Digital Commons Network^™

Challenges To Economic Sanctions In The U.S. Courts, Christine Abely

Fordham International Law Journal

The start of the new Trump term has made more salient calls to amend the International Emergency Economic Powers Act (IEEPA)1 to place limitations on the use of economic sanctions by the executive branch. Though the first Trump administration and the Biden administration both used sanctions in large numbers, they did so in very different manners. This Essay explores the use of sanctions by President Biden and President Trump. It also details the grounds upon which sanctions may be subject to challenges in US courts, and the limits of the US judiciary to impose meaningful restraints on the executive’s use …

Honing The Economic Weapon: Application Of The Prosecutor's "Toolkit" In Sanctions Enforcement, Andrew Adams

Fordham International Law Journal

No abstract provided.

Our Humanity At Stake: The Human Costs Of Economic Sanctions For The Sanctioner, Alexandra Hofer

Fordham International Law Journal

No abstract provided.

Improving System-Level Outcomes Via Artificial Intelligence Decision Support In Kidney Utilization, Casey I. Canfield, Cihan H. Dagli, Daniel Burton Shank, Krista Lentine, Mark Schnitzler, Henry Randall, V. Sriram Siddhardh Nadendla, Brendon Cummiskey

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transplantation provides patients suffering from end-stage kidney disease a better quality of life and long-term survival. However, over 20% of deceased donor kidneys are not utilized and never transplanted. While this is sometimes medically appropriate, this also reflects missed opportunities. We are designing Artificial Intelligence decision support for the kidney offer process to support both demand at the transplant center and supply at the organ procurement organization. This includes (1) developing deep learning models, (2) evaluating the effect of explainable interfaces, (3) improving fairness in the model output, (4) identifying factors that influence adoption decisions, and (5) conducting a randomized …

Spatial Analysis And Machine Learning Integration For Nutritional Status Mapping Using Ann And Random Forest Models, Desi Anis Anggraini, Fachrul Kurniawan, Fresy Nugroho, Meidya Koeshardianto, Mohammad Iqbal Bachtiar

Knowledge Engineering and Data Science

Nutritional problems among children under five remain a major public health challenge. This research seeks to create a spatially oriented system for evaluating and mapping nutritional status utilizing Artificial Neural Network (ANN) and Random Forest (RF) algorithms. Data obtained from the Sumenep District Health Office included age, weight, height, and gender variables. Both models were trained using a 70:30 data ratio and evaluated with accuracy, precision, recall, and F1-score metrics. The ANN model achieved an accuracy of 95.8%, while the RF model reached 97.7%. Classification results were visualized through a Geographic Information System (GIS) to illustrate spatial distribution and identify …

Time Series Forecasting With Lstm: An Extensive Content Analysis, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao

Knowledge Engineering and Data Science

This paper presents a comprehensive bibliometric and content review of the trend, architecture, and application of long short-term memory (LSTM) models for time series forecasting. The study aims to provide insights into the overall statistics and distribution of papers focused on LSTM for forecasting. Additionally, the research questions address the most highly cited papers based on LSTM approaches in forecasting, the most productive journals in this field, and identifying trends, gaps, summary tasks and their performance, datasets availability, and future research directions for LSTM in forecasting. This paper is a comprehensive review of LSTM for forecasting from 2017 to 2023 …

From Data To Insight: A Machine Learning Approach In Classifying Dairy Cow Productivity Level And Identifying Important Influencing Variables, Fatkhurokhman Fauzi, Achmad Fauzan, Rhendy K P Widiyanto, Khairil Anwar Notodiputro, Bagus Sartono

Knowledge Engineering and Data Science

Identifying influential predictor variables is crucial for enhancing model interpretability in supervised classification. This study applies Permutation Variable Importance (PVI), a model-agnostic approach, to evaluate variable relevance after model fitting. Using data from the 2024 Indonesia Dairy Cow Productivity Survey, this research investigates five classification techniques: (1) Support Vector Machine (SVM), (2) Neural Network (NN), (3) k-Nearest Neighbors (kNN), (4) Naïve Bayes Classifier (NB), and (5) Logistic Regression (LR), to identify which method(s) yield the best performance based on evaluation metrics such as accuracy, sensitivity, and specificity. PVI is employed to identify the most influential predictor variables within the best-performing …

A Hybrid Soft Voting And Stacking-Based Meta-Learning Approach For Sentiment Analysis Of Bangkalan Batik, Moh. Imron Wahyudi, Lailil Muflikhah, Rizal Setya Perdana

Knowledge Engineering and Data Science

Sentiment analysis is an important field in Natural Language Processing (NLP) that focuses on processing consumer opinions to gain useful insights. The information generated from sentiment analysis can be used as a basis for business decision-making, service quality evaluation, and the formulation of more effective marketing strategies. In the local context, Bangkalan Batik, as one of Madura's distinctive cultural products, has high economic value and cultural identity. However, consumer reviews available online, for example through Google Maps, are still rarely utilized optimally by MSMEs as a source of strategic information. Therefore, this study was conducted to develop a sentiment classification …

Mapping Of Product Sales Potential Based On Brands In The East Kalimantan Region Using Hybrid Analytical Framework, Achmad F O Gaffar Mr, Mulyanto Mulyanto Mr, Arief Bw Putra Mr, Muhammad Taufiq Sumadi Mr, Emmilya Umma Aziza Gaffar

Knowledge Engineering and Data Science

In geographically dispersed markets, operational costs should be reflected in sales planning to support accurate performance evaluation. However, such considerations are often neglected in practice. This study proposes a hybrid analytical framework to map brand-based product sales potential, with and without operational cost consideration, using historical sales data from PT Karya Inti Total Anugerah (PT KITA) in East Kalimantan. The framework integrates spatial, statistical, and machine learning techniques. Principal Component Analysis (PCA) is used to reduce the dimensionality of variables related to travel distance, total sales, and units sold, where travel distance represents the primary contributor to operational costs. K-Means …

Comparative Analysis Of Deep Learning Algorithms For Predicting Enso Based On Non-Sequential Sampling Procedure Algorithms, Ria Faulina, Siti Hadijah Hasanah, Nuramaliyah Nuramaliyah, Ika Nur Laily Fitriana

Knowledge Engineering and Data Science

The El Niño–Southern Oscillation (ENSO) is a major climate phenomenon that significantly influences global weather patterns, particularly rainfall and temperature variability across different regions. Accurate ENSO forecasting is therefore essential to support disaster risk mitigation and strategic decision-making in climate-sensitive sectors such as agriculture, fisheries, and water resource management. This study investigates the performance of deep learning approaches for ENSO prediction using a non-sequential sampling procedure on historical climate data. Three models are comparatively evaluated: Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and a hybrid CNN–LSTM architecture. The results demonstrate that the hybrid CNN–LSTM model outperforms the standalone CNN …

Comparative Performance Of Vgg16 And Efficientnetb0-Based Transfer Learning For Brain Tumor Classification, Huzain Azis, Rizqi Ananda Jalil, Abdul Rachman Manga'

Knowledge Engineering and Data Science

The classification of brain tumors using Magnetic Resonance Imaging (MRI) images is essential for early diagnosis but remains challenging due to tumor diversity. This study evaluates the effectiveness of two distinct architectural approaches for feature extraction: VGG16, representing a classic sequential design, and EfficientNetB0, a modern architecture optimized for parameter efficiency through compound scaling. Using a dataset of 2,870 MRI images categorized into four classes, we implemented a static transfer learning strategy by freezing all pre-trained ImageNet weights to act as fixed feature extractors. Features were extracted from specific layers, the final pooling layer for VGG16 and the Global Average …

Ahp–Python Framework For Multicriteria Modeling Of Rice Production In Asean, Mayang Anglingsari Putri, Risqy Siwi Pradini, Anuraga Jayanegara, Alexander Dimas Yonanta Putra

Knowledge Engineering and Data Science

Rice production is a key indicator of food security and agricultural stability in Southeast Asia, especially among Association of Southeast Asian Nations (ASEAN) countries. Despite shared regional goals, disparities in rice production remain, and previous studies mainly rely on descriptive statistics, lacking structured multicriteria decision-making frameworks and computational tools for cross-country comparisons. This study addresses these gaps by proposing an integrated Analytic Hierarchy Process (AHP)–Python framework to evaluate and rank ASEAN rice production from 2013 to 2022. Three criteria are used: Total Production Volume (K1), Production Growth Trend (K2), and Recent Year Performance (K3), capturing both long-term consistency and short-term …

A Bounded Custom Gpt Structures Operational Knowledge For Small-Industry Decision Support, Ikhwan Arief, Alizar Hasan, Nilda Tri Putri, Hafiz Rahmann

Knowledge Engineering and Data Science

Small manufacturing and craft-based firms increasingly use Generative Artificial Intelligence (GenAI) through public chat interfaces, low-cost tools, and informal experimentation. However, these firms often make operational decisions with incomplete records, tacit owner knowledge, fragmented spreadsheets, and limited managerial capacity. Under such conditions, open-ended chatbots may generate fluent but unsafe recommendations by overlooking missing information, contradictory evidence, feasibility constraints, and implementation constraints. This study presents Asisten Cerdas Industri Kecil as a bounded Custom GPT artifact for operational diagnosis, priority selection, and short-horizon action planning in small industries. Using a Design Science Research approach, the study develops a documented artifact corpus comprising …

Is There A Regulator In The Polish Electronic Delivery Market? The Role Of The President Of Uke, Mateusza Chołodecki

internetowy Kwartalnik Antymonopolowy i Regulacyjny (internet Quarterly on Antitrust and Regulation)

This paper examines the regulatory role of the President of the Office of Electronic Communications (UKE) within the electronic delivery market in Poland, focusing specifically on the statutory competencies granted by the Electronic Delivery Act. The paper identifies significant limitations of the President of UKE’s current regulatory scope, by analysing these competencies and their alignment with Poland’s postal and telecommunications regulatory frameworks. The analysis reveals that the regulatory powers of the President UKE that concern electronic delivery services are narrowly defined, primarily covering oversight over tariffs, T&Cs, and operator designation, without broader supervisory authority or clearly articulated regulatory objectives. Consequently, …

Characterizing Heat Transfer Performance In A Slurry Bubble Column Reactor Equipped With A Real Heat Exchanger, Dalia S. Makki, Hasan Sh Majdi, Amer A. Abdulrahman, Abbas J. Sultan, Bashar J. Kadhim, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Abstract: This study examines the impact of equipping a real heat exchanger in a slurry bubble column SBC on instantaneous and local heat transfer coefficients IHTC and LHTC, as well as the overall heat transfer coefficient U, employing advanced heat transfer techniques. The experiments were conducted in a 0.15 m inner diameter Plexiglas SBC with varying gas flowrates Ug (0.14–0.35) m/s at several radial sites along the column's diameter (±0.18, ±0.46, and ± 0.74) and three axial locations (H/D = 2, 3 and 4). To simulate the industrial Fischer–Tropsch bubble column reactor FT-BCR, a real heat exchanger consisting of 18 …

Tumor Microenvironment Immunomodulation By Nanoformulated Tlr 7/8 Agonist And Pi3k Delta Inhibitor Enhances Therapeutic Benefits Of Radiotherapy, Mostafa Yazdimamaghani, Oleg V. Kolupaev, Chaemin Lim, Duhyeong Hwang, Sonia J. Laurie, Charles M. Perou, Alexander V. Kabanov, Jonathan S. Serody

Chemical and Biochemical Engineering Faculty Research & Creative Works

Infiltration of immunosuppressive cells into the breast tumor microenvironment (TME) is associated with suppressed effector T cell (Teff) responses, accelerated tumor growth, and poor clinical outcomes. Previous studies from our group and others identified infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs) as critical contributors to immune dysfunction in the orthotopic claudin-low tumor model, limiting the efficacy of adoptive cellular therapy. However, approaches to target these cells in the TME are currently lacking. To overcome this barrier, polymeric micellular nanoparticles (PMNPs) were used for the co-delivery of small molecule drugs activating Toll-like receptors 7 and 8 …

Umfc #132: A Comprehensive Forensic Case Report, Allison Paige Mitchell

Graduate Student Theses, Dissertations, & Professional Papers

This case report of an individual designated as University of Montana Forensic Case 132 (UMFC 132) serves to partially fulfill the requirements for the Master of Arts (MA) degree in Forensic and Biological Anthropology. UMFC 132 is a complete human skeleton, used as part of the teaching collection in the University of Montana Forensic Anthropology Laboratory. The minimum number of individuals (MNI) of UMFC 132 is 1. The analysis of UMFC 132 was conducted according to bioarchaeological and forensic anthropological standards of skeletal assessment. UMFC 132 was estimated to be a mid-adult, between the ages of [30-40 years] of age …

Workable Seams, Jackson Mills Smith

Graduate Student Theses, Dissertations, & Professional Papers

In Jackson Mills Smith’s Workable Seams, readers encounter the stories, landscapes, and lives of rural Knox County, Indiana, from the oscillating vantage of a Hoosier boy raised with a Cajun sensibility. After relocating from Louisiana to the river bottoms of the crossroad state at a young age, the speaker gradually uncovers a local history only previously understood in fragmentary shards and fading glimpses.

Alternating between semi-lyrical embodied experiences and memories, documentary pieces in conversation with the state’s historical archive, and the retelling of exaggerated local yarns, poetry is a means of inquiry in Workable Seams. Topics range from …

Enhanced Biofuel Cells Based On A Hybrid Enzymatic/Bimetallic Composite For Complete Lactate Catalytic Electrooxidation, Jefferson Honorio Franco, João Victor Bonaldo, Shelley D. Minteer, Adalgisa R. De Andrade

Chemistry Faculty Research & Creative Works

We describe complete lactate electrooxidation in an enzymatic biofuel cell that combines the catalytic action of the bimetallic composite Ru@Pt-CNT and the enzyme oxalate oxidase (OxOx). The Ru@Pt-CNT/OxOx hybrid electrode was 2.0-fold more catalytically active than the electrode containing the bimetallic composite only. During chronoamperometric experiments, the hybrid electrode achieved a 35% higher maximum current density (2.65 ± 0.15 mA cm^-2) than the Ru@Pt-CNT electrode. Electrochemical impedance spectroscopy showed that the hybrid electrode had lower charge transfer resistance than the Ru@Pt-CNT electrode, confirming that OxOx had a high affinity for lactate during the bioelectrocatalytic reaction on the electrode …

Fecal Glucocorticoid Metabolite And T3 Profiles Of Orphaned Elephants Differ From Non-Orphaned Elephants In Zambia, Daniella E Chusyd, Janine L Brown, Steve Paris, Nicole Boisseau, Webster Mwaanga, Moses Kasongo, Lisa Olivier, Stephanie L Dickinson, Bailey Ortyl, Tessa Steiniche, Steven N Austad, David B Allison, Michael D Wasserman

Children’s Nutrition Research Center Staff Publications

Background: Elephants provide valuable insight into how early-life adverse events (ELAEs) associate with animal health and welfare because they can live to advanced ages, display extensive cognitive and memory capabilities, and rely heavily on social bonds. Although it is known that African savanna elephants that experienced ELAEs, such as being orphaned due to human activities, have altered behavioral outcomes, little is known regarding the physiological consequences associated with those stressors.

Methods: We compared fecal glucocorticoid (fGCM) and thyroid (fT3) metabolites as well as body condition scores (BCS) in rescued and rehabilitated orphaned (early-dry season: n = 20; late-dry season: n …

Mapping Epidermal And Dermal Cellular Senescence In Human Skin Aging, Grace T Yu, Clarisse Ganier, David B Allison, Tamara Tchkonia, Sundeep Khosla, James L Kirkland, Magnus D Lynch, Saranya P Wyles

Children’s Nutrition Research Center Staff Publications

Single-cell RNA sequencing and spatial transcriptomics enable unprecedented insight into cellular and molecular pathways implicated in human skin aging and regeneration. Senescent cells are individual cells that are irreversibly cell cycle arrested and can accumulate across the human lifespan due to cell-intrinsic and -extrinsic stressors. With an atlas of single-cell RNA-sequencing and spatial transcriptomics, epidermal and dermal senescence and its effects were investigated, with a focus on melanocytes and fibroblasts. Photoaging due to ultraviolet light exposure was associated with higher burdens of senescent cells, a sign of biological aging, compared to chronological aging. A skin-specific cellular senescence gene set, termed …

Separability Doctrine: Perspectives From China, England And The Model Law, Jia Jun Benjamin Goh

Research Collection Yong Pung How School Of Law

In this article, the author compares the application of the separability doctrine in the People's Republic of China, England and Wales, and select Model Law jurisdictions (including Singapore and Hong Kong). This article argues that the proper scope of the doctrine must include situations of both contractual validity and existence are in question. Additionally, the doctrine should apply in finding that the law of the arbitration agreement is different from the law of the main contract. Finally, the doctrine must also serve to protect party autonomy to shield an arbitration agreement from self defeating main agreements.

A Comparative Analysis Of Artificial Intelligence Regulation: Implications For Singapore, Cheng Kit Kit Pang

Research Collection Yong Pung How School Of Law

In relation to artificial intelligence (“AI”) regulation, Singapore presently adopts a wait-and-see approach, refraining from implementing any hard regulation before 2026. This article is directed at making recommendations for Singapore’s future AI hard regulation and conducts a comparative analysis of the hard AI regulation in the EU, the People’s Republic of China (“China”) and South Korea. This article draws lessons specifically from Asian jurisdictions with similar socio-legal and commercial considerations. In particular, China and South Korea are at the forefront, actively pushing for hard regulation. Key takeaways include the potential drivers for a shift towards hard regulation, the scope and …

Machine Learning Modeling For Hydrolysis Recycling Of Pet Waste, Jie Li, Lanjia Pan, Hossein Abedsoltan, Hailong Wang, Taiyang Liu, Xiangzhou Yuan, Yong Sik Ok, Yin Wang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The hydrolysis of polyethylene terephthalate (PET) into terephthalic acid (TPA) can efficiently recycle waste PET, but achieving high conversion efficiency through smart reaction design remains challenging. To develop a robust and accurate machine learning (ML) model for the in-depth understanding and intelligent design of PET hydrolysis, we compiled a new dataset comprising 942 data points and comprehensive information of 44 variables involved in heating type, acid/base catalyst (ABC), organic solvent (OS), co-solvent (CS), phase transfer catalyst (PTC), and operational conditions. The developed Neural Network model demonstrated the best performance in predicting PET conversion, with a testing determination coefficient (R^{2 …}

Cultivating Confidence, Leila Halawi, Mark Miller, Sam Holley

Publications

Artificial intelligence (AI) is pervasive in scholarly publications, internet sites, and public discourse. AI is a term with broad scope that refers to machines that can learn and perform tasks that typically require human intelligence. The specter of AI intruding into many aspects of aviation has raised alarms, concerns, and prodigious misunderstanding of potential and contemplated applications in systems and processes. The EASA AI Roadmap (EASA, 2023 ), a linear projection with three levels EASA, 2023 extending into 2050, places the human-AI teaming period (through 2035) at Level 2. This suggests a ten-year span to develop the interactive issues to …

Embracing Ai In Higher Education: Redefining Teaching And Learning In The Digital Era, Najem Tala, Leila Halawi

Publications

This research explores the transformative potential of Artificial Intelligence (AI) in education, focusing on its ability to address emerging challenges and revolutionize teaching practices. We critically assess the current educational landscape, evaluate AI's role as a catalyst for educational reform, and examine implementation challenges. Our analysis emphasizes the evolving impact of AI on personalized learning, student engagement, and administrative efficiency and contributes to the growing body of literature on educational technology. The discussion highlights both the opportunities and limitations of AI in education, pointing to critical areas that remain underexplored.

Integrating Sustainability Into Aviation Training: Perspectives From Industry Professionals, Eva Maleviti, Sarah Talley

Publications

This paper is part of a broader research project aimed at identifying the most appropriate training materials, formats, and delivery methods for aviation sustainability content for future aviation professionals, starting from the early stages of their training. The current paper presents the data analysis and results of a short online survey targeting aviation professionals. Specifically, it provides preliminary data on sustainability perspectives from global aviation professionals. Through qualitative analysis, the creation of a baseline from a random sample of aviation professionals offers insight into their perspectives and how they could be influenced toward a more sustainable pathway. Additionally, the paper …

A Maintenance Repair And Overhaul Model For Operational Sustainability; Incorporating Processes And Risks., Linn Guinn, Mary M.H. Woody, Eva Maleviti

Publications

Maintenance, Repair, and Overhaul (MRO) companies are integral to the aviation industry, with the core responsibility of ensuring aircraft remain safe and airworthy. Their role is critical in maintaining the industry’s high standards of performance and safety. To remain competitive, MROs must provide a wide range of services—including inspections, periodic checks, engine overhauls, avionics repairs, fuselage and cabin modifications, and interior refurbishments— while consistently meeting regulatory and safety requirements. Beyond technical compliance, MROs must adopt a quality-driven, continuous improvement approach to manage risks effectively. This requires the integration of processes, programs, and systems aligned with international standards to strengthen resilience, …

Implementation Of A Pediatric Skills And Simulation Workshop Among Rural Nurses, Cassandra Grabiel

Doctor of Nursing Practice (DNP) Practice Innovation Projects

No abstract provided.

Impact Of Acuity-Based Assignments On The Satisfaction And Burnout Of Inpatient Rehabilitation Nurses, Madelyn Miller Smith

Doctor of Nursing Practice (DNP) Practice Innovation Projects

Background: With half of healthcare workers reporting burnout, job dissatisfaction and burnout are nursing epidemics. Staffing shortages and heavy workloads are leading dissatisfiers. Acuity-based assignments (ABAs) can predict patient needs and equitably distribute workload among nurses.
Local problem: Nurses of a 21-bed inpatient rehabilitation facility identified burnout related to workload. There was no standard practice for creating assignments, and the existing acuity measure was not rehab-specific.
Methods: An ABA tool was implemented over 12 weeks. Nurse satisfaction and burnout were measured with an abbreviated Copenhagen Burnout Inventory and the Nurse Satisfaction with the Quality of Care Scale, which were administered …