different scales through a multi-branch network with different receptive fields. An AFM (adaptive fusion module) is proposed. It calculates the importance of different pixels by optimizing the mean variance at the spatial and feature levels. It enhances the texture and semantic features of pedestrians and fuses the features of different scales …

Enhancing Consumer Trust In Displayed Information Through Digital Price Tags In Retail Marketing, Mark Yi-Cheon Yim, Sukki Yoon

Marketing Department Faculty Journal Articles

Although digital price tags have been widely adopted in many brick-and-mortar retailers, our understanding of their optimal use remains limited. Considering their ability to easily update prices and promotional messages remotely, concerns have emerged regarding consumer trust in the displayed information. This study examines the role of digital price tags in retail marketing, with a particular focus on their effectiveness in building consumer trust in displayed information. To explore this, three online experiments are conducted to investigate strategies for enhancing consumer trust in the use of digital price tags. Studies 1a and 1 b provide evidence that digital price tags …

Executive Committee - Agenda, 5/20/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

The Nature Of Optical Afterglows Without Gamma-Ray Bursts: Identification Of At2023lcr And Multiwavelength Modeling, Maggie L. Li, Anna Y.Q. Ho, Geoffrey Ryan, Daniel A. Perley, Gavin P. Lamb, A. J. Nayana, Igor Andreoni, G. C. Anupama, Eric C. Bellm, Edo Berger, Joshua S. Bloom, Eric Burns, Ilaria Caiazzo, Poonam Chandra, Michael W. Coughlin, Kareem El-Badry, Matthew J. Graham, Mansi Kasliwal, Garrett K. Keating, S. R. Kulkarni, Harsh Kumar, Frank J. Masci, Richard A. Perley, Josiah Purdum, Ramprasad Rao, Antonio C. Rodriguez, Ben Rusholme, Nikhil Sarin, Jesper Sollerman, Gokul P. Srinivasaragavan, Vishwajeet Swain, Zachary Vanderbosch

Faculty Publications

In the past few years, the improved sensitivity and cadence of wide-field optical surveys have enabled the discovery of several afterglows without associated detected gamma-ray bursts (GRBs). We present the identification, observations, and multiwavelength modeling of a recent such afterglow (AT 2023lcr), and model three literature events (AT 2020blt, AT 2021any, and AT 2021lfa) in a consistent fashion. For each event, we consider the following possibilities as to why a GRB was not observed: (1) the jet was off-axis; (2) the jet had a low initial Lorentz factor; and (3) the afterglow was the result of an on-axis classical GRB …

Factors Impacting The Variability Of Post-Fire Forest Regeneration In Central European Pine Plantations, Florent Jouy, Maren Schüle, Yojana Adhikari, Anja Binder, Danica Clerc, Werner Gerwin, Thilo Heinken, Thomas Raab, Frank Repmann, Susanne Rönnefarth, Marina Schirrmacher, Marie-Therese Schmehl, Jens Schröder, Pierre L. Ibisch

Aspen Bibliography

Fire is increasingly posing a risk to forests and plantations, even in the temperate latitudes of central Europe. Little is known about fire ecology in this region, and therefore, appropriate approaches for the management and reforestation of burned sites are mostly lacking. In a Scots pine plantation region in Brandenburg (northeast Germany), the early tree regeneration of two nearby areas that burned 1 year apart was investigated. We observed that 3 years after the fire events, the forest in one study area showed a relatively high regeneration with a mean density of 7765 saplings/ha, clearly dominated by European aspen (93%); …

Characterization Of Mechanical Property Evolution And Durability Life Prediction Of Engineered Cementitious Composites Under Frozen State, Su Lu, Liqiang Yin, Shuguang Liu, Dandan Yin, Jiaxin Liu, Huifang Hou, Lin Li

Civil and Architectural Engineering Faculty Research

Engineered cementitious composites (ECCs) exhibit superior mechanical properties (MPs) and excellent crack control capabilities, making them widely used in practical engineering applications. However, the MPs of ECCs in frozen states (FSs), particularly their flexural properties (FPs), still need to be better understood. MP tests were designed for frozen ECC samples to investigate the service performance of ECCs in an FS. The samples underwent 0 to 300 freeze–thaw cycles (FTs), followed by compressive and flexural tests at a constant freezing temperature of −18 °C. The compressive properties (CPs) and FPs of the samples and their influencing mechanisms were analyzed. Based on …

Leveraging Artificial Intelligence In Education To Drive Cross-Sector Innovation, Brent Terwilliger, John Faraca

Publications

As artificial intelligence (AI) reshapes educational practices, particularly in technical fields such as uncrewed systems, robotics, and aviation/ aerospace, its integration raises promise and complexity. This exploratory study features an investigation of the impact AI tools adoption has on instruction, curriculum support, and workforce preparation, with a focus on online learning environments. Drawing from pilot survey data across aviation and aerospace education stakeholders and hands-on evaluation of AI video production platforms, findings reveal diverse applications, perceived benefits, and critical concerns, including ethical, pedagogical, and institutional challenges. Additionally, the analysis explored how AI-enabled education intersects with broader industry and government innovation …

May 20, 2025 Ereporter, University Of Alabama At Birmingham

eReporter (campus newsletter)

No abstract provided.

Epigenome-Wide Dna Methylation Association Study Of Chip Provides Insight Into Perturbed Gene Regulation, Sara Kirmani, Tianxiao Huan, Joseph C Van Amburg, Roby Joehanes, Md Mesbah Uddin, Ngoc Quynh H Nguyen, Bing Yu, Jennifer A Brody, Myriam Fornage, Jan Bressler, Nona Sotoodehnia, David A Ong, Fabio Puddu, James S Floyd, Christie M Ballantyne, Bruce M Psaty, Laura M Raffield, Pradeep Natarajan, Karen N Conneely, Joshua S Weinstock, April P Carson, Leslie A Lange, Kendra Ferrier, Nancy L Heard-Costa, Joanne Murabito, Alexander G Bick, Daniel Levy

Faculty, Staff and Student Publications

With age, hematopoietic stem cells can acquire somatic mutations in leukemogenic genes that confer a proliferative advantage in a phenomenon termed CHIP. How these mutations result in increased risk for numerous age-related diseases remains poorly understood. We conduct a multiracial meta-analysis of EWAS of CHIP in the Framingham Heart Study, Jackson Heart Study, Cardiovascular Health Study, and Atherosclerosis Risk in Communities cohorts (N = 8196) to elucidate the molecular mechanisms underlying CHIP and illuminate how these changes influence cardiovascular disease risk. We functionally validate the EWAS findings using human hematopoietic stem cell models of CHIP. We then use expression quantitative …

Network Analysis Of Antimicrobial Resistance In Staphylococcus Aureus: Characterization Of Hub Genes And Their Functional Implications, Md Imran Hasan, Davida Smyth, Jeong Yang, Ashley Teufel

Masters Theses (Archived)

Antimicrobial resistance is a major cause of morbidity and mortality in patients with S. aureus infections. In this study, we analyzed genes, molecular mechanisms, and pathways driving drug resistance in S. aureus using network analysis. Using whole-genome sequencing (WGS) data and systems biology approaches, we identified 229 AMR-associated genes and constructed a protein-protein interaction network among these genes. Through network topology and functional enrichment analyses, we not only confirmed their association with resistance, but also highlighted the central roles of these genes in resistance pathways, such as efflux, target replacement, and target protection, which are directly linked to multiple drug …

Measuring And Improving The Efficiency Of Python Code Generated By Llms Using Cot Prompting And Fine-Tuning, Ramya Jonnala

Masters Theses (Archived)

With the advanced AI technologies, the role of Large Language Models (LLMs) has grown rapidly for software development with generating the code that is functionally correct, solving complex problems, and debugging existing code. However, LLMs often produce inefficient code with unnecessary logic, hallucinated content, and errors. This research measures the efficiency of Python code generated by GPT-4o-Mini, GPT-3.5-Turbo, and GPT-4-Turbo models using execution time, memory usage, and maximum memory usage while maintaining correctness. Using EffiBench datasets on Google’s Vertex AI Workbench with different machine configurations, the study uses the seed parameter for consistency and optimization techniques like Chain-of-Thought (CoT) prompting …

Application Of The Polydisperse Spherical Model For Pore Distribution Development Of Metakaolin-Based Geopolymers, Kanako Toda, Ryuhei Motokawa, Takumi Saito

Alkali Activated Materials and Geopolymers: High-end technical applications [2025]

Please click Additional Files below to see the full abstract

Modification Of Rheological Properties Of Metakaolin Based Geopolymer Using Graphene Oxide, Seralathan Sivasubramaniam, Yogarajah Elakneswaran

Alkali Activated Materials and Geopolymers: High-end technical applications [2025]

Please click Additional Files below to see the full abstract

Predicting Patient No-Show Rate In Healthcare To Improve Operational Excellence, Saeed Ahmed Al Wari

Theses

The challenge of integrating no-show predictive models into healthcare environments is complex and multifaceted, extending far beyond the distinct technical challenge of building accurate models. This thesis will discuss more on the subject of incorporating machine learning into healthcare. While algorithmic accuracy and model validation are critical, they are a mere sub-system of a much larger operational, technological, ethical, legal and human ecosystem. Predictive models face mass deployment in healthcare systems which are complex networks of stakeholders across strict regulatory frameworks and deeply embedded workflows (AlMuhaideb et al., 2019). However, for these models to result in long term and real …

Predicting Customer Churn In E-Commerce, Hind Tawfiq Kazim

Theses

Customer retention has become a critical focus for businesses seeking to sustain growth and profitability in an increasingly competitive market. In this thesis, advanced machine learning techniques are used to develop a data-driven churn prediction model for Majid Al Futtaim's customer base. In an e-commerce environment, the research focuses on identifying the key transactional and behavioral factors that influence customer churn, based on customer relationship management theory. The study is contextualized in the context of increased digital consumer engagement and high customer acquisition costs, which make retaining existing customers more cost- effective than acquiring new ones. Our primary research questions …

Hybrid Sentiment Analysis Of Police Social Media: Managing Big Data Impact On Youth, Alunood Yousuf Alamiri

Theses

The pervasive influence of social media has reshaped public communication, particularly for institutions like law enforcement agencies that rely on these platforms to engage with the community. As police departments increasingly utilize social media to disseminate information, interact with the public, and manage public relations, the need for effective sentiment analysis becomes crucial. Understanding how police messages are received by the public, especially by the youth, who are among the most active and impressionable users of social media, is essential for maintaining public trust and ensuring effective communication. This thesis, seeks to develop a comprehensive solution for this challenge. The …

Geometric Calibration Of Near Focus Infrared (Ir) Sensors For Spacecraft Missions, Alex Allgrunn

Space Dynamics Laboratory Publications

SDL Presentation on Geometric Calibration of Near Focus IR Sensors for Spacecraft Missions

Historical Perspectives In Volatility Forecasting Methods With Machine Learning, Zhiang Qiu, Clemens Kownatzki, Fabien Scalzo, Eun Sang Cha

All Faculty Open Access Publications

Volatility forecasting for financial institutions plays a pivotal role across a wide range of domains, such as risk management, option pricing, and market making. For instance, banks can incorporate volatility forecasts into stress testing frameworks to ensure they are holding sufficient capital during extreme market conditions. However, volatility forecasting is challenging because volatility can only be estimated, and different factors influence volatility, ranging from macroeconomic indicators to investor sentiments. While recent works show promising advances in machine learning and artificial intelligence for volatility forecasting, a comprehensive assessment of current statistical and learning-based methods is lacking. Thus, this paper aims to …