Gestão da biblioteca escolar: metodologias, enfoques e aplicação de ferramentas de gestão e serviços de biblioteca

Este artigo apresenta a gestão da biblioteca escolar com enfoque na aplicação de ferramentas de gestão para avaliação da qualidade dos serviços oferecidos. Aborda as questões de qualidade e de administração como gestão garantindo aos serviços as características das expectativas e necessidades dos usuários da biblioteca escolar. O bibliotecário, como gestor dos serviços prestados na tomada de decisão, tem competência para utilizar as ferramentas que auxiliam a avaliar seus serviços, como brainstorming, diagrama de causa e efeito, diagrama de Pareto, histograma, matriz de priorização GUT, ciclo PDCA, fluxograma e 5W2H. Apresenta ainda algumas situações de problemas e dificuldades no âmbito da biblioteca escolar exemplificadas na utilização das ferramentas e a aplicação da junção de três ferramentas (fluxograma, PDCA e 5W2H) para avaliação dos serviços.

Literature of pioneer life in Iowa, 1923

Contains history and a bibliography of books and pamphlets written about frontier and pioneer life in the midwest.

Structural development accounting

We construct and estimate a unified model combining three of the main sources ofcross-country income disparities: differences in factor endowments, barriers to technologyadoption and the inappropriateness of frontier technologies to local conditions. The keycomponents are different types of workers, distortions to capital accumulation, directedtechnical change, costly adoption and spillovers from the world technology frontier. Despiteits parsimonious parametrization, our empirical model provides a good fit of GDP data forup to 86 countries in 1970 and 122 countries in 2000. Removing barriers to technologyadoption would increase the output per worker of the average non-OECD country relativeto the US from 0.19 to 0.61, while increasing skill premia in all countries. Removing barriersto trade in goods amplifies income disparities, induces skill-biased technology adoptionand increases skill premia in the majority of countries. These results are reverted if tradeliberalization is coupled with international IPR protection.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Market Index Biases and Minimum Risk Indices

Markets, in the real world, are not efficient zero-sum games where hypotheses of the CAPM are fulfilled. Then, it is easy to conclude the market portfolio is not located on Markowitz"s efficient frontier, and passive investments (and indexing) are not optimal but biased. In this paper, we define and analyze biases suffered by passive investors: the sample, construction, efficiency and active biases and tracking error are presented. We propose Minimum Risk Indices (MRI) as an alternative to deal with to market index biases, and to provide investors with portfolios closer to the efficient frontier, that is, more optimal investment possibilities. MRI (using a Parametric Value-at-Risk Minimization approach) are calculated for three stock markets achieving interesting results. Our indices are less risky and more profitable than current Market Indices in the Argentinean and Spanish markets, facing that way the Efficient Market Hypothesis. Two innovations must be outlined: an error dimension has been included in the backtesting and the Sharpe"s Ratio has been used to select the"best" MRI

The global welfare impact of China: Trade integration and technological change

This paper evaluates the global welfare impact of China's trade integration and technological change in a multi-country quantitative Ricardian-Heckscher-Ohlin model.We simulate two alternative growth scenarios: a "balanced" one in which China's productivity grows at the same rate in each sector, and an "unbalanced" one in whichChina's comparative disadvantage sectors catch up disproportionately faster to theworld productivity frontier. Contrary to a well-known conjecture (Samuelson 2004),the large majority of countries experience significantly larger welfare gains whenChina's productivity growth is biased towards its comparative disadvantage sectors.This finding is driven by the inherently multilateral nature of world trade.

Scale effect in hazard assessment - application to daily rainfall

Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24h. Events are modelled as a Poisson process and the 24h precipitation by a Generalized Pareto Distribution (GPD) of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA) corresponds to finite support variables, as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. We use the fact that a log-scale is better suited to the type of variable analyzed to overcome this inconsistency, thus showing that using the appropriate natural scale can be extremely important for proper hazard assessment. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimation is carried out by using Bayesian techniques

The effect of scale in daily precipitation hazard assessment

Daily precipitation is recorded as the total amount of water collected by a rain-gauge in 24 h. Events are modelled as a Poisson process and the 24 h precipitation by a Generalised Pareto Distribution (GPD) of excesses. Hazard assessment is complete when estimates of the Poisson rate and the distribution parameters, together with a measure of their uncertainty, are obtained. The shape parameter of the GPD determines the support of the variable: Weibull domain of attraction (DA) corresponds to finite support variables as should be for natural phenomena. However, Fréchet DA has been reported for daily precipitation, which implies an infinite support and a heavy-tailed distribution. Bayesian techniques are used to estimate the parameters. The approach is illustrated with precipitation data from the Eastern coast of the Iberian Peninsula affected by severe convective precipitation. The estimated GPD is mainly in the Fréchet DA, something incompatible with the common sense assumption of that precipitation is a bounded phenomenon. The bounded character of precipitation is then taken as a priori hypothesis. Consistency of this hypothesis with the data is checked in two cases: using the raw-data (in mm) and using log-transformed data. As expected, a Bayesian model checking clearly rejects the model in the raw-data case. However, log-transformed data seem to be consistent with the model. This fact may be due to the adequacy of the log-scale to represent positive measurements for which differences are better relative than absolute

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Utilização de diferentes recipientes na propagação da ameixeira através de estacas

O experimento foi desenvolvido em estufa com nebulização intermitente, objetivando comparar quatro tipos de recipientes no enraizamento de estacas de ameixeira. Foram utilizados ramos do ano das cultivares Frontier e Reubennel, dos quais foram retiradas estacas da porção mediana, com aproximadamente 12cm de comprimento, um par de folhas secionadas pela metade e duas incisões laterais na base. Posteriormente, as mesmas tiveram sua base tratada por imersão rápida durante 5 segundos em solução de ácido indolbutírico (AIB), a 2000mg.L-1 e acondicionadas nos seguintes recipientes: tubetes, bandejas de isopor (128 células), sacos plásticos grandes (14 x 20cm) e sacos plásticos pequenos (10 x 17cm), contendo vermiculita como substrato. O delineamento experimental adotado foi o inteiramente casualizado, com 3 repetições e 12 estacas por repetição. Após 70 dias, não foi observada diferença no percentual de enraizamento entre as cultivares. A bandeja proporcionou o menor enraizamento entre os recipientes, não havendo diferença entre os demais. O maior número de raízes foi obtido com a cultivar Frontier. O maior peso da matéria seca das raízes foi obtido com a cultivar Frontier em saco grandes. Maiores comprimentos de raízes foram obtidos nos maiores recipientes. O tubete proporciona maior economia e menor movimentação de substrato, sem reduzir o enraizamento.

Ranking-Dominance Relation for (Evolutionary) Multi-Objective Optimization

An alternative relation to Pareto-dominance relation is proposed. The new relation is based on ranking a set of solutions according to each separate objective and an aggregation function to calculate a scalar fitness value for each solution. The relation is called as ranking-dominance and it tries to tackle the curse of dimensionality commonly observedin evolutionary multi-objective optimization. Ranking-dominance can beused to sort a set of solutions even for a large number of objectives when Pareto-dominance relation cannot distinguish solutions from one another anymore. This permits search to advance even with a large number of objectives. It is also shown that ranking-dominance does not violate Pareto-dominance. Results indicate that selection based on ranking-dominance is able to advance search towards the Pareto-front in some cases, where selection based on Pareto-dominance stagnates. However, in some cases it is also possible that search does not proceed into direction of Pareto-front because the ranking-dominance relation permits deterioration of individual objectives. Results also show that when the number of objectives increases, selection based on just Pareto-dominance without diversity maintenance is able to advance search better than with diversity maintenance. Therefore, diversity maintenance is connive at the curse of dimensionality.