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In order to remain alive and relevant, cultural heritage sites have to react and adapt to changing context in a coherent manner, i.e., in a way that is in line with the memory and identity of the place. The incoherent changes, i.e., the transformations that according to the local community do not agree with a character of a place, can be destructive for the long-term vitality of urban cultural heritage. In this study, we test which factors influence social acceptance of different alternations within the context of urban historical gardens that might, in turn, ensure the resilience of the place. Our study focuses on the intangible qualities of the place measured by intrinsic value, perceived essentialism and anti-essentialism as important predictors shaping the response to change. The correlational study was conducted using an online questionnaire designed to empirically grasp intangible qualities of cultural heritage sites. Five hundred twenty-nine responses were included in the analysis. The study shows that perceived historic value, inherent value (uniqueness and importance of the place) and (anti-)essentialist character of a place capture the differences between parks well and enables the finding of interventions that are coherent with a site’s genius loci. Measuring intangible qualities of urban gardens can help to design changes that find higher approval among local community members and users of the site. We discuss how the analysis of an intrinsic value and essentialism allows for planning better spatial interventions that align with the human-centered approach to urban development.

Part 4: Communications: Types and Implementations; International audience; There are two approaches to defining subtyping relations: the syntactic and the semantic approach. In semantic subtyping, one defines a model of the language and an interpretation of types as subsets of this model. Subtyping is defined as inclusion of subsets denoting types.An orthogonal subtyping question, typical of object-oriented languages, is the nominal versus the structural subtyping. Dardha et al. [11, 12] defined boolean types and semantic subtyping for Featherweight Java (FJ) and integrated both nominal and structural subtyping, thus exploiting the benefits of both approaches. However, these benefits were illustrated only at a theoretical level, but not exploited practically.We present SFJ—Semantic Featherweight Java, an implementation of FJ which features boolean types, semantic subtyping and integrates nominal as well as structural subtyping. The benefits of SFJ, illustrated in the paper and the accompanying video (with audio/subtitles) [27], show how static type-checking of boolean types and semantic subtyping gives higher guarantees of program correctness, more flexibility and compactness of program writing.

Studies have documented that traditional motor skills (i.e. motor habits) are part of the cultural way of life that characterises each society. Yet, it is still unclear to what extent motor skills are inherited through culture. Drawing on ethnology and motor behaviour, we addressed this issue through a detailed description of traditional pottery skills. Our goal was to quantify the influence of three kinds of constraints: the transcultural constraints of wheelthrowing, the cultural constraints induced via cultural transmission, and the potters’ individual constraints. Five expert Nepalese potters were invited to produce three familiar pottery types, each in five specimens. A total of 31 different fashioning hand positions were identified. Most of them (14) were cross-cultural, ten positions were cultural, five positions were individual, and two positions were unique. Statistical tests indicated that the subset of positions used by the participants in this study were distinct from those of other cultural groups. Behaviours described in terms of fashioning duration, number of gestures, and hand position repertoires size highlighted both individual and cross-cultural traits. We also analysed the time series of the successive hand positions used throughout the fashioning of each vessel. Results showed, for each pottery type, strong reproducible sequences at the individual level and a clearly higher level of variability between potters. Overall, our findings confirm the existence of a cultural transmission in craft skills but also demonstrated that the skill is not fully determined by a cultural marking. We conclude that the influence of culture on craft skills should not be overstated, even if its role is significant given the fact that it reflects the socially transmitted part of the skill. Such research offers insights into archaeological problems in providing a representative view of how cultural constraints influence the motor skills implied in artefact manufacturing.

In this paper, we present a novel context-dependent approach to modeling word meaning, and apply it to the modeling of metaphor. In distributional semantic approaches, words are represented as points in a high dimensional space generated from co-occurrence statistics; the distances between points may then be used to quantifying semantic relationships. Contrary to other approaches which use static, global representations, our approach discovers contextualized representations by dynamically projecting low-dimensional subspaces; in these ad hoc spaces, words can be re-represented in an open-ended assortment of geometrical and conceptual configurations as appropriate for particular contexts. We hypothesize that this context-specific re-representation enables a more effective model of the semantics of metaphor than standard static approaches. We test this hypothesis on a dataset of English word dyads rated for degrees of metaphoricity, meaningfulness, and familiarity by human participants. We demonstrate that our model captures these ratings more effectively than a state-of-the-art static model, and does so via the amount of contextualizing work inherent in the re-representational process.

Large pretrained masked language models have become state-of-the-art solutions for many NLP problems. The research has been mostly focused on English language, though. While massively multilingual models exist, studies have shown that monolingual models produce much better results. We train two trilingual BERT-like models, one for Finnish, Estonian, and English, the other for Croatian, Slovenian, and English. We evaluate their performance on several downstream tasks, NER, POS-tagging, and dependency parsing, using the multilingual BERT and XLM-R as baselines. The newly created FinEst BERT and CroSloEngual BERT improve the results on all tasks in most monolingual and cross-lingual situations Comment: 10 pages, accepted at TSD 2020 conference

This paper analyzes the application of usage labels in three representative lexicographic works, namely the Portuguese, Spanish, and French Academy Dictionaries as a starting point for creating a consistent classification of usage labels and their encoding in accordance with TEI Lex-0. The use of labels is not always entirely consistent within individual dictionaries and even less so across different lexicographic projects. This makes the tasks of accurately classifying and encoding them quite difficult. This difficulty is compounded by the differences and partial incompatibilities found in the lexicographic literature on the treatment of diasystemic information. We address the existing literature and the initial classification of TEI Lex-0, and argue for the need to introduce some changes to TEI Lex-0, most notably in terms of diatextual labels. Finally, we argue that the existing classifications based on examples rather than on clear and explicit definitions of classification categories will always lack in precision and lead to mutually incompatible encodings of different dictionaries. We propose a set of definitions for usage label categories that can be adopted by TEI Lex-0 and used in other similar attempts to create interoperable lexical resources. An agreement on usage label categories is a first and necessary step before proceeding in the direction of harmonizing and standardizing the actual values of usage labels across various dictionaries and across different languages.

This article describes the procedures employed during the development of the first comprehensive machine-readable Turkish Sign Language (TiD) resource: a bilingual lexical database and a parallel corpus between Turkish and TiD. In addition to sign language specific annotations (such as non-manual markers, classifiers and buoys) following the recently introduced TiD knowledge representation (Eryiğit et al. 2016), the parallel corpus contains also annotations of dependency relations, which makes it the first parallel treebank between a sign language and an auditory-vocal language.

Background: The air traffic management (ATM) system has historically coped with a global increase in traffic demand ultimately leading to increased operational complexity. When dealing with the impact of this increasing complexity on system safety it is crucial to automatically analyse the losses of separation (LoSs) using tools able to extract meaningful and actionable information from safety reports. Current research in this field mainly exploits natural language processing (NLP) to categorise the reports,with the limitations that the considered categories need to be manually annotated by experts and that general taxonomies are seldom exploited. Methods: To address the current gaps,authors propose to perform exploratory data analysis on safety reports combining state-of-the-art techniques like topic modelling and clustering and then to develop an algorithm able to extract the Toolkit for ATM Occurrence Investigation (TOKAI) taxonomy factors from the free-text safety reports based on syntactic analysis. TOKAI is a tool for investigation developed by EUROCONTROL and its taxonomy is intended to become a standard and harmonised approach to future investigations. Results: Leveraging on the LoS events reported in the public databases of the Comisión de Estudio y Análisis de Notificaciones de Incidentes de Tránsito Aéreo and the United Kingdom Airprox Board,authors show how their proposal is able to automatically extract meaningful and actionable information from safety reports,other than to classify their content according to the TOKAI taxonomy. The quality of the approach is also indirectly validated by checking the connection between the identified factors and the main contributor of the incidents. Conclusions: Authors' results are a promising first step toward the full automation of a general analysis of LoS reports supported by results on real-world data coming from two different sources. In the future,authors' proposal could be extended to other taxonomies or tailored to identify factors to be included in the safety taxonomies.

Pitch-class distributions are of central relevance in music information retrieval, computational musicology and various other fields, such as music perception and cognition. However, despite their structure being closely related to the cognitively and musically relevant properties of a piece, many existing approaches treat pitch-class distributions as fixed templates. In this paper, we introduce the Tonal Diffusion Model, which provides a more structured and interpretable statistical model of pitch-class distributions by incorporating geometric and algebraic structures known from music theory as well as insights from music cognition. Our model explains the pitch-class distributions of musical pieces by assuming tones to be generated through a latent cognitive process on the Tonnetz, a well-established representation for harmonic relations. Specifically, we assume that all tones in a piece are generated by taking a sequence of interval steps on the Tonnetz starting from a unique tonal origin. We provide a description in terms of a Bayesian generative model and show how the latent variables and parameters can be efficiently inferred. The model is quantitatively evaluated on a corpus of 248 pieces from the Baroque, Classical, and Romantic era and describes the empirical pitch-class distributions more accurately than conventional template-based models. On three concrete musical examples, we demonstrate that our model captures relevant harmonic characteristics of the pieces in a compact and interpretable way, also reflecting stylistic aspects of the respective epoch. Paper with appendix

AbstractScientific writings, as one essential part of human culture, have evolved over centuries into their current form. Knowing how scientific writings evolved is particularly helpful in understanding how trends in scientific culture developed. It also allows us to better understand how scientific culture was interwoven with human culture generally. The availability of massive digitized texts and the progress in computational technologies today provide us with a convenient and credible way to discern the evolutionary patterns in scientific writings by examining the diachronic linguistic changes. The linguistic changes in scientific writings reflect the genre shifts that took place with historical changes in science and scientific writings. This study investigates a general evolutionary linguistic pattern in scientific writings. It does so by merging two credible computational methods: relative entropy; word-embedding concreteness and imageability. It thus creates a novel quantitative methodology and applies this to the examination of diachronic changes in the Philosophical Transactions of Royal Society (PTRS, 1665–1869). The data from two computational approaches can be well mapped to support the argument that this journal followed the evolutionary trend of increasing professionalization and specialization. But it also shows that language use in this journal was greatly influenced by historical events and other socio-cultural factors. This study, as a “culturomic” approach, demonstrates that the linguistic evolutionary patterns in scientific discourse have been interrupted by external factors even though this scientific discourse would likely have cumulatively developed into a professional and specialized genre. The approaches proposed by this study can make a great contribution to full-text analysis in scientometrics.