Silagem do bagaço de sorgo sacarino

Brazilian sweet sorghum is used to generate ethanol and the bagasse is burned in industrial boilers or deposited on soil polluting the environment. This study evaluated the performance of sorghum plants and its bagasse silage nutritional value aiming to use it in the ruminant nutrition. Experiments were set up on the UTFPR campus at Dois Vizinhos-PR. The first trial was established on October 2nd, 2012 using the genotypes ADV 2010, Hunnigreen, Sugargraze, Volumax, BR 505, 503, 501 and the second trial at 2013 on November 27th assessing the materials ADV 2010, Sugargraze, Hunnigreen, EX 5110, BR 506, 508, 509 and 511. Experimental was laid out as a randomized block design with three replications. Results were analyzed through ANOVA comparing the averages by Duncan test at 5% error probability. As field variables were evaluated: plant height (Pl hei), green mass production (GM Prod), percentage of leaves, stems and panicles in relation to the plant, stems production without straw (Prod stems with straw), whole stems production (Who stems Prod), stem diameter (Stem diam), juice production (Juice prod) and Brix degree (oBrix). After juice plant extraction, forage bagasse was crushed and packed in silos for 60 days and green matter yield was estimated (GM). In bagasse silage gauged to buffer capacity (BC), dry matter (DM), mineral matter (MM), crude protein (CP), ether extract (EE), total carbohydrates (TC), non-fibrous carbohydrates (NFCH), neutral detergent fiber (NDF), acid detergent fiber (ADF), lignin (LIG ) and digestibility "in vitro" (DIGIV). There was no significant difference (P> 0.05) between genotypes regarding to green matter production and on average, the second crop yield was lower and reflected in the reduction of bagasse production. Bagasse silage DM was of 32.3% and 33.1%; NDF 73% and 65.8%, crude protein 3.8% and 5.9; pH 3.7 and 3.7; TC and 9.8 and 10.7. mg MS-1; the amount of NFCH was 11.1 and 13.5%; DIG of DM 36.9 and 62.4% for the respectively to the bagasse produced from materials grown in the 2012/2013 and 2013/2014 seasons. Hybrid genotypes had a better agronomic performance while the varieties were more efficient in bromatological indexes. And despite the high percentage of NDF and the low protein level, it is possible to feed ruminants with this coproduct.

Quantum Gate and Quantum State Preparation through Neighboring Optimal Control

Successful implementation of fault-tolerant quantum computation on a system of qubits places severe demands on the hardware used to control the many-qubit state. It is known that an accuracy threshold Pa exists for any quantum gate that is to be used for such a computation to be able to continue for an unlimited number of steps. Specifically, the error probability Pe for such a gate must fall below the accuracy threshold: Pe < Pa. Estimates of Pa vary widely, though Pa ∼ 10−4 has emerged as a challenging target for hardware designers. I present a theoretical framework based on neighboring optimal control that takes as input a good quantum gate and returns a new gate with better performance. I illustrate this approach by applying it to a universal set of quantum gates produced using non-adiabatic rapid passage. Performance improvements are substantial comparing to the original (unimproved) gates, both for ideal and non-ideal controls. Under suitable conditions detailed below, all gate error probabilities fall by 1 to 4 orders of magnitude below the target threshold of 10−4. After applying the neighboring optimal control theory to improve the performance of quantum gates in a universal set, I further apply the general control theory in a two-step procedure for fault-tolerant logical state preparation, and I illustrate this procedure by preparing a logical Bell state fault-tolerantly. The two-step preparation procedure is as follow: Step 1 provides a one-shot procedure using neighboring optimal control theory to prepare a physical qubit state which is a high-fidelity approximation to the Bell state |β01⟩ = 1/√2(|01⟩ + |10⟩). I show that for ideal (non-ideal) control, an approximate |β01⟩ state could be prepared with error probability ϵ ∼ 10−6 (10−5) with one-shot local operations. Step 2 then takes a block of p pairs of physical qubits, each prepared in |β01⟩ state using Step 1, and fault-tolerantly prepares the logical Bell state for the C4 quantum error detection code.

A medida e as escalas de avaliação da saúde das populações neonatais e pediátricas : estudo de simulação de Monte Carlo com variáveis ordinais

A investigação na área da saúde e a utilização dos seus resultados tem funcionado como base para a melhoria da qualidade de cuidados, exigindo dos profissionais de saúde conhecimentos na área específica onde desempenham funções, conhecimentos em metodologia de investigação que incluam as técnicas de observação, técnicas de recolha e análise de dados, para mais facilmente serem leitores capacitados dos resultados da investigação. Os profissionais de saúde são observadores privilegiados das respostas humanas à saúde e à doença, podendo contribuir para o desenvolvimento e bem-estar dos indivíduos muitas vezes em situações de grande vulnerabilidade. Em saúde infantil e pediatria o enfoque está nos cuidados centrados na família privilegiando-se o desenvolvimento harmonioso da criança e jovem, valorizando os resultados mensuráveis em saúde que permitam determinar a eficácia das intervenções e a qualidade de saúde e de vida. No contexto pediátrico realçamos as práticas baseadas na evidência, a importância atribuída à pesquisa e à aplicação dos resultados da investigação nas práticas clínicas, assim como o desenvolvimento de instrumentos de mensuração padronizados, nomeadamente as escalas de avaliação, de ampla utilização clínica, que facilitam a apreciação e avaliação do desenvolvimento e da saúde das crianças e jovens e resultem em ganhos em saúde. A observação de forma sistematizada das populações neonatais e pediátricas com escalas de avaliação tem vindo a aumentar, o que tem permitido um maior equilíbrio na avaliação das crianças e também uma observação baseada na teoria e nos resultados da investigação. Alguns destes aspetos serviram de base ao desenvolvimento deste trabalho que pretende dar resposta a 3 objetivos fundamentais. Para dar resposta ao primeiro objetivo, “Identificar na literatura científica, os testes estatísticos mais frequentemente utilizados pelos investigadores da área da saúde infantil e pediatria quando usam escalas de avaliação” foi feita uma revisão sistemática da literatura, que tinha como objetivo analisar artigos científicos cujos instrumentos de recolha de dados fossem escalas de avaliação, na área da saúde da criança e jovem, desenvolvidas com variáveis ordinais, e identificar os testes estatísticos aplicados com estas variáveis. A análise exploratória dos artigos permitiu-nos verificar que os investigadores utilizam diferentes instrumentos com diferentes formatos de medida ordinal (com 3, 4, 5, 7, 10 pontos) e tanto aplicam testes paramétricos como não paramétricos, ou os dois em simultâneo, com este tipo de variáveis, seja qual for a dimensão da amostra. A descrição da metodologia nem sempre explicita se são cumpridas as assunções dos testes. Os artigos consultados nem sempre fazem referência à distribuição de frequência das variáveis (simetria/assimetria) nem à magnitude das correlações entre os itens. A leitura desta bibliografia serviu de suporte à elaboração de dois artigos, um de revisão sistemática da literatura e outro de reflexão teórica. Apesar de terem sido encontradas algumas respostas às dúvidas com que os investigadores e os profissionais, que trabalham com estes instrumentos, se deparam, verifica-se a necessidade de desenvolver estudos de simulação que confirmem algumas situações reais e alguma teoria já existente, e trabalhem outros aspetos nos quais se possam enquadrar os cenários reais de forma a facilitar a tomada de decisão dos investigadores e clínicos que utilizam escalas de avaliação. Para dar resposta ao segundo objetivo “Comparar a performance, em termos de potência e probabilidade de erro de tipo I, das 4 estatísticas da MANOVA paramétrica com 2 estatísticas da MANOVA não paramétrica quando se utilizam variáveis ordinais correlacionadas, geradas aleatoriamente”, desenvolvemos um estudo de simulação, através do Método de Monte Carlo, efetuado no Software R. O delineamento do estudo de simulação incluiu um vetor com 3 variáveis dependentes, uma variável independente (fator com três grupos), escalas de avaliação com um formato de medida com 3, 4, 5, e 7 pontos, diferentes probabilidades marginais (p1 para distribuição simétrica, p2 para distribuição assimétrica positiva, p3 para distribuição assimétrica negativa e p4 para distribuição uniforme) em cada um dos três grupos, correlações de baixa, média e elevada magnitude (r=0.10, r=0.40, r=0.70, respetivamente), e seis dimensões de amostras (n=30, 60, 90, 120, 240, 300). A análise dos resultados permitiu dizer que a maior raiz de Roy foi a estatística que apresentou estimativas de probabilidade de erro de tipo I e de potência de teste mais elevadas. A potência dos testes apresenta comportamentos diferentes, dependendo da distribuição de frequência da resposta aos itens, da magnitude das correlações entre itens, da dimensão da amostra e do formato de medida da escala. Tendo por base a distribuição de frequência, considerámos três situações distintas: a primeira (com probabilidades marginais p1,p1,p4 e p4,p4,p1) em que as estimativas da potência eram muito baixas, nos diferentes cenários; a segunda situação (com probabilidades marginais p2,p3,p4; p1,p2,p3 e p2,p2,p3) em que a magnitude das potências é elevada, nas amostras com dimensão superior ou igual a 60 observações e nas escalas com 3, 4,5 pontos e potências de magnitude menos elevada nas escalas com 7 pontos, mas com a mesma ma magnitude nas amostras com dimensão igual a 120 observações, seja qual for o cenário; a terceira situação (com probabilidades marginais p1,p1,p2; p1,p2,p4; p2,p2,p1; p4,p4,p2 e p2,p2,p4) em que quanto maiores, a intensidade das correlações entre itens e o número de pontos da escala, e menor a dimensão das amostras, menor a potência dos testes, sendo o lambda de Wilks aplicado às ordens mais potente do que todas as outra s estatísticas da MANOVA, com valores imediatamente a seguir à maior raiz de Roy. No entanto, a magnitude das potências dos testes paramétricos e não paramétricos assemelha-se nas amostras com dimensão superior a 90 observações (com correlações de baixa e média magnitude), entre as variáveis dependentes nas escalas com 3, 4 e 5 pontos; e superiores a 240 observações, para correlações de baixa intensidade, nas escalas com 7 pontos. No estudo de simulação e tendo por base a distribuição de frequência, concluímos que na primeira situação de simulação e para os diferentes cenários, as potências são de baixa magnitude devido ao facto de a MANOVA não detetar diferenças entre grupos pela sua similaridade. Na segunda situação de simulação e para os diferentes cenários, a magnitude das potências é elevada em todos os cenários cuja dimensão da amostra seja superior a 60 observações, pelo que é possível aplicar testes paramétricos. Na terceira situação de simulação, e para os diferentes cenários quanto menor a dimensão da amostra e mais elevada a intensidade das correlações e o número de pontos da escala, menor a potência dos testes, sendo a magnitude das potências mais elevadas no teste de Wilks aplicado às ordens, seguido do traço de Pillai aplicado às ordens. No entanto, a magnitude das potências dos testes paramétricos e não paramétricos assemelha-se nas amostras com maior dimensão e correlações de baixa e média magnitude. Para dar resposta ao terceiro objetivo “Enquadrar os resultados da aplicação da MANOVA paramétrica e da MANOVA não paramétrica a dados reais provenientes de escalas de avaliação com um formato de medida com 3, 4, 5 e 7 pontos, nos resultados do estudo de simulação estatística” utilizaram-se dados reais que emergiram da observação de recém-nascidos com a escala de avaliação das competências para a alimentação oral, Early Feeding Skills (EFS), o risco de lesões da pele, com a Neonatal Skin Risk Assessment Scale (NSRAS), e a avaliação da independência funcional em crianças e jovens com espinha bífida, com a Functional Independence Measure (FIM). Para fazer a análise destas escalas foram realizadas 4 aplicações práticas que se enquadrassem nos cenários do estudo de simulação. A idade, o peso, e o nível de lesão medular foram as variáveis independentes escolhidas para selecionar os grupos, sendo os recém-nascidos agrupados por “classes de idade gestacional” e por “classes de peso” as crianças e jovens com espinha bífida por “classes etárias” e “níveis de lesão medular”. Verificou-se um bom enquadramento dos resultados com dados reais no estudo de simulação.

Sparse probability density function estimation using the minimum integrated square error

We develop a new sparse kernel density estimator using a forward constrained regression framework, within which the nonnegative and summing-to-unity constraints of the mixing weights can easily be satisfied. Our main contribution is to derive a recursive algorithm to select significant kernels one at time based on the minimum integrated square error (MISE) criterion for both the selection of kernels and the estimation of mixing weights. The proposed approach is simple to implement and the associated computational cost is very low. Specifically, the complexity of our algorithm is in the order of the number of training data N, which is much lower than the order of N2 offered by the best existing sparse kernel density estimators. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to those of the classical Parzen window estimate and other existing sparse kernel density estimators.

Human Error Contribution in Collision and Grounding of Oil Tankers

The purpose of this article is to present a quantitative analysis of the human failure contribution in the collision and/or grounding of oil tankers, considering the recommendation of the ""Guidelines for Formal Safety Assessment"" of the International Maritime Organization. Initially, the employed methodology is presented, emphasizing the use of the technique for human error prediction to reach the desired objective. Later, this methodology is applied to a ship operating on the Brazilian coast and, thereafter, the procedure to isolate the human actions with the greatest potential to reduce the risk of an accident is described. Finally, the management and organizational factors presented in the ""International Safety Management Code"" are associated with these selected actions. Therefore, an operator will be able to decide where to work in order to obtain an effective reduction in the probability of accidents. Even though this study does not present a new methodology, it can be considered as a reference in the human reliability analysis for the maritime industry, which, in spite of having some guides for risk analysis, has few studies related to human reliability effectively applied to the sector.

Bayesian analysis of the error correction model

This paper presents a method for estimating the posterior probability density of the cointegrating rank of a multivariate error correction model. A second contribution is the careful elicitation of the prior for the cointegrating vectors derived from a prior on the cointegrating space. This prior obtains naturally from treating the cointegrating space as the parameter of interest in inference and overcomes problems previously encountered in Bayesian cointegration analysis. Using this new prior and Laplace approximation, an estimator for the posterior probability of the rank is given. The approach performs well compared with information criteria in Monte Carlo experiments. (C) 2003 Elsevier B.V. All rights reserved.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

Minimum error contrast enhancement

Contrast enhancement is an image processing technique where the objective is to preprocess the image so that relevant information can be either seen or further processed more reliably. These techniques are typically applied when the image itself or the device used for image reproduction provides poor visibility and distinguishability of different regions of interest inthe image. In most studies, the emphasis is on the visualization of image data,but this human observer biased goal often results to images which are not optimal for automated processing. The main contribution of this study is to express the contrast enhancement as a mapping from N-channel image data to 1-channel gray-level image, and to devise a projection method which results to an image with minimal error to the correct contrast image. The projection, the minimum-error contrast image, possess the optimal contrast between the regions of interest in the image. The method is based on estimation of the probability density distributions of the region values, and it employs Bayesian inference to establish the minimum error projection.

Bias and standard error for social reciprocity measurements

The directional consistency and skew-symmetry statistics have been proposed as global measurements of social reciprocity. Although both measures can be useful for quantifying social reciprocity, researchers need to know whether these estimators are biased in order to assess descriptive results properly. That is, if estimators are biased, researchers should compare actual values with expected values under the specified null hypothesis. Furthermore, standard errors are needed to enable suitable assessment of discrepancies between actual and expected values. This paper aims to derive some exact and approximate expressions in order to obtain bias and standard error values for both estimators for round-robin designs, although the results can also be extended to other reciprocal designs.

The modulation of simple reaction time by the spatial probability of a visual stimulus

Simple reaction time (SRT) in response to visual stimuli can be influenced by many stimulus features. The speed and accuracy with which observers respond to a visual stimulus may be improved by prior knowledge about the stimulus location, which can be obtained by manipulating the spatial probability of the stimulus. However, when higher spatial probability is achieved by holding constant the stimulus location throughout successive trials, the resulting improvement in performance can also be due to local sensory facilitation caused by the recurrent spatial location of a visual target (position priming). The main objective of the present investigation was to quantitatively evaluate the modulation of SRT by the spatial probability structure of a visual stimulus. In two experiments the volunteers had to respond as quickly as possible to the visual target presented on a computer screen by pressing an optic key with the index finger of the dominant hand. Experiment 1 (N = 14) investigated how SRT changed as a function of both the different levels of spatial probability and the subject's explicit knowledge about the precise probability structure of visual stimulation. We found a gradual decrease in SRT with increasing spatial probability of a visual target regardless of the observer's previous knowledge concerning the spatial probability of the stimulus. Error rates, below 2%, were independent of the spatial probability structure of the visual stimulus, suggesting the absence of a speed-accuracy trade-off. Experiment 2 (N = 12) examined whether changes in SRT in response to a spatially recurrent visual target might be accounted for simply by sensory and temporally local facilitation. The findings indicated that the decrease in SRT brought about by a spatially recurrent target was associated with its spatial predictability, and could not be accounted for solely in terms of sensory priming.

An Analysis of the Effect of Gaussian Error in Object Recognition

Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.

Error analysis of a Monte Carlo algorithm for computing bilinear forms of matrix powers

In this paper we present error analysis for a Monte Carlo algorithm for evaluating bilinear forms of matrix powers. An almost Optimal Monte Carlo (MAO) algorithm for solving this problem is formulated. Results for the structure of the probability error are presented and the construction of robust and interpolation Monte Carlo algorithms are discussed. Results are presented comparing the performance of the Monte Carlo algorithm with that of a corresponding deterministic algorithm. The two algorithms are tested on a well balanced matrix and then the effects of perturbing this matrix, by small and large amounts, is studied.