Reinforcement and inference in cross-situational word learning

Cross-situational word learning is based on the notion that a learner can determine the referent of a word by finding something in common across many observed uses of that word. Here we propose an adaptive learning algorithm that contains a parameter that controls the strength of the reinforcement applied to associations between concurrent words and referents, and a parameter that regulates inference, which includes built-in biases, such as mutual exclusivity, and information of past learning events. By adjusting these parameters so that the model predictions agree with data from representative experiments on cross-situational word learning, we were able to explain the learning strategies adopted by the participants of those experiments in terms of a trade-off between reinforcement and inference. These strategies can vary wildly depending on the conditions of the experiments. For instance, for fast mapping experiments (i.e., the correct referent could, in principle, be inferred in a single observation) inference is prevalent, whereas for segregated contextual diversity experiments (i.e., the referents are separated in groups and are exhibited with members of their groups only) reinforcement is predominant. Other experiments are explained with more balanced doses of reinforcement and inference

Essentiality Of Nickel In Plants: A Role In Plant Stresses

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The element Ni is considered an essential plant micronutrient because it acts as an activator of the enzyme urease. Recent studies have shown that Ni may activate an isoform of glyoxalase I, which performs an important step in the degradation of methylglyoxal (MG), a potent cytotoxic compound naturally produced by cellular metabolism. Reduced glutathione (GSH) is consumed and regenerated in the process of detoxification of MG, which is produced during stress (stress-induced production). We examine the role of Ni in the relationship between the MG cycle and GSH homeostasis and suggest that Ni may have a key participation in plant antioxidant metabolism, especially in stressful situations.6Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FAPESP [2014/09730-4

Existence Results for Abstract Partial Neutral Integro-differential Equation with Unbounded Delay

In this paper we study the existence and regularity of mild solutions for a class of abstract partial neutral integro-differential equations with unbounded delay.FONDECYT-CONICYT[1050314]FONDECYT-CONICYT[7050034]Capes, Brasi

Performance analysis and optimization of a N-class bipolar network

A wireless network with unsaturated traffic and N classes of users sharing a channel under random access is analyzed here. Necessary and sufficient conditions for the network stability are derived, along with simple closed formulas for the stationary packet transmission success probabilities and mean packet delays for all classes under stability conditions. We also show, through simple and elegant expressions, that the channel sharing mechanism in the investigated scenario can be seen as a process of partitioning a well-defined quantity into portions, each portion assigned to each user class, the size of which determined by system parameters and performance metrics of that user class. Using the derived expressions, optimization problems are then formulated and solved to minimize the mean packet delay and to maximize the channel throughput per unit of area. These results indicate that the proposed analysis is capable of assessing the trade-off involved in radio-resource management when different classes of users are considered7135118135132CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP311485/2015-4não tem2017/21347-0This work was supported in part by the Foundation for Research Support of the State of São Paulo under Grant 2017/21347-0, in part by the Brazilian National Council for Scientific and Technological Development under Grant 311485/2015-4, in part by the Academy of Finland via the ee-IoT Project under Grant 319009, in part by the FIREMAN Consortium under Grant CHIST-ERA 326270, in part by the EnergyNet Research Fellowship under Grant 321265 and Grant 328869, in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–Brazil (CAPES) under Grant 001, in part by the RNP, with resources from MCTIC, under the Radiocommunication Reference Center (CRR) Project of the National Institute of Telecommunications (Inatel), Brazil, under Grant 01250.075413/2018-0

Complex Network Tools to Understand the Behavior of Criminality in Urban Areas

Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis process, i.e. from data preparation to a deep analysis of criminal communities. Furthermore, the "toolset" available for those works is not complete enough, also lacking techniques to maintain up-to-date, complete crime datasets and proper assessment measures. In this sense, we propose a threefold methodology for employing complex networks in the detection of highly criminal areas within a city. Our methodology comprises three tasks: (i) Mapping of Urban Crimes; (ii) Criminal Community Identification; and (iii) Crime Analysis. Moreover, it provides a proper set of assessment measures for analyzing intrinsic criminality of communities, especially when considering different crime types. We show our methodology by applying it to a real crime dataset from the city of San Francisco - CA, USA. The results confirm its effectiveness to identify and analyze high criminality areas within a city. Hence, our contributions provide a basis for further developments on complex networks applied to crime analysis.Comment: 7 pages, 2 figures, 14th International Conference on Information Technology : New Generation

Automated Discovery of Relationships, Models, and Principles in Ecology

Ecological systems are the quintessential complex systems, involving numerous high-order interactions and non-linear relationships. The most used statistical modeling techniques can hardly accommodate the complexity of ecological patterns and processes. Finding hidden relationships in complex data is now possible using massive computational power, particularly by means of artificial intelligence and machine learning methods. Here we explored the potential of symbolic regression (SR), commonly used in other areas, in the field of ecology. Symbolic regression searches for both the formal structure of equations and the fitting parameters simultaneously, hence providing the required flexibility to characterize complex ecological systems. Although the method here presented is automated, it is part of a collaborative human-machine effort and we demonstrate ways to do it. First, we test the robustness of SR to extreme levels of noise when searching for the species-area relationship. Second, we demonstrate how SR can model species richness and spatial distributions. Third, we illustrate how SR can be used to find general models in ecology, namely new formulas for species richness estimators and the general dynamic model of oceanic island biogeography. We propose that evolving free-form equations purely from data, often without prior human inference or hypotheses, may represent a very powerful tool for ecologists and biogeographers to become aware of hidden relationships and suggest general theoretical models and principles.Peer reviewe

Effects of Different Moisture Contents on Physical Properties of PVA-Gelatin Films

In this work, it was investigated the effect of different moisture contents on PVA-gelatin films by means of dielectric properties, infrared spectroscopy, microwave response and gravimetric method. The films were elaborated from a blend of gelatin and PVA, with 0 and 25 % glycerol. The sorption isotherms were determined by gravimetric methods, at 25 A degrees C. A capacimeter was used for dielectric measurements, and a device called SOLFAN setup was used for microwave measurements. The sorption isotherms were markedly affected by the glycerol content and relative humidity, due to the hygroscopic nature of the films. The dielectric constant and the microwave response signal were also strongly affected by the moisture and glycerol content in the films. Finally, Infrared spectra showed some changes in the amide peak positions, attributed to the modifications in the interactions between the macromolecules. The behaviors obtained in this work were explained on the basis the way the water enters in the film matrix.FAPESP [05/54688-7

Reply to "Comment on "Stratigraphy of the Northern Pulo do Lobo Domain, SW Iberia Variscides: A palynological contribution" by Zelia Pereira et al. (2018) - Geobios 51, 491-506"

We acknowledge M. Francisco Pereira, D. Martínez Poyatos, I. Pérez-Cáceres, Cristina Gama and António Azor for the interest shown in our work, and appreciate the chance to clarify a few questions raised by Pereira et al.’s (2018) research. The main aim of Pereira et al. (2018) study was to better constrain the ages of the lithostratigraphic units that make the Northern Pulo do Lobo Domain, SW Iberia Variscides.info:eu-repo/semantics/publishedVersio

AGN feedback and star formation in the peculiar galaxy NGC 232: Insights from VLT-MUSE Observations

We use VLT-MUSE integral field unit data to study the ionized gas physical properties and kinematics as well as the stellar populations of the Seyfert 2 galaxy NGC\,232 as an opportunity to understand the role of AGN feedback on star formation. The data cover a field of view of 60$\times$60 arcsec$^{2}$ at a spatial resolution of $\sim$\,850\,pc. The emission-line profiles have been fitted with two Gaussian components, one associated to the emission of the gas in the disc and the other due to a bi-conical outflow. The spectral synthesis suggests a predominantly old stellar population with ages exceeding 2\,Gyr, with the largest contributions seen at the nucleus and decreasing outwards. Meanwhile, the young and intermediate age stellar populations exhibit a positive gradient with increasing radius and a circum-nuclear star forming ring with radius of $\sim$0.5\,kpc traced by stars younger than 20 Myr, is observed. This, along with the fact that AGN and SF dominated regions present similar gaseous oxygen abundances, suggests a shared reservoir feeding both star formation and the AGN. We have estimated a maximum outflow rate in ionized gas of $\sim$1.26\,M${\odot}$\,yr$^{-1}$ observed at a distance of $\sim$560 pc from the nucleus. The corresponding maximum kinetic power of the outflow is $\sim3.4\times10^{41}$ erg\,s$^{-1}$. This released energy could be sufficient to suppress star formation within the ionization cone, as evidenced by the lower star formation rates observed in this region.Comment: 14 pages,10 figures. Submitted to MNRA

Kinetic insights on wet peroxide oxidation of caffeine using EDTA-functionalized low-cost catalysts prepared from compost generated in municipal solid waste treatment facilities

Nowadays, sorted organic fraction of municipal solid waste is typically treated by anaerobic digestion processes, resulting therein a solid stream, further processed to obtain compost, whose production is higher than the existing demand as fertilizer. The current work proposes an alternative strategy for the recovering of compost through the production of low-cost catalysts by calcination (1073 K) and sulfuric acid treatments, followed by sequential functionalization with tetraethyl orthosilicate (TEOS) and ethylenediamine tetraacetic acid (EDTA). Activity and stability of the catalysts are assessed in the wet peroxide oxidation of synthetic wastewater effluents contaminated with caffeine, a model micro-pollutant, achieving its complete removal after 6 h at 353– 383 K and catalyst loads of 0.5–2.5 g L−1. The increase of the catalytic activity of the materials upon functionalization with TEOS and EDTA is demonstrated and a kinetic modeling of caffeine degradation and hydrogen peroxide consumption with the best catalyst is assessed by pseudo-first power-law rate equations.This work was financially supported by project ‘‘VALORCOMP - Valorización de compost y otros desechos procedentes de la fracción orgánica de los residuos municipales’’, 0119_VALORCOMP_2_P, through FEDER under Program INTERREG; and CIMO (UIDB/00690/2020) through FEDER under Program PT2020.info:eu-repo/semantics/publishedVersio