Digital Commons Network^™

Vortex Generation In Dipolar Supersolids, Jacob Harl

Miners Solving for Tomorrow Research Conference

Ultracold atomic gases offer highly tunable platforms for exploring complex quantum many-body phenomena. In addition, dipolar quantum gases of magnetic atoms featuring long-range anisotropic interactions are exquisite systems for realizing exotic phases-of-matter in an experimentally controlled way. A prototypical example is the supersolid state which simultaneously exhibits frictionless flow of superfuids and crystalline density modulation of solids. In this realm, we investigate the dynamical generation of vortex topological defects by imprinting a suitable phase jump in quasi-two-dimensional dipolar supersolids. This protocol enables the nucleation of a dark soliton which consecutively becomes unstable via the eponymous snake instability due to its …

Analysis Of Autonomous Vehicle Survivability To 5g Communication Errors, Sydney Clark

Miners Solving for Tomorrow Research Conference

Autonomous vehicles rely on low-latency, high-reliability data exchange for real-time perception and control. Disruptions such as packet loss, latency variation, protocol-level errors, and malicious interference can pose significant safety risks to both passengers and surrounding environments. This project aims to evaluate, quantify, and predict the survivability of autonomous vehicle systems to communication errors, with focus on 5G network environments. The impact of these communication impairments on vehicle stability and control will be investigated through high-fidelity cyber-physical simulation of the vehicle and its surrounding environment. Experiments designed to capture varying network conditions will be used to assess a broad range of …

State Of Tennessee Board Of Parole 2024-25 Annual Report, Tennessee. Board Of Parole.

Board of Parole

No abstract provided.

The Right To Rock The Cradle: Parental Leave And Flexible Work Arrangements As Social And National Capacity Priorities For 21st-Century U.S. Public Policy, Georgiana Constantin-Parke

Helms School of Government Spring Public Policy Conference

No abstract provided.

Predictive Modeling In Social Media Deepfake Identification, Samuel Whatley Ii

Helms School of Government Spring Public Policy Conference

No abstract provided.

Short-Form Content And The Long-Term Effects, Grace Brown

Research Days

This research aims to explain the rapid growth of short-form digital content. This is an exploration as to why platforms, like TikTok, have taken over modern entertainment. As media evolves away from long-form content with high-production towards short-form with minimal editing, audiences adapt. Short-form content allows social media users to scroll past “uninteresting” videos with ease, validates shortened attention spans and creates more economic incentives. TikTok has successfully developed a highly personalized and fast-paced algorithm, which many social media apps have attempted to mimic. This algorithm sustains engagement by encouraging rapid scrolling and continuous content consumption. While users can easily …

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 …

The Developmental Journey Of A Servant Leader Rise To Serve, Sacrifice To Lead, James Elliker

Servant Leadership: Theory & Practice

The writings of Robert Greenleaf (1970, 1972, 1977, 1998) and the examples of ancients (Green, 2023), have inspired a number of research efforts on the efficacy of a leader as servant approach to modern leadership. Greenleaf’s core principles included the desire to serve first, the ability to help grow others into healthy servant leaders themselves, and the potential to impact a broader society. His unique and insightful essays also imply the preexistence of a leader who is willing to serve. This article presents a possible servant leader developmental model to accomplish such objectives. The model highlights how anyone, should they …

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. …

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 …

Policy-Driven Scalable Generation Of Network Configurations With Dynamic Parameters, N/A

Defensive Publications Series

The technology described in this paper relates to generating network configurations utilizing a stateless, policy-driven architecture. The technology utilizes a centralized database storing applicable policies as the source of truth rather than persistently storing fully constructed configurations. During configuration updates, a system for generating the network configurations retrieves the applicable policies, updated with the current state and regenerates the network configurations entirely from scratch. A multi-phase translation process handles dynamic parameter constraints by gathering parameters, generating mutually exclusive and exhaustive override blocks using a recursive algorithm, and mapping applicable policies to these generated blocks via a soft matching process. This …

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 …

The Return Of Regime Politics: Liberator Or Tyrant, Dylan Coombs

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.

Intelligence Reform: A Strategic Overhaul Of The Intelligence Community, Johnny Davis

Helms School of Government Spring Public Policy Conference

No abstract provided.

What Is New In Temporary Mechanical Circulatory Support In 2024-2025?, Maya Guglin

The VAD Journal

This review covers the most interesting publications on temporary mechanical circulatory support in 2024-2025. We include the latest research on intra-aortic balloon pumps, Impella devices, and veno-arterial extracorporeal membrane oxygenation.

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

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 …

Spatial Evaluation Of Assessment Price Performance Through 3d Visualization And Geospatial Analytics, Su Yeon Jung Ph.D. (Economics)

GIS/ValuationTechnologies Conference 2026

Accurate evaluation of assessment prices is essential for fair and transparent property taxation. This presentation introduces a geospatial framework that visualizes and measures assessment ratio performance across local areas using 3D mapping techniques. Based on ratio-study principles, the approach employs GIS tools and 3D visualization to show spatial characteristics of areas where assessment levels are relatively high or low. A case study of Korean housing markets demonstrates how geospatial visualization reveals local inequities in assessment levels, helping assessors and policymakers better understand regional discrepancies and improve uniformity. This presentation highlights how 3D mapping and spatial analytics enhance interpretation of assessment …

Succession Success In Seven Steps, Damian Lara Esq.

GIS/ValuationTechnologies Conference 2026

Session will provide the tools and teach the best practices to develop and implement a successful succession plan. Presentation materials will include templets, questioners and guidelines to implement a customizable out of the box succession plan.

Meduncertainvlm: Multi-Modal Uncertainty Quantification In Vision-Language Models For Clinical Documentation, Shikhar Patel, Rushabh Darji

Artificial Super Intelligence (ASI) Conference

Vision-language models are increasingly deployed for clinical documentation tasks in radiology. A common application involves extracting diagnostic labels from chest radiographs with reports. These models must communicate calibrated uncertainty to avoid influencing patient care incorrectly. Overconfident predictions from poorly calibrated models pose a documented patient safety risk. Existing medical vision-language models produce only point estimates without any confidence bounds. Standard post-hoc calibration methods such as temperature scaling omit cross-modal signals entirely. They cannot detect cases where image and text branches make genuinely inconsistent predictions. This paper presents MedUncertainVLM, a framework that addresses this gap directly and systematically. The system uses …

2nd Annual Miners Solving For Tomorrow Research Conference - Undergraduate Schedule, Blake Bowman, Carter Lawson, Celia Freed, Adam Merchiori, Allie Dingfield, Catherine Skaggs, Drake O'Leary, Quinten Bachman, Elizabeth Bone, Joely Grace Hall, William Wisnasky, James Meyer, Sindhujaa Jaiganesh, Sophia Nicolette Petilla Militante, Brantley Carter, Adrianna Sasser, Alec Gamache, Micah Gargrave, Keagen Miller, Uma Adrianna Misra, Collin Gentry, Christy Johnson, Brady Carlson, Logan Williamson, Jivanji Sumariwalla, Hayden O'Dell, Elijah Brakensiek, Katharine Gray, Lukas Farthing, Jacob Harl, Landon Meyer, Nehemiah Milton, Lana Herkenhoff, Jenna Mueller, Lucas Ethington, Maya Southard, Aster Davidson, Ethan Beane, Jacob Penn, Connor Jordan, Amanda Hodges, Ethan Keuhn, Milan Jebaraj, Ariel Pilger, Sydney Clark, Maris Reinkemeyer, Manav Raja Vinotha, Punit Sesha Sai Turlapati, Benjamin Sullins, Benjamin Biehl, Jamie Koester, Aidan Sengupta

Miners Solving for Tomorrow Research Conference

No abstract provided.

2nd Annual Miners Solving For Tomorrow Research Conference, Blake Bowman, Carter Lawson, Celia Freed, Adam Merchiori, Allie Dingfield, Catherine Skaggs, Drake O'Leary, Quinten Bachman, Elizabeth Bone, Joely Grace Hall, William Wisnasky, James Meyer, Sindhujaa Jaiganesh, Sophia Nicolette Petilla Militante, Brantley Carter, Adrianna Sasser, Alec Gamache, Keagan Miller, Uma Adrianna Misra, Collin Gentry, Christy Johnson, Brady Carlson, Logan Williamson, Jivanji Sumariwalla, Hayden O'Dell, Elijah Brakensiek, Katharine Gray, Lukas Farthing, Jacob Harl, Landon Meyer, Nehemiah Milton, Lana Herkenhoff, Jenna Mueller, Lucas Ethington, Maya Southard, Aster Davidson, Ethan Beane, Jacob Penn, Connor Jordan, Amanda Hodges, Ethan Keuhn, Milan Jebaraj, Ariel Pilger, Sydney Clark, Maris Reinkemeyer, Manav Raja Vinotha, Punit Sesha Sai Turlapati, Benjamin Sullins, Benjamin Biehl, Jamie Koester, Aidan Sengupta, Antai Dong, Connor Bell, Dennis Dadzie, Joshua Gary, Adebayo Olayinka Oke, Deeshani Mitra, Yejun Kim, Josiah Mcdermott, Samiksha Aryal, Nicholas Brenner, Timothy Ennis, Maryam Sharifi Paroushi, Sujan Maharjan, Md Saiduzzaman, Hari Dhital, Manuela Isabel Arenas Alvarez, Eyuel A Getahun, Lucas Greiner, Amaneh Babaee, Shane Cairns, Nazish Khalid, Joseph Walton, Jie Shi, Ehsan Asheghianamiri, Mariam Elazhary, Makuach James Makeny Panther Athach, Rasman Mubtasaim Swargo, Shiva Kumar Goud Kasani, Pablo Jara, Sara Mccauley, Hartzell Weston, Al Mojahid Afridi, Matik Heskin, Nima Mahmoudzadeh, Effat Eskandari, Amitav Sen, Rabin Pandey, Amirhossein Habibi, Nuzaer Omar, Mizanur Rahman Jewel, Nathan Tibbetts, Manoj Twarakavi, Fahara Bristy, Akhrorbek Narmatov, Mahnaz Asgari Sooran, Tafang Hei, Nathan Roberts, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

No abstract provided.