Digital Commons Network^™

Upcycling Waste To Wealth: Cuo-Sio₂/Reduced Graphene Nanocomposite From Pomegranate Peels For One-Pot Low-Temperature Conversion Of Waste Oils Into Valuable Fatty Acid Monomers, Attia Attia, Shahenda Mahran Dr., Maria Centeno Prof., Basudeb Saha

Petroleum Engineering and Gas

and hence reduce the price of the fatty acid monomers. This study reports for the first time a novel, environmentally benign, highly active copper oxide-silica oxide/reduced graphene oxide (CuO-SiO2/RGO), heterogeneous nano-catalyst derived from waste pomegranate peels, for the one-pot, low-temperature synthesis of fatty acid monomers from high-acid-value waste vegetable oil (WVO). The synthesised nano-catalyst was extensively characterised using XRD, FT-IR, TEM, SEM, EDX and TGA-DTA. Further, it was utilised to synthesise fatty acidrich oleic phenoxypropyl acrylate (OPA) monomer from high acid value WVO via a single-step reaction.

The Association Between Food Benefit Online Ordering And Redemptions: Evidence From The Special Supplemental Nutrition Program For Women, Infants, And Children, Junzhou Zhang, Chuanyi Tang, Kayoung Park, Qi Zhang

Department of Marketing Faculty Scholarship and Creative Works

Objective:

To examine how the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) online food benefit ordering could influence WIC benefit redemptions.

Design:

A cross-sectional study. We compare the average redemption rates between online ordering early adopters and non-adopters among WIC customers before and after implementing WIC online ordering. A propensity score-weighted difference-in-difference model was used to estimate the coefficients.

Setting:

The Oklahoma WIC programme and a grocery store chain in Oklahoma.

Participants:

12743 Oklahoma WIC households that had redeemed their food benefits at the grocery store chain in 2020.

Results:

WIC online ordering significantly positively affected redemption …

In Re: Nfl Players Concussion Injury Litigation

2025 Decisions

USDC for the Eastern District of Pennsylvania

Harbor Business Compliance Corp V. Firstbase Io Inc

2025 Decisions

USDC for the Eastern District of Pennsylvania

Blackbird's Missouri River: The Pinnacle Of Omaha Diplomacy, 1790-1801, Brent Michael Wojcik

History Theses, Dissertations, and Student Creative Activity

This thesis will examine the history of Umóⁿhoⁿ (Omaha) diplomacy with a special emphasis on the era from 1790 to 1801, which is a significant period in Umóⁿhoⁿ diplomacy. Wazhiⁿ'gaçabe (Blackbird) was a influential diplomatic figure on the Great Plains. The Umóⁿhoⁿ and Wazhiⁿ'gaçabe created an era of prosperity from 1790 to 1801. The diplomatic connections at Wazhiⁿ'gaçabe disposal are unrivaled by his contemporary Indigenous leaders. This thesis will lay out evidence that supports Wazhiⁿ'gaçabe as one of the greatest negotiators and diplomats of the time. Multiple primary sources that had direct connections to Wazhiⁿ'gaçabe will be examined. The primary …

Enhance Telecom-Related International Indicators Using Machine Learning, Omar Alnemer

Theses

This thesis investigates the enhancement of the Network Readiness Index (NRI) through the application of machine learning methodologies to refine indicator weighting, clustering, and dimensionality. The study builds on research promoting data-driven methods to address the limitations of equal-weighted indices in capturing indicator importance and interdependence. The research aims to evaluate how unsupervised and supervised learning methods can optimize the interpretation of NRI data. The study focuses on three primary research questions: (1) How can PCA be used to reduce the dimensionality of the NRI without significant loss of information? (2) Can k-means clustering reveal meaningful groups of countries with …

Free-Running Ring Oscillators For Crystal-Free Communication Systems: Design, Simulation Challenges, And Frequency Stability Improvements, Haziq Rohail

Dissertations and Theses

This thesis presents techniques for enhancing the frequency stability of ring oscillators (ROs) for crystal-free wireless communication systems. The first major contribution is a tutorial-style study of frequency stability metrics, providing clear definitions, conversions methods, and comparative analysis of commonly used figures of merit such as phase noise, Allan deviation, and jitter. The second contribution addresses the challenges of simulating phase noise in free-running ROs. Key techniques including Periodic Steady-State Noise (PNoise), Harmonic Balance Noise (HBNoise), and transient noise analysis are evaluated in terms of accuracy, convergence behavior, and simulation runtime. Based on these results, practical guidelines are offered for …

Purdue University Entrepreneurship And Innovation Resources, Alicia South-Hurt, Purdue University Office Of Research

University General Facility Boilerplate Descriptions

Overview of entrepreneurial and technology transfer resources, initiatives, and infrastructure at Purdue University.

Topological Indices And Quantitative Structure-Property Analysis Of Novel Drugs For Acute Lymphoblastic Leukemia Treatment, P. Nathiya, M. Suresh, Jalal Hatem Hussein Bayati

Baghdad Science Journal

Acute lymphoblastic leukemia in children is a bone marrow and blood cancer. Healthy blood cells begin to change and grow out of control when leukemia initially occurs. Acute lymphoblastic leukemia (ALL) is an immune system-related malignancy of the lymphocytes, a subtype of white blood cells. The most common form of cancer affecting children is ALL. In this work, the topological indices are derived from the structure of a chemical graph, and predict the physical, chemical, and biological characteristics of several anticancer drugs. ALL are usually treated with drugs such as methotrexate, 6-mercaptopurine (6-MP), vincristine, L-asparaginase, and/or prednisone, etc., which are …

A Clustering Technique Based On The Hard K-Means (H.Km.) Method To Determine The Governorate That Have More Influence For Spreading Covid-19 In The Kingdom Of Saudi Arabia, Rand Muhaned Fawzi, Wurood R. Abd Al-Hussein, Iden Hassan Alkanani

Baghdad Science Journal

The Kingdom of Saudi Arabia is the gathering place of most of the nationalities of the Islamic world. When a certain disease spreads, it will be important to know which governorate has the greatest influence on the spread of the disease and take the necessary precautions to limit its spread, and this is the goal of this study. COVID-19, The SRS-COV-2 coronavirus that caused the most recent pandemic is known as the Corona pandemic. To determine which Saudi governorates had the greatest influence on the epidemics spread, data was gathered for thirteen governorates over two months (July and August). The …

A Comparative Of Detecting Physical And Cyber Attacks On Drones Using Machine Learning And Deep Learning Techniques, Khattab M Ali Alheeti, Sara Abbas Rafa, Maha Mahmood, Aythem Khairi Kareem, Mohammad Aljanabi, Ahmed Adil Nafea

Baghdad Science Journal

Multitudes of Unmanned Aerial Vehicles (UAVs) are generally embraced in military and civilian applications. Yet, this physical-cyber method is intimidated by cyber-attacks. Recently, Machine Learning (ML) based attacks detection approaches have been effectively embraced to detect cyber-attacks. This paper presented the Intrusion Detection Security (IDS) approach. The proposed approach investigates UAVs' cyber and physical attributes under normal process and attack circumstances. Two types of cyber-attacks have been classified: Denial-of-service (DoS) and replay. This study developed IDS approaches established on ML and Deep Learning (DL) prototypes, including Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naive Bayes (NB), and One Dimensional Convolutional …

An Efficient Glaucoma Classification For Fundus Images By Pre-Trained Deep Cnns And Accuracy-Weighted Voting Classifier Fusion, Salam Jabbar Edan, Mohammad-Reza Feizi-Derakhshi

Baghdad Science Journal

Glaucoma, a chronic eye disease characterized by progressive optic nerve damage, remains a significant public health concern worldwide. Early and accurate diagnosis is crucial for timely intervention and preventing irreversible vision loss. In this paper, developed an approach for glaucoma classification utilizing pre-trained convolutional neural networks (CNNs), specifically ResNet-101, ResNet-18, and DarkNet-19. Also employed accuracy-based weighted voting as a classifier fusion technique. Leveraging the capabilities of these CNN architectures, extract high-level features from retinal fundus images and apply transfer learning to adapt the networks for glaucoma classification. Leveraging the capabilities of these CNN architectures, extract high-level features from retinal fundus …

Accurate Skin Lesion Segmentation Through Feature Fusion In Dermoscopy Images, Fallah H. Najjar, Farhan Mohamed, Asniyani Nur Haidar Abdullah, Mohd Shafry Mohd Rahim, Karrar A. Kadhim

Baghdad Science Journal

In the diagnosis of skin cancer, dermoscopy images have to be evaluated for feature extraction. In this paper, the authors design a new method to enhance the skin dermoscopy image segmentation accuracy by eliminating artifacts and hair using photometric quasi-invariants, followed by a unique approach for skin lesion segmentation using histogram-based feature fusion. Histogram features are used to extract data range and mean images from the histogram, and these are fused with the free artifacts and hair image to generate the final image. the authors used the PH2 dataset for the proposed segmentation method because it contains the ground truth …

Assessing Solar Radiation Patterns In Sarawak Using Measured Data And The Hargreaves-Samani Model For Photovoltaic Systems Application, Chun Yong Soo, Xian Hwa Chan, Wan Mohamad Husni Wan Mokhtar, Ahmad Rujhan Mohd Rais

Makara Journal of Technology

This study evaluates the Hargreaves-Samani model for estimating solar radiation in five locations in Sarawak: Bintulu, Kapit, Sri Aman, Kuching, and Miri (Subis), using minimum and maximum temperatures as key inputs. Analysis reveals stable minimum temperatures (19.7 °C to 28.8 °C), supporting consistent solar radiation patterns favorable for Photovoltaic (PV) performance. Miri (Subis) recorded the highest daily maximum temperature of 44.8 °C, while Kuching had the lowest at 24.7 °C, highlighting significant regional climatic variability. Analysis also indicates strong solar potential in Bintulu, Kapit, Sri Aman, Kuching, and Miri, with radiation peaking at 7.5 kWh/m², though seasonal variations impact PV …

Direct Control Strategy Using Polynomial Fuzzy-Based Adaptive Fractional Order Pid Controller, Ali Rospawan, Clara Lavita Angelina, Faisal Samsuri, Muhammad Yeza Baihaqi, Edmun Halawa, Muhammad Munajat, Vincent Vincent, Surawan Setiyadi, Irwan Purnama, Joni Welman Simatupang

Makara Journal of Technology

This paper presents a novel direct control strategy using a polynomial fuzzy neural network-based adaptive fractional order proportional integral derivative (PFNN-AFOPID) controller for nonlinear and time-varying systems. The proposed approach integrates the enhanced flexibility of fractional order calculus PID with the superior nonlinear approximation capabilities of polynomial fuzzy models, enabling dynamic adjustment of all control parameters without requiring precise mathematical modeling of system dynamics. By extending traditional PID control with fractional-order operations, the controller achieves improved frequency response and robustness against disturbances. Experimental validation on a DC motor position control system demonstrates significant performance improvements. Compared to traditional PID, the …

The 9th Annual Lafora Science Symposium: A Rare Epilepsy Community Makes Progress Towards Clinical Readiness, Meredith I. Williams, Katherine J. Donahue, Pascual Sanz, Souad Messahel, Jose M. Serratosa, Jordi Duran, Roberto Michelucci, Lorenzo Muccioli, Antonio Delgado-Escueta, Viet-Hong Nguyen, Berge A. Minassian, Matthew S. Gentry

Pharmacy Faculty Articles and Research

Lafora disease (LD) is a fatal childhood progressive myoclonus epilepsy and glycogen storage disease that is caused by recessive mutations in either EPM2A or EPM2B. The hallmarks of LD are cytoplasmic, aberrant glycogen-like aggregates, called Lafora bodies (LBs), that drive disease progression. The 9th Annual Lafora Science Symposium was held in San Diego, California and brought together over 70 researchers, clinicians, academic trainees, and friends and family members of patients with LD and 80 attendees joined virtually. This symposium focused primarily on international collaborations for therapeutic development and biomarker identification and strategies for preparing the Lafora community for upcoming …

The Bg News August 27, 2025, Bowling Green State University

BG News (Student Newspaper)

The BGSU campus student newspaper. August 27, 2025. Volume 105-Issue 01.

A New Approach For Selecting Optimal Neuron Number In Input Layer Of Generalized Regression Neural Network Model, Muhammad Muhajir, Hermansah Hermansah, Aditya Pandu Wicaksono, Lathifah Aliya Pratiwi

Baghdad Science Journal

This study aimed to determine the input layer neurons for the Generalized Regression Neural Network (GRNN) model by using various classical methods, namely 1) Partial Autocorrelation Function (PACF), 2) frequency-based method, 3) frequency and Forward Selection (FS), 4) frequency and Backward Elimination (BE), 5) frequency and step-based methods, and 6) frequency method combined with the Least Absolute Shrinkage and Selection Operator (LASSO). These classical methods were combined with various parameters within GRNN, including smoothing parameters, forecasting strategies, and transformations. The most accurate model, with the lowest RMSE, MAE, MAPE, and SMAPE values, resulted from the combination of frequency and BE, …

Accelerating The Fusion Workforce In The Usa, Carlos Paz-Soldan, Eva Belonohy, Troy Carter, Laleh E. Coté, Evdokiya Kostadinova, Calvin Lowe, Subash L. Sharma, Sybil De Clark, Jaydeep Deshpande, Kate Kelly, Bobbi Makani, David A. Schaffner, Kathreen E. Thome

Faculty Research, Scholarly, and Creative Activity

The fusion energy research and development landscape has seen significant advances in recent years, with important scientific and technological breakthroughs and a rapid rise of investment in the private sector. The workforce needs of the nascent fusion industry are growing at a rate that academic workforce development programs are not currently able to match. This paper presents the findings of the Workforce Accelerator for Fusion Energy Development Conference held in Hampton, Virginia, United States of America (USA), on 29-30 May 2024, which was funded by the National Science Foundation of the USA. A major goal of the conference was to …

Poster: Development Of Situation Awareness Measurement For Cybersecurity Professionals, David Schuster, Crystal Fausett, Maiyi Huang, Sabina M. Patel, Jenna Korentsides, Joseph R. Keebler, Elizabeth H. Lazzara

Faculty Research, Scholarly, and Creative Activity

Better understanding of the implications of many aspects of human behavior, especially that of cybersecurity professionals, can help develop the cybersecurity workforce. Despite efforts aimed at documenting and understanding cybersecurity professionals' knowledge, understanding of how cognition supports human performance in specific cybersecurity tasks remains limited. Specifically, understanding of the elements of situation awareness (SA), defined as goal-directed knowledge, is necessary to support human-centered evaluation, selection, training, and recruitment strategies. In this poster, we propose a framework for developing measures of situation awareness for cybersecurity professionals and a method of capturing initial effectiveness data that does not rely on access to …

Poster: Cloudsweeper: Leveraging Large Language Models To Personalize Sensitive Archive Search, Victor Escuerdo, Sergio Talavera, Gautam Santhanu Thampy, Ivan Torres, Daniel Vega Lojo, Chris Kanich, Magdalini Eirinaki

Faculty Research, Scholarly, and Creative Activity

As cyber threats continue to evolve, overlooked or neglected files stored in cloud services can pose significant risks to personal privacy and data security. In this paper we present Cloudsweeper, a system that aims to improve cloud storage security by creating tools that help users identify and manage sensitive or unwanted files. Cloudsweeper leverages Large Language Models (LLMs) with a Retrieval-Augmented Generation (RAG) architecture to develop a personalized and privacy-focused archive search system. Cloudsweeper represents an innovative approach to secure archive management, balancing user control and privacy in cloud storage environments.

Poster: Threat Intelligence & Modeling Practices For Iomt Devices Using Wi-Fi Communications, Eva Wilson, Cody Ourique, Bernardo Flores

Faculty Research, Scholarly, and Creative Activity

The integration of internet connectivity into medical devices, known as the Internet of Medical Things (IoMT), is revolutionizing modern healthcare through remote monitoring and advanced diagnostics. Among these devices, the Continuous Positive Airway Pressure (CPAP) machine plays a critical role in managing patients with Sleep Apnea. However, the security of CPAP devices presents significant concerns due to potential vulnerabilities that could lead to critical failures, such as device shutdowns. An analysis was made of the device's connectivity interface, to identify potential exploit points and vulnerabilities. Additionally, we evaluated whether existing threat modeling frameworks - namely the MITRE Adversarial Tactics, Techniques, …

Context-Aware Natural Language Processing For Malware Detection, Helen Liu, Summer Mccune, Quang Duy Tran, Fabio Di Troia, Younghee Park

Faculty Research, Scholarly, and Creative Activity

As malware continues to evolve and cyber attacks become increasingly prevalent, it is critical to develop effective malware classification techniques for the detection and prevention of such malicious attacks. In our research, we approach malware classification from a natural language processing perspective to explore how various tokenization techniques on malware opcode features can enhance classification accuracy and combat malware obfuscation and evolution techniques with a deep learning approach, previously unaddressed by existing research. We bridge this gap by conducting extensive hyperparameter tuning experiments that examine the effects of five common tokenization methods, that is, White Space Separation, Top Single Words, …

Re: Butte Mine Flooding Operable Unit Berkeley Pit And Discharge Pilot Project – July 2025 Monthly Discharge Monitoring Report, Mark Thompson, Dave Griffis

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Explaining Time Series Classifiers Through Post-Hoc Xai Methods Capturing Temporal Dependencies, Ephrem Tibebe Mekonnen

Conference papers

Time series classification is essential in domains such as healthcare and finance, where accurate predictions can have significant real-world consequences. However, in many high-stakes applications, understanding why a model makes a certain decision is just as important as the prediction itself. While deep learning models excel at capturing complex temporal patterns, their black-box nature limits transparency, making it difficult to trust and interpret their decisions. Although eXplainable AI (XAI) methods have advanced considerably for image and tabular data, applying them to time series remains challenging due to the intricate temporal dependencies and high dimensionality of the data. Post-hoc model-agnostic XAI …

Computational Fluid Dynamics (Cfd) Modeling For Bio-Inspired Aerodynamic Optimization In Autonomous Drones, Hyginus C.O. Unegbu, Danjuma Saleh Yawas

Makara Journal of Technology

This study explores the aerodynamic benefits of bio-inspired design modifications for autonomous drones using advanced Computational Fluid Dynamics (CFD) simulations. Four bio-inspired configurations—leading-edge serrations, winglets, riblet surfaces, and curved wings—were assessed and compared against a baseline drone model to evaluate their impact on aerodynamic performance. The results indicated that all bio-inspired designs significantly enhanced lift, reduced drag, and improved overall aerodynamic efficiency. The leading-edge serration configuration achieved the highest performance gains, with a 33.6% increase in maximum lift coefficient (CL) and a 29.5% improvement in lift-to-drag ratio (CL/CD), primarily due to delayed flow separation and reduced turbulence. Winglets minimized wingtip …

Synthetic Malware Image Generation Based On Generative Models Against Zero-Day Attacks, Arjun Sudheer, Ayesha Ahmed, Fabio Di Troia, Younghee Park

Faculty Research, Scholarly, and Creative Activity

Malware detection is a critical task for protecting our assets from attacks. However, traditional approaches to malware detection often struggle with limited datasets, which hinder the effectiveness of machine learning models. In this paper, we propose a malware image generation system designed to craft high-quality synthetic malware image samples, addressing the challenges posed by small datasets in malware detection. The proposed system utilizes two popular generative models, WGAN-GP and Diffusion, to generate synthetic malware images. It converts malware binary files into image files using four different color spaces: monochrome, grayscale, RGB, and CMYK. These images are then evaluated based on …

Heterozygous Variants In Plcg1 Affect Hearing, Vision, Cardiac, And Immune Function, Mengqi Ma, Yiming Zheng, Mingxi Deng, Shenzhao Lu, Xueyang Pan, Xi Luo, Michelle Etoundi, David Li-Kroeger, Kim C Worley, Lindsay C Burrage, Lauren S Blieden, Aimee Allworth, Wei-Liang Chen, Giuseppe Merla, Barbara Mandriani, Catherine E Otten, Pierre Blanc, Jill A Rosenfeld, Debdeep Dutta, Shinya Yamamoto, Michael F Wangler, Ian A Glass, Jingheng Chen, Elizabeth Blue, Paolo Prontera, Jeremie Rosain, Sandrine Marlin, Seema R Lalani, Hugo J Bellen, Undiagnosed Diseases Network

Duncan NRI Faculty and Staff Publications

Phospholipase C isozymes (PLCs) hydrolyze phosphatidylinositol 4,5-bisphosphate (PIP₂) into inositol 1,4,5-trisphosphate (IP₃) and diacylglycerol (DAG), important signaling molecules involved in many cellular processes including Ca²⁺ release from the endoplasmic reticulum (ER). PLCG1 encodes the PLCγ1 isozyme that is broadly expressed. Hyperactive somatic mutations of PLCG1 are observed in multiple cancers, but only one germline variant has been reported. Here, we describe seven individuals with heterozygous missense variants in PLCG1 [p.(Asp1019Gly), p.(His380Arg), p.(Asp1165Gly), and p.(Leu597Phe)] who present with hearing impairment (5/7), ocular pathology (4/7), cardiac septal defects (3/6), and various immunological issues (5/7). To model these …

My Time With The Fusion Industry Association (“Fia”): Future-Focused Policy For A Fusion-Powered America, Erik J. Rorem

The Dialogue

No abstract provided.

Increasing And Improving Diversity And Hiring Of Individuals With Disabilities In The Workplace, Joshua Zhang

McNair Research Journal SJSU

This paper is a literature review of several literature on disability, diversity,

human resource/human resource management, and hiring in the

workplace/organization. The research question is how can employers

improve and increase hiring of individuals with disabilities in their

organizations? The objectives of this literature review paper are 1. Research

and analyze existing literature on disability, diversity, and workplace hiring,

2. Identify any limitations in gaps in research literature, and 3. Propose and

suggest areas and topics for future research. Each of the academic sources

in this paper are presented and discussed along with analysis. Additionally,

recommendations on how to best …