Quantum state tomography and quantum logical operations in a three qubits NMR quadrupolar system

In this work, we present an implementation of quantum logic gates and algorithms in a three effective qubits system, represented by a (I = 7/2) NMR quadrupolar nuclei. To implement these protocols we have used the strong modulating pulses (SMP) and the various stages of each implementation were verified by quantum state tomography (QST). The results for the computational base states, Toffolli logic gates, and Deutsch-Jozsa and Grover algorithms are presented here. Also, we discuss the difficulties and advantages of implementing such protocols using the SMP technique in quadrupolar systems.

Um rio de imagens

O presente artigo apresenta uma reflexão sobre a imagem dos rios ao longo da história da arte, a partir da pesquisa realizada por mim para a tese de doutorado “Poéticas Líquidas: a água na arte contemporânea“. Os rios são estudados tanto a partir de suas representações pictóricas de interesse histórico, como também enquanto suporte para a realização de obras de arte contemporânea. São identificadas conotações simbólicas e espirituais dos rios, como metáfora para o transcorrer da vida e para as transformações, assim como também suas questões mais terrenas, ligadas à ecologia e à sua relação com as cidades. Como reflexão final, apresento alguns trabalhos plásticos realizados por mim ao longo dos anos, que discutem a presença dos rios na vida contemporânea, a partir de proposições estéticas que refletem as conflituosas relações entre o homem e a natureza na atualidade.

Generalizations of Lie Algebras

The generalizations of Lie algebras appeared in the modern mathematics and mathematical physics. In this paper we consider recent developments and remaining open problems on the subject. Some of that developments have been influenced by lectures given by Professor Jaime Keller in his research seminar. The survey includes Lie superalgebras, color Lie algebras, Lie algebras in symmetric categories, free Lie tau-algebras, and some generalizations with non-associative enveloping algebras: tangent algebras to analytic loops, bialgebras and primitive elements, non-associative Hopf algebras.

Necessidades de saúde, políticas públicas e gênero: a perspectiva das práticas profissionais

Examina-se a relação entre políticas públicas e práticas dos profissionais, relativamente às necessidades de saúde. Em abordagem teórico-conceitual, as práticas são definidas como desempenhos permeados por determinantes técnico-cien­tíficos e sócio-históricos para a produção social de um trabalho, analisando-se suas possibilidades de mudanças culturais, éticas e políticas, para um agir crítico das desigualdades de gênero. Tomando-se a atenção integral à saúde dos homens, examina-se a relevância da distinção entre necessidades masculinas e femininas, enquanto realidades parciais não necessariamente convergentes na (re)produção daquelas desigualdades. Igualmente se examinam as práticas profissionais, como realidade parcial e distinta das políticas, estabelecendo relações não imediatas. Desenvolve-se que são obstáculos simbólicos e práticos para mudanças: a normalização biomédica redutora das necessidades, a cultura do trabalho autônomo e da abordagem individualizante das necessidades, a cultura tradicional de gênero conservando práticas desiguais para homens e mulheres e a ausência de inscrição dos direitos como parte do agir profissio­nal. Isto exige propostas específicas às práticas de saúde e às necessidades masculinas para maior convergência com as reformas das políticas.

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

Prominent Effect of Soil Network Heterogeneity on Microbial Invasion

Using a network representation for real soil samples and mathematical models for microbial spread, we show that the structural heterogeneity of the soil habitat may have a very significant influence on the size of microbial invasions of the soil pore space. In particular, neglecting the soil structural heterogeneity may lead to a substantial underestimation of microbial invasion. Such effects are explained in terms of a crucial interplay between heterogeneity in microbial spread and heterogeneity in the topology of soil networks. The main influence of network topology on invasion is linked to the existence of long channels in soil networks that may act as bridges for transmission of microorganisms between distant parts of soil.

A Bayesian Approach for Decision Making on the Identification of Genes with Different Expression Levels: An Application to Escherichia coli Bacterium Data

A common interest in gene expression data analysis is to identify from a large pool of candidate genes the genes that present significant changes in expression levels between a treatment and a control biological condition. Usually, it is done using a statistic value and a cutoff value that are used to separate the genes differentially and nondifferentially expressed. In this paper, we propose a Bayesian approach to identify genes differentially expressed calculating sequentially credibility intervals from predictive densities which are constructed using the sampled mean treatment effect from all genes in study excluding the treatment effect of genes previously identified with statistical evidence for difference. We compare our Bayesian approach with the standard ones based on the use of the t-test and modified t-tests via a simulation study, using small sample sizes which are common in gene expression data analysis. Results obtained report evidence that the proposed approach performs better than standard ones, especially for cases with mean differences and increases in treatment variance in relation to control variance. We also apply the methodologies to a well-known publicly available data set on Escherichia coli bacterium.

Automatic lumen segmentation in IVOCT images using binary morphological reconstruction

Abstract Background Atherosclerosis causes millions of deaths, annually yielding billions in expenses round the world. Intravascular Optical Coherence Tomography (IVOCT) is a medical imaging modality, which displays high resolution images of coronary cross-section. Nonetheless, quantitative information can only be obtained with segmentation; consequently, more adequate diagnostics, therapies and interventions can be provided. Since it is a relatively new modality, many different segmentation methods, available in the literature for other modalities, could be successfully applied to IVOCT images, improving accuracies and uses. Method An automatic lumen segmentation approach, based on Wavelet Transform and Mathematical Morphology, is presented. The methodology is divided into three main parts. First, the preprocessing stage attenuates and enhances undesirable and important information, respectively. Second, in the feature extraction block, wavelet is associated with an adapted version of Otsu threshold; hence, tissue information is discriminated and binarized. Finally, binary morphological reconstruction improves the binary information and constructs the binary lumen object. Results The evaluation was carried out by segmenting 290 challenging images from human and pig coronaries, and rabbit iliac arteries; the outcomes were compared with the gold standards made by experts. The resultant accuracy was obtained: True Positive (%) = 99.29 ± 2.96, False Positive (%) = 3.69 ± 2.88, False Negative (%) = 0.71 ± 2.96, Max False Positive Distance (mm) = 0.1 ± 0.07, Max False Negative Distance (mm) = 0.06 ± 0.1. Conclusions In conclusion, by segmenting a number of IVOCT images with various features, the proposed technique showed to be robust and more accurate than published studies; in addition, the method is completely automatic, providing a new tool for IVOCT segmentation.