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Data-driven compact AI model for automatic detection of thermal anomalies in large-format pouch cells
No full textData set for the articl
Decoupling Gender from ‘Midwifery’:A Utopian Vision
No full textThis chapter examines how the professional title ‘midwife’ is predicated on the understanding that people who access their services have a normative relationship between their gender and assigned sex and why this is problematic. As trans and nonbinary people increasingly require access to midwifery services, this chapter proposes an alternative professional title which is inclusive and liberates midwives from continuously reinscribing the sex/gender binary in their nomenclature. Using Levitas’ ‘utopia as method’ framework, this chapter proposes the title of ‘lead perinatal practitioner’. It is argued that this title signals a trailblazing contribution toward the eradication of gender inequalities in the reproductive arena by uncoupling the profession from patriarchal oppression inscribed in the sex/gender binary which has hitherto been positioned as the sine qua non of midwifery
Spontaneity, Creativity and Resourcefulness in Community Self-Protection
No full textThis chapter explores notions of spontaneity, creativity, and resourcefulness, by drawing on existing literature in unarmed civilian protection (UCP) and primary data collected from several context-specific projects in Cameroon, Colombia, Myanmar, and South Sudan. The chapter begins by charting the diverse range of self-protection measures that have emerged seemingly instinctively across a range of contexts, before progressing to outline some of the contextual factors which can be seen to have informed several locally led spontaneous and creative approaches to unarmed civilian protection. Reflecting on the contextual nature of UCP, the chapter will examine the different ways in which creativity and spontaneity are understood and practiced by local communities and actors, and how existing social, cultural, political, and religious dynamics shaped notions of self-protection and understandings of locally led approaches. Furthermore, evident challenges to locally led initiatives will be considered, and consideration will be given to how they can be supported in scaling up. Where relevant, the interplay and relationships between spontaneous and creative UCP activities and ‘external’ organisational strategies and programmes will be explored. The authors will attempt to understand how, given the power relations and dominance of external organisations in some contexts, existing national and international UCP organisations and programmes attempt to retain and nurture locally owned and led creative approaches to UCP, whilst simultaneously attempting to document, systematise, and share knowledge about locally led creative practices. In recognition of the authors’ roles in this process, the chapter will conclude with some reflection on the complex process of researching and documenting creative approaches to self-protection, whilst attempting to ensure that these often-spontaneous processes are in no way compromised
Systematic exploration of fuzzing in IoT:techniques, vulnerabilities, and open challenges
No full textAs our dependence on the internet and digital platforms grows, the risk of cyber threats rises, making it essential to implement effective measures to safeguard sensitive information through cybersecurity, ensure system integrity, and prevent unauthorized data access. Fuzz testing, commonly known as fuzzing, is a valuable technique for software testing as it uncovers vulnerabilities and defects in systems by introducing random data inputs, often leading to system crashes. In the Internet of Things (IoT) domain, fuzzing is crucial for identifying vulnerabilities in networks, devices, and applications through automated tools that systematically inject malformed inputs into IoT systems. However, despite its importance, existing research on fuzzing techniques in IoT contexts remains limited by the absence of standardized benchmarks, inefficiencies in re-hosting strategies, and difficulties in detecting complex, condition-dependent vulnerabilities. The primary objective of this study is to comprehensively evaluate current fuzzing practices, emphasizing adaptive techniques designed for IoT systems. Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) model, a systematic literature review was conducted across 32 academic articles published between 2020 and 2024. The analysis revealed that although fuzzing enhances IoT security, its effectiveness is hindered by device heterogeneity, limited system resources, and evolving cyber threat landscapes. The findings suggest that to overcome these limitations, future research should focus on AI-driven fuzzing methods, robust multi-architecture support, and the development of standardized evaluation frameworks to strengthen IoT cybersecurity.</p
Novel Approaches in Cardiovascular Diagnostics:Mapping the Research Landscape of the 21st Century
No full textThis chapter provides a comprehensive scientometric analysis of novel approaches in cardiovascular diagnostics from 2000 to 2024. The study leverages advanced bibliometric tools to examine the evolution of key technologies, including artificial intelligence (AI), computational fluid dynamics, data fusion, genetic biomarkers, imaging technologies, nanodiagnosis, and wearables. Bespoke datasets are created using Dimensions and Altmetric data, as well Google Cloud products, to analyse publication trends, clinical trials, patent activity, and policy citations, amongst others. Key findings highlight the dominance of imaging technologies’ research volume, reflecting their central role in cardiovascular diagnostics. AI and genetic biomarkers are rapidly growing fields, enhancing diagnostic precision and personalised care. Emerging technologies like wearables and nanodiagnosis show promise for continuous monitoring and early detection. The chapter also explores the impact of COVID-19 on accelerating research, the shift towards AI and data-driven diagnostics, and the global contributions to cardiovascular research. The analysis of patent and policy citations underscores the real-world impact of these technologies, with imaging and genetic biomarkers leading in policy/clinical guidelines integration
Application of Large Language Models in Traditional Chinese Medicine:A State-of-the-Art Review
No full textLarge language models (LLMs) are reshaping the landscape of Traditional Chinese Medicine (TCM). This review covers the latest applications of LLMs in TCM, including literature analysis, data mining, TCM knowledge management, diagnosis simulation and clinical decision making. LLMs can analyze large quantities of TCM literature and medical records to extract critical information, classify prescriptions, and build TCM knowledge maps to help researchers quickly grasp state-of-the-art and future research trends. LLMs can provide initial diagnostic recommendations by analyzing textual information such as a patient’s symptom description and medical history, enabling the optimization of TCM therapy and the training of TCM practitioners. Compared with traditional tools, LLMs can significantly improve the efficiency and accuracy of bibliographic analysis and TCM prescription classification, and offer new potential for data-driven standardized TCM diagnosis. However, challenges remain, including the standardization of TCM terminology and data formats, integration of different data sources, timely knowledge updates, and the interpretability and credibility of results generated by LLMs. Future research on standardized templates for patient symptom description, multimodal data fusion techniques, and real-time knowledge update systems is warranted to improve the transparency and interpretability of LLMs. This review highlights the potential of LLMs to modernize TCM research and practice, providing an up-to-date reference for data scientists, biomedical engineers, and TCM practitioners
Defund Culture:A Radical Proposal: Why the arts are so white, male and middle-class and what we can do about it
No full textDemonstrating that it is upper- and middle-class, privately educated, Oxbridge graduates who receive the majority of funding and support when it comes to the creative industries in the UK, Defund Culture argues powerfully that resources and opportunities should be disinvested from the cultural sphere as it exists now, and redistributed to other sections of society, in order to generate art, media and creativity that is more diverse and less boring, homogeneous and anti-intellectual
"A Sea of Opportunity" - The Maritime Dimension of Brexit Narratives
No full textBrexit was a seismic political event. The narratives that shaped its outcome reveal much about contemporary Britain and its constituent political, socio-cultural, and historic values and identities. In particular, Brexit magnified the importance of the ocean as both an economic lifeline, but also a politically contested space with fisheries and immigration at the forefront of the debate. Despite the prominence of maritime narratives in the campaign and referendum, and the enduring political, economic and security importance of these issues in the subsequent negotiations, this dimension of Brexit has been largely overlooked in academic analysis. This article sheds new light on how and why coastal communities in particular perceived political choices in a certain manner and presents the findings of a new dataset that helps unpack some of the ways the maritime dimension of Brexit narratives underpinned the process
A Novel Genetic Algorithm-based Routing Approach for Electric Vehicles
No full textRecent studies show that transportation accounts for 20 % of the total CO2 emissions of the world, placing it as the main contributor to climate change; therefore, decarbonization of road transport is necessary. Promoting the use of less polluting transport modes such as electric vehicles (EVs) is an important step toward achieving this objective. As it is expected that the use of EVs will rise significantly, this paper aims to help EVs’ drivers to have a better and less stressful driving experience through an innovative routing approach. It consists in leveraging genetic algorithms (GAs) to route an EV effectively based on multiple different factors including route length, its duration and the experienced wait-times. A novel ‘branching’ methodology is developed which takes a random point of an existing route, and attempts to find a unique sub-route to the destination from this point, creating a new additional route for the population to balance vast exploration and exploitation through allowing effective crossover. The preliminary simulation results obtained, using the traffic simulator SUMO, highlight that our proposed approach outperforms A* under congested traffic scenarios