From implicit preferences to ratings: Video games recommendation based on collaborative filtering

This work studies and compares the performance of collaborative filtering algorithms, with the intent of proposing a videogame-oriented recommendation system. This system uses information from the video game platform Steam, which contains information about the game usage, corresponding to the implicit feedback that was later transformed into explicit feedback. These algorithms were implemented using the Surprise library, that allows to create and evaluate recommender systems that deal with explicit data. The algorithms are evaluated and compared with each other using metrics such as RSME, MAE, Precision@k, Recall@k and F1@k. We have concluded that computationally low demanding approaches can still obtain suitable results.info:eu-repo/semantics/acceptedVersio

Changes in Iron Metabolism Induced by Anti-Interleukin-6 Receptor Monoclonal Antibody are Associated with an Increased Risk of Infection

(1) Background: Treatment of patients with rheumatoid arthritis (RA) with an anti-IL-6 receptor (anti-IL-6R) monoclonal antibody (tocilizumab) has been found to influence iron metabolism. The objective of the present study was to ascertain whether changes in iron metabolism induced by anti-IL-6R biologic therapy were independently associated with an increased infection risk. (2) Methods: A prospective longitudinal study of patients with RA treated with tocilizumab was conducted. RA patients treated with an antitumor necrosis factor α monoclonal antibody were also included as a control group. The primary outcome was occurrence of infection during the first 24 months of biologic therapy. (3) Results: A total of 15 patients were included, with a mean age of 51.0 ± 4,1 and 73.3% (n = 11) female. A multivariate survival regression model, adjusted for confounding factors, was fitted for each of the iron metabolism variables. Hazard ratios for being above the median of each parameter was considered. Transferrin saturation above the median value (>32.1%) was associated with a higher infection risk (HR 4.3; 95%CI 1.0-19.69; p = 0.05). Similarly, although non-significantly, higher serum iron was strongly associated with infection occurrence. (4) Conclusions: This study identified a probable association between infection risk and higher serum iron and transferrin saturation in patients with RA on anti-IL-6R biologic therapy. We suggest that both these parameters should be considered relevant contributing factors for infection occurrence in patients on anti-IL-6R therapy.info:eu-repo/semantics/publishedVersio

Electron Spin Resonance of defects in the Haldane System Y(2)BaNiO(5)

We calculate the electron paramagnetic resonance (EPR) spectra of the antiferromagnetic spin-1 chain compound Y(2)BaNi(1-x)Mg(x)O(5) for different values of x and temperature T much lower than the Haldane gap (~100K). The low-energy spectrum of an anisotropic Heisenberg Hamiltonian, with all parameters determined from experiment, has been solved using DMRG. The observed EPR spectra are quantitatively reproduced by this model. The presence of end-chain S=1/2 states is clearly observed as the main peak in the spectrum and the remaining structure is completely understood.Comment: 5 pages, 4 figures include

Resultados preliminares sobre o comportamento de cultivares e hídridos de milho normal em solos de cerrado na região de Brasília.

Resultados obtidos em condições de campo durante o ano agrícola de 1975/76, sobre o comportamento de 30 cultivares e híbrido de milho

Spatio-temporal analysis of brand interest using social networks

Social Networks have become part of many people's lives, and applications like Facebook and Twitter are used on a daily basis by millions of users. In such applications, users share their feelings, opinions, and experiences. Twitter in particular, is used to talk about diverse topics, including brands and their products and services. In this paper, we analyze how brand interest is reflected on Twitter and how this platform can be used to monitor mentions of specific brands, as an indicator of brand interest. Our methodology is based on time, location, and the number of brand-related tweets to perform a spatio-temporal analysis. This type of analysis can provide relevant insights into how brand interest evolves over the time and how it might differ from one country to another. We have collected four years' worth of data and report trends, differences, and similarities in terms of brand interest for each brand and for each country.info:eu-repo/semantics/acceptedVersio

Complementary action of chemical and electrical synapses to perception

Acknowledgements This study was possible by partial financial support from the following agencies: Fundação Araucária, EPSRC-EP/I032606/1, CNPq No. 441553/2014-1, CAPES No. 17656-12-5 and Science Without Borders Program— Process Nos. 17656125, 99999.010583/2013-00 and 245377/2012-3.Peer reviewedPostprin

Knowledge Acquisition by Networks of Interacting Agents in the Presence of Observation Errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erd\H{o}s-Renyi or Barabasi-Albert type. First we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall behavior of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.Comment: 10 pages, 7 figures. A working manuscrip