Maryland Shared Open Access Repository

MD-SOAR is a shared digital repository platform for twelve colleges and universities in Maryland. It is currently funded by the University System of Maryland and Affiliated Institutions (USMAI) Library Consortium (usmai.org) and other participating partner institutions. MD-SOAR is jointly governed by all participating libraries, who have agreed to share policies and practices that are necessary and appropriate for the shared platform. Within this broad framework, each library provides customized repository services and collections that meet local institutional needs. Please follow the links below to learn more about each library's repository services and collections.

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Recent Submissions

Radiation-driven Destruction of N-heterocycles in the Presence and Absence of Water Ice
(American Astronomical Society, 2026-01-28) Tribbett, Patrick; Yarnall, Yukiko; Gerakines, Perry A.; Hudson, Reggie L.; Materese, Christopher K.
Simple N-heterocycles are expected to be an abundant class of molecules within the interstellar medium, and increasingly complex heterocycles (e.g., nucleobases) have been detected within meteoritic organic material and in samples returned from the carbonaceous asteroid Bennu. Despite this, these molecules have not been detected in any interstellar environment or in the outer solar system. One possible reason for the nondetection of N-heterocycles could be that they are less stable to radiation than the aromatic compounds that have been identified in space (e.g., benzene). Here, we present the radiolytic destruction kinetics of benzene and several N-heterocycles, both as single-component ices and as dilute water-ice mixtures at 15 K, where we have quantified the radiolytic destruction rate constants and radiolytic half-lives of these aromatic molecules using IR spectroscopy. We found that the destruction rate constants for single-component ices, and to a lesser extent for water-ice mixtures, depended on the number of nitrogen atoms in the aromatic ring. Our radiolytic half-lives indicate that these molecules should persist in extraterrestrial radiation environments, and radiolytic destruction cannot fully explain the nondetections of N-heterocycles.
PhysE-Inv: A Physics-Encoded Inverse Modeling approach for Arctic Snow Depth Prediction
(2026-01-23) Sampath, Akila; Janeja, Vandana; Wang, Jianwu
The accurate estimation of Arctic snow depth ($h_s$) remains a critical time-varying inverse problem due to the extreme scarcity and noise inherent in associated sea ice parameters. Existing process-based and data-driven models are either highly sensitive to sparse data or lack the physical interpretability required for climate-critical applications. To address this gap, we introduce PhysE-Inv, a novel framework that integrates a sophisticated sequential architecture, an LSTM Encoder-Decoder with Multi-head Attention and physics-guided contrastive learning, with physics-guided inference.Our core innovation lies in a surjective, physics-constrained inversion methodology. This methodology first leverages the hydrostatic balance forward model as a target-formulation proxy, enabling effective learning in the absence of direct $h_s$ ground truth; second, it uses reconstruction physics regularization over a latent space to dynamically discover hidden physical parameters from noisy, incomplete time-series input. Evaluated against state-of-the-art baselines, PhysE-Inv significantly improves prediction performance, reducing error by 20\% while demonstrating superior physical consistency and resilience to data sparsity compared to empirical methods. This approach pioneers a path for noise-tolerant, interpretable inverse modeling, with wide applicability in geospatial and cryospheric domains.
Quantification of Aspergillus nidulans Actin Dynamics during Early Growth and Septum Formation
(2026-01-28) Huso, Walker; Hill, Garrett; Tarimala, Greeshma; Lee, Jiyon; Doan, Alexander G.; Lee, JungHun; Gray, Kelsey; Edwards, Harley; Harris, Steven D.; Marten, Mark
Filamentous fungi have complex, three-dimensional growth patterns and a non-adherent nature, which can present challenges for live-cell imaging for quantitative assessment of dynamic cellular processes. To address these challenges, a live-cell imaging system has been modified to constrain the model fungus Aspergillus nidulans to growth in a single focal plane. This enables high-resolution time-lapse imaging of actin dynamics throughout development using a Lifeact actin marker. This system was used to perform kymographic analysis to quantify actin velocity and hyphal extension rates during early hyphal development. Results show two distinct growth phases: germ tube extension (0.58 ?m/min) and hyphal extension (1.52 ?m/min). Actin exhibited bi-directional transport along hyphae with biased movement toward the spore body. Actin was also observed re-localizing from hyphal tips to sites of septum formation indicating active redistribution of cytoskeletal resources based on cellular demands. This technological advancement overcomes longstanding limitations in fungal live-cell imaging and provides a new platform for quantitative systems-level analysis of mycelial development, offering new insights into the spatiotemporal coordination of cytoskeletal dynamics during filamentous growth.
Time-Varying Causal Treatment for Quantifying the Causal Effect of Short-Term Variations on Arctic Sea Ice Dynamics
(2026-01-25) Sampath, Akila; Janeja, Vandana; Wang, Jianwu
Quantifying the causal relationship between ice melt and freshwater distribution is critical, as these complex interactions manifest as regional fluctuations in sea surface height (SSH). Leveraging SSH as a proxy for sea ice dynamics enables improved understanding of the feedback mechanisms driving polar climate change and global sea-level rise. However, conventional deep learning models often struggle with reliable treatment effect estimation in spatiotemporal settings due to unobserved confounders and the absence of physical constraints. To address these challenges, we propose the Knowledge-Guided Causal Model Variational Autoencoder (KGCM-VAE) to quantify causal mechanisms between sea ice thickness and SSH. The proposed framework integrates a velocity modulation scheme in which smoothed velocity signals are dynamically amplified via a sigmoid function governed by SSH transitions to generate physically grounded causal treatments. In addition, the model incorporates Maximum Mean Discrepancy (MMD) to balance treated and control covariate distributions in the latent space, along with a causal adjacency-constrained decoder to ensure alignment with established physical structures. Experimental results on both synthetic and real-world Arctic datasets demonstrate that KGCM-VAE achieves superior PEHE compared to state-of-the-art benchmarks. Ablation studies further confirm the effectiveness of the approach, showing that the joint application of MMD and causal adjacency constraints yields a 1.88\% reduction in estimation error.
Glitch Propagation through Flip-Flops Endangers Masking Schemes: Why Time Separation Is Required
(2026-04) Reefat, Hasin Ishraq; Ebrahimabadi, Mohammad; Takarabt, Sofiane; Guilley, Sylvain; Karimi, Naghmeh
Glitches are hardware-level hazards that are capable of compromising secure implementations. Even dominant protections against side-channel attacks must demonstrate immunity in the potential presence of glitches. In this paper, we study two hardware masking schemes rationales, namely Ishai-ShaiWagner (ISW) and its Enhanced version (E-ISW), as well as Domain-Oriented Masking (DOM). While other glitch-aware masking schemes have been proposed, our focus is specifically on the differences between E-ISW and DOM. Those two styles rely respectively on combinational and on sequential separation of shares. It is known that sequential separation, realized through pipelining stages, does impact the latency of the hardware masking scheme. Additionally, in this paper, we show another drawback: pipelining does not provide full independence between manipulated shares. Indeed, we show that pipelining elements (DFFs in practice) can propagate upstream activity downstream. This results in first-order leakage in real-world systems, especially when parasitic effects are considered. In this respect, we show that DOM is leaking at first-order, and that this leakage increases with both the complexity of the netlist (in terms of number of DOM gadgets) and with the extent to which the operational environment can be worsened by an attacker (e.g., lowering the voltage to increase the leakage). These findings provide valuable insights for advancing secure hardware design.