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Hybrid CFD and machine learning analysis of CO2 enhanced oil recovery in naturally fractured reservoirs.
Full text linkCO2 based Enhanced Oil Recovery (EOR) in unconventional reservoirs is an emerging technology. Scientific research efforts are directed towards understanding the propagation of CO2 front due to the complex interplay between CO2 injection and saturation, and reservoir's constitutive relationships. Conventional methods for characterising CO2-EOR rely on high-fidelity numerical solutions that often result in over or under prediction of CO2 geosequestration. In this study, we develop a novel hybrid Computational Fluid Dynamics (CFD) and Machine Learning (ML) framework that allows for rapid CO2 geosequestration prediction and its optimal injection. Very low or high injection rates have been shown to result in low sweep efficiency or excessive entry pressure, while an intermediate injection rate offers the best balance between the two. CFD data-driven Gaussian Process Regression (GPR) and Extreme Gradient Boosting (XGBoost) models have been developed, trained and tested for predicting CO2 saturation in the reservoir. Comparative analysis indicates that GPR outperforms XGBoost in terms of its predictive performance and robustness. Through the analysis of layer-resolved CO2 front displacement and development of data-driven surrogate models, this study contributes a novel framework for CO2-EOR predictive modelling and optimising injection strategies in naturally fractured reservoirs
Training for recovery: impact of sprint interval training on recovery dynamics and aerobic performance in kickboxing athletes.
Full text linkRecovery within and between rounds is crucial to combat sports performance. We sought to determine whether sprint interval training (SIT) improves recovery dynamics and aerobic performance. Methods: Eleven male kickboxing athletes (26 ± 5 years; body mass index 25 ± 3 kg/m2) were recruited. Participants were tested three times for VO2peak/time to exhaustion and critical power; baseline, 3 weeks control, 3 weeks of SIT (8 × 10s lower body sprints followed by a maximum of 10 min recovery before completing 8 × 10s upper body sprints). During SIT session 1 and 9 continuous gas analysis was performed. Results: There was a significant reduction in recovery time between lower and upper body sprints with training (session 1: 441 ± 150s; session 9: 268 ± 10s; P 0.05). Conclusion: SIT improves recovery time associated and aerobic performance associated with improved oxygen off-kinetics. Therefore, training needs to focus on improving oxygen off-kinetics to enhance combat performance
Cas-OVD: cascaded open-vocabulary detection of small objects using multi-refined region proposal network in autonomous driving.
Full text linkAlthough text information has aided existing models to achieve promising results in open vocabulary object detection (OVD), the lack of semantic information has led to the difficulty in small objects detection (SOD). Moreover, such semantic gap also causes failure when matching texts and image features, resulting in false negative instances being detected. To address these issues, we propose a Cascade Open Vocabulary Detector (Cas-OVD), which builds upon existing multi-stage detection pipelines but specializes in text-vision alignment for small objects. In particular, we adapt a multi-refined region proposal network, guided by a non-sampled anchor strategy, to reduce the missing and false detections of small objects. Meanwhile, a deformable convolution network based feature conversion module is proposed to enhance the semantic information of small objects even the potential ones with low confidence. Unlike existing methods that rely on coarse-grained image-based features for image-text matching, Cas-OVD refines these features through a cascade alignment process, allowing each stage to build on the results of the previous one. This can progressively enhance the feature correlation between the image regions and the textual descriptions through successive error correction. On the joint BDD100K-SODA-D dataset, Cas-OVD achieved 17.95% APall and 14.6% APs, outperforming RegionCLIP by 3.5% APall and 3.0% APs, respectively. On the OV_COCO dataset, Cas-OVD has the 32.71% APall and 17.26% APs, surpassing the RegionCLIP by 6.6% APall and 6.1% APs, respectively
The influence of antenatal relaxation classes on perinatal psychological wellbeing and childbirth experiences: a qualitative study.
Full text linkThere is growing evidence that antenatal education incorporating relaxation practices can positively influence perinatal psychological wellbeing. However, a paucity of qualitative research is evident. Gaining insight into how and why such education may influence childbearing women can inform the design of effective educational interventions. This study aimed to explore the perspectives of women and their partners on how and why a single Antenatal Relaxation Class (ARC) might influence perinatal psychological wellbeing and childbirth experiences. In this descriptive qualitative study, 17 women and 9 partners participated in semi-structured in-depth interviews. The data were analysed using thematic analysis. The study was carried out in a Scottish NHS Health Board where ARC was provided to expectant parents. Two themes were generated: "the turning point" and "recognition of an inner resource". Participants perceived ARC as "the turning point" when they became more confident, equipped, and less fearful and anxious towards childbirth. "Understanding of the psychophysiological processes of childbirth", "positive stories" and "practice of relaxation techniques" were reported as the main reasons for these positive changes. Participants explained ARC had enabled them to access a deep sense of calmness as "an inner resource", and motivated the use of relaxation techniques as a self-care behaviour throughout pregnancy and childbirth. The study therefore concludes that a single antenatal relaxation class has the potential to enhance perinatal psychological wellbeing and childbirth experiences. This study provides valuable insights for maternity services seeking to develop effective health-promoting antenatal education
Access to finance for small and medium enterprises in developing countries: key issues and options.
No full textSmall and Medium Enterprises (SMEs) constitute an essential sector in developed and developing economies. Using evidence from extant literature, recent market trends, and an array of statistics from reputable organisations concerned with SME issues, this chapter unravels the myriad of challenges faced by SMEs in accessing finance, different financing options available, and diverse ways of removing fund access bottlenecks using technological, institutional, and governmental instruments. Additionally, the study discusses a catalogue of financing options that SMEs can deploy or combine to meet the business needs. The paper ends with a discussion of various strategies/mechanisms for removing SMEs’ financing barriers alongside future opportunities for more inclusive and sustainable funding access globally
Modified CBAM: sub-block pooling for improved channel and spatial attention.
No full textThe Convolutional Block Attention Module (CBAM) has emerged as a widely adopted attention mechanism, as it seamlessly integrates into the Convolutional Neural Network (CNN) architecture with minimal computational overhead. However, its reliance on global average and maximum pooling in the channel and spatial attention modules leads to information loss, particularly in scenarios demanding fine-grained feature analysis, such as medical imaging. In this paper, we propose the Modified CBAM (MCBAM) to address this critical limitation. This novel framework eliminates the dependence on global pooling by introducing a sub-block pooling strategy that captures nuanced feature relationships, preserving critical spatial and channel-wise information. MCBAM iteratively computes attention maps along channel and spatial dimensions, adaptively refining features for superior representational power. Comprehensive evaluations on diverse datasets, including C-NMC (acute lymphoblastic leukemia), PCB (peripheral blood cells), and COVID-19 (Chest X-ray), demonstrate the efficacy of MCBAM. Additionally, we evaluate MCBAM against similar alternatives, such as the Bottleneck Attention Module (BAM), Normalisation-Based Attention Module (NAM), and Triplet Attention Module (TAM), demonstrating that MCBAM consistently outperforms these advanced attention mechanisms across all datasets and metrics. Furthermore, results reveal that MCBAM surpasses the standard CBAM and establishes itself as a robust and effective enhancement for attention mechanisms, with notable improvements in medical imaging tasks, offering critical advantages in complex scenarios
Social interaction and dark tourism in prison museums.
No full textThis study explores how prison tourism experiences are co-constructed through situated visitor interactions. Penal heritage sites are decommissioned prisons, transformed into immersive educational attractions, drawing upon multiple interpretative practices to engage visitors with historic and contemporary issues of crime and punishment. Using ethnomethodological conversation analysis (EMCA), this research examines how gestures, talk, gaze and bodily position influence how visitors see, interpret, and emotionally negotiate difficult heritage. Findings reveal that visitors co-produce dark tourism experiences and negotiate the perceived darkness of sites through embodied practice. Situating visitors as active social agents, this study provides insights into the co-construction of dark tourism experiences, emphasising interpretation as an emergent process shaped by interaction rather than predetermined by site design or individual motivation
Developing National Health Service pharmacists as researchers: learning from the Scottish Pharmacist Clinical Academic Fellowship programme.
No full textIn the United Kingdom (UK), the vision is to further develop the pharmacy workforce through career development pathways aligning to the Royal Pharmaceutical Society's post-registration foundation, advanced, and consultant practice curricula, which align with the four pillars of advanced practice recognized across multiple healthcare professionals—clinical practice, leadership and management, education, and research. However, it has been recognized that research capacity, competency, and confidence within the pharmacy profession require development. It has been noted that it is this 'pillar' that most frequently impedes successful credentialing at both 'Core advanced' and 'Consultant levels'. A report presenting the findings of a UK-wide call for evidence on clinical academic careers in pharmacy outlines recommendations to embed a research culture in pharmacy careers, develop a clinical academic pathway for pharmacy, and provide a pipeline of pharmacy research leaders. The establishment of such pathways would provide opportunities for building capacity within the profession. The Scottish Pharmacist Clinical Academic Fellowship (SPCAF) programme was created to develop a network of Clinical Academic Pharmacist posts; a collaborative initiative between National Health Service Education for Scotland and the two Pharmacy Higher Education Institutions in Scotland is aimed at developing pharmacists as researchers to advance pharmaceutical care within the National Health Service in Scotland. This commentary presents a summary of an archival review completed as part of a wider research programme that adopted a case study approach with the purpose of evaluating the SPCAF programme cohort 1 (2021–23). The scope is to support others looking to develop similar practice-based research programmes aiming to build research capacity, competence, and confidence in the pharmacy workforce
Stakeholders' perceptions of barriers, benefits, and drivers for digital building logbook adoption in building renovation projects in Europe.
Full text linkThe construction sector is responsible for a significant share of greenhouse gas emissions in Europe, making the decarbonisation of the existing building stock a critical priority. In this context, Digital Building Logbooks (DBLs) are increasingly promoted as digital tools to support renovation planning, data continuity, and circular economy practices across the building lifecycle. Despite growing policy attention, the adoption of DBLs in renovation projects remains limited in practice. This study provides one of the first empirical rankings of perceived barriers, benefits, and drivers influencing DBL adoption in renovation projects across Europe. An exploratory quantitative survey was conducted with a purposively selected sample of stakeholders involved in renovation-related activities. Likert-scale responses were analysed using descriptive ranking statistics and reliability testing, while qualitative data from open-ended responses were analysed using directed content analysis. The results indicate that stakeholders strongly recognise the benefits of DBLs, particularly in terms of improved access to reliable building information, informed decision-making, and support for circular renovation practices. However, adoption is constrained by regulatory uncertainty, limited awareness, and unclear governance and operational frameworks. The most influential drivers identified relate to interoperability with existing digital tools, rising awareness of DBLs among stakeholders, regulatory support, and the availability of standardised and operationally clear frameworks for DBL implementation
Measurement error, reliability, and validity.
No full textMeasurement error, reliability, and validity are essential concepts that all strength and conditioning coaches and applied sports scientists should understand and include in their practice. An understanding of these concepts enables applied practitioners to critically evaluate research and interpret data from their own practice to make informed training decisions with athletes. Measurements taken from athletes contain uncertainty that must be considered when evaluating performance; thus, being able to quantify and recognise sources of error is important for administering tests with athletes. Reliability refers to the consistency of measurements, providing the basis to detect real change with athletes. Validity ensures that the tests involved measure what they are intended to measure or if there is agreement between different methods of evaluating the same physical characteristics. With the emergence of new technologies available to practitioners, establishing concurrent validity of these newer methods and technologies provides confidence in adopting these new approaches to provide meaningful and actionable data. The aim of this chapter is to introduce foundational concepts and frameworks for evaluating measurement quality in strength and conditioning. The chapter will specifically focus on exploring the principles of measurement error, test-retest reliability, and concurrent validity, providing worked examples to illustrate applications in applied and research contexts
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