MD-SOAR Maryland Shared Open Access Repository
Not a member yet
34521 research outputs found
Sort by
A Participatory Design Approach to Improving Dancer Well-Being
No full textM.S. -- The University of Baltimore, 2025Thesis submitted to the Yale Gordon College of Arts and Sciences of The University of Baltimore in partial fulfillment of the requirements for the degree of Master of Science in Interaction Design and Information ArchitectureThis study explores the development of a low-fidelity mobile application designed to support dancers’ well-being by addressing the unique physical, mental, and emotional challenges they face. Drawing from a literature review, qualitative data from interviews, and participatory design methods, the research identifies key themes and needs rooted in autonomy, competency, and relatedness. These insights informed the creation of a prototype grounded in the CALO-RE taxonomy of behavior change, featuring tools for goal setting, personalization, gamification, and community engagement. Findings from user testing revealed both the app’s potential to streamline wellness practices and key areas for refinement, such as user flow and teacher integration. This paper highlights the untapped role of UI design in dancer well-being and demonstrates how a user-centered, participatory approach can lead to more effective, multifaceted tools that support dancers’ health beyond performance alon
Quantum Beats in Second-order Coherence: Principles and Applications
No full textThis dissertation is based on a novel experimental discovery of what we have labeled as a “ghost frequency comb (GFC),” observed from the measurements of nonlocal correlations with a laser beam. Unlike a conventional frequency comb, the laser beam used in this work does not consist of a pulse train—instead it is in a continuous-wave (cw) operation. In addition, the laser beam is in a multi-longitudinal-mode coherent state, far from a thermal state. The intensity fluctuations of the laser beam are found to be correlated within periodically spaced, precise, narrow time windows, giving periodic sharp correlation peaks. However, as long as the relative delay of the correlation falls into the region between these peaks, the intensity fluctuations of the laser beam remain uncorrelated. These experimental observations lead one to speculate whether there is a light source with such a peculiar statistical behavior, and beg two important questions: (1) How could a cw laser beam, approximated to be in coherent state, produce nontrivial intensity correlations like thermal state? (2) How could a cw laser generate a frequency comb? It is not surprising that a mode-locked laser can generate a train of sharp pulses as frequency comb, but the observation of a frequency comb from a cw laser beam would be unexpected. This dissertation provides a conclusive answer to these fundamentally interesting questions: the GFC is the result of two-photon interference—a pair of distinguishable groups of indistinguishable photons interfering with the pair itself. It is the nonlocal two-photon beats that produce the comb-like intensity fluctuation correlation. Besides its fundamental importance, this dissertation also explores useful applications of the GFC in precision spectroscopy. Nontrivial correlations of light have been a subject of debate since the development of intensity interferometry by Hanbury Brown and Twiss (HBT) in the 1950s. Conventional theory suggests that the HBT correlation of distant stars is the intrinsic statistical property of thermal state. Questions such as “Are the photons ‘bunched’ or ‘anti-bunched’ at the light source?” have been raised for decades. This dissertation also attempts to address this fundamental issue surrounding the origin of second-order correlation. In addition to the work with multi-cavity-mode cw laser beam mentioned above, a study of the second-order correlation of a multi-color or multi-frequency thermal light source in interferometric settings is reported. It is concluded that, like the GFC, the second-order correlation in multi-frequency thermal light also results from two-photon beats. Thus, this dissertation provides solid experimental evidence and theoretical analysis for exploring the nonlocal quantum interference as the origin of nontrivial correlations of light in general. The findings presented here should further corroborate the view that the two-photon correlation picture provides an accurate result in second-order coherence measurements
I Hate the News May 27
No full textFederal employee rights will change in the Trump-backed budget legislation “One Big Beautiful Bill.” Will budget-busting drugs like Jardiance and Farxiga soon cost less in Maryland? A new law sets up a mechanism. The state is fixing to charge for viewing land records and the Maryland State Bar and title attorneys are not happy. In Frederick County, MD, a fake mooning incident at a school board meeting. We have the audio, which may be more incendiary than the video. And more. Music by Arlington-based experimental music composer Pierre Bernasconi.https://open.spotify.com/episode/2G2iO1GoOVm5qJyRG2YoK
LOADS: LiDAR-based Privacy-Preserving Queue Monitoring and Analysis
No full text2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 17-21 March 2025, Washington DC, DC, USALong queues in retail and public environments can frustrate customers and negatively impact user experiences. Traditional camera-based monitoring systems are effective in analyzing queues, however, the potential for identification raises privacy concerns. Other queue-counting methods (such as WiFi or RFID) depend on user-carried devices or tags. In contrast, LiDAR sensors strictly measure distances and angles, which drastically reduces privacy risks and does not require users to carry specialized hardware. We present LOADS, an end-to-end, single-sensor, LiDAR-based IoT solution for queue-occupancy and wait-time estimation. LOADS incorporates Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to provide a robust method of accurately separating people from noise in real time. We employ a SARIMAX model to predict future queue lengths from historical data stored in a time-series database. A web interface shows real-time and historical queue information, enabling users to make informed decisions. We demonstrate the feasibility of LOADS in practical retail and conference scenarios, highlighting its privacy-preserving nature, accurate crowd estimation, and simple deployment.https://ieeexplore.ieee.org/document/1103866
Diurnal Cycle and Seasonality of Cirrus Clouds over the Amazon from a Seven-Year Ground-Based Lidar Record
No full textCirrus clouds strongly influence Earth’s radiation balance, yet their varied optical traits and formation pathways add uncertainty to climate models. Satellites offer a global view of cirrus but have key limitations: passive sensors struggle to detect thin layers, and active instruments in polar orbits miss the diurnal cycle. Consequently, long-term records above tropical forests are scarce. We analyzed 18 915 h of lidar data gathered near Manaus, Brazil (July 2011–December 2017), to characterize the cirrus clouds over the Amazon rainforest. An automated routine set cloud boundaries and multiple-scattering-corrected retrievals yielded cloud optical depth (COD) and lidar ratio. Cirrus were found to occur with a frequency of 73.2%. Thin layers (COD=0.03–0.30) are the most prevalent (33.0%), followed by sub-visual (0.30; 15.9%). The mean base and top altitudes were 12.8±2.2 km and 14.4±1.9 km, and the lidar ratio averaged 26.1±8.3 sr, reaching a peak for opaque cirrus. Thinner clouds clustered near the tropopause, while higher tops tracked the tropopause variability. A clear diurnal cycle shows a noon minimum frequency of occurrence and late-afternoon maximum, strongest for opaque cirrus and consistent with convective-anvil outflow. Optical properties such as COD, lidar ratio, and geometric properties follow a well-defined daily rhythm. Seasonally, cirrus are more frequent in the wet season (82.8%) than in the dry (54.5%). Bases, tops, and thickness are likewise larger in the wet season, whereas lidar ratios peak in the dry season. This long-term record benchmarks satellite retrievals, sharpens radiative-impact calculations and clarifies cirrus formation over tropical forests.LP acknowledges the support by the Coordena¸c˜ao de Aperfei¸coamento de Pessoal de N´vel Superior – Brasil (CAPES) – Finance Code 001. HB acknowledges the financial support from FAPESP under research grant 2013/50510-5. We thank Martina Kr¨amer for sharing the aircraft data on tropical cirrus. We thank EMBRAPA and the Brazilian Insti589 tute for Research in Amazonia for logistical support at the experimental site. Special thanks to Marcelo Rossi, Victor Souza, and Jocivaldo Souza at Embrapa, and to Ruth Araujo, Roberta Souza, Bruno Takeshi, and Glauber Cirino from INPAhttps://essopenarchive.org/users/934301/articles/1304897-diurnal-cycle-and-seasonality-of-cirrus-clouds-over-the-amazon-from-a-seven-year-ground-based-lidar-record?commit=7d67c920905c0c0888bfad1dda6b5a11f281215
Detection of Cortical Arousals in Sleep Using Multimodal Wearable Sensors and Machine Learning
No full textCortical arousals are brief brain activations that disrupt sleep continuity and contribute to cardiovascular, cognitive, and behavioral impairments. Although polysomnography is the gold standard for arousal detection, its cost and complexity limit use in long-term or home-based monitoring. This study presents a noninvasive machine learning based framework for detecting cortical arousals using the RestEaze™ system, a leg-worn wearable that records multimodal physiological signals including accelerometry, gyroscope, photoplethysmography (PPG), and temperature. Across multiple methods tested, including logistic regression, XGBoost, and Random Forest classi ers, we found that features related to movement intensity were the most effective in identifying cortical arousals, while heart rate variability had a comparatively lower impact. The framework was evaluated in 14 children with attentionde cit/hyperactivity disorder (ADHD) who were being assessed for possible restless leg syndrome related sleep disruption. The Random Forest model achieved the best performance, with a ROC AUC of 0.94. For the arousal class speci cally, it reached a precision of 0.57, recall of 0.78, and F1-score of 0.65. These ndings support the feasibility of wearable-based machine learning for real-world arousal detection, demonstrated here in a pediatric ADHD cohort with sleep-related behavioral concerns.This study was supported by the National Institutes of Health under award number 1R43MH133495 01A1 NIH SBIR Phase I The funding agency was not involved in the study design data collection data analysis decision to publish or preparation of the manuscripthttps://www.researchsquare.com/article/rs-6574148/v
Exploring Access to College and Career Resources in High/Low-Poverty Schools: An analysis of resource distribution in Maryland Public High Schools
No full textD.P.A. -- The University of Baltimore, 2025Dissertation submitted to the College of Public Affairs of The University of Baltimore in partial fulfillment of the requirements for the degree of Doctor of Public AdministrationThe present research examines inequities in college and career resources between High-poverty and Low-poverty schools in the Maryland State Public School system. This study utilizes data from Maryland State Department of Education Division and Assessment for the academic school year 2022-2023, which is considered public record. The units of analyses include 248 Maryland State Public High Schools, located in 23 Counties throughout Maryland. In SY2022-SY2023, there was a student enrollment of 409,729. This study examined data from 179 traditional high schools, 49 charter schools, and 20 vocational-technical high schools. Stratified sampling was used to examine 25 High-poverty and 61 Low-poverty schools identified by MSDE. Two analyses were conducted, an ANOVA and simple linear regression to examine disparities in resources distributed between High-poverty and Low-poverty schools. Results of analyses showed High-poverty schools received significantly less resources required for college and career preparation
Readiness for transformation in the academic workplace: A conceptual framework for practice, research, and change
No full textDespite legal mandates and historical investment from federal agencies, private funders, and colleges/universities, the representation of U.S.-born Black and African American, Latinx, and Indigenous faculty members remains abysmally low, meaning the academic workforce continues to be overwhelmingly White. Higher education institutions have made several efforts to increase the representation of racially minoritized faculty, but research shows that most colleges and universities are underprepared to transform in ways that genuinely welcome, retain, and support the success of these scholars. As such, campus administrators, funders, faculty, and diversity advocates have a vested interest in understanding how colleges and universities can be better prepared—or ready—to undertake transformation. This conceptual article advances a framework for examining readiness for transformation. Drawing from multiple fields and disciplines, we define readiness for transformation as the degree to which a higher education organization is prepared to undertake deep, cultural and structural changes that promote racial equity in the academic workplace. We argue that readiness for transformation demands attention to the individual/collective, organizational, and external levels—or what we refer to as “nested influences.” We identify conditions that shape readiness within each level, and within each condition, examples of evidence-based barriers and facilitators of readiness. We also make key recommendations for researchers and practitioners about how to use the framework to understand and facilitate transformation efforts. (PsycInfo Database Record (c) 2025 APA, all rights reserved)Funded by: National Science Foundation, Eddie Bernice Johnson INCLUDES Initiativehttps://psycnet.apa.org/doiLanding?doi=10.1037%2Fdhe000067
Paradoxes and paradigms: if polyglycine is the polymer, then what is the monomeric repeating unit?
No full textProteins/polypeptides are a large class of organic/biochemical/biomedical related molecules most simply and most generally described by the generic structure NH₂CH(R¹)CONHCH(R²)CONHCH(R³),,, NHCH(Rˢᵒᵐᵉ ˡᵃʳᵍᵉ ⁿᵘᵐᵇᵉʳ)COOH, or more properly as the corresponding zwitterion. In these species, R¹, R², Rˢᵒᵐᵉ ˡᵃʳᵍᵉ ⁿᵘᵐᵇᵉʳ are arbitrarily chosen from a well-defined collection of some 20 affixed groups. The archetypal example is polyglycine, the related “shorter” glycine, diglycine … hexaglycine. For these species, all of these R groups are H and much of their understanding has come from calorimetric determinations of their enthalpies of formation, and more recently high-level quantum chemical calculations. In the current study, we ask the question given as the title of this paper “If polyglycine is the polymer, then what is the monomeric repeating unit)?” Three natural choices are given,− CH₂–CO–NH− , −NH–CH₂− CO–, or− CH₂–NH–CO− . From the analysis of the energetics of the related dimer, 2,5-diketopierazine, we demonstrate that these choices are in fact equivalent.MPS gratefully acknowledges the Slovenian Research and Innovation Agency (ARIS Grant P1-0045, Inorganic Chemistry and Technology) for fnancial support.https://link.springer.com/article/10.1007/s11224-025-02563-
Correlated Modes of Spatiotemporal Variations between Light-Absorbing Aerosols and Tropospheric Temperature over the Indian Region
No full textLight-absorbing aerosols influence atmospheric temperatures by absorbing solar radiation, thereby altering the contrast between day and night temperatures. This study investigates the correlation between these aerosols and day-night (D-N) temperatureThis research is supported by the NASA Atmospheric Composition Modeling and Analysis Program (ACMAP, award number 80NSSC19K0950) and the Science of Terra, Aqua, and Suomi-NPP program (award number 80NSSC18K0846)https://www.authorea.com/doi/full/10.22541/essoar.174582434.40962892?commit=16e1a191b479880559928fa3fb159a022dfdf76