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Solution of Wiener-Hopf and Fredholm integral equations by fast Hilbert and Fourier transforms
No full textWe present numerical methods based on the fast Fourier transform (FFT) to solve convolution integral equations on a semi-infinite interval (Wiener-Hopf equation) or on a finite interval (Fredholm equation). We improve a FFT-based method for the Wiener-Hopf equation due to Henery by expressing it in terms of the Hilbert transform and computing the latter in a more sophisticated way with a sinc function expansion. We further enhance the error convergence using a spectral filter. We then generalise our method to the Fredholm equation by reformulating it as two coupled Wiener-Hopf equations and solving them iteratively. We provide numerical tests and open-source code
Mechanisms Supporting Policy Coherence In UK Food Strategies
No full textSUMMARY
Food policy has been an active area in the UK throughout 2025. Three of four UK nations having recently published food strategies and plans, with another in preparation, all within a changing geopolitical context. Against this backdrop, this working paper highlights key gaps and potential actions for fostering coherence within food strategies and governments in the UK based on an analysis of UK food strategies using a new tool, the Food Systems Policy Coherence (FSPC) Diagnostic tool. This tool, composed of two modules, aims to provide a simplified and standardised approach to measure policy coherence.
We applied Module 1 of the FSPC tool, which focuses on government structures and mechanisms to support coherence and covers five domains: Framework Documents; Political Commitment; Capacity and Implementation; Coordination Structures; Inclusivity, Stakeholder Engagement and Voice; and Monitoring and Accountability. For the UK strategies, Political Commitment was the best-performing domain, with all nations scoring highly, as a national food strategy or plan was in place, or in development, in each case. Capacity and Implementation, Coordinating Structures, and Monitoring and Accountability were the areas where most improvement is needed. Scores could be improved by including targets, key performance indicators, and detailed plans for monitoring progress and revising the food strategy
A hybrid combination approach to forecast freight rates volatility
Get PDFThe aim of this paper is to investigate the performance of machine learning algorithms along with traditional GARCH and GARCH-MIDAS models in forecasting volatility of dry bulk shipping freight rates, known as one of the most volatile asset classes. In doing so, we introduce a new market tightness index, capturing physical constraints in shipping markets as an explanatory variable. The results suggest that significant incremental information can be extracted by Machine Learning algorithms from additional volatility predictors with minimal noise fitting, if regularization is applied. However, traditional GARCH models perform better in capturing the long-term persistence of the volatility. Therefore, a novel hybrid ensemble stacking algorithm that combines GARCH models and tree-based algorithms is proposed. This hybrid model, which utilizes exogenous predictors and the GARCH-MIDAS specification with the marked tightness index, produces accurate and robust out-of-sample volatility forecasts over a range of time horizons, from one day to one month
The Impact of Changes in Real Income and the Real Effective Exchange Rate on Trade in Goods and Services
Get PDFWe use foreign trade data on both imports and exports of goods and services among a group of 15 advanced economies to determine the incomes and price elasticities of demand for exports and imports of goods, services and goods and services combined in the long run. We find that changes in foreign and domestic income have, as expected, a positive long‐run impact on the demand for exports and imports, respectively, with the impact of income changes being typically greater on the demand for services than on the demand for goods. We also confirm that a depreciation in the real effective exchange rate leads to an increase in exports for most of the economies, while the impact on the demand for imports is mixed. Finally, we find a large degree of heterogeneity in the income and price elasticities of demand for trade in goods and services among the 15 economies
Challenges and opportunities for inclusive, equitable and accessible school holiday clubs for children with special educational needs and disabilities (SEND)
Get PDFBackground
Children with special educational needs and disabilities (SEND), particularly those from families with low-income, experience inequities across educational and health outcomes. The school holidays are difficult for families with low-income, prompting UK government programmes including the Holiday Activity and Food (HAF) clubs. Little is known about how inclusive these holiday clubs are for children with SEND, despite this being a group who may particularly benefit. This study is embedded within a wider project on the HAF programme to explore the challenges and opportunities for inclusive and accessible holiday club provision and provides recommendations for the HAF Toolkit.
Methods
Participant experiences were captured using two qualitative methods: 1) interviews with holiday programme delivery staff and parents of attendees (staff n=28, parents n=10); 2) focus group discussions at creative workshops with parents whose children are eligible for the holiday programme but do not attend (n=22). The Framework Method and Reflexive Thematic Analysis were used.
Methods
Participant experiences were captured using two qualitative methods: (1) interviews with holiday programme delivery staff and parents of attendees (staff n = 28, parents n = 10); (2) focus group discussions at creative workshops with parents whose children are eligible for the holiday programme but do not attend (n = 22). The Framework Method and Reflexive Thematic Analysis were used.
Results
Findings reveal challenges and opportunities around accessing and experiencing the holiday clubs for children with SEND. Access subthemes included: lack of clarity in advertising whether clubs welcome children with SEND; frequent non-disclosure from parents of their child’s needs; accessible transportation; and additional resources needed for SEND provision. Experience subthemes included: food provision for children with SEND; training and staffing that covers the range of needs; and the experiences of children within mainstream provision versus specialist providers of SEND clubs. All participant groups illuminated areas where holiday clubs could be improved to ensure an enjoyable and equitable experience for children with SEND. However, wider debates around ableism and the challenges children with SEND face in society broadly were also illustrated in data. Further, the current economic context and the additional resources needed to support inclusive holiday club provision underpinned much of the data. Opportunities were highlighted such as parent volunteers and external investment, that could maximise the potential of the current government funding.
Conclusions
Our findings highlight issues in access and experience of holiday clubs for children with SEND and provide potential avenues for promoting inclusivity, including how adaptations to the Toolkit could specifically improve HAF. There are considerable challenges to achieving inclusive holiday clubs (financial or otherwise) but if we are to reduce inequities, addressing these should be a public health priority
Ideology and polarization set the agenda on social media
Get PDFThe abundance of information on social media has reshaped public discussions, shifting attention to the mechanisms that drive online discourse. This study analyzes large-scale Twitter (now X) data from three global debates-Climate Change, COVID-19, and the Russo-Ukrainian War-to investigate the structural dynamics of engagement. Our findings reveal that discussions are not primarily shaped by specific categories of actors, such as media or activists, but by shared ideological alignment. Users consistently form polarized communities, where their ideological stance in one debate predicts their positions in others. This polarization transcends individual topics, reflecting a broader pattern of ideological divides. Furthermore, the influence of individual actors within these communities appears secondary to the reinforcing effects of selective exposure and shared narratives. Overall, our results underscore that ideological alignment, rather than actor prominence, plays a central role in structuring online discourse and shaping the spread of information in polarized environments
A matter of respect: ‘Research in Autism Spectrum Disorders’ changing our name to ‘Research in Autism’
No full textRacial Capitalism: A Guide for the Naysayer
No full textRacial capitalism is celebrated by its adherents, as a concept that links together the ideological political processes of ‘race’-making and the accumulation of wealth. But it is also derided by its critics, as a mere fad that lacks analytical rigour. As an unashamedly political term that has influenced generations of thinkers and activists that are conversant with Black radical thought, it is bound to inspire such different reactions. This chapter is an attempt to do justice to racial capitalism as a concept, by arguing that it is a valuable resource for understanding the political and economic system it was created to describe. What follows, therefore, is a short introduction to what racial capitalism is, does and why it matters
Algebras of Actions in an Agent’s Representations of the World
Get PDFLearning efficient representations allows robust processing of data, data that can then be generalised across different tasks and domains, and it is thus paramount in various areas of Artificial Intelligence, including computer vision, natural language processing and reinforcement learning, among others. Within the context of reinforcement learning, we propose in this paper a mathematical framework to learn representations by extracting the algebra of the transformations of worlds from the perspective of an agent. As a starting point, we use our framework to reproduce representations from the symmetry-based disentangled representation learning (SBDRL) formalism proposed by [1] and prove that, although useful, they are restricted to transformations that respond to the properties of algebraic groups. We then generalise two important results of SBDRL –the equivariance condition and the disentangling definition– from only working with group-based symmetry representations to working with representations capturing the transformation properties of worlds for any algebra, using examples common in reinforcement learning and generated by an algorithm that computes their corresponding Cayley tables. Finally, we combine our generalised equivariance condition and our generalised disentangling definition to show that disentangled sub-algebras can each have their own individual equivariance conditions, which can be treated independently, using category theory. In so doing, our framework offers a rich formal tool to represent different types of symmetry transformations in reinforcement learning, extending the scope of previous proposals and providing Artificial Intelligence developers with a sound foundation to implement efficient applications
Interpreting evidence on the association between multiple adverse childhood experiences and mental and physical health outcomes in adulthood: protocol for a systematic review assessing causality
Get PDFIntroduction
Research suggests that adverse childhood experiences can have a lasting influence on children’s development that result in poorer health outcomes in adulthood. Like other exposure-outcome relationships, however, there is uncertainty about the extent to which the relationship between adverse childhood experiences and health is causal or attributable to other factors. The aim of this systematic review is to better understand the nature and extent of the evidence available to infer a causal relationship between adverse childhood experiences and health outcomes in adulthood.
Methods and analysis
A systematic review of evidence from cross-sectional and longitudinal studies will be conducted to examine the association between multiple adverse childhood experiences and mental and physical health outcomes in adulthood. A comprehensive search for articles will be conducted in four databases (Medline, CINAHL, PsycInfo and Web of Science) and Google Scholar. We will include studies published since 2014: (1) of adults aged 16 years or over with exposure to adverse childhood experiences before age 16 years from general population samples; (2) that report measures across multiple categories of childhood adversity, including both direct and indirect types and (3) report outcomes related to disease morbidity and mortality. Two reviewers will independently screen all titles and abstracts and full texts of potentially relevant studies. Included studies will be evaluated for risk of bias with the Risk Of Bias In Non-randomised Studies of Exposures tool. Data extraction will include extraction of study characteristics; measurement of adverse childhood experiences, outcome assessment and measurement of outcomes; details about confounding variables and contextual variables; methods of statistical analysis; and methods for assessing causal inference. We will carry out a meta-analysis and incorporate causal assessment with reference to the Bradford Hill criteria and the Grading of Recommendations Assessment, Development and Evaluation framework.
Ethics and dissemination
This study is a systematic review protocol collecting data from published literature and does not require approval from an institutional review board. The findings from this systematic review will be disseminated via a peer-reviewed journal publication, professional networks and social media
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