Exploring The Views Of Children With Cerebral Palsy, Their Parents And Physiotherapists On Participating In A Feasibility Randomised Controlled Trial Testing An Exergaming Device: A Qualitative Study, Rachel Rapson, Jos M. Latour, Jonathan Marsden, Bernie Carter

School of Nursing and Midwifery

Background: This study aimed to understand the experiences and views of children with cerebral palsy, their parents and physiotherapists participating in the ACCEPT feasibility randomised controlled trial, which explored a 10-week physiotherapy intervention using an interactive gaming training device. Design: Qualitative methods included semi-structured interviews, e-diary and photographs. Nine parent–child dyads and three physiotherapists participated. Children were aged between 7 and 16 years; four had co-existing additional needs. Interviews were transcribed. Reflexive thematic analysis was used. Results: Five themes covered the breadth of participants’ experiences: (1) Fitting in therapy; (2) Motivation; (3) New opportunities; (4) Physiotherapists out of their comfort …

Job Satisfaction, Burnout, And Intent To Stay In Neonatal Nursing In England And Wales: A Cross-Sectional Survey Study, Kathy Chant, Yoko Nishimura, Aviva Petrie, Jos M. Latour, Nicola Booth, Kelly Crofts, Lisa Viola, Katie Gallagher

School of Nursing and Midwifery

Objective: To explore job satisfaction, burnout and intent to stay in neonatal nurses in England and Wales. Methods: A cross-sectional online survey study using the McCloskey Mueller Satisfaction Scale (MMSS) to explore job satisfaction, the Copenhagen Burnout Inventory (CBI) to explore burnout and the Nurse Retention Index (NRI) to measure intent to stay. All neonatal nurses working in England and Wales were eligible to take part. Data were collected between February and September 2024. Results: A total of 1590 neonatal nurses completed the survey. Job satisfaction was neutral. Moderate work burnout was reported, with statistically significant differences in mean score …

Democratizing Restitution: Trust As An Equitable Approach To Competing Claims On Cultural Heritage Objects, Britta Redwood

Articles

As formerly colonized states began to win their independence in the mid-twentieth century, a growing chorus of voices called on museums in London, Paris, Berlin, and other European cities to return objects taken during the colonial period. Having largely ignored these requests until recently, museums throughout Europe and the United States have begun negotiating returns of these objects to their rightful owners. There is a growing recognition among Western cultural institutions that continuing to hold cultural heritage objects taken under conditions of coercion or violence is morally untenable. More recently, some scholars have argued for a human rights approach to …

Regulating Robotaxis, Bryant Walker Smith, Matthew T. Wansley

Articles

In several sunbelt cities, commercial robotaxi service has arrived. The leading robotaxi company is providing over 400,000 trips per week. The industry claims that robotaxis will save lives and provide convenient and affordable mobility. Critics counter that they will increase congestion, undermine transit, and subject the public to ubiquitous surveillance. We argue that the social impact of robotaxis depends on how they are regulated. We emphasize two points missing from the debate. First, some of the benefits of robotaxis may be political rather than technological—some longstanding public policy goals may become viable in a robotaxi world. Second, letting one private …

Standard Textualism, James A. Macleod

Articles

For as long as legal scholars have been writing about the rules-versus-standards distinction, textualism has been understood to produce characteristically rule-like law. This Article argues for the opposite view. Far from generating the “law of rules” that Scalia famously envisioned, the rule of modern textualism produces a law of standards—much more so than anybody, proponent of textualism or critic, appears to have recognized.

Two aspects of today’s textualism produce this result. The first is its emphasis on ordinary language and communication. Modern textualism typically produces standards because ordinary language and communication are typically standard-like. The second is modern textualism’s drive …

The Effects Of Financing Green And Brown Sectors: What Do Theories And Evidence Say?, Hao Liang, Maria Teresa Punzi

Research Collection Lee Kong Chian School Of Business

This paper critically examines the economic and welfare implications of financing green and brown sectors. Drawing on a comprehensive review of recent theoretical and empirical literature, we highlight that while conventional green finance—allocating capital toward environmentally friendly (“green”) sectors and away from carbon-intensive (“brown”) sectors—can promote decarbonization, it may also produce unintended externalities. In particular, it can inadvertently incentivize higher emissions from brown firms and contribute to economic disruption. Using a dynamic stochastic general equilibrium (DSGE) model, we demonstrate that lowering the cost of capital for green sectors leads to only modest reductions in emissions, whereas raising it for brown …

Humanizing The Base Of The Pyramid: Exploring The Influence Of Resource (Dis)Advantages On Value Creation, Ted London, Lisa Jones Christensen, Tyson Mackey, Alison Mackey, Heather Esper, Andrew Grogan-Kaylor

Faculty Publications

Base of the pyramid (BoP) scholarship emphasizes the potential for enterprises to generate profits by enhancing the wellbeing of the impoverished, often by selling socially-beneficial products (SBPs). Yet, many such BoP enterprises have experienced mixed results. We argue that this may stem from insufficient attention to how BoP consumers value SBPs and other products. We frame SBPs as a type of human capital investment and thus use human capital theory to study how the consumption of SBPs does or does not create value for consumers. Specifically, we use a novel data set from rural India to measure value creation in …

Longitudinal Associations And Interactions Of Adolescent Religious Deidentification And Parental Sanctification On Parent-Adolescent Relationships, Justin Hendricks, Sam A. Hardy, Michael A. Goodman, Emily De Schweintiz Taylor

Faculty Publications

In many religious families, shared religious identity is a strong source of intergenerational solidarity. However, when adolescents deidentify from their family faith, normative parent-adolescent conflict, which heightens in mid-adolescence and normally subsides in late-adolescence, may intensify and damage parent-adolescent social cohesion. Many religious parents view parenting relationships as sanctified, which typically leads to adaptive parenting, but in the context of deidentification may lead to greater distress. To understand how adolescent religious deidentification influences parentadolescent relationships, we examined the longitudinal associations and interactions of adolescent children’s religious deidentification and parental sanctification on parent-child religious conflict and parental warmth (N = 1,391 …

Developmental Themes Associated With Religious Activity After Early Return From A Latter-Day Saint Mission, Samuel E. Hancock, Sam A. Hardy, Michael Goodman, Camron Angell, Jenae M. Nelson

Faculty Publications

In the Church of Jesus Christ of Latter-day Saints, qualified young men are expected (and young women are given the option) to complete extended missionary service during the transition to adulthood. Some youth end their missionary service short of the anticipated duration, which is associated with markedly lower rates of religious activity post-return. This study is a qualitative inquiry into the developmental themes associated with early returned missionaries from the Church of Jesus Christ of Latter-day Saints who chose to remain active (be consistently involved with the church), sampling from areas with high rates of Latter-day Saint activity, where stigmatization …

The Role Of Silence In Symbolic Management, W. Chad Carlos, Ben W. Lewis

Faculty Publications

Symbolic management research examines how organizations shape external evaluations by making symbolic claims. A central concept in this literature is decoupling, which distinguishes symbolic claims from their substantive implementation. This work is grounded in the assumption that symbolic visibility is generally beneficial, leading organizations to make symbolic claims regardless of practice. Yet a growing set of cases challenge this assumption by documenting an inverse pattern in which organizations substantively implement practices while remaining symbolically silent. This absence of symbolic claims runs counter to prevailing theoretical expectations regarding the reputational value of symbolic action. In this paper, we address this theoretical …

An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare

Mansoura Engineering Journal

The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …

A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour

Mansoura Engineering Journal

This study proposes a machine learning–based framework that applies machine learning techniques to improve the efficiency of 5G network slicing through automated traffic classification and threshold-based load management . The proposed model optimizes resource allocation among the three standardized 5G slice types: enhanced Mobile Broadband (eMBB), ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). Two supervised learning algorithms—K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)—are trained using Quality of Service (QoS) parameters such as packet delay, loss rate, and Quality Class Identifier (QCI). Experimental evaluations were conducted on two large-scale datasets containing over 400,000 traffic instances, demonstrating that the …

Edge Guided Channel Attention In Fsrcnn: A Novel Approach For Depth Super Resolution, Yagneshkumar Jayantilal Parmar, Paresh M. Dholakia

Mansoura Engineering Journal

Depth images from low-cost sensors often suffer from blurred edges and structural distortions when processed with standard super-resolution models. While FSRCNN is efficient for RGB images, it struggles to handle the unique geometric requirements of depth maps. To solve this, we propose the Edge Guided Channel Attention FSRCNN (EGCA FSRCNN). This method incorporates an edge-guided modulation mechanism to preserve object boundaries and a Squeeze and Excitation (SE) block to focus on critical structural features. A major benefit of this framework is the use of frozen, pretrained FSRCNN weights, which bypasses the requirement for retraining. Our evaluation on the UTKinect, Middlebury, …

Intelligent Audio‑To‑Indian Sign‑Language And Sign‑To‑Audio Translation System Using Mediapipe, Tensorflow, Whisper And Google Tts, N. Pothanna, T. Kusuma, S. Haindavi, T. Sreeja, Shaik Shaheem Taj

Mansoura Engineering Journal

Communication barriers between the Deaf community and the general public remain a persistent challenge, particularly in multilingual settings where Indian Sign Language (ISL) is the primary mode of interaction. We propose a real-time bidirectional translation framework integrating MediaPipe for hand landmark extraction, a Convolutional Neural Network (CNN) classifier built with TensorFlow/Keras for gesture recognition, OpenAI Whisper for robust multilingual speech-to-text transcription, and Google TTS for naturalistic speech synthesis. The system achieves 93% classification accuracy across 35 ISL classes (alphabets A–Z and numerals 1–9) on a dataset of 42,700 images, with macro and weighted F1-scores of 0.93. Deployed as a Flask …

Code-Net++: An Attention-Guided Deep Learning Framework With Grad-Cam-Based Explainability For Covid-19 Detection Using Chest X-Ray Images, Fareesa Amina, Dr Krishnanaik Vankdoth

Mansoura Engineering Journal

Chest radiograph imaging has emerged as a practical and scalable diagnostic modality for respiratory diseases, including COVID-19. However, accurate discrimination of COVID-19 manifestations from other pulmonary abnormalities remains challenging because of low contrast, imaging noise, and overlapping radiographic patterns. This work presents CODE-NET++, an enhanced attention-guided deep learning framework with Grad-CAM-based explainability for reliable COVID-19 detection using chest X-ray images. The proposed framework integrates adaptive trilateral filtering for image enhancement, Reverse Edge Attention Network (RE-Net) for lesion-aware segmentation, and an Enhanced LinkNet architecture with dilated convolutions for multiscale feature extraction and classification. Grad-CAM-based explainable artificial intelligence visualization is incorporated to …

A Hybrid Object Detection And Temporal Attention Framework For Intelligent Video Surveillance, Sudheer Reddy Bandi, Eswari Vanaparthi, Yakshini Edapalli, Roshan Kavuri

Mansoura Engineering Journal

The rapid growth of urban areas has greatly heightened the need for smart video surveillance systems that can automatically process extensive amounts of CCTV footage. Traditional surveillance methods largely depend on human monitoring, which is not only inefficient but also susceptible to human mistakes, especially in intricate and crowded environments. To tackle these issues, this paper introduces a combined object detection and temporal attention for intelligent video surveillance that concurrently analyzes spatial and temporal data from video streams. The proposed system analyzes real-time CCTV footage utilising a multi-pathway frame extraction technique that includes slow, fast, and full-frame sampling to capture …

Explainable Multi-Horizon Wind Power Forecasting Via Aquila-Optimized Machine Learning Models, Mostafa A. Abdelnaby, Nahla B. Abdel-Hamid, Eman M. El-Gendy, Mahmoud M. Saafan

Mansoura Engineering Journal

The inherently unpredictable nature of wind energy necessitates the development of sophisticated forecasting models to ensure grid stability and optimal distribution. In this research, we propose a novel and systematic approach to wind power forecasting (WPF) across diverse timescales. This approach leverages the power of various machine learning (ML) models, metaheuristic hyperparameter optimization, and utilizes explainable artificial intelligence (XAI). The developed methodology is based on the Aquila optimizer (AO), capable of automatically adjusting different ML models for four different time periods (30 minutes, 6 hours, 24 hours, and 36 hours) on the data collected from the Gabal El-Zayt wind power …

A Novel Superaug Adaptive Data Augmentation Strategy For Metabolic Syndrome Prediction: The First Egyptian National Cohort Study With Multi-National Comparison, Nihal Elsonny, Ashraf Elsharkawy, Abeer Tawakol, Amira Y. Haikal

Mansoura Engineering Journal

Metabolic Syndrome (MetS) is a multifactorial disorder associated with an increased risk of cardiovascular disease, type 2 diabetes, and obesity-related complications. Early and accurate prediction of MetS remains challenging due to heterogeneous data sources, class imbalance, limited sample sizes in regional studies, and poor generalization across populations.

This study introduces a comprehensive machine learning framework for predicting MetS and its prognostic factors using two heterogeneous datasets: a newly collected Egyptian clinical cohort and the U.S.-based (NHANES) [CDC, 2023] dataset. For each dataset, multiple experimental pipelines are developed, integrating preprocessing, feature selection, data augmentation, hyperparameter tuning, and ensemble modeling. …

State-Dependent Queueing For Adaptive Signal Control: A Simulation-Based Performance Evaluation, Shaimaa Alseddiek, Usama Elrawy Shahdah, Hala B. Nafea, Hossam El-Din Moustafa, El-Said Ahmed Marzouk, Mohamed M. Ashour

Mansoura Engineering Journal

Urban traffic congestion persists as a critical challenge to transportation system efficiency, sustainability, and safety. Traditional queuing models utilizing fixed service rates inadequately represent the dynamic feedback between congestion and capacity in real vehicular flow. State-Dependent Queuing Models (SDQMs) address this limitation by modelling service rate as a function of queue length or density. This research advances SDQM application for adaptive traffic signal control through development of a calibrated state-dependent departure rate implemented within a microscopic simulation environment using SUMO and TraCI. Six control strategies including fixed-time, actuated, and two SDQM variants were evaluated across traffic demands ranging from undersaturated …

Psychological Impact Of Cultural Heritage Vr Experience Using Well-Mind Framework. (Case Study: Mahmoud Sami Palace In Mansoura)., Sara Ahmed El-Bayoumi, Hager Ahmed El-Sayed El-Ayouti, Mohamed Mohamed Shawki Abo Leila

Mansoura Engineering Journal

This study examines the psychological effects of immersive virtual reality (VR) experiences designed to preserve and disseminate intangible cultural heritage. It addresses the growing challenge of declining cultural engagement and the need for innovative tools that support psychological well-being, emotional engagement, and cultural connection. A VR-based reconstruction was developed within the historic Mahmoud Sami Al-Baroudi Palace in Mansoura, Egypt, focusing on traditional Egyptian practices and oral storytelling. The evaluation employed the WELL-MIND framework alongside participant feedback to assess both structured well-being indicators and subjective user experiences. The WELL-MIND-based assessment indicated improvements in cognitive stimulation, emotional engagement, and environmental perception. In …

Construction-Phase Leed Compliance In Egypt: Development Of A Rule-Based Expert System For Contractor Decision Support, Mohamed R. Ahmed, Atef A. Ragab, Sameh Y. Mahfouz

Mansoura Engineering Journal

This study develops a rule-based expert system implemented in Python to support contractors in achieving LEED BD+C: New Construction v4 certification during the construction phase in Egypt. The research identifies and validates construction-phase obstacles affecting LEED compliance through a structured questionnaire targeting building contractors in Egypt. The questionnaire process was conducted in two stages: a pilot survey was used to screen and refine the initially identified obstacles, while the main survey was used to validate the practical relevance of the retained obstacles within the Egyptian construction context. In parallel, the study analyzes construction-phase prerequisites and credits relevant to contractors through …

Data Collection Algorithm Based On Regression Analysis, Aiming To Minimize Data Processing Delays In 6g-Enabled Iot Networks, Archana Rajendra Mane, Sachin Vasant Chaudhari

Mansoura Engineering Journal

Researchers are currently investigating 6G wireless communication technologies because they can offer ultra-low latency, high data rates, and smarter network management than 5G. IoT services have spurred the development of cutting-edge technologies such as quantum communications, terahertz (THz), and artificial intelligence (AI), all of which are expected to be included into the subsequent generation of 6G networks. This paper presents a regression-based data collection algorithm for 6G-enabled IoT networks that dynamically prioritizes data through Random Forest regression. With a Mean Absolute Error (MAE) of 0.62 ms and a Root Mean Squared Error (RMSE) of 0.83 ms, the proposed method can …

Experimental Investigation And Optimization Of Process Parameters Affecting The Compressive And Flexural Strength Of Epoxy Concrete For Machine Tool Structure By Using Taguchi Method, Amitkumar C Gohil, Hardik G. Chothani

Mansoura Engineering Journal

The structural performance of machine tool is strongly influenced by rigidity and damping characteristic; however, conventional material such as grey cast iron and steel exhibits limitation in achieving an optimal balance between weight, strength and vibration damping. The necessitates the development of alternative material with improved performance. In this study epoxy concrete is investigated as a potential material for machine tool structure, focusing on its compressive strength and flexural strength. A systematic experimental approach based on Taguchi method (L25 orthogonal array) was employed to optimize key process parameter, including resin contain, aggregate size, sand proportion, shaking time and curing duration. …

Event-Related Potential Variation In Response Accuracy: A Comparative Analysis Using Mne-Python, Akash Rajak, Sachin Umrao

Mansoura Engineering Journal

Event-Related Potentials (ERPs) are extensively employed in the examination of neural responses linked with cognitive processing and changes in brain activity. In this work, we conducted a comparative analysis of ERPs on a publicly available EEG dataset (122 subjects, alcoholic and control groups) with the help of the MNE-Python framework. The 64 electrodes for EEG were placed according to the international 10 - 20 system, and EEG was sampled at a 256 Hz sampling rate over 1-second epochs. The preprocessing pipeline consisted of 1 - 40 Hz bandpass filtering, noise reduction, spectral computation, and ERP waveform analysis. Temporal neural activity …

Effect Of Load Variations On Power Quality And Ev Battery Performance In Vehicle-To-Grid System, Jitender Kaushal, Rahul Paswan

Mansoura Engineering Journal

Vehicle-to-Grid (V2G) technology enables the exchange of electricity between electric vehicles (EVs) and the utility grid, helping improve the integration of renewable energy sources and the grid's flexibility. Load-dependent power quality disturbances can affect the performance and reliability of V2G systems, which in turn can negatively impact system and battery operation. This study investigates the effect of resistive, inductive and nonlinear loads on the electrical performance and battery behaviour of a bidirectional V2G system. A complete MATLAB/Simulink model was developed to investigate the grid voltage, current, frequency, THD and the battery voltage, current and state of charge. The model uses …

Working Mule Or Sacrificial Lamb: Examining Agrarian Backlash And Populism In Rural Europe, Ava Elaine Rumsey

Honors College Theses

This thesis examines to what extent populism has become a political force across rural and agrarian communities in the European Union from 2023 to 2026. It distinguishes between ‘structural’ shifts, meaning the broader transformations in agrarian political economy, and ‘policy’ shifts, meaning the cumulative impact of Common Agricultural Policy (CAP) reform, notably its welfarist and regulatory priorities. This study draws on two types of evidence. First, it pulls from a wide range of secondary sources on the CAP and agrarian political transformation. Second, it analyzes the position papers, statements, and digital media of three organizations that represent important farming constituencies …

Fluency And Elaboration In Dolphin Object Play: Evidence For Creativity In Behavioral Exchanges?, Abigail H. Adams, Manon Themelin, Heather Manitzas Hill, Deirdre Yeater, Rachel Walker, Amy C. Hirons, Kathleen M. Dudzinski

Psychology Faculty Publications

Innovative behaviors in non-human animals have been proposed as indicators of flexible thinking. Although dolphins have demonstrated creativity under stimulus control, these paradigms relied on human-directed tasks and may have overlooked spontaneous expression. This study evaluated whether object play, an unprompted behavior, could serve as a proxy for dolphin creativity by examining object play in bottlenose dolphins (Tursiops truncatus) in managed care and wild Atlantic spotted dolphins (Stenella frontalis). Video data were coded for object play events and analyzed for fluency (behavioral diversity and frequency) and elaboration (sequential organization), with consideration of object type and social context. In managed care, …

Making Room For ‘Feelings’: What's At Stake For The Theory Of Practice Architectures?, George Variyan, Brad Gobby

Research outputs 2022 to 2026

This paper responds to Thelin, K. [2024. What about feelings? Elaboration on and consideration of the theoretical construct of emotions in practice and practice architectures. International Journal of Leadership in Education, 1–14] intriguing proposal that the theory of practice architectures (hereafter TPA) would benefit from an augmentation to its oft-repeated analytical mantra of ‘sayings, doings and relatings’ by adding the notion of feelings. Thelin's work is motivated by the increasing realisation amongst adherents that TPA has thus far been relatively silent on how emotions mediate practice. As such, there are ongoing efforts to think through the place of emotions in …

Push Dose Vasopressors For The Treatment Of Hypotension, Jennifer Ann Dailey

Doctor of Nursing Practice (DNP) Scholarly Projects

Millions of Americans experience life-threatening hypotension. Prolonged hypotension results in acute kidney injury, myocardial injury, even cardiac arrest, and is associated with increased morbidity and mortality (Khanna et al., 2019; Schuurmans et al., 2024; Singer et al., 2022). Hypotension and its associated complications result in higher hospital costs (Keuffel et al., 2018). While there is a high incidence of hypotension among ICU patients, a smaller percentage of patients require vasopressor infusions regionally and nationally (Moin et al., 2025; Pollard et al., 2019). Local data from a community hospital within a North Texas suburb demonstrates a larger percentage of ICU patients …

Schools, Space And Atmospheres: The Value Of Student Videos In Negotiating Contested Spaces In New Urban Vertical Schools, Prue Miles, Kylie Boltin, Stuart Poyntz, Jill Willis

Research outputs 2022 to 2026

Voices of young people are essential in civic discourse about thriving futures. Yet dialogue can be complicated when the experiences of adults and young people are vastly different, for example in school spaces designed by adults in cities designed for adults. Vertical, highrise inner city schools represent this intersection. A new genre of school in Australia, vertical schools symbolise aspirations for young people and livable cities as designed by adults. This paper draws from data collected in the Thriving in Vertical Schools project to explore the importance of affective learning atmospheres for students, and the value of digital stories to …