Hasil untuk "History of Great Britain"

G. Spivak

Andrew Iskauskas, Max Knobbe, Frank Krauss et al.

We apply, for the first time, Bayes Linear Emulation and History Matching to the calibration of non-perturbative models in Monte Carlo event generators. In contrast to the usual approach of "Monte Carlo tuning", History Matching does not result in best-fit plus ellipsoidal parameter uncertainty estimates but instead identifies all parameter space regions that are consistent with data. This approach leads to a systematic and robust quantification of parametric uncertainties in the models, especially in those challenging cases where different, possibly disjoint, regions of parameter space deliver similar results, which are usually not properly treated with current methodology. We highlight the power of this method with the hadronisation models available through Sherpa: the built-in cluster fragmentation Ahadic and string fragmentation through an interface to Pythia.

Jonathan Parry

This essay examines Disraeli’s last two published novels, Lothair (1870) and Endymion (1880), as works of political sociology. The mature Disraeli was fascinated by generalisation and social analysis. He naturally viewed the world in terms of dialectic. He assessed contemporary problems as a series of tensions between opposing forces. The task of the politician was to try to resolve them and to minimise social conflict. However, in Tancred (1847), the last novel he had published before Lothair, he had argued that the traditional harmonies of the world had been destroyed since the French Revolution, and that it was not clear how they could be restored. Lothair revisits some of the main themes of Tancred, especially the idea that Semite and Aryan characteristics were essential to the genius of mankind and in creative tension with each other. It connects this tension to the contemporary battle across Europe between religion and secular republicanism. Disraeli sought to communicate to a wide readership the importance of this battle, which he presented as one largely between the Catholic Church and the revolutionary secret societies. Though Lothair contained a lot of his familiar satire, it portrayed this culture war as a serious conflict of ideas in which most leaders on both sides were motivated by high-minded ideals. One subsidiary aim of the book was to explain the Irish policy that Disraeli had adopted on becoming Prime Minister in 1868, which had aimed to combine Anglican and Roman Catholic parliamentary groups. Gladstone and the Liberal party had defeated it and the electorate had then rejected it. Lothair reminded them of their insularity, underlining that mankind needed religious institutions, and that this need would be met by a revived Papacy if the state failed to support Anglicanism. But the novel also contained a lot of social analysis of Britain, which explained to readers—and to Disraeli himself—why the country seemed oblivious to dialectical clashes like those which he had tried to publicise in 1868. Disraeli then discussed Britain’s political sociology at more length in Endymion, which he began shortly after 1870 and published after his second premiership ended in 1880. The book showed that British politics was materialistic but socially stable. The dominance of commercial topics, the desire to make money, and the acceptance of social and economic change, all created a British political world in which politician-administrators had a natural advantage over those who appeared to resist change. But British economic and social success meant that the interests of land and money, and country and town, were easily reconciled. Radicals’ zeal for change was blunted by social reality, human vanity, and the pull of history—as well as by the continuing power of private influences, and the influence of aristocratic women in particular.

Akash Gupta, Ivaxi Sheth, Vyas Raina et al.

With the recent emergence of powerful instruction-tuned large language models (LLMs), various helpful conversational Artificial Intelligence (AI) systems have been deployed across many applications. When prompted by users, these AI systems successfully perform a wide range of tasks as part of a conversation. To provide some sort of memory and context, such approaches typically condition their output on the entire conversational history. Although this sensitivity to the conversational history can often lead to improved performance on subsequent tasks, we find that performance can in fact also be negatively impacted, if there is a task-switch. To the best of our knowledge, our work makes the first attempt to formalize the study of such vulnerabilities and interference of tasks in conversational LLMs caused by task-switches in the conversational history. Our experiments across 5 datasets with 15 task switches using popular LLMs reveal that many of the task-switches can lead to significant performance degradation.

Guy Tennenholtz, Nadav Merlis, Lior Shani et al.

We introduce Dynamic Contextual Markov Decision Processes (DCMDPs), a novel reinforcement learning framework for history-dependent environments that generalizes the contextual MDP framework to handle non-Markov environments, where contexts change over time. We consider special cases of the model, with a focus on logistic DCMDPs, which break the exponential dependence on history length by leveraging aggregation functions to determine context transitions. This special structure allows us to derive an upper-confidence-bound style algorithm for which we establish regret bounds. Motivated by our theoretical results, we introduce a practical model-based algorithm for logistic DCMDPs that plans in a latent space and uses optimism over history-dependent features. We demonstrate the efficacy of our approach on a recommendation task (using MovieLens data) where user behavior dynamics evolve in response to recommendations.

P. Lindert, J. Williamson

Meng-Hua Zhu, Natalia Artemieva, Alessandro Morbidelli et al.

The importance of highly siderophile elements (HSEs) to track planetary late accretion has long been recognized. However, the precise nature of the Moon's accretional history remains enigmatic. There exists a significant mismatch of HSE budgets between the Earth and Moon, with the Earth disproportionally accreted far more HSEs than the Moon did. Several scenarios have been proposed to explain this conundrum, including the delivery of HSEs to Earth by a few big impactors, the accretion of pebble-sized objects on dynamically cold orbits that enhanced the Earth's gravitational focusing factor, and the "sawtooth model" with much reduced impact flux before ~4.10 Gyr. However, most of these models assume a high impactor retention ratio f (fraction of impactor mass retained on the target) for the Moon. Here, we performed a series of impact simulations to quantify the f-value, followed by a Monte Carlo procedure enacting a monotonically decaying impact flux, to compute the mass accreted into lunar crust and mantle over their histories. We found that the average f-value for the Moon's entire impact history is about 3 times lower than previously estimated. Our results indicate that, to match the HSE budget of lunar crust and mantle, the retention of HSEs should have started ~ 4.35 Gyr ago, when most of lunar magma ocean was solidified. Mass accreted prior to 4.35 Gyr must have lost its HSE to the lunar core, presumably during the lunar mantle crystallization. The combination of a low impactor retention ratio and a late retention of HSEs in the lunar mantle provide a realistic explanation for the apparent deficit of Moon's late accreted mass relative to the Earth.

Natalia Tomashenko, Christian Raymond, Antoine Caubriere et al.

This work investigates the embeddings for representing dialog history in spoken language understanding (SLU) systems. We focus on the scenario when the semantic information is extracted directly from the speech signal by means of a single end-to-end neural network model. We proposed to integrate dialogue history into an end-to-end signal-to-concept SLU system. The dialog history is represented in the form of dialog history embedding vectors (so-called h-vectors) and is provided as an additional information to end-to-end SLU models in order to improve the system performance. Three following types of h-vectors are proposed and experimentally evaluated in this paper: (1) supervised-all embeddings predicting bag-of-concepts expected in the answer of the user from the last dialog system response; (2) supervised-freq embeddings focusing on predicting only a selected set of semantic concept (corresponding to the most frequent errors in our experiments); and (3) unsupervised embeddings. Experiments on the MEDIA corpus for the semantic slot filling task demonstrate that the proposed h-vectors improve the model performance.

I. Horvath, D. Szécsi, J. Hakkila et al.

The Hercules-Corona Borealis Great Wall is a statistically significant clustering of gamma-ray bursts around redshift 2. Motivated by recent theoretical results indicating that a maximal Universal structure size may indeed coincide with its estimated size (2-3Gpc), we reexamine the question of this Great Wall's existence from both observational and theoretical perspectives. Our statistical analyses confirm the clustering's presence in the most reliable data set currently available, and we present a video showing what this data set looks like in~3D. Cosmological explanations (i.e. having to do with the distribution of gravitating matter) and astrophysical explanations (i.e. having to do with the rate of star formation over cosmic time and space) regarding the origin of such a structure are presented and briefly discussed and the role of observational bias is also discussed at length. This, together with the scientific importance of using gamma-ray bursts as unique cosmological probes, emphasises the need for future missions such as the THESEUS satellite which will provide us with unprecedentedly homogeneous data of gamma-ray bursts with measured redshifts. We conclude from all this that the Hercules-Corona Borealis Great Wall may indeed be the largest structure in the Universe - but to be able to decide conclusively whether it actually exists, we need THESEUS.

Saeed Soori, Bugra Can, Mert Gurbuzbalaba et al.

ASYNC is a framework that supports the implementation of asynchrony and history for optimization methods on distributed computing platforms. The popularity of asynchronous optimization methods has increased in distributed machine learning. However, their applicability and practical experimentation on distributed systems are limited because current bulk-processing cloud engines do not provide a robust support for asynchrony and history. With introducing three main modules and bookkeeping system-specific and application parameters, ASYNC provides practitioners with a framework to implement asynchronous machine learning methods. To demonstrate ease-of-implementation in ASYNC, the synchronous and asynchronous variants of two well-known optimization methods, stochastic gradient descent and SAGA, are demonstrated in ASYNC.

G. Boulenger

W. Borah

Yonatan Belinkov, Alexander Magidow, Alberto Barrón-Cedeño et al.

Arabic is a widely-spoken language with a long and rich history, but existing corpora and language technology focus mostly on modern Arabic and its varieties. Therefore, studying the history of the language has so far been mostly limited to manual analyses on a small scale. In this work, we present a large-scale historical corpus of the written Arabic language, spanning 1400 years. We describe our efforts to clean and process this corpus using Arabic NLP tools, including the identification of reused text. We study the history of the Arabic language using a novel automatic periodization algorithm, as well as other techniques. Our findings confirm the established division of written Arabic into Modern Standard and Classical Arabic, and confirm other established periodizations, while suggesting that written Arabic may be divisible into still further periods of development.

Jian Yuan, Guozhong Xiu, Bao Shi et al.

Hereditary effects of exponentially damped oscillators with past histories are considered in this paper. Nonviscously damped oscillators involve hereditary damping forces which depend on time-histories of vibrating motions via convolution integrals over exponentially decaying functions. As a result, this kind of oscillators are said to have memory. In this work, initialization for nonviscously damped oscillators is firstly proposed. Unlike the classical viscously damped ones, information of the past history of response velocity is necessary to fully determine the dynamic behaviors of nonviscously damped oscillators. Then, initialization response of exponentially damped oscillators is obtained to characterize the hereditary effects on the dynamic response. At last, stability of initialization response is proved and the hereditary effects are shown to gradually recede with increasing of time.

M. Wallace, E. G. Burrows

Verónica Membrive Pérez

Dr. Martín Veiga Alonso is Director of the Irish Centre for Galician Studies and lecturer and co-ordinator of the Higher Diploma in Arts (Spanish) at the Department of Spanish, Portuguese and Latin American Studies at University College Cork. His main areas of research include contemporary Galician and Irish travel writing and poetry, with special focus on the Galician poet Antón Avilés de Taramancos, about whom he has published Escribir na multitude: a obra literaria de Antón Avilés de Taramancos (2014), Antón Avilés de Taramancos (2003), Biografía sonora de Avilés de Taramancos (2009), Cantos caucanos (2003) and the edited volume Raiceiras e vento. A obra poética de Antón Avilés de Taramancos (2003). Veiga is co-editor of Galicia 21: Journal of Contemporary Galician Studies and has recently edited a special issue devoted to the works of the Galician poet and essayist Xavier Queipo (2013). Furthermore, Martín Veiga is also a prolific translator and poet, and his volumes of poetry have received important awards. His collections are Tempo van de porcelana (1990), As últimas ruínas (1994, Espiral Maior Prize), Ollos de ámbar (2005, Esquío Prize) and Fundaxes (2006, Fiz Vergara Vilariño Prize). In this interview, held at University College Cork in July 2015, we discussed the historical vocation of Galician literature to look towards Ireland, as well as the role and activities of the Irish Centre for Galician Studies at UCC and the relevance and future of Galician Studies in Ireland and Europe.

Raphaële Espiet-Kilty

Since the 1970s and the introduction of a neoliberal economic model, British governments, whether Conservative or Labour, have attempted to roll back the state, particularly as far as social policy is concerned. The favoured solution has been to give power back to civil society based on the assumption that grassroots society is better able to solve the problems that affect it. The reasoning is clearly that philanthropy can cure Britain’s ailing society whereas welfare policies cannot. In addition to the issue of the changing relation between civil society and the state, another related issue needs to be considered: that of the power of civil society. Imagined? Idealised? Effective? Can civil society replace the welfare state? To answer these questions, one needs to consider who the volunteers are and what causes they commit themselves to, focussing on 2010-2015, a period during which the coalition government urged civil society or the Big Society to re-build itself to fill the gaps left by the dismantling of the welfare state accelerated by austerity-driven reductions in public funds.