Ludics without Designs I: Triads

In this paper, we introduce the concept of triad. Using this notion, we study, revisit, discover and rediscover some basic properties of ludics from a very general point of view.Comment: In Proceedings LINEARITY 2014, arXiv:1502.0441

Infinitary Classical Logic: Recursive Equations and Interactive Semantics

In this paper, we present an interactive semantics for derivations in an infinitary extension of classical logic. The formulas of our language are possibly infinitary trees labeled by propositional variables and logical connectives. We show that in our setting every recursive formula equation has a unique solution. As for derivations, we use an infinitary variant of Tait-calculus to derive sequents. The interactive semantics for derivations that we introduce in this article is presented as a debate (interaction tree) between a test > (derivation candidate, Proponent) and an environment << not S >> (negation of a sequent, Opponent). We show a completeness theorem for derivations that we call interactive completeness theorem: the interaction between > (test) and > (environment) does not produce errors (i.e., Proponent wins) just in case > comes from a syntactical derivation of >.Comment: In Proceedings CL&C 2014, arXiv:1409.259

Advances in Automatic Keyphrase Extraction

The main purpose of this thesis is to analyze and propose new improvements in the field of Automatic Keyphrase Extraction, i.e., the field of automatically detecting the key concepts in a document. We will discuss, in particular, supervised machine learning algorithms for keyphrase extraction, by first identifying their shortcomings and then proposing new techniques which exploit contextual information to overcome them. Keyphrase extraction requires that the key concepts, or \emph{keyphrases}, appear verbatim in the body of the document. We will identify the fact that current algorithms do not use contextual information when detecting keyphrases as one of the main shortcomings of supervised keyphrase extraction. Instead, statistical and positional cues, like the frequency of the candidate keyphrase or its first appearance in the document, are mainly used to determine if a phrase appearing in a document is a keyphrase or not. For this reason, we will prove that a supervised keyphrase extraction algorithm, by using only statistical and positional features, is actually able to extract good keyphrases from documents written in languages that it has never seen. The algorithm will be trained over a common dataset for the English language, a purpose-collected dataset for the Arabic language, and evaluated on the Italian, Romanian and Portuguese languages as well. This result is then used as a starting point to develop new algorithms that use contextual information to increase the performance in automatic keyphrase extraction. The first algorithm that we present uses new linguistics features based on anaphora resolution, which is a field of natural language processing that exploits the relations between elements of the discourse as, e.g., pronouns. We evaluate several supervised AKE pipelines based on these features on the well-known SEMEVAL 2010 dataset, and we show that the performance increases when we add such features to a model that employs statistical and positional knowledge only. Finally, we investigate the possibilities offered by the field of Deep Learning, by proposing six different deep neural networks that perform automatic keyphrase extraction. Such networks are based on bidirectional long-short term memory networks, or on convolutional neural networks, or on a combination of both of them, and on a neural language model which creates a vector representation of each word of the document. These networks are able to learn new features using the the whole document when extracting keyphrases, and they have the advantage of not needing a corpus after being trained to extract keyphrases from new documents. We show that with deep learning based architectures we are able to outperform several other keyphrase extraction algorithms, both supervised and not supervised, used in literature and that the best performances are obtained when we build an additional neural representation of the input document and we append it to the neural language model. Both the anaphora-based and the deep-learning based approaches show that using contextual information, the performance in supervised algorithms for automatic keyphrase extraction improves. In fact, in the methods presented in this thesis, the algorithms which obtained the best performance are the ones receiving more contextual information, both about the relations of the potential keyphrase with other parts of the document, as in the anaphora based approach, and in the shape of a neural representation of the input document, as in the deep learning approach. In contrast, the approach of using statistical and positional knowledge only allows the building of language agnostic keyphrase extraction algorithms, at the cost of decreased precision and recall

Shut Up and Run: The Never-ending Quest for Social Fitness

In this paper we explore possible negative drawbacks in the use of wearable sensors, i.e., wearable devices used to detect different kinds of activity, e.g., from step and calories counting to heart rate and sleep monitoring. These technologies, which in the latter years witnessed a rapid development in terms of accuracy and diffusion, are now available on different platforms at reasonable prices and can lead to an healthier behavior in people using them. Nevertheless, we will try to investigate possibly harming behaviors related to these devices. We will provide different scenarios in which wearable sensors, in connection with social media, data mining, or other technologies, could prove harmful for their users

Evaluating anaphora and coreference resolution to improve automatic keyphrase extraction

In this paper we analyze the effectiveness of using linguistic knowledge from coreference and anaphora resolution for improving the performance for supervised keyphrase extraction. In order to verify the impact of these features, we de\ufb01ne a baseline keyphrase extraction system and evaluate its performance on a standard dataset using different machine learning algorithms. Then, we consider new sets of features by adding combinations of the linguistic features we propose and we evaluate the new performance of the system. We also use anaphora and coreference resolution to transform the documents, trying to simulate the cohesion process performed by the human mind. We found that our approach has a slightly positive impact on the performance of automatic keyphrase extraction, in particular when considering the ranking of the results

How I do it: flexible endoscopic aspiration of intraventricular hemorrhage

Background: As intraventricular blood is a strong negative prognostic factor, intraventricular hemorrhage requires prompt and aggressive management to reduce intracranial hypertension. Method: A flexible scope can be used to navigate and to aspirate blood clots from all four ventricles. Complete restoration of CSF pathways from the lateral ventricle to the foramen of Magendie can be obtained. Conclusion: Flexible neuroendoscopic aspiration of IVH offers the opportunity to immediately reduce intracranial hypertension, reduce EVD obstruction and replacement rates, and decrease infections and shunt dependency

Influence of the specimen production and preparation on the compressive strength and the fatigue resistance of HPC and UHPC

The results of tests under monotonically increasing load and cyclic compression load are often analysed by means of probabilistic methods. Although there is a considerable scattering in the results, especially in the number of cycles to failure, the cause of these cannot be completely explained. The imperfections of the specimens tested are among the causes of this scattering mentioned in the literature. Based on a round robin test the influence of HPC and UHPC production and specimen preparation techniques on the mean values of the compressive strengths, number of cycles to failure and data scattering have been evaluated. The main findings of the study are that the production techniques have an influence on the compressive strength, however, do not affect the mean number of cycles to failure. Moreover, the accurate preparation of the specimens has a positive influence on the compressive strength and the scattering of the results of both compression and cyclic load tests. The mean number of cycles to failure of HPC specimens is not influenced by the preparation techniques, whereas the polishing technique may have a positive influence on the mean number of cycles to failure of UHPC specimens. © 2021, The Author(s)

Trivalent chromium ion removal from aqueous solutions using low-cost zeolitic materials obtained from exhausted FCC catalysts

The hydrothermal treatment of exhausted FCC catalysts with zeolite was optimized by varying the chemical composition of the synthesis mixture. The zeolitic products obtained were used to evaluate their ability for the capture of Cr(III) cations from aqueous solutions. It was shown that the zeolitic product materials were capable of reducing the Cr(III) ion concentration to values lower than 1.2 ppm. The chromium ion-containing solids were afterwards solidified in cement mortars on which leaching studies of this cation were made. The results obtained showed that the synthesized solids acted as effective Cr(III) ion immobilizers and that their inclusion as additives in cement formulations could provide an environmental friendly disposal procedure.Fil: González, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigación y Desarrollo en Ciencias Aplicadas; ArgentinaFil: Pereyra, Andrea Marisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigación y Desarrollo en Ciencias Aplicadas; Argentina. Universidad Tecnológica Nacional. Facultad Regional La Plata; ArgentinaFil: Basaldella, Elena Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Centro de Investigación y Desarrollo en Ciencias Aplicadas; Argentina. Universidad Tecnologica Nacional. Facultad Regional La Plata; Argentin