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Maine Law Magazine - Issue No. 100, University Of Maine School Of Law

Maine Law Magazine

Features

• Maine Law’s Privacy Program Continues to Innovate
  How Maine Law’s privacy and innovation programs are preparing students for emerging legal challenges.

• New Business & Law Clinic
  Strengthening Maine’s economy one startup at a time.

• Global Experiential Learning
  From the Arctic Circle to U.N. climate negotiations, students engage with environmental law where it happens.

• Rural Access to Justice
  The Rural Practice Clinic’s impact on Maine’s growing justice gap.

• Law & Conservation Efforts
  How Maine Law alumni steward change and safeguard the future through environmental advocacy.

• Supporting Maine’s Vulnerable
  The Refugee & Human Rights Clinic expands access to justice across Maine. …

Factors That Impact K-6th Grade Teachers’ Sense Of Self-Efficacy: A Mixed Methods Study, Becky A. Eckburg

West Chester University Graduate Theses, Dissertations, and Final Projects

Although there have been efforts to narrow the "achievement gap," research shows that the academic achievement levels of students in low socioeconomic school settings are likely to be significantly lower than the academic achievement levels of students in higher socioeconomic school settings (Babayiğit et al., 2021; Rahman et al., 2024). Studies also show that teachers have a significant impact on their students' growth, no matter what their academic setting may be (Petek & Pope, 2023), and that collective teacher self-efficacy is a significant factor in positive student achievement (Hattie, 2008). If targeted professional development could support teachers' self-efficacy, student achievement …

Structures Of Fantasy In Terry Gilliam's 'Time Bandits', Sean Fash

West Chester University Graduate Theses, Dissertations, and Final Projects

Terry Gilliam’s use of fantasy genre conventions in his filmography is obvious in presence, but elusive in understanding.  Time Bandits, as an early entry into this filmography, simultaneously seems to mock and embody these genre conventions.  This paper seeks to find a way to understand Time Bandits on a structural level through existing frameworks in fantasy criticism and to see what deeper meanings the film holds behind its silly, fantastical presentation.  These structural templates of analysis are John Clute’s “full fantasy model” from his Encyclopedia of Fantasy and Farah Mendlesohn’s “portal quest fantasy” from her Rhetorics of Fantasy.  By deconstructing …

From Pañales To Partnership: An Ethnographic Investigation Of Knowledge, Gender, And Power Within A Family Literacy Program, Sara Mohler

West Chester University Graduate Theses, Dissertations, and Final Projects

Within research on family literacy programming (Lynch & Prins, 2021), few studies bring together assets-based perspectives on knowledge and power alongside critical feminist lenses. This qualitative case study (Dyson & Genishi, 2005; Yin, 2018) informed by ethnography (Alonso Bejarano et al., 2019; Desmond, 2014; Günel & Watanabe, 2024) aimed to understand the culture of one family literacy program serving primarily Mexican-American families, named here the Treehouse Preschool, giving particular attention to the intersecting elements of knowledge, gender, and power as they are enacted across the roles and relationships of families and personnel participating in in the program. Data for this …

Prevalence And Incidence Of Heart Failure Phenotypes Among Transgender And Gender-Diverse Adults In The United States, Ian K. Everitt, Emily K. Quinn, Meredith S. Duncan, Chris Grasso, Sari L. Reisner, Guneet K. Jasuja, Tonia Poteat, Ayelet Shapira-Daniels, Howard Cabral, Vin Tangpricha, Michael K. Paasche-Orlow, Emelia J. Benjamin, Monica Mukherjee, Carl G. Streed

Biostatistics Faculty Publications

BACKGROUND: Prevalent and incident heart failure (HF) and its comorbidities have not been characterized in transgender and gender-diverse (TGD) populations. This study determines the prevalence and incidence of HF phenotypes by gender identity. METHODS: A retrospective cohort analysis was performed using deidentified administrative claims from the Optum Labs Data Warehouse (2006-2022). TGD adults and a sample of demographically similar cisgender comparators were identified using a validated algorithm, and gender identity was categorized as cisgender man, cisgender woman, transmasculine, transfeminine, or unclassified TGD. Prevalent and incident HF, including systolic, diastolic, and unclassified phenotypes, were assessed using diagnosis codes. Multivariable logistic and …

Unexpected Longevity In Myasthenia Gravis, Bhupendra O. Khatri, Scott Schutten, Sergey Tarima

Biostatistics Faculty Publications

Background: This study compares age at death in patients with myasthenia gravis (MG) and multiple sclerosis (MS) with the general U.S. population and examines age at death patterns during a period preceding modern high-efficacy therapies. Objective: To compare age at death among individuals with MG and MS with the general population and assess differences in age at death between MG and MS. Design: Retrospective population-based study using death certificate data from four U.S. states (Florida, Wisconsin, Texas, and New York) for 2000, 2005, 2010, and 2015. Methods: Individuals with MG or MS listed on death certificates were identified. Age at …

Catwalk Xt Enables Sensitive Detection Of Locomotor Deficits After C2 Hemisection And Integrates Readily Into Ongoing Experimental Workflows In Adult Female Rats, Aaron L. Silverstein, Christopher M. Calulot, Christopher J. Mclouth, John C. Gensel, Warren J. Alilain

Biostatistics Faculty Publications

Over half of all spinal cord injuries (SCIs) in the United States occur at the cervical level and often cause both life-threatening breathing dysfunction and profound locomotor deficits. Although the C2 hemisection (C2Hx) model is vital for study of breathing dysfunction after experimental SCI, post-C2Hx locomotor deficits have only been assessed by metrics such as the Martínez Scale and ladder tests, which require time-intensive scoring by human observers. However, the CatWalk XT Gait Analysis system (Noldus Information Technology) delivers automated, quantitative assessment of interlimb coordination, gait cycle, and paw function, providing robust locomotor data in a time-efficient and practical manner. …

Integration Of Community-Engaged Research Technology And Methods To Guide Tobacco Regulatory Science In Rural Communities, Melissa H. Abadi, Stephen R. Shamblen, Mary Kay Rayens, Kirsten T. Thompson, Amy Wildman, Kathy Rademacher, William Wieczorek, Raphael Nishimura, Shyanika W. Rose, Mikhail N. Koffarnus, Seth Himelhoch, Ellen J. Hahn

Biostatistics Faculty Publications

Objective – This study aims to build a rural Appalachian cohort to examine how US Food and Drug Administration (FDA) Center for Tobacco Products (CTP) regulatory policies influence tobacco and nicotine product use across levels of rurality. Methods – The AppalTRUST (Appalachian Tobacco Regulatory Science Team) Cohort integrates four inter-connected Community-engaged Research + Technology (CEnRT) elements to support recruitment and retention: (1) building trust and cultural relevance; (2) addressing barriers to participation in research; (3) focusing on ethics and confidentiality; and (4) fostering ongoing and consistent collaboration between the scientific and field teams. The study uses a dual sampling design …

Raising The Profile Of Collaborative Biostatisticians In Team Science, Margaret R. Stedman, C. Christina Mehta, Emily Slade, Patricia L. Hibberd, Glenn M. Chertow, Robert H. Podolsky, Sowmya R. Rao

Biostatistics Faculty Publications

Recent emphasis on transdisciplinary teams in science offers an opportunity for biostatisticians to assume roles beyond data management and analysis. Biostatisticians contribute to all phases of research, from hypothesis formulation and rigorous study design to data analysis and interpretation. Yet, their contributions are often underrecognized. We argue for better integration of biostatisticians in research training and team structures. Postgraduate physician-scientist training should include mentorship from biostatisticians and education on collaborative skills. Fully integrating biostatisticians as co-investigators improves rigor, reproducibility, and innovation. Institutional support, including protected time and updated promotion criteria, is essential to support sustained collaboration. Structural changes must address …

Rethinking Team Science Metrics Through Collaborative Guideposts, Kristen J. Mcquerry, Kelsey Karnik, Megan E. Hall, Caitline Phan, Yana Feygin, Emily Slade

Biostatistics Faculty Publications

Introduction – The increasing reliance on interdisciplinary and transdisciplinary teams has reshaped how science is conducted, yet evaluating the success of such teams remains a persistent challenge. Traditional metrics, such as publication counts, impact factors, and citation indices, fail to capture the full scope of team contributions, particularly in contexts where success may be defined by community engagement, mentorship, or long-term collaboration. Methods – In this Perspective, we introduce Collaborative Guideposts, a framework designed to align success metrics with a team’s organizing priorities. We illustrate this approach through two contrasting team models from a biostatistical collaboration center: Team A, a …

The Influence Of Support From Family, Friends, And Community On Perceived Mental Health Status In Diabetes, Courtney L. Ortz, Meredith S. Duncan, Oluwatosin Leshi, Suraksha Khanal, Brittany Smalls

Biostatistics Faculty Publications

Strong social support is a protective factor in diabetes and mental health management. The purpose of this study was to examine the influence of the type of support on perceived mental health status among people with diabetes. We used data from the 2021 Household Component of the Medical Expenditure Survey (MEPS). Regression models assessed the association between mental well-being (outcome) and expected help from family, friends, and the community (exposure). Support from both friends and family were significantly associated with better mental well-being, adjusting for covariates. Secondary analyses showed that those who reported greater anticipated support from family were more …

Body Mass Index Has No Impact On Complications And Mortality For Patients With Stage Iv Pancreatic Ductal Adenocarcinoma, Ren Bryant, Hannah Darnell, Megan Hall, Kelsey N. Karnik, Kristen J. Mcquerry, Ruben R. Plentz

Biostatistics Faculty Publications

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of United States (USA) cancer death. Overweight and obesity developing into a growing global medical and socio-economic problem, affecting approximately 42% of adults in the USA population. The aim of our analysis was to evaluate the influence of overweight and obesity on complications and clinical outcome in patients with stage IV PDAC.

Methods: We retrospectively reviewed electronic health records of patients diagnosed with stage IV PDAC (n=162) who followed with the University of Kentucky from January 2017–October 2024. Comparisons were based on the body mass index (BMI): low BMI …

The Multidimensional Impacts Of Poverty On Adolescent Outcomes, Klarence Baker

Graduate Research Papers

Poverty is a pervasive, multidimensional phenomenon that extends beyond financial scarcity to encompass a lack of both tangible and intangible resources necessary for healthy development. This research article synthesizes current literature to explore the profound impacts of poverty on adolescents specifically examining how economic hardship influences long term outcomes in financial attainment, educational success, and physical and mental health. This study investigates how cooccurring risk factors can disrupt neural development and social trajectories. The primary purpose of this study is to assess the duration and severity of poverty exposure and its lasting effects extending into adulthood. This research examines three …

Mapping The Geography Of Economic Espionage In The United States (2000–2025): An Applied Counterintelligence And Spatial Analysis, David A. Turner

Graduate Research Papers

This Graduate Research Project examines whether economic espionage incidents within the United States exhibit structured geographic patterns aligned with innovation ecosystem density. Using a verified dataset of 135 publicly documented economic espionage and foreign-linked trade secret theft cases between 2000 and 2025, this study applies Geographic Information Systems (GIS) analysis to evaluate spatial concentration, sectoral prioritization, and foreign nexus distribution.

Kernel Density Estimation and state-level aggregation reveal disproportionate clustering within innovation-dense regions, including California, New York, and major Midwestern industrial corridors. Aerospace and defense technologies, energy technologies, and semiconductors and microelectronics collectively account for 55.6 percent of all documented cases. …

Digital Lover: Insecure Attachment Styles And Romantic Parasocial Relationship Among Chinese Female Otome Game Playersdigital Lover: Insecure Attachement Styles And Romantic Parasocial Relationship Among Chinese Female Otome Game Players, Weifan (Kyrie) Zhang M.S.

Selected Full Text Dissertations, 2011-

The existing literature has explored the relationship between insecure attachment styles and parasocial relationships, particularly focusing on traditional media such as television. However, it has largely overlooked the novel form of media represented by contemporary Chinese otome games, which offer an idealized digital environment potentially more appealing to players with insecure attachment styles. Moreover, previous studies have not sufficiently differentiated between general parasocial interactions and the specific nuances of parasocial romantic relationships unique to romantic video games (RVGs). This study seeks to bridge these gaps by examining the psychological underpinnings of Chinese female players' engagement with female-oriented romantic video games. …

Skin Type Diversity In Image Datasets, Neda Alipour

Doctoral

Image-based AI systems that analyse human skin are increasingly used in healthcare and computer vision applications. However, many human skin-based image datasets do not provide reliable information about skin type, making it difficult to assess whether these systems perform consistently across the full spectrum of skin colour. The objective of this thesis is to examine how skin type diversity is represented and measured in image datasets, and to evaluate the reliability of image-based skin type measurement methods under different imaging conditions. Using publicly available skin lesion image datasets as a well-defined and widely used sub-class of skin image datasets, this …

Selling Ideals: Sexualization In Teen Girl Magazines, 2007-2017, Megan Coogan

Honors Theses - Providence Campus

Magazines are made to sell more than just a product; they sell lifestyles and ideals. Teen girl magazines target adolescents starting as young as twelve years old, but is the content in its pages appropriate and identifiable for that demographic? This study investigated how levels of perceived sexualization changed between 2007, 2012, and 2017, in Seventeen and Teen Vogue magazines. A decrease in perceived sexualization was expected across the ten-year period of time. This window of time reflects the last ten years of publication for both magazines. Research was conducted by creating and utilizing a grading system for non-explicit sexualized …

The Lived Experience Of Intimate Partner Violence For Females In Emerging Adulthood: A Qualitative Study, Laurel Dobkin M.S.

Selected Full Text Dissertations, 2011-

Emerging adulthood is the developmental period between ages 18 to 25 where individuals begin to explore their worldviews and develop intimate relationships. This period is important for developing a sense of identity and self (Arnett, 2000, 2014). During this period, negative events or relationships, such as intimate partner violence (IPV), may have detrimental effects (Erikson, 1968; Barreto & Frazier, 2012). While literature suggests that IPV has high rates and negative consequences in emerging adulthood (Bhattacharjee & Gopal, 2022; Centers for Disease Control and Prevention [CDC], 2024; Shen & Kusunoki, 2019), there is little research on the subjective experience of females …

Flood Risk Prediction System For Irish River Networks, Fernando Adalberto Naatz Heringer, Hugo Rodrigues De Freitas

ICT

Flooding costs the Irish economy more than 300 million euros annually; however, the hydrometric and meteorological data needed to predict dangerous river rises is already collected and freely available. This project applies machine learning to a decade of hourly observations from OPW Station 09001 on the River Liffey at Leixlip and Met Eireann Casement Aerodrome to build a flood risk prediction system with a 72-hour forecast horizon.

A two-phase modelling pipeline was built following the CRISP-DM framework. Phase 1 compared LSTM and GRU recurrent neural networks on the task of forecasting the river level in metres 72 hours ahead. LSTM …

Machine Learning System For Cereal Yield Prediction In South America., Victor Gabriel Oliveira, Kelvin Henrique Ferreira Dumas

ICT

This project developed a machine learning solution to predict cereal yield in South America using FAOSTAT agricultural data. The objective was to estimate yield in kg/ha for rice, maize, and wheat based on variables such as country, crop type, year, harvested area, producer price, pesticide use, and nutrient indicators.

The project followed the CRISP-DM methodology, covering business understanding, data understanding, data preparation, modelling, evaluation, and deployment. Several regression models were tested, including Random Forest, Gradient Boosting, AdaBoost, XGBoost, KNN, and SVR.

The models were evaluated using MAE, MSE, RMSE, and R² score. The results showed that tree-based ensemble models performed …

A Comparative Analysis Of Supervised Machine Learning Techniques For Predicting It Incident Resolution Time, Ammad Hussain, Hussnain Yaqoob

ICT

IT support teams are facing the persistent challenge in estimating how long an incident will take to resolve. The lack of reliable predictions, planning decisions around staffing, escalation and user communication are largely guesswork. This project set out to address that gap by building a machine learning solution capable of predicting incident resolution time from details available at the point a ticket is logged.

Using the UCI IT Incident Event Log dataset, which contains 141,712 records from a real service management system, the project followed the CRISP-DM framework across six phases from business understanding through to deployment. After thorough data …

A Comprehensive Study Of Sarima And Xgboost Models For Short-Term Traffic Volume Forecasting At A Melbourne Intersection (Victoria), Australia, Douglas Vinicius Dierings, Felipe Fontanive Marques

ICT

Traffic congestion is an increasing challenge in modern cities, impacting transportation efficiency and urban sustainability. This project focuses on short-term traffic volume forecasting, using 15-minute Sydney Coordinated Adaptive Traffic System (SCATS) data collected from the State of Victoria, Australia. The study compares two forecasting approaches: SARIMA, a statistical time-series model, and XGBoost, a decision-tree machine-learning model. Historical traffic data from 2022 to 2024 was analysed to identify traffic patterns, seasonal trends, and peak traffic periods. The models were evaluated for their effectiveness in handling urban traffic behaviour. The results of this study aim to support smarter traffic management, infrastructure planning, …

Identifying New Programme Development Viability, Grant Goodwin

ICT

Higher Education Institutions (HEIs) face the challenge of developing programmes that respond to changing labour market needs while providing graduates with relevant employment opportunities and ensuring institutional financial viability. Rapid technological and economic changes make it increasingly important for HEIs to use reliable data to identify emerging skills and workforce demands. This project explores the use of machine learning and nationally collected employment data to support evidence-based decision-making in higher education programme development. By analysing patterns and relationships within labour market data, machine learning models can help identify areas of growing demand and provide insights into the potential alignment between …

Seasonal Dublin Airport Passenger Arrivals Forecast For The Economy Sector Of Dublin Airport, Roberto Tavares De Oliveira Neto

ICT

Dublin Airport plays a significant role in Ireland’s tourism and commercial sectors, with passenger demand directly influencing retail, hospitality, car rental and other airport-related businesses. Accurate forecasting of passenger numbers can support these sectors in planning marketing activities, managing stock levels and making evidence-based operational decisions. This project develops a monthly forecasting framework for passenger arrivals at Dublin Airport using data from the Central Statistics Office (CSO). Building on previous exploratory data analysis, the study evaluates five time series forecasting approaches: ARIMA, SARIMA, Holt-Winters Triple Exponential Smoothing, TBATS, and an automated model comparison pipeline using PyCaret. The models are assessed …

Machine Learning For Early Obesity Risk Prediction, Giuseppe Cutugno

ICT

Obesity is a major global public health concern, with significant implications for individual health, healthcare systems, and wider economic outcomes. Early identification of obesity risk can support preventive strategies and encourage healthier lifestyle choices before health conditions become more severe. This project develops a machine learning framework for estimating obesity levels using data relating to individuals’ physical characteristics, eating habits, lifestyle behaviours, and demographic factors. Following the CRISP-DM framework, the project examines the structure and limitations of the dataset, including its mixture of objective measurements, survey-based variables, and synthetically generated observations. Two modelling approaches are considered, one including BMI as …

Predicting The Next Recession With Machine Learning, David Heffernan

ICT

Economic recessions can have significant consequences for businesses, households, financial markets, and policymakers, creating a need for improved understanding of the factors associated with economic downturns. This project analyses historical US economic and financial data to examine patterns associated with previous recessionary periods and assess whether machine learning can be used to identify recession risk. The study uses a two-tier analytical approach, combining a macroeconomic dataset covering 1960 to the present with a more detailed dataset from 1987 onwards that incorporates financial markets, house prices, and consumer confidence. Building on previous exploratory analysis, the project develops and evaluates three machine …

Understanding Host Behaviour And Property Review Characteristics Using New York City Airbnb Dataset, Anna Szkwara

ICT

This project applies strategic thinking and the CRISP-DM methodology to analyse Airbnb listings in New York City and identify patterns associated with host performance and market vulnerability. Airbnb has become a major global accommodation platform, creating opportunities for individual hosts while also increasing competition within the short-term rental market. The project focuses on whether data-driven analysis can identify factors that may influence host success and provide useful insights for hosts with less experience or expertise than larger hospitality organisations. The dataset contains 85 variables, many of which require careful evaluation due to redundancy, high cardinality, sensitivity, or limited relevance to …

The Impact Of Strategic Planning On Teachers' Perceptions Of Their Practice: A Mixed-Methods Study, Vivian Robert

Selected Full Text Dissertations, 2011-

Strategic planning is a vital endeavor for school districts across New York State. Often, however, significant human and financial capital is invested in these processes without investigating their impact beyond immediate student outcomes. While student success is the ultimate priority, little attention has been paid to the effect strategic planning has on the practitioners charged with implementing it, specifically teachers. This phenomenological mixed-method case study investigates how strategic planning influences teachers’ perceptions of their practice and identifies how districts can better engage educators to ensure the successful realization of district goals. In this study, district leaders participated in semi-structured interviews, …

Design, Syntheses And Biological Applications Of Fluorescent Probes For Nad(P)H, Hsa And Cellular Microenvironment Sensing, Adenike M. Olowolagba

Dissertations, Master's Theses and Master's Reports

Fluorescent probes have emerged as powerful tools for investigating complex biological processes due to their high sensitivity, selectivity, and capability for real-time, non-invasive imaging. In particular, the detection of key biomolecules such as NAD(P)H, viscosity-related parameters, human serum albumin (HSA), and pH is essential for understanding cellular metabolism, redox homeostasis, and disease progression. In Chapter 2, three coumarin-based fluorescent probes (A–C) were designed, synthesized, and characterized for monitoring NAD(P)H levels in living cells. Probes A and B feature coumarin–cyanine hybrid structures linked via vinyl and thiophene bridges to 3-quinolinium acceptors, respectively, while probe C incorporates a dicyano moiety to replace …

Characterizing Cyber Intrusions In Critical Infrastructure Networks Using Discrete-Event Simulation, Lawrence M. Dilworth

Dissertations, Master's Theses and Master's Reports

Over the past two decades, cybersecurity compliance frameworks such as the North American Electric Reliability Corporation Critical Infrastructure Protection (CIP) have introduced prescriptive measures for protecting power system networks, emphasizing restricted access, segmentation, and minimizing routable exposure. While effective for baseline cyber hygiene, these approaches do not capture system-level risks or adversarial propagation across interconnected infrastructure. In contrast, Cyber-Informed Engineering (CIE), advanced by Idaho National Laboratory, embeds security in system design by considering threat vectors and physical constraints.

Despite CIP guidance, many deployments rely on IP-routable, bidirectional communication that enables handshaking, allowing adversaries to infer reachable targets. This work presents …