Satellite image classification and segmentation using non-additive entropy

Here we compare the Boltzmann-Gibbs-Shannon (standard) with the Tsallis entropy on the pattern recognition and segmentation of coloured images obtained by satellites, via "Google Earth". By segmentation we mean split an image to locate regions of interest. Here, we discriminate and define an image partition classes according to a training basis. This training basis consists of three pattern classes: aquatic, urban and vegetation regions. Our numerical experiments demonstrate that the Tsallis entropy, used as a feature vector composed of distinct entropic indexes $q$ outperforms the standard entropy. There are several applications of our proposed methodology, once satellite images can be used to monitor migration form rural to urban regions, agricultural activities, oil spreading on the ocean etc.Comment: 4 pages, 5 figures, ICMSquare 201

Evidence of Quaternary tectonics along Río Grande valley, southern Malargüe fold and thrust belt, Mendoza, Argentina

The Malargüe fold and thrust belt is developed in the Argentinian Andes between 34° and 37° S, through the tectonic inversion of Upper Triassic and Lower Jurassic depocenters of the Neuquén Basin, with an uplift history since the Cretaceous. Evidence of Quaternary deformation has been described in the northern part of it (34–34.5°S), potentially coeval to neotectonic activity along the eastern edge of San Rafael block. To the south, compressional and extensional structures active during the Quaternary were found in the Dorso de los Chihuidos along the Agrio fold and thrust belt front (37.5–38°S). Contrastingly, the southern segment of the Malargüe fold and thrust belt between these two areas with described neotectonic activity is partially covered by Quaternary products of the Payún Matrú volcanic field, that may hide evidence of recent deformation. In this 300 km gap of neotectonic information, the landscape imprint of two individual structures aligned in the mountain front through the Río Grande valley was analyzed. New evidence of neotectonic deformation were recognized, in particular over the western slope of the Cara Cura range, expressed by faulting and folding of Quaternary deposits and lava flows. An 40Ar/39Ar age from a deformed lava flow at the flanks of an anticline in the foothills of the Cara Cura range may suggest at least an upper Pleistocene compressional tectonic activity. Longitudinal river profile analysis revealed anomalies that show some correlation with the neotectonic structures described, especially knickpoints and concavity index changes. Meanwhile normalized steepness index values showed a moderate response to recent deformation. A proposed schematic geomorphic evolution for this segment of Río Grande river is discussed to put the neotectonic activity into the context of landscape formation. All together this evidence supports the idea of an active front through the Río Grande valley during the Quaternary, coetaneous to an active broken foreland to the east in the southern Central Andes.Fil: Colavitto, Bruno. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Sagripanti, Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Fennell, Lucas Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Folguera Telichevsky, Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; ArgentinaFil: Costa, Carlos. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Departamento de Geología; Argentin

Photoinduced dynamics in protonated aromatic amino acid

UV photoinduced fragmentation of protonated aromatics amino acids have emerged the last few years, coming from a situation where nothing was known to what we think a good understanding of the optical properties. We will mainly focus this review on the tryptophan case. Three groups have mostly done spectroscopic studies and one has mainly been involved in dynamics studies of the excited states in the femtosecond/picosecond range and also in the fragmentation kinetics from nanosecond to millisecond. All these data, along with high level ab initio calculations, have shed light on the role of the different electronic states of the protonated molecules upon the fragmentation mechanisms

Organização formal dos partidos políticos brasileiros. (2010-2015)

Anais do IV Encontro de Iniciação Científica da Unila - “UNILA 5 anos: Integração em Ciência, Tecnologia e Cultura na Tríplice Fronteira” - 05 e 06 de novembro de 2015 – Sessão Ciência Política, Sociologia, Filosofia e AntropologiaO presente trabalho traz como objetivo a realização de um mapeamento da organização formal dos partidos políticos brasileiros registrados no período de 2010 a primeira metade de 2015. Mapeamento que foi realizado com base em conceitos teóricos trazidos por autores clássicos da ciência política que realizam uma teorização sobre a organização formal dos partidos políticos, autores estes tais como, Sartori, Duverge e Panebianco. A presente pesquisa busca trazer esses conceitos teóricos apresentados pelos autores mencionados anteriormente e fazer uma análise empírica, desenvolvendo assim a relação entre o teórico com o empírico. Se ressalta que o trabalho realiza o mapeamento dos 32 partidos devidamente registrados no TSE no ano de 2014. Foi utilizado como fonte da pesquisa o próprio site do TSE, sites dos próprios partidos e também reportagens de notícias e jornais que se relacionavam com alguns partidos envolvidos na análise. O trabalho se baseia na hipótese de que os partidos políticos são organizados de acordo com sua posição ideológica, ou seja, o fato do partido ser de esquerda, direita ou centro influenciaria na forma de organização dos partidos.Pesquisador e Bolsista da Fundação Araucári

Performing edge detection by difference of Gaussians using q-Gaussian kernels

In image processing, edge detection is a valuable tool to perform the extraction of features from an image. This detection reduces the amount of information to be processed, since the redundant information (considered less relevant) can be unconsidered. The technique of edge detection consists of determining the points of a digital image whose intensity changes sharply. This changes are due to the discontinuities of the orientation on a surface for example. A well known method of edge detection is the Difference of Gaussians (DoG). The method consists of subtracting two Gaussians, where a kernel has a standard deviation smaller than the previous one. The convolution between the subtraction of kernels and the input image results in the edge detection of this image. This paper introduces a method of extracting edges using DoG with kernels based on the q-Gaussian probability distribution, derived from the q-statistic proposed by Constantino Tsallis. To demonstrate the method's potential, we compare the introduced method with the traditional DoG using Gaussians kernels. The results showed that the proposed method can extract edges with more accurate details.Comment: 5 pages, 5 figures, IC-MSQUARE 201

The synthesis of mono- and difluorinated 2,3-dideoxy-d-glucopyranoses

The synthesis of 2,3-dideoxy-2,3-difluoro-d-glucose and 2,3-dideoxy-3-fluoro-d-glucose is reported in, respectively, 5 and 6 steps from d-glucal, using a fluorination strategy

Characterization of Excited States in Time-Dependent Density Functional Theory Using Localized Molecular Orbitals

Localized molecular orbitals are often used for the analysis of chemical bonds, but they can also serve to efficiently and comprehensibly compute linear response properties. While conventional canonical molecular orbitals provide an adequate basis for the treatment of excited states, a chemically meaningful identification of the different excited-state processes is difficult within such a delocalized orbital basis. In this work, starting from an initial set of supermolecular canonical molecular orbitals, we provide a simple one-step top-down embedding procedure for generating a set of orbitals which are localized in terms of the supermolecule, but delocalized over each subsystem composing the supermolecule. Using an orbital partitioning scheme based on such sets of localized orbitals, we further present a procedure for the construction of local excitations and charge-transfer states within the linear response framework of time-dependent density functional theory (TDDFT). This procedure provides direct access to approximate diabatic excitation energies and, under the Tamm--Dancoff approximation, also their corresponding electronic couplings -- quantities that are of primary importance in modelling energy transfer processes in complex biological systems. Our approach is compared with a recently developed diabatization procedure based on subsystem TDDFT using projection operators, which leads to a similar set of working equations. Although both of these methods differ in the general localization strategies adopted and the type of basis functions (Slaters vs. Gaussians) employed, an overall decent agreement is obtained

Simulation-Based Parallel Training

Numerical simulations are ubiquitous in science and engineering. Machine learning for science investigates how artificial neural architectures can learn from these simulations to speed up scientific discovery and engineering processes. Most of these architectures are trained in a supervised manner. They require tremendous amounts of data from simulations that are slow to generate and memory greedy. In this article, we present our ongoing work to design a training framework that alleviates those bottlenecks. It generates data in parallel with the training process. Such simultaneity induces a bias in the data available during the training. We present a strategy to mitigate this bias with a memory buffer. We test our framework on the multi-parametric Lorenz's attractor. We show the benefit of our framework compared to offline training and the success of our data bias mitigation strategy to capture the complex chaotic dynamics of the system

Are Public Schools Ready to Integrate Math Classes with Khan Academy?

We study the impacts of the program Khan Academy in Schools using a randomized control trial in Brazilian primary public schools. Once a week, teachers would take their students to the school's computer lab and teach using the computer-assisted learning platform, instead of their standard math classes. We find positive effects of the program on measures of attitudes towards math, which were not translated to a positive average treatment effect on students' math proficiency. We explore treatment heterogeneity by quality of implementation. This provides suggestive evidence that the program may have positive effects when there are no infrastructure problems and when the implementation modality is based on one computer per student. These results highlight the implementation challenges associated with educational tech-interventions in developing countries and help explain the mixed results found in the literature

LightGWAS: A Novel Machine Learning Procedure for Genome-Wide Association Study

This paper proposes a novel machine learning procedure for genome-wide association study (GWAS), named LightGWAS. It is based on the LightGBM framework, in addition to being a single, resilient, autonomous and scalable solution to address common limitations of GWAS implementations found in the literature. These include reliance on massive manual quality control steps and specific GWAS methods for each type of dataset morphology and size. Through this research, LightGWAS has been contrasted against PLINK2, one of the current state-of-the-art for GWAS implementations based on general linear model with support to firth regularisation. The mean differences measured upon standard classification metrics, extracted via quantitative empirical tests through k-fold cross-validation technique, indicated that LightGWAS outperforms PLINK2 for balanced, imbalanced, and high-imbalanced genomic datasets. Paired difference tests denoted statistical significance in the results extracted from the experiments with imbalanced datasets. This article contributes to the body of knowledge by presenting a potentially more efficient GWAS procedure based on nonparametric approaches. LightGWAS ensures adaptability with higher precision in the discovery of causal single-nucleotide polymorphisms, thanks to the leaf-wise tree growth algorithm offered by the state-of-the-art for gradient boosting decision trees. Control for false-positives and statistical power are automatically addressed by the model’s training process, which significative reduces human dependency during the study design