Digital Commons Network^™

Supporting Young Carers In Early Childhood: Mapping Power, Threat, Meaning, And Strengths: A Ptmf-Informed Qualitative Study, Carly Ellicott, Ali Bidaran, Felicity Dewsbery, Alyson Norman, Helen Lloyd

School of Psychology

Background/Objectives: This qualitative study examines strengths and strains faced by professionals working with young carers throughout the United Kingdom (UK) in the context of society’s youngest carers; young carers in early childhood (YCEC) (0–8 years). Methods: The Power Threat Meaning Framework (PTMF) was utilised to map key findings of three focus groups. This conceptual lens offers a narrative-based understanding of ways in which power operates in society. Increasingly applied to explore experiences of individuals, communities, and groups, the PTMF proposes that concepts of distress are founded in broader contexts of injustice and social inequalities. Twenty-four participants were recruited from throughout …

Vigilante Violence, The Rise Of The New Right, And The Persistence Of The Texas Farmworkers, 1975–1980, Brent M. S. Campney, Tim Bowman

History Faculty Publications

This study charts the ineffective vigilante violence perpetrated by growers in the Rio Grande Valley of Texas to suppress farmworker activism from the mid-to-late 1970s and their abrupt shift in tactics with a 1980 strike in Hereford, Texas, toward the adoption of strictly nonviolent and tediously legalistic new methods associated with the neoconservative backlash. It does so in two major sections. In the first, grower violence is chronicled in detail that underscores both its rage and ineffectiveness. The second section shows how the New Right usurped the longstanding usage of physical violence against ethnic Mexicans in Texas, prompting conservatives to …

Understanding The Compatibility Of Fluoride-Based Radiopharmaceutical Reaction Solutions And Pdms, Mark Mc Veigh, Charles Frech, Mai Lin, Robert Ta, H Charles Manning, Leon M Bellan

Faculty, Staff and Student Publications

Microfluidic devices offer unique and exciting benefits when applied to radiopharmaceutical manufacturing, and these platforms are now starting to be integrated into commercial products. The field has strayed away from the use of polydimethylsiloxane (PDMS), the most common microfluidic device material, due to its suspected incompatibility with 18F, the most commonly used radionuclide. However, existing literature provides conflicting conclusions as to the existence and extent of this incompatibility. In this study, we use several analytical instruments to uncover the underlying interaction between fluoride and PDMS. SEM imaging and profilometry confirm the reactive relationship between the two materials and suggest that …

Autograft Enlargement After The Ross Procedure In Pediatric Patients: Somatic Growth Or Pathologic Dilatation?, Ioannis Zoupas, Alexander C Mills, Scott D Olson, Damien J Lapar

Faculty, Staff and Student Publications

Purpose of ReviewPulmonary autograft autotransplantation represents a popular surgical approach for pediatric patients requiring aortic valve replacement due to the potential for autograft enlargement to accommodate somatic growth. Nevertheless, autograft dilatation and the subsequent need for reintervention are quite common. Published data suggest that autograft enlargement may result from pathological passive remodeling rather than active somatic growth and vice versa. The present review serves to comprehensively evaluate available evidence related to the fate of the pulmonary autograft after the Ross procedure as it relates to the etiology, risk factors and patterns of autograft failure.ResultsStudies present conflicting results supporting both pathological …

Prevalence And Outcomes Of Her2-Low Versus Her2-0 Status In Patients With Metastatic Breast Cancer, Akshara Singareeka Raghavendra, Diane D Liu, Senthil Damodaran, Sarah Pasyar, Yu Shen, Jason A Mouabbi, Carlos H Barcenas, Kelly K Hunt, Debu Tripathy

Faculty, Staff and Student Publications

Background: HER2-low breast cancer (HER2 immunohistochemical [IHC] score 1+, or IHC 2+ without HER2 gene amplification) is distinct from HER2-positive and HER2-0 breast cancer (IHC 0), with a differing prognosis and specific therapeutic options. The DESTINY-Breast04 trial demonstrated notable efficacy of the HER2 antibody-drug conjugate trastuzumab deruxtecan over standard chemotherapy in patients with metastatic breast cancer (MBC) defined as HER2-low. More recently, the DESTINY-Breast06 trial confirmed this benefit in hormone receptor-positive and HER2-ultralow (less than 1+, but with ≤10% of infiltrating cancer cells showing incomplete and faint/weak membrane staining) cases, prompting re-evaluation of HER2 diagnostic thresholds and treatment strategies.

Methods …

A Neutrosophic Homological-Gröbner Framework For Ai-Driven Media Education Evaluation, Mona Gharib, Hafiz Muhammad Athar Farid, José M. Merigó, Muhammad Riaz

Sustainable Machine Intelligence Journal

The integration of artificial intelligence (AI) with media technologies has transformed teaching in Journalism and Communication, introducing new challenges for quality evaluation. Traditional assessment methods fail to capture the uncertainty, inconsistency, and incompleteness inherent in modern educational data. This paper proposes a Neutrosophic Homological–Gröbner Framework, which unifies three perspectives: neutrosophic sets to encode uncertain evidence, homological algebra to analyze structural coherence, and Gröbner bases to systematically simplify interdependent evaluation rules.

Within this framework, diverse evidence is encoded into neutrosophic triplets, daggregate into course-level indicators, and organized into neutrosophic chain complexes, where Betti indices reveal coherence and fragmentation. Educational policies are …

High-Performance Deep Learning Techniques For Plant Disease Detection: Performance Analysis, Validation, And Applications, Doaa El-Shahat, Ahmed Elmasry

Sustainable Machine Intelligence Journal

The early detection of plant diseases is an indispensable task to improve crop yields and production quality. Crop disease observations by experienced pathologists are difficult and might take a long time. Therefore, deep learning (DL) techniques have been utilized to present an automated detection technique that could accurately and timely detect plant diseases. Several DL models in the literature were proposed, but no paper conducted a comparative study between those models to determine which of them was the best alternative for this task. Therefore, twenty-one DL models are compared in this review paper to show which of them could achieve …

Rf-Et-Ann: Hybrid Machine Learning Model For Forecasting Short-Term Photovoltaic Power Production, Walid Abdullah, Ahmed Ismail Ebada, Mohamed Abouhawwash

Sustainable Machine Intelligence Journal

Accurately forecasting photovoltaic (PV) power generation is a challenging problem due to the non-linear and highly variable characteristics of solar data, which is strongly influenced by several interdependent factors, such as environmental conditions, system characteristics, and technical aspects. In this study, a newly proposed machine learning (ML) technique based on integrating random forest (RF), extra trees (ET), and artificial neural networks (ANN) is presented to tackle this problem with better predictive accuracy, ensuring that solar energy is used more consistently, effectively, and economically; this model is dubbed RF-ET-ANN for short. Hybridization of these three models will help capture non-linear aspects …

Gnmsa: An Accurate Parameter Estimation Of Semi-Empirical Proton Exchange Membrane Fuel Cells Model Using A Hybrid Artificial Intelligence–Based Optimization Approach, Dina Atef, Doaa El-Shahat, Hafiz Burhan Ul Haq, Zaka Ur Rehman, Muhammad Nauman Irshad

Sustainable Machine Intelligence Journal

The PEMFC parameter estimation problem has recently piqued the interest of several researchers due to its significance in reaching better PEMFC modeling. However, existing PEMFC parameter estimation algorithms encounter significant difficulty in solving this problem because of its complex and highly nonlinear nature. Therefore, this paper presents a new hybrid approach, termed GNMSA, for addressing this problem more accurately. This hybrid approach combines the exploration operator of the generalized normal distribution optimization with the exploitation operator of the mantis search optimization (MSA), resulting in this strong variant that has high abilities to alleviate stagnation in local optima and expedite convergence …

An Enhanced Optimization Algorithm For Estimating Pem Fuel Cells Parameters: Performance Comparison And Real-World Applicability, Ibrahim Alrashdi, Karam M. Sallam

Sustainable Machine Intelligence Journal

Accurate modeling is critical for the efficient design, control, and optimization of a proton exchange membrane (PEM) fuel cell. This problem is regarded as a multi-modal, multi-variate, non-linear optimization problem, and several methods in the literature have been presented to tackle it. However, those methods still suffer from either being stuck into local optima or a slow convergence rate. To solve this problem more accurately in terms of final results and convergence speed, this study proposes a hybrid optimization algorithm based on enhancing the recently proposed crested porcupine optimizer (CPO) using two new optimization methods, namely ranking-based optimization and exploration-exploitation …

Deep Learning In Precision Agriculture: A Systematic Review Of Methods, Datasets, And Applications, Mariam Ahmed

Sustainable Machine Intelligence Journal

With the growing demand for food and water for the world population. Deep learning is one of the most powerful approaches for smart agriculture, offering the capacity for accurate and fast data manipulation and decision-making. To this end, this study contributes to the body of knowledge as follows. We present a comprehensive review of deep learning methods commonly applied in precision agriculture, categorized into three main categories: discriminative, generative, and hybrid models. Given the data-driven nature of DL, we provided a structured overview and tabulation of available datasets in precision agriculture, by categorizing them according to modality to guide dataset …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

The Bg News January 14, 2026, Bowling Green State University

BG News (Student Newspaper)

The BGSU campus student newspaper. January 14, 2026. Volume 105-Issue 13.

From Covenant To Contract: How Secularization Of Christian Society Changed The Moral Basis Of Law, Rudy Iturrino

Doctoral Dissertations and Projects

Modern secular society has replaced religious understandings of obligation with legal contracts in which the state acts as the final arbiter. The purpose of this document analysis is to explore how the Christian concept of covenant was gradually replaced by secular legal contracts during the Reformation and Enlightenment, and how this shift influences modern views on eminent domain and national security policy. This dissertation was guided by Social Contract Theory. The following research question guided this study: What patterns from a document analysis reveal how the Christian idea of covenant was replaced by secular contract theory during the Reformation and …

Where The Government Steps Back, Business And Philanthropy Can Step Forward Together, Emily Brenner, Tory Martin, Anneliese Orr

Research, Reports, and Publications

No abstract provided.

Weighing The Power Of Ai Against Its Impact, Kallie Bauer, Emily Brenner

Research, Reports, and Publications

No abstract provided.

Innovation And Survival: The Charitable Sector Is Looking For New Ways To Work, Jeff Williams

Research, Reports, and Publications

No abstract provided.

We Need Data And We Need Context. Both Are At Risk., Joe Vandoornik, Kallie Bauer

Research, Reports, and Publications

No abstract provided.

Employee Well-Being At Risk During Times Of Hyper Disruption, Jill Roof, Anneliese Orr, Mandy Sharp Eizinger

Research, Reports, and Publications

No abstract provided.

Small Courageous Minds, Desirae Bach

Masters Theses

This thesis examines the barriers, agreements, and disagreements between mental health and Christianity, specifically as it relates to helping Christian children with anxiety. The following investigation explores how God defines and reacts to anxiety in the Bible and how anxiety is explained through scientific research. By explaining both scientific and biblical views of anxiety, the Christian community can grasp a better understanding of how to help children with anxiety. The research also builds a foundational investigation on how anxiety affects children and possible solutions for relieving anxiety in children. Educating children at a young age about mental health and offering …

Factors Influencing Sugary Drink Consumption Among Residential Students At Liberty University, Chinonso Felistas Eziechi

Masters Theses

Introduction/Background: Sugary drink consumption among college students remains a public health concern due to its association with obesity, diabetes, and cardiovascular disease. Despite high awareness of health risks, consumption among emerging adults remains elevated. Guided by the Social Cognitive Theory, this study examined the psychosocial, behavioral, and environmental determinants of sugary drink consumption among residential students at Liberty University. Objective: To identify key predictors of sugary drink consumption and evaluate how expectations, self-regulation, and environmental factors shape beverage behaviors. Design, Setting, Participants: This cross-sectional study used an anonymous Qualtrics survey distributed on campus. Of approximately 745 eligible residential students, 473 …

The Impact Of Awareness Of Campus Health Services On Utilization Of Medical Care Among Residential Students At Liberty University, Catherine Pandagade

Masters Theses

College students represent the most prominent group of individuals when considering their lifestyles throughout aging. Therefore, this age group serves as a good opportunity for health education that could build positive health behaviors for life. Existing literature have said that the 18-25 year olds tend to have fewer resources and be often uninsured and have the highest rates of preventable diseases.2 Objective: The aim of this research is to investigate the impact of awareness and its subsequent effect on utilization of available health resources on campus among the student population of Liberty University. Additionally, the purpose of the research through …

Basil Oil As An Environmentally Friendly Corrosion Inhibitor For Aisi 1010 Mild Steel Pipes In The Cooling Towers, Mohammed Ali Kadhim, Nagam Obaid Kariem, Rasha Al-Saedi

Baghdad Science Journal

One of the most significant industrial problems is the corrosion of construction metals such as mild steel in pipes and storage tanks of cooling towers. Several preventive measures are used to minimize corrosion. One of them uses various corrosion inhibitors, some of which are organic and others inorganic. Most inorganic corrosion inhibitors are environmentally unfriendly materials. These inhibitors, mixed with cooling tower water, are discharged into rivers or seawater. Many of them are toxic and affect biological life through their ingestion by humans and animals or through their entry into the soil. Basil plant oil is suggested as a new …

Truncated Exponentiated Ailamujia Exponential Distribution: Properties And Applications, Samer Abdulqader Salih, Dabya Mahmood Ali, Hind Khaled Kolaib, Alaa Abdulrahman Khalaf

Baghdad Science Journal

Probability distribution has shown its practicality in almost every area of human effort. This paper introduces a novel family of distributions called the [0, 1] Truncated Exponentiated Ailamujia-G family. The [0, 1] Truncated Exponentiated Ailamujia Exponential ([0, 1]TEAE) distribution, which is a sub-model of the recently created family, is completely constructed. The [0, 1]TEAE distribution is created by merging the [0, 1] Truncated and Exponentiated Ailamujia distributions. the mathematical features of the [0, 1]TEAE distribution, including moments, skewness, kurtosis, incomplete moments, renyi entropy, quantile function, and probability-weighted moments, are extensively examined. The quantiles for the chosen parameter values are clearly …

Influence Of Rotation And An Inclined Magnetic Field For The Peristaltic Flow Of Viscoplastic Fluid Through A Porous Medium, Khalid Khaleefah Jassim, Mohammed Salim Ramadhan

Baghdad Science Journal

This research deals with the influencing of rotation and an inclined magnetic field on the analysis of blended convection heat transfer within a viscoelastic fluid that flows peristaltically through an inclined tapered asymmetric channel, that traversing in a porous media. The foundational equations of continuity, momentum, and energy were established in Cartesian coordinates. Furthermore, a range of dimensionless numbers, including Reynolds number, Brandt number, and Froude number, were introduced to regulate the governing equations in their imensionless forms. The governing equations were further simplified under the presumption of long wave lengths and small Reynolds numbers. The perturbation method was utilized …

A Proposed Cryptographic Algorithm Based On Three-Pass Protocol And The Elliptic Curve Cryptography, Rifaat Z. Khalaf, Hamza B. Habib

Baghdad Science Journal

The internet lately has become an integral part of people’s lifestyles. It impacts various aspects of their daily lives, including education, communication, etc. Hence, the need for efficient and fast cryptography algorithms has increased. In this paper, a new cryptographic algorithm is proposed using the authenticated Three-Pass Protocol (TPP) and the Elliptic Curve Cryptography (ECC). In the proposed algorithm, the ECC is used to encrypt and decrypt data (a text of size 128 bits), and the TPP is used for transmitting this data without sharing the keys. In the standard ECC, the receiver publishes the elliptic curve (EC) equation, the …

Estimation Of The Reliability Function Of The Maxwell - Boltzmann Distribution Using The M-Robust Estimation Methods And Comparing Them With Conventional Methods, Shaymaa Riyadh Thanoon

Baghdad Science Journal

To achieve the best possible outcomes. The reliability function estimation was also established for the In this study, the scal parameter Maxwell distribution was estimated using both traditional and robust methods, and the results were compared typical estimation methods, which included the Maximum Likelihood method (MLE), the moments method (MOM), and the M- robust method The results were compared using the mean error squared (MSE). The M-robust technique was found to have the lowest mean square error across all sample sizes, as demonstrated by the findings hence, it is regarded as being more effective than the conventional estimate methods. In …

Improving Energy And Capacity-Awareness Of Effective Satellite Communication In 6g Heterogeneous Internet Of Things, Ahmed Mahdi Jubair, Khitam Abdulbasit Mohammed, Fouad H. Awad

Baghdad Science Journal

The spreading of Sixth Generation (6G) communication within the Internet of Things (IoT) is one of the recent innovations in networking services. As the number of devices becomes increasingly connected through extensive communication network connectivity, energy efficiency has become a significant concern with the widespread use of massive IoT devices. While general lack of energy optimization can lead to several issues, including data loss, link failure, and high-power utilization, directly affect the communication quality of the network. To address these challenges, it is crucial to develop a model that combines effective optimization and resource allocation, based on both Quality of …

Robust Qr Code Counterfeit Detection By Integrating Vgg19 Neural Embedding And Triplet Loss, Gede Putra Kusuma, Yulianto Yulianto, Renaldy Fredyan, Hendi Chandi, Jeffry William Tan, Philip Kwan, Muhammad Dafa Syukur

Baghdad Science Journal

Detecting counterfeit Quick Response codes plays a critical role in protecting the integrity of products and documents. This paper presents a novel methodology to increase the reliability of QR code counterfeit detection by integrating neural embedding VGG19 and triplet loss. The approach uses deep neural networks. Specifically, the modification of the VGG19 architecture is used to extract unique features from QR codes. These features are embedded in a multi-dimensional space using neural embedding methods. The use of the triplet loss function aims to increase the discriminative power of the embeddings, ensuring the discriminative power of the embeddings, and ensuring that …

Bioinformatics-Inspired Secure Video Encryption Using Chaotic Maps And Light Streaming Algorithms, Rajaa K. Hasoun, Rasha S. Ali, Ahmed G. Hameed, Ghassan H. Abdul-Majeed

Baghdad Science Journal

The Traditional encryption methods, such as AES, can be too slow for large video files, necessitating the development of faster and more efficient solutions for real-time video security. This research aims to enhance video security during transmission by developing a novel video encryption algorithm that is both fast and robust, specifically designed to handle large video datasets efficiently. The proposed video encryption algorithm integrates lightweight streaming algorithms for enhanced speed, modern cryptographic techniques, and chaotic maps for heightened security. The encryption process involves three key steps: Dividing the video into frames and scrambling/encrypting each frame, employing three innovative techniques: vertical …