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A Systematic Review Of Audio Deepfake Detection Techniques For Digital Investigation, Mahra Alnaqbi, Richard Adeyemi Ikuesan Dec 2026

A Systematic Review Of Audio Deepfake Detection Techniques For Digital Investigation, Mahra Alnaqbi, Richard Adeyemi Ikuesan

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Deepfake technology has been driven by advanced machine learning and revolutionized multimedia creation by synthesizing hyper-realistic content. It includes images, videos, and audio. While its creative applications in entertainment and accessibility are significant, the technology also poses critical risks, especially in fraud, disinformation, and identity theft. Audio deepfakes are a subset of this phenomenon that replicate human voices with enhanced precision, mimicking tone, accent, and subtle vocal nuances. This has raised concerns in security-sensitive domains like voice authentication and forensic investigations. This systematic literature review (SLR) adopts PRISMA guidelines to explore the state-of-the-art in audio deepfake detection. It examines existing …

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Temporally Rigorous And Traceable Predictive Maintenance Via Joint Labeler-Model Optimization, Maytha Al-Ali, Ahmad Alharbi Dec 2026

Temporally Rigorous And Traceable Predictive Maintenance Via Joint Labeler-Model Optimization, Maytha Al-Ali, Ahmad Alharbi

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Predictive maintenance (PdM) is a critical enabler of intelligent asset management in Industry 4.0, yet many existing frameworks remain difficult to operationalize due to methodological fragmentation. Common limitations include sacrificing temporal realism and class granularity for computational expediency, decoupling labeling strategy design from model hyperparameter optimization, and insufficient support for reproducibility and deployment traceability; particularly in rare-failure regimes. To address these challenges, we propose a unified, end-to-end, and fully traceable PdM framework that jointly optimizes labeling and model parameters while enforcing strict temporal fidelity. The proposed pipeline co-optimizes the failure lookahead window () and LightGBM hyperparameters within a single Bayesian …

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Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi Dec 2026

Smart Medical System Integrating Clinical Workflows For Robust Skin Cancer Detection Across Heterogeneous Pathologies, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

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Skin cancer is among the most prevalent and life-threatening dermatological diseases worldwide, with melanoma responsible for a substantial proportion of skin cancer–related deaths due to delayed and unreliable diagnosis. Conventional clinical screening based on visual inspection and expert interpretation is inherently subjective and often affected by inter-observer variability, lesion heterogeneity, and imaging artifacts, highlighting the need for accurate and generalizable automated diagnostic systems. This study proposes a novel hybrid deep learning architecture for skin cancer classification that integrates an attention-guided autoencoder with a transformer-inspired global context modeling module, forming a unified and robust representation learning framework. The encoder–decoder structure is …

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Large Language Models In Nlp: Evolution, Architectural Trends, And Open Challenges, Haseeb Javed, Babar Shah, Farman Ali, Daehan Kwak Dec 2026

Large Language Models In Nlp: Evolution, Architectural Trends, And Open Challenges, Haseeb Javed, Babar Shah, Farman Ali, Daehan Kwak

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The rise of Large Language Models (LLMs) has transformed how Natural Language Processing (NLP) and its subdomains are approached. Recent technological advancements have driven this transformation. This study offers researchers a detailed overview of LLMs, comparing them with traditional rule-based systems, statistical techniques, machine learning, neural networks, and the rise of transformer-based architectures. From a wider perspective, language models such as GPT, BERT, T5, PaLM, and LLaMA have facilitated the transformation of entire sectors, including healthcare and business, due to their highly scalable nature. Despite their wide range of applications, LLMs face numerous challenges, such as output biases, limited interpretability, …

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Transient Phenomenology Of Third Landscape In The United Arab Emirates, Luca Donner, Francesca Sorcinelli Dec 2026

Transient Phenomenology Of Third Landscape In The United Arab Emirates, Luca Donner, Francesca Sorcinelli

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The Third Landscape, theorized by Gilles Clément, represents a residual territorial area, abandoned or not yet used, in which nature reclaims anthropized places. It is a paradigm based on the idea of a marginal, neglected context, but characterized by great intrinsic biodiversity. Starting from this theoretical assumption and supported by a photographic investigation, this study aims to identify some phenomenological characteristics of the Third Landscape in the United Arab Emirates. The scientific contribution will make use, in its dialectical and descriptive development, of reflections by authors such as, among others, Clément, Bauman, Lovelock, D’Angelo, Burkhardt, Augé, and Lynch. Starting from …

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A Global High-Resolution Comprehensive Heat Indices Dataset From 1950 To 2024, Abdul Malik, Sateesh Masabathini, Mohsin Ahmed Shaikh, Qinqin Kong, Muhammad Usman, Dasari Hari Prasad, Ibrahim Hoteit Dec 2026

A Global High-Resolution Comprehensive Heat Indices Dataset From 1950 To 2024, Abdul Malik, Sateesh Masabathini, Mohsin Ahmed Shaikh, Qinqin Kong, Muhammad Usman, Dasari Hari Prasad, Ibrahim Hoteit

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Heatwaves are becoming more intense and frequent as global temperatures rise, affecting vulnerable populations, particularly in low-income communities. Addressing the impacts of heatwaves requires high-resolution data to assess their influence on labour productivity, public health, and climate risk. We introduce the Comprehensive Heat Indices (CHI) dataset, a high-resolution (0.1° × 0.1°) hourly dataset from 1950 to 2024, derived from the ERA5 and ERA5-Land reanalyses. The CHI dataset encompasses thirteen heat stress indices, including wet-bulb temperature, universal thermal climate index, mean radiant temperature, wind chill, and lethal heat stress index (Ls). Thresholds for Ls are empirically linked to mortality, enabling the …

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Quantifying Customer Sentiment For Automobile Brand Perception Analysis Using Machine Learning On Twitter, Sujith Samuel Mathew, Kadhim Hayawi, Neethu Venugopal, May El Barachi Dec 2026

Quantifying Customer Sentiment For Automobile Brand Perception Analysis Using Machine Learning On Twitter, Sujith Samuel Mathew, Kadhim Hayawi, Neethu Venugopal, May El Barachi

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Social networking sites provide a platform for individuals to express their opinions publicly. Brand managers actively use these platforms to gain insights into brand perceptions, as users often share their views on products and services. In this study, we use sentiment analysis to assess customer sentiment towards five leading automobile brands, analyzing text content shared on Twitter(or X). The research models the ’Brand Polarity Score’, which indicates whether customers perceive the brand positively or negatively. This score is further weighted based on the tweet’s influence, characterized by the engagement metrics of the tweet and the author’s follower count. We also …

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Does Self-Efficacy Of Teachers Toward Inclusive Education Differ Between Primary And Secondary School? A Cross-Cultural Study Of Ghana And The United Arab Emirates, Ahmed Mohamed, Maxwell Peprah Opoku, Bernadette M. Guirguis, Ebenezer Mensah Gyimah, Maya Al Yafi, Shouq Alqahtani, Safa Alharthi, Mahra Aldhanhani, Al Zahra Aljaberi Dec 2026

Does Self-Efficacy Of Teachers Toward Inclusive Education Differ Between Primary And Secondary School? A Cross-Cultural Study Of Ghana And The United Arab Emirates, Ahmed Mohamed, Maxwell Peprah Opoku, Bernadette M. Guirguis, Ebenezer Mensah Gyimah, Maya Al Yafi, Shouq Alqahtani, Safa Alharthi, Mahra Aldhanhani, Al Zahra Aljaberi

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There are ongoing debates on the level of education that students with special educational needs could participate in and enjoy as part of their fundamental right to education. There is a notion that students with special educational needs could be more easily included in primary schools than in secondary schools. However, teachers were excluded from such discussions. The current study aims to invigorate such discussion by exploring primary and secondary school teachers' self-efficacy across Ghana and the United Arab Emirates (UAE). a total of 897 teachers were recruited from Ghana and the UAE to rate their self-efficacy via the Teacher …

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Local Government Policies Restricting Unhealthy Outdoor Food Advertising In Australia: Stakeholder Perspectives Identify Political Willingness Is Key To Overcoming Barriers, Alexia Bivoltsis, Frith Klug, Jacinta Francis, Clare Whitton, Gina S.A. Trapp, Claire E. Pulker Dec 2026

Local Government Policies Restricting Unhealthy Outdoor Food Advertising In Australia: Stakeholder Perspectives Identify Political Willingness Is Key To Overcoming Barriers, Alexia Bivoltsis, Frith Klug, Jacinta Francis, Clare Whitton, Gina S.A. Trapp, Claire E. Pulker

Research outputs 2022 to 2026

Background: Unhealthy outdoor food advertising is strongly linked to poor diet, highlighting the need for policies. Western Australian (WA) local governments (LGs) can restrict advertising on their owned infrastructure through their Public Health Plans, but limited policy action has occurred. This study aimed to explore the perspectives of WA LGs and public health organizations (PHOs) on current and potential policies restricting unhealthy outdoor food advertising on LG owned infrastructure to (1) identify barriers and enablers to the policy making process, (2) assess the current level of political willingness (i.e. political want, political can and political must) and (3) inform development …

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A Global Image-Based Data Repository Of Killer Whale Interactions With Elasmobranchs, Emma Luck, Isabella L. Reeves, Maeva Terrapon, Rebecca Wellard, Stephanie K. Venables, Alison V. Towner, Alison A. Kock, Charlotte Hussain, Molly Altschwager, Rosie Ballard, Evans Baudin, Nancy Black, Evan Brodsky, Jade Cantrall, Julio Cardoso, Matt I.D. Carter, Oliver Clarke, Santiago Diaz-Pazmino, David Donnelly, Georgina Cabayol Ferraz, Arlaine Francisco, Laura González García, Mark Jackman, Aimee Jan, Eric Martin, Dane Mcdermott, James Moskito, Blair Ranford, Jesús Erick Higuera Rivas, Jasmin O’Brien, Anton Oleynik, Hernán Orellana-Vásquez, Daniela Alarcón Ruales, Gemma Sharp, Jade Sharp, Alisa Schulman-Janiger, Colleen M. Talty, Paul Tixier, John A. Totterdell, Steve Truluck, Jennah Tucker, Tara Weberg, M. Fernanda Urrutia-Osorio, Machi Yoshida, Jochen R. Zaeschmar, Lauren Meyer Dec 2026

A Global Image-Based Data Repository Of Killer Whale Interactions With Elasmobranchs, Emma Luck, Isabella L. Reeves, Maeva Terrapon, Rebecca Wellard, Stephanie K. Venables, Alison V. Towner, Alison A. Kock, Charlotte Hussain, Molly Altschwager, Rosie Ballard, Evans Baudin, Nancy Black, Evan Brodsky, Jade Cantrall, Julio Cardoso, Matt I.D. Carter, Oliver Clarke, Santiago Diaz-Pazmino, David Donnelly, Georgina Cabayol Ferraz, Arlaine Francisco, Laura González García, Mark Jackman, Aimee Jan, Eric Martin, Dane Mcdermott, James Moskito, Blair Ranford, Jesús Erick Higuera Rivas, Jasmin O’Brien, Anton Oleynik, Hernán Orellana-Vásquez, Daniela Alarcón Ruales, Gemma Sharp, Jade Sharp, Alisa Schulman-Janiger, Colleen M. Talty, Paul Tixier, John A. Totterdell, Steve Truluck, Jennah Tucker, Tara Weberg, M. Fernanda Urrutia-Osorio, Machi Yoshida, Jochen R. Zaeschmar, Lauren Meyer

Research outputs 2022 to 2026

Killer whales (Orcinus orca) are cosmopolitan apex predators that interact with numerous species, including sharks, skates, and rays (subclass Elasmobranchii). Interactions between killer whales and elasmobranchs have garnered attention from the scientific community, but the dynamics of these events are poorly understood, as interactions are often challenging to observe. In this study, we collated imagery of interactions between killer whales and elasmobranchs to create the first image-based repository of interspecific interactions between marine predators. A total of 320 photos and videos from 82 unique interactions were collected from 12 countries. A minimum of 18 elasmobranch species across 16 genera were …

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Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations, Liwan Qi, Bochun Wu, Shoubo Li, Yi Gong, Wei Ni Dec 2026

Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations, Liwan Qi, Bochun Wu, Shoubo Li, Yi Gong, Wei Ni

Research outputs 2022 to 2026

This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of …

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Natural Gas Hydrate Production And Co2 Storage Via Clathrate Hydrates: Challenges And Opportunities, Abdirahman Hassan Mohamed, Aliyu Adebayo Sulaimon, Haylay Tsegab, Bhajan Lal, Stefan Iglauer, Muhammad Ali Dec 2026

Natural Gas Hydrate Production And Co2 Storage Via Clathrate Hydrates: Challenges And Opportunities, Abdirahman Hassan Mohamed, Aliyu Adebayo Sulaimon, Haylay Tsegab, Bhajan Lal, Stefan Iglauer, Muhammad Ali

Research outputs 2022 to 2026

One of the most demanding environmental and economic challenges of this era is that of supplying the increasing global energy demand while reducing and neutralizing the CO2 footprint. In this regard, the provision of a secure and diversified energy supply and the sequestration of CO2 into geological formations are currently of great significance. However, the buoyant nature of CO2 under the temperature and pressure conditions of typical geological sites leads to the risk of CO2 leakage, and thus necessitates long-term monitoring. Therefore, the hydrate-based sequestration of CO2 beneath oceanic sediments has become a desirable alternative to conventional geologic sequestration in …

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Adding A Weight To Constrain The Trunk Increases Knee Joint Kinetics During Sidestep Cutting In Female Athletes, Daniel Kadlec, J. Jordan, Jacqueline Alderson, Sophia Nimphius Dec 2026

Adding A Weight To Constrain The Trunk Increases Knee Joint Kinetics During Sidestep Cutting In Female Athletes, Daniel Kadlec, J. Jordan, Jacqueline Alderson, Sophia Nimphius

Research outputs 2022 to 2026

Sidestep cutting exposes the knee to high multiplanar loads that both challenge tissue capacity and provide an opportunity to develop resilience through progressive exposure. This study investigated task constraints applied at the trunk and preparatory step and changes in lower-body joint kinetics associated with ACL injury risk during sidestepping in female athletes. Twenty-one trained female athletes performed six sidestep conditions: pre-planned and unplanned sidesteps, each with and without trunk (holding ~ 5–7.5% body mass at chest level) and preparatory-step (ducking under an adjustable rope at eye height) constraints. Relative joint power at the hip, knee, and ankle was analysed using …

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Enhanced Carbon Burial In Seagrass Meadows Under Ocean Acidification Revealed By Carbon Dioxide Vents, Theodor Kindeberg, Teixidó, Steeve Comeau, Jean Pierre Gattuso, Beat Gasser, Alice Mirasole, Samir Alliouane, Ioannis Kalaitzakis, Denisa Berbece, Christopher Cornwall, Pere Masque Dec 2026

Enhanced Carbon Burial In Seagrass Meadows Under Ocean Acidification Revealed By Carbon Dioxide Vents, Theodor Kindeberg, Teixidó, Steeve Comeau, Jean Pierre Gattuso, Beat Gasser, Alice Mirasole, Samir Alliouane, Ioannis Kalaitzakis, Denisa Berbece, Christopher Cornwall, Pere Masque

Research outputs 2022 to 2026

Seagrass meadows are natural carbon sinks, yet the effect of ocean acidification on their carbon burial capacity remains poorly understood. Here we investigated natural carbon dioxide vents in Ischia, Italy to assess how seawater pH influences carbon burial in an area dominated by the seagrass Posidonia oceanica. Organic carbon burial rates (mean ± standard error) between 1954 – 2021 were low under ambient conditions (1.5 ± 0.5 g m-2 yr-1) but increased sharply under acidified conditions (7 ± 1 g m-2 yr-1), reaching sevenfold higher values under extreme acidification (10 ± 3 g m-2 yr-1). Stable isotopes suggest that these …

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Robust Hybrid Tree-Based Machine Learning-Assisted Optimization Of Well Parameters To Reduce Asphaltene Precipitation Risk In Oil Fields, Malek Jalilian, Madani, Alireza Keshavarz, Stefan Iglauer, Abbas Khaksar Manshad, Amir H. Mohammadi Dec 2026

Robust Hybrid Tree-Based Machine Learning-Assisted Optimization Of Well Parameters To Reduce Asphaltene Precipitation Risk In Oil Fields, Malek Jalilian, Madani, Alireza Keshavarz, Stefan Iglauer, Abbas Khaksar Manshad, Amir H. Mohammadi

Research outputs 2022 to 2026

Asphaltene precipitation is a persistent flow-assurance issue in carbonate oil wells, leading to increased intervention frequency and production losses. This study utilizes multi-decade surveillance and operational data from a mature carbonate field (1983–2023) to train and optimize five tree-based models: Decision Tree, Random Forest, Extra Trees, Gradient-Boosting Decision Tree, and CatBoost, employing a Tree-Structured Parzen Estimator. These models, constrained by operational parameters, were integrated to identify optimal settings that can minimize the frequency of asphaltene precipitation and the subsequent cleanups. The novelty of this research lies in the direct integration of interpretable tree ensembles with an optimizer that adheres to …

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Bridg-Ics: Ai-Grounded Knowledge Graphs For Intelligent Threat Analytics In Industry 5.0 Cyber-Physical Systems, Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim, Iqbal H. Sarker, Helge Janicke Dec 2026

Bridg-Ics: Ai-Grounded Knowledge Graphs For Intelligent Threat Analytics In Industry 5.0 Cyber-Physical Systems, Padmeswari Nandiya, Ahmad Mohsin, Ahmed Ibrahim, Iqbal H. Sarker, Helge Janicke

Research outputs 2022 to 2026

Industry 5.0’s increasing integration of IT and OT systems is transforming industrial operations but also expanding the cyber–physical attack surface. Industrial Control Systems (ICS) face escalating security challenges as traditional siloed defenses fail to provide coherent, cross-domain threat insights. We present BRIDG-ICS (BRIDge for Industrial Control Systems), an AI-enriched Knowledge Graph (KG) framework for context-aware threat analysis and quantitative assessment of cyber resilience in smart manufacturing environments. BRIDG-ICS fuses heterogeneous industrial and cybersecurity data into an integrated Industrial Security Knowledge Graph linking assets, vulnerabilities, and adversarial behaviors with probabilistic risk metrics (e.g., exploit likelihood, attack cost). This unified graph representation …

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Acute Effects Of Accentuated Eccentric Loading On Mean Concentric Velocity During Resistance Training: A Systematic Review And Meta-Analysis, Jiahao Yang, Tsuyoshi Nagatani, Paul Comfort, Kristina L. Kendall, G. Gregory Haff Dec 2026

Acute Effects Of Accentuated Eccentric Loading On Mean Concentric Velocity During Resistance Training: A Systematic Review And Meta-Analysis, Jiahao Yang, Tsuyoshi Nagatani, Paul Comfort, Kristina L. Kendall, G. Gregory Haff

Research outputs 2022 to 2026

Background: Accentuated eccentric loading (AEL) may acutely enhance the concentric (CON) barbell velocity after the additional eccentric (ECC) load is removed, however there are inconsistent results regarding the effectiveness of this practice within the scientific literature. Objective: The aims of the present study were to: (1) examine the acute effects of applying AEL, only on the first repetition of a set, on mean barbell velocity during the CON phase of the first 3 repetitions of the set and (2) investigate the influence of the magnitude of ECC load, loading differential and exercise selection on the acute effects of AEL. Methods: …

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Examining Teachers’ Attitudes Towards Inclusive Education For All: Development Of A New Scale, Stephan Kielblock, Woodcock, John Ehrich Dec 2026

Examining Teachers’ Attitudes Towards Inclusive Education For All: Development Of A New Scale, Stephan Kielblock, Woodcock, John Ehrich

Research outputs 2022 to 2026

Teachers’ attitudes towards inclusive education are widely recognised as a key indicator of the inclusiveness of classroom environments. However, existing instruments inadequately capture teachers’ mindsets in relation to inclusive education for all learners. This study addresses this gap by developing and validating a new cross-cultural measurement instrument: the Attitudes Towards Inclusion for All scale (ATIFA), in both English (ATIFA-EN) and German (ATIFA-DE). Data were collected from pre-service and in-service teachers in Australia (n = 146) and Germany (n = 238). Exploratory factor analysis and Rasch modelling identified four robust subscales—Philosophy, Practice, Social Inclusion, and Support—with strong psychometric properties. Evidence of …

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Stocks And Fluxes Of Carbon And Nitrogen In Northeastern Brazil Coastal Seascapes, Antoniwal A. Jatobá-Junior, Pere Masque, Carlos Eduardo De Rezende, Vanessa Hatje Dec 2026

Stocks And Fluxes Of Carbon And Nitrogen In Northeastern Brazil Coastal Seascapes, Antoniwal A. Jatobá-Junior, Pere Masque, Carlos Eduardo De Rezende, Vanessa Hatje

Research outputs 2022 to 2026

Quantifying carbon and nitrogen dynamics is essential for understanding the role of coastal ecosystems in climate change mitigation and habitat connectivity. We assessed organic carbon (OC) and total nitrogen (TN) stocks, accumulation rates, and isotopic composition (δ13C and δ15N) in sediment across diverse seascapes in northeastern Brazil, including high- and low-salinity mangroves, a tidal flat, a freshwater marsh, and an inundated forest. OC stocks in the upper meter of sediment were highest in the freshwater marsh (283 ± 64 Mg OC ha−1) and tidal flat (266 ± 27 Mg OC ha−1), and …

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The Impact Of Testing-Parameter Variability On Force Production In The Isometric Single-Leg Long-Lever Bridge: Implications For Training And Testing Rigor In Sporting Environments, Adam E. Sundh, Nicholas J. Ripley, A. J. Lamb, Conor J. Cantwell, Paul Comfort Dec 2026

The Impact Of Testing-Parameter Variability On Force Production In The Isometric Single-Leg Long-Lever Bridge: Implications For Training And Testing Rigor In Sporting Environments, Adam E. Sundh, Nicholas J. Ripley, A. J. Lamb, Conor J. Cantwell, Paul Comfort

Research outputs 2022 to 2026

Background: The aim of this study was to determine the impact of knee angle variability on force production outcomes during the single-leg isometric long-lever bridge, thus providing monitoring guidelines for testing rigor with direct implications for feasibility across a variety of high-performance sporting environments. Methods: Thirty men (age: 19.4 ± 1.3 years; height: 179.8 ± 6.3 cm; body mass: 80.4 ± 10.3 kg) and 14 women (age: 20.0 ± 1.3 years; height: 166.9 ± 7.2 cm; body mass: 64.4 ± 7.4 kg) all of whom were Division 3 athletes with no recent injury history volunteered to participate in the study. …

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Primary Breast Sarcoma In Pediatric, Adolescent, And Young Adult Patients: A Single-Institution Retrospective Review, Amelie D. Perrier Dec 2026

Primary Breast Sarcoma In Pediatric, Adolescent, And Young Adult Patients: A Single-Institution Retrospective Review, Amelie D. Perrier

Summer Research Program Abstracts

No abstract provided.

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The Effects Of Eps Level And Presentation Format Of Analysts’ Forecast Deviation On Non-Professional Investors’ Investment Judgments, Clarence Goh, Prasart Jongjaroenkamol, Poh-Sun Seow Dec 2026

The Effects Of Eps Level And Presentation Format Of Analysts’ Forecast Deviation On Non-Professional Investors’ Investment Judgments, Clarence Goh, Prasart Jongjaroenkamol, Poh-Sun Seow

Research Collection School Of Accountancy

We experimentally investigate how the presentation format of the extent to which a firm's earnings per share (EPS) diverges from analysts' EPS forecasts (i.e. deviation information) and a firm's EPS level affect the investment judgments of non-professional investors (referred to hereafter as “investors”). Our results suggest that investors' investment judgments are more positive when firms with low (high) EPS levels disclose deviation information in percentage (absolute) terms. Furthermore, when the percentage of forecast deviation is held constant, investment judgments are more positive when EPS levels are high versus low if the deviation information is expressed in absolute terms. By contrast, …

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Evaluating The Pulse Of Exercise Programs: Developing And Validating The Intervention Usability Scale For Exercise (Iuse) To Enhance Implementation And Adherence, Anne Inger Mørtvedt, Eva Ageberg, Steven Elmer, Kevin Trewartha, Erich Petushek Dec 2026

Evaluating The Pulse Of Exercise Programs: Developing And Validating The Intervention Usability Scale For Exercise (Iuse) To Enhance Implementation And Adherence, Anne Inger Mørtvedt, Eva Ageberg, Steven Elmer, Kevin Trewartha, Erich Petushek

Michigan Tech Publications

Background: Adherence to exercise interventions is often suboptimal, despite numerous studies documenting barriers and facilitators. Usability may be a critical yet underexplored determinant of adherence. This study aimed to develop and assess the psychometric properties of the Intervention Usability Scale for Exercise (IUSE). Methods: Item generation and content validation involved cognitive interviews and feedback from eight exercise intervention stakeholders and ten target users from the general public. Subsequently, 526 target users from University, Qualtrics and Prolific participant panels assessed exercise programs through an online survey. Dimensionality was assessed using Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA), and bifactor models. …

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Mtorc2-Nav1.2 Signaling Drives Early Hyperexcitability In Alzheimer’S Disease Mouse Model, Nolan M Dvorak, Jeffrey L Noebels Dec 2026

Mtorc2-Nav1.2 Signaling Drives Early Hyperexcitability In Alzheimer’S Disease Mouse Model, Nolan M Dvorak, Jeffrey L Noebels

Faculty, Staff and Students Publications

Hyperexcitability is a biomarker of early-stage Alzheimer’s Disease (AD) and hastens cognitive decline later in its course. Mechanistic target of rapamycin (mTOR) signaling contributes to the slope of this trajectory, as evidenced by early increased brain expression and the rescue of hyperexcitability by genetic deletion of mTOR complex 2 (mTORC2); however, a molecular mechanism directly linking mTOR signaling to membrane hyperexcitability in early-stage AD remains elusive. Here, we show that hyperactive mTOR signaling stimulates the voltage-gated Na+ channel 1.2 (Nav1.2), a previously identified downstream phosphorylation target of mTORC2 and a key regulator of membrane electrogenesis. Augmented Nav1.2 channel function induced …

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Long-Term Analysis Of Pm2.5 Elemental Composition And Source Contributions In Coastal Urban Environments Of Corpus Christi And Houston In Texas, Sai Deepak Pinakana, Jeremy A. Sarnat, Amit U. Raysoni Dec 2026

Long-Term Analysis Of Pm2.5 Elemental Composition And Source Contributions In Coastal Urban Environments Of Corpus Christi And Houston In Texas, Sai Deepak Pinakana, Jeremy A. Sarnat, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Long-term assessments of fine particulate matter play a key role in identifying persistent and emerging emission contributors. Coastal urban areas are highly susceptible to transboundary dust and wildfire events in addition to local pollution sources. Multi-decadal assessments in these regions using chemical speciation data could offer insights into major pollutant sources and their trends. This study utilizes nearly two decades of PM2.5 elemental composition data at two major coastal cities in Texas: Houston and Corpus Christi. Fourteen trace elements were analyzed to characterize the seasonal variability and long-term source evolution using a combination of Spearman’s correlation analysis, principal component analysis, …

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Impact Of School Nurse Education On Factors Influencing Hpv Vaccine Communication With Parents, Jihye Choi, Efrat K Gabay, Jeanette Deason, Elizabeth Baumler, Diane Santa Maria, Daisy Mullassery, Lara S Savas, Erika Thompson, Sanghamitra M Misra, Paula M Cuccaro Dec 2026

Impact Of School Nurse Education On Factors Influencing Hpv Vaccine Communication With Parents, Jihye Choi, Efrat K Gabay, Jeanette Deason, Elizabeth Baumler, Diane Santa Maria, Daisy Mullassery, Lara S Savas, Erika Thompson, Sanghamitra M Misra, Paula M Cuccaro

Faculty, Staff and Student Publications

Human papillomavirus (HPV) can cause six cancer types but can be prevented with timely vaccination in early adolescence. However, despite the wide availability of the HPV vaccine, uptake remains suboptimal among US adolescents. School nurses are invaluable resources to students and their families regarding adolescent immunization needs. As part of the All for Them vaccination program, we assessed the impact of the continued nurse education (CNE) intervention on school nurses’ HPV vaccine communication with parents. Seventy-two school nurses and nurse administrators in Texas participated in the study. Using a single-arm study design, we measured participants’ potential barriers to and self-efficacy …

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Artificial Intelligence (Ai) For Social Innovation In Health Education: Promoting Health Literacy Through Personalized Ai-Driven Learning Tools – A Systematic Review, Dina Mansour Tbaishat, Maha Waleed Elfadel Dec 2026

Artificial Intelligence (Ai) For Social Innovation In Health Education: Promoting Health Literacy Through Personalized Ai-Driven Learning Tools – A Systematic Review, Dina Mansour Tbaishat, Maha Waleed Elfadel

All Works

Background: Artificial Intelligence (AI) is transforming health education by enabling personalized, adaptive, and scalable approaches that may enhance aspects of health literacy. Despite rapid adoption, comprehensive synthesis of AI tools’ impact on health literacy as social innovation is limited. Understanding these effects guides educators, developers, and policymakers in designing potentially effective, inclusive, and ethical AI interventions. This review examines generative AI models, chatbots, and adaptive learning systems in supporting health literacy globally. Methods: A systematic review was conducted following PRISMA guidelines. Literature was identified primarily through PubMed/Medline, Scopus, and ScienceDirect. Connectedpapers.com was used exclusively as a citation chasing tool, performing …

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A Performance-Optimized V2v Task Offloading Framework For Real-Time Vehicular Communication, Tariq Qayyum, Asadullah Tariq, Ikbal Taleb, Mohamed Adel Serhani, Zouheir Trabelsi Dec 2026

A Performance-Optimized V2v Task Offloading Framework For Real-Time Vehicular Communication, Tariq Qayyum, Asadullah Tariq, Ikbal Taleb, Mohamed Adel Serhani, Zouheir Trabelsi

All Works

As vehicular applications become increasingly complex, their computational demands often exceed the capabilities of individual vehicles. Vehicular Edge Computing (VEC) alleviates this limitation by enabling task delegation to nearby edge resources; however, high mobility, dynamic topology, and fluctuating vehicle density make real-time offloading decisions challenging. To address these issues, we propose a performance-optimized Vehicle-to-Vehicle (V2V) task offloading framework for dense and dynamic Vehicular Ad-hoc Networks (VANETs). The framework follows a two-stage design: (i) context-aware edge-node selection based on live topology capture via periodic beaconing, and (ii) cumulative score-based dynamic priority queuing at the selected edge node. The priority score jointly …

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An Advanced Healthcare System With An Automated Vit Model For Dermoscopic Skin Cancer Identification, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi Dec 2026

An Advanced Healthcare System With An Automated Vit Model For Dermoscopic Skin Cancer Identification, Ahed Abugabah, Prashant Kumar Shukla, Suchi Mishra, Abhishek Dwivedi

All Works

Early and reliable diagnosis of skin cancer from dermoscopic images remains challenging due to class imbalance, subtle inter-class variations, lesion boundary ambiguity, and illumination inconsistency, which can degrade the robustness of conventional convolutional neural networks (CNNs). To address these limitations, this study proposes an automated smart healthcare framework for dermoscopic skin cancer diagnosis using an Enhanced Vision Transformer (E-ViT) that improves global-context modeling through self-attention while strengthening fine-grained lesion representation learning. Unlike standard ViT configurations, the proposed architecture integrates multi-scale patch embedding and attention refinement to better capture border irregularities and color–texture heterogeneity that are critical for melanoma discrimination. Furthermore, …

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Fig-Gan: Fundus Image Generation Via Deep Learning Based Generative Adversarial Network For Amd Disease Diagnosis, Kailasa Thrishul, Ahed Abugabah, Amina Salhi, Manel Ayadi, Mohamed M. Sithik, D. Jayaprakash, A. Ahilan Dec 2026

Fig-Gan: Fundus Image Generation Via Deep Learning Based Generative Adversarial Network For Amd Disease Diagnosis, Kailasa Thrishul, Ahed Abugabah, Amina Salhi, Manel Ayadi, Mohamed M. Sithik, D. Jayaprakash, A. Ahilan

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Globally, age-related macular degeneration (AMD) remains a main cause of irreversible vision loss. Recently, deep learning models have primarily focused on classifying fundus images for early detection of AMD progression. However, existing models rarely address the generation of future progression-aware fundus images, particularly when complete real longitudinal follow-up scans are unavailable. This limitation makes it difficult to track retinal changes over time and highlights the need for generative models capable of producing realistic drusen-level structural variations. To address these issues, a novel deep learning-based FIG-GAN model is to generate synthetic future fundus images from baseline inputs. Multi-Attention U-Net (MAU-Net) is …

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