Primeiro registro de macroflora do Pleistoceno Final nas margens do rio Teles Pires, MT, Brasil

Este trabalho tem como objetivo realizar o reconhecimento taxonômico de folhas fósseis de angiospermas, as quais foram recuperadas pelo salvamento paleontológico realizado no âmbito do Programa Investigação, Monitoramento e Salvamento do Patrimônio Paleontológico da UHE Teles Pires. Os depósitos fossilíferos, encontrados em amostras de argilitos laminados, situavam-se no atual leito e terraços (diques marginais) do rio Teles Pires, dentro da área destinada ao reservatório. Na base do afloramento fitofossilífero estudado, restos vegetais em clastos de lama retrabalhados apresentaram idade absoluta entre 22.580 e 23.290 anos AP, obtida por método de radiocarbono (14C). Para a presente contribuição, foram selecionados para determinação taxonômica 27 espécimes, preservados na forma de impressões e compressões. Através da análise e descrição da arquitetura foliar dos espécimes foram identificadas uma monocotiledônea e sete eudicotiledôneas (Albizia subdimidiata e Parkia multijuga, da Família Fabaceae; Brosimum cf. gaudichaudii, da Família Moraceae; Theobroma speciosum e Apeiba sp., da Família Malvaceae; Aspidosperma cf. polyneuron, da Família Apocynaceae, e um espécime atribuído à Família Myrtaceae – Tribo Myrtae). A composição florística dos táxons analisados, juntamente com a distribuição geográfica dos seus representantes atuais e seus respectivos hábitos e hábitats, acusou a predominância de elementos florísticos tipicamente da Floresta Amazônica, sob regime de clima úmido. Porém, duas espécies que podem ocorrer em vegetação de savana foram assinaladas (i.é, Aspidosperma cf. polyneuron, Brosimum cf. gaudichaudii).This work aims at the taxonomic recognition of fossil leaves of angiosperms, which were recovered by the paleontological rescue carried out under the Program Research, Monitoring and Salvage of the Paleontological Heritage of the Teles Pires Hydroelectric Power Plant. The fossiliferous deposits, found in samples of laminated argillite, were located in the current bed and terraces (marginal dikes) of the Teles Pires River, inside the area destined to the water reservoir. At the base of the studied phytophossiliferous outcrop, vegetal remains in reworked mud clasts presented absolute age between 22,580 and 23,290 years BP, through the dating obtained by radiocarbon method (14C). For the present contribution, 27 specimens, preserved in the form of impressions and compressions, were selected for taxonomic determination. A monocotyledonous and seven eudycotyledonous (Albizia subdimidiata and Parkia multijuga, of the Family Fabaceae, Brosimum cf. gaudichaudii, of the Family Moraceae, Theobroma speciosum and Apeiba sp., of the Family Malvaceae, Aspidosperma cf. polyneuron, of the Family Apocynaceae, and a specimen attributed to the Family Myrtaceae - Tribe Myrtae) were identified through the analysis and description of the foliar architecture of the specimens. The floristic composition of the analyzed taxa, together with the geographical distribution of their current representatives and their respective habitats and habits, accused the predominance of floristic elements typically found in the Amazon Rainforest, under a humid climate regime. However, two species that may occur in savanna vegetation have been identified (i.e., Aspidosperma cf. polyneuron, Brosimum cf. gaudichaudii)

An energy-based comparative analysis of common approaches to text classification in the Legal domain

Most Machine Learning research evaluates the best solutions in terms of performance. However, in the race for the best performing model, many important aspects are often overlooked when, on the contrary, they should be carefully considered. In fact, sometimes the gaps in performance between different approaches are neglectable, whereas factors such as production costs, energy consumption, and carbon footprint must take into consideration. Large Language Models (LLMs) are extensively adopted to address NLP problems in academia and industry. In this work, we present a detailed quantitative comparison of LLM and traditional approaches (e.g. SVM) on the LexGLUE benchmark, which takes into account both performance (standard indices) and alternative metrics such as timing, power consumption and cost, in a word: the carbon-footprint. In our analysis, we considered the prototyping phase (model selection by training-validation-test iterations) and in-production phases separately, since they follow different implementation procedures and also require different resources. The results indicate that very often, the simplest algorithms achieve performance very close to that of large LLMs but with very low power consumption and lower resource demands. The results obtained could suggest companies to include additional evaluations in the choice of Machine Learning (ML) solutions.Comment: Accepted at The 4th International Conference on NLP & Text Mining (NLTM 2024), January 27-28 2024, Copenhagen, Denmark - 12 pages, 1 figure, 7 table

Neural paraphrasing by automatically crawled and aligned sentence pairs

Paraphrasing is the task of re-writing an input text using other words, without altering the meaning of the original content. Conversational systems can exploit automatic paraphrasing to make the conversation more natural, e.g., talking about a certain topic using different paraphrases in different time instants. Recently, the task of automatically generating paraphrases has been approached in the context of Natural Language Generation (NLG). While many existing systems simply consist in rule-based models, the recent success of the Deep Neural Networks in several NLG tasks naturally suggests the possibility of exploiting such networks for generating paraphrases. However, the main obstacle toward neural-network-based paraphrasing is the lack of large datasets with aligned pairs of sentences and paraphrases, that are needed to efficiently train the neural models. In this paper we present a method for the automatic generation of large aligned corpora, that is based on the assumption that news and blog websites talk about the same events using different narrative styles. We propose a similarity search procedure with linguistic constraints that, given a reference sentence, is able to locate the most similar candidate paraphrases out from millions of indexed sentences. The data generation process is evaluated in the case of the Italian language, performing experiments using pointer-based deep neural architectures.Comment: The 6th International Conference on Social Networks Analysis, Management and Security (SNAMS 2019

A novel integrated industrial approach with cobots in the age of industry 4.0 through conversational interaction and computer vision

From robots that replace workers to robots that serve as helpful colleagues, the field of robotic automation is experiencing a new trend that represents a huge challenge for component manufacturers. The contribution starts from an innovative vision that sees an ever closer collaboration between Cobot, able to do a specific physical job with precision, the AI world, able to analyze information and support the decision-making process, and the man able to have a strategic vision of the future

A novel integrated industrial approach with cobots in the age of industry 4.0 through conversational interaction and computer vision

From robots that replace workers to robots that serve as helpful colleagues, the field of robotic automation is experiencing a new trend that represents a huge challenge for component manufacturers. The contribution starts from an innovative vision that sees an ever closer collaboration between Cobot, able to do a specific physical job with precision, the AI world, able to analyze information and support the decision-making process, and the man able to have a strategic vision of the future

Exploring narrative linearity between Twitter and the news: Echoes of the Arab Spring in Brazil

This article explores the use of narrative theory as an analytical framework to investigate the extent to which popular hashtags and the news can develop into intersecting stories. It juxtaposes the case of hashtag-based reports seen during the Arab Spring to understand the coverage of notorious political episodes in Brazil. Namely, the 2016 impeachment of Dilma Rousseff and the 2018 election of Jair Bolsonaro. Here, narrative linearity emerges as a tool to observe the borrowing of Twitter hashtags in several journalistic pieces. It is contended that the linearity of authorship, narration, and representation of time appears as a satisfactory pathway to trace the development of hashtags into popular news stories. Results suggested that hashtags can significantly follow narratives and agendas in journalism while differing from their original social media context

Voter Buying: Shaping the Electorate through Clientelism

Studies of clientelism typically assume that political machines distribute rewards to persuade or mobilize the existing electorate. We argue that rewards not only influence actions of the electorate, but can also shape its composition. Across the world, machines employ “voter buying” to import outsiders into their districts. Voter buying demonstrates how clientelism can underpin electoral fraud, and it offers an explanation of why machines deliver rewards when they cannot monitor vote choices. Our analyses suggest that voter buying dramatically influences municipal elections in Brazil. A regression discontinuity design suggests that voter audits—which undermined voter buying—decreased the electorate by 12 percentage points and reduced the likelihood of mayoral reelection by 18 percentage points. Consistent with voter buying, these effects are significantly greater in municipalities with large voter inflows, and where neighboring municipalities had large voter outflows. Findings are robust to an alternative research design using a different data set

The role of mobile policies in coalition building : the Barcelona model as coalition magnet in Buenos Aires and Rio de Janeiro (1989-1996)

Research on policy mobility has tended to focus on what moves (e.g. policy models, templates) and who moves them (e.g. consultants, international organizations) with less attention paid to the relational politics of grounding dominant ideas in local policy making. The ‘demand side’ at the end of the mobilization process (e.g. local authorities and policy actors) is usually depicted as passive or as having stable interests. This assumption is problematic as it can reinforce taken for granted power asymmetries in the flow of urban policy ideas, particularly in cases where cities in the Global North are presented as ‘exporting sites’ for a Global South audience of ‘importing sites’. Drawing on the concept of policy ideas as ‘coalition magnets’ from policy studies, this paper demonstrates how local policies are relationally produced by cosmopolitan policy actors on the ‘demand side’ who strategically mobilize circulating ideas as a tool for coalition building. We provide a relational comparative study of Buenos Aires and Rio de Janeiro’s policy processes and urban outcomes in mobilizing the Barcelona model of urban regeneration and strategic planning drawing on evidence from interviews, document analysis, and the biographies of key policy actors. It demonstrates the strategic importance of mobile policies for emerging political actors who employ them as a ‘coalition magnet’ to build support for their governments