Digital Commons Network^™

Wedge-Tailed Shearwater Ardenna Pacifica Fallout Patterns Inform Targeted Management, Brooke Friswold, Keith Swindle, David Hyrenbach, Melissa R. Price

Marine Ornithology

Seabird fledglings are often attracted to artificial, bright lights, leading to their grounding. This phenomenon is termed “fallout” and is associated with an increased risk of mortality from land-based threats. This study evaluated temporal trends and spatial factors, such as fallout clustering near lights and proximity to colonies, to inform targeted management actions. Standardized surveys were conducted from 2002 to 2010 for Wedge-tailed Shearwater Ardenna pacifica (WTSH) fallout on the island of O‘ahu, Hawai‘i, USA. First, yearly fallout counts along the transect showed a two-year cycle and identified 25 November as the date with the highest fallout across years. Second, …

Retracted: A Quantum Convolutional Neural Network Approach For Early And Accurate Diagnosis Of Parkinson's Disease, Aiesha Mahmoud Ibrahim, Mazin Abed Mohammed, Omar Al-Boridi

Iraqi Journal for Computer Science and Mathematics

Parkinson's disease (PD) is a progressive neurological disorder that primarily affects individuals over the age of 55. It is characterized by a range of motor and non-motor symptoms that can significantly impact various aspects of daily life. Despite notable advancements in medical science, there is currently no permanent cure or definitive treatment for PD. This therapeutic gap underscores the critical importance of early diagnosis, which remains a major focus of ongoing research. Due to the disease's gradual progression, PD symptoms may take years to fully develop, making early detection essential for improving patient outcomes and quality of life. Moreover, the …

Retracted: Solving Time-Fractional Nonlinear Variable-Order Delay Pdes Using Feedforward Neural Networks, Hala S. Alruhaili, Adel S. Hussain, Abdullah M. S. Ajlouni, Funda Türk, Emad A. Az-Zo’Bi, Mohammad A. Tashtoush

Iraqi Journal for Computer Science and Mathematics

This study presents an innovative application of Feedforward Neural Networks ‘FNNs’ to solve Variable-Order Fractional Partial Differential Equations ‘VO-FPDEs’ with time delays. Utilizing the Caputo definition, the variable-order fractional derivatives are approximated in terms of integer-order derivatives. The problem is reformulated as a system of partial differential equations with delay terms, which is then addressed using ‘FNNs’ to achieve explicit approximate solutions. Comprehensive error and convergence analyses validate the method’s precision and reliability. The effectiveness of the proposed approach is highlighted through numerical examples, with graphical and tabular representations showcasing minimal absolute errors and robust convergence. These results demonstrate the …

The Future Of Intelligent Industrial Systems: Plc, Node-Red, And Iot/Iiot, Firas Ahmed Hussein, Mohammad Tariq Yaseen, Mohammed Obaid Mustafa

AUIQ Technical Engineering Science

Integrating Programmable Logic Controllers (PLCs) with Node-RED and IoT/IIoT has emerged as a transformative technique for developing intelligent industrial systems as industrial automation improves. This narrative review brings together more than 70 research sources on industrial PLC, Node-RED, IoT, and IIoT applications. Case studies, experimental implementations, and industry reports are used to discover trends, challenges, and opportunities. The review focuses on three main topics: PLCs in modern industrial systems and their evolution and integration with IoT/IIoT; Node-RED as a middleware for industrial automation and its ability to connect PLCs to cloud and edge computing; and IIoT and smart manufacturing and …

Detecting Android Malware Based On Static Analysis Using Classification And Modified Clustering Techniques, Abdullah Allawi Al-Sraratee, Ahmed Habeeb Al-Azawei

Journal of Intelligent Informatics, Networking, and Cybersecurity

Because Android malware harms internet security, prior research proposes several different approaches to detect it accurately. However, such proposed models depend on numerous number of features to attain high accuracy. This could lead to high computation cost and potential overfitting. Furthermore, manual data labeling is labor-intensive, requiring significant human effort and skills. This research aims to: 1) extend previous literature on Android malware detection, 2) improve the accuracy of Android malware detection based on a low number of features, and 3) modify a clustering technique to group data into two different clusters to address the issue of unlabeled data. To …

Electrochemically-Assisted Low Power Density Laser Writing On Stainless Steel Via Enrichment Of Chromium Oxides, Zechariah Pfaffenberger, Lianlian Liu, Tae Kyong John Kim, Vignesh Venkataramani, Lydia Kisley

Faculty Scholarship

Laser color marking produces nearly permanent, environmentally friendly, vibrant colors on surfaces. However, previous work has used high-power-density pulsed lasers to induce the physicochemical reactions for marking. Here, laser color marking on stainless steel 304 (SS304) is performed with a less expensive continuous wave (CW) laser and a power density five orders of magnitude below that previously reported by combining an electrochemical cell with a fluorescence microscope. Using a combination of optical microscopy, x-ray photoelectron spectroscopy, and bulk electrochemistry, it is demonstrated that the laser-induced luminescence and colors are due to enrichment (32 ± 9% increase) of Cr2O3 in the …

2025 July 17 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Conquer And Prevail Issue 192 July 17 2025, Wofford College. Office Of Marketing And Communications

Conquer and Prevail Newsletter

No abstract provided.

Recent Advances In Modelling Of Frost Formation For Mechanical Systems, Yong Tao

Mechanical Engineering Faculty Publications

The physics underlying frost and ice formation has been extensively studied over the past few decades, with significant contributions to our understanding of this phenomenon. These insights have primarily been applied to engineering systems with refrigerated surfaces, such as refrigerators, freezers and heat pumps of various sizes. Despite considerable progress, the dynamic and complex mechanisms governing frost and ice formation remain an active area of research, as competing factors continue to challenge predictive accuracy. The increasing interest from stakeholders in reducing energy consumption and carbon footprints in mechanical systems further underscores the importance of advancing modelling and simulation capabilities in …

Investigating The Capacity Of Tdp-43 Low Complexity Domain To Target Protein Aggregates In Yeast, Nicholas J. Grahame

Biology Summer Fellows

Utilizing protein TDP-43 and fluorescent proteins to:

Investigate TDP-43’s LCD region in protein aggregates. Use fluorescent protein tagging to visualize co-localization and aggregation. Leverage yeast as a model system for studying LLPS and aggregation.

Can we target chaperone proteins to TDP-43 LCD region?

A Predictive Framework For Early Detection And Personalised Monitoring Of Parkinson’S Disease Using Artificial Intelligence And Large Language Models, Priyadharshini S

Theses and Dissertations

Parkinson’s Disease (PD) is a multifaceted and progressive neurodegenerative disorder that presents a spectrum of motor and non-motor symptoms. Early and accurate diagnosis is essential for effective disease management and improved patient outcomes, yet remains clinically challenging due to symptom overlap and diagnostic limitations. This thesis proposes a comprehensive and interpretable artificial intelligence (AI)-driven diagnostic framework that aims to transform the early detection, personalised monitoring, and treatment recommendation process for PD. The proposed solution integrates deep learning, radiomics, evolutionary optimisation, and large language models (LLMs), ensuring a highly accurate and clinically adaptable system.

The research begins by analysing T2-weighted 3D …

An Inquiry Into The Effectiveness Of Vegetation Barrier Composition On Air Pollutant Mitigation In Fulshear, Texas, 77441, Ananya R. Pasunuri

Cities and the Environment (CATE)

In many suburban areas, particularly around Greater Houston, rapid residential expansion has contributed to declining air quality. This study investigates the impact of vegetation barriers in mitigating pollution caused by ongoing construction, with a specific focus on FM 1463 in Fulshear, TX, 77441. The Texas Department of Transportation (TxDOT) has stated that the construction project would not significantly deteriorate air quality; however, their assessment failed to consider the effects on PM 2.5 levels. This study examines whether the construction had measurable effects on air quality by comparing AQI and PM 2.5 data from 2020 and 2024. Additionally, it evaluates the …

Quantum Memory, Isabel Martinez-Robles

Physics and Astronomy Summer Fellows

Isolated quantum systems are almost always observed to achieve thermal equilibrium in experiments. Understanding cases where they do not thermalize, and therefore retain memory about the initial state, could lead to the development of a quantum memory. We excite atoms in a magneto-optical trap, where they are cold enough to treat as stationary. In our experiment, our atoms exchange energy via dipole-dipole interactions and fail to thermalize. We present a theoretical and computational analysis that suggests that our system starts in an exceptional initial state.

Limitations Of Using Large Language Models For Automated Essay Scoring, Thomas A. Fink

Theses

Background: Automated essay scoring (AES) is a challenging deep learning problem. The two most widely used methods for predicting essay quality scores, supervised learning-based and LLM-based, have their own limitations. Although supervised learning-based methods are more accurate, they only predict a score and do not offer descriptive feedback to students. On the other hand, LLM-based methods can offer rubric-guided feedback but are known to be less accurate.

Methods: This work focuses on improving the accuracy of state-of-the-art LLM-based AES methods. We began by thoroughly investigating why these methods were performing poorly for certain datasets and certain examples. This led us …

Predicting Sleep And Sleep Stage In Children Using Actigraphy And Heartrate Via A Long Short-Term Memory Deep Learning Algorithm: A Performance Evaluation, Robert Weaver Med, Phd, James White, Olivia Finnegan, Hongpeng Yang, Zifei Zhong, Keagan Kiely, Catherine Jones, Yan Tong, Srihari Nelakuditi, Rahul Ghosal, David E. Brown, Russell R. Pate Ph.D., Gregory J. Welk, Massimiliano De Zambotti, Yuan Wang, Sarah Burkart, Elizabeth L. Adams Phd, Bridget Armstrong, Michael Beets Med, Mph, Phd

Faculty Publications

Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short-term memory (LSTM) is a machine learning algorithm that may address these deficiencies. This study evaluated the agreement of LSTM sleep estimates from actigraphy and heartrate (HR) data with polysomnography (PSG). Children (N = 238, 5–12 years,52.8% male, 50% Black 31.9% White) participated in an overnight laboratory polysomnography. Participants were referred be-cause of suspected sleep disruptions. Children wore an ActiGraph GT9X accelerometer and two of three consumer wearables(i.e., Apple Watch Series 7, Fitbit Sense, Garmin Vivoactive 4) on their non-dominant wrist during the polysomnogram. LSTM estimated sleep versus wake and sleep stage (wake, not-REM, REM) using raw actigraphy and HR data for each 30-s epoch. Logistic regression and random forest were also estimated as a benchmark for performance with which to compare the LSTM results. A 10-fold cross-validation technique was employed, and confusion matrices were constructed. Sensitivity and specificity were calculated to assess the agreement between research-grade and consumer wearables with the criterion polysomnography. For sleep versus wake classification, LSTM outperformed logistic regression and random forest with accuracy ranging from 94.1to 95.1, sensitivity ranging from 94.9 to 95.9 across different devices, and specificity ranging from 84.5 to 89.6. The addition of HR improved the prediction of sleep stages but not binary sleep versus wake. LSTM is promising for predicting sleep and sleep staging from actigraphy data, and HR may improve sleep stage prediction.

Class Action Cy Près Revisited, Christopher J. Ryan Jr.

Louisiana Law Review

No abstract provided.

Can Commentary Command Courtroom Clout?: The Court’S Deference To Commentary To The United States Sentencing Guidelines In A Post-Kisor World, Gabriella A. Leccese

Louisiana Law Review

No abstract provided.

Correlated Sampling Of Parallel Partial And Linked Emulators For Geophysical Applications, Joseph Lyon

Dissertations (1934 -)

Computer models, or simulators, are mathematical representations of real world phenomena that, to run at new input settings, are often computationally intensive and prohibitively slow. Surrogate models, or emulators, provide a method of rapidly predicting simulator outputs with uncertainty at untested configurations by treating the computer model output as a single realization of a stochastic process, specifically a Gaussian Process (GP).In this dissertation, we consider three projects: Correlated Linked GP Emulation, Spatially Correlated Parallel Partial Emulation, and Optimizing the Zero-censored Gaussian Process with Spatially Correlated Sampling. First, the Correlated Linked Emulator, focuses on developing a model for the covariance of …

Cognitive Fatigue Assessment For Human-Robot Collaboration: Review & Open Challenges, Manizheh Zand, Sally Wood, Fatemeh Davoudi Kakhki, Maria Kyrarini

General Engineering

As Human Robot Collaboration (HRC) technologies continue to advance, robots are increasingly being deployed to assist in various settings, including manufacturing, healthcare, and home environments. A critical aspect of designing safe and adaptable HRC systems is the ability to assess and monitor an individual’s Cognitive Fatigue (CF) during interactions with robots. This is especially important in ensuring safe and effective environments, as fluctuations in CF can affect both performance and safety. Although prior research has explored cognitive workload and fatigue, a significant gap exists in understanding how to effectively measure and manage CF in real-time during HRC. This paper reviews …

Numerical Simulation Of Frost Formation And Heat Transfer On Fin-And-Tube Heat Exchangers In Turbulent Cross-Flow, Mahsan Farzaneh, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Frost formation in fin-and-tube heat exchangers in turbulent cross-flow presents significant challenges in industrial refrigeration applications, affecting heat transfer efficiency and operational reliability. The purpose of this work is to investigate frost deposition and growth on a staggered bank of a fin-and-tube freezer coil under turbulent forced convection conditions. The focus here is on investigating conditions that closely replicate real-world scenarios in large walk-in industrial freezers. Using a direct numerical simulation approach, we examine the flow dynamics and thermal behaviour in the presence of frost, considering turbulent regimes characterized by a Reynolds number in the range 1050≤𝑅⁢𝑒𝐷,avg≤4800, with the characteristic …

Stokes-Dependent Droplet Collection Efficiency On A Naca 0012 Airfoil From Droplet-Informed Simulations With Statistical Overloading, Arash Shad, Hashnayne Ahmed, ‪Nadim Zgheib, S. Balachandar, S. A. Sherif

Mechanical Engineering Faculty Publications

Accurate modelling of ice accretion on aircraft wings requires analysing droplet impingement on the surface to optimize the design of ice-protection systems. We perform Euler–Lagrange simulations of a droplet-laden flow impinging on a NACA 0012 airfoil. Our study includes water droplets with eight discrete sizes ranging from 1 to 160 microns. We vary the free-stream velocity of the incoming airflow in the range 60≤⁢𝑈≤⁢240 m s−1 and the chord length of the airfoil in the range 0.5≤⁢𝑐≤⁢2 m. Due to the dilute nature of supercooled clouds, one-way coupling is used in the simulations. The effects of droplet breakup and collision …

A Rapid Method For Identifying Plant Oxidative Stress And Implications For Riparian Vegetation Management, Mizanur Rahman, Takashi Asaeda, Kiyotaka Fukahori, Md Harun Rashid, Hideo Kawashima, Junichi Akimoto, Refah Tabassoom Anta

School of Earth, Environmental, & Marine Sciences Faculty Publications

Native and invasive plants of the riverain region undergo a range of environmental stresses that result in excess reactive oxygen species (ROS). Hydrogen peroxide (H2O2) is a relatively stable and quickly quantifiable way among different ROS. The herbaceous species including Artemisia princeps, Sicyos angulatus, and Solidago altissima were selected. The H2O2 and photosynthetic pigment of leaves were measured, soil samples were analyzed to quantify macronutrients such as total nitrogen (TN), total phosphorus (TP), and soil moisture, and photosynthetic photon flux density (PPFD) was also recorded at different observed sites of Arakawa Tarouemon, Japan. The H2O2 concentration of S. altissima significantly …

Spatiotemporal Responses To A Rural Highway By Four Mammal Species, Caitlin K. Brett, Anna Rose Mehner, John H. Young Jr., Sarah E. Lehnen, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Roads can negatively impact the wildlife communities they transect. Road mortalities from wildlife-vehicle collisions are one direct effect, but roads may also indirectly affect wildlife behavior, movement, or local distribution. Quantifying the spatial extent of these road-effects is important for understanding how roads indirectly affect species of concern, identifying potential sources of disturbance, and for estimating the effectiveness of road mitigation structures. Farm-to-Market Road (FM)106, which transects part of the Laguna Atascosa National Wildlife Refuge in Cameron County, Texas, has been identified as a potential source of wildlife road mortalities, particularly for one of the two remaining breeding populations of …

Solar Absorption Cooling Systems – A Case Study In Egypt, Hesham Safwat, Iman El-Mahallawi

Mechanical Engineering

Climate change with Egypt’s increasingly hot weather and plans towards energy transition, addressing an approach for clean HVAC (Heating, Ventilation, and Air Condition) solutions is becoming requisite. This paper examines the potential of utilizing solar absorption cooling systems in institutional buildings by presenting a case study of a proposed solar absorption cooling system for a library building with an area of 4402 m2, located at the British University in Egypt. The proposed solution is to replace 30% of the existing conventional air conditioning units with a hot-water driven single-effect absorption chiller powered by solar thermal vacuum tube solar collectors, coupled …

The Response Of Mitochondrial Position To Glucose Stimulation In The Min6 Model System, Luis Perez

Arts & Sciences Graduate Student Theses and Dissertations

The compartmentalization of eukaryotic cells into membrane-bound organelles with specific subcellular positioning enables precise spatial and temporal control of cellular functions. While functionally significant mitochondrial localization has been demonstrated in cells such as neurons, it remains unclear how general these cell principles are. Here, we examine the spatial organization of mitochondria within MIN6 pancreatic beta cells under variable glucose conditions. We observe glucose-dependent redistributions of mitochondria, favoring peripheral localization at elevated glucose levels when insulin secretion is also elevated. Our results suggest that active mitochondrial transport along microtubules and calcium activity, but not ATP synthesis, are critical regulators of this …

Developing A Stochastic Rupture Model Catalog For Earthquakes With Magnitudes Of Seven Or Greater Along The Alaskan Subduction Zone, Alexandru Mihai Lapadat

Geosciences

Alaska represents one of the most seismically active regions in the Ring of Fire and world impacted by large-magnitude (Mw > 6.5) earthquake events, posing significant risks to local communities and infrastructure, but also distant populations due to the associated tsunami hazard. However, limited seismo-geodetic datasets hinder the understanding of the slip kinematics of megathrust earthquakes in the Alaskan subduction zone, complicating the estimation of future earthquake probabilities, surface displacements, and the design of a GNSS-aided Earthquake Early Warning (EEW) system. This research contributes an extensive synthetic rupture model catalog for the Alaskan subduction zone, generated using the stochastic methodology of …

A Rigorous Framework For An Improved Messinger/Myers Model Of Ice Accretion Under Conditions Of Variable Property And Unsteady Aircraft Icing, Hashnayne Ahmed, Arash Shad, ‪Nadim Zgheib, S. A. Sherif, S. Balachandar

Mechanical Engineering Faculty Publications

We analyse the Messinger/Myers model by critically evaluating simplifying assumptions through a rigorous formulation of the rime ice accretion process. We explore the effects of both constant and variable ice density and thermal conductivity, along with the effects of sublimation from the ice surface. The effects of key factors such as droplet impact rate, ambient temperature relative to the freezing temperature and the temperature difference between the ambient air and the airfoil surface are examined. Under these varying conditions, the present rigorous formulation is used to assess the significance of unsteady effects, variable ice properties and sublimation. We observe that …

Using Confidence Scores To Improve Eyes-Free Detection Of Speech Recognition Errors, Sadia Nowrin, Keith Vertanen

Michigan Tech Publications

Conversational systems rely heavily on speech recognition to interpret and respond to user commands and queries. Despite progress on speech recognition accuracy, errors may still sometimes occur and can significantly affect the end-user utility of such systems. While visual feedback can help detect errors, it may not always be practical, especially for people who are blind or low-vision. In this study, we investigate ways to improve error detection by manipulating the audio output of the transcribed text based on the recognizer's confidence level in its result. Our findings show that selectively slowing down the audio when the recognizer exhibited uncertainty …

Identifying The Desired Word Suggestion In Simultaneous Audio, Dylan Gaines, Keith Vertanen

Michigan Tech Publications

We explore a method for presenting word suggestions for non-visual text input using simultaneous voices. We conduct two perceptual studies and investigate the impact of different presentations of voices on a user's ability to detect which voice, if any, spoke their desired word. Our sets of words simulated the word suggestions of a predictive keyboard during real-world text input. We find that when voices are simultaneous, user accuracy decreases significantly with each added word suggestion. However, adding a slight 0.15 s delay between the start of each subsequent word allows two simultaneous words to be presented with no significant decrease …

Perceptions Of Blind Adults On Non-Visual Mobile Text Entry, Dylan Gaines, Keith Vertanen

Michigan Tech Publications

Text input on mobile devices without physical keys can be challenging for people who are blind or low-vision. We interview 12 blind adults about their experiences with current mobile text input to provide insights into what sorts of interface improvements may be the most beneficial. We identify three primary themes that were experiences or opinions shared by participants: the poor accuracy of dictation, difficulty entering text in noisy environments, and difficulty correcting errors in entered text. We also discuss an experimental non-visual text input method with each participant to solicit opinions on the method and probe their willingness to learn …