Hasil untuk "History of Great Britain"

Lvmin Zhang, Shengqu Cai, Muyang Li et al.

Autoregressive video generation relies on history context for content consistency and storytelling. As video histories grow longer, efficiently encoding them remains an open problem - particularly for personal users and local workflows where compute and memory budgets are limited. We present a lightweight history encoder that maps long video histories into short-length embeddings, pretrained with a frame query objective that learns to attend to content features at arbitrary temporal positions. The pretraining stage provides the encoder with dense history coverage on large-scale video data; the subsequent finetuning stage adapts the pretrained encoder under an autoregressive video generation objective to establish content-level consistency. In this way, the lightweight embeddings achieve comparable performance to heavier alternatives. We evaluate the framework with ablative settings and discuss the architecture designs.

Thibaud Harrois, Pauline Schnapper

The article examines the continuity and potential fragility of the United Kingdom’s political consensus on support for Ukraine in the wake of Russia’s full-scale invasion in 2022. Although peripheral to British pre-election debates, foreign policy, especially regarding Ukraine, nonetheless emerged as a focal point of strategic alignment among Britain’s main political parties in 2024. Drawing on the framework of neo-classical realism, the article situates British foreign policy within the dual pressures of international threats and domestic political dynamics. It assesses manifestos from the 2024 general election, initial policy actions by Keir Starmer’s government and evolving public opinion. While both Conservative and Labour governments provided strong military, economic, and humanitarian support to Ukraine, underpinned by legal and ethical justifications, this apparent continuity and stability masks underlying tensions. The long-term stability of this consensus was challenged by rising economic concerns, voter fatigue, and the populist rhetoric of Reform UK. Moreover, the reelection of Donald Trump as President of the USA introduced new uncertainties for transatlantic cooperation, prompting the UK to seek deeper partnerships with European allies. The article concludes that while the UK’s current position remains one of strong support, it is founded on politically and economically fragile foundations that may evolve as domestic and international conditions change.

Se-eun Yoon, Ahmad Bin Rabiah, Zaid Alibadi et al.

Customers reach out to online live chat agents with various intents, such as asking about product details or requesting a return. In this paper, we propose the problem of predicting user intent from browsing history and address it through a two-stage approach. The first stage classifies a user's browsing history into high-level intent categories. Here, we represent each browsing history as a text sequence of page attributes and use the ground-truth class labels to fine-tune pretrained Transformers. The second stage provides a large language model (LLM) with the browsing history and predicted intent class to generate fine-grained intents. For automatic evaluation, we use a separate LLM to judge the similarity between generated and ground-truth intents, which closely aligns with human judgments. Our two-stage approach yields significant performance gains compared to generating intents without the classification stage.

Tri Tran

Jacob Carlson, Tom Bryan, Melissa Dell

Thousands of users consult digital archives daily, but the information they can access is unrepresentative of the diversity of documentary history. The sequence-to-sequence architecture typically used for optical character recognition (OCR) - which jointly learns a vision and language model - is poorly extensible to low-resource document collections, as learning a language-vision model requires extensive labeled sequences and compute. This study models OCR as a character level image retrieval problem, using a contrastively trained vision encoder. Because the model only learns characters' visual features, it is more sample efficient and extensible than existing architectures, enabling accurate OCR in settings where existing solutions fail. Crucially, the model opens new avenues for community engagement in making digital history more representative of documentary history.

Teppei Minoda, Shintaro Yoshiura, Tomo Takahashi

We argue that observations of the reionization history can be used as a probe of primordial density fluctuations, particularly on small scales. Although the primordial curvature perturbations are well constrained from measurements of cosmic microwave background (CMB) anisotropies and large-scale structure, these observational data probe the curvature perturbations only on large scales, and hence its information on smaller scales will give us further insight on primordial fluctuations. Since the formation of early galaxies is sensitive to the amplitude of small-scale perturbations, and then, in turn, gives an impact on the reionization history, one can probe the primordial power spectrum on small scales through observations of reionization. In this work, we focus on the running spectral indices of the primordial power spectrum to characterize the small-scale perturbations, and investigate their impact on the reionization history using the numerical code \texttt{21cmFAST}, which adopts a simple but commonly used reionization model. We also derive the constraints on the running spectral indices from observations of the reionization history indicated by the luminosity function of the Lyman-$α$ emitters. We show that the reionization history, in combination with large-scale observations such as CMB, would be a useful tool to investigate primordial density fluctuations.

Ciarán O'Rourke

Literary critics have generally cast Derek Mahon as a humanist in dialogue with existentialist themes, or as a poet of exile, while highlighting the qualities of irony and skepticism that permeate his work. This paper is receptive to such readings, but proposes an alternative emphasis, situating Mahon as an anti-capitalist writer, his poetic ventures often serving to critique and counteract what he called “the bedlam of acquisitive force / That rules us, and would rule the universe” (2018a: 59). This discussion surveys Mahon’s long-standing respect for a variety of anti-capitalist poets and thinkers, from Brecht and Pasolini to Naomi Klein; sheds light on his penetrating investigations of warfare and ecological despoliation as offshoots of imperial and capitalist expansion; and explores his advocacy of poetry as a corrective to what he viewed as the glib commercialism and intellectual complacencies accompanying market-driven globalization, or in his words, “the explosive growth of high finance / directing thought” (2020h: 67). Over the course of this paper, my objective is to present a “new” Mahon: a poet whose self-described “left-wingery” informed, and found expression in, his work and practice (2017d: 82).

Yablonskaya, Olga V.

The article examines the circumstances of emigration of children from Great Britain in the XIX–ХХ centuries based on the material of the sources. It is proved that the resettlement was caused by the pauperization of the urban population in the conditions of industrialization. In Canada, minors could be adopted or work on farms, as servants, receiving maintenance and wages. The children had to go to school. It was a prerequisite. Children’s emigration made it possible to fill the labor shortage in Canada, help in the development of the British periphery, strengthen the ties of the metropolis and overseas possessions. Emigration was also the deportation of an overweight population and juvenile delinquents. The lack of proper supervision has led to child abuse and exploitation. The author concludes, that the majority of British migrant children have adapted to Canada, have been given the opportunity to self-actualize.

Xuan Long Do, Bowei Zou, Liangming Pan et al.

Conversational question generation (CQG) serves as a vital task for machines to assist humans, such as interactive reading comprehension, through conversations. Compared to traditional single-turn question generation (SQG), CQG is more challenging in the sense that the generated question is required not only to be meaningful, but also to align with the occurred conversation history. While previous studies mainly focus on how to model the flow and alignment of the conversation, there has been no thorough study to date on which parts of the context and history are necessary for the model. We argue that shortening the context and history is crucial as it can help the model to optimise more on the conversational alignment property. To this end, we propose CoHS-CQG, a two-stage CQG framework, which adopts a CoHS module to shorten the context and history of the input. In particular, CoHS selects contiguous sentences and history turns according to their relevance scores by a top-p strategy. Our model achieves state-of-the-art performances on CoQA in both the answer-aware and answer-unaware settings.

Damian Clarke, Manuel Llorca Jaña, Daniel Pailañir

Quantile regression and quantile treatment effect methods are powerful econometric tools for considering economic impacts of events or variables of interest beyond the mean. The use of quantile methods allows for an examination of impacts of some independent variable over the entire distribution of continuous dependent variables. Measurement in many quantative settings in economic history have as a key input continuous outcome variables of interest. Among many other cases, human height and demographics, economic growth, earnings and wages, and crop production are generally recorded as continuous measures, and are collected and studied by economic historians. In this paper we describe and discuss the broad utility of quantile regression for use in research in economic history, review recent quantitive literature in the field, and provide an illustrative example of the use of these methods based on 20,000 records of human height measured across 50-plus years in the 19th and 20th centuries. We suggest that there is considerably more room in the literature on economic history to convincingly and productively apply quantile regression methods.

Jan Zapletal, Raphael Watschinger, Günther Of et al.

The presented paper concentrates on the boundary element method (BEM) for the heat equation in three spatial dimensions. In particular, we deal with tensor product space-time meshes allowing for quadrature schemes analytic in time and numerical in space. The spatial integrals can be treated by standard BEM techniques known from three dimensional stationary problems. The contribution of the paper is twofold. First, we provide temporal antiderivatives of the heat kernel necessary for the assembly of BEM matrices and the evaluation of the representation formula. Secondly, the presented approach has been implemented in a publicly available library besthea allowing researchers to reuse the formulae and BEM routines straightaway. The results are validated by numerical experiments in an HPC environment.

Manuela D’Amore

Centred on the Victorian intellectual Harriet Martineau (1802-76), this paper will show how she lived her condition as a deaf person and an ‘invalid’. Detailed information about her memories of the ‘world of sound’—also the impact that deafness had on her life—can be found in her hybrid prose. Blending different genres and text forms, Letter to the Deaf (1834), the journal article ‘Deaf Mutes’ (1854) and her two-volume Autobiography (1855–1877) are clear on her determination to use her most painful experiences to promote social change. In fact, she immediately started from the feelings that she associated with the pleasures of sound and music. Before she lost her hearing as a young adolescent, she enjoyed singing and ‘was never out of tune’: it was only after she became fully aware of her disability that she urged her ‘fellow sufferers’ to trust even experimental science to gain ‘every breath of sound’ and play an active role in the public sphere. An eclectic and prolific writer, Harriet Martineau contributed to a thorough rediscussion of the nineteenth-century cult of invalidism in England. Even today her works show how she challenged Victorian convictions on deafness and traditional medical practices, while laying the basis for a more equal and inclusive society.

T. Tomlinson, A. Fernandes, A. Grollman

Aristolochia herbals have a 2500-year history of medicinal use. We focused this article on Portland’s Powders, an 18th-century British gout medicine containing Aristolochia herbs. The powders constitute an 18th-century iteration of an herbal remedy, which was used, with variations, since at least the fifth century BCE. The use of Portland’s Powders in Great Britain may appear to be an unusual choice for investigating a public health problem currently widespread in Asia. Yet it exemplifies long-term medicinal use of Aristolochia herbs, reflecting our argument that aristolochic acid nephropathy (AAN) is a historically persistent iatrogenic disease. Moreover, we provide compelling evidence that individuals taking Portland’s Powders for gout would have ingested toxic quantities of aristolochic acid, which causes AAN and cancer. Several factors, including long history of use, latency of toxic effects, and lack of effective regulation, perpetuate usage of Aristolochia herbals to the present day.

Takumi Nakane, Xuequan Lu, Chao Zhang

In evolutionary algorithms, genetic operators iteratively generate new offspring which constitute a potentially valuable set of search history. To boost the performance of crossover in real-coded genetic algorithm (RCGA), in this paper we propose to exploit the search history cached so far in an online style during the iteration. Specifically, survivor individuals over past few generations are collected and stored in the archive to form the search history. We introduce a simple yet effective crossover model driven by the search history (abbreviated as SHX). In particular, the search history is clustered and each cluster is assigned a score for SHX. In essence, the proposed SHX is a data-driven method which exploits the search history to perform offspring selection after the offspring generation. Since no additional fitness evaluations are needed, SHX is favorable for the tasks with limited budget or expensive fitness evaluations. We experimentally verify the effectiveness of SHX over 4 benchmark functions. Quantitative results show that our SHX can significantly enhance the performance of RCGA, in terms of accuracy.

José Francisco Fernández

Lillis Ó Laoire is a sean-nós singer and lecturer in the School of Languages, NUI Galway. He is a Donegal native and a graduate of NUI Galway and of University College Cork. He has been a visiting Professor at Loyola Marymount University, Los Angeles. He has co-authored a book (with Seán Williams) on the great Connemara singer Joe Heaney, Bright Star of the West (Oxford UP, 2011). His research interests include Gaelic song traditions and history, performance and transmission of folklore, ecocriticism and ethnomusicology. As a scholar, he has published articles in Journal of Rural Studies, Folk Life: Journal of Ethnological Studies and in the American Journal of Irish Studies, among other specialized journals. This interview took place in January 2019 at NUI Galway, where he teaches Irish language, folklore and Celtic Civilisation.

Jean-Gabriel Young, Guillaume St-Onge, Edward Laurence et al.

Network growth processes can be understood as generative models of the structure and history of complex networks. This point of view naturally leads to the problem of network archaeology: reconstructing all the past states of a network from its structure---a difficult permutation inference problem. In this paper, we introduce a Bayesian formulation of network archaeology, with a generalization of preferential attachment as our generative mechanism. We develop a sequential Monte Carlo algorithm to evaluate the posterior averages of this model, as well as an efficient heuristic that uncovers a history well correlated with the true one, in polynomial time. We use these methods to identify and characterize a phase transition in the quality of the reconstructed history, when they are applied to artificial networks generated by the model itself. Despite the existence of a no-recovery phase, we find that nontrivial inference is possible in a large portion of the parameter space as well as on empirical data.

Tatiana Viktoroff

The article examines the history of the reception of mother Maria’s poetry in Soviet and post-Soviet Russia, in France and in Great Britain. It analyses how her image and “hypostasis” became mythologized in Russian and foreign cultures in the context of mother Maria’s personality and her life-creating orientation. The author distinguishes several periods in the perception of mother Maria’s image (1965, 1989, the 2000s), analyzes the most important “portraits” of mother Maria the poet those that influenced generations; traces the changes in researchers’ approaches to the study of her work.

Ruth Barton

Jordan Cotler, Frank Wilczek

We demonstrate that temporal observables, which are sensitive to a system's history (as opposed to its state), implicate entangled histories. We exemplify protocols for measuring such observables, and algorithms for predicting the (stochastic) outcomes of such measurements. Temporal observables allow us to define, and potentially to measure, precise mathematical consequences of intrinsically disjoint, yet mutually accessible, branches within the evolution of a pure quantum state.