Real and complex integral closure, Lipschitz equisingularity and applications on square matrices

Recently the authors investigated the Lipschitz triviality of simple germs of matrices. In this work, we improve some previous results and we present an extension of an integral closure result for the real setting. These tools are applied to investigate classes of square matrices singularities classified by Bruce and Tari

Linear decomposition of approximate multi-controlled single qubit gates

We provide a method for compiling approximate multi-controlled single qubit gates into quantum circuits without ancilla qubits. The total number of elementary gates to decompose an n-qubit multi-controlled gate is proportional to 32n, and the previous best approximate approach without auxiliary qubits requires 32nk elementary operations, where k is a function that depends on the error threshold. The proposed decomposition depends on an optimization technique that minimizes the CNOT gate count for multi-target and multi-controlled CNOT and SU(2) gates. Computational experiments show the reduction in the number of CNOT gates to apply multi-controlled U(2) gates. As multi-controlled single-qubit gates serve as fundamental components of quantum algorithms, the proposed decomposition offers a comprehensive solution that can significantly decrease the count of elementary operations employed in quantum computing applications

O uso da ponta de cana na engorda de novilhos em confinamento.

bitstream/item/138481/1/COT-09.pdfCNPGC

Avaliação econômica da engorda de novilhos confinados com subprodutos da microdestilaria de álcool.

Desempenho dos animais. Avaliação econômica.bitstream/item/104806/1/Avaliacao-economica-da-engorda.pd

Nota sobre métodos de colheita do sorgo sacarino para produção de álcool.

Sorgo sacarino cv. BR 501 foi colhido com e sem folhas para produção de caldo. Devido ao maior custo envolvido com a mão-de-obra, a retirada das folhas mostrou-se anti-econômica. Pesquisas para reduzir estes custos poderiam ser bastante benéficas.bitstream/item/132260/1/BP01.pd

Characterizing Nodes and Edges in Dynamic Attributed Networks: A Social-based Approach

How to characterize nodes and edges in dynamic attributed networks based on social aspects? We address this problem by exploring the strength of the ties between actors and their associated attributes over time, thus capturing the social roles of the actors and the meaning of their dynamic interactions in different social network scenarios. For this, we apply social concepts to promote a better understanding of the underlying complexity that involves actors and their social motivations. More specifically, we explore the notion of social capital given by the strategic positioning of a particular actor in a social structure by means of the concepts of brokerage, the ability of creating bridges with diversified patterns, and closure, the ability of aggregating nodes with similar patterns. As a result, we unveil the differences of social interactions in distinct academic coauthorship networks and questions \& answers communities. We also statistically validate our social definitions considering the importance of the nodes and edges in a social structure by means of network properties.Comment: 11 pages, 5 figure

Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks

Plant phenology studies rely on long-term monitoring of life cycles of plants. High-resolution unmanned aerial vehicles (UAVs) and near-surface technologies have been used for plant monitoring, demanding the creation of methods capable of locating, and identifying plant species through time and space. However, this is a challenging task given the high volume of data, the constant data missing from temporal dataset, the heterogeneity of temporal profiles, the variety of plant visual patterns, and the unclear definition of individuals' boundaries in plant communities. In this letter, we propose a novel method, suitable for phenological monitoring, based on convolutional networks (ConvNets) to perform spatio-temporal vegetation pixel classification on high-resolution images. We conducted a systematic evaluation using high-resolution vegetation image datasets associated with the Brazilian Cerrado biome. Experimental results show that the proposed approach is effective, overcoming other spatio-temporal pixel-classification strategies

Revisiting the drivers of acoustic similarities in tropical anuran assemblages

Acoustic signaling is key in mediating mate-choice, which directly impacts individual fitness. Because background noise and habitat structure can impair signal transmission, the acoustic space of mixed-species assemblages has long been hypothesized to reflect selective pressures against signal interference and degradation. However, other potential drivers that received far less attention can drive similar outputs on the acoustic space. Phylogenetic niche conservatism and allometric constraints may also modulate species acoustic features, and the acoustic space of communities could be a side-effect of ecological assembly processes involving other traits (e.g. environmental filtering). Additionally, the acoustic space can also reflect the sorting of species relying on public information through extended communication networks. Using an integrative approach, we revisit the potential drivers of the acoustic space by addressing the distribution of acoustic traits, body size, and phylogenetic relatedness in tropical anuran assemblages across gradients of environmental heterogeneity in the Pantanal wetlands. We found the overall acoustic space to be aggregated compared with null expectations, even when accounting for confounding effects of body size. Across assemblages, acoustic and phylogenetic differences were positively related, while acoustic and body size similarities were negatively related, although to a minor extent. We suggest that acoustic partitioning, acoustic adaptation, and allometric constraints play a minor role in shaping the acoustic output of tropical anuran assemblages and that phylogenetic niche conservatism and public information use would influence between-assemblage variation. Our findings highlight an overlooked multivariate nature of the acoustic dimension and underscore the importance of including the ecological context of communities to understand drivers of the acoustic space