953 resultados para BRANCH-POINTS


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In the current higher education climate, there is a growing perception that the pressures associated with being an academic middle manager outweigh the perceived rewards of the position. This article investigates the personal and professional circumstances that lead academics to become middle managers by drawing on data from life history interviews undertaken with 17 male and female department heads from a range of disciplines, in a post-1992 UK university. The data suggests that experiencing conflict between personal and professional identities, manifested through different socialization experiences over time, can lead to a ‘turning point’ and a decision that affects a person’s career trajectory. Although the results of this study cannot be generalized, the findings may help other individuals and institutions move towards a firmer understanding of the academic who becomes head of department—in relation to theory, practice and research.

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High rates of nutrient loading from agricultural and urban development have resulted in surface water eutrophication and groundwater contamination in regions of Ontario. In Lake Simcoe (Ontario, Canada), anthropogenic nutrient contributions have contributed to increased algal growth, low hypolimnetic oxygen concentrations, and impaired fish reproduction. An ambitious programme has been initiated to reduce phosphorus loads to the lake, aiming to achieve at least a 40% reduction in phosphorus loads by 2045. Achievement of this target necessitates effective remediation strategies, which will rely upon an improved understanding of controls on nutrient export from tributaries of Lake Simcoe as well as improved understanding of the importance of phosphorus cycling within the lake. In this paper, we describe a new model structure for the integrated dynamic and process-based model INCA-P, which allows fully-distributed applications, suited to branched river networks. We demonstrate application of this model to the Black River, a tributary of Lake Simcoe, and use INCA-P to simulate the fluxes of P entering the lake system, apportion phosphorus among different sources in the catchment, and explore future scenarios of land-use change and nutrient management to identify high priority sites for implementation of watershed best management practises.

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A parallel formulation for the simulation of a branch prediction algorithm is presented. This parallel formulation identifies independent tasks in the algorithm which can be executed concurrently. The parallel implementation is based on the multithreading model and two parallel programming platforms: pthreads and Cilk++. Improvement in execution performance by up to 7 times is observed for a generic 2-bit predictor in a 12-core multiprocessor system.

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Empirical mode decomposition (EMD) is a data-driven method used to decompose data into oscillatory components. This paper examines to what extent the defined algorithm for EMD might be susceptible to data format. Two key issues with EMD are its stability and computational speed. This paper shows that for a given signal there is no significant difference between results obtained with single (binary32) and double (binary64) floating points precision. This implies that there is no benefit in increasing floating point precision when performing EMD on devices optimised for single floating point format, such as graphical processing units (GPUs).

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Let K⊆R be the unique attractor of an iterated function system. We consider the case where K is an interval and study those elements of K with a unique coding. We prove under mild conditions that the set of points with a unique coding can be identified with a subshift of finite type. As a consequence, we can show that the set of points with a unique coding is a graph-directed self-similar set in the sense of Mauldin and Williams (1988). The theory of Mauldin and Williams then provides a method by which we can explicitly calculate the Hausdorff dimension of this set. Our algorithm can be applied generically, and our result generalises the work of Daróczy, Kátai, Kallós, Komornik and de Vries.

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Damage following ischemia and reperfusion (I/R) is common in the intestine and can be caused during abdominal surgery, in several disease states and following intestinal transplantation. Most studies have concentrated on damage to the mucosa, although published evidence also points to effects on neurons. Moreover, alterations of neuronally controlled functions of the intestine persist after I/R. The present study was designed to investigate the time course of damage to neurons and the selectivity of the effect of I/R damage for specific types of enteric neurons. A branch of the superior mesenteric artery supplying the distal ileum of anesthetised guinea pigs was occluded for 1 h and the animals were allowed to recover for 2 h to 4 weeks before tissue was taken for the immunohistochemical localization of markers of specific neuron types in tissues from sham and I/R animals. The dendrites of neurons with nitric oxide synthase (NOS) immunoreactivity, which are inhibitory motor neurons and interneurons, were distorted and swollen by 24 h after I/R and remained enlarged up to 28 days. The total neuron profile areas (cell body plus dendrites) increased by 25%, but the sizes of cell bodies did not change significantly. Neurons of type II morphology (intrinsic primary afferent neurons), revealed by NeuN immunoreactivity, were transiently reduced in cell size, at 24 h and 7 days. These neurons also showed signs of minor cell surface blebbing. Calretinin neurons, many of which are excitatory motor neurons, were unaffected. Thus, this study revealed a selective damage to NOS neurons that was observed at 24 h and persisted up to 4 weeks, without a significant change in the relative numbers of NOS neurons.

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In this paper, we consider some non-homogeneous Poisson models to estimate the probability that an air quality standard is exceeded a given number of times in a time interval of interest. We assume that the number of exceedances occurs according to a non-homogeneous Poisson process (NHPP). This Poisson process has rate function lambda(t), t >= 0, which depends on some parameters that must be estimated. We take into account two cases of rate functions: the Weibull and the Goel-Okumoto. We consider models with and without change-points. When the presence of change-points is assumed, we may have the presence of either one, two or three change-points, depending of the data set. The parameters of the rate functions are estimated using a Gibbs sampling algorithm. Results are applied to ozone data provided by the Mexico City monitoring network. In a first instance, we assume that there are no change-points present. Depending on the adjustment of the model, we assume the presence of either one, two or three change-points. Copyright (C) 2009 John Wiley & Sons, Ltd.

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We show that a broad class of quantum critical points can be stable against locally correlated disorder even if they are unstable against uncorrelated disorder. Although this result seemingly contradicts the Harris criterion, it follows naturally from the absence of a random-mass term in the associated order parameter field theory. We illustrate the general concept with explicit calculations for quantum spin-chain models. Instead of the infinite-randomness physics induced by uncorrelated disorder, we find that weak locally correlated disorder is irrelevant. For larger disorder, we find a line of critical points with unusual properties such as an increase of the entanglement entropy with the disorder strength. We also propose experimental realizations in the context of quantum magnetism and cold-atom physics. Copyright (C) EPLA, 2011

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This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.

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In this note we discuss the convergence of Newton`s method for minimization. We present examples in which the Newton iterates satisfy the Wolfe conditions and the Hessian is positive definite at each step and yet the iterates converge to a non-stationary point. These examples answer a question posed by Fletcher in his 1987 book Practical methods of optimization.