Procter & Gamble (United Kingdom)
Open Access Institutional Repository at Robert Gordon UniversityNot a member yet
9563 research outputs found
Sort by
Deep learning and attention-based methods for human activity recognition and anticipation: a comprehensive review.
Get PDFIn recent years, there has been a significant increase in research focused on Human Activity Analysis (HAA). This field has progressed from basic activity recognition tasks to addressing more challenging ones, such as predicting future human actions based on partially observed videos and even predicting actions before they happen. The evolution of HAA has been driven by recent advancements in attention-based models like Transformers, along with a wide range of applications from security surveillance to advanced monitoring systems, behaviour analysis, and more. A comprehensive review of HAA literature from 2017 to 2025, with a novel taxonomy emphasising activity recognition, prediction, and anticipation, is presented. We critically review and examine recognition methods from trimmed and untrimmed videos, context-aware and trajectory-based prediction, and short-term and long-term anticipation. Through a comprehensive analysis, we review and evaluate key aspects of this domain, including attention-based contextual comprehension, temporal dynamics modelling, and multi-model fusion methods. Furthermore, we critically examine and assess the public datasets utilised in driving this research forward, pinpointing limitations and primary challenges within this domain. Finally, the paper provides a summary of recent developments in HAA and suggests future directions, with the hope that it will serve as a valuable reference for researchers in the field
Exploring third sector clients and student managed impacts: a case study approach.
Get PDFThe benefits of event experience have always been valued and fostered within event pedagogy (McDonald, 2000; Robertson, 2012; Lamb, 2015; Ryan, 2016). Likewise, the value of volunteering and community fundraising has been found to be integral to third sector organisations with an integration of social impact philanthropy from both perspectives (Owen, 2019). Combining these facets this provides social development opportunities for students and beneficiaries (Edward, Mooney and Heald 2001). The Event Management as a course requiring tangible outputs and skills development, the UG course at Robert Gordon University works closely with third sector clients in the creation, management, delivery and evaluation of live event projects. Combining both event experience, client management and impact projection and implantation. The course requires students to work closely with a charity client to develop objectives (Canziani and Tullar, 2017). For charity clients this comes with necessary trust of the students who becomes the ‘image-maker’ in terms of driving fundraising, target market fixation and stakeholder management (Getz, 2012). With a focus problem-based learning (Savin-Boden, 2004) the process requires students to develop critical and lateral thinking skills in creation of outputs which are purposefully set in nature. As such this initial study aims to uncover the initial student managed impacts and how these align with client expectations. Furthermore, exploring the relationship journey between client and student. Exploring an investigatory and interpretivist case study approach this study provides impact reports from 3 charity clients and 3 students as part of preliminary findings over one academic year. Reviewing interview discussions, reflective diary practice with event journey evaluations and charity impact this will uncover the initial student managed impacts in alignment of client expectations, reviewing the relationship journey (Kania, 2014). These case studies seek to explore discussion from academic council with the view to lead to future longitudinal investigation
Event classification on subsea pipeline inspection data using an ensemble of deep learning classifiers.
Get PDFSubsea pipelines are the backbone of the modern oil and gas industry, transporting a total of 28% of global oil production. Due to several factors, such as corrosion or deformations, the pipelines might degrade over time, which might lead to serious economic and environmental damages if not addressed promptly. Therefore, it is crucial to detect any serious damage to subsea pipelines before they cause dangerous catastrophes. Inspections of subsea pipelines are usually made using a Remote Operating Vehicle and the inspection data is usually processed manually, which is subject to human errors, and requires experienced Remote Operating Vehicle operators. It is thus necessary to automate the inspection process to enable more efficiency as well as reduce costs. Besides, it is recognised that specific challenges of noisy and low-quality inspection data arising from the underwater environment prevent the industry from taking full advantage of the recent development in the Artificial Intelligence field to the problem of subsea pipeline inspection. In this paper, we developed an ensemble of deep learning classifiers to further improve the performance of single deep learning models in classifying anomalous events on the subsea pipeline inspection data. The output of the proposed ensemble was combined based on a weighted combining method. The weights of base classifiers were found by minimising the difference between the weighted combining result and the given associated ground truth annotation information. Three inspection datasets, gathered from different oil and gas companies in the United Kingdom, were analysed. These datasets were recorded under varying conditions and include a range of anomalies. The results showed that the proposed ensemble achieves around 78% accuracy on two datasets and more than 99% accuracy on one dataset, which is better compared to base classifiers and two popular ensembles
Role of selenium and 17β oestradiol in modulating lipid accumulation in in vitro models of obesity and NAFLD.
Get PDFAbdominal obesity is prevalent in women and during menopause, making them more susceptible to weight gain, fat redistribution, and subsequent development of metabolic syndrome and associated diseases such as non-alcoholic fatty liver disease (NAFLD). Evidence from menopausal/postmenopausal women has demonstrated an association between declining oestrogen (i.e. 17β oestradiol; E2) levels and the development/progression of both obesity and associated diseases. Furthermore, dietary intake of the micronutrient selenium (Se) is reduced in obese postmenopausal women and a negative correlation between Se level and body mass index (BMI) has been reported. This suggests that novel nutritional and hormonal solutions are needed to moderate fat deposition in postmenopausal women. This study used mouse 3T3-L1 and human HepG2/C3A cells, as in vitro models of obesity and NAFLD, respectively, to understand basic cellular mechanisms associated with lipogenesis, and to study the role of Se and oestrogen, as E2, in modulating lipid deposition. Supplementation of 3T3-L1 cells during differentiation to adipocytes with 200 nmol/L Se reduced lipid deposition (~20%) by increasing the expression of genes related to redox status (Gpx1, Selenow, and Ucp2) and reducing the expression of markers of energy metabolism, inflammation and adipocyte differentiation (Lep, Cox-2, and Fabp4); whereas administration of 10 nmol/L E2 regulated lipid synthesis and metabolism (reductions in Fasn, Pparg, and Hsl expression and increased Fabp4 and Glut4 expression). In HepG2/C3A cells, both Se and E2 reduced lipid accumulation (15%−20%), via regulation of lipid and energy metabolism and inflammatory genes (SREBF1, SCD1, COX2, and LEP). These results suggest that both hormonal treatment and micronutrient supplementation may be beneficial in obesity and NAFLD management. If our current in vitro findings were subsequently demonstrated in vivo, they could provide valuable data to support the use of either Se supplementation and/or oestrogen-based therapies to prevent and manage obesity and NAFLD in postmenopausal women
The effects of hip flexion angle on quadriceps femoris muscle hypertrophy in the leg extension exercise.
Get PDFThis study compared the effects of 90° versus 40° hip flexion in the leg extension exercise on quadriceps femoris muscle hypertrophy. Twenty-two untrained men completed a ten-week intervention comprising two resistance training sessions per week with four sets of leg extension to momentarily failure. A within-participant design was used, with lower limb side randomly allocated to the 40 or 90° condition. Muscle thickness of distal and proximal rectus femoris and vastus lateralis were quantified via ultrasound. Data were analysed within a Bayesian framework including univariate and multivariate mixed effect models with random effects to account for the within participant design. Differences between conditions were estimated as average treatment effects (ATE) and inferences made based on posterior distributions and Bayes Factors (BF). Results indicated a greater hypertrophic response in the rectus femoris for the 40° condition, with 'extreme' evidence supporting a hypertrophic response favoring the 40° hip angle for the rectus femoris (BF > 100; p(Distal/ATE and Proximal/ATE > 0) > 0.999), and 'strong' evidence supporting no difference in hypertrophic response for the vastus lateralis (BF = 0.07). Therefore, both conditions could be viable options for increasing quadriceps femoris hypertrophy. However, when training for maximizing rectus femoris hypertrophy among untrained men, we suggest training with a reduced hip flexion in the leg extension exercise
Frequency, type and severity of drug-related problems and pharmacist interventions in Paxlovid prescribing: a descriptive analysis.
Get PDFPaxlovid® (nirmatrelvir and ritonavir) is the only licensed oral antiviral for COVID-19. Ritonavir is a potent inhibitor of cytochrome P450 enzymes causing numerous drug-drug interactions (DDIs). The aim of this study was to describe the frequency, type, and severity of detected drug related problems (DRPs) associated with Paxlovid®. This study involved a retrospective quantitative analysis including all patients prescribed Paxlovid® at a public hospital in Vienna, Austria. Data were collected from the patients' records by a clinical pharmacist. A customised, piloted data collection form was used. A sample of data was checked for consistency by an independent clinical pharmacist. Any DDI and severity classification was recorded using an established interaction checker tool. Dosage adjustments due to renal impairment were recorded. 122 of 140 patients (87.1%) required interventions to prevent DRPs. Pharmacists' intervention at dispensing was needed in 63.6% (n=89) of cases. In 3 (2.1%) patients, Paxlovid® was prescribed despite being contra-indicated due to severe renal impairment. The most common were DDIs (n=80; 57.1%). Renal impairment and DDIs were noted in 24.3% (n=34) of cases. A total of 313 DDIs were recorded in 114 (81.4%) patients, with severe interactions in 24 (17%) patients. The study concluded that pharmacists' involvement in prescribing highly interacting drugs such as Paxlovid® is essential to enhance patient safety
Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset]
No full textThis study proposed a new sensor calibration methodology and the design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams. Furthermore, machine learning models were developed in this study to explore how impurities in gas streams can be quantified. In the case study for the machine learning models, a nitrogen gas (N2) system with impurities was used for the demonstration. The study compares the performance of sensors in quantifying the concentrations of component gases in binary gas and multi-component gas mixtures. The binary gas mixture is made up of N2 and NO2, while the multi-component gas mixtures are mixtures of N2 with two-gas, three-gas, or four-gas combinations of NO, NO2, C3H8, and NH3; each gas mixture has a constant 10% O2 by volume (as oxygen reduction is a requirement in electrochemical sensors). The hybrid artificial intelligence system of quantifying gas concentrations is scalable and can be applied in complex gas mixtures found in different industries. For instance, in a CO2 gas stream, the binary gas mixture could represent a mixture of CO2 with NO2; while the multi-component gas mixtures could represent CO2 with two-gas, three-gas, or four-gas combinations of NO, NO2, C3H8, and NH3
The history and development of health psychology in the United Kingdom.
No full textIdeas about how the mind, body and health are interconnected date to ancient times and became a focus of psychology in the 20th century. In the first half of the 20th century, medical psychology and psychosomatic medicine applied psychological science to health, and psycho-physiological research investigated relationships between processes such as stress and health indicators. By the 1950s and 60s, psychologists investigated personal and social correlates of behaviours being identified as harmful to health, such as smoking. The 1970s were a key period for UK health psychology, with oral history evidence now available. At that time, medical schools were recruiting psychologists to teach and to conduct research, often addressing practical healthcare problems, such as presurgical anxiety or nonadherence. Social psychological theory was typically used to understand health risk behaviours (e.g., smoking, alcohol use). Also at this time, several UK clinical psychologists took positions in general hospitals, increasingly addressing healthcare issues and adaptation to illness or treatments. Links with "health psychology" development elsewhere, such as in the USA, provided inspiration. In the 1980s it grew as an identity that united a diversity of science and practice, increasingly using theory. Informal professional networks appeared in the 1980, followed by the Health Psychology Section of the British Psychological Society in 1986, with annual conferences and Masters degrees following. Whilst academic health psychology posts increased during the 1990s, many were filled by those with social psychology or psychophysiology backgrounds; practitioners were still clinical psychologists. The upgrade in 1997 from a BPS Section to a BPS Division of Health Psychology enabled practitioners to be chartered in health psychology without a clinical psychology background. By the end of the 2000s, UK health psychology was a recognised academic discipline and health profession with government-accredited training and registration. Its role in health and social care, training, research, policy and practice has continued to strengthen into the 21st century
Imposter participants in synchronous qualitative research: a systematic scoping review.
Get PDFAlthough the issue of bots and fraudulent participants is well established within quantitative research, in recent years there have been increasing incidences of imposter participants within qualitative research. However, how qualitative researchers conceptualise this challenge and what the perceived impact of these imposter participants are, remains underexplored. This systematic scoping review identified 15 articles published since 2018 addressing the topic of imposter participants and fraudulent data in synchronous qualitative research. The review identified that the majority of current articles are commentaries or case study narratives, with little apparent inter disciplinary engagement. Findings indicate that where recommendations are offered these can be subjective or influenced by discipline, with a lack of an evidence informed approach being adopted. The analysis identified three primary issues for applied qualitative research fields, with threats to data integrity and reliability, threats to research diversity, accessibility and reach, and questions of trust and ethics within research highlighted. Developing evidence-based guidance and ensuring cross-disciplinary engagement will be central to maintaining the relevance, impact, and validity of applied qualitative research
Unsupervised similarity-aligned ensemble metrics for evaluating legal Q&A LLM responses. [Dataset]
No full textThis repository contains code and datasets related to the paper titled "Unsupervised Similarity-Aligned Ensemble Metrics for Evaluating Legal Q&A LLM Responses"
Data sources:
Access Repository Dashboard
Do you manage Open Access Institutional Repository at Robert Gordon University? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!