Poster Sessions

Muslim women are leaders, not only in their ethno-religious communities, but also in mainstream American social and political spaces.  My research seeks to fill the gap in the literature about Muslim women by focusing on Muslim American women’s leadership roles in both their ethno-religious communities and in mainstream American society.  

Using ethnographic participant observation and qualitative interviews, I concentrate on how their roles as activists, community organizers, and political leaders significantly impacts the rights of Muslims in New York.  While much of my research concentrates on community leaders, I also highlight how Muslims are advocating for their religious rights in their everyday life.  Although, community leaders have a platform to advocate for the right to practice Islam without discrimination, it is also important to showcase the everyday struggles and community building moments shaping Muslim life.  This research has the potential to shape public policy and immigration law.

This qualitative phenomenological study investigates the intersection of academic burnout, physiological resource depletion, and credential inflation among early-career professionals within 24 months of graduate degree completion. Grounded in Human Capital Theory, Career Construction Theory, and the Study-Demands Model, the research examines how navigating uninterrupted academic pathways and managing substantial student loan debt impact physical health capital and career adaptability.

Utilizing the Maslach Burnout Inventory-Student Survey (MBI-SS), semi-structured interviews, and graphic elicitation timelines, the study explores how financial and academic pressures, such as the tendency to forgo necessary healthcare due to student loan debt, shape the post-graduation professional transition. Findings provide vital insights for institutional stakeholders seeking to foster wellness-informed graduate program designs.

Coastal heritage sites in Antigua face compounding threats: accelerating erosion, increasing frequency of extreme weather events, and urbanization. The catastrophic impact of Hurricane Irma in 2017, destroying up to 45% of residential homes in some coastal communities, illustrates the scale of that vulnerability. Sites such as Winthrope's Bay along Antigua's northeastern coastline have been reported as largely eroded into the sea, while others along the eastern coastline have been bulldozed due to development pressure. The focus of this project is to document, survey, and assess the geographic extent of coastal archaeological sites and evaluate their vulnerability to climate impacts and ongoing development. Land based mapping and survey will employ the use of differential GPS units and basic pedestrian survey methods. Drone-based photogrammetry will be used to generate 3D models of the landscape for cultural heritage preservation, erosion monitoring, and site boundary delineation.

We study the nonequilibrium thermodynamics of a qubit interacting with thermal environments through repeated collisions with clusters of either qubits or harmonic oscillators. A composite system–bath interaction generates steady-state energetic coherence, providing in particular a qubit quantum battery charged by coherence rather than population inversion. We derive analytical expressions for the steady-state coherence and ergotropy for arbitrary cluster size and treat bosonic and fermionic bath statistics within a unified framework.

Cartucho (1931), by Nellie Campobello, is a collection of vignettes that portrays Pancho Villa’s soldiers during the Mexican Revolution. My project analyzes descriptions of characters’ belongings through the figure of synecdoche, characterized by the substitution of whole for part or vice versa. It suggests that the “synecdochal gaze” of Campobello forges a visual language that articulates a diverse set of narrative devices to represent death, draw attention to class differences, and humanize combatants. My project concludes with a reflection on the utility of synecdoche for understanding the decline of Villa’s movement as well as for comprehending history's relation to the present.

Over five consecutive semesters (Spring 2023 through Fall 2025), this study examined the development of clinical judgment in prelicensure nursing students across their clinical education experiences. The purpose was to evaluate the effectiveness of an unfolding case study assignment in fostering clinical judgment, increasing confidence in clinical decision-making, and serving as a potential replacement for traditional care plan and concept map assignments. Research questions focused on whether the unfolding case study supported clinical judgment development, enhanced student confidence, and represented an effective alternative learning strategy. Students completed a self-reported measure based on the Lasater Clinical Judgment Rubric, with repeated measures collected across five semesters to assess changes over time. In addition, qualitative data were gathered through open-ended questions exploring students’ perceptions of changes in competence and confidence following completion of the assignment. Quantitative and qualitative findings are currently being evaluated to determine the impact of the unfolding case study on student learning outcomes and clinical judgment development.

This project investigates how droplets spread, merge, and redistribute liquid on solid surfaces, with applications to spray painting and coating. High-speed images of a viscous glycerin solution were used to examine the effects of droplet volume ratio and overlap on coalescence and edge displacement. Python-based image analysis identified droplet silhouettes and estimated projected widths from selected experimental images. Results show that smaller droplets move farther during coalescence, while greater overlap reduces edge retraction. Continued merging after spraying stops can concentrate liquid into patches and decrease wetted coverage. These findings suggest that controlling droplet size distribution and overlap can improve coating uniformity. The project combines experimental observations with quantitative image analysis to connect droplet behavior with practical strategies for achieving more consistent surface coverage.

As large language models (LLMs) become part of everyday programming practice, educators face a new challenge: students can obtain working solutions without engaging in the reasoning that builds lasting skill. This project investigates how students use LLMs during programming tasks and uses those insights to design a guided learning environment that encourages students to question, predict, and explain their thinking before reaching a solution. Rather than restricting AI use, the project aims to turn it into an opportunity for deeper learning. The work proceeds in stages: first observing how students interact with AI tools without guidance, then developing and evaluating a tool in computing courses, and finally examining how guided AI use supports long-term problem-solving ability. Early observations show wide variation in how students rely on these tools, alongside student concern about their own independence. The project aims to give educators practical, evidence-based strategies for integrating AI into instruction across computing and beyond.

Legal socialization is the process in which we form our beliefs and views of the justice system. An important question to consider is what can be done early on in a person’s life to shape a positive outlook on the justice system. While debates ensue regarding the effectiveness of these officers in improving safety, another consideration is whether exposure to these officers during the middle school and high school years may help to form more positive perceptions of the justice system. If first impressions can be lasting, how can interactions with police in a school setting shape views and beliefs of the justice system as opposed to a first encounter when one is getting in trouble? This study explores the how police in schools may impact legal socialization by surveying college students about their exposure to police in middle and high school and their current views of the justice system. 

Uncertainty avoidance and perceived threat underlie conservative convictions to resist change and justify inequality. Uncertainty avoidance may manifest both through motivational tendencies to resolve the uncertainty (need for cognitive closure) and cognitive and emotional distress when faced with uncertainty (intolerance of uncertainty). The aim of this study is to explore how different facets of intolerance of uncertainty impact the relationship between political orientation and engagement in social justice and advocacy. Findings suggest that low intolerance of uncertainty (or high tolerance of uncertainty) in conservative college students is associated with reduced awareness of the impact of these forces on one’s life. Additionally, conservatism was associated with reduced tendencies to confront discrimination, but there were differential effects of prospective and inhibitory anxiety related to intolerance of uncertainty in the two samples. Future research should explore how political orientation and intolerance of uncertainty may impact behavior beyond self-report.

As artificial intelligence (AI) enters workplace negotiations, how do people and AI agents communicate, and how does language relate to negotiation outcomes? Drawing on social role theory and the agency–communion framework, this study examines negotiations between job candidates and an AI human resources manager. Using a lexicon-based approach, we analyze candidates’ gender, agentic and communal language patterns, economic outcomes, and participants’ experiences. Preliminary results suggest that the AI uses more communal language associated with warmth, politeness, and relational orientation, while candidates use more agentic language linked to assertiveness and goal orientation, among both women and men. Candidates’ agentic language is associated with greater individual gains, whereas the AI’s communal language is not consistently related to participants’ comfort or perceived fairness. We extend social role theory by showing how gender-linked communication may be expressed differently in human-AI interaction, with implications for economic and interpersonal outcomes for AI adoption in organizations.

This study investigated whether ABO and Rh blood group antigens are associated with patterns of immune hypersensitivity reactions, including asthma, allergic rhinitis, eczema, food allergies, and delayed allergic responses. An anonymous survey was completed by 112 participants and analyzed using descriptive statistics. Results showed notable differences among blood groups. Type B participants demonstrated the strongest overall hypersensitivity profile, with higher rates of food allergies, gastrointestinal symptoms, and rapid reaction onset. Type O participants experienced a broad range of respiratory, skin, and environmental symptoms, while Type A participants reported the highest rates of eczema. Type AB participants consistently showed the lowest levels of hypersensitivity. Rh-negative individuals also reported increased food allergies and skin-related symptoms compared with Rh-positive participants. Although these findings do not establish causation, they suggest that blood type may contribute to variations in immune responsiveness. Further research with larger sample sizes and clinical confirmation is needed to better understand these associations.

The purpose of this study was to measure whether there exists a demand for a potential student-athlete mentoring program among current FSC student-athletes. This involved a survey of all current student-athletes. Surprisingly, the student-athletes were not in favor of having this mentoring program implemented. Out of 109 student-athletes, only 35 said yes while 74 said no. For prospective mentees, the majority of both male and female student-athletes were not interested in the program. For the prospective mentors, we had a slightly different response. About ⅓ of the male mentors wanted the program, while most of the female mentors were in favor of the implementation. Student-athletes in individual sports were in favor of implementing a mentoring program, while those in team sports opposed a mentoring program being introduced. For student-athlete’s majors for the mentees, as well as mentors, there was no significant difference between major and interest.

Poster presentation of soon to be published book on Munich's famous Oktoberfest and modern German history.

Youth gambling is an increasing human services concern linked to childhood trauma, social inequities, and developmental vulnerability. Youth who experience multiple adverse childhood experiences (ACEs) are at greater risk of developing compulsive gambling behaviors, often using gambling to cope with emotional distress. These risks are amplified in economically strained communities where expanding mobile gambling platforms increase access and exposure. Early gambling initiation, particularly before age 10, is associated with a much higher likelihood of severe gambling problems in adulthood. Adolescent vulnerability is further intensified by the maturational gap, where emotional reactivity develops earlier than impulse control. Similar trends involving trauma, socioeconomic stress, and digital gambling access are emerging globally. Because youth gambling affects educational, behavioral health, family, and community systems, effective prevention and intervention require an interdisciplinary, trauma-informed approach. Human services professionals must understand these interconnected risk factors to develop culturally responsive interventions that strengthen emotional regulation, reduce impulsive behaviors, and address the systemic conditions that increase youth gambling risk.

We consider the Kuramoto model for systems of coupled oscillators whose underlying graph is the Cayley graph of a finite group.  Collective synchronization of the Kuramoto system occurs when a solution is phase-locked.  We produce such phase-locked solutions using linear characters of the group, called character-twisted states of the system.  We analyze the stability of the character-twisted equilibria in the case when the group is abelian.

The purpose of this project is to design a multi-section study to examine associations between course alignment and student learning in Farmingdale State College's Introduction to Nutrition Science course. This course fulfills 3 credits of SUNY's General Education Natural Sciences requirement and tends to have 20+ sections each Fall and each Spring, but it is not standardized, presenting an opportunity for a Scholarship of Teaching and Learning (SoTL) study.

Supernatural entities like ghosts and demons are often treated as abject in horror films and literature, seen as objects of terror that must be exorcised. But sociologist Avery Gordon argues that the figure of the ghost can instead be used to imagine the erasure of historically marginalized communities through symbolic and literal violence. Since Gordon’s book Ghostly Matters: Haunting & The Sociological Imagination was published at the turn of the century, the hegemony of cisgender, White, straight men creators in horror cinema and literature has been challenged by new voices in the genre with more revolutionary visions for the ghost that utilize the trope to challenge systems of inequality. This paper will undertake a content analysis of 8 films and 38 books from LGBTQ+ creators, examining how they use haunting to make the unseen seen and critique intersecting systems of inequality, such as institutionalized racism, imperialism, heteronormativity, and cisnormativity.

This research presents recent advances in enhancing recycled aggregate concrete (RAC) through the incorporation of three widely used nano-additives: nano-silica, multiwalled carbon nanotubes (MWCNTs), and graphene-based materials. Although RAC offers significant sustainability benefits by reducing construction waste and natural aggregate consumption, its widespread application remains limited by lower strength and durability associated with higher porosity and weaker interfacial transition zones. The review critically examines the influence of nanoparticle type and dosage on key mechanical properties, including compressive, tensile, and flexural strength, as well as durability performance. The mechanisms responsible for these improvements, such as accelerated cement hydration, pore refinement, interfacial transition zone densification, and nanoscale crack-bridging, are discussed. Cost considerations and optimum dosage ranges are also evaluated to identify practical and economical mix design strategies. Finally, current research gaps related to nanoparticle dispersion, field-scale implementation, and long-term durability are highlighted to guide future sustainable concrete development efforts.

This interdisciplinary project explores competitive workplace weight loss programs in the style of The Biggest Loser TV show. We ask what people's experiences are with workplace weight loss programs via in-depth interviews and how recent trends like GLP1s may have impacted those experiences. This project is a collaboration across sociology and business disciplines, asking questions about how social pressures around body size and the “body work” of engaging in competitive weight loss may shape workplace cultures and relationships between coworkers as a result. This presentation will focus on the creation of the project, integration of student research assistants, review of the literature related to workplace weight loss programs, and initial reflections on data collection.

This poster describes a proposed study about the experiences of Muslim therapists with Islamaphobic discrimination whether between the therapists and clients or in their work within a mental health practice. We propose to conduct semistructured virtual interviews and to content analyze these interviews to better understand the different experiences of discrimination that Muslim therapists may face.

Podcasts are an important new avenue for sharing knowledge and exhibiting expertise. However, there remains a question of who is allowed to represent fields like I-O psychology, human resources, and talent development in podcasts. Despite these fields' efforts to generate and maintain diverse and inclusive cultures, there may be a disparity in who is allowed to represent these fields in mass media. The present study evaluated the gender and ethnic presentation of podcast hosts and podcast guests for prominent human capital podcasts. Initial results reveal that 48.2% of podcast hosts are female and 64% present as Caucasian. 68% of guests were coded as Caucasian and 52% presented as female. This indicates that the majority of podcasters, guests and media figures in human capital space continue to be primarily Caucasian. This may indicate a lack of diverse voices in the field.

Airlines face increasingly complex capacity planning decisions requiring passenger demand forecasts at unprecedented granularity. We introduce a hierarchical framework generating carrier-specific passenger forecasts across 10-year strategic horizons. The framework combines attention-LSTM route forecasting with persistence-based carrier decomposition, achieving 9.55% MAPE on route-level predictions while outperforming ARIMA by 19.6% (p < 0.001). We validate the framework using 25 years of real U.S. airline data (10.26M records), confirming that carrier market shares always sum to 100% and that dominant airlines remain dominant while competitive markets remain balanced. The framework generates 120-month forecasts (2025-2034) for 26 carrier-route combinations, providing airlines with operational tools for fleet deployment and capital allocation decisions.

Using the Global Supply Chain Pressure Index (GSCPI) and monthly data (1998–2025), this paper examines the impact of supply chain stress on asset returns across countries, U.S. sectors, and precious metals. The research found that higher supply chain pressure significantly reduces equity returns, particularly during extreme disruptions. It was also found that trade-intensive and production-intensive sectors (e.g., energy, materials, industrials, financials) are more adversely affected than defensive sectors (e.g., utilities, consumer staples). This research also investigated how the level of supply chain pressure causes asymmetric return dynamics under low-pressure and high-pressure regimes. Portfolio analysis indicates limited hedging during severe disruptions, with selective benefits for certain precious metals and sectoral portfolios.

The Trans-Caspian International Transport Route (TITR) is a vital Asia–Europe corridor constrained by fragmented tariffs, logistical bottlenecks, and commodity price volatility. Geopolitical shocks, such as the recent closure of the Strait of Hormuz, intensify these pressures. We model the corridor as a multi-agent stochastic differential game between governments maximizing fiscal revenue and private carriers optimizing profit and throughput. Commodity prices follow a geometric mean-reverting process. To compute the Nash equilibrium in this high-dimensional, non-convex setting, we use a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) framework. Solving the associated Hamilton-Jacobi-Isaacs equations yields optimal “bang-bang” tax policies governed by endogenous price thresholds. Simulations over 5,000 episodes show that the centralized critic accurately approximates the agents’ Hamiltonians and converges stably. Agents internalize volatility through shadow pricing, and threshold-based taxation substantially improves throughput while preserving fiscal stability. The study shows that MADDPG can reliably uncover discontinuous optimal policies in mixed competitive-cooperative environments.

The Eastern oyster Crassostrea virginica is a filter feeder that is exposed to a variety of anthropogenic contaminants including pharmaceuticals in the seawater within its natural habitat. Atenolol, a β-adrenergic antagonists, is frequently detected in the marine environment. However, the impacts of atenolol on marine organisms have been understudied. This study aims to broaden our knowledge of the impact of pharmaceuticals on marine invertebrates by evaluating the impact of the β-adrenergic antagonist atenolol on oysters hemocytes and assessing the use of C. virginica hemocytes as a screening tool. Results indicate atenolol is sub-lethal with no impact on viability. However, apoptosis temporarily increased for hemocytes exposed to 266 µg/L of atenolol. Furthermore, differences in response by agranulocytes and granulocytes were observed, supporting the need to evaluate hemocyte subpopulations along with the whole population. These findings suggest oyster hemocytes may be a useful tool in addressing the gap of knowledge in ecotoxicological impacts of emerging contaminants on marine organisms and can serve as a preliminary assessment of immunotoxicity of these contaminants prior to in-vivo experiments.

Oxyhalide solid electrolytes are promising materials for all-solid-state lithium batteries because they can provide high lithium-ion conductivity and improved structural and chemical stability. However, the effects of oxygen concentration, lithium content, and local bonding on lithium-ion transport are not fully understood. In this work, we use first-principles calculations to investigate Nb-based oxyhalide solid electrolytes. Our results show that oxygen content strongly affects lithium-ion transport, with the highest conductivity generally occurring at a Cl/O ratio of approximately 4:1. Higher lithium concentration does not necessarily increase conductivity because strong Li–O interactions can restrict lithium-ion movement. We identify LiNb₂OCl₉ as a promising low-lithium-content oxyhalide with relatively high lithium-ion conductivity. The calculated conductivity, diffusion coefficient, and activation energy are 1.1 mS/cm, 5.89 x 10 ^-8 cm²/s, and 0.245 eV, respectively. These results provide guidance for designing high-conductivity oxyhalide solid electrolytes for next-generation all-solid-state lithium batteries.

This project uses Large Eddy Simulation (LES) to explore how downstream boundary conditions may influence flow and detonation-wave behavior in Rotating Detonation Engines (RDEs). Three outlet treatments are compared in the same two-dimensional engine model: a Mach-dependent condition with relaxation, supersonic extrapolation, and a fixed-pressure subsonic condition. All cases use the same operating and initial conditions. Preliminary results suggest a possible influence of outlet treatment on transient wave evolution.

This project examines whether shifting daylight across the clock affects outdoor recreation. Disc golf is an outdoor sport in which players throw discs toward metal baskets, and UDisc is a widely used app that records course activity. Using daily UDisc records from 726 courses in Arizona, California, Colorado, Nevada, New Mexico, and Utah from 2021–2025, we compare Arizona, which does not change clocks, with nearby states that observe Daylight Saving Time. Poisson pseudo-maximum likelihood models control for weather, astronomical daylight, course-year differences, and date-specific shocks. Following the fall transition, disc golf visits decline by about 6 percent overall and by 12.6 percent on weekdays, while weekend visits show little change. Spring results move in the opposite direction. The findings suggest that the timing of daylight, not just its total amount, can influence outdoor recreation.

Is soil an artifact too? At Pre-Columbian sites across Antigua, Amerindian lifeways created rich, fertile soils that proved resilient and erosion resistant. These constructed soils have persisted despite centuries of colonial monoculture, and now face stronger storms and rising seas. In summer 2026, we documented ancient shell middens acting as sea walls and as lifeboats for mangroves squeezed by sea level rise and coastal development. Soil chemistry shows these sites are enriched in elements critical to agriculture.

Implementation of SDARI With Autistic Youth This project examined outcomes following community-based implementation of Socio-Dramatic Affective Relational Intervention (SDARI), a manualized, improvisation-based social intervention, among autistic youth. Nineteen youth ages 8–16 participated in eight weekly SDARI sessions delivered within a community mental health practice. Pre- and post-intervention measures assessed parent-reported social responsiveness and, among adolescent participants, self-reported loneliness, belongingness, and psychological flexibility. Paired-samples t-tests indicated significant improvements across all outcomes. Parent-reported social responsiveness improved following intervention, while adolescents reported reduced loneliness, increased belongingness, and greater psychological flexibility. Findings provide preliminary support for the feasibility and potential benefits of implementing SDARI within routine community practice. Importantly, observed changes extended beyond traditionally measured social behaviors to youths’ subjective experiences of social connection and psychological flexibility.

Misconceptions about learning and memory are common among college students, but do these beliefs relate to how students actually study? In a preregistered, multi-institutional study, 914 undergraduates from six U.S. colleges and universities completed measures assessing misconceptions about learning and memory and their academic behaviors. Students endorsed an average of 6 of 14 misconceptions, with beliefs in learning styles, single-concept studying, and left/right brain dominance among the most common. Stronger endorsement of misconceptions predicted more frequent use of maladaptive study strategies, whereas the number of misconceptions students held did not. Moreover, endorsement of specific misconceptions predicted corresponding academic behaviors for 10 of the 14 misconception–behavior pairs examined. These findings suggest that misconceptions about learning and memory are associated with students’ academic decision-making and may represent important targets for interventions designed to promote more effective learning strategies.

As artificial intelligence (AI) enters workplace negotiations, how do people and AI agents communicate, and how does language relate to negotiation outcomes? Drawing on social role theory and the agency–communion framework, this study examines negotiations between job candidates and an AI human resources manager. Using a lexicon-based approach, we analyze candidates’ gender, agentic and communal language patterns, economic outcomes, and participants’ experiences. Preliminary results suggest that the AI uses more communal language associated with warmth, politeness, and relational orientation, while candidates use more agentic language linked to assertiveness and goal orientation, among both women and men. Candidates’ agentic language is associated with greater individual gains, whereas the AI’s communal language is not consistently related to participants’ comfort or perceived fairness. We extend social role theory by showing how gender-linked communication may be expressed differently in human-AI interaction, with implications for economic and interpersonal outcomes for AI adoption in organizations.

Drawing on Sophocles’ Ajax, this project proposes a new interpretive framework for examining the psychological and behavioral trajectories of certain mass shooters. Just as Freud and Jung drew upon classical literature to articulate psychological complexes, the Ajax Complex identifies a recurring pattern involving identity, perceived humiliation, grievance, and violent retribution. Through an examination of Sophocles’ tragic hero alongside contemporary cases of mass violence, the research identifies six stages that may illuminate how perceived injustice and wounded identity can culminate in catastrophic violence. Rather than proposing a clinical diagnosis, the Ajax Complex offers an interdisciplinary framework connecting classical literature, psychology, and contemporary social concerns. Ultimately, the project demonstrates how ancient dramatic literature can contribute to our understanding of one of society’s most troubling contemporary phenomena.

This exploratory study examines how small businesses perceive artificial intelligence (AI), assess their readiness for its integration, and navigate emerging organizational and workforce challenges. Drawing on survey responses from 70 small businesses and 15 semi-structured interviews with business owners and managers in the New York metropolitan region, the study explores variation in AI awareness, interest, use, and hesitation. Survey data address perceived opportunities and barriers, potential applications, decision-making support, training needs, and reasons for non-adoption. Interviews examine organizational capabilities, operational concerns, workforce implications, and the role of human judgment in evaluating and using AI. The analysis considers how technological interest intersects with resource constraints, employee skills, communication, and adaptability. By integrating survey and interview evidence, the study seeks to clarify factors shaping AI readiness and organizational adaptation. Its intended contribution is to inform small-business support, workforce development, and educational approaches that prepare future managers for responsible engagement with AI-enabled workplace environments.

Predator and prey interactions are important in understanding how ecosystems function, but observing these interactions directly in nature can be challenging. The clay caterpillar decoy method was used to explore predator activity and better understand how different organisms interact within the FSC campus. The Robert F. Ench Teaching Garden and a more urban site with a pedestrian walking path near Lupton Hall were compared. Decoys were checked daily for any bite marks by birds, mammals, insects, and other organisms. The Teaching Gardens had greater predator biodiversity (H=1.76), with most predators being birds, compared to the walking path along Lupton Hall (H=1.63) which was dominated by small arthropods. While predator attack rate of decoys was initially faster at Lupton Hall, attack rates converged as the study progressed. A follow-up validation study was conducted to align predator species with bite mark morphology. In addition to aesthetic beauty, this work suggests that gardens may also enhance ecosystem stability and resilience.

The growing use of generative AI tools among students raises an important pedagogical question: how can AI be structured to promote active learning rather than passive answer-seeking? This study introduces the Physics AI-Replication (P-A.I.R.) framework, in which students identify challenging problems, use AI to explain underlying concepts and solutions, generate similar problems, and practice independently before reviewing answers. Survey data from 39 undergraduate students in algebra-based physics indicate that nearly all participants reported improved conceptual understanding following engagement with P-A.I.R. across the semester, and self-confidence scores were consistently above the scale midpoint (mean = 7.03; range 5-9). A strong association between conceptual clarity and replication helpfulness (Spearman r = 0.582, p < 0.001) supports the framework's design. Qualitative findings highlight conceptual clarification and structured problem-solving. These results suggest that P-A.I.R. offers a practical approach for integrating AI into physics learning.

Menopause, osteoarthritis, and sarcopenia are interconnected conditions that may significantly influence women’s musculoskeletal health, physical function, and quality of life as they age. This proposed exploration will examine the potential relationships among hormonal changes associated with menopause, joint degeneration associated with osteoarthritis, and age-related declines in muscle mass, strength, and function characteristic of sarcopenia. Particular attention will be given to how these conditions may interact to contribute to mobility limitations, pain, reduced physical activity, functional decline, and increased risk for falls. The project will explore current evidence and identify gaps in the literature that may support future narrative or scoping research. Findings may help inform interdisciplinary approaches to prevention, assessment, and management of musculoskeletal health in postmenopausal women.

As AI tools increasingly generate written responses, instructors face new incentives to assess student learning through methods resistant to automation. A three-minute in-class presentation serves as an alternate form of assessment, offering several pedagogical advantages such as encouraging critical thinking, real-time synthesis of information and enhancing communication skills. This paper provides a practical toolkit for implementing such presentations in a Principles of Microeconomics class. It provides guidance on the assignment structure, grading rubrics and student preparation strategies as well as offers some critical reflections on how the presentations may unfold based on several years of experience overseeing them.

Microplastics are ubiquitous in marine environments. Suspension-feeding organisms, like the gastropod Crepidula fornicata, ingest these particles along with plankton and suspended particulate matter. We investigated mucus production, essential for digestion, in the intestinal tissues of this snail following exposure to 3 µm polystyrene microplastics. Specimens exposed to microplastics over 24 hours saw the area of active mucocyte tissue (AMT) decrease at 6 hours, increase going on 12h, and then decrease again. These changes likely reflect natural variations in feeding activity suggesting innate diurnal rhythms. The slipper shell often inhabits  high water energetic regions and suspended sediment, and their ability to tolerate regular ingestion of inorganic particles, including microplastics, appears unaffected by microplastic exposure

This research is a qualitative study of the meanings of sustainability that are developed through the work of implementing a sustainability standard certification program, focusing on the concepts of the triple-bottom-line and continuous improvement that frame the meanings of sustainability. I describe what I call an ‘aspirational frame’ in which sustainability goals are considered both fully realized in the future but also fully real in the present, emphasizing the journey towards the ideal rather than the destination. The impact of sustainability standards has always been controversial, particularly when the focus is on measurable environmental outcomes. My study shows however that standards help lay the groundwork for collective action by creating consensus, common language, and values, and through these elements, a community primed for increasingly impactful action. I show how meaning construction through framing helps members make sense of conflicting information and identify opportunities in the midst of challenges.

This project explores whether low-cost MEMS microphones can provide an affordable alternative to traditional laboratory measurement microphones. Microphones using one, two, three, and four MEMS sensors were designed to study how the number of sensors affects performance and sound quality. Several construction methods were also developed, ranging from professionally manufactured circuit boards to designs that can be built using basic fabrication and soldering techniques. Single- and four-MEMS prototypes were built and tested using a controlled 1 kHz sound and compared with a laboratory reference microphone. These initial tests demonstrate the potential of MEMS technology for making acoustic measurements more accessible. The long-term goal is to create reliable, well-tested microphone designs that can be reproduced at low cost, expanding opportunities for hands-on acoustics research and education in schools and undergraduate laboratories.

This mixed-methods study examined the experience of 320 students who transferred to 4-year institutions of higher education in New York State. Students transferring from 2-year institutions transferred significantly more credits than those from 4-year institutions. Those who completed an associate degree secured a significantly higher number of accepted credits than those who transferred without a degree. Students who transferred from 4-year schools reported a more positive transfer experience than students from 2-year schools. Cost and proximity to home were the top transfer considerations and most students used the institution's website as their primary resource for transfer information. Qualitative analyses of open-ended questions indicate that barriers to the student transfer experience include advisement challenges, credit transfer issues, financial concerns, and registration difficulties, while supports include structured transfer programming, efficient course evaluation, and accessible, supportive advising.

This paper incorporates goods’ qualities into the analysis of time allocation decisions and explains how the inability of poor individuals or households to afford high-quality goods can push them into time poverty. The paper exploits simple but overlooked dependencies between quality and time: Goods and services of higher quality can make time more enjoyable or save more time, allowing individuals to increase the quality of their time, and to increase leisure and income (by increasing labor). Possible attributes that determine quality are here grouped into three categories: durability, effectiveness and enjoyability. These categories are shown to affect time allocation decisions, and to have distinctive effects on high- and low-income individuals. The income poor have limited access to goods and services that save time and improve the enjoyability of time, leading to a type of time poverty that is different in nature from the time poverty faced by higher income individuals.

Over the past two decades, Asian Americans have been subjected to a sharp rise in 
harassment and violence, with incidents being even more pronounced during the COVID-19 
pandemic. This broader climate of anti-Asian hostility has heightened concerns about safety, which may have long-lasting effects on academic achievement, mental health, and overall well-being. This research project investigates how exposure to violence in one's neighborhood is related to school absences among Asian American youths. Furthermore, it sheds light on the role of school connectedness in promoting regular attendance in class.

In many materials, transitions from one structure to another are spanned by intermediary phases possessed of some degree of greater disorder than either end member.  In CoIn2, we find a temperature T-induced Peierls transition that occurs at T = 194(1) K mediated by an acentric, incommensurately modulated charge density wave (CDW) that spans ΔT > 12 K and extends into the Peierls phase itself.  Our Hall effect measurements reveal anomalous transport in the CDW phase at applied field H > 1 T, suggesting a dynamical nature of the structural modulation.  Our high-resolution synchrotron x-ray scattering measurements reveal that the intermediate phase is in reality two discrete phases, each corresponding to a distinct incommensurate modulation.  These incommensurate phases melt with increased T, consistent with recent work on low dimensional CDWs, with melting characterized by contraction of wave vector q and decay of intensity I.

This paper proposes a general model from the perspective of game theory to examine the long-term social and economic consequences of COVID-19, focusing primarily on increased screen time, the rise of remote work, and exploitative practices by health insurers. Our results highlight that COVID-19 has profoundly reshaped traditional norms and significantly altered behavioral patterns, creating tension and conflict between those adhering to pre-pandemic norms and their counterparts embracing new ones. Individuals and firms that can successfully adapt to new norms are likely to experience reduced conflict and may gain a competitive advantage in the unprecedented post-COVID-19 era.

This paper develops a dynamic game-theoretical model to analyze the trade war between the United States and China. It interprets the trade conflict starting from 2018 as a strategic response by the U.S. to China’s rapid rise. The model examines several critical issues related to the trade war, including the timing for initiating a trade war by the U.S., the effects of various scales of trade war, the impact of internal growth of national power (IGNP) rates of both countries, and the role of third-party actors. The model indicates that there exists a tradeoff between the scale of a trade war and its timing. Moreover, the model implies that the outcome of the trade war depends largely on each country’s capacity for sustained internal national power growth, suggesting that the U.S. efforts begun in 2018 may have been too late to curb China’s rise and that the Covid-19 pandemic may have imposed relatively greater constraints on China than on the U.S. The analysis further indicates that third-party support plays a tie-breaking role in shaping the outcome of the conflict.

Environmental Conservation Police Officers (ECOs) enforce New York's environmental and wildlife laws — confronting illegal wildlife trade, pollution, and threats to natural resources across the state. Yet the DEC has identified officer staffing as a persistent barrier, and there is little empirical research on how this specialized workforce is recruited, trained, and retained. Developed in collaboration with the NYS DEC, this study examines the academy experience and early-career attrition to build an evidence base for strengthening the environmental enforcement workforce.

This proposed investigation addressed how environmental and everyday chemical exposures may contribute to breast cancer risk by disrupting DNA repair, one of the body’s most important defenses against cancer development. The study focused on the homologous recombination pathway, a high-fidelity DNA repair system governed by BRCA genes, whose dysfunction is strongly linked to hereditary breast cancer. By examining how specific chemicals interfere with this pathway, the research connects environmental exposure to a well-established genetic mechanism of cancer susceptibility. Using a powerful microbial model system, we systematically tested representative chemicals found in contaminated groundwater, agricultural products, and personal care items to determine whether they cause toxicity or DNA damage that depends on homologous recombination for repair. In parallel, we used a highly sensitive assay to detect genomic instability that was not necessarily dependent on the HR pathway for DNA repair. Our aim was to investigate whether these compounds affected genome integrity. 

Preserving Parkchester: An Examination into the Decay of WPA-Era Sculptures centers on Parkchester, a planned community in the Bronx, New York City. Despite attempts made to elevate Parkchester’s status, the complex is not landmarked. Through interdisciplinary research comprised of site visits and analysis of text and image, both historical and contemporary, the paper examines how transparency—or lack thereof—shapes New York City’s landmarking process. Parkchester’s stalled campaign toward landmark designation exposes a flaw in the Landmarks Preservation Commission’s process, leaving unclear who decides what parts of the city, and whose stories, are worth preserving. The Preserving Parkchester microsite functions as an interactive, public-facing companion to the research. Through historical and contemporary text and images, the microsite invites visitors to explore Parkchester’s history and ongoing questions surrounding its preservation, bringing the research to a broader audience.

Network of Quantum Support Vector Machines (N-QSVM) & Red Wine Quality Assessment
Quantum Machine Learning (ML) techniques are advancing at a fast pace. In this work, Network of Quantum Support Vector Machines (N-QSVM) that is recently introduced will be explained as a new quantum ML technique with its computational effectiveness testing on a dataset related to wine quality. The results indicated this new technique to be strong; however, additional testing on different datasets would be needed in the future works.

Accounting graduates increasingly enter a profession transformed by automation, data analytics, artificial intelligence, and digital platforms. Yet many academic institutions struggle to keep pace with these shifts, resulting in a widening technological skills gap. This paper utilizes a T.E.C.H. Framework as a model for redesigning the accounting curricula in response to this digital transformation and to assist educators narrow the technological skills gap of accounting graduates.

The framework guides educators through four interconnected dimensions: transforming the context of the subject matter, embedding technology, crafting new student learning objectives, and honing the evaluation of learning. Using a foundational accounting course as an illustrative example, the paper demonstrates how traditional transaction-focused instruction can be reoriented toward analytical, technology-enabled, and judgment-based competencies that align with evolving professional expectations. Therefore, students graduate with the technological fluency, digital problem solving skills, and applied experience demanded by employers.

Interaction Service robotics have been growing rapidly in areas like logistics, health care and retail spaces, where robots need to operate smoothly and safely in human-centered environments. Monitoring Human-Robot Interaction (HRI) in such dynamic environments requires not only robust action detection but also high-level behavior understanding. In this work, we propose a Neuro-Symbolic (NeSy) framework that combines deep-learning based perception with symbolic reasoning to recognize HRI. We use a YOLO-based detector to detect persons and robots from multi-view cameras. Then we apply a multi-object tracking system to associate detections with tracks to generate trajectories. Prolog-based rules are applied to interpret human and robot tracks to infer high-level behaviors in the spatio-temporal domain. We evaluate our framework using the multi-view synthetic warehouse dataset, PhysicalAI-SmartSpaces. Our work demonstrates improved precision and recall in recognizing various HRIs using NeSy framework and provides a promising path toward reliable HRI understanding in complex and dynamic environments.  

This research project aims to explore and identify the key factors, including a series of motivators and inhibitors, that potentially influence consumers’ attitudes toward Autonomous Delivery Robots (ADRs). This research project is based on two major studies. The initial study is conducted with consumers across the U.S. via an online survey. This is to figure out whether the potential motivating factors (e.g., perceived usefulness, ease of use, anthropomorphism, and social influence) and inhibiting factors (e.g., perceived insecurity and social risks) can impact consumers’ attitudes toward ADRs. Furthermore, it is subjected to investigation whether the impact of the proposed motivating and inhibiting factors on consumers’ attitudes toward ADRs is mediated by their perceived enjoyment of the potential interactions with ADRs. Then a replicate study is conducted with English-speaking consumers in Australasia via another online survey. The findings provide important implications to companies regarding the effective adoption of ADRs in package deliveries.

Mathematical reasoning is fundamental to computer science, yet many introductory programming students struggle to connect mathematical concepts with computational logic. Drawing on extensive experience teaching mathematics and computer science, this reflective paper explores lesson and assignment design that bridges mathematical thinking and programming practice in an introductory Java course. Three strategies are emphasized: making mathematical foundations explicit, translating problem scenarios into mathematical representations before coding, and connecting mathematical models to programming constructs and program state. Classroom examples and a representative lab illustrate how these strategies address challenges involving integer division, quotient–remainder reasoning, Boolean expressions, and operator precedence. Reflective observations and informal assessments suggest that integrating mathematical reasoning throughout instruction can support students’ conceptual understanding, confidence, and engagement. The paper concludes with lessons learned and practical recommendations for incorporating mathematical thinking into introductory computer science education.

This project develops a real-time digital twin framework that synchronizes a physical UR3e collaborative robot with a virtual model in Unreal Engine. Robot states are streamed through real-time communication and mapped using coordinate transformation and robot kinematics. Spatial accuracy, latency, update rate, and synchronization stability are evaluated quantitatively. The framework provides a practical foundation for real-time monitoring, virtual commissioning, and human–robot collaboration in Industry 5.0 manufacturing.