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Analysis of Blood Stasis for Stent Thrombosis Using an Advection-Diffusion Lattice Boltzmann Scheme
Get PDFAn advection-diffusion solver was applied to assess how stent strut shape and position impact the development of a pro-thrombotic region within the stented human artery. Presented here is a suitably parameterised advection-diffusion equation with a source term that is spatially uniform within a certain sub-domain of interest to compute a “time concentration”. The latter will serve as a surrogate quantity for the “age” of fluid parcels, i.e., the time the fluid parcel has spent in the sub-domain. This is a particularly useful concept in the context of coronary artery haemodynamics, where “stasis of blood” (or residence time) is recognized as the most important factor in thrombotic initiation. The novel method presented in this work has a very straightforward and convenient single lattice Boltzmann simulation framework encapsulation. A residence time surrogate is computed, presented and correlated with a range of traditional haemodynamic metrics (wall shear stress, shear rate and re-circulation region shapes) and finally, the role of these data to quantify the risk of thrombus formation is assessed
The Learn Together programme (Part A): Co-designing an approach to support patient and family involvement and engagement in patient safety incident investigations
Get PDFBackground Whilst patients and families can and do support patient safety in several ways, empirical evidence for the specific impact of involvement in patient safety incident investigations and their outcomes, has been limited, with little information about how to undertake involvement meaningfully.
Aim 1) develop a set of common principles to guide involvement of patients and families in patient safety incident investigations; 2) develop a working programme theory for how these might be enacted; 3) co-design guidance to support the meaningful involvement of patients and families in patient safety incident investigations.
Methods We synthesised three existing data sets (literature review, documentary analysis of incident investigation policies, and interviews with patients, families, lawyers, incident investigators, and healthcare staff) relating to patient and family involvement in incident investigations. Ten common principles and a working programme theory were drafted. Within a convened co-design community, we then developed guidance for patients, families, staff, and investigators in local NHS Trust and national investigations, via a series of workshops.
Findings We developed ten 'common principles' and a working programme theory for an approach that might support meaningful patient and family involvement in incidents investigations. Based on these principles and the programme theory, we co-designed guidance to be used within NHS Trust and national investigations of harm that follow patient safety incidents. The guidance includes information, resources and tools to enable better understanding and practice, from the perspective of patients, families, investigators and staff, on how to be meaningfully involved.
Conclusions Our common principles and co-designed guidance emphasise two key things. First, that organisational learning is not the only desired outcome for incident investigations, with patients, families and staff reporting the need for restoration and repair. Second, that investigations can be part of restoration, but when it fails to address the needs of stakeholders arising from investigations, it can compound the harm of the original incident. As a result, we juxtapose existing theories, and illuminate new insights, proposing a theory of 'restorative learning'. We see design as an ongoing phenomenon -the guidance is our current iteration, and we learnt several valuable lessons about doing co-design
Optimal Satellite Selection using Quantum Convolutional Autoencoder for Low-Cost GNSS Receiver Applications
Get PDFThe increasing reliance on global navigation satellite systems for diverse applications necessitates the development of efficient satellite selection methods to optimize positioning accuracy and system performance. In particular, low-cost global navigation satellite systems receivers face challenges in managing data from multiple visible satellites, often resulting in suboptimal performance due to high geometric dilution of precision values. Effective satellite selection is crucial for improving the accuracy and reliability of positioning solutions in these systems. Quantum computing and machine learning provide promising solutions by using data patterns for complex optimization problems. This work proposes the quantum convolutional autoencoder-based optimal satellite selection method. This new satellite selection method examined the data collected from the receiver located at latitude 16.33° N and longitude 80.62° E, collected on March 10, 2022. The main aim is to enhance the performance of low-cost receivers by minimizing the geometric dilution of precision values and optimizing the tetrahedron volume function. Quantum convolutional autoencoders process the satellite data to balance the navigational solution’s computational burden and the navigational algorithm’s accuracy. The model aims to identify the most optimal satellites for positioning by setting geometric dilution of precision as the cost function. The QCAE-based method achieves a CEP of 1.384 m and SEP of 1.759 m for four selected satellites, compared to 5.937 m and 6.691 m for PSOSSM. For nine satellites, QCAE achieves a CEP of 1.287 m and SEP of 1.713 m, while PSOSSM results in 5.725 m and 6.385 m, respectively. Additionally, QCAE reduces computations by over 64%, requiring 730 multiplications and 713 additions, compared to 2034 multiplications and 2017 additions for all visible satellites. This proposed approach provides the optimal navigation solution for cost-effective implementations in a real-time environment. This research provides new insights into satellite selection strategies using machine learning approaches
Study on Capability of the Octocopter Configuration in a Finite Element Analysis Simulation Environment
Get PDFIn this paper, a mechanical structure is proposed for generating 100,000 volts on board the drone heavy-lift octocopter UAV (Unmanned Aerial Vehicle) and for exploring the possibility of using this structure to transfer the harvested energy wirelessly to nearby UAVs. The feasibility of generating of a large electric field around the UAV structure is investigated theoretically using ANSYS and MATLAB simulation tools. The high-voltage generation mechanism is based on the boost DC-to-DC conversion technique, utilizing a traditional voltage step-up converter and voltage multiplier circuits. The analysis of the modeled octocopter geometry and the corresponding electric field distribution around the vehicle is presented through graphical representation of the simulated parameters. Additionally, the use of traditional carbon fiber material in the proposed octocopter structure and its impact on the generated electric field is carefully considered
Operating Department Practitioner's research priorities: A Delphi study
Get PDFWith the 2022 Allied Health Professions’ Research and Innovation Strategy and the College of Operating Department Practitioners (CODP) joining the Council for Allied Health Professions Research, understanding the Operating Department Practitioner (ODP) profession’s vision for research and innovation and identifying its research priorities has become important. This Delphi study aimed to establish research priorities for the ODP profession. Questionnaires were distributed to ODPs using CODP and social media networks. Round One saw 49 eligible responses; this reduced to 21 in Round Two and 17 in Round Three. Thirty-one research priorities were identified by consensus. Priority rank was determined by mean score, percentage agreement, and coefficient of variance. By reaching a consensus, ODPs co-created research priorities and identified several themes that will contribute to professional development and patient care and support funding opportunities. The five key themes were Workforce Transformation, Education, Patient Safety and Experience, Innovation and Technology, and Theatre Culture
Estimating the Cost and Carbon Output of Musculoskeletal Primary Care Management Decisions: A Retrospective Analysis of Electronic Health Records
Get PDFBackground: Healthcare accounts for up to 5% of worldwide carbon emissions and costs global economies an estimated $9 trillion annually. Primary care accounts for up to one‐fifth of all NHS carbon emissions, with musculoskeletal (MSK) pain accounting for 14%–30% of all primary care consultations. Method: A cost‐carbon calculator model was used to undertake a retrospective economic and environmental analysis of resource use for non‐inflammatory MSK pain primary care consulters. Data used to populate the model was derived from Electronic Health Records and patient surveys collected during The Multi‐level Integrated Data for Musculoskeletal Health Intelligence and ActionS GP Study. The model was utilised to estimate the mean (with 95%CI's) cost and carbon output per MSK consulter, while also examining variations at two levels: (a) the Primary Care Network (PCN), and (b) the consulter's index MSK pain site. Results: One thousand eight hundred seventy‐five individuals from 30 NHS primary care practices across 13 PCNs were eligible for EHR and survey data analysis. The mean carbon and cost output per person (over 6 months) was 46.91 kg CO2e (95% CIs; 45.02, 48.81 kg CO2e) and £182.65 (95% CIs; £178.69, £190.62), respectively, with substantial variation observed across PCNs. The resource category with the highest carbon footprint was consistently pharmacological intervention across all PCNs. Individuals who consulted for multisite/widespread pain and back pain had the highest mean carbon and cost output respectively. Conclusion: This is the first study, we are aware of, that presents data on both the environmental and economic impact of the primary care of non‐inflammatory MSK pain. Future work should focus on benchmarking the cost and carbon output of MSK care pathways and standardising methods that are implemented to influence sustainable practice and policy development
Providing inclusive care and empowering people with dementia as a clinical pharmacist: a qualitative study of clinical pharmacist’s experiences
Get PDFObjectives
Dementia is a growing global health concern, significantly impacting primary care settings, where the majority of care for people with dementia is provided. Underserved and vulnerable groups, who often face disparities in access to care are at greater risk of this strain. Clinical pharmacists are well-positioned to provide care but their potential contribution to enhancing person-centred and inclusive care for people with dementia is largely unexplored. The aims are to explore the views and experiences of primary care based clinical pharmacists in providing inclusive care to people with dementia in the community.
Method
We conducted 13 semi-structured interviews with primary care clinical pharmacists in England in 2023–2024, which were analysed using reflexive thematic analysis.
Results
Two overarching themes were developed from the interviews: 1) involving patients in decision-making, ensuring person-centered care and 2) the prevalence of health inequalities and the impact on patient care.
Conclusion
Taking a personalised and person-centred approach clinical pharmacists can engage with patients and carers in decision-making. This can empower people, particularly those from minoritised or disadvantaged groups, to take an active role in their care. This may help with medication adherence but also build trust, potentially leading to better quality and more equitable care. Personalised care should consider cultural beliefs and preferences to reduce misunderstandings or stigma and improve the overall experience for individuals, helping to reduce disparities
The Uptake of Urban Digital Twins in the Built Environment: A Pathway to Resilient and Sustainable Cities
Get PDFUrban Digital Twin (UDT) technology is increasingly recognised as a promising tool for designing and developing sustainable, resilient urban environments. Nonetheless, the current literature lacks a comprehensive understanding of UDTs' current applications in the built environment. Therefore, this study addresses the identified gap by analysing scholarly literature and industry reports connected to UDT implementations. The results of scientometric analysis revealed five key research fields including: (i) UDT for urban monitoring and controlling, (ii) UDT for smart urban planning, (iii) UDT for environmental management, (iv) UDT for decision-making, and (v) UDT for smart and sustainable cities. Further, this study analysed 10 industry reports on UDT technology to identify practical insights and evaluate industry-driven approaches for implementing UDT solutions in urban environments. Despite promising progress, the findings indicate the absence of a clear, structured process to facilitate consistent implementation, scalability, and interoperability in UDT technology. This further highlights the need for globally recognised guidelines and well-defined KPIs to fully realise its potential in urban environments. The study also presents a new classification model developed from analysing the research flow to elaborate on the main outcomes from five clusters towards UDT pathways. The new proposed model reintroduces the structure of UDT literature with a new flow to interpret and correlate the content identified in previous studies. Based on these insights, the study offers recommendations to support the advancement of UDT technology for building resilient, sustainable cities
Digital Twin Technology for Education, Training and Learning in Construction Industry: Implications for Research and Practice
Get PDFPurpose: This study explores the potential of Digital Twin (DT) technology to enhance education and training in the construction industry. It aims to provide a clear understanding of how DT can be applied for educational purposes and proposes a framework to facilitate the adoption of DT in construction training. Design/methodology/approach A systematic literature review was conducted to examine the current applications of DT technology in construction education and training. A total of 19 relevant studies were identified and analysed to evaluate the tools, technologies, educational objectives, and integration methods used in developing DT models for the construction sector. Based on this analysis, a conceptual framework was developed to guide the integration of DT technology into construction education, addressing gaps in the current literature and practices. Findings The analysis revealed a strong consensus on the effectiveness of DT technology in supporting education and training objectives within the construction industry. The study highlighted the fragmented nature of the current literature and proposed a comprehensive framework designed to facilitate the integration of DT in construction education. This framework offers a structured approach to bridging the gap between theoretical learning and real-world application. Originality/value The research presents a new systematic framework developed based on an in-depth review for utilizing DT in education, training and learning (ETL) processes in construction. The framework provides a novel and structured learning process to integrate theoretical knowledge with practical skills to support workforce development in the construction industry. This framework offers a structured roadmap for future research and practical applications
