Physical Sciences and Mathematics Commons^™

Global Time-Resolved Measurements Of Inlet/Isolator Unstart Induced By Mass Injection, Andrew N. Bustard, Benjamin L. Bemis, Aaron Marques, Matthew J. Zahr, Thomas J. Juliano

Publications

The inner surface pressure of an axisymmetric inlet/isolator model was measured using anodized-aluminum pressure-sensitive paint (PSP) viewing through cast acrylic. Temperaturesensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at 𝑹𝒆 = 7.1 ×106 /m under conventional noise conditions. Transverse jet injection with jet-to-inlet mass-flow ratios up to 0.8 was used to induce unstart in the inlet/isolator. Background-oriented schlieren visualization of the inlet shocks was collected simultaneously with the PSP to determine when the inlet unstarted. Computational fluid dynamics results were used to determine off-wall flow structures and quantify approach …

Residential Ai Data Centers: Security, Privacy, And Governance Concerns, Alan Saquella

Publications

The concept of placing mini data centers and distributed AI computer nodes inside residential homes may appear innovative from an energy efficiency perspective, but it introduces significant security, privacy, governance, and liability concerns. What is effectively occurring is the expansion of commercial and potentially critical infrastructure into lightly protected residential environments.

Once a residence becomes part of a distributed computer grid supporting hyper-scalers, AI providers, or enterprise workloads, the home is no longer simply a private residence. It becomes a commercial technology asset, a potential cyber target, and even a physical target. A distributed network of thousands of residential nodes …

Saag: Structured Agent Assessment And Grounding, Ritvik Garimella, Vedant Khandelwal, Anvi Kohli, Amit Sheth

Publications

Exact-match evaluation of agent-calling obscures qualitatively different failure modes: a model may select the right function yet hallucinate argument values, or satisfy a schema while choosing a agent for the wrong reason. Existing benchmarks collapse these distinctions into a single binary score, leaving practitioners unable to diagnose where agent calls fail. We propose SAAG a cascaded diagnostic framework that decomposes agent-calling evaluation into three sequential stages: registry conformance, structural completeness, and argument grounding, each producing interpretable stage-specific diagnostics. These diagnostics additionally enable iterative self-repair: on prediction failure, the stage-specific signal guides targeted correction without leaking ground-truth values. We evaluate this …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …

Perseus Interim Evaluation Report, Data Innovation Project, University Of Southern Maine

Publications

The Data Innovation Project (DIP) from the University of Southern Maine’s Catherine Cutler Institute serves as the external evaluator for the USDA NIFA SAS-funded Promoting Economic Resilience and Sustainability of the Eastern U.S. Forests (PERSEUS) project. This project is a joint effort between Purdue University, the University of Georgia, and the University of Maine. The DIP supports the project in assessing its progress, implementation, and emerging impacts through data collection from project participants and systematic document review (i.e. annual USDA reports, personnel lists, and meeting notes). This includes synthesizing quantitative and qualitative data and incorporating these metrics into independent evaluation …

A Climatology Of Sudden Stratospheric Warmings And Their Tropospheric Response, Joe Lovelien, Mark Sinclair

Publications

Sudden Stratospheric Warmings (SSWs) are major disruptions of the wintertime polar vortex that can significantly influence surface weather, including cold air outbreaks (CAOs) across the midlatitudes. This study presents a climatology of SSWs from 1948-2024 using NCEP-NCAR reanalysis data and examines their temporal distribution, relationships with large-scale climate variability, and impacts on surface temperatures in the United States. SSWs are identified using previously published definitions based on the reversal of zonal-mean winds at 60°N and 10 hPa. A total of 44 SSW events were identified, with a strong seasonal preference for January through March. Some decadal variability is observed, though …

Clear-Air Turbulence Climatology And Trends, Liam Rodgers, Mark Sinclair

Publications

Clear‑air turbulence (CAT) is a major aviation hazard that occurs near airline cruising altitudes in both cloud and cloud‑free environments. Its lack of a distinct visual signature makes detection and avoidance difficult. CAT is associated with wind shear near jet streams, gravity waves, and Kelvin–Helmholtz instability and may be further enhanced by climate change. This study examines the climatology, spatial distribution, seasonal variability, and trends of CAT over the contiguous United States.

Pilot Reports (PIREPs) from 2001–2025 between 100 and 400 hPa are analyzed alongside jet stream, shear, and stability diagnostics derived from NCEP–NCAR Reanalysis data. Proxies such as inverse …

An Analysis Of The Rapid Intensification Of Hurricane Milton, Ayden Rodriguez, Mark Sinclair

Publications

Hurricane Milton (October 2024) provides a compelling case study of a multiscale pathway to rapid intensification (RI), highlighting the alignment of synoptic preconditioning, favorable environmental conditions, and rapid inner-core structural evolution. The storm originated from the interaction of multiple tropical waves embedded within a low-level trough associated with the Central American Gyre, which enhanced low-level vorticity and moisture convergence prior to development. Upon entering the Gulf of Mexico, Milton encountered an environment characterized by anomalously warm sea surface temperatures, high ocean heat content, and weak vertical wind shear, enabling steady intensification and the onset of explosive RI that exceeded conventional …

Course Insight Portfolio: Math 1080, A Gentle Introduction To Infinite Series, Igor Luis Aureliano, Ross George

Publications

This lesson aims to introduce the concept of an infinite series through geometric representations and partial sums to help students develop an intuitive understanding of convergence. A common misconception students may have when first encountering infinite series is the belief that “a sum of infinitely many things must be infinite”. Through the study of a convergent geometric series, students will investigate how the limit of partial sums can produce a finite value, thereby addressing this misconception and developing a more accurate understanding of infinite series.

Course Insight Portfolio: Math 1020 Business Calculus I, Ibrahim Khalilullah, M.G.M. Al Faruque, Jessica Ratovondranto, Leslie Spahr

Publications

This portfolio presents an overview of the student educational context, key course concepts, and some approaches to clarify student misconceptions associated with MATH 1020 (Business Calculus I). The portfolio includes a concept map illustrating the major topics of the course and an overview of common student misconceptions, and lesson plans designed to address those misconceptions through research informed instructional practices.

The concept map highlights the interconnected nature of topics such as functions, limits, continuity, differentiability, derivatives, optimization, graph interpretation, and applications of calculus. Particular attention is given to areas where students commonly experience difficulty, including distinguishing domain, codomain, and range; …

Course Insight Portfolio Math 1040: Precalculus And Introductory Differential Calculus, Jessica Ayers, Morgan Hayes, Meghan Kerrick, Uthman Rasaq, Drishty Singh

Publications

This portfolio includes four primary elements. First is a document titled “Where did they come from? Where are they going?” that provides a description of the types of students who are likely to take the course, followed by the “Course Concept Map” that visually depicts the flow of topics and possible misconceptions in MATH 1040. Additionally, the “Misconceptions Overlay” document lists articles that offer interesting discussion and further insight into the ideas students may bring to MATH 1040 or develop throughout the course. Two lesson plans are included that cover “Continuity and Introduction to Classifying Discontinuities” as well as an …

Course Insight Portfolio: Math 1060 Calculus Of One Variable I, Minh Ha, Dinaniaina Florence Rafidimanantsoa, Preston Sessoms, Rishabh Shukla

Publications

The following portfolio is a representation of the course MATH 1060, Calculus I, taught at Clemson University. The contents can be broken down into 3 major components.

• The first being an analysis of the students who may typically be in the course, the prerequisites required to take the course, and what paths students have after completing the course. This analysis is based upon the course curriculum at Clemson, and as a result will likely not align with that of other universities

. • The second major component is a map of the concepts discussed in MATH 1060 as well …

“It’S A Lot More To It Than Just Research”: Integrating Critical Data Literacy And Reasoning With Data Into A Stem Summer Camp, Marc T. Sager, Saki L. Milton, Candace Walkington

Publications

Purpose: This study explores how middle-grade girls from predominantly underrepresented and underserved racially and ethnically minoritized (UUREM) backgrounds developed critical data literacy (CDL) through participation in a week-long residential STEM camp. Given the increasing importance of data science education in a data-driven world, this research examines how informal learning environments can support CDL development among youth from historically marginalized groups.

Design/Methodology/Approach: The study draws on qualitative interview data from eleven participants, and their group-produced artifacts to investigate how the camp experience supported engagement with data and the development of CDL. Interviews explored participants' experiences with data collection, organization, analysis, and …

A Critical Review Of Statistical, Signal Processing And Machine Learning Methods For Continuous And High-Frequency Water Quality Data Improvement, A.T. Badrudeen, D. Sahoo, Calvin Sawyer, Jeremy Pike, R.D. Haramel

Publications

In the digital water world, high-frequency water quality monitoring from sensors is crucial for capturing rapid changes, especially during storm events or discharge fluctuations, in which important signals can occur at sub-hourly intervals. These signals are represented in a time series and can sometimes be irregular, noisy, and prone to missing values or errors due to buried conditions, sediment interference, and signal loss. The fine resolution of reporting also increases the risk of sensor errors and data loss, necessitating effective correction methods to ensure the accuracy and usability of the data. This literature review investigates the current state of time …

Biologically-Inspired Multiscale Neuromorphic Architecture, Christian O'Reilly, Ramtin Zand

Publications

This white paper proposes a biologically-inspired multiscale neuromorphic architecture that bridges key gaps between artificial neural networks (ANNs), spiking neural networks (SNNs), and biological neural networks (BNNs). While SNNs offer promising energy efficiency, their broader adoption remains limited by suboptimal performance and the need for novel learning paradigms. To address these challenges, the proposed framework integrates structural and functional principles observed in the brain, including hierarchical organization, sparse and modular connectivity, predictive coding, and diverse neuronal dynamics.

The architecture operates across micro-, meso-, and macro-scales, incorporating neuron-level diversity (e.g., excitatory/inhibitory and principal/support cells), canonical microcircuits (CMCs), and large-scale hierarchical organization. …

Dyno : Dynamic Neurosymbolic Orchestrator For Multi-Agent Systems, Ritvik Garimella, Chathurangi Shyalika, Renjith Prasad, Amit Sheth

Publications

Large Language Model (LLM)-based multi-agent systems (LaMAS) represent an emerging paradigm for tackling complex, multi-step reasoning and decision-making problems. As these systems scale, orchestration, which is the ability to coordinate, manage, and evaluate the interactions among diverse agents, becomes central to their success. While recent orchestrators such as AgentFlow have demonstrated promise in managing communication and task delegation, they remain limited in their ability to understand task semantics, coordinate heterogeneous agent types (e.g., reactive vs. cognitive), and adaptively align outputs with human-defined goals. In this position paper, we introduce the DYNO (Dynamic Neurosymbolic Orchestrator), a system developed as part of …

Preparing Tomorrow’S Professionals: Industry-Informed Ai Integration, Brent A. Terwilliger Ph.D, John Faraca

Publications

As AI reshapes operations across aviation and aerospace, organizations are investing in ways to preserve data integrity, safeguard proprietary knowledge, and uphold critical professional competencies. This presentation shares emerging findings from a study that surveys and interviews industry professionals about their use of AI tools, their concerns about misuse, and the importance of secure, enterprise-controlled “walled garden” environments. The work explores how employers define appropriate, effective, and innovative AI adoption, particularly in roles requiring high-stakes decision-making, compliance, and technical acumen.

By analyzing organizational expectations around AI-related knowledge, skills, and abilities (KSAs), this research offers practical guidance for academic programs seeking …

Student Perspectives On Ai-Enabled Tools For Adaptive Learning, John Faraca

Publications

Artificial Intelligence (AI) is increasingly influencing the delivery of higher education, especially in aviation technical disciplines. From AI-assisted gimbals and video production tools to generative AI platforms, these technologies are helping learners to engage with course material, accomplish objectives, and connect academic concepts with professional applications. By offering pathways for personalization, streamlining resource access, and supporting interactive instruction, AI tools expand opportunities for effective learning. This work builds on a current collaborative research project with a faculty researcher to explore the student perspective in the active review and application of these tools to highlight their potential to improve usability, address …

Perspectives On Firearm Storage Conversations: Summary Of Health Care Provider Interviews And Parent Focus Group, Rachel M. Gallo Mph

Publications

This report summarizes perspectives from Maine parents who own firearms and health care providers on safe firearm storage and related conversations in health care settings. Through interviews and a parent focus group, the project explored how firearms are stored, what influences storage decisions, and how families and providers feel about discussing firearm safety. Parents emphasized the importance of responsible ownership, education, and individualized storage solutions, while identifying cost as a key barrier to safer storage options. Many health care providers expressed interest in addressing firearm safety but cited limited time, lack of training, and concerns about patient trust as challenges. …

Adverse Childhood Experiences, Positive Childhood Experiences, And Digital Media Use Among Children And Adolescents In The United States, Elizabeth L. Crouch, Emma Boswell, Monique J. Brown Ph.D., Kevin J. Bennett

Publications

No abstract provided.

Insights On Ai-Supported Uncrewed And Autonomous Systems Education, Brent A. Terwilliger Ph. D, John Faraca

Publications

Artificial Intelligence (AI) related technology is reshaping the educational experience in programs focused on uncrewed and autonomous systems, aviation, robotics, and aerospace, with growing implications for workforce readiness and cross-sector innovation. Early survey data, capturing student, educator, and employer perspectives, reveals that AI-supported tools are notably changing student engagement, communication, and skills development. Initial indications underscores the importance of AI proficiency and technological familiarity in hiring and workforce development, particularly in technical and operational roles. Key areas of focus include the use of AI to strengthen outreach and interactivity; enrich instruction through intelligent simulations; inform curricular improvements using data analytics; …

X-Ray Microcalorimeter Observations Of High-Mass X-Ray Binaries With The Resolve Instrument Onboard Xrism, Pragati Pradhan, Masahiro Tsujimoto

Publications

The X-ray Imaging and Spectrometer Mission (XRISM) was put into orbit successfully in September 2023. Resolve, one of the scientific instruments onboard XRISM, hosts an X-ray spectrometer based on X-ray microcalorimetery technology. It excels in high spectral resolution, a large throughput, a large bandpass, low background, and good timing accuracy. These properties are suited to bring new insights especially in high-mass X-ray binaries (HMXB). We describe these unique features of Resolve and present initial highlights of two HMXB sources.

The Giant Outburst Of Exo 2030+375, P. Thalhammer, R. Ballhausen, E. Sokolova-Lapa, J. Stierhof, A. Zainab, R. Staubert, K. Pottschmidt, J.B. Coley, R.E. Rothschild, G.K. Jaisawal, B. West, P.A. Becker, Pragati Pradhan, P. Kretschmar, J. Wilms

Publications

The Be X-ray binary EXO 2030+375 went through its third recorded giant outburst from June 2021 to early 2022. We present the results of both spectral and timing analysis based on NICER monitoring, covering the 2−10 keV flux range from 20 to 310 mCrab. Dense monitoring with observations carried out about every second day and a total exposure time of ∼160 ks allowed us to closely track the source evolution over the outburst. Changes in the spectral shape and pulse profiles showed a stable luminosity dependence during the rise and decline. The same type of dependence has been seen in …

The Unaltered Pulsar: Gro J1750-27, A Supercritical X-Ray Neutron Star That Does Not Blink An Eye, C. M. Malacaria, L. Moritz Ducci, M. Falanga, D. A. Altamirano, E. Bozzo, S. J. Guillot, G.K. Jaisawal, P. Kretschmar, M. Ng, Pragati Pradhan, R. Rothschild, A. Sanna, P. Thalhammer, J. Wilms

Publications

When accreting X-ray pulsars (XRPs) undergo bright X-ray outbursts, their luminosity-dependent spectral and timing features can be analyzed in detail. The XRP GRO J1750-27 recently underwent one such episode, during which it was observed with NuSTAR and monitored with NICER. Such a data set is rarely available, as it samples the outburst over more than 1 month at a luminosity that is always exceeding ∼5 × 1037 erg s−1 . This value is larger than the typical critical luminosity value, where a radiative shock is formed above the surface of the neutron star. Our data analysis of the joint spectra …

Multi-Wavelength Study Of 1erass J085039.9−421151 With Erosita, Nustar, And X-Shooter, A. Zainab, A. Avakyan, V. Doroshenko, P. Thalhammer, E. Sokolova-Lapa, R. Ballhausen, N. Zalot, J. Stierhof, S. Hämmerich, C. M. Diez, P. Weber, T. Dauser, K. Berger, P. Kretschmar, K. Pottschmidt, Pragati Pradhan, N. Islam, C. Maitra, J.B. Coley, P. Blay, R.H.D. Corbet, R.E. Rothschild, K. Wood, A. Santangelo, U. Heber, J. Wilms

Publications

The eROSITA instrument on board Spectrum-Roentgen-Gamma (SRG) has completed four scans of the X-ray sky, leading to the detection of almost one million X-ray sources in eRASS1 alone, including multiple new X-ray binary candidates. We report on analysis of the X-ray binary 1eRASS J085039.9−421151, using a ∼55 ks long NuSTAR observation, following its detection in each eROSITA scan. An analysis of the eROSITA and NuSTAR X-ray spectra in combination with X-shooter data of the optical counterpart provide evidence of an X-ray binary with a red supergiant (RSG) companion, confirming previous results. However, we did determine a cooler spectral type for …

Stable Coronal X-Ray Emission Over 20 Yr Of Xz Tau, Steven M. Silverberg, Hans Moritz Günther, Pragati Pradhan, David A. Principe, P.C. Schneider, Scott J. Wolk

Publications

XZ Tau AB is a frequently observed binary young stellar object in the Taurus Molecular Cloud; XZ Tau B has been classified as an EXOr object. We present new Chandra/HETG-ACIS-S observations of XZ Tau AB, complemented with variability monitoring of the system with XMM-Newton, to constrain the variability of this system and identify high-resolution line diagnostics to better understand the underlying mechanisms that produce the X-rays. We observe two flares with XMM-Newton but find that outside of these flares the coronal X-ray spectrum of XZ Tau AB is consistent over 20 yr of observations. We compare the ensemble of XZ …

A Search For Subdwarf B Binaries Using Pulsation Timing From Tess, Tomomi Otani, Andrzej S. Baran, Lindsay C. Spence, Ted A. Von Hippel, Ellesse A. Lynum-Lozano, Julia M. Clark

Publications

Hot subdwarf B (sdB) stars are post-main-sequence stars of high temperature and gravity. Approximately 30% of sdBs exhibit stable pressure and/or gravity-mode pulsations, which can be used via the timing method to test for companion stars and determine their orbital solutions. We used short cadence data from the Transiting Exoplanet Survey Satellite (TESS) to search for previously undiscovered companions to sdBs. In this paper, we focus on searching for companions with orbital periods shorter than 13.5 days which are detectable within one sector of TESS data (about 27 days). The timing method requires that we derive pulsation frequencies in subsets …

Impact Of Mining Activities On Land Use Land Cover (Lulc) Using Geospatial Techniques In The Obuasi Municipality, Jonathan Arthur Quaye-Ballard, Samira Naa Yemoley Nsiah, Jephthah Marfo Nimoh, Titus Tienaah, Tina Dzigbordi Wemegah, Precious Adwoa Okyere

Publications

Introduction: Sustainable development, which balances economic, social, and environmental factors to meet the needs of the present and future generations, is a collective responsibility. Rapid population growth and intensification of socio-economic activities are causing significant changes in Land Use Land Cover (LULC), directly impacting ecosystem services, biodiversity, and climate. The Obuasi community is already facing environmental degradation and health problems due to gold mining.

Methodology: The study assessed the spatial extent and intensity of mining activities in the Obuasi Municipality on the LULC and predicted future LULC changes due to mining activities using geospatial techniques. The LULC changes were analysed …

Farming With Data: Tracing Critical Tensions Using Data Science For Food Justice, Marc Sager, Maximilan Sherard, Anthony Petrosino

Publications

In this manuscript, we explore the intersection of artificial intelligence (AI) and equitable learning in higher education, focusing on data science as a subset of AI and social justice as the core theme of equity. Our investigation sheds light on the nuanced tensions inherent in employing data science for social justice. Rooted in situated perspectives of learning and consequential learning, our study employs an instrumental case-study methodology and analysis techniques from interaction and conversation analysis. Collaborating with three undergraduate students and an urban farm, the students used data science practices to highlight inequities surrounding food justice and access to food. …

Sepsis: I Can Catch Your Lies – A New Paradigm For Deception Detection, Anku Rani, Dwip Dalal, Shreya Gautam, Pankaj Gupta, Vinija Jain, Aman Chadha, Amitava Das, Amit P. Sheth

Publications

Deception is the intentional practice of twisting information. It is a nuanced societal practice deeply intertwined with human societal evolution, characterized by a multitude of facets. This research explores the problem of deception through the lens of psychology, employing a framework that categorizes deception into three forms: lies of omission, lies of commission, and lies of influence. The primary focus of this study is specifically on investigating only lies of omission. We propose a novel framework for deception detection leveraging NLP techniques. We curated an annotated dataset of 876,784 samples by amalgamating a popular large-scale fake news dataset and scraped …