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State Preparation of Lattice Field Theories Using Quantum Optimal Control
Get PDFWe explore the application of quantum optimal control (QOC) techniques to state preparation of lattice field theories on quantum computers. As a first example, we focus on the Schwinger model, quantum electrodynamics in 1 + 1 dimensions. We demonstrate that QOC can significantly speed up the ground state preparation compared to gate-based methods, even for models with long-range interactions. Using classical simulations, we explore the dependence on the interqubit coupling strength and the device connectivity, and we study the optimization in the presence of noise. While our simulations indicate potential speedups, the results strongly depend on the device specifications. In addition, we perform exploratory studies on the preparation of thermal states. Our results motivate further studies of QOC techniques in the context of quantum simulations for fundamental physics
06 - Testing Trapping Methods for Ambrosia Beetles (Curculionidae) in Southeastern Virginia. Morgan Harrison, Sajrim Chowdhury, Umme Akter and Deborah Waller. Biology Department, Old Dominion University.
No full textNative and invasive ambrosia beetles infest a wide variety of tree species in southeastern Virginia and cause significant damage. We investigated several trapping methods to collect ambrosia beetles by using five different tree species as lures. One objective of the study was to determine the most effective lure for each species of ambrosia beetle. Sections of tree limbs approximately 7cm diameter and 25cm in length were soaked in ethanol and hung from trees in several natural locations. Beetles attracted to the lures were collected and identified to species
31 - Shaped Adversarial Patches
Get PDFIn recent years, the development and deployment of computer vision models have become widespread, with applications ranging from autonomous vehicles to security systems. Among these, object detection algorithms like YOLO are particularly significant due to their real-time performance and accuracy in identifying and localizing objects within an image. However, the robustness of these models is increasingly challenged by adversarial attacks, which are deliberate manipulations designed to deceive the model\u27s predictions.
In this paper, I present an approach to advancing the deception capabilities of adversarial patches, specifically targeting YOLO-based person detectors. The objective is to design and implement shaped adversarial patches that can be applied directly over a person, effectively lowering the confidence scores of the detector and ultimately fooling the system into failing to recognize the person altogether.
This work builds on existing research in adversarial machine learning, where the creation of adversarial patches has been shown to significantly undermine the reliability of computer vision models. By exploring new patch shapes and configurations, I aim to enhance the effectiveness of these patches, making them more adaptable and capable of bypassing detection algorithms. The results of this research could have profound implications for the security and reliability of AI systems in real-world environments, where adversarial attacks pose a growing threat
33 - DNA Methylation Prediction
No full textDeep learning has become an essential tool for deciphering genomic sequences and predicting regulatory activities in cellular biology. However, training a deep neural network to achieve a model with optimal performance for prediction tasks in functional genomics remains a challenge due to the high complexity in the regulatory biology of DNA sequence. In this study, we explore the impact of multiple key network training parameters, including the optimization algorithm, training objective, input context length, and network architecture on model performance for DNA methylation prediction from DNA sequence. Our results show that deeper architectures improve predictive accuracy but require careful selection of optimization algorithms to prevent overfitting. We also find that increasing input context length enhances model performance up to a certain threshold, beyond which diminishing returns occur. Additionally, loss function choice significantly influences model stability and generalization, with certain formulations better capturing sequence-level dependencies. By systematically evaluating these factors across multiple model architectures, we identify approaches that enhance predictive accuracy and consistency. Our findings provide insights into the trade-offs between model depth, optimization techniques, loss function selection, and sequence length offering a framework for improving deep learning applications in genomics. This work contributes to the development of more effective computational tools for analyzing regulatory sequences and understanding their role in gene regulation and disease
[Review of the Book Querns and Mills in Mediterranean Antiquity. Tradition and Innovation During the First Millennium BC, by N. Alonso, T. J. Anderson, L. Jaccottey].
Get PDF[First paragraph] Querns and Mills in Mediterranean Antiquity (hereafter QMMA) is the publication of an EAA (European Association of Archaeologists) session on querns held in Barcelona in 2018. The purpose of the session—and by extension the volume—was to fill a gap by studying the smaller, hand-operated millstones, which have received less attention than their larger Roman-era and medieval counterparts. A second aim was to begin a conversation about standardizing the study of millstones, and particularly querns, in terminology and methodology
Absorbing Knowledge 2
No full textThese mind-altering bookends signify that no matter what your limitations might be there is always something to be gained from opening a book. One side of my conceptual cranium sculpture signifies the soft spongy matter ready to soak in all the knowledge it can manage. It is “Brainstorming” all the ideas it is gathering while reading through as many of the books it can capture. The opposite side demonstrates the dense rigid structure of a thriving mind in action. This brain is gaining information from the simple ABC’s to complex DNA and thriving. I live with dyslexia but never tire of a great illustrated “DIY” manual. My dad suffered years with dementia, but we would read through a Sportsman’s Guide or military surplus catalog, and it brought him so much happiness, occasionally he would recall a memory while going through those catalogs. My hand built ceramic bookends are not inspired by a storybook, but by The Dictionary of Thoughts, which is filled with endless inspiring quotes. I am afraid the digital electronic handheld devices children are getting addicted to may make books obsolete one day, the way that printed newspapers and magazines are slowly fading away. These bookends may someday be a relic like the card catalog or the microfiche reader.
Artist\u27s Expo Pagehttps://digitalcommons.odu.edu/undergradsymposium_artgallery/1174/thumbnail.jp
AI-Generated Messaging for Life Events Using Structured Prompts: A Comparative Study of GPT With Human Experts and Machine Learning
Get PDFLarge Language Models (LLMs) play an increasingly integrated and pivotal role in generating diverse types of texts, such as social media messages, emails, narratives, and technical reports, among other textual communication forms. As AI-generated messaging filters into human communication, a systematic exploration of their effectiveness for mimicking human-like communication of life events is needed. In this study, we employ a zero-shot structured narrative prompt to generate 24,000 life event messages for birth, death, hiring, and firing events using OpenAI\u27s GPT-4. From this dataset, we manually classify 2880 messages and evaluate their validity in conveying these life events through the form of X (formerly Twitter) posts. Human evaluators found that 87.43% of the sampled messages (n = 2880) sufficiently met the intentions of their structured prompts based on their interpretations of the prompt and the corresponding AI-generated message. To automate the identification of valid and invalid messages, we train and validate nine Machine Learning models (ML) on the classified datasets. Leveraging an ensemble of these nine models, we extend our analysis to predict the classifications of the remaining 21,120 untagged messages. Finally, we manually tag 1% of the messages with predicted classifications and attain 90.57% accuracy (sd = 29.3%, n = 212) across the four life event types. The ML models excelled at classifying valid messages as valid, but experienced challenges at simultaneously classifying invalid messages as invalid. Our findings advance the study of LLM capabilities, limitations, and validity while offering practical insights for message generation and natural language processing applications
51 - Sexual Trauma as a Moderating Factor in the Association Between PTSD and Trauma-Related Drinking to Cope
No full textStrong associations between posttraumatic stress disorder symptoms (PTSS) and drinking to cope are well established. Previous research also suggests an association between sexual trauma and problematic drinking behaviors, but not drinking to cope with PTSS (aka “trauma-related drinking to cope”, or TRD) specifically. The present study examines the possible moderating role of adolescent and adult sexual assault and harassment (AASA) in the association between PTSS and TRD within a diverse college sample (N=726, Mage=22.87, SD=7.20; 48.8% White, 35.8% Black; 77.0% Women). Pearson and point-biserial correlation analyses showed that TRD was significantly correlated with PTSS, r(720) = .38, p \u3c .001, but not associated with AASA, gender, or race, r(719) = .053, p = .156; r(693) = .035, p = .361; r(611) = .068, p = .092, respectively. Moderation analyses showed that AASA significantly moderated the association between PTSS and TRD ( = -.088, t = -2.34, p = .020), with greater number of AASA experiences weakening the association. Contrary to our hypothesis, this finding suggests that those with greater AASA tend to use TRD less in association with PTSS compared to those with less AASA. One explanation for this finding may be that the high prevalence of alcohol surrounding AASA experiences may lead to those with greater AASA to be disinclined to use alcohol. Alternatively, those who experience AASA may be drinking to cope, but not with PTSS specifically. Additional research should explore the role of other types of traumatic events in the association between PTSS and TRD
77 - Reported Barriers to Dental Care Among U.S. and Non-U.S. Pregnant Women: A Narrative Review
No full textINTRODUCTION
Dental care during pregnancy is essential to a healthy delivery and early childhood development. While dental care is recommended by health and dental professionals and stakeholders, the prevalence of pregnant women who seek dental care remains low due to reported and perceived barriers. This narrative review sought to identify reported barriers to dental care among U.S. and non-U.S. pregnant women.
Methods:
The literature search was conducted from October 2024-March 2025 and included peer-reviewed, quantitative and qualitative articles written in English published between 2000-2025. Searches were conducted in PubMed, Dentistry and Oral Sciences, and CINAHL databases using keywords “pregnancy and dental service and barriers” and “oral health and dental care and pregnancy.” Relevant studies were selected and analyzed to compare barriers encountered by pregnant women in the U.S. and abroad.
Results:
A total of 31 articles, 10 U.S. articles and 21 non-U.S. articles were included in this review. In general, most of the reported barriers were the same for U.S. and non-U.S. pregnant women. The most commonly mentioned barriers were misconceptions about dental care, cost, perceived need, fear/anxiety, safety concerns, and inadequate knowledge about dental care.
Conclusions:
Identifying the commonly reported barriers to dental care encountered among pregnant women may assist in developing intentional interventions that target these concerns. Addressing these concerns may increase access to dental care thereby improving oral health outcomes
Pint-Sized Advisories
No full textPint-Sized Advisories is a game inspired by Nintendo\u27s WarioWare series made for the ODU Serious Games Jam of Spring 2025, where it won 2nd place out of 11 entries overall, winning first in the Fun Factor category, while tying for first in Rhetoric and Theme . The game covers themes of environmental friendliness on an individual level: within the story, an organization is making micro-PSAs to hold the attention spans of teenagers. The player is required to complete each PSA (some task) before the viewer swipes away. These PSAs start short and only get shorter as the game progresses, requiring the player to execute quickly but carefully.
I, Bowman Eggleston, handled the programming, art, and music for the game, with extra music contributions and playtesting by Autumn Carey. As with all games in the jam, the game was fully designed, developed, and programmed in under 14 days, pushing the creative limits of what such a short time allows. Following this submission, we may further develop the game, but as it stands now, the current product is a testament to the creative potential of works created from limitations and constraints. The development of the game served as a learning opportunity for us, where we practiced time management and game development skills. Working under the limitations imposed by the game jam, including the time constraint and the requirement that the game be informational, was challenging but educational and exciting, and it was a great way to get experience as an aspiring game developer