UMBC Faculty Collection

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

Browse

Now showing 1 - 20 of 10357

Fabrication of silicon W and G center embedded light-emitting diodes for electroluminescence
(AIP, 2024-11-20) Ebadollahi, Nikki; Namboodiri, Pradeep N.; Pederson, Christian; Veetil, Vijin Kizhake; Davanco, Marcelo I.; Srinivasan, Kartik A.; Katzenmeyer, Aaron M.; Pelton, Matthew; Pomeroy, Joshua M.
The need for reliable quantum light sources drives our research to study color centers (CCs) in silicon as telecommunication O-band emitters. Building from photoluminescence measurements, we compare new electroluminescence measurements. To this end, we synthesized CC-embedded p-i-n junctions in silicon, creating CC light-emitting diode devices. The two types of CCs synthesized were G-centers and W-centers, which show zero-phonon lines at approximately 1279 nm and 1218 nm, respectively. Here, we present our device design, fabrication process flow, and report on the device performance results from measurements to date.
Encounters in the New World: Jesuit Cartography of the Americas
(Taylor and Francis, 2023-07-17) Short, John Rennie
Emotion Regulation, Coping Self-Efficacy, and PTSD Symptoms Among Individuals in Residential Substance Use Disorder Treatment: A Brief Report
(Taylor & Francis, 2025-03-16) Mette, Meghan; Meyer, Laurel E.; Berg, Samantha; Wenzel, Kevin R.; Schacht, Rebecca
Individuals with posttraumatic stress disorder (PTSD) often have difficulty regulating their emotions and might use substances as an alternative to healthy emotion regulation strategies. Unsurprisingly, emotion regulation difficulties are often severe in those with substance use disorders (SUD), which are highly comorbid with PTSD. Enhancing coping self-efficacy (CSE) is a promising PTSD treatment strategy, but it is unclear how CSE relates to PTSD symptom severity in those that experience particular difficulty in regulating emotions (e.g. SUD populations), or how it might function in clinical, treatment seeking samples. This study assessed the potential moderation effect between CSE and emotion regulation difficulty with regard to PTSD symptoms among 126 adults in residential SUD treatment (Mage = 39.77 [SD = 12.25]; 37% women; 62% men; 48% white; 39% black; 14% multiracial/other). Hierarchical regression analyses revealed main effects for both emotion regulation and CSE, but no significant interaction between the two, emphasizing the distinction between belief in coping ability versus defined regulation skills and pointing to potential clinical implications. Additional research is needed to quantify the conceptual overlap between emotion regulation and CSE in this population.
A Learning Approach to SQL Query Results Ranking Using Skyline and Users' Current Navigational Behavior
(IEEE, 2013-12) Chen, Zhiyuan; Li, Tao; Sun, Yanan
Users often find that their queries against a database return too many answers, many of them irrelevant. A common solution is to rank the query results. The effectiveness of a ranking function depends on how well it captures users' preferences. However, database systems often do not have the complete information about users' preferences and users' preferences are often heterogeneous (i.e., some preferences are static and common to all users while some are dynamic and diverse). Existing solutions do not address these two issues. In this paper, we propose a novel approach to address these shortcomings: 1) it addresses the heterogeneous issue by using skyline to capture users' static and common preferences and using users' current navigational behavior to capture users' dynamic and diverse preferences; 2) it addresses the incompleteness issue by using a machine learning technique to learn a ranking function based on training examples constructed from the above two types of information. Experimental results demonstrate the benefits of our approach.
Effects of fire and grazing on biogeochemical cycles in Brazilian pastures using LPJmL5-Pasture-Burning
(EGU, 2025-04-08) Brunel, Marie; Wirth, Stephen; Drüke, Markus; Thonicke, Kirsten; Barbosa, H. M. J.; Heinke, Jens; Rolinski, Susanne
Abstract. Farmers across the world frequently use fire during the winter or dry season, to remove accumulated dead pasture biomass. These fire-management practices have profound effects on vegetation, soil nutrients, and biogeochemical cycles, yet they are rarely represented in process-based fire models embedded within Dynamic Global Vegetation Models (DGVMs). We couple the Chalumeau algorithm, which estimates expected burning dates, with the SPITFIRE module in the DGVM LPJmL and enable the modelling of fire as a grassland management method. Using this model development, we examine the short- and long-term impacts of varying burning strategies, frequencies, and livestock densities across distinct regions, using Brazil as a case study. Our results show that integrating grazing and fire management leads to a gradual decline in vegetation carbon, accompanied by a substantial reduction of the ecosystem and soil nitrogen. This study emphasises the importance of incorporating such practices into DGVMs to enhance the accuracy of impact assessments for pasture management. Furthermore, our findings call for improved data collection describing fire usage methods by farmers, as well as long-term measurements, particularly on vegetation, soil carbon and nitrogen development under burning practices.
Effects of backward-propagating waves and lumped mirror losses on self-induced transparency modelocking in quantum cascade lasers
(AIP, 2009-08-20) Talukder, Muhammad Anisuzzaman; Menyuk, Curtis
Work to date on self-induced transparency modelocking in quantum cascade lasers (QCLs) has neglected backward-propagating waves and lumped mirror losses. In this work, we remove these unrealistic assumptions. The qualitative features of the modelocking are unaffected by this improvement in the model, but the parameter regime in which stable modelocked pulses may be found is reduced. This reduction is due to incomplete gain recovery near the edges of the QCL when pulses pass through after reflecting from the mirrors, coincident with the loss of pulse energy at the mirrors. Spatial hole burning is observed in parameter regimes in which continuous waves can grow, but it does not affect the stability of the modelocking.
Dynamical Mechanisms Underlying the 2022/23 California Flooding: Analysis With A Stationary Wave Model
(2024) DeAngelis, Anthony M.; Schubert, Siegfried D.; Chang, Yehui; Lim, Young-Kwon; Thomas, Natalie; Koster, Randal D.; Bosilovich, Michael G.; Molod, Andrea M.; Collow, Allison; Dezfuli, Amin
In late December 2022 and the first half of January 2023, much of California experienced an unprecedented series of atmospheric rivers that produced heavy rains and near-record flooding. Previous work shows that a chain of dynamical events contributed to the extreme precipitation, including the development of a Rossby wave (as a result of forcing linked to the MJO) that emerged from the Indian Ocean in mid-December, and the subsequent development of a persistent positive Pacific North American (PNA) pattern that ultimately directed moisture onto the US West Coast starting in late December. Here, we use a stationary wave model (SWM) to further elucidate the dynamical and thermodynamical processes that drove the aforementioned chain of events. The results reveal the following: 1) The mid-December Rossby wave was likely induced by vorticity stretching and advection in the middle East linked indirectly to the MJO, 2) The initial development of the PNA in late December was triggered by transient and stretching sources of vorticity in the Pacific that were themselves induced by the aforementioned Rossby wave, and 3) The PNA was maintained through mid-January in part by diabatic heating west of Hawaii that was associated with anomalous precipitation influenced by the PNA circulation anomalies, thus representing a feedback on the PNA. One key finding from the SWM analysis is the limited direct role of tropical heating for inducing any of the dynamical mechanisms related to the California extreme event.
Dynamic Query Forms for Database Queries
(IEEE, 2014-09) Tang, Liang; Li, Tao; Jiang, Yexi; Chen, Zhiyuan
Modern scientific databases and web databases maintain large and heterogeneous data. These real-world databases contain hundreds or even thousands of relations and attributes. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. This paper proposes DQF, a novel database query form interface, which is able to dynamically generate query forms. The essence of DQF is to capture a user's preference and rank query form components, assisting him/her in making decisions. The generation of a query form is an iterative process and is guided by the user. At each iteration, the system automatically generates ranking lists of form components and the user then adds the desired form components into the query form. The ranking of form components is based on the captured user preference. A user can also fill the query form and submit queries to view the query result at each iteration. In this way, a query form could be dynamically refined until the user is satisfied with the query results. We utilize the expected F-measure for measuring the goodness of a query form. A probabilistic model is developed for estimating the goodness of a query form in DQF. Our experimental evaluation and user study demonstrate the effectiveness and efficiency of the system.
Double-header: Anuva Maloo for MCPS SMOB
(I Hate Politics Podcasts, 2025-04-04) Dasgupta, Sunil; Treviño, Lorena; Johnson, Walter
Guest Host Lorena Treviño of Walter Johnson High School talks with Montgomery Blair High School junior Anuva Maloo, one of two finalists for the Student Member of the Montgomery County Board of Education in 2025-26. The SMOB is one of eight on the county school board, nearly co-equal with other generally elected members, but voted in by MCPS secondary school students only. Music for this episode comes from Adam Bobrow. Suvarna Insta: @anuva4smob
Don't torque like that. Measuring compact object magnetic fields with analytic torque models
(2025-04-11) Stierhof, J. J. R.; Sokolova-Lapa, E.; Berger, K.; Vasilopoulos, G.; Thalhammer, P.; Zalot, N.; Ballhausen, R.; Mellah, I. El; Malacaria, C.; Rothschild, R. E.; Kretschmar, P.; Pottschmidt, Katja; Wilms, J.
Context. Changes of the rotational period observed in various magnetized accreting sources are generally attributed to the interaction between the in-falling plasma and the large-scale magnetic field of the accretor. A number of models have been proposed to link these changes to the mass accretion rate, based on different assumptions on the relevant physical processes and system parameters. For X-ray binaries with neutron stars, with the help of precise measurements of the spin periods provided by current instrumentation, these models render a way to infer such parameters as the strength of the dipolar field and a distance to the system. Often, the obtained magnetic field strength values contradict those from other methods used to obtain magnetic field estimates. Aims. We want to compare the results of several of the proposed accretion models. To this end an example application of these models to data is performed. Methods. We reformulate the set of disk accretion torque models in a way that their parametrization are directly comparable. The application of the reformulated models is discussed and demonstrated using Fermi/GBM and Swift/BAT monitoring data covering several X-ray outbursts of the accreting pulsar 4U 0115+63. Results. We find that most of the models under consideration are able to describe the observations to a high degree of accuracy and with little indication for one model being preferred over the others. Yet, derived parameters from those models show a large spread. Specifically the magnetic field strength ranges over one order of magnitude for the different models. This indicates that the results are heavily influenced by systematic uncertainties.
Distributed urban forest patch sampling detects edge effects and woodland condition for monitoring and management
(Wiley, 2025) Baker, Matthew; Yesilonis, Ian; Templeton, Laura; Shobe, Beatriz Manon; Bos, Jaelyn; Sonti, Nancy F.; Lautar, Katherine
Urban forest patches, including woodland interiors and bounding edge habitat, result from secondary succession and fragmentation of more extensive forested landscapes in the eastern United States. Management regimes, surrounding land use, and successional processes lead to distinct environments and contribute to local and regional heterogeneity. However, many woodlands are degraded due to frequent disturbance, aggressive exotic species, and heavy browsing, which stress canopies, reduce regeneration, and may reduce ecosystem services. Effective management requires rapid, repeatable assessment of forest composition, structure, and condition at the scale of local decision-making. We present and apply a protocol for characterizing urban woodlands that generates new insight into the status of urban woodlands and baseline data for change detection over time. Samples of overstory composition, ground cover, surface soil measurements, and the Schumacher Vine Encroachment Index were collected at 845 points across each of 47 patches across Baltimore, Maryland. Simple citywide summaries allowed characterization of Baltimore's urban overstories as overwhelmingly native, though dominated by a range of successional conditions. By contrast, we found that ground layers were predominantly exotic, with abundant invasives or ruderal native species benefiting from disturbed conditions. Seven overstory types were distinguished, the majority under threat from aggressive vines. Most soils showed little evidence of compaction, but variable organic content. Distributed data allowed cross-patch comparison as well as within-patch analyses along edge-to-interior gradients. Species diversity, nativity, and overstory basal area all increased toward woodland interiors, whereas soil compaction and vine encroachment decreased. Structural and compositional shifts in both overstory and ground layer species revealed indicators of edge (15.2–18.7 m) and interior (>41.5 m) conditions, as well as evidence of transitional zones with distinct patterns of biodiversity. Despite high levels of fragmentation and disturbance that challenge municipal land managers operating with limited resources, rapid, low-cost sampling enabled comparison across multiple scales, encouraging repeated sampling and adaptive response to changing forest conditions. Qualitative and quantitative analysis as well as specific examples illustrated the generic utility of the protocol for a range of applications and its ability to produce new insight enabling management action and informed conservation planning.
A Hybrid Scheduling Algorithm for Data Intensive Workloads in a MapReduce Environment
(2012-11) Nguyen, Phuong; Simon, Tyler A.; Halem, Milton; Chapman, David; Le, Quang
The specific choice of workload task schedulers for Hadoop MapReduce applications can have a dramatic effect on job workload latency. The Hadoop Fair Scheduler (FairS) assigns resources to jobs such that all jobs get, on average, an equal share of resources over time. Thus, it addresses the problem with a FIFO scheduler when short jobs have to wait for long running jobs to complete. We show that even for the FairS, jobs are still forced to wait significantly when the MapReduce system assigns equal sharing of resources due to dependencies between Map, Shuffle, Sort, Reduce phases. We propose a Hybrid Scheduler (HybS) algorithm based on dynamic priority in order to reduce the latency for variable length concurrent jobs, while maintaining data locality. The dynamic priorities can accommodate multiple task lengths, job sizes, and job waiting times by applying a greedy fractional knapsack algorithm for job task processor assignment. The estimated runtime of Map and Reduce tasks are provided to the HybS dynamic priorities from the historical Hadoop log files. In addition to dynamic priority, we implement a reordering of task processor assignment to account for data availability to automatically maintain the benefits of data locality in this environment. We evaluate our approach by running concurrent workloads consisting of the Word-count and Terasort benchmarks, and a satellite scientific data processing workload and developing a simulator. Our evaluation shows the HybS system improves the average response time for the workloads approximately 2.1x faster over the Hadoop FairS with a standard deviation of 1.4x.
Distinguishing between whole cells and cell debris using surface plasmon coupled emission
(Optica, 2018-04-01) Talukder, Muhammad Anisuzzaman; Menyuk, Curtis; Kostov, Yordan
Distinguishing between whole cells and cell debris is important in microscopy, e.g., in screening of pulmonary patients for infectious tuberculosis. We propose and theoretically demonstrate that whole cells and cell debris can be distinguished from the far-field pattern of surface plasmon coupled emission (SPCE) of a fluorescently-labeled sample placed on a thin metal layer. If fluorescently-labeled whole cells are placed on the metal film, SPCE takes place simultaneously at two or more different angles and creates two or more distinct rings in the far field. By contrast, if fluorescently-labeled cell debris are placed on the metal film, SPCE takes place at only one angle and creates one ring in the far-field. We find that the angular separation of the far-field rings is sufficiently distinct to use the presence of one or more rings to distinguish between whole cells and cell debris. The proposed technique has the potential for detection without the use of a microscope.
Dèyè mòn, gen mòn: Qualitative Examination of Drivers and Facilitators of Stigma as a Barrier to Sexual and Maternal Healthcare in Haiti
(Elsevier, 2025-04-04) Abrams, Jasmine; Rutledge, Jaleah D.; Raskin, Elizabeth; Kiyanda, Alexis; Gaillard, Joanne; Maxwell, Morgan; Kershaw, Trace
Haitian women face heightened risk of contracting HIV and encounter challenges in accessing quality care due to sociocultural and economic barriers. Stigma compounds these challenges, especially for pregnant women living with HIV. Globally, HIV-related stigma is a recognized barrier to testing, treatment, and prevention, contributing to low testing rates and substandard treatment and care. This study examines sources and origins of stigma that impact pregnant women's access to and experience with sexual and maternal healthcare. Qualitative data was collected from 85 participants via focus groups with HIV-positive pregnant women (n = 26) and HIV-negative pregnant women (n = 35). We also conducted 24 interviews with maternal health care providers, HIV prevention specialists, and traditional healers. We used thematic analysis to identify key themes related to drivers and facilitators of stigma and its impact on access to healthcare among pregnant women in rural Haiti. Drivers of stigma were: 1) Lack of Knowledge, 2) Stereotypes, Prejudice, & Blaming People Living with HIV (PLHIV), 3) Lack of Hospital Resources and Protocols. Facilitators of stigma were: 1) Underdeveloped Healthcare Infrastructure, 2) Classism, 3) Healthcare as a Commodity, 4) Hospital Policies and Practices, and 5) Patriarchal Society. Each of these facilitators uniquely influence HIV stigma experiences and practices. Our study identified complex multilevel drivers and facilitators of HIV and class related stigma and its impact on sexual and maternal healthcare access in Haiti, emphasizing the need for more comprehensive interventions that address psycho-socio-cultural determinants of health.
Dispersion management in a harmonically mode-locked fiber soliton laser
(Optica, 2000-02-01) Carruthers, Thomas F.; Duling, Irl N.; Horowitz, Moshe; Menyuk, Curtis
Harmonically mode-locked Er-fiber soliton lasers have become a reliable source of high-repetition-rate picosecond pulses in high-speed communications and photonic analog-to-digital conversion systems because of their low-noise, dropout-free operation. We have fabricated such a laser with a strongly dispersion-managed cavity and modeled its operation, and we have found that dispersion management significantly extends the power range over which uninterrupted single-pulse production is attained and dramatically decreases the effects of amplified spontaneous emission on the phase noise of the laser.
Design of a dual-channel modelocked fiber laser that avoids multi-pulsing
(Optica, 2019-05-13) Zhang, Xianting; Wang, Shaokang; Guo, Nan; Li, Feng; Menyuk, Curtis; Wai, P. K. A.
Multi-channel modelocked lasers and their design have attracted much attention. Here, we use the Swift-Hohenberg equation to study dual-channel simultaneous modelocking (DSML) in a fiber laser. When a quartic filter is added to the laser cavity, the stable dual-channel simultaneous modelocking can be obtained for a given filter bandwidth when frequency separation, ωₛ, is less than a calculated threshold, ωₜₕ. When ωₛ > ωₜₕ, a multipulsing instability occurs. We use a linear stability analysis to determine the limit that the multi-pulsing instability imposes on DSML, and we propose a cavity design that avoids the multi-pulsing instability.
Design and Verification of a Synchronus First In First Out (FIFO)
(2025-04-15) Penta, Yatheeswar; Islam, Riadul
This project focuses on designing and verifying a synchronous FIFO First In First Out (FIFO) memory, a critical component in digital systems for temporary data storage and seamless data transfer. The FIFO operates under a single clock domain, ensuring synchronized read and write operations, making it suitable for systems requiring high-speed, reliable data buffering. This design includes FIFO's key features, such as read and write operations, full and empty flag generation, and pointer management for memory control. The FIFO was implemented using Verilog to define the Register Transfer Level (RTL) design, ensuring functionality and timing requirements were met. For verification, three approaches were employed: (1) UVM-based Verification: A Universal Verification Methodology (UVM) testbench was developed to test the FIFO design rigorously. The testbench includes components like interface, sequence item, driver, monitor, scoreboard, agent, and environment. Directed and random tests were performed to verify corner cases, such as simultaneous reads and writes, full and empty conditions, and overflow and underflow scenarios; (2) Traditional Verilog Testbench: A standalone Verilog testbench was also used to validate the functionality of the FIFO through directed test scenarios and waveform analysis; (3) FPGA implementation: Additionally, the design was implemented on an FPGA for real-time testing to verify its functionality and timing behavior in hardware. FPGA-based verification ensured the design performed as expected under practical conditions. The results confirmed the correct operation of the FIFO, including accurate data transfer, flag behavior, and timing synchronization. The project successfully demonstrated the robustness and reliability of the synchronous FIFO design, highlighting its importance in modern digital systems for efficient data handling and buffering.
Descriptor: Event-Based Crossing Dataset (EBCD)
(IEEE, 2025-04-17) Mule, Joey; Challagundla, Dhandeep; Saini, Rachit; Islam, Riadul
Event-based vision revolutionizes traditional image sensing by capturing asynchronous intensity variations rather than static frames, enabling ultrafast temporal resolution, sparse data encoding, and enhanced motion perception. While this paradigm offers significant advantages, conventional event-based datasets impose a fixed thresholding constraint to determine pixel activations, severely limiting adaptability to real-world environmental fluctuations. Lower thresholds retain finer details but introduce pervasive noise, whereas higher thresholds suppress extraneous activations at the expense of crucial object information. To mitigate these constraints, we introduce the Event-Based Crossing Dataset (EBCD), a comprehensive dataset tailored for pedestrian and vehicle detection in dynamic outdoor environments, incorporating a multi-thresholding framework to refine event representations. By capturing event-based images at ten distinct threshold levels (4, 8, 12, 16, 20, 30, 40, 50, 60, and 75), this dataset facilitates an extensive assessment of object detection performance under varying conditions of sparsity and noise suppression. We benchmark state-of-the-art detection architectures—including YOLOv4, YOLOv7, YOLOv10, EfficientDet-b0, MobileNet-v1, and Histogram of Oriented Gradients (HOG)—to experiment upon the nuanced impact of threshold selection on detection performance. By offering a systematic approach to threshold variation, we foresee that EBCD fosters a more adaptive evaluation of event-based object detection, aligning diverse neuromorphic vision with real-world scene dynamics. We present the dataset as publicly available to propel further advancements in low-latency, high-fidelity neuromorphic imaging: https://ieee-dataport.org/documents/event-based-crossing-dataset-ebcd
Demonstration of polarization pulling using a fiber-optic parametric amplifier
(OPTICA, 2012-11-19) Stiller, B.; Morin, P.; Nguyen, D. M.; Fatome, J.; Pitois, S.; Lantz, E.; Maillotte, H.; Menyuk, Curtis; Sylvestre, T.
We report the observation of all-optical polarization pulling of an initially polarization-scrambled signal using parametric amplification in a highly nonlinear optical fiber. Broadband polarization pulling has been achieved both for the signal and idler waves with up to 25 dB gain using the strong polarization sensitivity of parametric amplifiers. We further derive the probability distribution function for the final polarization state, assuming a randomly polarized initial state, and we show that it agrees well with the experiments.
Deep Reinforcement Learning-Based Computation Computational Offloading for Space–Air–Ground Integrated Vehicle Networks
(2025) Xie, Wenxuan; Chen, Chen; Ju, Ying; Shen, Jun; Pei, Qingqi; Song, Houbing
In remote or disaster areas, where terrestrial networks are difficult to cover and Terrestrial Edge Computing (TEC) infrastructures are unavailable, solving the computation computational offloading for Internet of Vehicles (IoV) scenarios is challenging. Current terrestrial networks have high data rates, great connectivity, and low delay, but global coverage is limited. Space–Air–Ground Integrated Networks (SAGIN) can improve the coverage limitations of terrestrial networks and enhance disaster resistance. However, the rising complexity and heterogeneity of networks make it difficult to find a robust and intelligent computational offload strategy. Therefore, joint scheduling of space, air, and ground resources is needed to meet the growing demand for services. In light of this, we propose an integrated network framework for Space-Air Auxiliary Vehicle Computation (SA-AVC) and build a system model to support various IoV services in remote areas. Our model aims to maximize delay and fair utility and increase the utilization of satellites and Autonomous aerial vehicles (AAVs). To this end, we propose a Deep Reinforcement Learning algorithm to achieve real-time computational computational offloading decisions. We utilize the Rank-based Prioritization method in Prioritized Experience Replay (PER) to optimize our algorithm. We designed simulation experiments for validation and the results show that our proposed algorithm reduces the average system delay by 17.84%, 58.09%, and 58.32%, and the average variance of the task completion delay will be reduced by 29.41%, 48.74%, and 49.58% compared to the Deep Q Network (DQN), Q-learning and RandomChoose algorithms.

Browse

Recent Submissions