18624 research outputs found
Sort by
Men, feminist welfare, and allyship in social work education
No full textFeminist approaches have played a key role in transforming the welfare state as well as social work. Given this, in a social work degree, there is a tacit assumption that over the course of their enrolment, social work students will find their professional identity in this symbiosis of feminism and welfare and, possibly, become feminist allies. How this is negotiated in the classroom and what that means in practice is the focus of a growing discussion. Drawing on recent academic literature on this topic, this chapter attempts to ground key terms, such as male feminist allyship highlighting tensions as well as opportunities that might assist students to position themselves in relation to political and professional identities that are strongly contested. The chapter takes a comparative approach focused on allyship in relation to social movements and developmental social work education. This departs somewhat from the main-stream debate in social work that is focused on masculinity and associated societal norms and structures. We believe that bringing social psychology and sociological contributions to the discussion offers a different perspective to the social work allyship literature that tends to draw on feminist ethics and associated narratives and norms that define (male) moral agents. The chapter takes a chronological approach providing a very brief summary of both historical and theoretical trajectories that, organised around an ethics of care, increasingly de-centre essential difference, gender, and the human at the centre of allyship rendering visible the need to critically reflect on what feminist allyship means within a contemporary social work context. © 2024 selection and editorial matter, Carolyn Noble, Shahana Rasool, Linda Harms-Smith, Gianinna Muñoz-Arce and Donna Baines; individual chapters, the contributors
Emergency nurse roles, challenges, and preparedness in hospitals in the context of armed conflict
Get PDFIntroduction: An understanding of emergency nurses' roles, challenges, and preparedness in the context of armed conflict is necessary to capture in-depth insights into this specialty and their preparational needs when working in these unique environments. Unfortunately, the evidence about emergency nurses' work in the context of armed conflict is scant. Method: Semi-structured interviews were conducted with 23 participants and analyzed using qualitative content analysis. The COREQ guideline for reporting qualitative research was followed. Results: The emergency nurses' roles, challenges, and preparedness in hospitals in the context of armed conflict were explored in detail. The main challenges that these nurses faced included poor orientation, access block, and communication barriers. Various perspectives about preparation, including education, training, and strategies for preparing emergency nurses were identified. The most striking findings in these settings were the diversity of armed conflict injuries, clinical profiles of patients, triage of mass casualties, trauma care, surge capacity, orientation, communication, and strategies for preparing nurses. Conclusions: This study provided an exploration of the scope of emergency nurses' roles, and how they were prepared and expected to function across multiple hospitals in armed conflict areas. The resultant snapshot of their experiences, challenges, and responsibilities provides an informative resource and outlines essential information for future emergency nursing workforce preparedness. There is a broad range of preparational courses being undertaken by emergency nurses to work effectively in settings of armed conflict; however, required education and training should be carefully planned according to their actual roles and responsibilities in these settings. © The Author(s), 2024. Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health, Inc
Efficient motion modelling with variable-sized blocks from hierarchical cuboidal partitioning
Get PDFThis paper explores the potential of cuboidal partitioning in motion modelling compared to the commonly used fixed-sized block-based architecture in scalable video coding. The traditional approach of dividing frames into fixed-sized blocks for independent motion compensation often results in coding inefficiency due to poor alignment with object boundaries. Hierarchical block partitioning has been introduced as a solution, but it suffers from an increased number of motion vectors, limiting its effectiveness. In contrast, cuboidal partitioning offers a promising alternative. It involves approximate segmentation of images into variable-sized rectangular segments (cuboids) that align well with object boundaries. The segmentation is based on a homogeneity constraint, minimizing the sum of squared errors (SSE). This property makes cuboidal partitioning compatible with block-based video coding techniques. In this paper, we investigate the potential of cuboids in motion modelling, specifically comparing them to fixed-sized blocks used in scalable video coding. Our approach involves constructing a motion-compensated current frame using the cuboidal partitioning information from the anchor frame within a group-of-pictures (GOP). The predicted current frame serves as the base layer, while the current frame is encoded as an enhancement layer using the scalable High Efficiency Video Coding (HEVC) encoder. Experimental results demonstrate significant bitrate savings ranging from 6.71% to 10.90% on 4 K video sequences. These savings highlight the superiority of our proposed model, which leverages cuboidal partitioning to improve coding efficiency and alignment with object boundaries. By adopting this approach, we mitigate the limitations of fixed-sized blocks and offer a more effective solution for motion modelling in scalable video coding. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023
It’s so ridiculously soulless: geolocative media, place and third wave gentrification
No full textThe impact of gentrification in cities is well established. The continuous evolution in geolocation and social media is intensifying the contest between competing stakeholder claims to authenticity about gentrifying places. In this article, we examine the way that different geolocative social media define a struggle over the rights to authenticity in a rapidly gentrifying neighborhood in Brisbane, Australia. Local voices are often submerged by the voices of commercial imperative, particularly when the rent gap in gentrifying neighborhoods begins to attract abstract capital with a vested interest in commodifying local culture. We use Instagram and Facebook to critically examine how the hegemonic influence of social media can construct a gentrifying neighborhood in immaterial space and argue that these constructions work to eradicate the complex array of communities that comprise this neighborhood in material space. © The Author(s) 2022
Countermeasure strategies to address cybersecurity challenges amidst major crises in the higher education and research sector : an organisational learning perspective
Get PDFPurpose: The purpose of this research paper was to analyse the counterstrategies to mitigate cybersecurity challenges using organisational learning loops amidst major crises in the Higher Education and Research Sector (HERS). The authors proposed the learning loop framework revealing several counterstrategies to mitigate cybersecurity issues in HERS. The counterstrategies are explored, and their implications for research and practice are discussed. Methodology: The qualitative methodology was adopted, and semi-structured interviews with cybersecurity experts and top managers were conducted. Results: This exploratory paper proposed the learning loop framework revealing introducing new policies and procedures, changing existing systems, partnership with other companies, integrating new software, improving employee learning, enhancing security, and monitoring and evaluating security measures as significant counterstrategies to ensure the cyber-safe working environment in HERS. These counterstrategies will help to tackle cybersecurity in HERS, not only during the current major crisis but also in the future. Implications: The outcomes provide insightful implications for both theory and practice. This study proposes a learning framework that prioritises counterstrategies to mitigate cybersecurity challenges in HERS amidst a major crisis. The proposed model can help HERS be more efficient in mitigating cybersecurity issues in future crises. The counterstrategies can also be tested, adopted, and implemented by practitioners working in other sectors to mitigate cybersecurity issues during and after major crises. Future research can focus on addressing the shortcomings and limitations of the proposed learning framework adopted by HERS. © 2024 by the authors
Signaling pathways underlying TGF-β mediated suppression of IL-12A gene expression in monocytes
Get PDFTransforming growth factor
The carbon stock potential of the restored mangrove ecosystem of Pasarbanggi, Rembang, Central Java
No full textMangrove ecosystems can absorb significant amounts of carbon and help mitigate climate change. However, their existence continues to be endangered by natural and human forces. Therefore, mangrove restoration is regarded as a crucial component of the global climate change agenda. This study aims to estimate the potential total carbon stock of restored mangrove ecosystems in Pasarbanggi, Rembang, Central Java. The above-below-ground (root) carbon stock was calculated using several published allometric equations. The loss-on-ignition method analyzed leaf litter and sediment carbon stocks. This study estimates the Pasarbanggi mangrove ecosystem's total carbon stock potential at 0.02 × 106 MgC, which is equivalent to the potential CO2 emission of 0.08 × 106 MgCO2e, with up to 65% stored in sediments. This study highlights the critical role of restored mangrove ecosystems on the climate change mitigation agenda by reducing the concentration of atmospheric CO2. © 2023 Elsevier Lt
To be, or not to be, that is the question : stuttering into academia
No full textIn this chapter Grant Meredith, the discipline leader of Information Technology for the Global Professional School at Federation University (Australia) outlines his journey as a person who stutters from his rural Australian upbringing through to being an Information Technology academic. This passage to academia is a reflection on an unconventional odyssey that has meandered from blue collar careers to a university education and beyond. The author discusses what it means to him to have vocal difference and how it may have influenced his research path. Along the way he questions his identity as a person who stutters and find his own “community” to engage within
Transcendental groups
Get PDFIn this note we introduce the notion of a transcendental group, that is, a subgroup G of the topological group C of all complex numbers such that every element of G except 0 is a transcendental number. All such topological groups are separable metrizable torsion-free abelian groups. If
Intelligent feature selection algorithm using SA-SVM classification for skin cancer diagnosis
No full textIn recent decades, the incidence of malignant melanoma as a deadly skin cancer has increased worldwide. With its high medical costs and death rates, this cancer has prioritized the need for early diagnosis. Computer-based detection systems can improve the diagnosis rate of melanoma by 5%-30% compared to the naked eye and reduce human error. Although much effort has been made to advance the detection of skin cancers, there are still serious concerns about it. This chapter introduces automatic skin cancer diagnosis and an overview of methods in each step toward detection. A novel algorithm in feature selection and classification stages of automatic skin cancer diagnosis is designed and implemented to identify malignant and benign lesions. A smart algorithm is proposed based on inertia-based particle swarm optimization (IPSO) and the self-advising SVM (SA-SVM). This algorithm optimizes the feature selection stage. Additionally, SA-SVM, known as a new classifier in skin cancer detection systems, is employed along with the proposed algorithm. The statistical and performance measurement analyses of algorithms are presented to prove the superiority of the proposed algorithms. © 2024 selection and editorial matter, Adel Al-Jumaily, Paolo Crippa, Ali Mansour, and Claudio Turchetti; individual chapters, the contributors