Digital Commons Network^™

Performance Assessment And Design Improvements For An Urban Coastal Detention Basin Under Intensifying Rainfall Extremes, Imiya Mudiyanselage Chathuranika, Agyare Asante, Faeghe Borhani, Xixi Wang, Mujde Erten-Unal, Dalya Ismael

Civil & Environmental Engineering Faculty Publications

Coastal urban areas are increasingly exposed to flooding driven by more frequent and intense rainfall events, rising sea levels, and expanding impervious surfaces. Norfolk, Virginia, a low-lying coastal city with aging stormwater infrastructure, faces heightened vulnerability to these hydrologic pressures. This study evaluates the hydraulic performance of an existing urban detention basin within the Edgewater–Larchmont catchment under 10-, 50-, and 100-year, 2-h design storms using the U.S. Environmental Protection Agency’s Storm Water Management Model (SWMM). Simulations were conducted for both pre- and post-development conditions to assess changes in peak discharge, storage capacity, and water level dynamics. Results show that urbanization, …

Optimizing Maintenance Routes For Highway Infrastructure Using Leader-Follower Autonomous Vehicles, Qing Tang, Chenxi Chen, Xianbiao Hu, Yuxin Ding, Tianjia Yang

Civil & Environmental Engineering Faculty Publications

The Autonomous Truck Mounted Attenuator (ATMA), a leader–follower style connected and automated vehicle system, enhances safety during transportation infrastructure maintenance in work zones. However, the significantly lower speed of ATMA, compared to regular vehicles, causes moving bottlenecks that reduce roadway capacity and prolong queuing, leading to further delays. Different ATMA routes lead to varying patterns of time-dependent capacity drop, affecting the user equilibrium traffic assignment and resulting in differing system costs. This study aims to optimize ATMA routing within a network to minimize the system cost associated with its slow-moving operation. To this end, a queuing-based traffic assignment approach is …

Iuse: A Gamified Virtual Learning Platform For Connected Vehicle Applications To Enhance Undergraduate Transportation Education, Tianyu Shen, Di Yang, Kai Sun, Hong Yang, Kun Xie, Mansoureh Jeihani

Civil & Environmental Engineering Faculty Publications

Emerging transportation technologies are rapidly reshaping transportation systems and industry practice. However, most transportation undergraduate curricula still emphasize foundational topics such as geometric design, travel demand forecasting, pavements, and soil properties, typically delivered through lecture-centric instruction. While these subjects remain essential to the discipline, they do not fully reflect the pace of technological change or provide sufficient opportunities for experiential learning with modern tools and data. This gap limits students’ exposure to CV concepts and their ability to translate theory into practice.

Focusing on a key emerging technology, connected vehicles (CVs), this paper bridges the above gap by introducing a …

Good Forestry In The Granite State - 3rd Edition, Cooperative Extension

UNH Cooperative Extension

No abstract provided.

Lung Inflammation From Daily Exposure To Airborne Particulate Matter In A Trade School, Kynda Tinawi, Céline Plante, Alan Da Silveira Fleck, Édith Giasson, Isabelle Valois, Caroline Couture, Eva Suarthana, Maximilien Debia, Audrey Smargiassi

Études primaires

Background Workers are exposed daily to various airborne chemical agents, however, associations between daily exposures to particulate matter and lung inflammation in occupational settings have been little explored. Objective To estimate the association between daily occupational exposure to respirable (PM4 and PM2.5), ultrafine particles, their oxidative potential, and fractional exhaled nitric oxide within apprentices in a school of construction trades. Methods We used a repeated measures design over 5 consecutive days in 56 apprentices from 3 construction trade sectors (bricklaying, welding, and carpentry). Fractional exhaled nitric oxide was measured each day post-work. Personal and work area daily PM4 were collected …

Early Drowsiness Detection Via Second-Order Derivative Analysis Of Heart Rate Variability: A Non-Contact Ecg Approach With Machine Learning, Fabrice Vaussenat, Abhiroop Bhattacharya, Julie Payette, Alireza Saidi, Victor Bellemin, Geordi-Gabriel Renaud-Dumoulin, Sylvain G. Cloutier, Ghislain Gagnon

Études primaires

Drowsy driving contributes to roughly 20% of traffic fatalities, yet most detection systems rely on behavioral cues that appear only after impairment has set in. Here we ask whether first and second derivatives of heart rate variability (HRV) can detect pre-crash states earlier than conventional approaches. Twenty-five participants completed 49 driving simulator sessions while we recorded cardiac activity through capacitive ECG electrodes embedded in the seat backrest—a non-contact method that avoids the privacy concerns of camera-based monitoring. To prevent circular evaluation, ground truth labels were based solely on crash proximity rather than HRV-derived scores. The combined HRV feature set (conventional …

If Only Pickups And Vans Could Fly: Vehicle Maintenance And The Challenge Of Safely Lifting Large Vehicles On A Two-Post Lift, Damien Burlet-Vienney, Sylvie Beaugrand, Maud Gonella, Bertrand Galy, Élise Ledoux

Études primaires

The use of automotive lifts requires mechanics to work under or near a multi-ton load. Based on consultation with stakeholders, pickups and vans appear to pose problems when raised using two-post above-ground lifts (2PAG lifts), the most common type of automotive lift in garages. The aim of this study is therefore to highlight the work activity performed by mechanics when raising pickups and vans on 2PAG lifts and to describe the factors they take into account to ensure vehicle stability. Data collection took place under actual conditions in five garages. A total of 108 lifting situations were filmed and analyzed, …

Managing Complexity: Manager-Stakeholder Communication, Relational Dynamics, And The Dual Nature Of Rtw Communication, H. Bertolini, Marc Corbière, Alessia Negrini, Nadine Larivière, Patrizia Villotti, Dominic Prévost, Meryl Caiada, Jason Amorim, Fergal O'Hagan

Études primaires

Purpose

The return to work (RTW) process of worker absent due to common mental disorders (CMD) or musculoskeletal disorders (MSD) represents a complex challenge that involves multiple stakeholders. The aim of this study was to examine how managers perceive the factors that facilitate or hinder communication with other stakeholders during the RTW process.

This qualitative study was based on four focus groups conducted in Canada (Quebec and Ontario) with 18 managers.

Thematic analysis identified five themes related to facilitators and seven themes related to communication obstacles. Among the main facilitators, trust, clarity, and collaboration emerged as key elements …

Occupational Exposure To Pesticides Increases The Risk Of Amyotrophyc Lateral Sclerosis: A Systematic Review And Meta-Analysis, France Labrèche, Pamela Prudhomme, Maryse Gagnon, Nicolas Dupré, Sabrina Gravel

Études primaires

Objective To systematically review the evidence on the association between occupational exposure to pesticides and the risk of amyotrophic lateral sclerosis (ALS).

Methods A systematic search, conducted in eight bibliographic databases for publications between 1990 and 2025, identified observational studies estimating the risk of ALS after occupational pesticide exposure. Study quality was assessed using the WHO Risk of Bias (RoB) assessment instrument for systematic reviews, with the ROBINS-E (RoB in non-randomised studies of exposure) tool domains of bias. Pooled risk estimates were produced using random-effects models with restricted maximum likelihood, heterogeneity was assessed with I² statistics, and meta-regressions and publication …

Tracking Vigilance While Driving: Pilot Study Of Heart Rate Variability Classification Under A Controlled Sleep-Deprivation Protocol, James Elber Duverger, Eli Moser, Philippe Boudreau, Marie Claude Ouimet, Diane B. Boivin, Alireza Saidi

Études primaires

Decreased vigilance associated with drowsiness is a major cause of motor vehicle crashes, but its physiological characterization and detection remain difficult due to behavioral and environmental confounding factors. This study presents an original experimental framework combining a highly controlled sleep-deprivation protocol, repeated driving simulations, and a machine-learning-based heart rate variability (HRV) analysis to study the physiological and behavioral changes in vigilance during a prolonged period of wakefulness while driving. Twelve healthy young adults participated in a 30-h sleep-deprivation constant routine protocol that included driving simulations every two hours, with data collection: electrocardiography (ECG), subjective ratings of drowsiness, psychomotor vigilance test, …

Computer Vision-Based Collision Prevention In Construction: Bridging Academic Advances And Industrial Requirements, Marwa Ziadia, François Gauthier, Damien Burlet-Vienney

Études primaires

Computer vision (CV) technologies have emerged as promising tools for real-time collision risk management. This paper examines CV-based collision-prevention systems from academic and industrial perspectives with a focus on identifying technical and implementation challenges affecting their deployment on construction sites. A scoping review of 158 publications was conducted, alongside an assessment of commercial CV-based collision-prevention systems currently used in construction. The analysis focused on five key functions: object detection, distance measurement and proximity estimation, tracking, worker re-identification (ReID), and deployment robustness. Academic studies demonstrate substantial progress in detection accuracy, real-time processing, trajectory tracking, and predictive risk assessment through deep learning …

Partnerships To Advance Patient Safety And Address Preventable Harm: Case Studies From International Health Care Leaders, Rachel Bonesteel, Robert Saunders, Tilithia Mcbride, Susan Sheridan, David W Bates, Mark Mcclellan, Charles H Kahn, Eyal Zimlichman

Faculty, Staff and Students Publications

There have been notable improvements in patient safety in recent years; however, significant challenges remain in reducing the incidence of preventable patient harm. Supporting patient safety efforts is increasingly important given increasing complexity of care and changing health needs, especially with aging populations. Emerging technologies and capabilities open new possibilities to address longstanding patient safety problems. For example, predictive analytics to support provider decision-making, increased patient interest in engagement in their care, and artificial intelligence provide opportunities to further reduce harm. Many of these examples support a more proactive approach to patient safety by focusing on anticipating, predicting, and preventing …

External Validation Of A Machine Learning Model To Predict Postpartum Hemorrhage In A Us Northeastern Healthcare System, Vesela P Kovacheva, Ricardo Kleinlein, Nolan Wheeler, Kartik K Venkatesh, Eric Jelovsek, David W Bates, Kathryn J Gray

Faculty, Staff and Students Publications

Introduction: Postpartum hemorrhage (PPH) is a major cause of maternal morbidity and mortality. Timely prediction may prevent adverse maternal outcomes, and efforts are needed to develop accurate predictive tools. A high-performing machine learning model to predict PPH using data from the US Consortium for Safe Labor (CSL) remains to be widely validated in contemporary clinical settings using electronic health record (EHR) data. Our goal was to evaluate the performance of the CSL PPH predictive model using EHR data across a large healthcare system in the Northeastern United States.

Methods: We conducted a retrospective cohort study across eight hospitals in the …

Exposing The Work Of The Market Through The Case Of Alternative Provision For English School Students, Nick Pratt, Elizabeth Done, Sam Morahan

School of Law, Humanities and Social Sciences

Pupils in England who for some reason are not able to attend school often find themselves in Alternative Provision (AP). These are special arrangements designed to address their specific needs and help them return to mainstream schooling. AP involves a financial agreement between the provider and the organisation that commissions the provision and thus operates as an explicit form of education market in which educational services are traded directly for financial recompense. We report on a case study of one AP provider in the South-West of England undertaken over a one-year period which generated data through individual, semi-structured interviews and …

The Career Choices Of Final Year Nursing Students In The United Kingdom: A Qualitative Study., Kevin Hambridge, Frazer Underwood, Gosia Bettache, Matt Carey, Halil Kaya, Lisa Burrows, Rachel Tims, Christian Brailsford

School of Nursing and Midwifery

Aim: The aim of this study is to explore the career choices of final year under-graduate nursing students in the United Kingdom. Background: Worldwide there is a decreasing number of nurses and in the United Kingdom there is a decreasing amount of nursing students. There is sparce evidence relating to the career's choices of nursing students and reasons for those choices. Obtaining a deeper comprehension of these choices may aid healthcare employers, in partnership with universities, to design the future nursing workforce. Design: A qualitative design was used. Methods: Twenty-one final year under-graduate nursing students from across a range of …

An Evidence Review Of Technology Enabled Social Care In The Uk: Report For Cornwall Health Determinants Research Collaboration, Sheena Asthana, Michael Loizou, Marius Varga, Oliver Beer, Rory Baxter, Kieran Green

School of Nursing and Midwifery

The Urgent Need for a Shift from Crisis Intervention to Prevention. As highlighted by the Chief Medical Officer, demographic ageing—particularly acute in coastal areas like Cornwall—necessitates a fundamental shift in care models to allow individuals to live as independently as possible. Currently, the potential of digital technologies to support this aim is not being realised. To maintain wellbeing and reduce demand on statutory services, the system must pivot from reactive crisis management to a greater focus on prevention. While technology can play a pivotal role, it will only succeed if integrated into interoperable, data-driven systems that facilitate early intervention and …

How Does Pre-Registration Child Specific Education Prepare Newly Qualified Nurses’ To Care For Children, Young People, And Their Families? An Empty Narrative Review, Matt Carey, Danielle Edge, Julie Blamires, Mandie Foster, Sarah Neill

School of Nursing and Midwifery

This narrative review investigates the influence of child-specific content within pre-registration nursing programs on newly qualified nurses’ perceptions of preparedness to care for children, young people, and their families. Despite international recognition of the specialised competencies required for pediatric nursing, the proportion and quality of child-focused education across Higher Education Institutions is not clear. The Population, Exposure, Outcome framework provided a comprehensive search strategy applied across eight databases to identify relevant studies that met the inclusion and exclusion criteria. Of 663 records identified, 451 were screened and 25 full texts wereassessed for eligibility by two reviewers. No studies met the …

Microbial Collagenase Activity Is Linked To Oral–Gut Translocation In Advanced Chronic Liver Disease, Shen Jin, Aurelie Cenier, Daniela Wetzel, Bethlehem Arefaine, Mar Moreno-Gonzalez, Marilena Stamouli, Merianne Mohamad, Mariia Lupatsii, Emilio Ríos, Sunjae Lee, Ane Zamalloa, Shilpa Chokshi, Adil Mardinoglu, Saeed Shoaie, Naiara Beraza, Vishal C. Patel, Melanie Schirmer

Peninsula Medical School

Microbiome perturbations are associated with advanced chronic liver disease (ACLD), but how microorganisms contribute to disease mechanisms is unclear. Here we analysed metagenomes of paired saliva and faecal samples from an ACLD cohort of 86 individuals, plus 2 control groups of 52 healthy individuals and 14 patients with sepsis. We identified highly similar oral and gut bacterial strains, including Veillonella and Streptococcus spp., which increased in absolute abundance in the gut of patients with ACLD compared with controls. These microbial translocators uniquely share a prtC gene encoding a collagenase-like proteinase, and its faecal abundance was a robust ACLD biomarker (area …

Designing A Mobile App For Post Traumatic Stress Disorder: Insights From Lived Experience And Clinical Practice, Rohit Shankar, Richard Laugharne, Michael Loizou, Marius Varga, Sivia Lin, Bojana Daw Srdanovic, Roger Farrell

Peninsula Medical School

Post-traumatic stress disorder (PTSD) is a disabling anxiety disorder precipitated by severe trauma. Many people with this condition have little access to clinical interventions, especially in low-middle-income countries. For the development of any digital health intervention, it is vital to know the opinions of PLE and clinicians to guide the developers. We conducted two focus groups, one with clinicians (n = 5) and one with people with lived experience (PLE) (n = 11), to gain knowledge of their views on the development of a PTSD App. Transcripts of both focus groups were coded and thematically analysed. The key themes that …

Visual And Rhetorical Analysis Practices In The Sociology Classroom: A Focus On “Zombie” And Derry Girls, Kate Antosik-Parsons, Ann Johnson, Danielle Nielsen, Diane Sabenacio Nititham

Journal of Excellence in College Teaching and Learning

The purpose of this article is to provide a lesson that uses readily available and relatable popular media to address contemporary social issues and ongoing global concerns. Using sociological theories and rhetorical analysis, our three-day activity, “Public Art, Place, and Global Conflict” introduced students to The Troubles, the ethno-national conflict in Northern Ireland that lasted from the late 1960s to 1998. We taught visual media analysis to identify multidimensional social dynamics in the protest song and music video “Zombie” by Irish band The Cranberries (1996), and two episodes of the TV show Derry Girls (2018-2022), a teen sitcom by Lisa …

Am I Top Of The Pops? Does Feedback Of Live Gps Between Sets Of Hurling-Specific Small-Sided Games Improve Subsequent Running And Physiological Performance?, Shane Malone, John Keane, Tom Hargroves, Conor P. Clancy, John David Duggan, Damien Young, Kieran D. Collins

Research Outputs: 2025-Present

The investigation aimed to determine if live feedback of team- and player-specific global positioning system (GPS) running performance data between bouts of hurling small-sided games (SSGs) altered the physical and physiological responses during subsequent bouts of SSGs during a 6-week hurling pre-season period. Twenty-four (n = 24) hurling players (age 25.5 ± 3.2 years; height 177.9 ± 3.2 cm; body mass 83.5 ± 4.5 kg) received either feedback or no feedback during hurling-specific SSGs across a 6-week pre-season period. Teams were assigned to two specific groups, a) GPS live feedback or b) no GPS live feedback (control) for each session, …

Preface, Páraic Carroll, Beatriz Martinez-Pastor, Bidisha Ghosh, Marina Efthymiou, Nikolaos Valantasis-Kanellos, Ciaran Mcnally

Research Outputs: 2025-Present

No abstract provided.

Modified Atmospheric Packaging An Emerging Non-Invasive Packaging Technique For Strawberry Preservation- A Review, Mehraj Fatema Z. Mulla, Tigist Shonte, Lorraine Foley, Michael T. Gaffney, Jesus Maria Frias, Shivani Pathania

Research Outputs: 2025-Present

Strawberries are highly perishable due to their soft texture, high respiration rate, and susceptibility to microbial spoilage. Modified Atmosphere Packaging (MAP) has emerged as a non-invasive preservation strategy to address these limitations while retaining quality. This review aims to critically evaluate the principles, effectiveness, technological advancements, and limitations of MAP in strawberry preservation. It also explores emerging materials, active agents, and modelling tools used to optimize MAP systems. A comprehensive literature review was conducted, focusing on MAP applications in strawberries, including recent innovations such as active MAP, nanocomposite and bio-based films, and complementary treatments like coatings and essential oils. Recent …

Hybrid Bacterial Colony Optimization And Particle Swarm Optimization For Load Balancing In Fog Computing, Aryan Kumar, Punit Gupta, Rohit Verma

Research Outputs: 2025-Present

Fog computing minimizes latency and bandwidth consumption by processing data near the source, but it has the challenge of workload balancing across the dynamic and resource limited fog nodes. Uneven task assignment can result in bottlenecks, idle resources, and lowered Quality of Service (QoS) standards. In this work, we introduce a hybrid metaheuristic load balancing algorithm for fog computing by combining the Bacterial Colony Optimization (BCO) and the Particle Swarm Optimization (PSO) techniques to enhance load balancing. BCO has good solution space exploration capabilities, whereas PSO has the advantage of quick convergence; the hybrid takes advantage from both to achieve …

E-Profits: A Business-Aligned Evaluation Metric For Profit-Sensitive Customer Churn Prediction, Awais Manzoor, M. Atif Qureshi, Etain Kidney, Luca Longo

Research Outputs: 2025-Present

Retention campaigns in customer relationship management often rely on churn prediction models evaluated using traditional metrics such as AUC and F1-score. However, these metrics fail to reflect financial outcomes and may mislead strategic decisions. We introduce e-Profits, a novel business-aligned evaluation metric that quantifies model performance based on customer lifetime value, retention probability, and intervention costs. Unlike existing profit-based metrics such as Expected Maximum Profit, which assume fixed population-level parameters, e-Profits uses Kaplan–Meier survival analysis to estimate tenure-conditioned (customer-level) one-period retention probabilities and supports granular, per-customer profit evaluation. We benchmark six classifiers across two telecom datasets (IBM Telco and Maven …

Survival Of Listeria Monocytogenes And Salmonella Typhimurium In Pepperoni With Reduced Salt And Sodium Nitrite Levels, And Sublethal Thermal Treatments, Shannon Heapes, Victoria Caballero, Jesus Frias, Bradley Afanda, Martin Danaher, Joseph P. Kerry, Geraldine Duffy

Research Outputs: 2025-Present

There is increasing pressure to reduce sodium nitrite and salt levels in processed and fermented meats in response to consumer demands and updated legislation. However, such reductions may impact pathogen control. In this study, the survival of Listeria monocytogenes and Salmonella Typhimurium was evaluated in pepperoni produced with reduced salt and sodium nitrite levels, with or without an enhanced postfermentation thermal treatment. Pepperoni batters with formulations varying in sodium nitrite (50–150 ppm) and salt (1.4%–2.5%), were inoculated with cocktails of L. monocytogenes or S. Typhimurium (~log₁₀ 4–6 CFU g⁻¹), subjected to a postfermentation thermal treatment (53.5°C × …

Synthesising Cross-Speaker Data For Low-Resource Pathological Speech Recognition With Peft, Kesego Mokgosi, Milad Dadgar, Cathy Ennis, Robert Ross

Research Outputs: 2025-Present

Dysarthric speech recognition is essential for enhancing communication and accessibility for individuals with speech impairments, yet its development is hindered by a scarcity of robust, speaker-specific datasets. This study explores low-resource dysarthric speech recognition through cross-speaker transfer using synthetic data and parameter-efficient fine-tuning (PEFT). We integrate SpeechT5 text-to-speech (TTS) synthesis with x-vector speaker embeddings to generate speaker-specific dysarthric speech, enabling model adaptation while preserving pathological speech characteristics such as prosodic irregularities. Experiments on the TORGO dataset show that mixed cross-synthetic data with LoRA fine-tuning achieves a WER of 0.17, representing a 71.7% improvement over the standard model (0.60 WER) without …

Pab-Pif: A Hybrid Architecture To Evaluate Mutable And Immutable Blockchains In Iot–Fog Networks, Marco Scarpa, Mohammad Sadeghzadeh, Saeed Javanmardi, Bahareh Pahlevanzadeh, Mauro Iacono

Research Outputs: 2025-Present

Blockchain provides secure and decentralized data storage. Normal blockchains permanently store data. Mutable blockchains allow users to change data, but this reduces tamper resistance. This paper tests both methods in PaB-PIF, a hybrid architecture for IoT-Fog networks. Our design uses an immutable mainchain in the cloud layer and mutable sidechains in the fog layer. We analyze throughput, latency, and tamper resistance using math models and simulations. Results show that blockchain greatly improves network security. Without blockchain, the network has zero tamper resistance. The mutable blockchain in the fog layer has a tamper resistance of 0.58. The immutable blockchain in the …

Shap-Rc: A Framework For Explaining Annotator Disagreement In Sexism Detection, Madhuri Sawant, Arjumand Younus, Simon Caton, M. Atif Qureshi

Research Outputs: 2025-Present

The effectiveness of supervised machine learning models is heavily influenced by the quality of training data, which is often shaped by human annotators. Subjective NLP tasks such as hate speech detection, toxicity identification, and sexism classification frequently exhibit annotator disagreement due to differences in individual perspectives. This study investigates annotator disagreement in sexism detection using English tweets from the EXIST 2023 competition. To systematically analyse disagreement, tweets are categorised based on annotator consensus levels, examining how annotator demographics and linguistic features contribute to labelling inconsistencies. We interpret disagreement patterns using Shapley Additive Explanations (SHAP) and assess the consistency of SHAP-derived …

Browser-Based Phishing Detection System Using Modern Web Technologies, Muhammad Arshad, Beena Sherin Kuriakose, Choo Wou Onn, Farhan Ahmad Siddiqui, Mohammad Shahid Kamal

Research Outputs: 2025-Present

Phishing remains one of the most persistent cybersecurity threats, exploiting human trust to steal sensitive information through deceptive websites. Traditional detection methods, reliant on blacklists and reactive reporting, offer limited protection against rapidly evolving zero-day attacks. To address these challenges, this study proposes and evaluates a hybrid browser-resident phishing detection framework that combines three complementary detection mechanisms: a locally executed Random Forest model using URL lexical features, lightweight real-time DOM structure analysis, and VirusTotal’s multi-engine reputation service. Communication between the client and server is optimised using gRPC over the QUIC protocol, ensuring secure, high-performance data exchange with built-in retry mechanisms …