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Data-agnostic face image synthesis detection using Bayesian CNNs
No full textFace image synthesis detection is considerably gaining attention because of the potential negative impact on society that this type of synthetic data brings. In this paper, we propose a data-agnostic solution to detect the face image synthesis process. Specifically, our solution is based on an anomaly detection framework that requires only real data to learn the inference process. It is therefore data-agnostic in the sense that it requires no synthetic face images. The solution uses the posterior probability with respect to the reference data to determine if new samples are synthetic or not. Our evaluation results using different synthesizers show that our solution is very competitive against the state-of-the-art, which requires synthetic data for training
A new method to perform Lithium-ion battery pack fault diagnostics – Part 2: Algorithm performance in real-world scenarios and cell-to-cell transferability
Get PDFThe last decade has witnessed significant progress towards zero-emission electric aviation. Lithium-ion batteries are at the centre of this technological transformation. However, electric flight requires suitable considerations for safety concerns associated with Lithium-ion batteries. Fault diagnostic approaches aimed at validating the safety of batteries before every flight have emerged as an attractive prospect. In this pursuit, a three-paper series proposing a novel fault diagnosis algorithm is presented. The algorithm is capable of diagnosing faults in an aircraft battery using the data collected during charging and was previously validated for a particular cell type under steady charging conditions. In this paper, two extensional aspects of the algorithm are investigated: cell-to-cell transferability and disparate charging conditions. While crucial for practical implementation, these aspects were overlooked in previous literature. Through experiments conducted at module-level, it was revealed that the algorithm could diagnose faults for a different cell type with minimal preliminary cell-level characterisation, thus demonstrating its ease of transferability. Moreover, modifications introduced in the algorithm enabled it to perform fault diagnosis under unsteady charging conditions for an aerospace module despite significant internal temperature gradients. Thus, the successful working of the algorithm in the considered aspects, which are unprecedented in literature, prove its feasibility for real-life application
In preprints : hormonal stepping stones to diverging root organogenesis
No full textLegumes form a symbiotic relationship with bacteria called rhizobia. The rhizobia fix atmospheric dinitrogen, which is used by the plant as a nitrogen resource, and take up molecules, including carbon compounds, from the plant. Rhizobia are housed in nodules that develop on roots after a series of orchestrated stages that are triggered by the perception and entry of rhizobia at root hairs (reviewed by Luo et al., 2023). Study of this relationship and the mechanisms that govern nodule formation and inhibition may reveal targets to promote enhanced nodulation efficiency and increased nitrogen acquisition for the plant. Phytohormones have been shown to play a key role in both nodule formation and inhibition; therefore, a better understanding of hormonal regulatory activity could provide options for such enhancement. To address this, Drapek and colleagues (2023 preprint) focus on the dynamics of gibberellin (GA), a phytohormone previously identified as both a positive and negative regulator of nodulation (Rizza et al., 2017; Fonouni-Farde et al., 2016)
Evidence synthesis and linkage for modelling the cost-effectiveness of diagnostic tests : preliminary good practice recommendations
Get PDFObjectives: To develop preliminary good practice recommendations for synthesising and linking evidence of treatment effectiveness when modelling the cost-effectiveness of diagnostic tests. Methods: We conducted a targeted review of guidance from key Health Technology Assessment (HTA) bodies to summarise current recommendations on synthesis and linkage of treatment effectiveness evidence within economic evaluations of diagnostic tests. We then focused on a specific case study, the cost-effectiveness of troponin for the diagnosis of myocardial infarction, and reviewed the approach taken to synthesise and link treatment effectiveness evidence in different modelling studies. Results: The Australian and UK HTA bodies provided advice for synthesising and linking treatment effectiveness in diagnostic models, acknowledging that linking test results to treatment options and their outcomes is common. Across all reviewed models for the case study, uniform test-directed treatment decision making was assumed, i.e., all those who tested positive were treated. Treatment outcome data from a variety of sources, including expert opinion, were utilised for linked clinical outcomes. Preliminary good practice recommendations for data identification, integration and description are proposed. Conclusion: Modelling the cost-effectiveness of diagnostic tests poses unique challenges in linking evidence on test accuracy to treatment effectiveness data to understand how a test impacts patient outcomes and costs. Upfront consideration of how a test and its results will likely be incorporated into patient diagnostic pathways is key to exploring the optimal design of such models. We propose some preliminary good practice recommendations to improve the quality of cost-effectiveness evaluations of diagnostics tests going forward
Thermal analysis of novel Nitrate-Chloride salt mixtures for CSP applications
No full textNitrate salts have better thermal stability, low vapour pressure and non-toxic nature compared to synthetic heat transfer oil like Therminol VP-1®. Solar salt, a mixture of 60%NaNO3 -40%KNO3 by weight, is finding increased application as a Heat Transfer Fluid (HTF) and Thermal Energy Storage (TES) material in Concentrated Solar Power (CSP) plant. In this research work, two novel salt mixtures are prepared and tested for their melting point, short and long duration thermal stability. The formulation 1 is a ternary salt comprising of 44%KNO3- 32%Ca(NO3)2- 24%NaNO3, referred to as Base Salt. Formulation 2 is a quinary mixture of 90%Base salt + 5%NaCl + 5%KCl, referred to as Base-Chloride. Solar salt is also tested and compared alongside the novel mixtures. The experiments conclude that the melting point of Solar salt is 223°C, Base salt is 135.8°C and Base-Chloride is 142.2°C. Considering Short duration thermal stability, decomposition point of Solar salt is 631°C, Base salt is 585°C and Base-Chloride is 589°C. Considering long duration stability, all the three mixtures remain stable till 400°C, when heated at constant temperature for 24 hours. The novel mixtures have significantly lower melting points, thus providing wider operating temperature range compared to Solar salt
pH-Responsive amphiphilic triblock fluoropolymers as assemble oxygen nanoshuttles for enhancing PDT against hypoxic tumor
No full textPhotodynamic therapy (PDT) is a cancer treatment strategy that utilizes photosensitizers to convert oxygen within tumors into reactive singlet oxygen (1O2) to lyse tumor cells. Nevertheless, pre-existing tumor hypoxia and oxygen consumption during PDT can lead to an insufficient oxygen supply, potentially reducing the photodynamic efficacy. In response to this issue, we have devised a pH-responsive amphiphilic triblock fluorinated polymer (PDP) using copper-mediated RDRP. This polymer, composed of poly(ethylene glycol) methyl ether acrylate, 2-(diethylamino)ethyl methacrylate, and (perfluorooctyl)ethyl acrylate, self-assembles in an aqueous environment. Oxygen, chlorine e6 (Ce6), and doxorubicin (DOX) can be codelivered efficiently by PDP. The incorporation of perfluorocarbon into the formulation enhances the oxygen-carrying capacity of PDP, consequently extending the lifetime of 1O2. This increased lifetime, in turn, amplifies the PDT effect and escalates the cellular cytotoxicity. Compared with PDT alone, PDP@Ce6-DOX-O2 NPs demonstrated significant inhibition of tumor growth. This study proposes a novel strategy for enhancing the efficacy of PDT
A data-driven approach to understanding non-response and restoring sample representativeness in the UK Next Steps cohort
Get PDFNon-response is common in longitudinal surveys, reducing efficiency and introducing the potential for bias. Principled methods, such as multiple imputation, are generally required to obtain unbiased estimates in surveys subject to missingness which is not completely at random. The inclusion of predictors of non-response in such methods, for example as auxiliary variables in multiple imputation, can help improve the plausibility of the missing at random assumption underlying these methods and hence reduce bias. We present a systematic data-driven approach used to identify predictors of non-response at Wave 8 (age 25–26) of Next Steps, a UK national cohort study that follows a sample of 15,770 young people from age 13–14 years. The identified predictors of non-response were across a number of broad categories, including personal characteristics, schooling and behaviour in school, activities and behaviour outside of school, mental health and well-being, socio-economic status, and practicalities around contact and survey completion. We found that including these predictors of non-response as auxiliary variables in multiple imputation analyses allowed us to restore sample representativeness in several different settings, though we acknowledge that this is unlikely to universally be the case. We propose that these variables are considered for inclusion in future analyses using principled methods to explore and attempt to reduce bias due to non-response in Next Steps. Our data-driven approach to this issue could also be used as a model for investigations in other longitudinal studies
Additive manufacturing of thermal management components in mobility applications
No full textThe adoption of metallic additive manufacturing (AM), often referred to as “3D printing,” for heat exchangers offers significant thermal management benefits that range from optimized heat energy transfer to supporting integrated designs that can reduce weight, size, and component numbers. The benefits of utilizing AM for heat exchangers transcend industries and have relevance within the aerospace and automotive industries, where “New Mobility” requirements result in the need for efficient energy systems, increasingly efficient component design, and often higher temperatures. However, there are currently some unsettled drawbacks to the use of AM. Metal AM material performance in high-temperature applications is still not well understood, and there is a need for significant standardization that goes beyond the material grades, printing process parameters, and characterization processes for performance reliability. Also, to maximize the efficiency of AM heat exchangers, the design of the resulting component will be significantly different from those manufactured traditionally; this then raises many quality concerns. This report will introduce the concept of AM heat exchangers while examining the critical unsettled issues of quality control (particularly in automotive and aerospace applications), design, simulation, and testing. Finally, the report delves into regulation, standards, and certification. Recommendations are made on each of these topic areas to collectively stimulate community debate, offering insights into vital areas or future research.
NOTE: SAE EDGE Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny
Conceptualising sustainability as the pursuit of life
Get PDFComplex and urgent challenges including climate change and the significant decline in biodiversity provide a broad agenda for interdisciplinary scholars interested in the implications facing businesses, humanity, and other species. Within this context of sustainability, persistent conflicts between key paradigms create substantial barriers against—but also opportunities for—developing new conceptual approaches and theoretical models to understand and respond to these critical issues. Here, I revisit paradigmatic tensions to assess their impact on research and debate on sustainability, ethics, and business. Drawing on relational ontology and values of nature that recognise humanity’s tight embeddedness within the planetary ecosystem, I examine how conceptualising sustainability as the pursuit of life might generate new insights for research and practice into the wider transformation needed to sustain and restore socioecological systems. The aim here, however, is not to reconcile these paradigmatic tensions but instead use them as a fruitful lens for examining the implications for sustainability, while acknowledging the inherent ethical dilemmas for individuals, organisations, and society