Variational Deep Semantic Hashing for Text Documents

As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

Mercado, legislação, sistemas de produção e sanidade.

Capítulo 1: O comércio de organismos aquáticos ornamentais. Capítulo 2: Legislação brasileira aplicada à aquicultura e comercialização. Capítulo 3: Sistemas e infraestrutura de produção Capítulo 4: Sanidade.bitstream/item/225053/1/lv-2021.pd

Electrically controlled long-distance spin transport through an antiferromagnetic insulator

Spintronics uses spins, the intrinsic angular momentum of electrons, as an alternative for the electron charge. Its long-term goal is in the development of beyond-Moore low dissipation technology devices. Recent progress demonstrated the long-distance transport of spin signals across ferromagnetic insulators. Antiferromagnetically ordered materials are however the most common class of magnetic materials with several crucial advantages over ferromagnetic systems. In contrast to the latter, antiferromagnets exhibit no net magnetic moment, which renders them stable and impervious to external fields. In addition, they can be operated at THz frequencies. While fundamentally their properties bode well for spin transport, previous indirect observations indicate that spin transmission through antiferromagnets is limited to short distances of a few nanometers. Here we demonstrate the long-distance, over tens of micrometers, propagation of spin currents through hematite (\alpha-Fe2O3), the most common antiferromagnetic iron oxide, exploiting the spin Hall effect for spin injection. We control the spin current flow by the interfacial spin-bias and by tuning the antiferromagnetic resonance frequency with an external magnetic field. This simple antiferromagnetic insulator is shown to convey spin information parallel to the compensated moment (N\'eel order) over distances exceeding tens of micrometers. This newly-discovered mechanism transports spin as efficiently as the net magnetic moments in the best-suited complex ferromagnets. Our results pave the way to ultra-fast, low-power antiferromagnet-insulator-based spin-logic devices that operate at room temperature and in the absence of magnetic fields

Complex Ashtekar variables and reality conditions for Holst's action

From the Holst action in terms of complex valued Ashtekar variables additional reality conditions mimicking the linear simplicity constraints of spin foam gravity are found. In quantum theory with the results of You and Rovelli we are able to implement these constraints weakly, that is in the sense of Gupta and Bleuler. The resulting kinematical Hilbert space matches the original one of loop quantum gravity, that is for real valued Ashtekar connection. Our result perfectly fit with recent developments of Rovelli and Speziale concerning Lorentz covariance within spin-form gravity.Comment: 24 pages, 2 picture

Determinação do comprimento ótimo de transectos para estimativa de necromassa floresta.

O objetivo deste trabalho foi avaliar diferentes comprimentos de transecto para determinação da necromassa florestal caída sobre o chão. Os dados são provenientes de transectos de 10 metros, medidos durante o teste de metodologia do Inventário Florestal Nacional na Amazônia, Cerrado e Caatinga, e no inventário em Santa Catarina, representando Floresta Ombrófila Mista e Floresta Estacional Decidual. O comparativo do coeficiente de variação, para transectos de 10 a 150 m indica que as maiores alterações desse estimador ocorrem no intervalo de 10 até 50 m, estabilizando-se a partir deste comprimento. A adoção de transectos de 10 m nas tipologias avaliadas é recomendável, pois com este comprimento ocorre uma redução de 35% na distância total de caminhamento em relação aos transectos de 20 m, para obter o mesmo erro amostral.Nota Científic

Taxonomic resolution refinement does not improve understanding of invertebrate's role on leaf litter breakdown

Abstract The invertebrate biodiversity of subtropical streams depends on the seasonal input of organic matter, as much as the leaf decomposition process on stream system. However, one of the challenges in determining the importance of invertebrates for leaf breakdown in subtropical streams is the low taxonomic resolution applied in most studies. To overcome this limitation, here we used litter bags with senescent leaves to evaluate the impact of different taxonomic resolutions of trophic group classification to assess the seasonal importance of invertebrate community for leaf litter breakdown in a subtropical stream (Atlantic Forest in western of Paraná state, Brazil). Litterfall was quarterly measured over a year. The leaf litter accumulated in an interval of 30 days was retrieved, weighed, and used for the leaf breakdown experiments (by litter bags). We found a lower importance of invertebrate community richness and density (shredders and scrapers) in leaf breakdown process irrespective of the taxonomic resolution (family or genus level used). Hyphomycetes biomass and fungi sporulation also did not present changes among sample times, and consecutively, importance for leaf breakdown. However, the richness and density of Chironomidae taxa respond differently depending on the taxonomic resolution used. Low litter breakdown may be explained by the increase of consumption of microorganisms, due to high density of Chironomidae scrapers evaluated at the genus level. Moreover, temperature is the main factor responsible for breakdown over the year, in a positive way. Therefore, our results indicated the family level as the taxonomic resolution sufficient to assess the role of shredders and scrapers in the leaf litter breakdown process of this subtropical stream system

Choosing the most effective pattern classification model under learning-time constraint

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Nowadays, large datasets are common and demand faster and more effective pattern analysis techniques. However, methodologies to compare classifiers usually do not take into account the learning-time constraints required by applications. This work presents a methodology to compare classifiers with respect to their ability to learn from classification errors on a large learning set, within a given time limit. Faster techniques may acquire more training samples, but only when they are more effective will they achieve higher performance on unseen testing sets. We demonstrate this result using several techniques, multiple datasets, and typical learning-time limits required by applications.Nowadays, large datasets are common and demand faster and more effective pattern analysis techniques. However, methodologies to compare classifiers usually do not take into account the learning-time constraints required by applications. This work presentsCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFUNDECT - FUNDAÇÃO DE APOIO AO DESENVOLVIMENTO DConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)CNPq [303182/2011-3, 477692/2012-5, 552559/2010-5, 481556/2009-5, 303673/2010-9, 470571/2013-6, 306166/2014-3, 311140/2014-9]CAPES [01-P-01965/2012]FAPESP [2011/14058-5, 2012/18768-0, 2007/52015-0, 2013/20387-7, 2014/16250-9]311140/2014-9; 303182/2011-3; 477692/2012-5; 552559/2010-5; 481556/2009-5; 303673/2010-9; 303182/2011-3; 470571/2013-6; 306166/2014-301-P-01965/20122011/14058-5, 2012/18768-0; 2007/52015-0; 2013/20387-7; 2014/16250-9sem informaçã

Gilbert Damping in Magnetic Multilayers

We study the enhancement of the ferromagnetic relaxation rate in thin films due to the adjacent normal metal layers. Using linear response theory, we derive the dissipative torque produced by the s-d exchange interaction at the ferromagnet-normal metal interface. For a slow precession, the enhancement of Gilbert damping constant is proportional to the square of the s-d exchange constant times the zero-frequency limit of the frequency derivative of the local dynamic spin susceptibility of the normal metal at the interface. Electron-electron interactions increase the relaxation rate by the Stoner factor squared. We attribute the large anisotropic enhancements of the relaxation rate observed recently in multilayers containing palladium to this mechanism. For free electrons, the present theory compares favorably with recent spin-pumping result of Tserkovnyak et al. [Phys. Rev. Lett. \textbf{88},117601 (2002)].Comment: 1 figure, 5page

Scents from Brazilian Cerrado: The essential oil from Calea teucriifolia (Gardner) Baker (Asteraceae).

Edition of Abstracts of the 48th International Symposium on Essential Oils, Pécs, Hungary, 2017. Abstracts. Babedio, 2017. ISEO 2017, 10 a 13 set. 2017. P-63