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631 Research products, page 1 of 64

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  • 2017-2021
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  • Other research product . 2021
    Open Access English
    Authors: 
    De Giusti, Marisa Raquel; Nusch, Carlos Javier; Golfetto, Enzo;
    Country: Argentina

    Presentation of the LibLink Initiative (Library Linkages) of ISTEC. The main strategies, projects, and actions carried out in the meeting with the Hermes project are presented. Proyecto de Enlace de Bibliotecas

  • Open Access English
    Authors: 
    Gómez, Sergio Alejandro;
    Country: Argentina

    In this paper, we present a tool for possibilistic logic programming.This tool is a desktop-based, stand-alone application that assists a user in creating, editing and querying a possibly inconsistent possibilistic program. The tool computes all the arguments emerging from the program, the grounded extension based on Dung-style semantics, and it is capable of showing arguments and grounded extensions graphically. The language for programs is enriched with pragmas for allowing the user to con gure labels for necessity degrees, deciding if using transposes of strict rules, performing consistency checks within arguments, and appeal to the use of accrual of rules for building arguments. We describe its usage, architectural elements and we also provide experimental evaluation of its performance. Sociedad Argentina de Informática e Investigación Operativa

  • Open Access English
    Authors: 
    Marchiano, María; Tanco, Matías Germán;
    Country: Argentina

    Background: DJing is a performance where a DJ plays pre-made electronic dance music’s tracks (EDM) for a dancing crowd during a party. DJs claim they read the crowd in order to play music (Broughton & Brewster, 2002), making DJ-audience interaction very relevant to DJing. The active participation of the crowd that the party requires makes a difference from other performer-audience situations. We think that this could be a case of Second Person Interaction, whose main features involve face-to-face exchanges, direct perception of mental states in others’ body expressions, psychological attributions, changes in both mental states and reciprocal actions (Pérez & Gomila, 2021). Both the musical performance and the one-to-many interaction’s features involved in DJing has not yet been fully described from a second-person perspective. Aims: The research aimed to describe DJ-crowd interaction from the DJ’s perspective, identify its second person features, and analyze the impact of this interaction on music. Laboratorio para el Estudio de la Experiencia Musical

  • Open Access English
    Authors: 
    Cura Costa, Emanuel; Otsuki, Leo; Rodrigo Albors, Aida; Tanaka, Elly M.; Chara, Osvaldo;
    Country: Argentina

    Axolotls are uniquely able to resolve spinal cord injuries, but little is known about the mechanisms underlying spinal cord regeneration. We previously found that tail amputation leads to reactivation of a developmental-like program in spinal cord ependymal cells (Rodrigo Albors et al., 2015), characterized by a high-proliferation zone emerging 4 days post-amputation (Rost et al., 2016). What underlies this spatiotemporal pattern of cell proliferation, however, remained unknown. Here, we use modeling, tightly linked to experimental data, to demonstrate that this regenerative response is consistent with a signal that recruits ependymal cells during ~85 hours after amputation within ~830 μm of the injury. We adapted Fluorescent Ubiquitination-based Cell Cycle Indicator (FUCCI) technology to axolotls (AxFUCCI) to visualize cell cycles in vivo. AxFUCCI axolotls confirmed the predicted appearance time and size of the injury-induced recruitment zone and revealed cell cycle synchrony between ependymal cells. Our modeling and imaging move us closer to understanding bona fide spinal cord regeneration. This is the second release of the Jupyter Notebooks that contains source code for data analysis performed for Cura Costa et al., 2021. You can view the current version of the notebooks on GitHub or browse them online using nbviewer. Instituto de Física de Líquidos y Sistemas Biológicos

  • Other research product . 2021
    Open Access English
    Authors: 
    Aromí, José Daniel; De Raco, Sergio Andrés;
    Country: Argentina

    We propose and implement a methodology for data collection and analysis of Twitter discussions linked to the Argentine economy. Starting with a list of “seed users” later expanded based on following-follower relationships, we build a network of interactions and fetch their tweet timelines. Then, we use a community detection model to compress the structure of underlying relationships and a standard topic model to represent the latent issues discussed in each community. Results suggest that this strategy is able to learn a useful organization and to summarize the contents of social media exchanges of the Argentine economic tweetosphere. Potential applications could be to characterize the links between different economic sectors and to construct community-level indicators of opinions. Sociedad Argentina de Informática e Investigación Operativa

  • Open Access English
    Authors: 
    Albanese, Federico; Feuerstein, Esteban;
    Country: Argentina

    Texts can be characterized from their content using machine learning and natural language processing techniques. In particular, understanding their topic is useful for different tasks such as personalized message recommendation, fake news detection or public opinion monitoring. Latent Dirichlet Allocation (LDA) is an unsupervised generative model for the decomposition of topics, which seeks to represent texts as random mixtures over topics with a Dirichlet distribution, and each topic is characterized by a distribution over words. However, this method is challenging to apply when the text is short and sometimes incoherent, as is often the case with posts on social networks such as twitter. Therefore, different works have shown that tweet pooling (aggregating tweets into longer documents) improves LDA results, but its performance depends on which method was used to aggregating the texts. We propose the new method to detect topics on twitter: “Community pooling”. In this novel scheme, first we define the retweet graph where users are the nodes and retweets between them are the edges. Then, we use the Louvain method for community detection in order to uncover the communities (a group of users who mainly interact with each other but not with other groups). Finally we aggregate into a single document all the tweets authored by all users in a community. Therefore, this method drastically reduces the number of total documents and makes denser word co-occurrence matrix, which is beneficial to LDA algorithm. With the intention of evaluating our model, we created two datasets of tweets with different characteristics. A first generic dataset involving various topics such as music, health and movies and a second dataset corresponding to an event: Biden’s presidential inauguration day in the United States. We compare the performance of our model with state of the art schemes and previous pooling models in terms of document retrieval performance, cluster quality and supervised machine learning classification score. Results showed that Community pooling had a better performance on all datasets and tasks, with the only exception of the retrieval task on the event dataset. Moreover, Community polling was faster than all other aggregation techniques (less than half the running time), which is particularly useful in big data scenarios. Sociedad Argentina de Informática e Investigación Operativa

  • Open Access English
    Authors: 
    Bermúdez, Carlos; Alfonso, Hugo; Minetti, Gabriela F.; Salto, Carolina;
    Country: Argentina

    In the Simulated Annealing (SA) algorithm, the Metropolis algorithm is applied to generate a sequence of solutions in the search space, known as the Markov chain. Usually, the algorithms employ the same Markov Chain Length (MCL) in the Metropolis cycle for each temperature. However, SA can use adaptive methods to compute the MCL. This work aims to analyze the effect of using different MCL strategies in SA behavior. This experimentation considers the Water Distribution Network Design (WDND) problem, a multimodal and NP-hard problem interesting to optimize. The results indicate that the use of adaptive MCL strategies improves the solution quality versus the static one. Workshop: WASI – Agentes y Sistemas Inteligentes Red de Universidades con Carreras en Informática

  • Open Access English
    Authors: 
    Laguna, Rodrigo; Moncecchi, Guillermo;
    Country: Argentina

    This work presents Clean-Dirty Containers in Montevideo (CDCM), a novel dataset for detection and classi cation of residue con-tainers. Images were collected from several sources, including Google Street View, Social Networks and smarthpone taken photos. The dataset is publicly available under a Creative Commons License. Sociedad Argentina de Informática e Investigación Operativa

  • Open Access English
    Authors: 
    Caligiore Gei, Pablo F.;
    Country: Argentina

    Garlic is a relevant crop worldwide, with more than 1.6 M hectares and a production of 30 M tons. In Argentina the crop is located in the western part of the country, in the provinces of Mendoza and San Juan. The vast majority of the local production is exported, generating an average income of 150 M USD. Garlic stakeholders and growers constitute a dynamic sector which constantly demands new tools to improve their efficiency, in a cost-effective manner. In this regard, previous experiments have evaluated the use of remote sensing to estimate garlic growth variables, particularly associated to irrigation and nutrition practices and weather conditions. However, the correlation with pest/disease outbreaks are scarce and often related to controlled conditions environments. White rot (WR), caused by the soilborne fungus Stromatinia cepivora, is an increasing threaten to garlic crops worldwide. Reports mention that WR causes 50% of yield reduction and sometimes can lead to complete loss. Once present in a field, the fungus produces resistance structures called sclerotia that remain in the soil for long periods of time, infecting any Allium crop for many years after that. Hence, the early detection of the presence of WR is essential for the sustainability of the garlic production in the region. The objective of the present study was to evaluate the usefulness of multispectral images for the estimation of production variables and crop health in garlic. Sociedad Argentina de Informática e Investigación Operativa

  • Open Access English
    Authors: 
    Ríos, Pablo; Raschia, María Agustina; Maizon, Daniel O.; Demitrio, Daniel; Poli, Mario A.;
    Country: Argentina

    In recent years, machine learning methods have been shown to be efficient in identifying a subset of single nucleotide polymorphisms (SNP) underlying a trait of interest. The aim of this study was the construction of predictive models using machine learning algorithms, for the identification of loci that best explain the variance in milk fat production of dairy cattle. Further objectives involve determining the genes flanking relevant SNPs and retrieving the pathways, biological processes, or molecular functions overrepresented by them. Fat production values adjusted for fixed effects (FPadj) and estimated breeding values for milk fat production (EBVFP) were used as phenotypes and SNPs as predictor variables. The models constructed for EBVFP performed better and yield considerably less relevant SNPs than models for FPadj. Among the genes flanking relevant SNPs, signaling transduction pathways and gated channel activities were detected as overrepresented. The loci obtained for EBVFP matched better with previously reported relevant loci for milk fat content than those obtained for FPadj. Based on the better performance showed by the models trained for EBVFP and their agreement with previous reported results for the trait studied, we conclude that the relationship among individuals should be accounted for in the phenotype used. Sociedad Argentina de Informática e Investigación Operativa

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