955 resultados para Multiple-minima Problem


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This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.

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Senile plaques associated with Alzheimer's disease contain deposits of fibrils formed by 39- to 43-residue β-amyloid peptides with possible neurotoxic effects. X-ray diffraction measurements on oriented fibril bundles have indicated an extended β-sheet structure for Alzheimer's β-amyloid fibrils and other amyloid fibrils, but the supramolecular organization of the β-sheets and other structural details are not well established because of the intrinsically noncrystalline, insoluble nature of amyloid fibrils. Here we report solid-state NMR measurements, using a multiple quantum (MQ) 13C NMR technique, that probe the β-sheet organization in fibrils formed by the full-length, 40-residue β-amyloid peptide (Aβ1–40). Although an antiparallel β-sheet organization often is assumed and is invoked in recent structural models for full-length β-amyloid fibrils, the MQNMR data indicate an in-register, parallel organization. This work provides site-specific, atomic-level structural constraints on full-length β-amyloid fibrils and applies MQNMR to a significant problem in structural biology.

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Some foreign genes introduced into plants are poorly expressed, even when transcription is controlled by a strong promoter. Perhaps the best examples of this problem are the cry genes of Bacillus thuringiensis (B.t.), which encode the insecticidal proteins commonly referred to as B.t. toxins. As a step toward overcoming such problems most effectively, we sought to elucidate the mechanisms limiting the expression of a typical B.t.-toxin gene, cryIA(c), which accumulates very little mRNA in tobacco (Nicotiana tabacum) cells. Most cell lines transformed with the cryIA(c) B.t.-toxin gene accumulate short, polyadenylated transcripts. The abundance of these transcripts can be increased by treating the cells with cycloheximide, a translation inhibitor that can stabilize many unstable transcripts. Using a series of hybridizations, reverse-transcriptase polymerase chain reactions, and RNase-H-digestion experiments, poly(A+) addition sites were identified in the B.t.-toxin-coding region corresponding to the short transcripts. A fourth polyadenylation site was identified using a chimeric gene. These results demonstrate for the first time to our knowledge that premature polyadenylation can limit the expression of a foreign gene in plants. Moreover, this work emphasizes that further study of the fundamental principles governing polyadenylation in plants will have basic as well as applied significance.

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Previous biochemical studies have suggested a role for bacterial DNA topoisomerase (TOPO) I in the suppression of R-loop formation during transcription. In this report, we present several pieces of genetic evidence to support a model in which R-loop formation is dynamically regulated during transcription by activities of multiple DNA TOPOs and RNase H. In addition, our results suggest that events leading to the serious growth problems in the absence of DNA TOPO I are linked to R-loop formation. We show that the overexpression of RNase H, an enzyme that degrades the RNA moiety of an R loop, can partially compensate for the absence of DNA TOPO I. We also note that a defect in DNA gyrase can correct several phenotypes associated with a mutation in the rnhA gene, which encodes the major RNase H activity. In addition, we found that a combination of topA and rnhA mutations is lethal.

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In this paper, we present a Text Summarisation tool, compendium, capable of generating the most common types of summaries. Regarding the input, single- and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractive-oriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture for compendium is divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions of compendium with respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows that compendium is very competitive and appropriate to be used as a tool for generating summaries.

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There are many models in the literature that have been proposed in the last decades aimed at assessing the reliability, availability and maintainability (RAM) of safety equipment, many of them with a focus on their use to assess the risk level of a technological system or to search for appropriate design and/or surveillance and maintenance policies in order to assure that an optimum level of RAM of safety systems is kept during all the plant operational life. This paper proposes a new approach for RAM modelling that accounts for equipment ageing and maintenance and testing effectiveness of equipment consisting of multiple items in an integrated manner. This model is then used to perform the simultaneous optimization of testing and maintenance for ageing equipment consisting of multiple items. An example of application is provided, which considers a simplified High Pressure Injection System (HPIS) of a typical Power Water Reactor (PWR). Basically, this system consists of motor driven pumps (MDP) and motor operated valves (MOV), where both types of components consists of two items each. These components present different failure and cause modes and behaviours, and they also undertake complex test and maintenance activities depending on the item involved. The results of the example of application demonstrate that the optimization algorithm provide the best solutions when the optimization problem is formulated and solved considering full flexibility in the implementation of testing and maintenance activities taking part of such an integrated RAM model.

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"C00-2118-0026."

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In large epidemiological studies missing data can be a problem, especially if information is sought on a sensitive topic or when a composite measure is calculated from several variables each affected by missing values. Multiple imputation is the method of choice for 'filling in' missing data based on associations among variables. Using an example about body mass index from the Australian Longitudinal Study on Women's Health, we identify a subset of variables that are particularly useful for imputing values for the target variables. Then we illustrate two uses of multiple imputation. The first is to examine and correct for bias when data are not missing completely at random. The second is to impute missing values for an important covariate; in this case omission from the imputation process of variables to be used in the analysis may introduce bias. We conclude with several recommendations for handling issues of missing data. Copyright (C) 2004 John Wiley Sons, Ltd.

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We consider a buying-selling problem when two stops of a sequence of independent random variables are required. An optimal stopping rule and the value of a game are obtained.

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The Gauss-Marquardt-Levenberg (GML) method of computer-based parameter estimation, in common with other gradient-based approaches, suffers from the drawback that it may become trapped in local objective function minima, and thus report optimized parameter values that are not, in fact, optimized at all. This can seriously degrade its utility in the calibration of watershed models where local optima abound. Nevertheless, the method also has advantages, chief among these being its model-run efficiency, and its ability to report useful information on parameter sensitivities and covariances as a by-product of its use. It is also easily adapted to maintain this efficiency in the face of potential numerical problems (that adversely affect all parameter estimation methodologies) caused by parameter insensitivity and/or parameter correlation. The present paper presents two algorithmic enhancements to the GML method that retain its strengths, but which overcome its weaknesses in the face of local optima. Using the first of these methods an intelligent search for better parameter sets is conducted in parameter subspaces of decreasing dimensionality when progress of the parameter estimation process is slowed either by numerical instability incurred through problem ill-posedness, or when a local objective function minimum is encountered. The second methodology minimizes the chance of successive GML parameter estimation runs finding the same objective function minimum by starting successive runs at points that are maximally removed from previous parameter trajectories. As well as enhancing the ability of a GML-based method to find the global objective function minimum, the latter technique can also be used to find the locations of many non-global optima (should they exist) in parameter space. This can provide a useful means of inquiring into the well-posedness of a parameter estimation problem, and for detecting the presence of bimodal parameter and predictive probability distributions. The new methodologies are demonstrated by calibrating a Hydrological Simulation Program-FORTRAN (HSPF) model against a time series of daily flows. Comparison with the SCE-UA method in this calibration context demonstrates a high level of comparative model run efficiency for the new method. (c) 2006 Elsevier B.V. All rights reserved.

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This study examined relations between stress and coping predictors and distress and positive outcomes in multiple sclerosis (MS). A total of 502 people with MS completed a questionnaire at Time 1 and, 3 months later, Time 2 (n= 404). Predictors included Time 1 illness (duration, number of symptoms, course), number of problems, appraisal and coping (acceptance, problem solving, emotional release, avoidance, personal health control, energy conservation). Dependent variables were Time 2 distress (anxiety, depression) and positive outcomes (life satisfaction, positive affect, benefits). Results indicated that as hypothesised, personal health control, emotional release and physical assistance were related to the positive outcomes, whereas avoidance was related to distress, and acceptance was associated with the positive outcomes and distress. Findings highlight the differential relations between coping strategies and positive and negative outcomes and the role of appraisal and coping in regulating distress and promoting positive psychological states while managing a chronic illness.

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Objective: To examine adjustment in children of a parent with multiple sclerosis within a stress and coping framework and compare them with those who have 'healthy' parents. Subjects: A total of 193 participants between 10 and 25 years completed questionnaires; 48 youngsters who had a parent with multiple sclerosis and 145 youngsters who reported that they did not have a parent with an illness or disability. Method: A questionnaire survey methodology was used. Variable sets included caregiving context (e.g. additional parental illness, family responsibilities, parental functional impairment, choice in helping), social support (network size, satisfaction), stress appraisal, coping (problem solving, seeking support, acceptance, wishful thinking, denial), and positive (life satisfaction, positive affect, benefits) and negative (distress, health) adjustment outcomes. Results: Caregiving context variables significantly correlated with poorer adjustment in children of a parent with multiple sclerosis included additional parental illness, higher family responsibilities, parental functional impairment and unpredictability of the parent's multiple sclerosis, and less choice in helping. As predicted, better adjustment in children of a parent with multiple sclerosis was related to higher levels of social support, lower stress appraisals, greater reliance on approach coping strategies (problem solving, seeking support and acceptance) and less reliance on avoidant coping (wishful thinking and denial). Compared with children of 'healthy' parents, children of a parent with multiple sclerosis reported greater family responsibilities, less reliance on problem solving and seeking social support coping, higher somatization and lower life satisfaction and positive affect. Conclusions: Findings delineate the key impacts of young caregiving and support a stress and coping model of adjustment in children of a parent with multiple sclerosis.

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Visualisation of multiple isoforms of kappa-casein on 2-D gels is restricted by the abundant alpha- and beta-caseins that not only limit gel loading but also migrate to similar regions as the more acidic kappa-casein isoforms. To overcome this problem, we took advantage of the absence of cysteine residues in alpha(S1)- and beta-casein by devising an affinity enrichment procedure based on reversible biotinylation of cysteine residues. Affinity capture of cysteine-containing proteins on avidin allowed the removal of the vast majority of alpha(S1)- and beta-casein, and on subsequent 2-D gel analysis 16 gel spots were identified as kappa-casein by PMF. Further analysis of the C-terminal tryptic peptide along with structural predictions based on mobility on the 2-D gel allowed us to assign identities to each spot in terms of genetic variant (A or B), phosphorylation status (1, 2 or 3) and glycosylation status (from 0 to 6). Eight isoforms of the A and B variants with the same PTMs were observed. When the casein fraction of milk from a single cow, homozygous for the B variant of kappa-casein, was used as the starting material, 17 isoforms from 13 gel spots were characterised. Analysis of isoforms of low abundance proved challenging due to the low amount of material that could be extracted from the gels as well as the lability of the PTMs during MS analysis. However, we were able to identify a previously unrecognised site, T-166, that could be phosphorylated or glycosylated. Despite many decades of analysis of milk proteins, the reasons for this high level of heterogeneity are still not clear.

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The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time. The distribution problem is generally formulated as the vehicle routing problem (VRP). Nevertheless, there is a rigid assumption that there is only one depot. In cases, for instance, where a logistics company has more than one depot, the VRP is not suitable. To resolve this limitation, this paper focuses on the VRP with multiple depots, or multi-depot VRP (MDVRP). The MDVRP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To deal with the problem efficiently, two hybrid genetic algorithms (HGAs) are developed in this paper. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method and the nearest neighbor heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different problem sizes. It is proved that the performance of HGA2 is superior to that of HGA1 in terms of the total delivery time.

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This paper formulates several mathematical models for determining the optimal sequence of component placements and assignment of component types to feeders simultaneously or the integrated scheduling problem for a type of surface mount technology placement machines, called the sequential pick-andplace (PAP) machine. A PAP machine has multiple stationary feeders storing components, a stationary working table holding a printed circuit board (PCB), and a movable placement head to pick up components from feeders and place them to a board. The objective of integrated problem is to minimize the total distance traveled by the placement head. Two integer nonlinear programming models are formulated first. Then, each of them is equivalently converted into an integer linear type. The models for the integrated problem are verified by two commercial packages. In addition, a hybrid genetic algorithm previously developed by the authors is adopted to solve the models. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total traveling distance.