Challenges of digital twin in high value manufacturing

Digital Twin (DT) is a dynamic digital representation of a real-world asset, process or system. Industry 4.0 has recognised DT as the game changer for manufacturing industries in their digital transformation journey. DT will play a significant role in improving consistency, seamless process development and the possibility of reuse in subsequent stages across the complete lifecycle of the product. As the concept of DT is novel, there are several challenges that exist related to its phase of development and implementation, especially in high value manufacturing sector. The paper presents a thematic analysis of current academic literature and industrial knowledge. Based on this, eleven key challenges of DT were identified and further discussed. This work is intended to provide an understanding of the current state of knowledge around DT and formulate the future research directions

Mothers working to prevent early stillbirth study (MiNESS 20–28):a case–control study protocol

Introduction: In the UK, 1600 babies die every year before, during or immediately after birth at 20–28 weeks’ gestation. This bereavement has a similar impact on parental physical and psychological well-being to late stillbirth (>28 weeks’ gestation). Improved understanding of potentially modifiable risk factors for late stillbirth (including supine going-to-sleep position) has influenced international clinical practice. Information is now urgently required to similarly inform clinical practice and aid decision-making by expectant mothers/parents, addressing inequalities in pregnancy loss between 20 and 28 weeks. Methods and analysis: This study focuses on what portion of risk of pregnancy loss 20–28 weeks’ gestation is associated with exposures amenable to public health campaigns/antenatal care adaptation. A case–control study of non-anomalous singleton baby loss (via miscarriage, stillbirth or early neonatal death) 20+0 to 27+6 (n=316) and randomly selected control pregnancies (2:1 ratio; n=632) at group-matched gestations will be conducted. Data is collected via participant recall (researcher-administered questionnaire) and extraction from contemporaneous medical records. Unadjusted/confounder-adjusted ORs will be calculated. Exposures associated with early stillbirth at OR≥1.5 will be detectable (p0.80) assuming exposure prevalence of 30%–60%. Ethics and dissemination: NHS research ethical approval has been obtained from the London—Seasonal research ethics committee (23/LO/0622). The results will be presented at international conferences and published in peer-reviewed open-access journals. Information from this study will enable development of antenatal care and education for healthcare professionals and pregnant people to reduce risk of early stillbirth. Trial registration number: NCT06005272

Embedding retrieval practice in undergraduate biochemistry teaching using PeerWise

Retrieval practice is an evidence‐based approach to teaching; here, we evaluate the use of PeerWise for embedding retrieval practice into summative assessment. PeerWise allows anonymous authoring, sharing, answering, rating, and feedback on peer‐authored multiple choice questions. PeerWise was embedded as a summative assessment in a large first‐year introductory biochemistry module. Engagement with five aspects of the tool was evaluated against student performance in coursework, exam, and overall module outcome. Results indicated a weak‐to‐moderate positive but significant correlation between engagement with PeerWise and assessment performance. Student feedback showed PeerWise had a polarizing effect; the majority recognized the benefits as a learning and revision tool, but a minority strongly disliked it, complaining of a lack of academic moderation and irrelevant questions unrelated to the module. PeerWise can be considered a helpful learning tool for some students and a means of embedding retrieval practice into summative assessment

A modified model for the Lobula Giant Movement Detector and its FPGA implementation

The Lobula Giant Movement Detector (LGMD) is a wide-field visual neuron located in the Lobula layer of the Locust nervous system. The LGMD increases its firing rate in response to both the velocity of an approaching object and the proximity of this object. It has been found that it can respond to looming stimuli very quickly and trigger avoidance reactions. It has been successfully applied in visual collision avoidance systems for vehicles and robots. This paper introduces a modified neural model for LGMD that provides additional depth direction information for the movement. The proposed model retains the simplicity of the previous model by adding only a few new cells. It has been simplified and implemented on a Field Programmable Gate Array (FPGA), taking advantage of the inherent parallelism exhibited by the LGMD, and tested on real-time video streams. Experimental results demonstrate the effectiveness as a fast motion detector

Towards information management framework for digital twin in aircraft manufacturing

Aircraft manufacturing industries often evolve in the ecosystem of complex designs and manufacturing processes associated with large volume of information generated along the lifecycle. Digital Twin (DT) technology has the potential of leveraging such information to provide useful insights benefiting the overall business in many ways. Information Management (IM) for DT is still an ongoing challenge for many industries, thus leaving a considerable research gap. In this paper, an IM framework for DT in the aircraft manufacturing sector is proposed. The key phases and elements of IM are discussed on which the framework is constructed. The potential application of the framework along aircraft lifecycle is further discussed. The framework not only provides an effective approach to managing information but also opens new research prospects in DT domain

Data management for developing digital twin ontology model

Digital Twin (DT) is the imitation of the real world product, process or system. Digital Twin is the ideal solution for data-driven optimisations in different phases of the product lifecycle. With the rapid growth in DT research, data management for digital twin is a challenging field for both industries and academia. The challenges for DT data management are analysed in this article are data variety, big data & data mining and DT dynamics. The current research proposes a novel concept of DT ontology model and methodology to address these data management challenges. The DT ontology model captures and models the conceptual knowledge of the DT domain. Using the proposed methodology, such domain knowledge is transformed into a minimum data model structure to map, query and manage databases for DT applications. The proposed research is further validated using a case study based on Condition-Based Monitoring (CBM) DT application. The query formulation around minimum data model structure further shows the effectiveness of the current approach by returning accurate results, along with maintaining semantics and conceptual relationships along DT lifecycle. The method not only provides flexibility to retain knowledge along DT lifecycle but also helps users and developers to design, maintain and query databases effectively for DT applications and systems of different scale and complexitie

Papers Dietary fat intake and prevention of cardiovascular disease: systematic review

Abstract Objective To assess the effect of reduction or modification of dietary fat intake on total and cardiovascular mortality and cardiovascular morbidity. Design Systematic review. Data sources Cochrane Library, Medline, Embase, CAB abstracts, SIGLE, CVRCT registry, and biographies were searched; trials known to experts were included. Included studies Randomised controlled trials stating intention to reduce or modify fat or cholesterol intake in healthy adult participants over at least six months. Inclusion decisions, validity, and data extraction were duplicated. Meta-analysis (random effects methodology), meta-regression, and funnel plots were performed. Results 27 studies (30 902 person years of observation) were included. Alteration of dietary fat intake had small effects on total mortality (rate ratio 0.98; 95% confidence interval 0.86 to 1.12). Cardiovascular mortality was reduced by 9% (0.91; 0.77 to 1.07) and cardiovascular events by 16% (0.84; 0.72 to 0.99), which was attenuated (0.86; 0.72 to 1.03) in a sensitivity analysis that excluded a trial using oily fish. Trials with at least two years' follow up provided stronger evidence of protection from cardiovascular events (0.76; 0.65 to 0.90). Conclusions There is a small but potentially important reduction in cardiovascular risk with reduction or modification of dietary fat intake, seen particularly in trials of longer duration

OPTIMA: A prospective randomized trial to validate the predictive utility and cost-effectiveness of gene expression test-directed chemotherapy decisions in early breast cancer

Background: Multi-parameter gene expression assays (MPAs) are widely used to estimate individual patient residual risk in hormone-sensitive HER2-negative node-negative early breast cancer, allowing patients with low risk to safely avoid chemotherapy. Evidence for MPA use in node-positive breast cancer is limited. OPTIMA (Optimal Personalised Treatment of early breast cancer usIng Multi-parameter Analysis) aims to validate MPA’s as predictors of chemotherapy sensitivity in a largely node-positive breast cancer population

Getting to Net Zero Working Group : Energy Networks Snap-Shot Report

The electricity gas and heat networks are finding it necessary to increase their ad hoc interactions as they develop their contribution to the net zero1 targets for green house gases for the UK and Scotland. The organisations involved in the “Getting to Net Zero” working group are all directly engaged in the energy sector encountering day-to-day challenges around how to include “getting to net zero” in their operations. The working group met to consider the progress of networks to date in addressing net zero and to identify immediate actions that would remove barriers to progress. This snap shot report summarises the working group findings