How to Rewrite the History of Historiography? Prolegomena for a History of the Truth in History

How to rewrite the history of historiography at the beginning of this century? This paper tries to answer this question using just four words: history, science, truth and credibility. The revision and transformation that has been done over the categories, concepts or ways of representing history, created during the nationalist modernity, leads us to question how is it possible to write history nowadays, since when those old contents and forms that settled historiographical commonplaces produced in the 19th and 20th centuries seem to have become exhausted. Therefore, we try to show how the crisis of a historical epistemology of “naturalistic” character gave rise to the possibility of considering historical discipline as part of a larger phenomenon: that of culture and its relationship to how societies remember or forget. At the same time, this displacement has also implied the construction of another class of social memory: the opening to the understanding of history as a kind of cultural memory

Entrenamiento Croslingüe para Búsqueda de Respuestas de Opción Múltiple

In this work we explore to what extent multilingual models can be trained for one language and applied to a different one for the task of Multiple Choice Question Answering. We employ the RACE dataset to fine-tune both a monolingual and a multilingual models and apply these models to another different collections in different languages. The results show that both monolingual and multilingual models can be zero-shot transferred to a different dataset in the same language maintaining its performance. Besides, the multilingual model still performs good when it is applied to a different target language. Additionally, we find that exams that are more difficult to humans are harder for machines too. Finally, we advance the state-of-the-art for the QA4MRE Entrance Exams dataset in several languages.En este trabajo exploramos en qué medida los modelos multilingües pueden ser entrenados para un solo idioma y aplicados a otro diferente para la tarea de respuesta a preguntas de opción múltiple. Empleamos el conjunto de datos RACE para ajustar tanto un modelo monolingüe como multilingüe y aplicamos estos modelos a otras colecciones en idiomas diferentes. Los resultados muestran que tanto los modelos monolingües como los multilingües pueden transferirse a un conjunto de datos diferente en el mismo idioma manteniendo su rendimiento. Además, el modelo multilingüe todavía funciona bien cuando se aplica a un idioma de destino diferente. Asimismo, hemos comprobado que los exámenes que son más difíciles para los humanos también son más difíciles para las máquinas. Finalmente, avanzamos el estado del arte para el conjunto de datos QA4MRE Entrance Exams en varios idiomas.This work has been funded by the Spanish Research Agency under CHIST-ERA LIHLITH project (PCIN-2017-085/AEI) and deepReading (RTI2018-096846-B-C21 /MCIU/AEI/FEDER,UE)

Wavelength-stepping algorithm for testing thickness, front and back surfaces of optical plates with high signal-to-noise ratio

We propose a least-squares phase-stepping algorithm (LS-PSA) consisting of only 14 steps for high-quality optical plate testing. Optical plate testing produces an infinite number of simultaneous fringe patterns due to multiple reflections. However, because of the small reflection of common optical materials, only a few simultaneous fringes have amplitudes above the measuring noise. From these fringes, only the variations of the plate's surfaces and thickness are of interest. To measure these plates, one must use wavelength-stepping, which corresponds to phase-stepping in standard digital interferometry. The designed PSA must phase-demodulate a single fringe sequence and filter out the remaining temporal fringes. In the available literature, researchers have adapted PSAs to the dimensions of particular plates. As a consequence, there are as many PSAs published as different testing plate conditions. Moreover, these PSAs are designed with too many phase-steps to provide detuning robustness well above the required level. Instead, we mathematically prove that a single 14-step LS-PSA can adapt to several testing setups. As is well known, this 14-step LS-PSA has a maximum signal-to-noise ratio (SNR) and the highest harmonics rejection among any other 14-step PSA. Due to optical dispersion and experimental length measuring errors, the fringes may have a slight phase detuning. Using propagation error theory, we demonstrate that measuring distances with around 1% uncertainty produces a small and acceptable detuning error for the proposed 14-step LS-PSA.Comment: 8 pages, 14 figures, original research under revision for publication in OPTICA's JOSA-