UMBC Faculty Collection

Permanent URI for this collectionhttp://hdl.handle.net/11603/15

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Magneto-optics in a van der Waals magnet tuned by self-hybridized polaritons
(Springer Nature, 2023-08) Dirnberger, Florian; Quan, Jiamin; Bushati, Rezlind; Diederich, Geoffrey M.; Florian, Matthias; Klein, Julian; Mosina, Kseniia; Sofer, Zdenek; Xu, Xiaodong; Kamra, Akashdeep; Garc�a-Vidal, Francisco J.; Al�, Andrea; Menon, Vinod M.
Controlling quantum materials with light is of fundamental and technological importance. By utilizing the strong coupling of light and matter in optical cavities1?3, recent studies were able to modify some of their most defining features4?6. Here we study the magneto-optical properties of a van der Waals magnet that supports strong coupling of photons and excitons even in the absence of external cavity mirrors. In this material?the layered magnetic semiconductor CrSBr?emergent light?matter hybrids called polaritons are shown to substantially increase the spectral bandwidth of correlations between the magnetic, electronic and optical properties, enabling largely tunable optical responses to applied magnetic fields and magnons. Our results highlight the importance of exciton?photon self-hybridization in van der Waals magnets and motivate novel directions for the manipulation of quantum material properties by strong light?matter coupling.
Unifying radiative transfer models in computer graphics and remote sensing, Part II: A differentiable, polarimetric forward model and validation
(Elsevier, 2024-01-03) Salesin, Katherine; Knobelspiesse, Kirk D.; Chowdhary, Jacek; Zhai, Peng-Wang; Jarosz, Wojciech
The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 2 of this work, we demonstrate that Monte Carlo forward models in computer graphics are capable of sufficient accuracy for remote sensing by extending Mitsuba 3, a forward and inverse modeling framework recently developed in the computer graphics community, to simulate simple atmosphere-ocean systems and show that our framework is capable of achieving error on par with codes currently used by the remote sensing community on benchmark results.
Unifying radiative transfer models in computer graphics and remote sensing, Part I: A survey
(Elsevier, 2023-12-02) Salesin, Katherine; Knobelspiesse, Kirk D.; Chowdhary, Jacek; Zhai, Peng-Wang; Jarosz, Wojciech
The constellation of Earth-observing satellites continuously collects measurements of scattered radiance, which must be transformed into geophysical parameters in order to answer fundamental scientific questions about the Earth. Retrieval of these parameters requires highly flexible, accurate, and fast forward and inverse radiative transfer models. Existing forward models used by the remote sensing community are typically accurate and fast, but sacrifice flexibility by assuming the atmosphere or ocean is composed of plane-parallel layers. Monte Carlo forward models can handle more complex scenarios such as 3D spatial heterogeneity, but are relatively slower. We propose looking to the computer graphics community for inspiration to improve the statistical efficiency of Monte Carlo forward models and explore new approaches to inverse models for remote sensing. In Part 1 of this work, we examine the evolution of radiative transfer models in computer graphics and highlight recent advancements that have the potential to push forward models in remote sensing beyond their current periphery of realism.
Ethical Challenges in Intercultural Citizenship Education with ?Difficult Topics? in the World Language Classroom and Beyond
(MDPI, 2025-02-24) Porto, Melina; Golubeva, Irina; Byram, Michael
The purpose of this article is to examine the ethical challenges that arise in the world language classroom and beyond from using intercultural citizenship pedagogy. Intercultural citizenship is, in general, seen as a recent and positive development in intercultural language education for helping students engage with topics of social significance in the classroom. However, there are ethical challenges involved, for instance, related to the political or sensitive nature of such topics. We define and illustrate some of these ethical concerns and their implications for education by drawing on an intercultural citizenship project about COVID-19 carried out in two higher education contexts in 2020. The analysis of this example shows that these ethical concerns are unavoidable but can be minimised with an action research perspective and a combination of pedagogies of intercultural citizenship, discomfort, and the arts. We conclude with a discussion of the transferability of the example and its consequences for any language and intercultural communication teaching which deals with controversial and sensitive matters.
Queering ?Common Sense?: Using Critical Discourse Analysis of LGBTQ Book Bans in Florida Public Schools to Unmask Heteronormativity
(University of Nebraska, 2025-02-18) Zito, Talia; Morse, Nicole
Historically, censorship of LGBTQ+ content in education has been rooted in socio-political efforts to marginalize non-heteronormative identities. However, even those who oppose censorship tend to frame their arguments around concepts like ?age-appropriateness? and ?protecting children.? Our Critical Discourse Analysis examines formal challenges to And Tango Makes Three in one Florida school district in 2022 to show how these concepts are deployed on both sides of the debate. The book, depicting a same-sex penguin couple raising a chick, faced objections under Florida?s HB 1557, a law designed to restrict discussions of sexual orientation and gender identity in schools. Ultimately, the picture book was removed from the shelves despite proponents advocating for its educational value. Our analysis examines how both opponents and proponents of LGBTQ+ children?s literature rely on ?common sense? discourse and arguments about ?age appropriateness? to support their claims. We argue that such discursive moves, while seemingly neutral, perpetuate discriminatory ideologies and reinforce normative power structures. Given that both sides? appeals to common sense and age-appropriatness fail to challenge and often reinforce exclusionary beliefs, we argue that advocates should look beyond common sense and instead draw on queer theory as a resource in these struggles against censorship. Effective advocacy must confront how heteronormative assumptions are embedded in educational policies and practices. Queer theory offers a powerful framework to reimagine advocacy strategies, challenging the notion of political neutrality by exposing how what appears to be unbiased or ?common sense? is often deeply embedded in normative assumptions and power dynamics. By reframing the discourse, advocates can challenge and dismantle the underlying heteronormative ideologies. Embracing queer theoretical insights can lead to a more inclusive and equitable environment, where LGBTQ+ literature is celebrated for its role in promoting diversity, challenging normative constructs, and reimagining educational environments and social worlds.
Global linearization without hyperbolicity
(2025-02-13) Kvalheim, Matthew D.; Sontag, Eduardo D.
We give a proof of an extension of the Hartman-Grobman theorem to nonhyperbolic but asymptotically stable equilibria of vector fields. Moreover, the linearizing topological conjugacy is (i) defined on the entire basin of attraction if the vector field is complete, and (ii) a $C^{k\geq 1}$ diffeomorphism on the complement of the equilibrium if the vector field is $C^k$ and the underlying space is not $5$-dimensional. We also show that the $C^k$ statement in the $5$-dimensional case is equivalent to the $4$-dimensional smooth Poincar\'{e} conjecture.
Key Governance Practices That Facilitate the Use of Remote Sensing Information for Wildfire Management: A Case Study in Spain
(MDPI, 2025-01) Prados, Ana; Allen, Mackenzie
We present results from a comprehensive analysis on the use of Earth Observations (EO) in Spain for wildfire risk management. Our findings are based on interviews with scientists, firefighters, forest engineers, and other professionals from government and private sector organizations in nine autonomous regions in Spain. Our aim is to identify the key governance practices facilitating or hindering the use of remote sensing (RS) information and to provide recommendations for improving their integration into landscape management and fire suppression activities to reduce wildfire risk. We share several case studies detailing activities and institutional arrangements facilitating the translation of satellite science and research into decision-making environments, with a focus on how this knowledge flows among the various stakeholder categories. Among the barriers faced by fire management teams in Spain, we identified institutional silos, lack of technical skills in satellite data processing and analysis, and the evolving acceptance of satellite data by decision makers.
Delivery of Tempol from Polyurethane Nanocapsules to Address Oxidative Stress Post-Injury
(ACS, 2025-02-19) Ale, Temitope; Ale, Tolulope; Baker, Kimberly J.; Zuniga, Kameel M.; Hutcheson, Jack; Lavik, Erin
Traumatic brain injuries (TBIs) result in significant morbidity and mortality due to the cascade of secondary injuries involving oxidative stress and neuroinflammation. The development of effective therapeutic strategies to mitigate these effects is critical. This study explores the fabrication and characterization of polyurethane nanocapsules for the sustained delivery of Tempol, a potent antioxidant. The nanocapsules were designed to extend the release of Tempol over a 30-day period, addressing the prolonged oxidative stress observed post-TBI. Tempol-loaded polyurethane nanocapsules were synthesized using interfacial polymerization and nanoemulsion techniques. Two generations of nanocapsules were produced, differing in Tempol loading and PEGylation levels. The first generation, with lower Tempol loading, exhibited an average size of 159.8 � 12.61 nm and a Z-average diameter of 771.9 � 87.95 nm. The second generation, with higher Tempol loading, showed an average size of 141.4 � 6.13 nm and a Z-average diameter of 560.7 � 171.1 nm. The zeta potentials were ?18.9 � 5.02 mV and ?11.9 � 3.54 mV for the first and second generations, respectively. Both generations demonstrated the presence of urethane linkages, confirmed by Fourier Transform Infrared Spectroscopy (FTIR). Loading studies revealed Tempol concentrations of 61.94 � 3.04 ?g/mg for the first generation and 77.61 � 3.04 ?g/mg for the second generation nanocapsules. Release profiles indicated an initial burst followed by a sustained, nearly linear release over 30 days. The higher PEGylation in the second generation nanocapsules is advantageous for intravenous administration, potentially enhancing their therapeutic efficacy in TBI treatment. This study demonstrates the feasibility of using polyurethane nanocapsules for the prolonged delivery of Tempol, offering a promising approach to manage oxidative stress and improve outcomes in TBI patients. Future work will include testing these nanocapsules in vivo to determine their potential at modulating recovery from TBI.
Supporting Campus Activism through Creating DIY-AT in a Social Justice Aligned Makerspace
(ACM, 2025-01-31) Higgins, Erin; Oliver, Zaria; Hamidi, Foad
Utilizing digital fabrication methods (e.g., 3D printing) has exciting implications for the design and production of customized assistive technology (AT). However, utilizing these tools currently requires a high level of technical expertise as well as time and money investments. Furthermore, facilitating collaboration between end users and makers needs effective and inclusive approaches with shared language and support for asynchronous, dispersed communication of design requirements. While these Do-It-Yourself (DIY) approaches are shown to support end-user agency and furthering technology democratization, research has to yet explore how they can further align with social justice values and practices. We explored these possibilities by facilitating DIY-AT design with students with disabilities, activist staff members, and community members within a university makerspace. By explicitly encouraging participants to consider social justice issues important to them as they engaged in DIY-AT design, we studied the considerations and supports needed for facilitating flexible co-design activities and broader conversations about accessibility barriers at the university. Adopting a transdisciplinary approach, we offer lessons learned about the potential of co-designing DIY-ATs as a way to investigate questions of social justice, inclusion, and access in academic contexts. We show how these created DIY-ATs can be leveraged by students and staff as tangible artifacts to encourage more funding and support from university administration for accessibility initiatives.
Exploring the Relationship Between Nursing Staff and Family Members? Appraisal of Resident Care in Nursing Homes: The Role of Facility Ownership
(MDPI, 45699) Millar, Roberto; Diehl, Christin; Kusmaul, Nancy; Stockwell, Ian
Background/Objectives: To address long-standing staffing challenges and elevating care standards in the United States, new legislation will require a minimum of 0.55 h per resident day (HPRD) of registered nurse (RN) care, 2.45 HPRD of certified nursing aide (CNA) care, and a combined total of 3.48 HPRD across any combination of nursing staff. We examine differences in family members? views of care quality between facilities meeting the minimum staffing requirements and those that do not and whether there is any difference in those associations by facility ownership. Methods: This cross-sectional study utilized public data from 218 Medicare and Medicaid-certified nursing facilities in Maryland, collected in 2023. We used regression analyses to examine the association between staffing requirements and quality of care ratings, considering facility ownership status as a potential moderator. Results: Compared to facilities with CNA staffing levels below the cut off, facilities that met the CNA staffing requirement were rated more favorably by family members in overall quality and across the subdomains of staffing, care, activities, and security. In contrast, meeting the RN 0.55 cut off was not associated with family ratings across any quality domain. A facility for-profit status did not moderate the relationship between staffing and family ratings. Conclusions: These results suggest that CNA staff time is a significant driver of care quality and that non-profit facilities may already be closer to meeting new federal requirements. These findings highlight the need for regulations that support the minimum nursing staffing requirements to enhance care quality. Future research should identify the specific factors contributing to higher quality care in non-profit facilities and explore ways to implement these practices in for-profit settings.
An Ecosystem of Support: A U.S. State Government-Supported DIY-AT Program for Residents with Disabilities
(ACM, 2024-10-27) Higgins, Erin; Sakowicz, Marie E.; Hamidi, Foad
While Do-It-Yourself (DIY) approaches to producing customized assistive technology (AT) have been shown to support end-user agency and further technology democratization, research has shown that the utilization of digital fabrication tools requires a high level of technical expertise as well as financial investment. Facilitation of collaborations between end users and makers is a possible solution to these issues, however, previous efforts have uncovered issues around shared language, lack of consistent communication, and liability concerns. A promising direction for addressing these issues is to conceive of new types of multi-organizational collaborations that draw on complementary strengths. We explored these possibilities through an Action Research study in which we collaborated with the Maryland department of disability to launch a state level DIY-AT program. Through developing and supporting this program, we studied motivations for participation, relationships to creating and customizing AT, how individuals participated in and grew the program, and how the program allowed for individuals to reflect on their disabilities and AT use. Our findings generated an ecosystem model describing the interdependent relationships between and roles held by each stakeholder in the state DIY-AT program as well as a description of how this ecosystem encouraged expanding and transcending the understandings and definitions of AT and disability. We offer lessons learned for the design of future government-supported DIY-AT programs and reflections on the role of HCI researchers within these ecosystems.
Co-designing a 3D-Printed Tactile Campus Map With Blind and Low-Vision University Students
(ACM, 2024-10-27) Crawford, Kirk Andrew; Posada, Jennifer; Okueso, Yetunde Esther; Higgins, Erin; Lachin, Laura; Hamidi, Foad
Blind and low-vision (BLV) university students often encounter campus accessibility challenges that impede their ability to navigate campus environments effectively. The lack of customization offered by some navigational-focused assistive technologies (ATs) often falls short in addressing their diverse and specific navigational needs. 3D printing, a promising tool for creating affordable and personalized aids, has been explored as a method to create customized tactile maps to aid BLV individuals with general navigation. However, the use of 3D-printed tactile maps by BLV university students and the impact of their direct involvement in the design process remain largely unexplored. We employed a participatory design (PD) approach to engage BLV students from a university in the United States (U.S.) through semi-structured interviews and a co-design session to create a prototype 3D-printed tactile map. Additionally, we consulted with a blind rehabilitation and independence expert for insight into their perspective on AT and, more specifically, tactile maps and showed the prototype to a group of visually impaired youth and instructors visiting our university for feedback. We present and discuss our findings, provide an overview of the prototype design process, and outline future work.
Decoding the Privacy Policies of Assistive Technologies
(ACM, 2024-10-22) Crawford, Kirk; Khoo, Yi Xuan; Kumar, Asha; Mentis, Helena; Hamidi, Foad
As assistive technologies (ATs) have evolved, they have become increasingly connected. However, these increasing connections pose significant privacy challenges, especially when user privacy is described using complex privacy policies. Our study decodes the privacy policies of 18 ATs to understand how data collection and processing are communicated with users. We find that (1) AT privacy policies are structured to offer legal protections to their companies and not always to protect user privacy, (2) AT privacy policies are absent protections for individuals with disabilities, (3) AT policies are inconsistent when describing data storage, handling, and security methods, (4) AT policies often do not differentiate between essential and non-essential data collection, and (5) there is often a lack of transparency in AT policies around third-party data sharing. These findings reveal that AT privacy policies overlook and underestimate a user?s acceptable privacy risks. We conclude our study by discussing AT design implications.
Advancing climate model interpretability: Feature attribution for Arctic melt anomalies
(2025-02-11) Ale, Tolulope; Schlegel, Nicole-Jeanne; Janeja, Vandana
The focus of our work is improving the interpretability of anomalies in climate models and advancing our understanding of Arctic melt dynamics. The Arctic and Antarctic ice sheets are experiencing rapid surface melting and increased freshwater runoff, contributing significantly to global sea level rise. Understanding the mechanisms driving snowmelt in these regions is crucial. ERA5, a widely used reanalysis dataset in polar climate studies, offers extensive climate variables and global data assimilation. However, its snowmelt model employs an energy imbalance approach that may oversimplify the complexity of surface melt. In contrast, the Glacier Energy and Mass Balance (GEMB) model incorporates additional physical processes, such as snow accumulation, firn densification, and meltwater percolation/refreezing, providing a more detailed representation of surface melt dynamics. In this research, we focus on analyzing surface snowmelt dynamics of the Greenland Ice Sheet using feature attribution for anomalous melt events in ERA5 and GEMB models. We present a novel unsupervised attribution method leveraging counterfactual explanation method to analyze detected anomalies in ERA5 and GEMB. Our anomaly detection results are validated using MEaSUREs ground-truth data, and the attributions are evaluated against established feature ranking methods, including XGBoost, Shapley values, and Random Forest. Our attribution framework identifies the physics behind each model and the climate features driving melt anomalies. These findings demonstrate the utility of our attribution method in enhancing the interpretability of anomalies in climate models and advancing our understanding of Arctic melt dynamics.
Identifying Flaky Tests in Quantum Code: A Machine Learning Approach
(2025-02-06) Kaur, Khushdeep; Kim, Dongchan; Jamshidi, Ainaz; Zhang, Lei
Testing and debugging quantum software pose significant challenges due to the inherent complexities of quantum mechanics, such as superposition and entanglement. One challenge is indeterminacy, a fundamental characteristic of quantum systems, which increases the likelihood of flaky tests in quantum programs. To the best of our knowledge, there is a lack of comprehensive studies on quantum flakiness in the existing literature. In this paper, we present a novel machine learning platform that leverages multiple machine learning models to automatically detect flaky tests in quantum programs. Our evaluation shows that the extreme gradient boosting and decision tree-based models outperform other models (i.e., random forest, k-nearest neighbors, and support vector machine), achieving the highest F1 score and Matthews Correlation Coefficient in a balanced dataset and an imbalanced dataset, respectively. Furthermore, we expand the currently limited dataset for researchers interested in quantum flaky tests. In the future, we plan to explore the development of unsupervised learning techniques to detect and classify quantum flaky tests more effectively. These advancements aim to improve the reliability and robustness of quantum software testing.
LLM-ProS: Analyzing Large Language Models' Performance in Competitive Problem Solving
(2025-02-04) Hossain, Md Sifat; Tabassum, Anika; Arefin, Md Fahim; Zaman, Tarannum Shaila
The rapid advancement of large language models has opened new avenues for automating complex problem-solving tasks such as algorithmic coding and competitive programming. This paper introduces a novel evaluation technique, LLM-ProS, to assess the performance of state-of-the-art LLMs on International Collegiate Programming Contest (ICPC) problems. Using a curated dataset of 166 World Finals problems from 2011 to 2024, we benchmark the models' reasoning, accuracy, and efficiency. We evaluate the five models-GPT-4o, Mistral Large, Llama-3.1-405B, and the o1 family, consisting of o1-mini and o1-preview, across critical metrics like correctness, resource utilization, and response calibration. Our results reveal significant differences in the models' abilities to generalize, adapt, and solve novel problems. We also investigated the impact of training methodologies, dataset contamination, and chain-of-thought reasoning on model performance. The findings provide new insights into optimizing LLMs for algorithmic tasks, highlighting both strengths and limitations of current models.
Gender Dynamics in Software Engineering: Insights from Research on Concurrency Bug Reproduction
(2025-02-27) Zaman, Tarannum Shaila; Kishan, Macharla Hemanth; Lota, Lutfun Nahar
Reproducing concurrency bugs is a complex task due to their unpredictable behavior. Researchers, regardless of gender, are contributing to automating this complex task to aid software developers. While some studies have investigated gender roles in the broader software industry, limited research exists on gender representation specifically among researchers working in concurrent bug reproduction. To address this gap, in this paper, we present a literature review to assess the gender ratio in this field. We also explore potential variations in technique selection and bug-type focus across genders. Our findings indicate that female researchers are underrepresented compared to their male counterparts in this area, with a current male-to-female author ratio of 29:6. Through this study, we emphasize the importance of fostering gender equity in software engineering research, ensuring a diversity of perspectives in the development of automated bug reproduction tools.
A Decentralized, Secure, and Reliable Vehicle Platoon Formation With Privacy Protection for Autonomous Vehicles
(IEEE, 2025-02-20) Khan, Rabia; Mehmood, Amjad; Song, Houbing; Maple, Carsten
Vehicle platooning enables vehicles to drive cooperatively on highways and motorways. This is to weigh numerous benefits such as lesser fuel consumption, safe drive and better road utilization. The main research focus of vehicle platoons is secure and dynamic platoon formation and ensuring privacy of vehicular data. Platoons are not safe from cyber-attacks and key is to safeguard the platoons from different known/unknown cyber threats. This paper introduces a dynamic and secure platoon formation technique targeting three different vehicle conditions on road. While the private credentials of CAVs is protected using zk-SNARK encryption protocol through permissioned Blockchain. The proposed system has been evaluated for its performance against DDoS and impersonation attack. Platoon formation time has been compared with other benchmarks and shows better results. While the performance against DDoS and impersonation attacks in comparison to the benchmarks is also improved. Since the limitation of zk-SNARK is it takes time to generate a proof and this has been also the focus of this study. The protocol has been fine tuned to adjust its parameters so that it could generate proof in less possible time.
Predicting Students' Interest from Small Group Conversational Characteristics: Insights from an AI Literacy Education with High School Students
(ACM, 2025-02-18) Zha, Shenghua; Chen, Lujie Karen; Hung, Woei; Gong, Na; Moore, Pamela; Klemetsrud, Bethany
Recent years have seen developments in AI instructional practices for K-12 students. In literature, students' interest in AI is shown to correlate with gaining AI knowledge; however, little is known about how AI interest manifests in classroom discourses during AI literacy lessons. This study examined students' participation in an integrated AI curriculum delivered to a cognitive science class in a high school in the southern US. Students worked in small groups and built a supervised machine learning model to recognize kids' drawings at different stages of artistic development. Our analysis showed that semantic features extracted from students' small group conversations significantly predicted their interest in learning AI. However, we found no significant relationship between students' social construction of knowledge and their interests. This study sheds light on the relationship between the learning process and interest; when further developed, this analysis may be developed into a classroom activity analytics tool that may provide real-time feedback to teachers engaged in AI literacy education to enhance teaching effectiveness in this nascent content area.
Polyurethane Nanocapsules Incorporating Epigallocatechin Gallate, A Green Tea Extract
(Wiley, 2025-02-26) Ale, Temitope; Ghunney, Nhyira; Pandala, Narendra; Tucker, Budd; McFadden, Kassandra; Hutcheson, Jack; Lavik, Erin
Explosions cause 79% of combat-related injuries, often leading to traumatic brain injury (TBI) and hemorrhage. Epigallocatechin gallate (EGCG), a green tea polyphenol, aids neuroprotection and wound healing. In this work, we sought to investigate the fabrication and characterization of polyurethane nanocapsules encapsulating EGCG, demonstrating controlled, on-demand release, and highlighting their potential for targeted therapeutic delivery in trauma care.

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