Hasil untuk "History of Spain"

Qiaorong S. Yu, Stephanie O'Neil, Xuejian Shen et al.

In this study, we define the novel splashback depth $\mathcal{D}$ and width $\mathcal{W}$ to examine how the splashback features of dark matter haloes are affected by the physical properties of haloes themselves. We use the largest simulation run in the hydrodynamic MillenniumTNG project. By stacking haloes in bins of halo mass, redshift, mass-dependent properties such as peak height and concentration, and halo formation history, we measure the shape of the logarithmic slope of the density profile of dark matter haloes. Our results show that the splashback depth has a strong dependence on the halo mass which follows a power law $\mathcal{D}\propto\left(\log_{10}M\right)^{2.8}$. Properties with strong correlation with halo mass demonstrate similar dependence. The splashback width has the strongest dependence on halo peak height and follows a power law $\mathcal{W}\proptoν^{-0.87}$. We provide the fitting functions of the splashback depth and width in terms of halo mass, redshift, peak height, concentrations and halo formation time. The depth and width are therefore considered to be a long term memory tracker of haloes since they depend more on accumulative physical properties, e.g., halo mass, peak height and halo formation time. They are shaped primarily by the halo's assembly history, which exerts a stronger influence on the inner density profile than short-term dynamical processes. In contrast, the splashback features have little dependence on the short term factors such as halo mass accretion rate and most recent major merger time. The splashback depth and width can therefore be used to complement information gained from quantities like the point of steepest slope or truncation radius to characterise the halo's history and inner structure.

Qishuai Zhong, Zongmin Li, Siqi Fan et al.

Effective engagement by large language models (LLMs) requires adapting responses to users' sociodemographic characteristics, such as age, occupation, and education level. While many real-world applications leverage dialogue history for contextualization, existing evaluations of LLMs' behavioral adaptation often focus on single-turn prompts. In this paper, we propose a framework to evaluate LLM adaptation when attributes are introduced either (1) explicitly via user profiles in the prompt or (2) implicitly through multi-turn dialogue history. We assess the consistency of model behavior across these modalities. Using a multi-agent pipeline, we construct a synthetic dataset pairing dialogue histories with distinct user profiles and employ questions from the Value Survey Module (VSM 2013) (Hofstede and Hofstede, 2016) to probe value expression. Our findings indicate that most models adjust their expressed values in response to demographic changes, particularly in age and education level, but consistency varies. Models with stronger reasoning capabilities demonstrate greater alignment, indicating the importance of reasoning in robust sociodemographic adaptation.

Marcial Rubio Árquez

La prison royale de Séville constitue un espace paradigmatique de la coexistence entre la monarchie, les élites citoyennes et le monde du crime. Sa taille réduite offrait des conditions de vie déshumanisantes mais, cette prison, bien que lieu d'enfermement, était un territoire poreux et intriqué. Son existence et son maintien témoignent de la coexistence paradoxale de réalités contradictoires : répression de la criminalité, expression d'une religiosité aussi hétérodoxe que populaire et manifestation de la charité des élites sévillanes. Les textes qui témoignent de cette coexistence sous différentes perspectives ont été rassemblés ici pour tenter d’en dégager le paradigme spatial.

Nanzhe Wang, Louis J. Durlofsky

Geological carbon storage entails the injection of megatonnes of supercritical CO2 into subsurface formations. The properties of these formations are usually highly uncertain, which makes design and optimization of large-scale storage operations challenging. In this paper we introduce a history matching strategy that enables the calibration of formation properties based on early-time observations. Early-time assessments are essential to assure the operation is performing as planned. Our framework involves two fit-for-purpose deep learning surrogate models that provide predictions for in-situ monitoring well data and interpreted time-lapse (4D) seismic saturation data. These two types of data are at very different scales of resolution, so it is appropriate to construct separate, specialized deep learning networks for their prediction. This approach results in a workflow that is more straightforward to design and more efficient to train than a single surrogate that provides global high-fidelity predictions. The deep learning models are integrated into a hierarchical Markov chain Monte Carlo (MCMC) history matching procedure. History matching is performed on a synthetic case with and without 4D seismic data, which allows us to quantify the impact of 4D seismic on uncertainty reduction. The use of both data types is shown to provide substantial uncertainty reduction in key geomodel parameters and to enable accurate predictions of CO2 plume dynamics. The overall history matching framework developed in this study represents an efficient way to integrate multiple data types and to assess the impact of each on uncertainty reduction and performance predictions.

Michele Moresco

As revealed by Hubble in 1928, our Universe is expanding. This discovery was fundamental to widening our horizons and our conception of space, and since then determining the rate at which our Universe is expanding has become one of the crucial measurements in cosmology. At the beginning of this century, these measurements revealed the unexpected behavior that this expansion is accelerating and allowed us to have a first glimpse of the dark components that constitute $\sim$95\% of our Universe. Cosmic chronometers represent a novel technique to obtain a cosmology-independent determination of the expansion of the Universe, based on the differential age dating of a population of very massive and passively evolving galaxies. Currently, with this new cosmological probe it is possible to constrain the Hubble parameter with an accuracy of around 5\% at $z\sim0.5$ up to 10-20\% at $z\sim2$. In this Chapter, the cosmic chronometers approach is presented, describing the method and how an optimal sample can be selected; it is then discussed how the most recent measurements of the expansion history of the Universe have been obtained with this approach, as well as the cosmological constraints that can be derived. Particular attention will be given to the systematics involved in this approach and the treatment to properly take them into account. We conclude by presenting forecasts that show how future spectroscopic surveys will significantly boost the accuracy of this method and open the possibility to a percent determination of the Hubble constant, making cosmic chronometers a powerful independent tool to derive information on the expansion history of the Universe.

María Morales-Suárez-Varela, Diana Toledo, María Amelia Fernández-Sierra et al.

Certain patient profile characteristics, such as preexisting medical conditions, can modify the risk of developing SARS-CoV-2 pneumonia among adults vaccinated and not vaccinated against pneumococcal disease. This retrospective cohort study aimed to quantify the risk of pneumonia caused by SARS-CoV-2 among individuals from 15 to 64 years old with and without pneumococcal vaccination in Spain during the 2020–2021 influenza season and establish a risk profile of patients more likely to develop SARS-CoV-2 pneumonia. Data (demographic information, patient medical history, and lifestyle habits) were gathered both directly from the patient via personal interview and by reviewing electronic medical records. In an adjusted analysis for pneumococcal vaccinated patients, visits to hospital outpatient clinics were protective while visits to primary health care services, being widowed, obese, and not using masks in outdoor open spaces were identified as risk factors. For patients who had not received a pneumococcal vaccine, visits to hospital outpatient clinics were protective, while being overweight or obese, alcohol consumption, and not using masks in outdoor open spaces were identified as risk factors. Concerning comorbidities, in the pneumococcal vaccinated group none were found to be protective but having diabetes or other respiratory diseases were identified as risk factors. In the unvaccinated group, undergoing immunosuppressive treatment and having metastatic tumors were protective factors, while cerebrovascular disease and obesity with a BMI ≥ 40 were risk factors. A similar risk profile for developing SARS-CoV-2 pneumonia in pneumococcal vaccinated and non-vaccinated individuals was found. Generally, vaccinated individuals had a lower risk of developing SARS-CoV-2. The findings suggest that vaccination against <i>S. pneumoniae</i> could prevent and reduce SARS-CoV-2 pneumonia. Additionally, this study has identified individuals with other medical conditions, such as obesity, underweight, diabetes, and a history of respiratory diseases, who are at an increased risk of developing SARS-CoV-2 pneumonia and could benefit from vaccination and supervision.

Àlex Pocino

Ressenya de  Miquel González i Sugranyes, La República a Barcelona, 1873-1874, edició i estudi introductori de Jordi Roca Vernet i presentació de documents i biografies de Ginés Puente, Barcelona, Ajuntament de Barcelona, 2023, 429 p.

Gabriel López-Martínez, Klaus Schriewer

The cemetery is a cultural landscape that represents themes of great relevance to interpret the structure of a society, roles, and hierarchies, as a reflection of its social life. The cemetery gathers a whole symbolic universe where local social histories are represented, beyond the history of art and the architectural aspect. As a heritage element, the cemetery shows us the socio-cultural changes of a territory: religious questioning, changes linked to the family, individualization of contemporary society or broader questions about socio-economic structure. This article presents the experience conducted during the last 6 years in the Cemetery “Nuestro Padre Jesús” in Murcia (Spain), through a collaboration among the Sociedad Murciana de Antropolgía (SOMA), the University of Murcia and the Municipality of Murcia, developing the project “Funerary Cultures”, whose main objective is to promote the heritage, cultural and historical values of the funerary culture. Specifically, as a result of this teaching innovation experience, the six thematic guides to visit the cemetery are presented as an experience of <i>patrimonialization</i> of elements of the cemetery and its consequent selection and consensus exercise to determine what was considered as heritage in the context of the cemetery. Finally, a proposal of a systematic process in the valuation and selection of the material objects in the cemetery is presented; this proposal allows us to establish a debate on what considerations to take into account when considering the relationship between cultural heritage and the cemetery as a cultural landscape in permanent transformation.

Jiamin Yu

With the popularity of Telematics and Self-driving, more and more rating factors, such as mileage, route, driving behavior, etc., are introduced into actuarial models. There are quite a few doubts and disputes on the rationality and accuracy of the selection of rating variables, but it does not involve the widely accepted historical claim records. Recently, Tesla Insurance released a new generation of Safety Score-based insurance, irrespective of accident history. Forward-looking experts and scholars began to discuss whether claim history will disappear in the future auto insurance rate-making system. Therefore, this paper proposes a new risk variable elimination method as well as a real-time road risk model design framework and concludes that claim history will be regarded as a "noise" factor and deprecated in the Pay-How-You-Drive model.

Arno Thomaes, Sylvie Barbalat, Marco Bardiani et al.

To address the decline in biodiversity, international cooperation in monitoring of threatened species is needed. Citizen science can play a crucial role in achieving this challenging goal, but most citizen science projects have been established at national or regional scales. Here we report on the establishment and initial findings of the European Stag Beetle Monitoring Network (ESBMN), an international network of stag beetle (<i>Lucanus cervus</i>) monitoring schemes using the same protocol. The network, started in 2016, currently includes 14 countries (see results) but with a strong variation in output regarding the number of transects (148 successful transects in total) and transect walks (1735). We found differences across European regions in the number of stag beetles recorded, related to phenology and temperature, but not for time of transect start. Furthermore, the initial experiences of the ESBMN regarding international cooperation, citizen science approach, and drop-out of volunteers is discussed. An international standardised protocol that allows some local variation is essential for international collaboration and data management, and analysis is best performed at the international level, whereas recruiting, training, and maintaining volunteers is best organised locally. In conclusion, we appeal for more joint international citizen science-based monitoring initiatives assisting international red-listing and conservation actions.

Rik Koncel-Kedziorski, Noah A. Smith

We introduce a technique for improving document-level language models (LM) by leveraging "ancient history": text that is outside the LM's current context window. We learn an auxiliary function to select spans from the ancient history which can help the LM to predict future text. The selected text spans are then copied directly into the LM's context window, replacing less predictive spans. This method can improve perplexity of pretrained LMs with no updates to the LM's own parameters. We further observe that an auxiliary function trained in a specific textual domain like Wikipedia will also work in a substantially different domain such as scientific publications. With this technique we see a 7 percent perplexity reduction on Wikipedia articles, and a 12 percent perplexity reduction on scientific texts.

Clement Etienam

The work discussed and presented in this paper focuses on the history matching of reservoirs by integrating 4D seismic data into the inversion process using machine learning techniques. A new integrated scheme for the reconstruction of petrophysical properties with a modified Ensemble Smoother with Multiple Data Assimilation (ES-MDA) in a synthetic reservoir is proposed. The permeability field inside the reservoir is parametrised with an unsupervised learning approach, namely K-means with Singular Value Decomposition (K-SVD). This is combined with the Orthogonal Matching Pursuit (OMP) technique which is very typical for sparsity promoting regularisation schemes. Moreover, seismic attributes, in particular, acoustic impedance, are parametrised with the Discrete Cosine Transform (DCT). This novel combination of techniques from machine learning, sparsity regularisation, seismic imaging and history matching aims to address the ill-posedness of the inversion of historical production data efficiently using ES-MDA. In the numerical experiments provided, I demonstrate that these sparse representations of the petrophysical properties and the seismic attributes enables to obtain better production data matches to the true production data and to quantify the propagating waterfront better compared to more traditional methods that do not use comparable parametrisation techniques.

Kaiqing Zhang, Erik Miehling, Tamer Başar

In decentralized stochastic control, standard approaches for sequential decision-making, e.g. dynamic programming, quickly become intractable due to the need to maintain a complex information state. Computational challenges are further compounded if agents do not possess complete model knowledge. In this paper, we take advantage of the fact that in many problems agents share some common information, or history, termed partial history sharing. Under this information structure the policy search space is greatly reduced. We propose a provably convergent, online tree-search based algorithm that does not require a closed-form model or explicit communication among agents. Interestingly, our algorithm can be viewed as a generalization of several existing heuristic solvers for decentralized partially observable Markov decision processes. To demonstrate the applicability of the model, we propose a novel collaborative intrusion response model, where multiple agents (defenders) possessing asymmetric information aim to collaboratively defend a computer network. Numerical results demonstrate the performance of our algorithm.

Débora Cota

The clay in Josefina Plá (Spain, 1903 - Paraguay, 1999) presents a grandiose and unfinished archive on the cultural history of Paraguay and in its interior shows an effective concern with the Paraguayan cultural identity, as well as the appreciation of the figure of the Other claiming it as forming element of such culture. This work, therefore, is dedicated to the archive policies adopted by her about the clay, especially to what is meant by a " memory desire " and a "identity desire " linked to the construction of the history of Paraguay. It starts, especially, from the analysis of the tale “La mano en la tierra” and the author's study on pottery, titled La cerámica popular paraguaya (1994). But, it is also considered its ceramic production and its study on the Spanish-Guarani clay. In these works, clay is a productive element and presents itself as a place of archive (DERRIDA) where Paraguay is printed, inscribed, consigned and produced. Josefina Plá arrives in Paraguay in 1926 and gets involved with the country's assumed culture, in many cases the role of propellant, systematizer and conveyor the Paraguayan culture. In addition to being an artist and writer, she constantly participates in the discussion, debates and research, developing the important task of archivist of that culture.

Chris Kirrane

This paper examines the history of previous examples of EMU from the viewpoint that state actors make decisions about whether to participate in a monetary union based on rational self-interest concerning costs and benefits to their national economies. Illustrative examples are taken from nineteenth century German, Italian and Japanese attempts at monetary integration with early twentieth century ones from the Latin Monetary Union and the Scandinavian Monetary Union and contemporary ones from the West African Monetary Union and the European Monetary System. Lessons learned from the historical examples will be used to identify issues that could arise with the move towards closer EMU in Europe.

Tony Sit, Zhiliang Ying, Yi Yu

Statistical analysis on networks has received growing attention due to demand from various emerging applications. In dynamic networks, one of the key interests is to model the event history of time-stamped interactions amongst nodes. We propose to model dynamic directed communication networks via multivariate counting processes. A pseudo partial likelihood approach is exploited to capture the network dependence structure. Asymptotic results of the resulting estimation are established. Numerical results are performed to demonstrate effectiveness of our proposal.

P. Lamb, R. Peppler

K. Hoganson

M. Potrony, J. Puig-Butillé, P. Aguilera et al.

J. Leeman, Lisa M. Rabin, Esperanza Román Mendoza