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A sparse optimization approach to infinite infimal convolution regularization
Get PDFIn this paper we introduce the class of infinite infimal convolution functionals and apply these functionals to the regularization of ill-posed inverse problems. The proposed regularization involves an infimal convolution of a continuously parametrized family of convex, positively one-homogeneous functionals defined on a common Banach space . We show that, under mild assumptions, this functional admits an equivalent convex lifting in the space of measures with values in . This reformulation allows us to prove well-posedness of a Tikhonov regularized inverse problem and opens the door to a sparse analysis of the solutions. In the case of finite-dimensional measurements we prove a representer theorem, showing that there exists a solution of the inverse problem that is sparse, in the sense that it can be represented as a linear combination of the extremal points of the ball of the lifted infinite infimal convolution functional. Then, we design a generalized conditional gradient method for computing solutions of the inverse problem without relying on an a priori discretization of the parameter space and of the Banach space . The iterates are constructed as linear combinations of the extremal points of the lifted infinite infimal convolution functional. We prove a sublinear rate of convergence for our algorithm and apply it to denoising of signals and images using, as regularizer, infinite infimal convolutions of fractional-Laplacian-type operators with adaptive orders of smoothness and anisotropies
Global Sensitivity Analysis of Helmholtz Coils for Enhanced Homogeneous Magnetic Field of Electromagnetic Flowmeters
Get PDFHelmholtz coils are widely used to generate homogeneous magnetic fields. Various parameters influence the magnetic field strength and homogeneity, including coil shape, size, spacing, winding layers, winding turns, and axial and radial gaps between windings. Previous researches have partially examined these parameters through local sensitivity analysis, where each parameter is varied independently while others are held constant. However, such studies often have limited applicability due to the interdependence of parameters including coil size, spacing, and windings. This work employs a new global sensitivity analysis, reciprocal optimum solution, to investigate the interconnections between these parameters and their effects on magnetic flux density and field homogeneity. This approach eliminates the need to manually optimize variable ranges and mitigates the issues of randomness, uncertainty, and slow convergence by producing both deterministic formulas and a blueprint for designing Helmholtz coils with homogeneous magnetic fields. Using this method, we produced open-source Helmholtz coils development software. This enables users to obtain design parameters for Helmholtz coils for a required homogeneous magnetic field domain, when provided either its cross-sectional diameter or the coil spacing required for the device.</p
Topology Optimization of a Fully Superconducting Air-core Motor for Electric Aircraft
Get PDFSuperconducting motors have great potential to achieve high power density and high efficiency in electric propulsion systems for aerospace applications. A new lightweight air-core topology for a fully superconducting motor is designed and optimized. The stator is made of yttrium barium copper oxide (YBCO) cable and has two sets of windings. These are spatially displaced radially and have a specific circumferential offset to cancel certain harmonics. The rotor is also constructed with YBCO cable. This paper focuses on the optimization of superconducting motor windings in terms of winding harmonics. The topology of the stator and rotor is designed through a series of analytical calculations and comparisons. Four superconducting motor topologies with different pole numbers are presented with detailed design for the stator and rotor windings. An illustration of how the harmonics reduction design methodology is applied is included. The analytical design is verified by a 2D finite element model of the superconducting motor using the COMSOL software.</p
Mapping commercial practices of the pesticide industry to shape science and policymaking:a scoping review
Get PDFThere is a growing body of evidence for how health harming industries (HHIs) engage in similar practices to influence science and policymaking. However, limited attention has been paid to the pesticide industry within the commercial determinants of health (CDOH) field. We conducted a scoping review to map practices adopted by the pesticide industry to influence science and policymaking and to assess the breadth and focus of the associated literature. We included 31 documents and categorized the extracted data using a typology of commercial practices. The documents described how major pesticide companies, and their trade bodies, have acted to influence science and maintain favourable regulatory environments while undermining the credibility of researchers and agencies that publish findings threatening to their commercial interests. A large proportion of the literature consists of historical analyses, narrative reviews, commentaries/perspective pieces, and investigative reports published in the grey literature, predominantly informed by analysis of internal industry documents and freedom of information requests. Most studies focus on high-income settings. There were a limited number of primary peer-reviewed empirical studies that explicitly aimed to study the practices of the pesticide industry from a CDOH perspective. However, our findings show that major pesticide companies adopt political and scientific practices highly similar to other HHIs. The review shows a critical need for research on the pesticide industry’s current practices in low- and middle-income countries where the negative impacts of its activities on health and the environment are likely to be more marked
A randomised feasibility trial comparing group and individual format Groups for Health interventions for loneliness in people who experience psychosis
Get PDFObjectives: Loneliness in people who experience psychosis is common and associated with poor mental health. In this randomised trial, we tested the feasibility and acceptability of an adapted Groups for Health (G4H) intervention for loneliness, delivered in group or individual format. Design: Mixed methods, two-arm feasibility randomised controlled trial. Methods: Forty individuals who self-identified as having psychosis were recruited from UK mental health care services, recovery colleges and charities. G4H was modified for people with psychosis, with participants randomised to receive the intervention delivered via group (N = 20) or individual (N = 20) format. The primary outcomes related to trial acceptability and feasibility. Exploratory repeated measures ANOVAs and t-tests evaluated differences between formats over time in loneliness, wellbeing and possible mechanisms of change including social identification, identity integration and perceived in-group and out-group empathy. Measures were completed at baseline, end of treatment and 1- and 6-month follow-up. Results: Recruitment, retention and trial acceptability ratings for both group and individual formats of G4H were acceptable to good. No participants reported experiencing a serious adverse event. Exploratory ANOVAs indicated no differences related to format but positive change in key variables of loneliness, wellbeing, social identification and identity integration over time. T-tests for loneliness indicated that this change was step-wise from baseline, through end of treatment to 1-month follow-up. Conclusions: G4H is a feasible intervention for people with psychosis who identify as lonely and it can be delivered in either group or individual formats. This feasibility trial provides support for a future full randomised controlled trial.</p
VR Cybersickness Classification Using Machine Learning Models on Open-Access EEG Datasets from the Human Vestibular Network
Get PDFThis paper addresses key challenges in EEG-based cybersickness classification using machine learning (ML) models. Despite significant research in this area four critical issues remain unresolved: 1) the availability of open-access EEG datasets; 2) imbalanced data distribution; 3) limited generalizability testing, and 4) insufficient exploration of personalized EEG data.</p
Lift Recovery in Post-Stall Region
Get PDFAccurate prediction of airfoil performance through stall underpins the successful design of modern proprotors and wind turbines, which can exhibit significantly stalled flow during normal operation. Existing stall models typically employ two-region approaches: coupling pre-stall data with semi-empirical deep-stall models. None of the current low-order methods accurately captures the initial drop and recovery of lift in the post-stall regime. This paper proposes a novel three-region lift model, which accurately predicts the regions of stall, recovery, and deepstall across a range of airfoils and Reynolds numbers. This is achieved through the inclusion of a semi-empirical implementation of Rayleigh’s flat plate theory. The model is directly compared against published alternatives and integrated into a low-order solver. The inclusion of the new model results in thrust prediction improvements across the operational range when compared to current two-region approaches of 7% for a small-scale rotor. It is also shown to be up to 74% more accurate in the initial drop and recovery regions than other published methods for an isolated airfoil. In all scenarios, the model is shown to produce a more physical representation of an airfoil through stall, which has great potential for improving the fidelity of performance, structural, and acoustic simulations.</p
The experience of imposed digitalization of education provision across sectors:Autoethnographic experiences through a Foucauldian lens
Get PDFWorldwide, over the course of the global COVID-19 pandemic, major disruption to schooling and education provision at all levels has presented governments, school leaders, faculty, teachers, parents and students with a host of challenges. These challenges also brought increased attention to how ill-prepared education institutions were to ‘pivot’ from face-to-face teaching and learning to online forms of remote provision. In this paper, we will explore how this imposed digitalization affected leadership and governance from the experience of the various stakeholders involved. In exploring the imposed digitalization of education provision across educational sectors in two different geographical and cultural contexts, Malta and Turkey, we utilize a critical autoethnography to question how power and knowledge reflexively generated our actions and interpretations, as well as critically reflect on our own practice as researchers. As researchers, through reflexivity and introspection, we engage in self-study as participants, recognizing our interpretation of facts as shaped by our sociocultural circumstances. Regarding education institutions as a key test site for digital technologies and a ripe field for critical educational research, we thus explore the leadership and governance experiences of this imposed digitalization and its ensuing effects through the prism of social theory, specifically a Foucauldian perspective using his ‘trident’ of problematization, critique and scepticism. Our autoethnographic exploration of imposed digitalization across distinct education sectors in diverse cultural contexts has implications for theory, policy and practice
Advances in Organic Small Molecule-Based Fluorescent Probes for Precision Detection of Liver Diseases:A Perspective on Emerging Trends and Challenges
Get PDFLiver disease poses a significant challenge to global health, and its early diagnosis is crucial for improving treatment outcomes and patient prognosis. Since fluctuation of key biomarkers during the onset and progression of liver diseases can directly reflect liver health and normal/abnormal function, biomarker-based assays are vital tools for the early detection of liver disease. In this context, small molecule fluorescent probes have undeniably emerged as indispensable tools for diagnosis and analysis, with an ever-growing number of small molecule-based fluorescent probes being developed over recent years, with the sole aim of monitoring relevant biomarkers of liver disease. This perspective will focus on the development and application of probes developed primarily over the last 10 years for diagnosing a range liver disease-related processes. It will outline the foundational design strategies for developing promising probes, their optical response to key biomarkers, and how they have been demonstrated in proof-of-concept imaging applications. Current challenges and new developments in the field will be discussed, with the aim of providing insights and highlighting opportunities in the field.</p
Psychological consequences of global armed conflict
Get PDFArmed conflict unvaryingly leads to a loss of life, serious violations of human rights and international law, and extensive human suffering. As technological advances change the landscape of modern armed conflict, developments are also urgently needed to ensure accessible, evidence-based care is readily available to those affected
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