Technological intrusion and communicative renewal:The case of two rural solar farm developments in the UK

from rural areas of the South West, UK. Drawing on a Habermasian theoretical frame, I examine local resident narratives that emerged through the local public sphere and how these formed discursive meanings that provided shared background social norms for residents towards the solar farm developments. The paper begins by operationalising Habermas’s theoretical ideas for empirical research and situating the research within existing literature. The theoretical and methodological sections are followed by the examination of three local narratives that emerged: idealised rural land use, farming and income generation, and money making and the pursuit of profit. Such narratives are considered in view of public opportunities for robust dialogue and debate to judge the normative democratic character of the solar farm developments. The paper concludes that the community development offered significantly more discursive space for debate than the commercial development and increased the developments’ overall democratic legitimacy. It is maintained that such a Habermasian theoretical frame adapted for empirical analysis is valuable for normatively assessing democratic processes which are needed in view of conceptually weak accounts of ‘energy democracy’

Community energy business model evolution:a review of solar photovoltaic developments in England

The ongoing energy system transformation process is placing citizens and communities at the heart of future energy systems. To date, their participation has focused on the ownership and control of renewable energy installations facilitated by supportive national policies. Yet across many European countries, policies that have previously supported the deployment of small-scale renewable projects are being withdrawn. Social innovation and the evolution of business models are needed if citizen participation is to continue and succeed in this new policy landscape. At the same time, few business models stand still. This paper reviews the evolution of community energy business models in England to provide insights into the potential of community participation in the energy system post subsidies. Concentrating on community solar photovoltaic projects as the cornerstone technology, this review identifies and critique three archetypal business models as sequentially dominating English community renewable energy to date. Using insights from both Science and Technology Studies and Transaction Cost Economics, it explores the drivers and origin of these models as well as resulting community benefits. Looking forwards and by reviewing current activity, this paper identifies new intermediary actors as playing a key role in facilitating and brokering new, increasingly complicated and commercial community energy business models. We argue that this marks a significant break from the past and may, in time, offer more opportunities for community participation in energy system transformation. Moreover, it offers some communities the possibility of staying small and retaining their more radical potential

Enhancing Illicit Activity Detection using XAI: A Multimodal Graph-LLM Framework

Financial cybercrime prevention is an increasing issue with many organisations and governments. As deep learning models have progressed to identify illicit activity on various financial and social networks, the explainability behind the model decisions has been lacklustre with the investigative analyst at the heart of any deep learning platform. In our paper, we present a state-of-the-art, novel multimodal proactive approach to addressing XAI in financial cybercrime detection. We leverage a triad of deep learning models designed to distill essential representations from transaction sequencing, subgraph connectivity, and narrative generation to significantly streamline the analyst's investigative process. Our narrative generation proposal leverages LLM to ingest transaction details and output contextual narrative for an analyst to understand a transaction and its metadata much further.Comment: 6 pages, 3 figure

Conceptualisations of social justice: exploring the views of newly-qualified social workers in statutory social work practice

Cut to the chase This thesis explores the ways in which newly-qualified statutory social workers (NQSWs) conceptualise social justice. Social justice is widely considered to be a central value to social work but lacks a coherent and consistent definition. The literature presents a range of conceptual variants, and while the Professional Capabilities Framework (PCF) for social work in England includes social justice among its requirements for social work practice, it does not explicitly define it. Drawing on a combination of constructivism and critical realism, I treat social justice as a contestable and contested concept, but one that impacts, and is impacted by, events in world. Fifteen NQSWs were individually interviewed (alongside five experienced practitioners) about how they understood or defines social justice, what they believed had contributed to their conceptualisation, and what their experiences of social justice in practice were like. The resultant data were thematically analysed. The way participants described their social justice conceptualisations varied. This may be because of the influence of pre-qualifying experience which is, by its very nature, individual. The main contributions to knowledge of this thesis are threefold. The first is the approach taken to the research. The second is the finding that while participant concepts varied, their descriptions of practice experience were more cohesive. The third is the proposal of a new framework for conceptualising social justice in view of the findings; the Social Justice Tetrahedron. The thesis concludes with discussions of future research, and recommendations for the dissemination of its ideas in social work practice and education

SIM-STEM Lab: Incorporating Compressed Sensing Theory for Fast STEM Simulation

Recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future.Comment: 20 pages (includes 3 supplementary pages), 15 figures (includes 5 supplementary figures), submitted to Ultramicroscop

Faecal metabarcoding reveals pervasive long-distance impacts of garden bird feeding

Supplementary feeding of wildlife is widespread, being undertaken by more than half of households in many countries. However, the impact that these supplemental resources have is unclear, with impacts largely considered to be restricted to urban ecosystems. We reveal the pervasiveness of supplementary foodstuffs in the diet of a wild bird using metabarcoding of blue tit (Cyanistes caeruleus) faeces collected in early spring from a 220 km transect in Scotland with a large urbanization gradient. Supplementary foodstuffs were present in the majority of samples, with peanut (Arachis hypogaea) the single commonest (either natural or supplementary) dietary item. Consumption rates exhibited a distance decay from human habitation but remained high at several hundred metres from the nearest household and continued to our study limit of 1.4 km distant. Supplementary food consumption was associated with a near quadrupling of blue tit breeding density and a 5-day advancement of breeding phenology. We show that woodland bird species using supplementary food have increasing UK population trends, while species that do not, and/or are outcompeted by blue tits, are likely to be declining. We suggest that the impacts of supplementary feeding are larger and more spatially extensive than currently appreciated and could be disrupting population and ecosystem dynamics

Simultaneous High-Speed and Low-Dose 4-D STEM Using Compressive Sensing Techniques

Here we show that compressive sensing allow 4-dimensional (4-D) STEM data to be obtained and accurately reconstructed with both high-speed and low fluence. The methodology needed to achieve these results compared to conventional 4-D approaches requires only that a random subset of probe locations is acquired from the typical regular scanning grid, which immediately generates both higher speed and the lower fluence experimentally. We also consider downsampling of the detector, showing that oversampling is inherent within convergent beam electron diffraction (CBED) patterns, and that detector downsampling does not reduce precision but allows faster experimental data acquisition. Analysis of an experimental atomic resolution yttrium silicide data-set shows that it is possible to recover over 25dB peak signal-to-noise in the recovered phase using 0.3% of the total data

A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam Scanning Electron Microscopy

Cryo Focused Ion-Beam Scanning Electron Microscopy (cryo FIB-SEM) enables three-dimensional and nanoscale imaging of biological specimens via a slice and view mechanism. The FIB-SEM experiments are, however, limited by a slow (typically, several hours) acquisition process and the high electron doses imposed on the beam sensitive specimen can cause damage. In this work, we present a compressive sensing variant of cryo FIB-SEM capable of reducing the operational electron dose and increasing speed. We propose two Targeted Sampling (TS) strategies that leverage the reconstructed image of the previous sample layer as a prior for designing the next subsampling mask. Our image recovery is based on a blind Bayesian dictionary learning approach, i.e., Beta Process Factor Analysis (BPFA). This method is experimentally viable due to our ultra-fast GPU-based implementation of BPFA. Simulations on artificial compressive FIB-SEM measurements validate the success of proposed methods: the operational electron dose can be reduced by up to 20 times. These methods have large implications for the cryo FIB-SEM community, in which the imaging of beam sensitive biological materials without beam damage is crucial.Comment: Submitted to ICASSP 202