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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The Trade Wind Regime of eastern Australia
(AMS, 2014-04-03) Murphy, Michael; Siems, Steven T
Despite their prevalence along much of the coastline and potential importance in the annual cycle of precipitation, the characteristics of the trade wind regime of eastern Australia and their associated temperature inversion are poorly understood. This region exemplifies conditions at the western flanks of the subtropical high pressure systems, where the trade winds vary considerably from classic models developed from observations in the eastern North Pacific and Atlantic oceans. Upper-air data from several observing stations along the coast of eastern Australia were analysed over the period 1976-2010 and a climatology of the trade winds and the basic characteristics of the trade wind inversion are presented. The trade wind regime dominates during the winter (late summer) in the deep tropics (subtropics) with its poleward fringe in southeastern Queensland. Interannual variability in the frequency of low-level wind directions associated with the trades has a strong linear relationship with the intensity of the subtropical ridge. The basic properties of the inversion (i.e. base height, strength, and thickness) are found to have a distinct annual cycle with a pattern that is largely independent of latitude. Monthly mean inversion base height and thermodynamic properties of the inversion (e.g. strength) have different annual cycles and vary independently of one another, contrary to research in other parts of the tropics. Interannual variations in inversion base height have the strongest linear relationship with the intensity and latitude of the subtropical ridge, while variations in the frequency of occurrence of the inversion are linearly related to the local sea surface temperature anomaly. This study elucidates the nature of the trade winds on the western flanks of the subtropical highs and, by developing a climatology of this weather regime, provides the foundation for a more complete understanding of precipitation in tropical Australia.
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MODIS dynamical and microphysical regimes as viewed by AIRS
(NASA, 2014-09-30) Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Jin, Daeho; Kato, Seiji; Huffman, George J.; Yuan, Tianle
Grouping systematic patterns in co-variations of cloud extinction and vertical location according to MODIS.
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Can Kink Lead to a Happier Life?
(Greater Good Magazine, 2025-08-25) Larson, Vicki; Kuperberg, Arielle; Walker, Alicia M.
Once considered a mental disorder, today kink is having a moment. Recent movies like Babygirl tell tales of a high-powered woman exploring the world of dominance and submission. In the FX/Hulu series Dying for Sex, based on a true story, a woman who has terminal cancer is introduced to kink with different men. And then, of course, we have 2011’s hugely popular romance trilogy and movie franchise Fifty Shades of Grey. As a result, the once-fringe practice is slowly becoming normalized.
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Side Effects of Erasing Concepts from Diffusion Models
(2025-08-24) Saha, Shaswati; Saha, Sourajit; Gaur, Manas; Gokhale, Tejas
Concerns about text-to-image (T2I) generative models infringing on privacy, copyright, and safety have led to the development of Concept Erasure Techniques (CETs). The goal of an effective CET is to prohibit the generation of undesired "target" concepts specified by the user, while preserving the ability to synthesize high-quality images of the remaining concepts. In this work, we demonstrate that CETs can be easily circumvented and present several side effects of concept erasure. For a comprehensive measurement of the robustness of CETs, we present Side Effect Evaluation (SEE), an evaluation benchmark that consists of hierarchical and compositional prompts that describe objects and their attributes. This dataset and our automated evaluation pipeline quantify side effects of CETs across three aspects: impact on neighboring concepts, evasion of targets, and attribute leakage. Our experiments reveal that CETs can be circumvented by using superclass-subclass hierarchy and semantically similar prompts, such as compositional variants of the target. We show that CETs suffer from attribute leakage and counterintuitive phenomena of attention concentration or dispersal. We release our dataset, code, and evaluation tools to aid future work on robust concept erasure.
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Investigating Symbolic Triggers of Hallucination in Gemma Models Across HaluEval and TruthfulQA
(2025-09) Lamba, Naveen; Tiwari, Sanju; Gaur, Manas
Hallucination in Large Language Models(LLMs) is a well studied problem. However, the properties that make LLM intrinsically vulnerable to hallucinations have not been identified and studied. This research identifies and characterizes the key properties, allowing us to pinpoint vulnerabilities within the model’s internal mechanisms. To solidify on these properties, we utilized two established datasets, HaluEval and TruthfulQA and convert their existing format of question answering into various other formats to narrow down these properties as the reason for the hallucinations. Our findings reveal that hallucination percentages across symbolic properties are notably high for Gemma-2-2B, averaging 79.0% across tasks and datasets. With increased model scale, hallucination drops to 73.6% for Gemma-2-9B and 63.9% for Gemma-2-27B, reflecting a 15 percentage point reduction overall. Although the hallucination rate decreases as the model size increases, a substantial amount of hallucination caused by symbolic properties still persists. This is especially evident for modifiers (ranging from 84.76% to 94.98%) and named entities (ranging from 83.87% to 93.96%) across all Gemma models and both datasets. These findings indicate that symbolic elements continue to confuse the models, pointing to a fundamental weakness in how these LLMs process such inputs—regardless of their scale.