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Introduction: Yugoslav hauntologies.
Full text linkIn this introductory essay, the editors trace the specific contours of Yugoslav hauntings of the late capitalist present, with reference to contemporary art practices in the post-Yugoslav space. Drawing on discursive histories of Yugonostalgia, contemporary debates that problematize Yugofuturisms, and the contentious geopolitical forces informing the production and consumption of contemporary art, the editors set out a broad terrain of engagements with the hauntological that address unevenly inherited artistic legacies and burdens following the disintegration of socialist Yugoslavia. The editors introduce ideas from Ozren Pupovac, Sara Ahmed, Giorgio Agamben, Zdenka Badinovac, Mark Fisher, Mitija Velikonja, Nataša Kovačević, Ana Vujanović and Bojana Cvejić, Piro Rexhepi, and Dubravka Ugrešić, among others, to argue for a hauntological engagement with the history and re-examination of socialist Yugoslavia in contemporary art
An innovative northern goshawk optimization-hybrid neural network algorithm for highly accurate state of health estimation of lithium-ion batteries.
No full textThe State of Health (SOH) of lithium-ion batteries is an important parameter of the battery management system and plays a decisive role in the reliability and safety of the batteries. This paper proposes an innovative northern goshawk optimization - hybrid neural network (NGO-HNN) algorithm for highly accurate SOH estimation. First, the convolutional neural network (CNN) layer extracts local features from the original battery data to capture important patterns during the battery charging process. Next, the bidirectional long short-term memory network (BiLSTM) layer learns the long-term dependencies of the battery data from both forward and backward directions to enhance the understanding of the temporal information. Then, the self-attention (SA) weights the output of the BiLSTM to highlight the features most relevant to the SOH estimation. Finally, the NGO algorithm globally optimizes the model's hyperparameters by simulating the predatory behavior of the northern goshawk, avoiding getting trapped in local optimal solutions and further improving the model's accuracy and generalization ability. The verification results on the National Aeronautics and Space Administration (NASA) dataset show that, compared with the hybrid neural network (HNN) algorithm, the proposed NGO - HNN algorithm reduces the maximum error (ME) by more than 37.27% in the single - battery verification and by more than 15.86% in the multi - battery cross - validation. This research provides an efficient and reliable solution for the SOH estimation of lithium-ion batteries
A cross-sectional study of how cancer nurses document the nursing processes using digital health record (DHR).
No full textThe aim of the study is to explore how nurses document the nursing processes within a cancer care setting using digital health record (DHR). How do nurses document the nursing processes within a cancer care setting using DHR? A cross-sectional study. Twenty clinical care records were randomly selected from a large metropolitan hospital in a single medical oncology inpatient ward in Australia. The audit was conducted using the D-Catch instrument to assess the completeness and quality of nursing record using the five elements of the nursing process. Data analysis was conducted in IBM SPSS Statistics version 29. The findings from the study showed evidence of high scores across all aspects of the nursing process, both in the completeness of record and an overall positive outcome for the quality of nursing documentation. However, documentation relating to assessment of patients' holistic care needs showed low to zero evidence of any documented record. This study provided important insight into the documentation of the nursing processes within DHR. The concerns around limited documentation in capturing holistic care needs require attention. The application of D-Catch tool in assessing the nursing process remains useful, as shown in this study; however, its usability within a digital context needs further investigation
Achieving net zero: enhancing climate literacy in Scottish secondary schools through newspaper style educational posters.
No full textAchieving Net Zero is a series of information graphics-led posters presented through a broadsheet format for distribution initially in a pilot to secondary schools in Aberdeen and Aberdeenshire to raise public awareness of Scotland’s commitment to achieving net zero by 2045. The project presents complex information about sustainability, renewable energy, climate change, emissions and related topics in accessible visual formats to helps viewers understand how each element fits into the bigger picture as Scotland moves towards its 2045 target. For those wanting to delve deeper, each poster also has a supporting page on the Achieving Net Zero website (https://www.achievingnetzero.scot). These pages provide links to all the research materials used in creating the poster to allow the viewers to investigate the topics in more depth
Scottish fashion futures: reflecting on Scotland’s fashion identity, influence and impact.
Full text linkNational fashion systems are recognised as increasingly important and will play a valuable role in helping the fashion industry transition towards a more sustainable future. These national systems make an important contribution to the economy and provide opportunities for local communities. Fashion in and of itself is an important symbol of national identity and culture and the people working within the industry (designing, producing, communicating, managing, etc) are also recognised as signifiers who bring about new ideas and change. Scotland has a vast iconography and is recognised globally for its rich heritage in fashion and textiles, which spans centuries. Current literature surrounding Scottish fashion tends to focus on traditional textiles in terms of how they have evolved throughout history. The Scottish textile industry remains profitable, and Scotland has a strong reputation for producing high quality, artisan goods. Textile mills in Scotland have a long history of supplying to global luxury brands and some of these manufacturers have evolved into brands in their own right, synonymous with high quality and sustainability. Recent research in the fields of national identity, Scottish identity and Scottish fashion suggests that it is valuable to revisit, reflect upon and update existing narratives. Leading Scottish identity scholars propose that Scotland might be a victim of its own rich heritage, which makes it difficult for a more modern identity to be established. The current research explores Scottish fashion openly in a series of workshop discussions with Scottish fashion industry academics and practitioners. These revealed a difficulty in defining contemporary Scottish fashion as well as a tension between how Scottish fashion is perceived within and outside of Scotland. Recommendations are made around the strengthening of "Made in Scotland" as an initiative, better support for graduates and industry skills shortages, and an accessible and inclusive information sharing platform
Adaptive surrogate-based strategy for accelerating convergence speed when solving expensive unconstrained multi-objective optimisation problems.
Full text linkMulti-Objective Evolutionary Algorithms (MOEAs) have proven effective at solving Multi-Objective Optimisation Problems (MOOPs). However, their performance can be significantly hindered when applied to computationally intensive industrial problems. To address this limitation, we propose an adaptive surrogate modelling approach designed to accelerate the early-stage convergence speed of state-of-the-art MOEAs. This is important because it ensures that a solver can identify optimal or near-optimal solutions with relatively few fitness function evaluations, thereby saving both time and computational resources. Our method employs a two-loop architecture. The outer loop runs a (baseline) host MOEA which carries out true fitness evaluations. The inner loop contains an Adaptive Accelerator that leverages data-driven machine learning (ML) surrogate models to approximate fitness functions. Integrated with NSGA-II and MOEA/D, our approach was tested on 31 widely known benchmark problems and a real-world North Sea fish abundance modelling case study. The results demonstrate that by incorporating Gaussian Process Regression, one-dimensional Convolutional Neural Networks, and Random Forest Regression, our proposed approach significantly accelerates the convergence speed of MOEAs in the early phases of optimisation
The Border Security, Asylum and Immigration bill.
Full text linkThe Border Security, Asylum and Immigration bill is presently being considered by the House of Lords. It is the first wide-ranging immigration-related piece of legislation of the Labour government following the May 2025 general election. The bill gives a clear indication, therefore, of the approach the new government will take to immigration and asylum. It is not unreasonable to think a new approach would be taken. In a statement to the House of Commons Home Secretary Yvette Cooper criticised the previous government as regards net migration, asylum and border security and stated that action was being taken to 'turn that around'. Initial developments suggested that a new and less illiberal approach would be taken. The Labour government scrapped the use of the Bibby Stockholm barge to detain asylum seekers, and as put an end of the plan to summarily send persons arriving on small boats on UK shores to Rwanda. The stated reasons for the change of policies, however, does not appear to be humanity and human rights. Rather it is effectiveness and cost-efficiency. The question, then, is whether the Border Security, Asylum and Immigration bill will continue along the same line as the previous Conservative government or mark a new and welcome departure in immigration and asylum law and policy. The answer appears to be the former, albeit through slightly different means
Operations and supply chain management: principles and practice.
Full text linkOperations and Supply Chain Management (OSCM) has continually evolved, incorporating a broad array of strategies, frameworks, and technologies to address complex challenges across industries. This encyclopedic article provides a comprehensive overview of contemporary strategies, tools, methods, principles, and best practices that define the field's cutting-edge advancements. It also explores the diverse environments where OSCM principles have been effectively implemented. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners
Brain activity during ankle movements in female athletes with chronic ankle instability: a pilot fMRI investigation.
No full textThis pilot study aimed to evaluate brain activity in sensorimotor regions during a unilateral ankle movement (dorsiflexion/plantarflexion) task using functional magnetic resonance imaging in female collegiate athletes with and without chronic ankle instability. This is a cross-section study set in a sports performance and research centre with participants of twenty-two female soccer athletes from a Division III university (chronic ankle instability: n = 11; control: n = 11) to measure brain activity during a unilateral ankle movement functional magnetic resonance imaging task. Neuroimaging analyses revealed significant differences in sensorimotor brain activity, with greater activity in the ipsilateral primary motor cortex in the chronic ankle instability group compared to the control group (p =.039). Altered brain activity during unilateral ankle movements in athletes with chronic ankle instability could reflect disruptions in central nervous system processing. These preliminary findings offer a potential mechanistic target for rehabilitation strategies aimed at restoring central nervous system function and improving motor control in athletes with chronic ankle instability
Virtual reality, traditional textiles and contemporary consumers.
Full text linkAugmented Fashion was an AHRC-funded interdisciplinary research project involving academics and industry partners from the fashion, textiles and computing science disciplines in both the UK and China. The project explored ways to engage consumers with the craftsmanship, heritage, value and sustainability of traditional fashion and textile products, using immersive technologies such as augmented reality (AR) and virtual reality (VR) to attract the attention of contemporary audiences with these traditional and sometimes under-valued products. Immersive VR content was created for Harris Tweed®, aiming to engage contemporary consumers in the UK and China with this iconic heritage textile brand. Data was gathered using an interpretive paradigm via a qualitative survey, comparing brand image perceptions, brand identity and awareness of sustainability created by traditional, real-world video content versus immersive content (a 3D virtual world). Comparing Chinese consumer reactions with those of the UK provides useful international insight into the acceptance of and attitudes towards VR fashion content. Reactions from both UK and Chinese consumers were surprisingly similar, suggesting that the use of immersive technologies changed consumer perceptions of the Harris Tweed® brand; respondents saw it as more modern, futuristic and fashion-forward, aimed at a younger target audience. This is an important finding given the need for heritage brands to gain new customers from younger demographics
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