Digital Commons Network^™

Successful Management Of A Large Pediatric Traumatic Pneumothorax Using A Thoracic Vent Device After Blunt Chest Injury: A Case Report, Jayanjali Bodavula, Melika Babadi, Morgan W. Stewart, Brett Dunbar

Student Publications

Traumatic pneumothorax is a common complication of blunt thoracic trauma and is traditionally managed with tube thoracostomy, particularly in larger or symptomatic cases requiring pleural decompression. Thoracic vent devices, such as the UreSil Thora-Vent, represent a less invasive pleural drainage option for the management of spontaneous or iatrogenic pneumothorax. However, literature regarding their use in traumatic pneumothorax, particularly in pediatric patients, remains limited. We present a case of a 13-year-old girl who developed a large left-sided traumatic pneumothorax after blunt thoracic trauma sustained during a softball collision. Computed tomography demonstrated a large left-sided pneumothorax and a nondisplaced left sixth rib …

An Automated Electrochemistry Platform For Accelerating The Characterization Of Enzymatic Electrochemistry, Michael A. Pence, Zachary A. Nguyen, Luke G. Kays, Dylan G. Boucher, Joaquín Rodríguez-López, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Enzymatic electrochemistry harnesses the selectivity of enzymes to enable electrochemical applications spanning sensing, synthesis, and energy conversion. However, the sequential nature of electroanalytical experiments limits throughput, restricting the scale at which enzyme-electrode systems can be screened. Here we demonstrate the capabilities of an automated electrochemistry platform, eLab, to increase the throughput of enzymatic electrochemistry investigations. We used the eLab to collect over 10,000 cyclic voltammograms across a large parameter space consisting of two enzyme variants (promiscuous and wild-type glucose oxidase), 20 saccharide substrates, 21 concentrations, and four scan rates, with measurements being made all in triplicate. The expansive dataset enabled …

The Fingers-Based Occlusion Effect Triggering Methodology That Will Be Utilized For Creating Visual Imagery And Visual Patterns Utilizing A Pen Tool Where The Pen Tool Can Be Utilized To Create Visual Imagery And Visual Patterns On Physical Surfaces And On 3-Dimensional Virtual Space Areas., Punarjeewa Abeysekera

Defensive Publications Series

This paper describes a fingers-based occlusion effect triggering methodology that will be utilized for creating visual imagery and visual patterns utilizing a pen tool where the pen tool can be utilized to create visual imagery and visual patterns on physical surfaces and on 3-dimensional virtual space areas. The fingers-based occlusion effect triggering methodology will incorporate a pen tool, a built-in display that produce illumination, tracking markers and built-in camera configuration. The methodology will be required to utilize a power source that will be required to power the pen tool and its entities. And the methodology will be required to utilize …

Method For Trust-Aware And Language Model–Driven Email Threat Detection And Mitigation, Niranjan M M

Defensive Publications Series

Email remains the primary communication channel for enterprises and continues to be the most exploited attack vector for cyber threats. Modern email attacks increasingly rely on impersonation, social engineering, and contextual manipulation rather than traditional malware or malicious links, allowing them to evade existing detection mechanisms. At the same time, email security systems are adopting large language models (LLMs) to improve intent detection and contextual analysis, introducing new risks where email content itself can manipulate or degrade automated reasoning.

The proposal introduces a secure, trust-aware, and LLM-safe framework for automated email threat detection and remediation. The proposed system integrates sender …

Risk Authority Platform, Soumick Sinha, Mayank Johari, Lucas Fernando Müller, Sanjay Sawhney

Defensive Publications Series

Proposed herein is a Risk Authority platform that continuously computes an authoritative Trust Score and Trust Deficit for users or entities from heterogeneous security, identity, threat, compliance, privilege, and vendor-risk telemetry. The platform normalizes signals, applies configurable weighting and time decay, and maintains a versioned canonical trust state. A drift detection and reconciliation engine compares downstream trust states against the authoritative state and issues deterministic, idempotent reconciliation tokens when deviations or model-version mismatches occur. Software development kit (SDK) and application programming interface (API) integrations can validate schemas, verify tokens, and propagate risk updates. A closed-loop adaptive policy controller maps Trust …

Primitive For Finding Actionable Information In Time Series Based On Motif Locations, Michael Yeh, Yan Zheng, Junpeng Wang

Defensive Publications Series

The present disclosure relates to a system and method for finding actionable information in time series based on motif locations. The method includes an analysis computer that obtains time series data. The analysis computer generates a plurality of motifs. For each motif of the plurality of motifs, the analysis computer determines identified locations in the time series data that match the motif and determines a plurality of motif type scores based on the identified locations of the motif. The analysis computer determines a selected motif of the plurality of motifs based on the plurality of motif type scores for each …

Method, System, And Computer Program Product For Online Account Recovery, Elisa Duarte

Defensive Publications Series

Methods, systems, and computer program products are provided for online account recovery. An example method includes: receiving an account recovery request associated with a user account a user is unable to access, the account recovery request including identity data and payment device data, the payment device data obtained via short range wireless communication in response to the user arranging the payment device relative to a computing device; in response to receiving the account recovery request, authenticating the chip based on a cryptogram; in response to authenticating the chip, inputting a payment device identifier and the identity data into a model …

Optimally Scaled Low-Rank Adaptation For Efficient High-Rank Fine-Tuning, Yilang Zhang, Xiaodong Yang, Yiwei Cai

Defensive Publications Series

A method can be performed during a round of iteration during a loss function optimization process. The method can include a computer obtaining a first matrix and a second matrix. The computer can determine a selected scaling process from a first scaling process and a second scaling process. The computer can modify the first matrix and the second matrix using the selected scaling process to obtain a first modified matrix and a second modified matrix. The computer can determine a first moment and a second moment based on the first modified matrix and the second modified matrix. The computer can …

Autonomous Mobile Robot For Transferring Planar Workpieces Between Processing Stations Using An Orientation-Holding Con­Veyor Stage And A Self-Locking Kinematic Dock, Alexander Willer

Defensive Publications Series

An autonomous mobile robot (AGV / AMR) transfers a planar workpiece — for example a printed circuit board — between processing stations by carrying a transfer-conveyor segment on a powered stage that holds the segment’s orientation independently of the robot’s heading. This lets a minimal-footprint, non-holonomic robot present the conveyor to a station port facing any direction, in confined space, without sweeping the segment through its diagonal. At each station a docking interface is provided that separates location from clamping: passive kinematic features (a fully-locating feature plus a relieved one, optionally tapered) locate the segment, while one or more self- …

Predictive Doppler Frequency Pre-Compensation For Non-Terrestrial Network Handovers, Edison Chen, Xuqiang Zhang

Defensive Publications Series

In non-terrestrial networks, for example, networks that use low-earth-orbit satellites, handovers between satellites may be subject to latency due to significant Doppler frequency shifts for the target satellite. This disclosure describes a predictive method for Doppler pre-compensation that may be centered at a user equipment (UE) (e.g., a smartphone, tablet, or vehicle-mounted terminal). The technique may involve the UE recording the magnitude of a frequency compensation value from its connection with a source satellite. For an initial uplink transmission to a target satellite, the UE may then apply a predictive pre-compensation value, which could be derived by inverting the polarity …

In-Band Threat Context Propagation For Distributed Policy Enforcement, Niranjan M M

Defensive Publications Series

The proposal introduces a data-plane aligned mechanism for propagating compact, actionable threat context in-band with live traffic to enable immediate and coordinated security enforcement across distributed environments. Instead of relying on centralized control-plane signaling or out-of-band policy distribution, the approach encodes deterministic enforcement intent such as action, severity, scope, and validity into bounded in-band metadata that travels along the same forwarding path as the affected traffic.

Enforcement points decode and validate this metadata in the fast path and apply policy actions at data-plane speed without requiring context lookups or external coordination. Rich threat details remain out-of-band and are optionally resolved …

System For Converting Predictive Insights Into Executable Tasks Using Retrieval-Augmented Generation, N/A

Defensive Publications Series

Predictive analytics tools are highly effective at identifying organizational risks, such as potential employee turnover, but they often fall short in providing managers with clear steps to resolve these issues. To bridge this gap, the described technology functions as an intelligent intermediary layer that translates high level statistical risk drivers into concrete, multi-step intervention strategies.  When a predictive engine detects a risk, the system uses a retrieval augmented generation framework to pull relevant contextual information from an internal knowledge base, which can include organizational playbooks and historical success records. This specific context is then fed into a generative large language …

System For Context-Aware Data Redaction Using Instruction-Constrained Generative Ai, N/A

Defensive Publications Series

Data redaction techniques, such as manual review or simple pattern-matching, may present challenges related to speed, potential for errors, and contextual understanding for identifying sensitive information. The described system and method may be used for a context-aware redaction process that uses a generative artificial intelligence (AI) model. Source text can be encapsulated within a detailed instructional prompt that guides the AI model's function toward identifying and substituting sensitive data. This process can be managed by an orchestration layer that is configured to interact with an AI inference engine, for example, under a zero-retention policy. By replacing identified data with semantic …

Prioritization Of Work Items Using Ai-Based Weighted Strategic Alignment, Tanmay Kayande, Deep Raithatha

Defensive Publications Series

Prioritization of work items within an organization can be a subjective and manual process, potentially leading to a disconnect between development efforts and strategic business objectives. A disclosed technology describes a system, for example, a computing device (e.g., a server, a smartphone, a wearable device), where an artificial intelligence agent can analyze unstructured work requests, such as feature ideas or bug reports. The agent may evaluate an item against a configurable registry of weighted strategic drivers, and can assign a numerical score and a natural language justification. A total priority score may then be calculated for a work item by …

An Evaluation Of The “Police Response To Uncrewed Aircraft Systems Operations” Online Training Program, Anthony Galante, Leila Halawi

Publications

This study evaluates the impact of the “Police Response to Uncrewed Aircraft Systems Operations” online training program of officers from the Daytona Beach Police Department (DBPD). By measuring the effectiveness of the training through pretest and posttest assessments and considering variables such as educational background, length of service, and rank, this research underscores the training’s potential to enhance UAS response capabilities. Employing a self-selection sampling method, the study engaged 82 voluntary participants from the DBPD, revealing significant improvement across all groups in UAS knowledge and confidence levels. Despite limitations, these findings offer compelling evidence of the training’s efficacy and advocate …

Alumni Voices. Beyond Graduation: The Lifelong Global Impact Of A Uk Education, Sladana Krstic, Alexander Towne

Higher education research

The third round of the British Council Alumni Voices survey provides robust and timely evidence of the enduring value of a UK higher education experience. Drawing on three years of longitudinal survey data, supplemented by a number of interviews, the findings highlight how UK education continues to deliver skills, support professional progression, and foster long lasting international networks that extend well beyond graduation and national borders. Nearly three quarters of respondents report that in the last 12 months they have maintained contact with people they first met during their UK studies, and almost 84 percent have recommended a UK study …

Modeling And Forecasting Intraday Spot Volatility, Adam Clements, Daniel P. A. Preve

Research Collection School Of Economics

We propose a multiple-equation regression-based method for modeling and forecasting intraday spot volatility. In this approach, intraday intervals are treated as individual time series, deviating from the common practice of treating the data as one continuous sample. Our empirical study, which spans more than two decades and encompasses six US blue-chip stocks, employs the recent OK volatility estimator developed by Li, Wang, and Zhang (2024) to expose the dynamics of latent intraday spot volatility over time. We demonstrate that the proposed method effectively captures the intricate dynamics of intraday spot volatility and find strong evidence that it outperforms a competing …

How Do Sectoral Shocks Shape Future Gdp?, Paul Ho, Danial Lashkari, Pierre-Daniel Sarte

Research Collection School Of Economics

A production sector’s size, as measured by its Domar weight, captures the contemporaneous aggregate effect of its productivity shocks. Any future aggregate effects, however, depend on that sector’s participation in the investment network. We derive a dynamic generalization of Hulten’s theorem in an environment with intermediate-input and investment networks. This generalization, implied by production efficiency alone, decomposes each sector’s Domar weight into an impact and a propagation component. The relative size of these components then determines how persistent the aggregate effects of sectoral shocks are, but cannot be known absent information on the economy’s production structure. We show in a …

Exploring The Relationship Between Energy Use And Sectoral Output At The Useful Stage, Daniel Chester, Ritika Susarla, Paul Brockway, Emmanuel Aramendia, Matthew Magness, Matthew Kuperus Heun

University Faculty Publications and Creative Works

1.Develop a publicly-available dataset of sectoral useful energy/exergy intensities

• And final, where not already existing

• How do global sector-level trends change when viewed from the useful stage?
• Are similar convergence patterns observed compared to previous analysis?
• How do sectoral differences explain aggregate convergence/divergence?

Smart-Twin: Systematic Modeling And Real-Time Transportation With Digital Twins, Hovannes Kulhandjian

Mineta Transportation Institute

Urban transportation networks are increasingly affected by everyday congestion, non-recurring disruptions, and limited real-time visibility into what is happening on the road. Transportation agencies require advanced tools that support faster, proactive management and data-driven infrastructure decisions rather than passive monitoring. This report presents SMART-TWIN, an Artificial Intelligence (AI)–driven Digital Twin framework designed for real-time traffic operations, disruption detection, and performance-based decision-making support. The SMART-TWIN architecture integrates microscopic traffic simulation (detailed traffic modeling), long-horizon synthetic demand generation simulating real travel patterns, supervised machine learning, and performance analysis within a unified and reproducible workflow. A corridor-scale Digital Twin was developed for the …

The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou

Research Collection Lee Kong Chian School Of Business

Over the last decade, there has been an explosion in the use of diverse data sources by management scholars to observe and capture managerial and organizational constructs that have historically been difficult to access. This surge has been driven by the growing availability of rich, multi-modal data—textual, image, and audio (Luo, Jia, Ouyang, & Fang, 2024)—together with advances in analytical techniques to process and analyze data, such as computer-aided text analysis (Harrison, Thurgood, Boivie, & Pfarrer, 2019), machine learning (Choudhury, Wang, Carlson, & Khanna, 2019; Harrison, Josefy, Kalm, & Krause, 2023), and deep learning (Gouvard, Goldberg, & Srivastava, 2023). These …

Keeping Up With The Times? Rethinking Social Evaluations Research Under Contemporary Technological And Sociopolitical Forces, Marco Clemente, Michael Etter, Yuliya Snihur, Gokhan Ertug, Graffin Scott, Anastasiya Zavyalova

Research Collection Lee Kong Chian School Of Business

The context within which social evaluations form has been fundamentally altered by contemporary forces, such as digital technologies, polarization, activism, politicization of business, and geopolitical tensions. While research on social evaluations has generated rich insights into the formation and development of constructs, such as legitimacy, status, reputation, stigma, trust, and celebrity, much of this work has been developed under the assumptions of relative stability, coherent audiences, and well-defined intermediary roles. These assumptions are increasingly challenged in this changing context, requiring us to rethink the formation and management of social evaluations. The articles in this special issue focus on these changes. …

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

Shadows Of Salem: Recovered Memories In The Sandusky Case, Stewart Justman

Global Humanities and Religions Faculty Publications

In 2012 the former Penn State football coach Jerry Sandusky was convicted of 45 counts of the sexual abuse of children.  However, none of his accusers accused him of anything until Victim 1, Aaron Fisher, entered treatment with a psychologist who diagnosed him at first sight as a victim of sexual abuse. The psychologist denied that he engaged in recovered-memory therapy. The record suggests otherwise. If a competent defense had shown at trial that the psychologist practiced on Victim 1 the same mode of therapy he rejected out of hand, the case against Sandusky might have collapsed, much as the …

Reading List: Introduction To Mystery And Detective Literature, Jesse Cordes Selbin

Open Syllabus Collection

The bloody knife. The telltale footprint. The courtroom confession. We all know the cliches of the detective and mystery genres, so why do they remain novel even when you know “whodunit”? This class will investigate the literary and cultural factors that make detective fiction perennially popular, from Sherlock Holmes to your favorite true crime podcast. In order to explore central questions raised by mystery novels, short stories, poems, and plays about the craft of storytelling itself, we will read bestselling authors like Edgar Allan Poe, Arthur Conan Doyle, Robert Louis Stevenson, and Charles Dickens, as well as lesser-known writers like …

Cultivating Narratives: A Critical Discourse Analysis Of Higher Education Student-Led Farms And Gardens, Maximilan Sherard, Marc T. Sager

Publications

Despite extensive research on community agriculture, little attention has been paid to student-led farms or gardens (SFGs) in higher education contexts. SFGs represent a unique site for community agriculture due to their diverse stakeholders, academic affiliations, and the institutional policies they navigate. This study examines online promotional materials from 42 SFGs located on land-grant higher education campuses across the United States. Using critical discourse analysis, we (1) map these organizations’ practices and (2) identify competing discourses about community and agriculture within their promotional narratives. We identify and explain four core practices (membership, growing, distribution, and purpose) and connect these practices …

Field Trials Report 2025: Wa Farming Systems Project (Daw2204-003rtx), Department Of Primary Industries And Regional Development, Western Australia

Farm Systems and Economics research reports

In 2025 the Western Australian Farming Systems Project continued its program of field trials, from Northampton in the north to Wittenoom Hills in the south, to address our project outputs; investigate diversity within farming systems, evaluate changes in sowing opportunities, identify profitable low greenhouse gas emission options and monitor crown rot following diverse crop sequences.

A Comparative Study Of Aging And Cortical Folding In Chimpanzees And Olive Baboons, William D. Hopkins, Angela M. Achorn, Michele M. Mulholland, Elizabeth R. Magden, Steven J. Schapiro, Courtney L, Fults, Jean‐Francois Mangin, Adrien Meguerditchian

Anthropology Faculty Publications

In light of the evidence that nonhuman primates naturally develop Alzheimer's disease neuropathologies, there is a renewed interest in research on the comparative biology of aging, including neurological changes across the age groups in species with diverse lifespans. In this paper, we examined age‐related differences in two measures of cortical folding, mean depth and fold opening, in a sample of chimpanzees (Pan troglodytes) and olive baboons (Papio anubis). We found significant species differences in the slope and pattern of age‐related changes in cortical folding. As predicted, chimpanzees showed negative linear associations between age and mean depth and …

Can The World Cup Stay Forever?, Essraa Nawar

Library Articles and Research

"

Something has felt different these past few weeks.

Maybe you’ve felt it too.

People seem happier.

My social media feed isn’t dominated by politics, wars, or bad news. Instead, it’s filled with strangers hugging after goals, families gathering around giant screens, children wearing jerseys from countries they’ve never visited, and fans dancing together in the streets. "

Data-Driven Decision-Making Capacity Of State Vr Agencies, Catherine Ipsen, Christopher Clapp, Jordan A. Costello

Employment

Federal agencies are required to use data to support policy and program decisions. This factsheet explores VR capacity to use their data to shape decision-making and develop return on investment (ROI) models.