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Discovery Of Suitable Habitat For Freshwater Mussel Species In The Appomattox River Through The Use Of Environmental Dna., Nicholas Duellman

Longwood Senior Thesis Proposal

Freshwater mussels are a keystone species providing crucial ecosystem services and river composition resiliency. Anecdotal evidence suggests the presence of freshwater mussels within the Appomattox river, the specifics of population sizes and suitable habitat remains an open question. Environmental DNA (eDNA) usage in conservation ecology has exploded in use within the past two decades, being far less invasive and cost-demanding than traditional methods. An eDNA metabarcoding pipeline of the 16s mitochondrial ribosomal subunit was built in R v. 4.4.2, using dada2 v. 3.2.1 package to trim MinION single read ASV outputs for freshwater mussel species identification in the interest of …

04.07.2025 Ored Connect, Liz Williamson

ORED Newsletter

New ORED Website Goes Live

Oxford Pitch Competition

Hughes Miller, Strategic Partnerships

Evaluating Wrist Placement And Signal Processing Techniques For Real-World Hrv Monitoring Using Ppg, Andrew Murphy

College of Computing and Digital Media Dissertations

This thesis investigates trade-offs between signal quality and data coverage in photoplethysmographic (PPG) heart rate variability (HRV) monitoring using wrist-worn devices. The goal was to evaluate whether wrist placement and signal processing techniques can improve measurement reliability in real-world conditions. Data was collected from healthy participants wearing smartwatches on both wrists during rest and a structured math task introducing natural wrist movement. Three distinct processing methodologies were compared, including a proposed Rolling-Standardized Derivative (RSD) approach. Results showed that while HRV signals from both wrists were highly correlated at rest, motion caused a measurable drop in signal quality and inter-wrist agreement, …

Living With Alzheimer’S: A Guide To How To Lower The Risk Of Memory Loss & Care For Those With Alzheimer’S, Mona Muzammil, Washain Muzammil

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Chemistry)

Despite the frequent characterization of Alzheimer's disease as a “loss of self,"" this enlightening book demonstrates unequivocally that a person's unique self persists throughout the course of the disease. The important message in Caring for People with Alzheimer’s is how much can be done in care settings to support a person's sense of identity and thereby enrich the lives of people experiencing the many losses associated with dementia. Drawing from a diverse body of research, this book brings together the recommendations of the best thinkers and practitioners in multiple disciplines to illustrate the meaning of self and the importance of …

Tiny Creatures, Big Lessons: Using Music Education And Ecoliteracy To Impact Young Learners' Perspectives On Bugs And Nature, Paige Burgess '25

Honor Scholar Theses

This thesis aims to demonstrate that relationships between students and nature can be improved through teaching young learners about music and bugs together, potentially leading to a greater overall love for and willingness to protect nature. The thesis features original teacher action research conducted over multiple weeks in a first grade classroom, with observations and data to support the efficacy of the methods discussed. This thesis analyzes literature that supports how increasing empathy toward bugs at a young age can have tangible benefits for the environment, how ecoliteracy as a framework is an effective means of teaching about nature, and …

The Effect Of Weed Control Using Herbicide On Soil Bacteria, Growth, And Yield Of Sweet Corn, Lafi Na'imatul Bayyinah, Purwanto, Risqa Naila Khusna Syarifah, Rama Adi Pratama, Ida Widiyawati, Hendra

Jurnal Kultivasi

Weeds are managed by herbicides, but this can reduce the abundance of soil bacteria. This research aimed to determine the effect of active compounds of herbicides on weeds, the abundance of soil bacteria, growth and yield of sweet corn. The experiment was conducted from June to October 2023 in the fields and Laboratory of Agronomy and Horticulture, Universitas Jenderal Soedirman, Purwokerto. A randomized block design was used, consisting of eight treatments and four replications. The treatments included control (H0); weeding (H1); paraquat (H2); glyphosate (H3); paraquat, atrazine, mesotrione (H4); glyphosate, atrazine, mesotrione (H5); paraquat, atrazine, mesotrione, nicosulfuron (H6); and glyphosate, …

Closing Remarks, Jay Yang

Value and Responsibility in AI Technologies

Closing remarks from director of Gonzaga's Institute for Informatics and Applied Technology, Dr. Jay Yang, with a reception to follow.

Highly Regenerable Magnetic Sulfonated Chitosan Crosslinked With Glutaraldehyde Composite Beads (Iron Sand/Naso3-Chi-G) For Aqueous Mercury Removal, Fathurrahmi Fathurrahmi, Rahmi Rahmi, Lelifajri Lelifajri, Anggun Sixthia Wulan Ayu, Muhammad Iqhrammullah

Karbala International Journal of Modern Science

We developed a novel adsorbent from sulfonated, glutaraldehyde-crosslinked chitosan embedded with magnetic iron sand. The adsorbent was synthesized through a two-step process: (1) sulfonation with N(SO₃Na)₃ to introduce sulfonate groups, and (2) crosslinking with glutaraldehyde to enhance structural stability. The optimal formulation, containing 43.5% iron sand and crosslinked with 0.17 M glutaraldehyde, exhibited the highest Hg²⁺ adsorption capacity (30.74 mg/g) at pH 3. The adsorbents were characterized using Scanning Electron Microscopy (SEM), Fourier transform infra-red spectroscopic (FT-IR), and X-ray diffraction (XRD) techniques. Adsorption equilibrium was achieved within 60 minutes, and isotherm modeling showed that the process followed the Freundlich model …

Enhancing State-Of-The-Art Motor Imagery Classification With Reinforcement Learning, Anton Shepelev

USF Tampa Graduate Theses and Dissertations

One of the key obstacles to the rapid adoption of non-invasive Brain-Computer Interfaces (BCIs) for Motor Imagery (MI) is the low signal-to-noise ratio, and the substantial data requirements which can be mentally taxing for users. EEGNet, a compact Convolutional Neural Network (CNN), has long been considered the state-of-the-art (SOTA) for MI classification, demonstrating strong performance even with limited data. However, recent studies advocate for integrating Deep Reinforcement Learning (RL) to further enhance classification accuracy by dynamically optimizing feature extraction and decision-making processes. Despite this potential, practical implementations remain scarce due to challenges in stabilizing RL training and adapting it to …

Improved Estimator For Population Mean Utilizing Known Medians Of Two Auxiliary Variables Under Neutrosophic Framework, Rajesh Singh, Shobh Nath Tiwari

Neutrosophic Systems with Applications

In the context of classical statistics, the estimation of the population mean is done with determinate, precise, and crisp data when auxiliary information is available. However, there are instances where dealing with uncertain, indeterminate, and imprecise data in interval form is required. To overcome this issue, Florentin Smarandache introduced neutrosophic statistics as a novel approach. This paper introduces a neutrosophic modified ratio-cum-product log-type estimator for the estimation of the population mean using known medians of two auxiliary variables in the neutrosophic context. The bias and mean squared error (MSE) for the proposed estimators are computed to the first-order approximation. The …

Enhancing Smart City Management With Ai: Analyzing Key Criteria And Their Interrelationships Using Dematel Under Neutrosophic Numbers And Mabac For Optimal Development, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

Purpose: This paper explores the transformative role of AI across various domains of smart cities, including urban mobility, energy management, public safety, healthcare, environmental monitoring, economic development, and data management. It aims to develop a novel decision-making framework that integrates AI technologies with a hybrid approach to analyze the interrelationships among smart city components.

Methodology: This paper employs a hybrid decision-making framework that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with single-valued trapezoidal neutrosophic numbers (STrNN). This approach is used to analyze the complex relationships among criteria and sub-criteria in smart city contexts, addressing uncertainty and incomplete information …

Antioxidant Activity Of Pamam Dendrimer Stabilized Ascorbic Acid, Gabriella Srikureja

Honors Theses

Ascorbic acid (vitamin C) is an essential micronutrient for human health. It acts as an enzymatic cofactor in anabolic biochemical pathways such as the synthesis of collagen, dopamine, and norepinephrine. Unfortunately, this versatility comes at the cost of a high degradation rate both in and outside of the food matrix. Previous research exploring stabilizing aqueous ascorbic acid through Poly(amidoamine) (PAMAM) dendrimers found success in reducing the rate of degradation.

To confirm the antioxidant activity of ascorbic acid in its stabilized dendrimer complex, 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assays examined via Cary 5000 UV-Vis-NIR spectrophotometer found that performing the DPPH assay under aqueous conditions …

Maldi-Mass Spectrometry Imaging To Investigate Distribution Of Per- And Polyfluoroalkyl Substances In Exposed Poplar Tissues, Tonglin Zhou, Varuni Abhayarayne, Joseph Akor, Honglan Shi, Paul Ki-Souk Nam, Joel Gerard Burken, John Yang

Miners Solving for Tomorrow Research Conference

No abstract provided.

Preliminary Assessment Of Non-Volatile Particulate Matter And Gaseous Emissions From A Premixed Pre-Vaporized Combustor Designed For Civil Supersonic Transport, Ugochukwu Ewuzie, Godwin Ifeanyi Ogbuehi, Steven Achterberg, Monday Uchenna Okoronkwo, Philip D. Whitefield

Miners Solving for Tomorrow Research Conference

No abstract provided.

Opioid Vs. Money Choice Preference Patterns In Regular Heroin Users, Amolak S. Jhand, Mark Greenwald

Medical Student Research Symposium

About two-thirds of people treated for opioid use disorder (OUD) return to opioid use within the first-year post-treatment, and about 10% report use while on agonist therapy. Understanding determinants of opioid-seeking is vital to reducing recurrence and its risks. We assessed individual differences in effortful choices between opioid and money amounts, modeling real-world choices.

Our lab conducted studies in which regular heroin-users were stabilized on buprenorphine to suppress withdrawal. Within experimental sessions, the participant could choose repeatedly across 12 trials between units of hydromorphone (HYD, 1 or 2 mg IM) vs. money ($2 or $4); HYD and money amounts differed …

The Effect Of Nanomorphology As Quantified Via The K‑Index On The Drug Delivery Properties Of Isocyanate-Derived Aerogels, Stephen Y. Owusu, A. B. M. Shaheen Ud Doulah, Vaibhav A. Edlabadkar, Kamden J. George, Chariklia Sotiriou-Leventis

Miners Solving for Tomorrow Research Conference

No abstract provided.

Integrating Standards For Infrastructure Improvement And Resilience In University Curricula, Lisa Greenwood, Jennifer Schneider, Sumita Mishra, Yewande S. Abraham, Shriram Karpoora Sundara Pandian

Articles

In today’s ever-changing world, we are increasingly vulnerable to shocks and stresses that disrupt industry and society. Persistent threats from natural and manmade hazards require our communities and infrastructure to be resilient despite possible disruption. Creating robust infrastructures is founded on operational and physical standards to withstand and respond to threats such as environmental exposures, climate change, and informational security breaches. The significant U.S. investment in infrastructure projects through the Infrastructure Investment and Jobs Act has amplified the need for professionals in engineering and related fields who – in addition to technical knowledge - possess the necessary knowledge and skill …

Reframing Information Seeking In The Age Of Generative Ai: A Critical And Humanistic Approach, Joseph Kevin Sebastian

Library Faculty Research

Information-seeking has long been the subject of theoretical modeling, often drawing from cognitive, behavioral, computational, and even evolutionary perspectives to explain how individuals navigate, filter, and utilize information. Several dominant frameworks—Carol Kuhlthau’s Information Search Process, Marcia Bates’ Berrypicking Model, Peter Pirolli & Stuart Card’s Information Foraging Theory, Kiyohiko Nakamura’s Information Criteria framework, and Ian Ruthven’s Information Shaping Theory —have provided structured ways of understanding how people interact with information environments. However, while these frameworks offer valuable insights, they often operate within mechanistic or efficiency-driven paradigms, which risk overlooking the complex, embodied, and socioculturally situated nature of human information behaviors. These …

Development And Application Of Self-Supervised Machine Learning For Smoke Plume And Active Fire Identification From The Fire Influence On Regional To Global Environments And Air Quality Datasets, Nicholas Lahaye, Anastasija Easley, Kyongsik Yun, Hugo Lee, Erik Linstead, Michael J. Garay, Olga V. Kalashnikova

Engineering Faculty Articles and Research

Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) was a field campaign aimed at better understanding the impact of wildfires and agricultural fires on air quality and climate. The FIREX-AQ campaign took place in August 2019 and involved two aircraft and multiple coordinated satellite observations. This study applied and evaluated a self-supervised machine learning (ML) method for the active fire and smoke plume identification and tracking in the satellite and sub-orbital remote sensing datasets collected during the campaign. Our unique methodology combines remote sensing observations with different spatial and spectral resolutions. With as much as a 10% …

Evaluating Microplastic Removal Efficiency In Portable Filtration Methods, Abagail Dupriest, Abbey Lowe, Allie Smith, Kat Orsi

Expo Student Presentations

2025 Spring Expo Poster Presentation

• Physical & Applied Sciences

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“Lyfting” The Possibilities And Opportunities For Sustainable And Safe Transportation To Access Medical Care, Saneywongse Le Mar

Goal 3: Good Health and Well-Being

No abstract provided.

Turning Farm Waste Into Energy: Pragmatic Approaches For Cleaner Midwestern American Communities, Rebecca Gaisie

Selected or Submitted Student Research Papers/Projects

Mismanagement of farm waste in the Midwest of the United States has resulted in significant methane emissions, water contamination, and public health concerns. The present manure management rules are still inconsistent, underfunded, and insufficient to motivate individuals to behave in a way that benefits the environment, despite increasing concerns about the environment. This policy study investigates anaerobic digestion as a potential means to convert waste into energy that could support rural and environmental development. Some of the problems with the federal and state legislation examined in this study under an EPI framework are a lack of incentives, inadequate technical support, …

Food Insecurity In Latin America: Climate Change, Industrial Agriculture, And The Case For Regenerative Solutions, Leila Hernandez-Webster

CISLA Senior Integrative Projects

This study critically analyzes the nexus between climate change and food insecurity in Latin America, with a particular focus on Costa Rica’s agricultural sector. It interrogates how industrial agricultural practices, deforestation, and trade liberalization have contributed to environmental degradation and heightened socio-economic vulnerabilities, especially among smallholder farmers. Through the lens of political ecology, this research situates these dynamics within the broader context of neoliberal and neo-extractivist development paradigms, which have systematically eroded food sovereignty. This study also evaluates agro-ecological responses, particularly agroforestry, as viable strategies for promoting ecological resilience and socio-economic equity. In doing so, it underscores the imperative of …

Tackling Crime: A Data-Driven Comparison Of Nfl Players With The General Population, Ryan Piersza

Honors Projects in Data Science

This research investigates the frequency of arrests among NFL players compared to the general population and analyze the types of crimes committed. A main theme from the literature is that previous groups of NFL players were found to be arrested at a rate lower than the general population. However, there has been no analysis on how the COVID-19 pandemic impacted the crime rates and types. Data obtained from the FBI’s Uniform Crime Report, The U.S Census Bureau, an NFL arrest database, and player statistics from Pro Football Reference is used for the analysis. The data is analyzed with a rate …

2025- The Twenty-Ninth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the 29th Annual Symposium of Student Scholars, held on April 16-18, 2025. Includes abstracts from the presentations and posters.

Irreversible K-Threshold Number Ck(G) And Saturation Probability P[G] For Corona Product And Double Corona Product Graphs, Eric J. Moon, Soumya Bhoumik, Paul Flesher

SACAD: Scholarly Activities

We discuss the Irreversible k-conversion process for graphs, where a vertex becomes saturated and remains saturated indefinitely if at least k of its neighbors are saturated. We investigate sets S₀, which when initially saturated, lead to complete graph saturation. We are interested in the minimum |S₀| = C_k(G), called the k-threshold number. We consider the construction of the Corona Product Graphs (of C_n and K_p). Additionally, we extend our analysis by defining and exploring Double Corona Product Graphs (of C_n and K_p). Then we incorporate …

Network-Based Crypto Asset Analysis, Ling Cheng

Dissertations and Theses Collection (Open Access)

The rise of cryptocurrency, particularly Bitcoin (BTC), has revolutionized the financial landscape, enabling decentralized, peer-to-peer transactions without the need for intermediaries such as banks or financial institutions. Since its inception in 2009, Bitcoin has grown exponentially, not only in terms of market value but also in its impact on global finance. However, together with this popularity comes a wide range of cybercrimes including hacking, Ponzi schemes, wash trading, extortion, and money laundering. As noted in recent research, the volume of illicit cryptocurrency activities has grown significantly, with billions of dollars in crypto assets being stolen or used for illegal purposes …

Application Of Analytical Methodologies To The Analysis Of Food Flavoring Agents: Part Ii, James Daniel, Kexin Li, Anaaya Monroe, Melissa C. Rhoten

Spring Showcase for Research and Creative Inquiry

No abstract provided.

Application Of Analytical Methodologies To The Analysis Of Food Flavoring Agents: Part Iii, Samantha Ruano, Bryant Corbin, Moorea Whitfield, Melissa C. Rhoten

Spring Showcase for Research and Creative Inquiry

No abstract provided.

Application Of Analytical Methodologies To The Analysis Of Food Flavoring Agents: Part Iv, Tyler Witt, Anna Wallace, Melissa C. Rhoten

Spring Showcase for Research and Creative Inquiry

No abstract provided.