Digital Commons Network^™

Should Ptin Omissions Be Criminalized?, Linda Galler, Jay A. Soled

Hofstra Law Faculty Scholarship

Linda Galler is the Max Schmertz Distinguished Professor of Law at the Maurice A. Deane School of Law at Hofstra University, and Jay A. Soled is a distinguished professor of taxation at Rutgers Business School.

In this article, Galler and Soled examine a recent legislation discussion draft that would increase penalties on return preparers who omit their identification numbers from tax returns or refund claims, and they reach different conclusions on whether Congress should criminalize those failures.

The Supreme Court’S Specious Code Of Conduct, James J. Sample

Hofstra Law Faculty Scholarship

Congressionally imposed ethics enforcement would enhance the Supreme Court's exercise of constitutional powers by reducing the interference of improper personal motives during its factual and legal determinations. The Court has long recognized the self-evident truth that "no man can be a judge in his own case." The Framers recognized the limits inherent in human nature: humans are not angels. Accordingly, the Constitutional scheme of separated powers, as elucidated by Madison, "[does] not mean that these departments ought to have no partial agency in, or no control over, the acts of each other." Congress rightly has the constitutional means and motive …

A Tax Friendly Approach To Agrivoltaics, Avery S. Younis

Law Student Publications

The first reported agrivoltaic farm experiment was performed on lettuce crops in 2013 in Montpellier, France. Ground-mounted solar panels were co-located with either food crops or livestock to simultaneously engage in agricultural activities while producing energy. This dual purposing of land is called agrivoltaics. Agrivoltaic projects are promising because the co-location aids with food production, renewable energy production, and preservation of natural resources.

In America, the agricultural industry is supported by a myriad of policies protecting and benefitting farmers. One such benefit comes from current use programs. Many states offer current use programs in which agricultural land is assessed and …

Examining The Implications Of A Stricter Tacking Standard In The Aftermath Of Bertini V. Apple, Catherine S. Condyles

Law Student Publications

Trademarks serve to indicate an item’s source of origin and distinguish it from other commodities in the market. When there are two or more entities with similar trademarks, who offer related goods or services, the entity to use the mark first has seniority over the other users. Furthermore, the senior user has priority, making him or her “entitled to enjoin other ‘junior’ users from using the mark, or one that is deceptively similar to it” in a way that is likely to confuse consumers. But under certain circumstances a trademark owner can claim priority over a mark by relying instead …

An Artificial Intelligence Model For Predicting Hospital Readmission Using Electronic Health Records Data, Rezarta Cara, Klodian Dhoska, Fjona Cara, Fredrick Kayusi, Linety Juma

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study investigates the application of a machine learning model—specifically the Light Gradient Boosting Machine (LightGBM)—to predict 30-day hospital readmissions using structured electronic health record (EHR) data. Hospital readmissions remain a critical challenge in healthcare systems, often indicating gaps in continuity of care and contributing to higher costs. By leveraging demographic, clinical, and diagnostic variables from 350 anonymized patient records, the model aimed to accurately identify individuals at high risk of readmission. Key features included age, number of previous admissions, length of stay, number of medications, chronic disease status, and gender. Data preprocessing, model training, and evaluation were conducted using …

Optimizing Hospital Operational Efficiency Using Ai: A Multi-Objective Nsga-Ii Model For Real-World Medical Data In Syria, Khder Alakkari, Bushra Ali, Teba Majed Hameed

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study presents an AI-driven multi-objective optimization approach using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to enhance hospital operational efficiency in Syria. Using real-world data from the Tishreen University Hospital over a 60-day period, the research addresses three conflicting objectives: minimizing average patient waiting time, reducing daily operational costs, and maximizing the number of patients treated. Six key operational variables were selected to build the optimization model, including bed availability, physician count, and daily admissions. The NSGA-II algorithm successfully generated a set of Pareto-optimal solutions, each reflecting different trade-offs among the objectives. Statistical analysis and visualizations confirmed the complexity …

Reimagining Intelligence: A Comprehensive Review Of Human-Centric Ai Systems And Their Societal And Healthcare Integration, Zakaria Benlalia, Ghada Al-Kateb, Mourad Mzili, Konstantina Diamanti

Mesopotamian Journal of Artificial Intelligence in Healthcare

Human-Centric Artificial Intelligence (HCAI) is rapidly emerging as a transformative paradigm, shifting the focus of AI development from mere algorithmic optimization to ethical alignment, user trust, and societal integration most notably within the critical domain of healthcare. This review offers a comprehensive examination of the principles, architecture, challenges, and future directions underpinning HCAI, with an emphasis on its applications in health-related contexts. We begin by exploring the conceptual foundations of human-centricity, including core values such as transparency, fairness, autonomy, and privacy, all of which are essential in sensitive environments like clinical decision-making and patient data management. The paper then surveys …

Prediction Of Cardiac Arrest Using A Hybrid Voting Classifier Combining Random Forest And Support Vector Machine, Ahmed Hamid Elias, Amr Badr, Raad S. Alhumaima

Mesopotamian Journal of Artificial Intelligence in Healthcare

Early and adequate identification of patients at risk of cardiac arrest remains a fundamental challenge in medical environments. Within this piece of work, we design and evaluate a hybrid machine-learning pipeline integrating Random Forest (RF) and Support Vector Machine (SVM) classifiers by soft voting to detect cardiac arrest occurrences from a publicly available dataset of 303 patient records with 13 clinical features. After median imputation and data cleaning, continuous features were normalized and the cohort was divided into 70 % training and 30 % test sets. RF scored 97 % with an AUC of 1.00 on its own, and SVM …

Optimizing Decision Tree Classifiers For Healthcare Predictions: A Comparative Analysis Of Model Depth, Pruning, And Performance, Hussein Alkattan, Ali Subhi Alhumaima, Mohammed Shakir Mohmood, Ghassan Dhahir Mohammed Al-Thabhawee

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study presents of Decision Tree classifiers for predictive modeling in medicine, focusing on model depth optimization, pruning techniques, and performance evaluation. On the basis of a synthetic healthcare dataset containing over 55,000 records, each with features such as age, gender, blood type, bill amount, and medical condition, we investigate the impact of varying tree depth from 1 to 5 on predictive accuracy, interpretability, and generalizability. Shallow models have strong transparency but poor classification strength, and deep models obtain stronger interactions but suffer from overfitting. With pruning, we find a balance between model simplicity and precision and yield strong classifiers …

Retinal Vessel Image Segmentation Based On Guided Filter And Neural Networks, Ibrahem Al-Jadir, Jawad S. Hameed, Husam Yahya, Dalia N. Al-Oboudi

Mesopotamian Journal of Artificial Intelligence in Healthcare

Accurate segmentation of retinal blood vessels is essential for the early diagnosis and monitoring of various ophthalmic and systemic diseases. This work shows how to use a modified U-Net architecture to improve how retinal blood vessels are segmented. The method uses rolling guidance filters with two different sets of parameters to make the edges of the vessels sharper and make it easier to tell them apart. Separate U-Net models process each filtered image independently, and then the outputs are combined to make the final segmentation result. Both networks are trained at the same time using a shared loss function. Tests …

Arcadia Magazine, 2025-01

Alumni Magazine

No abstract provided.

Why Should I Stay? Canadian Black Youth And Public Libraries, Amber Matthews

STEMPS Faculty Publications

This study used narrative inquiry and critical approaches to race to explore Black youth perceptions of public libraries and community-based programs. The study was conducted in Ontario with youth aged 13 to 24 and parents of youth. Data was drawn from semi-structured interviews with youth and parents and an arts-based qualitative tool. Libraries were identified as safe and welcoming community spaces. However, youth feel poorly represented and seek youth programs with a race-conscious and inclusive approach. Core recommendations include equitable approaches to representation, strengthening relationships with partner organizations, and addressing performative approaches to inclusion.

Designing A Tpack-Based Mobile Learning Model For Biology Education Using Nominal Group Techniques, Cik Jamaliah Abd Manaf, Shakinaz Desa, Muhammad Ikhwan Mat Saad, Helen Crompton

STEMPS Faculty Publications

Mobile learning (m-learning) enhances STEM education, particularly in biology, by supporting visualization and interaction. However, a structured framework integrating technological, pedagogical, and content knowledge (TPACK) is essential. This study designs a TPACK-based mobile learning model for biology using the Nominal Group Technique (NGT). A workshop with 10 experts identified seven key components and 67 elements, with nine elements rejected due to low consensus. The validated framework will guide model development using Interpretive Structural Modelling (ISM) to enhance critical thinking, collaboration, and digital citizenship, ultimately fostering effective mobile learning environments for biology education.

Technology Integration In Online Feminist Pedagogy, Xinyue Ren

STEMPS Faculty Publications

Feminist pedagogy refers to a liberatory way of teaching to develop democratic and transformative learning experiences in which students can be empowered to make a social change (Grissom-Broughton, 2020). Previous research showed that feminist pedagogy was often used to guide course design and development in various disciplines, such as music, art, language, and environmental education (Cannizzo, 2021; Grissom-Broughton, 2020; Jespersen, 2014; Springgay & Zaliwska, 2017). For example, in music education, instructors increased the representations of multicultural voices in course materials and applied in-depth discussions and essays as learning assessments to develop critical and reflective thinking among students. In a feminist-oriented …

The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis

STEMPS Faculty Publications

Artificial Intelligence (AI) is reshaping the landscape of knowledge representation. There is an increasingly strong bidirectional relationship, between AI techniques and ontologies. AI techniques revolutionized traditional, manual ontology development and contribute to automated ontology construction, while ontologies enhance the performance of AI systems and their semantic accuracy. Through a comprehensive review of current literature, this paper aims to examine: i) how Machine Learning (ML) techniques contribute to the automated construction, refinement, and validation of ontologies; ii) the most widely used and effective ML approaches for ontology construction; iii) how domain-specific requirements influence the selection and adaptation of AI techniques for …

Exploring The Impact Of Generative Ai Chatgpt On Critical Thinking In Higher Education: Passive Ai-Directed Use Or Human-Ai Supported Collaboration?, Nesma Ragab Nasr, Chih-Hsiung Tu, Jennifer Werner, Tonia Bauer, Cherng-Jyh Yen, Laura Sujo-Montes

STEMPS Faculty Publications

Generative AI is weaving into the fabric of many human aspects through its transformative power to mimic human-generated content. It is not a mere technology; it functions as a generative virtual assistant, raising concerns about its impact on cognition and critical thinking. This mixed-methods study investigates how GenAI ChatGPT affects critical thinking across cognitive presence (CP) phases. Forty students from a four-year university in the southwestern United States completed a survey; six provided their ChatGPT scripts, and two engaged in semi-structured interviews. Students’ self-reported survey responses suggested that GenAI ChatGPT improved triggering events (M = 3.60), exploration (M = 3.70), …

Bridging The Gap: The Role Of Parent-Teacher Perception In Child Developmental Outcomes, Mckayla Jensen, Mikaela J. Dufur, Jonathan A. Jarvis, Shana L. Pribesh

STEMPS Faculty Publications

Background/Objectives: Time spent with parents and educators encompasses a large portion of a child’s waking hours, with the home and early childhood education and care serving as two of the first settings in which children develop social and cognitive abilities. While previous studies have used social and cognitive tests to examine antecedents of child behavior, we extend such studies to take into account the congruence and incongruence of parents’ and teachers’ views on those antecedents. We examine the importance of parent-teacher alignment on the perceptions of a child’s personality and abilities in early development. Methods: Parents and teachers of 2968 …

Addressing Anti-Black Racism In Library And Information Science Curriculum, Amber Matthews

STEMPS Faculty Publications

This paper explores the development of the graduate course Anti-Racism in Library and Information Science that was piloted at Western University in 2022 and 2023. The one-semester (13-week) course was designed with Black-led community organizations and students contributed to anti-racist information and memory work through experiential learning partnerships. The course used critical Library and Information Science (LIS) literature alongside Black Canadian scholarly perspectives that were grounded in anti-oppression and anti-racism frameworks. The course goals were for students to develop an understanding of how race and other structural inequities inform lived experiences and tools to support collaborative community-led projects. The LIS-tailored …

Assessing The Impact Of Substituting Interaction Types: An Empirical Study Of The Interaction Equivalency Theory, Scott Hauert, Tian Luo, Cherng-Jyh Yen

STEMPS Faculty Publications

Studies on learner–learner and learner–instructor interaction provide insight into the preferences and perceived effects of interaction types. However, evidence of the impact on measured performance resulting from substituting learner–content interaction for learner–learner interaction is sparse. Using an experimental design, this study examined the impact of substituting interaction types on perception of workload, perception of learning, and measured performance in an online, asynchronous, undergraduate-level setting of formal distance education. The results of this study showed (a) learner–learner interactions were perceived to be significantly more work than learner–content interactions, (b) learner–content interactions were perceived to be significantly more helpful in learning the …

Using Machine Learning To Enhance Interaction And Creativity Among Children By Using The Scratch And Mblock Programming Languages And Many Different Kids’ Machine Learning Platforms For Designing A.I Programs, Amani Y. Noori

Mesopotamian Journal of Computer Science

Artificial intelligence (AI) and machine learning (ML) technologies have experienced substantial growth in the last decade, affecting billions of individuals across all facets of contemporary life. This trend of AI's expanding influence is expected to persist. The increasing significance of AI and ML in computer science and society supports the integration of AI and ML principles at an early stage.ML can be made more approachable and interesting for children by utilizing beginner-friendly kids’ programming languages like scratch. We design models for incorporating machine learning techniques using scratch and mblock programming languages to recognize images and text. These models are created …

Increasing Serious Illness Conversations In Patients At High Risk Of One-Year Mortality Using Improvement Science: A Quality Improvement Study, Kanishk D. Sharma, Sandip A. Godambe, Prachi P. Chavan, Agatha Parks-Savage, Marissa Galicia-Castillo

Department of Family and Community Medicine Faculty Publications

Background: Serious illness conversation (SIC) in an important skillset for clinicians. A review of mortality meetings from an urban academic hospital highlighted the need for early engagement in SICs and advance care planning (ACP) to align medical treatments with patient-centered outcomes. The aim of this study was to increase SICs and their documentation in patients with low one-year survival probability identified by updated Charlson Comorbidity Index (CCI) scores. Methods: This was a quality improvement study with data collected pre- and post-intervention at a large urban level one trauma center in Virginia, which also serves as a primary teaching hospital to …

Loss Of Endogenous Circadian Clock Function In Mice Alters Respiratory Cycle Timing In A Time Of Day- And Sex-Specific Manner, Aaron A. Jones, Deanna M. Arble

Biological Sciences Faculty Research and Publications

Resting breathing and ventilatory chemoreflexes are regulated in a 24-hr manner by the endogenous circadian clock. However, it is unclear how circadian biology influences different phases of the breath-to-breath respiratory cycle which are predominantly controlled by pontomedullary regions of the brainstem. Here, we performed whole-body plethysmography during quiet wakefulness in young adult male and female mice lacking the core clock gene Brain and Muscle Arnt-like 1 (BMAL1) to determine the extent to which the molecular clock affects respiratory cycle timing and ventilatory airflow mechanics. Breath waveform analysis revealed that male BMAL1 knockout (KO) mice exhibit time of day-specific differences in …

Long-Term Increases In Wing Length Occur Independently Of Changes In Climate And Climate-Driven Shifts In Body Size, Tiffany Dias, Nathan P. Lemoine, Scott W. Yanco, Marketa Zimova, Rachael A. Bay, Brian C. Weeks

Biological Sciences Faculty Research and Publications

Recent widespread reductions in body size across species have been linked to increasing temperatures; simultaneous increases in wing length relative to body size have been broadly observed but remain unexplained. Size and shape may change independently of one another, or these morphological shifts may be linked, with body size mediating or directly driving the degree to which shape changes. Using hierarchical Bayesian models and a morphological time series of 27 366 specimens from five North American migratory passerine bird species, we tested the roles that climate and body size have played in shifting wing length allometry over four decades. We …

Global Decoupling Of Functional And Phylogenetic Diversity In Plant Communities, Stefan A. Schnitzer

Biological Sciences Faculty Research and Publications

Plant communities are composed of species that differ both in functional traits and evolutionary histories. As species’ functional traits partly result from their individual evolutionary history, we expect the functional diversity of communities to increase with increasing phylogenetic diversity. This expectation has only been tested at local scales and generally for specific growth forms or specific habitat types, for example, grasslands. Here we compare standardized effect sizes for functional and phylogenetic diversity among 1,781,836 vegetation plots using the global sPlot database. In contrast to expectations, we find functional diversity and phylogenetic diversity to be only weakly and negatively correlated, implying …

Improvement Of Internet Of Things (Iot) Interference Based On Pre-Coding Techniques Over 5g Networks, Inas F. Jaleel, Rasha S. Ali, Ghassan A. Abed

Mesopotamian Journal of CyberSecurity

The advent of 5G technology has revolutionized wireless communication, offering unprecedented data rates, reduced latency, and enhanced connectivity. A critical component driving these advancements is Multiple-Input Multiple-Output (MIMO) technology. MIMO utilizes multiple antennas at both the transmitter and receiver ends to improve communication performance. In the context of the Internet of Things (IoT), MIMO plays a pivotal role in enhancing network efficiency, reliability, and capacity and can improve system capacity and reduce interference between different users. By leveraging MIMO, IoT devices can achieve higher data throughput and better signal quality, even in challenging environments. This is particularly important for IoT …

Data Mining And Machine Learning-Based Healthcare Monitoring In Cloud-Iot, Sarah Amer, Rania Hazim, Wassan Kader

Mesopotamian Journal of CyberSecurity

Healthcare monitoring Cloud-IoT systems use data mining and machine learning methods to analyse patient data in real-time from linked devices. By offering insights for the early diagnosis of anomalies and individualized treatment suggestions, this strategy improves healthcare management. In this research first the Collect and Load the Clevant Heart Disease Dataset for Data Collection Process. Next, preprocess the loaded data using the Synthetic Minority Oversampling Technique (SMOTE), and then the feature extraction process is done using the Principal Component Analysis (PCA) Method. In this case, the characteristic must be extracted by feeding a specific column. The classification procedure is then …

Department Of Computer Engineering, University Of Diyala, 32001 Diyala, Iraq., Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel

Mesopotamian Journal of CyberSecurity

Android devices are rapidly being used, which makes it easy for the malware threat to rise to higher levels. This ever-growing problem has prompted the need to enhance detection systems as far as these devices are concerned. Standard techniques of machine learning (ML) are sufficient from the point of view of their speed for searching patterns and behaviors of contemporary malware; however, it is more important to have effectively enhanced methods. The purpose of this paper is to expand the utilization of Android malware identification via artificial neural networks (ANNs) and compare its efficiency with that of other ML methods. …

Antdroidnet Cybersecurity Model: A Hybrid Integration Of Ant Colony Optimization And Deep Neural Networks For Android Malware Detection, Riyadh Rahef Nuiaa Al Ogaili, Osamah Adil Raheem, Mohamed H Ghaleb Abdkhaleq, Zaid Abdi Alkareem Alyasseri, Zaid Abdi Alkareem Alyasseri, Ali Hakem Alsaeedi, Yousif Raad Muhsen, Selvakumar Manickam

Mesopotamian Journal of CyberSecurity

Malware detection is a vital problem, and efficient methods that can efficiently detect malware are needed. The increasing use of mobile computers makes malware detection a vital part of security in an era where smartphones have come to play a key role in many of our daily lives. Earlier approaches, however, suffer from high false positive rates; they are not scalable for larger databases, or they are not amenable to adapt well to novel zero-day malware. For these reasons, the demand for more sensitive and flexible detection models is high. In this study, we develop a hybrid mobile malware detection …

Improved Blockchain Technique Based On Modified Slim Algorithm For Cyber Security, Sarah Mohammed Shareef, Rehab Flaih Hassan

Mesopotamian Journal of CyberSecurity

The number of cybersecurity incidents is increasing, and the cost of a security breach has a catastrophic financial effect. The existing real estate information systems require more robust and resilient cybersecurity solutions to secure hardware, software, and databases. Cybersecurity often relies on user behavior. Phishing attacks and social engineering can bypass blockchain security, highlighting the need for robust user education and awareness. Many blockchain networks face challenges in handling a high volume of transactions. Solutions that work well on a small scale may not perform efficiently as the network grows, leading to delays and increased costs. A secure system is …

Endogenous Self-Peptides Guard Immune Privilege Of The Central Nervous System, Min Woo Kim, Wenqing Gao, Cheryl F Lichti, Xingxing Gu, Taitea Dykstra, Jay Cao, Igor Smirnov, Pavle Boskovic, Denis Kleverov, Andrea F M Salvador, Antoine Drieu, Kyungdeok Kim, Susan Blackburn, Clair Crewe, Maxim N Artyomov, Emil R Unanue, Jonathan Kipnis

2020-Current year OA Pubs

Despite the presence of strategically positioned anatomical barriers designed to protect the central nervous system (CNS), it is not entirely isolated from the immune system