Due to high penetration of renewable generation in power systems, and the need to provide the interface between distributed energy resources, the split-source inverter (SSI) provides both the boosting and the conversion capabilities in one single-stage. Also the need for converter-based artificial inertia has become more important. In this paper a model-predictive control (MPC) based on virtual synchronous generator (VSG) algorithm for a parallel-connected three-phase SSI is proposed for conceiving regulation of local voltage and realizing power-sharing of an islanded AC microgrid (MG). A virtual synchronous generator (VSG) is deployed to ensure active-power-sharing and provide inertia-emulation and hence reducing the rate of change of frequency (RoCoF) that results from sudden load change. To accomplish a simple control construction, quick dynamic performance, high stability, and enhanced current limitation, a finite-set MPC (FS-MPC) is used. The analysis and modeling of the proposed technique are presented in detail. A simulation model is used to investigate the proposed system performance.
Background and objective: Diabetes is a disease that requires early detection and early treatment, and complications are likely to occur in late stages of the disease, threatening the life of patients. Therefore, in order to diagnose diabetic patients as early as possible, it is necessary to establish a model that can accurately predict diabetes. Methodology: This paper proposes an ensemble learning framework: KFPredict, which combines multi-input models with key features and machine learning algorithms. We first propose a multi-input neural network model (KF_NN) that fuses key features and uses a decision tree-based selection recursive feature elimination algorithm and correlation coefficient method to screen out the key feature inputs and secondary feature inputs in the model. We then ensemble KF_NN with three machine learning algorithms (i.e., Support Vector Machine, Random Forest and K-Nearest Neighbors) for soft voting to form our predictive classifier for diabetes prediction. Results: Our framework demonstrates good prediction results on the test set with a sensitivity of 0.85, a specificity of 0.98, and an accuracy of 93.5%. Compared with the single prediction method KFPredict, the accuracy is up to 18.18% higher. Concurrently, we also compared KFPredict with the existing prediction methods. It still has good prediction performance, and the accuracy rate is improved by up to 14.93%. Conclusion: This paper constructs a diabetes prediction framework that combines multi-input models with key features and machine learning algorithms. Taking tthe PIMA diabetes dataset as the test data, the experiment shows that the framework presents good prediction results.
Political theory is interested in the misrecognition of identity because it impacts individuals' autonomy in their self‐definition and thus their ability to articulate and pursue identity‐related interests. Here, we explore minority group members' experiences of being seen in terms that do not accord with their self‐definition. Our data are qualitative, gathered through walking interviews with 24 Muslims in Scotland. Focusing on interactions in which they reported discrepancies between how they and others saw them, we differentiate four forms of misrecognition: (1) having the meaning of a valued identity (i.e., one's Muslim identity) defined by others in ways that one judges inaccurate and inappropriate; (2) having one's membership of a valued community (e.g., as a member of Scottish society) denied or rejected; (3) having one's identity (i.e., one's Muslim identity) overlooked such that one's distinctive identity‐related needs are not taken into account; (4) being seen in terms of just one of one's many social identities (i.e., one's Muslim identity) such that other identities (judged more situationally relevant) are ignored. This empirically grounded typology contributes to wider debates about the forms of identity (mis)recognition and their political implications.
This paper investigates the relationship between board overconfidence and mergers and acquisitions (M&A) performance based on 754 M&A deals in the UK from 2002 to 2018. Employing three proxies to measure overconfidence, namely, fraction of male directors on the board, multiple acquisitions and merger characteristics, our results suggest that a higher fraction of male directors on the board and multiple acquisitions lead to poor M&A performance. The results also show that multiple acquirers’ deals generate higher returns than subsequent deals and this is due to self-attribution bias. In terms of merger characteristics, this study has found that, when overconfident acquirers use cash as the method of payment or when they embark on diversifying M&A, it leads to poor M&A performance. The results are robust across both univariate and multivariate analyses and also across alternate measures of post-merger performance. The findings of this study have important policy implication with regard to the ratio of male directors, number of acquisitions and the method of payment.
The comprehensive analysis of social identity cannot simply focus on individuals' cognitive self‐definition. Rather it should also theorize the social conditions that affect individuals' opportunities to act in terms of those self‐definitions. We argue that the social distancing interventions associated with Covid‐19 provide an opportunity to explore the significance of otherwise taken‐for‐granted social factors which routinely support and sustain individuals' identity enactments. Using qualitative data gathered with 20 members of the Scottish Muslim community (19 diary entries and 20 post‐diary interviews), we explore their experiences of restricted access to community‐relevant social spaces (e.g., mosques and prayer rooms). Our analysis shows that while these regulations could result in new opportunities for Muslims' religious identity enactments, they also impeded their abilities to act in terms of their religious identification. Addressing such impediments, we develop our understanding of the contextual factors that shape individuals' abilities to enact identity‐defining norms and values.
Background: Previous studies show the uptake of biannual ultrasound (US) surveillance in patients with cirrhosis is suboptimal. Here, our goal was to understand in broader terms how surveillance is being delivered to cirrhosis patients with cured hepatitis C in the UK. Methods: Hepatitis C cirrhosis patients achieving a sustained-viral-response (SVR) to antiviral therapies were identified from the national Hepatitis-C-Research-UK resource. Data on (i) liver/abdominal US examinations, (ii) HCC diagnoses; and (iii) HCC curative treatment, were obtained through record-linkage to national health registries. The rate of US uptake was calculated by dividing the number of US episodes by follow-up time. Results: 1,908 cirrhosis patients from 31 liver centres were followed for 3.8 (IQR:3.4-4.9) years. 10,396 liver/abdominal USs were identified. The proportion with biannual US was 19% in the first 3 years after SVR and 9% for all follow-up years. Higher uptake of biannual US was associated with attending a liver transplant centre; older age and cirrhosis decompensation. Funnel plot analysis indicated significant inter-centre variability in biannual US uptake, with 6/29 centres outside control limits. Incident HCC occurred in 133 patients, of which 49/133 (37%) were treated with curative intent. The number of US episodes in the two years prior to HCC diagnosis was significantly associated with higher odds of curative-intent treatment (aOR:1.53;95%CI: 1.12-2,09; P=0.007). Conclusions: This study provides novel data on the cascade of care for HCC in the UK. Our findings suggest biannual US is poorly targeted, inefficient and is not being delivered equitably to all patients.
In rheumatoid arthritis, the emergence of anti-citrullinated autoimmunity is associated with HLA-antigen-T cell receptor complexes. The precise mechanisms underpinning this breach of tolerance are not well understood. Porphyromonas gingivalis expresses an enzyme capable of non-endogenous C-terminal citrullination with potential to generate citrullinated autoantigens. Here we document how C-terminal citrullination of ovalbumin peptide323-339 alters the interaction between antigen-presenting cells and OTII T cells to induce functional changes in responding T cells. These data reveal that C-terminal citrullination is sufficient to breach T cell peripheral tolerance in vivo and reveal the potential of C-terminal citrullination to lower the threshold for T cell activation. Finally, we demonstrate a role for the IL-2/STAT5/CD25 signalling axis in breach of tolerance. Together, our data identify a tractable mechanism and targetable pathways underpinning breach of tolerance in rheumatoid arthritis and provide new conceptual insight into the origins of anti-citrullinated autoimmunity.
The importance of sufficient moderate-to-vigorous physical activity as a key component of a healthy lifestyle is well established, as are the health risks associated with high levels of sedentary behaviour. However, many people with RA do not undertake sufficient physical activity and are highly sedentary. To start addressing this, it is important to be able to carry out an adequate assessment of the physical activity levels of individual people in order that adequate steps can be taken to promote and improve healthy lifestyles. Different methods are available to measure different aspects of physical activity in different settings. In controlled laboratory environments, respiratory gas analysis can measure the energy expenditure of different activities accurately. In free-living environments, the doubly labelled water method is the gold standard for identifying total energy expenditure over a prolonged period of time (>10 days). To assess patterns of physical activity and sedentary behaviour in daily life, objective methods with body-worn activity monitors using accelerometry are superior to self-reported questionnaire- or diary-based methods.
Background Movement behaviours (eg, sedentary behaviour (SB), moderate and vigorous physical activity (MVPA), light intensity physical activity (LIPA) and sleep) are linked to cognition, yet the relative importance of each component is unclear, and not yet explored with compositional methodologies. Objective To (i) assess the associations of different components of daily movement and participant’s overall cognition, memory and executive function, and (ii) understand the relative importance of each individual component for cognition. Methods The 1970 British Cohort Study (BCS70) is a prospective birth cohort study of UK-born adults. At age 46, participants consented to wear an accelerometer device and complete tests of verbal memory and executive function. Compositional linear regression was used to examine cross-sectional associations between 24-hour movement behaviours and standardised cognition scores. Isotemporal substitution was performed to model the effect of reallocating time between components of daily movement on cognition. Results The sample comprised 4481 participants (52% female). Time in MVPA relative to SB, LIPA and sleep was positively associated with cognition after adjustments for education and occupational physical activity, but additional adjustment for health status attenuated associations. SB relative to all other movements was robustly positively associated with cognition. Modelling time reallocation between components revealed an increase in cognition centile after MVPA theoretically replaced 9 min of SB (OR=1.31; 95% CI 0.09 to 2.50), 7 min of LIPA (1.27; 0.07 to 2.46) or 7 min of sleep (1.20; 0.01 to 2.39). Conclusions Relative to time spent in other behaviours, greater MVPA and SB was associated with higher cognitive scores. Loss of MVPA time, given its smaller relative amount, appears most deleterious. Efforts should be made to preserve MVPA time, or reinforce it in place of other behaviours.
Pneumatic conveying is a well‐established technology within a wide range of industrial sectors. This chapter outlines the fundamentals of gas–solids flow in pipelines and details three simulation methods: single and two fluid models and combined CFD–DEM. The principal theories and equations commonly available in commercial off‐the‐self and open‐source software packages are given. Example results of pressure drop, volume fraction, etc. are provided.
The acceptability and feasibility of large-scale testing with lateral flow tests (LFTs) for clinical and public health purposes has been demonstrated during the COVID-19 pandemic. LFTs can detect analytes in a variety of samples, providing a rapid read-out, which allows self-testing and decentralized diagnosis. In this Review, we examine the changing LFT landscape with a focus on lessons learned from COVID-19. We discuss the implications of LFTs for decentralized testing of infectious diseases, including diseases of epidemic potential, the ‘silent pandemic’ of antimicrobial resistance, and other acute and chronic infections. Bioengineering approaches will play a key part in increasing the sensitivity and specificity of LFTs, improving sample preparation, incorporating nucleic acid amplification and detection, and enabling multiplexing, digital connection and green manufacturing, with the aim of creating the next generation of high-accuracy, easy-to-use, affordable and digitally connected LFTs. We conclude with recommendations, including the building of a global network of LFT research and development hubs to facilitate and strengthen future diagnostic resilience. The feasibility of large-scale testing with lateral flow tests has been demonstrated in the COVID-19 pandemic. This Review examines lessons learned from the COVID-19 pandemic to inform the design and bioengineering of next-generation lateral flow tests to strengthen future diagnostic resilience. Lateral flow tests (LFTs) were adopted at an unprecedented scale during the COVID-19 pandemic, enabling access to testing beyond healthcare settings.Only 0.4% of the 3 billion COVID-19 tests performed through to mid-2022 were conducted in low-income regions, raising ethical concerns and constraining our collective ability to respond to a pandemic.Key barriers to COVID-19 LFT development and adoption include lack of access to well characterized samples, limited accuracy, lack of connectivity, lack of evidence of cost-effectiveness, regulatory delays and centralized manufacturing capabilities.LFTs could also play an important part in the detection of other diseases of epidemic potential and antimicrobial resistance.Bioengineering approaches, such as the use of nano- and quantum materials, nucleic-acid-based LFTs, CRISPR and machine learning, will improve the sensitivity, specificity, multiplexing and connectivity features of LFTs.We recommend investing in an international LFT research and development hub network to spearhead the development of a pipeline of innovative bioengineering approaches to design next-generation LFTs. Lateral flow tests (LFTs) were adopted at an unprecedented scale during the COVID-19 pandemic, enabling access to testing beyond healthcare settings. Only 0.4% of the 3 billion COVID-19 tests performed through to mid-2022 were conducted in low-income regions, raising ethical concerns and constraining our collective ability to respond to a pandemic. Key barriers to COVID-19 LFT development and adoption include lack of access to well characterized samples, limited accuracy, lack of connectivity, lack of evidence of cost-effectiveness, regulatory delays and centralized manufacturing capabilities. LFTs could also play an important part in the detection of other diseases of epidemic potential and antimicrobial resistance. Bioengineering approaches, such as the use of nano- and quantum materials, nucleic-acid-based LFTs, CRISPR and machine learning, will improve the sensitivity, specificity, multiplexing and connectivity features of LFTs. We recommend investing in an international LFT research and development hub network to spearhead the development of a pipeline of innovative bioengineering approaches to design next-generation LFTs.
Introduction: High alcohol availability is related to increased alcohol consumption and harms. Existing quantitative research provides potential explanations for this relationship but there is little understanding of how people experience local alcohol availability. This is the first review to synthesise qualitative research exploring the relationship between alcohol availability and other factors in local alcohol environments. Methods: The scoping review includes qualitative studies exploring community-level alcohol availability and other factors, facilitating the purchase and consumption of alcohol. We included studies focusing on children and adolescents as well as adults. Study findings were brought together using thematic analysis and the socio-environmental context model, which explains how certain environments may facilitate drinking. Results: The review includes 34 articles. The majority of studies were conducted since 2012. Most studies were conducted in the United Kingdom, Australia and South Africa. The physical availability of alcohol and proximity to local amenities and temporal aspects, like late night opening hours, may be linked to social factors, such as normalisation of drinking and permissive drinking environments. The review highlights the importance of social and cultural factors in shaping interactions with local alcohol environments. Discussion and conclusion: This qualitative scoping review advances understanding of the pathways linking alcohol availability and alcohol harms by showing that availability, accessibility and visibility of alcohol may contribute towards permissive drinking environments. Further research is needed to better understand how people experience alcohol availability in their local environment and how this can inform alcohol control policies.
This paper reviews options for reducing harm from pharmaceuticals that are known to cause adverse impacts by their presence in the environment. It reviews recent global and EU policy development, which could go further in recognising and addressing the issue in a global context. It considers green chemistry, which can help clean up production processes, but holds only long‐term promise for creating ‘green’ alternatives. It explores the potential of health promotion and disease prevention, which can contribute significantly to a reduction of the disease burden and thus the need for medicines, both for infectious and for non‐communicable disease. Eco‐directed sustainable prescribing practices are reviewed, which have been adopted successfully to reduce the use of harmful pharmaceuticals. We note recent developments in medicines optimisation and precision medicine, which hold promise for improving patient outcomes, saving costs and reducing pharmaceutical use, through individually tailored prescribing whereby the patient co‐decides their therapy. Waste prevention through re‐use or redistribution is beginning to find public support, whilst ‘take‐back’ waste disposal schemes set up via extended producer responsibility systems have achieved high returns. Finally, the paper summarises preferred advanced wastewater technologies, including also innovative low‐cost, low‐energy options. In summary, whilst end‐of‐pipe options have a role to play, particularly for highly‐concentrated wastewaters, solutions further up the medicinal chain and disease prevention interventions, informed by a broad view of health and health care, are needed in order to pursue a much greater potential reduction of pharmaceuticals in the environment than can be achieved by end‐of‐pipe solutions alone. This article is protected by copyright. All rights reserved. Environ Toxicol Chem 2023;00:0–0.
Previous studies of emoji effects on text sentiment demonstrate mixed findings. Further, these studies are limited by confounds, e.g., underlying text sentiment, lack of ecological validity. We considered emoji effects on the emotional valence of affectively neutral English-language text messages. We additionally considered differences across US-American, British, and Danish participants. 217 participants considered screenshots of question-and-response text message exchanges with/without emoji, in a 4 (emoji type: no emoji, negative, neutral, positive) × 3 (nationality: American, British, Danish) mixed-factors design. Cumulative link mixed-effects models demonstrated that messages + negative emoji were rated more-negatively than any other emoji conditions. Responses + positive emoji were rated more-positively than any other emoji condition. Responses + neutral emoji and responses without emoji were perceived as equally emotive. There was no emoji type × nationality interaction, suggesting that emoji effects were consistent across participants. Findings are considered viz linguistic processing, social interactions, education, marketing, and public health interventions.
Surgical intervention is required to successfully treat severe, large-gap (≥4 cm) peripheral nerve injuries. However, all existing treatments have shortcomings and an alternative to the use of autologous nerves is needed. Human and porcine nerves are physiologically similar, with comparable dimensions and architecture, presence and distribution of Schwann cells, and conserved features of the extracellular matrix (ECM). We report the repair of fully transected radial nerves in 10 Rhesus Macaques using viable, whole sciatic nerve from genetically engineered (GalT-KO), designated pathogen free (DPF) porcine donors. This resulted in the regeneration of the transected nerve, and importantly, recovery of wrist extension function, distal muscle reinnervation, and recovery of nerve conduction velocities and compound muscle action potentials similar to autologous controls. We also demonstrate the absence of immune rejection, systemic porcine cell migration, and detectable residual porcine material. Our preliminary findings support the safety and efficacy of viable porcine nerve transplants, suggest the interchangeable therapeutic use of cross-species cells, and highlight the broader clinical potential of xenotransplantation.
Following its initial identification on December 31, 2019, COVID-19 quickly spread around the world as a pandemic claiming more than six million lives. An early diagnosis with appropriate intervention can help prevent deaths and serious illness as the distinguishing symptoms that set COVID-19 apart from pneumonia and influenza frequently don't show up until after the patient has already suffered significant damage. A chest X-ray (CXR), one of many imaging modalities that are useful for detection and one of the most used, offers a non-invasive method of detection. The CXR image analysis can also reveal additional disorders, such as pneumonia, which show up as anomalies in the lungs. Thus these CXRs can be used for automated grading aiding the doctors in making a better diagnosis. In order to classify a CXR image into the Negative for Pneumonia, Typical, Indeterminate, and Atypical, we used the publicly available CXR image competition dataset SIIM-FISABIO-RSNA COVID-19 from Kaggle. The suggested architecture employed an ensemble of EfficientNetv2-L for classification, which was trained via transfer learning from the initialised weights of ImageNet21K on various subsets of data (Code for the proposed methodology is available at: https://github.com/asadkhan1221/siim-covid19.git). To identify and localise opacities, an ensemble of YOLO was combined using Weighted Boxes Fusion (WBF). Significant generalisability gains were made possible by the suggested technique's addition of classification auxiliary heads to the CNN backbone. The suggested method improved further by utilising test time augmentation for both classifiers and localizers. The results for Mean Average Precision score show that the proposed deep learning model achieves 0.617 and 0.609 on public and private sets respectively and these are comparable to other techniques for the Kaggle dataset.
Background Evidence for benefits of physical activity after stroke is unequivocal. However, many people with stroke are inactive, spending > 80% of waking hours sedentary even when they have physical capacity for activity, indicating barriers to physical activity participation that are not physical. WeWalk is a 12-week person-centred dyadic behaviour change intervention in which a person with stroke (PWS) and a walking buddy form a dyad to work together to support the PWS to increase their physical activity by walking outdoors. This pilot study examined the feasibility of recruiting dyads, explored their perceptions of acceptability and their experiences using WeWalk, to identify required refinements before progression to a clinical trial. Methods Design: A single-arm observational pilot study with qualitative evaluation. Intervention: WeWalk involved facilitated face-to-face and telephone sessions with a researcher who was also a behaviour change practitioner, supported by intervention handbooks and diaries, in which dyads agreed walking goals and plans, monitored progress, and developed strategies for maintaining walking. Evaluation: Descriptive data on recruitment and retention were collected. Interview data were collected through semi-structured interviews and analysed using thematic analysis, guided by a theoretical framework of acceptability. Results We recruited 21 dyads comprising community dwelling PWS and their walking buddies. Ten dyads fully completed WeWalk before government-imposed COVID-19 lockdown. Despite lockdown, 18 dyads completed exit interviews. We identified three themes: acceptability evolves with experience, mutuality, and person-centredness with personally relevant tailoring. As dyads recognised how WeWalk components supported walking, perceptions of acceptability grew. Effort receded as goals and enjoyment of walking together were realised. The dyadic structure provided accountability, and participants’ confidence developed as they experienced physical and psychological benefits of walking. WeWalk worked best when dyads exhibited relational connectivity and mutuality in setting and achieving goals. Tailoring intervention components to individual circumstances and values supported dyads in participation and achieving meaningful goals. Conclusion Recruiting dyads was feasible and most engaged with WeWalk. Participants viewed the dyadic structure and intervention components as acceptable for promoting outdoor walking and valued the personally tailored nature of WeWalk. Developing buddy support skills and community delivery pathways are required refinements. ISCTRN number: 34488928.
Nature-based solutions (NbS) can be beneficial to help human communities build resilience to climate change by managing and mitigating related hydro-meteorological hazards (HMHs). Substantial research has been carried out in the past on the detection and assessment of HMHs and their derived risks. Yet, knowledge on the performance and functioning of NbS to address these hazards is severely lacking. The latter is exacerbated by the lack of practical and viable approaches that would help identify and select NbS for specific problems. The EU-funded OPERANDUM project established seven Open-Air Laboratories (OALs) across Europe to co-develop, test, and generate an evidence base from innovative NbS deployed to address HMHs such as flooding, droughts, landslides, erosion, and eutrophication. Herein, we detail the original approaches that each OAL followed in the process of identifying and selecting NbS for specific hazards with the aim of proposing a novel, generic framework for selecting NbS. We found that the process of selecting NBS was overall complex and context-specific in all the OALs, and it comprised 26 steps distributed across three stages: (i) Problem recognition , (ii) NbS identification, and (iii) NbS selection. We also identified over 20 selection criteria which, in most cases, were shared across OALs and were chiefly related to sustainability aspects. All the identified NbS were related to the regulation of the water cycle, and they were mostly chosen according to three main factors: (i) hazard type, (ii) hazard scale, and (iii) OAL size. We noticed that OALs exposed to landslides and erosion selected NbS capable to manage water budgets within the soil compartment at the local or landscape scale, while OALs exposed to floods, droughts, and eutrophication selected approaches to managing water transport and storage at the catchment scale. We successfully portrayed a synthesis of the stages and steps followed in the OALs' NbS selection process in a framework. The framework, which reflects the experiences of the stakeholders involved, is inclusive and integrated, and it can serve as a basis to inform NbS selection processes whilst facilitating the organisation of diverse stakeholders working towards finding solutions to natural hazards. We animate the future 2 development of the proposed framework by integrating financial viability steps. We also encourage studies looking into the implementation of the proposed framework through quantitative approaches integrating multi-criteria analyses.
The bone marrow (BM) is the primary site of adult haematopoiesis, where stromal elements (e.g., fibroblasts, mesenchymal stem cells/MSCs) work in concert to support blood cell development. However, the establishment of an abnormal clone can lead to a blood malignancy such as acute myeloid leukaemia (AML). Despite our increased understanding of the pathophysiology of the disease, patient survival remains suboptimal, mainly driven by the development of therapy resistance. In this review, we highlight the importance of BM fibroblasts and MSCs in health and AML and their impact on patient prognosis. We discuss how stromal elements reduce the killing effects of therapies via a combination of contact‐dependent (e.g., integrins) and contact‐independent (i.e., secreted factors) mechanisms, accompanied by the establishment of an immunosuppressive microenvironment. Importantly, we underline the challenges of therapeutically targeting the BM stroma to improve AML patient outcomes, due to the inherent heterogeneity of stromal cell populations.
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