Digital Commons Network^™

Assessing Sediment Composition, Organic Matter, Metal Contamination, And Ecological Risks In Port Everglades, Florida, Elisa Prodhomme, Gabrielle Spankus

Undergraduate Student Symposium

Port sediments often accumulate heavy metals and organic pollutants from anthropogenic inputs. The planned expansion of Port Everglades (Fort Lauderdale, Florida, USA) raises concern that dredging may remobilize contaminated sediments, potentially affecting nearby benthic habitats, including coral reefs. To assess sediment quality, eighteen cores were collected from five port sites and one control site, along with additional surface sediments. Cores were sectioned at 10 cm intervals and analyzed for 14 metals (ICP-MS), percent organic matter, and grain size. Geo-accumulation index results indicated moderate to strong contamination by As and Mo, while ecological risk assessments suggested moderate to high overall metal …

Endoparasites In Magnificent Frigatebirds (Fregata Magnificens Rothschildi) From Southeast Florida, Usa, Isabelle Petty, Alexia Hilber

Undergraduate Student Symposium

The Magnificent Frigatebird (Fregata magnificens) is a pelagic seabird widely distributed across tropical and subtropical regions. Due to its wide-ranging foraging behavior and fish-based diet, these birds are susceptible to parasitic infections. However, little is known about the species' endoparasite communities. Despite its ecological importance, research on this species remained limited, particularly regarding the diversity and distribution of endoparasites. This study aims to investigate the endoparasite community in these birds. Specimens were collected from multiple rehabilitation centers from southeast Florida. A total of six individuals were examined (MAFR 2000, 3105, 3106, 3107, 3108, and 3109) for parasite presence …

Disrupting Stat3 Signaling In Glioblastoma Stem Cells Using Nitro-Modified Curcumin Analogs, Sneha Subhash, Swara Chindhade, Maria Moreno Hollweg, Kyuree Chang

Undergraduate Student Symposium

Signal Transducer and Activator of Transcription 3 (STAT3) is frequently overactivated in cancers, including glioblastoma (GBM), where its dysregulation is associated with aggressive disease and poor patient survival. STAT3 supports tumor progression by promoting proliferation, resistance to apoptosis, maintenance of cancer stem cells, and immune suppression. Although numerous STAT3 inhibitors are under preclinical and clinical evaluation, none have yet achieved FDA approval. GBM remains a highly lethal brain cancer with limited therapeutic options, underscoring the need for new targeted treatments. Nitro-containing compounds, known for their strong electron-withdrawing characteristics, are emerging as potential anticancer agents. A library of 41 nitro-containing chalcones …

Ticked Off: A Systematic Review Of Alpha-Gal Syndrome Mechanisms

Undergraduate Student Symposium

Alpha-gal syndrome is characterized by an IgE-mediated immune response against galactose-α-1,3-galactose. In the United States, the principal vector is the Lone Star tick, whose range has expanded nationwide. 110,000 cases have been reported since 2010, with the CDC estimating 450,000 as many cases go unrecognized. Vomiting, difficulty breathing, and hypotension can occur immediately or hours after exposure. Ongoing exposure to alpha galactose with AGS increases mast cell inflammatory response, raising coronary artery disease risk. Perioperative ingredients like gelatin, monoclonal antibodies, and stearic acid have triggered anaphylactic shock in AGS patients. These complications hinder diagnosis. The inclusion criteria required original research …

Snapping Shrimp Acoustic Activity As An Indicator Of Ecosystem Health Across Mangrove, Seagrass, And Coral Reef Habitats In The Florida Keys, Catherine Salazar, Alexander Wheeler

Undergraduate Student Symposium

Mangroves, coral reefs, and seagrass provide refugia, nursery areas, and feeding grounds for many marine species. These ecosystems have faced declines in habitat complexity through natural and anthropogenic causes. Passive acoustic monitoring (PAM) is used to track changes in habitat characteristics through the monitoring of acoustic species, like snapping shrimp. Snapping shrimp are among the most active species inhabiting shallow subtropical marine environments, and their abundance, often tracked through their acoustic activity, are strong indicators of a healthy ecosystem. This study compares the acoustic activity of snapping shrimp across mangrove, seagrass, and coral reef habitats in Key Largo, Florida, as …

Sold For Parts: Moral Connections Between Paid Surrogacy And Paid Organ Donation, Alessandra Coke

Undergraduate Student Symposium

Throughout this presentation, I make ethical arguments about paid surrogacy, based on established arguments regarding paid living organ donation possible due to similarities between the procedures. I establish the differences between conceptualizations of surrogacy: unpaid/altruistic and paid/compensated, and clarify what is meant by paid surrogacy. The primary similarity between paid living organ donation and paid surrogacy is that both practices are a 'voluntary' violation of bodily integrity for financial benefit. I argue that both practices due to financial incentives cannot truly be seen as voluntary. I argue that the reasons that are used to understand paid living organ donation as …

Analyzing The Variation In Microplastic Intake Of Waterhyacinth And Pennywort In Lake Okeechobee, Aashvi Gowrisankar

Undergraduate Student Symposium

The Florida Everglades ecosystem faces many threats, including municipal pollution and agricultural runoff. This study compares the microplastic intake of two types of floating vegetation in Lake Okeechobee. Water hyacinth (Pontederia crassipes) has a greater root mass and surface area than its native equivalent pennywort (Hydrocotyle umbellate). We hypothesize that water hyacinth would have greater microplastic intake due to its increased capillary action. Our project was conducted using three guiding questions: which plant type had the greatest microplastic intake, did accumulation vary with location, and did concentration vary among roots, stems, and leaves in each plant …

Advances In Aortic Valve Replacement For The Recovery Of Elderly Patients In Southern Florida, Khushi Faldu

Undergraduate Student Symposium

Aortic stenosis, a narrowing of the aortic valve, is a significant health burden in aging populations, as in Broward County, Florida, where the elderly demographic is rapidly expanding. The classical approach to valve replacement is performed via Surgical Aortic Valve Replacement (SAVR). Recently, Transcatheter Aortic Valve Replacement (TAVR), a minimally invasive alternative, has emerged as a life-changing option for patients with a high surgical risk. Using inductive methods, this study compiled and analyzed data from existing research records and publications comparing endothelial recovery following TAVR and SAVR. We aim to design a teaching case study to highlight how procedural choice …

When Peers Matter: Peer Communication And The Association Between Parental Dependence And Superiority Cognitions, Preya Pandya, Bala Sivani Paddala, Anisha Nandra

Undergraduate Student Symposium

Although parent-child relationships have been widely studied during childhood and adolescence, less attention has been given to how these relationships continue to influence adjustment during emerging adulthood. This developmental period is marked by instability and exploration, as young adults begin transitioning into adult roles such as higher education, employment, and long-term relationships. Research suggests that parenting continues to matter during this time, with successful separation-individuation representing a normative developmental task. Excessive parental dependence, however, may be associated with maladjustment. At the same time, peers play an increasingly important role in emerging adulthood, and positive peer relationships are often linked to …

Reengineering Bone Health: Preventing Steroid-Induced Osteoporosis Without Jaw Damage, John Voudouris

Undergraduate Student Symposium

Glucocorticoid ("steroid") drugs are essential for treating autoimmune diseases, but long-term use often weakens bones, leading to a condition called glucocorticoid-induced osteoporosis (GIO). In the United States, steroids such as prednisone and dexamethasone are prescribed to over 10 million patients annually, and roughly 30% of long-term users develop GIO, contributing $20-30 billion in annual health-care costs. To this end, bisphosphonates are commonly used to treat GIO by preventing bone-loss; however, they can also cause a serious adverse effect called medication-related osteonecrosis of the jaw (MRONJ). Thus, safer jaw-protective treatments are urgently needed. In this study, we tested a different strategy …

Servant Leadership & Navigating The Covid-19 Pandemic: A Case Study On Port Tampa Bay, Laura M. Holland, Deirdre Dixon

Servant Leadership: Theory & Practice

When the COVID-19 pandemic hit the United States in March 2020, many supply chain companies found themselves facing increased demand, labor shortages, and low capacity. Due to complex relationships in the supply chain industry, it was difficult for ports to manage these challenges and continue to operate efficiently. For ports to successfully navigate these challenges, they needed to implement leadership across all levels. We examined the leadership of Port Tampa Bay to see if Servant Leadership was present. Port Tampa Bay was Florida’s largest port that handled major cargo. Through 2020–2022, the port had not seen any of the congestion …

Enabling Parameter-Efficient Multi-Tasking Via Multi-Head Architecture For Edge Device Deployment, Redwanul Islam Arif, Mohammod Akib Khan, Syed Hasib Akhter Faruqui, Sahidul Islam

Artificial Super Intelligence (ASI) Conference

Deploying Deep Neural Networks (DNNs) on edge devices requires balancing task performance with strict memory and computational constraints. Conventional approaches to multi-task learning often rely on replicating heavy backbones, which is infeasible for resource-constrained environments. In this work, we propose and rigorously analyze a parameter-efficient multi-branch architecture based on a shared, ImageNet-pretrained ResNet-18 backbone. Instead of deploying independent models for distinct visual tasks, we consolidate feature extraction for multiple tasks into a single, unified framework. We first conduct an ablation study to determine the optimal depth of task-specific fully connected (FC) classification heads, maximizing learning capacity while minimizing computational overhead. …

Qcausalmed: Hybrid Quantum-Ai Approaches For Optimizing Causal Inference In Personalized Oncology, Nikunj Doshi, Kavach Shah, Shikhar Patel

Artificial Super Intelligence (ASI) Conference

Estimating individualized treatment effects from observational clinical data is a central challenge. Personalized oncology depends on this estimation for meaningful patient-level decisions. Standard variable selection methods tend to over-adjust for spurious covariates in practice. They also under-adjust for true confounders when the causal graph is high-dimensional. This failure arises because optimal adjustment set identification is NP-hard in the general case. This paper proposes QCausalMed, a hybrid quantum-classical pipeline addressing this problem. The system formulates confounder selection as a Quadratic Unconstrained Binary Optimization problem. This QUBO problem is solved using the Quantum Approximate Optimization Algorithm, or QAOA. The resulting quantum-selected minimal …

Optimization, Co-Design And Nextgen Of Agentic Ai, Bhawesh Singh

Artificial Super Intelligence (ASI) Conference

As generative artificial intelligence and multi-agent systems transition from experimental research prototypes into the backbone of enterprise-critical infrastructure, the industry has reached a pivotal juncture where computing bottlenecks represent the primary barrier to progress. The historical reliance on "brute-force" scaling, simply increasing model parameter counts, has reached a point of diminishing returns, as the exponential escalation in training costs and energy consumption becomes economically and environmentally unsustainable. To address these challenges, this paper provides a comprehensive examination of six cutting-edge technological pillars currently redefining neural architecture and optimization: Neural Architecture Search (NAS) for automated design, Advanced efficient training techniques, Energy-efficient …

Ai-Driven Enterprise Architecture And Value Realization Framework, Hemant Soni

Artificial Super Intelligence (ASI) Conference

For over 40 years enterprise architecture has promised to align technology investment with organizational strategy. Just a portion of that promise has been fulfilled. Extensive documentation or artifact repositories that describe the enterprise in detail but hardly ever influence its direction in any discernible way has been the field's main output. This paper begins with that diagnosis which was most accurately expressed by Tamm et al. and in the context of the public sector by Dang and Pekkola and inquires as to whether artificial intelligence can solve the underlying structural issue instead of just speeding up the documentation process. We …

Zenbrain: A Neuroscience-Inspired 7-Layer Memory Architecture For Autonomous Ai Systems, Alexander Bering

Defensive Publications Series

We present ZenBrain, an open-source memory architecture for AI systems that implements seven distinct memory layers inspired by cognitive neuroscience. Unlike existing approaches that treat AI memory as simple key-value storage, dual-layer retrieval, or LLM-driven reorganization, ZenBrain models the full lifecycle of human memory: encoding, consolidation, retrieval, decay, and active forgetting. The system integrates 12 neuroscience-inspired algorithms including FSRS-based spaced repetition, Hebbian learning dynamics for knowledge graphs, neuroscience-modeled sleep consolidation simulating hippocampal replay, emotional memory modulation, and Bayesian confidence propagation. ZenBrain is deployed in production as part of ZenAI with 9,228 passing tests, and is published as composable npm packages …

“Sanctuary And Sovereignty: The Constitutional And Christian Mandate For Order In U.S. Immigration Policy”, Christopher J. Boosey, Franklin Patterson

Helms School of Government Spring Public Policy Conference

No abstract provided.

Strategy In A Disrupted World: Evaluating The 2025 Nss Through The Five Disruptions Framework, Anthony Hughes

Helms School of Government Spring Public Policy Conference

No abstract provided.

Innovator - Spring 2026

Innovator

06 - Message From the President

08 - Time Machine

12 - News

22 - Gabrielle Kemberling ’12

28 - The Oughton Family

34 - Beyond the Seams

44 - Question & Innovate

46 - Ram Roundup

48 - Which Ram Was the GOAT?

52 - Class Notes

56 - In Memory

58 - Trivia

Innovator - Fall 2025

Innovator

06 - Message From the President

08 - Time Machine

10 - News

24 - Nureed Saeed ‘99

28 - Cell Mates

32 - Robert C. Sergott, MD

36 - Working Smarter

42 - Question & Innovate

44 - Alumni Impact

48 - Leeor Gal ‘19

50 - Class Notes

56 - In Memory

58 - Trivia

Innovator - Winter 2025

Innovator

06 - Message from the President

08 - Time Machine

10 - News

14 - New Leader for a New Century

18 - Fashion’s Fairy Godmother

22 - Diploma School of Nursing

26 - Question & Innovate

28 - Alumni Impact

30 - Ram Roundup

32 - From the Washington Ballet to Wimbledon

36 - Homecoming 2024 and Alumni Awards

42 - JCLS Alumni Day

44 - Class Notes

50 - Love Train

52 - In Memory

54 - Trivia

Innovator - Summer 2024

Innovator

06 - A Message from the President

10 - Time Machine

16 - The Nexus

32 - Our History

38 - Weaving a Legacy of Excellence

40 - Bridging the Gaps

44 - Harnessing the Qualities That Create Healthcare Heroes

48 - Question & Innovate

52 - Alumni Impact

54 - Ram Roundup

58 - Be Kind

62 - Class Notes

68 - In Memory

70 - Trivia

Innovator - Fall 2023

Innovator

06 - Get to Know Jefferson's Interim President

08 - Leadership Announcements

10 - Time Machine

14 - The Nexus

22 - Climate Change on Your Block

30 - Humana and Jefferson

34 - Question & Innovate

38 - Caffeinated Creativity

42 - Alumni Impact

46 - Ram RoundUp

50 - Brotherhood's Enduring Legacy

56 - Class Notes

60 - In Memory

62 - Trivia

Nihilism: A Philosophical Essay, Stanley Rosen

Hannah Arendt Marginalia - All

New Haven : Yale University Press, 1969.

Call # : B828.3 .R6

Contains marginal lining  PDF Information : 7.7 MB, 24 Pages

Advancing Equitable Faculty Evaluations: Refining Behavior-Based Rubrics For Systemic Change, Celia Freed

Miners Solving for Tomorrow Research Conference

Bias in faculty evaluations continues to influence decisions about promotion, tenure, and resource allocation, disproportionately affecting women and underrepresented faculty. To address these inequities, this study develops and implements behavior- and-outcome based evaluation rubrics designed to improve fairness, clarity, and consistency. Using a case study approach, calibration data, participant feedback, and refinement are used to guide rubric development and standardization. Over one academic year, this project progressed through data analysis, rubric revision, faculty feedback, and pilot implementation, followed by evaluation of its effectiveness. The study advances research on structured evaluation systems and examines how behavior-based criteria can potentially enhance inclusivity …

Biosensors For Biomedicine, Drake O'Leary

Miners Solving for Tomorrow Research Conference

This project investigated the use of engineered bacterial reporter systems to detect cellular stress responses associated with antibiotic activity. While constructs were successfully introduced and tested against known antibiotics, the reporter consistently produced a blue signal across conditions, limiting the ability to distinguish specific stress responses. This suggests issues such as leaky expression, insufficient regulatory control, or lack of specificity in the reporter design. Although results were inconclusive, this work highlights key challenges in developing reliable biosensors and provides a foundation for future optimization. Improving signal specificity and reducing background expression will be critical for enabling accurate characterization of antibiotic …

Asphalt Pavement Rejuvenation Investigated By Nuclear Magnetic Resonance Relaxometry, Catherine Skaggs

Miners Solving for Tomorrow Research Conference

Asphalt is a relatively inexpensive material commonly used for road pavements; however, asphalt ages from exposure to oxygen and UV radiation, leading to loss of elasticity, which leads to cracks and potholes. To slow or reverse asphalt aging, pavement preservation treatments are in use. It’s unclear whether these treatments truly rejuvenate the pavement structure or merely offer a short-term benefit. Nuclear Magnetic Resonance (NMR) relaxometry is an analytical technique that uses the recovery of excited nuclear magnetization as a parameter to gain insights into molecular environments. Recovery-time distributions gathered from asphalt materials show differences between regular and rejuvenated asphalt samples, …

Multi-Frequency Temporal Sampling For Training Video Object Counting Models, Ivor Rendulic, Filip Pavetić

Defensive Publications Series

Machine learning models may face challenges in counting distinct objects in videos, particularly when presented with variations in frame rates or object speeds. Disclosed systems and techniques can address these challenges with a data augmentation methodology for generating training data. For example, an approach can involve creating multiple training examples from a single source video by sampling its frames at various temporal frequencies. A dynamic labeling protocol may be used to assign an object count label to a new sequence that reflects the number of objects discernible in that specific, potentially sparser, sequence. Training a model on these varied representations …

System And Method For Predictive Network Equipment Decommissioning Management, N/A

Defensive Publications Series

The technology described in this paper relates to a predictive network equipment decommissioning management system. The described technology automates the creation and management of decommissioning requests to improve accuracy and reduce cycle times. By utilizing multi-signal context heuristics, the system determines the specific decommissioning scenario for various assets. A hybrid inference engine is employed to predict the presence of unmonitored passive components. An ambiguity resolution engine identifies vague or untagged parts using computer vision and topological exclusion techniques. A dynamic granularity transformation engine re-aggregates discrete components into top-level assemblies, accommodating for configuration drift over time. Furthermore, a retrofit analysis engine …

Automated Security Policy Validation From Natural Language Documentation Using Large Language Models, Leonid Kuligin, Aleksandr Ostapenko

Defensive Publications Series

Determining security permissions from natural language documentation, for example, runbooks, can be a time-consuming and error-prone process that may lead to runtime failures or security vulnerabilities. A system can use large language models (LLMs) to analyze documentation, infer a candidate permission policy, and generate a corresponding test script. The script can then be executed in a sandboxed environment using the candidate policy. An iterative refinement loop may diagnose permission-related failures and use an LLM to propose policy modifications to address those failures. This automated process can assist in generating a functional permission policy derived from operational instructions, which may reduce …