973 resultados para Cluster Approach
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A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.
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This study monitored the dynamics and diversity of the human faecal 'Atopobium cluster' over a 3-month period using a polyphasic approach. Fresh faecal samples were collected fortnightly from 13 healthy donors (6 males and 7 females) aged between 26 and 61 years. Fluorescence in situ hybridization was used to enumerate total (EUB338mix) and 'Atopobium cluster' (ATO291) bacteria, with counts ranging between 1.12 × 1011 and 9.95 × 1011, and 1.03 × 109 and 1.16 × 1011 cells (g dry weight faeces)-1, respectively. The 'Atopobium cluster' population represented 0.2-22 % of the total bacteria, with proportions donor-dependent. Denaturing gradient gel electrophoresis (DGGE) using 'Atopobium cluster'-specific primers demonstrated faecal populations of these bacteria were relatively stable, with bands identified as Collinsella aerofaciens, Collinsella intestinalis/Collinsella stercoris, Collinsella tanakaei, Coriobacteriaceae sp. PEAV3-3, Eggerthella lenta, Gordonibacter pamelaeae, Olsenella profusa, Olsenella uli and Paraeggerthella hongkongensis in the DGGE profiles of individuals. Colony PCR was used to identify 'Atopobium cluster' bacteria isolated from faeces (n = 224 isolates). 16S rRNA gene sequence analysis of isolates demonstrated Collinsella aerofaciens represented the predominant (88 % of isolates) member of the 'Atopobium cluster' found in human faeces, being found in nine individuals. Eggerthella lenta was identified in three individuals (3.6 % of isolates). Isolates of Collinsella tanakaei, an 'Enorma' sp. and representatives of novel species belonging to the 'Atopobium cluster' were also identified in the study. Phenotypic characterization of the isolates demonstrated their highly saccharolytic nature and heterogeneous phenotypic profiles, and 97 % of the isolates displayed lipase activity.
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ESA’s first multi-satellite mission Cluster is unique in its concept of 4 satellites orbiting in controlled formations. This will give an unprecedented opportunity to study structure and dynamics of the magnetosphere. In this paper we discuss ways in which ground-based remote-sensing observations of the ionosphere can be used to support the multipoint in-situ satellite measurements. There are a very large number of potentially useful configurations between the satellites and any one ground-based observatory; however, the number of ideal occurrences for any one configuration is low. Many of the ground-based instruments cannot operate continuously and Cluster will take data only for a part of each orbit, depending on how much high-resolution (‘burst-mode’) data are acquired. In addition, there are a great many instrument modes and the formation, size and shape of the cluster of the four satellites to consider. These circumstances create a clear and pressing need for careful planning to ensure that the scientific return from Cluster is maximised by additional coordinated ground-based observations. For this reason, ESA established a working group to coordinate the observations on the ground with Cluster. We will give a number of examples how the combined spacecraft and ground-based observations can address outstanding questions in magnetospheric physics. An online computer tool has been prepared to allow for the planning of conjunctions and advantageous constellations between the Cluster spacecraft and individual or combined ground-based systems. During the mission a ground-based database containing index and summary data will help to identify interesting datasets and allow to select intervals for coordinated studies. We illustrate the philosophy of our approach, using a few important examples of the many possible configurations between the satellite and the ground-based instruments.
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Flow in geophysical fluids is commonly summarized by coherent streams, for example conveyor belt flows in extratropical cyclones or jet streaks in the upper troposphere. Typically, parcel trajectories are calculated from the flow field and subjective thresholds are used to distinguish coherent streams of interest. This methodology contribution develops a more objective approach to distinguish coherent airstreams within extratropical cyclones. Agglomerative clustering is applied to trajectories along with a method to identify the optimal number of cluster classes. The methodology is applied to trajectories associated with the low-level jets of a well-studied extratropical cyclone. For computational efficiency, a constraint that trajectories must pass through these jet regions is applied prior to clustering; the partitioning into different airstreams is then performed by the agglomerative clustering. It is demonstrated that the methodology can identify the salient flow structures of cyclones: the warm and cold conveyor belts. A test focusing on the airstreams terminating at the tip of the bent-back front further demonstrates the success of the method in that it can distinguish fine-scale flow structure such as descending sting jet airstreams.
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Malvales is an order of flowering plants with a controversial circumscription. The relationships between taxa, particularly Malvaceae, Bombacaceae, Sterculiaceae, and Tiliaceae, are not well delineated. Several studies have reported the fatty acid compositions of Malvaceae plants but not for taxonomic purposes. In the present study, the fatty acid composition of oilseeds from seven species belonging to the Malvaceae family was determined by capillary gas chromatography/mass spectrometry (GC/MS), and the quantitative distribution of fatty acids was analyzed by a cluster analysis With Euclidean Distance and UPGMA. The oil content in the seeds was very low (8.3-11.8%). The profile of fatty acids showed that there were two distinct groups: species rich in palmitic acid (Herissantia tiubae, Sidastrum paniculatum and Sida rhombifolia) and species rich in linoleic acid (other Sida species). The fatty acid profiles found for Sida species are consistent with other reported data. Although our data support a distinction between Sida and Sidastrum, more species should be analyzed to evaluate the real taxonomic value of differences in fatty acid content for distinguishing Malvaceae. (C) 2010 Elsevier Ltd. All rights reserved.
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The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.
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An experimental overview of reactions induced by the stable, but weakly-bound nuclei (6)Li, (7)Li and (9)Be, and by the exotic, halo nuclei (6)He, (8)B, (11)Be and (17)F On medium-mass targets, such as (58)Ni, (59)Co or (64)Zn, is presented. Existing data on elastic scattering, total reaction cross sections, fusion, breakup and transfer channels are discussed in the framework of a CDCC approach taking into account the breakup degree of freedom.
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Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even when the actual population is finite. Two alternatives that incorporate the finite nature of the population are obtained from the superpopulation model proposed by Scott and Smith (1969. Estimation in multi-stage surveys. J. Amer. Statist. Assoc. 64, 830-840) or from the finite population mixed model recently proposed by Stanek and Singer (2004. Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 1119-1130). Predictors derived under the latter model with the additional assumptions that all variance components are known and that within-cluster variances are equal have smaller mean squared error (MSE) than the competitors based on either the ME or Scott and Smith`s models. As population variances are rarely known, we propose method of moment estimators to obtain empirical predictors and conduct a simulation study to evaluate their performance. The results suggest that the finite population mixed model empirical predictor is more stable than its competitors since, in terms of MSE, it is either the best or the second best and when second best, its performance lies within acceptable limits. When both cluster and unit intra-class correlation coefficients are very high (e.g., 0.95 or more), the performance of the empirical predictors derived under the three models is similar. (c) 2007 Elsevier B.V. All rights reserved.
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Herein, we report a new approach of an FePt nanoparticle formation mechanism studying the evolution of particle size and composition during the synthesis using the modified polyol process. One of the factors limiting their application in ultra-high-density magnetic storage media is the particle-to-particle composition, which affects the A1-to-L1(0) transformation as well as their magnetic properties. There are many controversies in the literature concerning the mechanism of the FePt formation, which seems to be the key to understanding the compositional chemical distribution. Our results convincingly show that, initially, Pt nuclei are formed due to reduction of Pt(acac)(2) by the diol, followed by heterocoagulation of Fe cluster species formed from Fe(acac)(3) thermal decomposition onto the Pt nuclei. Complete reduction of heterocoagulated iron species seems to involve a CO-spillover process, in which the Pt nuclei surface acts as a heterogeneous catalyst, leading to the improvement of the single-particle composition control and allowing a much narrower compositional distribution. Our results show significant decreases in the particle-to-particle composition range, improving the A1-to-L1(0) phase transformation and, consequently, the magnetic properties when compared with other reported methods.
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BACKGROUND: Facilitation of local women's groups may reportedly reduce neonatal mortality. It is not known whether facilitation of groups composed of local health care staff and politicians can improve perinatal outcomes. We hypothesised that facilitation of local stakeholder groups would reduce neonatal mortality (primary outcome) and improve maternal, delivery, and newborn care indicators (secondary outcomes) in Quang Ninh province, Vietnam. METHODS AND FINDINGS: In a cluster-randomized design 44 communes were allocated to intervention and 46 to control. Laywomen facilitated monthly meetings during 3 years in groups composed of health care staff and key persons in the communes. A problem-solving approach was employed. Births and neonatal deaths were monitored, and interviews were performed in households of neonatal deaths and of randomly selected surviving infants. A latent period before effect is expected in this type of intervention, but this timeframe was not pre-specified. Neonatal mortality rate (NMR) from July 2008 to June 2011 was 16.5/1,000 (195 deaths per 11,818 live births) in the intervention communes and 18.4/1,000 (194 per 10,559 live births) in control communes (adjusted odds ratio [OR] 0.96 [95% CI 0.73-1.25]). There was a significant downward time trend of NMR in intervention communes (p = 0.003) but not in control communes (p = 0.184). No significant difference in NMR was observed during the first two years (July 2008 to June 2010) while the third year (July 2010 to June 2011) had significantly lower NMR in intervention arm: adjusted OR 0.51 (95% CI 0.30-0.89). Women in intervention communes more frequently attended antenatal care (adjusted OR 2.27 [95% CI 1.07-4.8]). CONCLUSIONS: A randomized facilitation intervention with local stakeholder groups composed of primary care staff and local politicians working for three years with a perinatal problem-solving approach resulted in increased attendance to antenatal care and reduced neonatal mortality after a latent period. TRIAL REGISTRATION: Current Controlled Trials ISRCTN44599712. Please see later in the article for the Editors' Summary.
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Market risk exposure plays a key role for nancial institutions risk management. A possible measure for this exposure is to evaluate losses likely to incurwhen the price of the portfolio's assets declines using Value-at-Risk (VaR) estimates, one of the most prominent measure of nancial downside market risk. This paper suggests an evolving possibilistic fuzzy modeling approach for VaR estimation. The approach is based on an extension of the possibilistic fuzzy c-means clustering and functional fuzzy rule-based modeling, which employs memberships and typicalities to update clusters and creates new clusters based on a statistical control distance-based criteria. ePFM also uses an utility measure to evaluate the quality of the current cluster structure. Computational experiments consider data of the main global equity market indexes of United States, London, Germany, Spain and Brazil from January 2000 to December 2012 for VaR estimation using ePFM, traditional VaR benchmarks such as Historical Simulation, GARCH, EWMA, and Extreme Value Theory and state of the art evolving approaches. The results show that ePFM is a potential candidate for VaR modeling, with better performance than alternative approaches.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Complex cluster [TiO5 center dot V-O(z)] and [SrO11 center dot V-O(z)] (where V-O(z)=V-O(X), V-O(center dot), V-O(center dot center dot)) vacancies were identified in disordered SrTiO3 powders prepared by the polymeric precursor method, based on experimental measurements by x-ray absorption near edge structure spectroscopy. The paramagnetic complex states of [TiO5 center dot V-O(center dot)] and [SrO11 center dot V-O(center dot)] with unpaired electrons were confirmed by electron paramagnetic resonance spectroscopy. The disordered powders showed strong photoluminescence at room temperature. Structural defects of disordered powders, in terms of band diagram, density of states, and electronic charges, were interpreted using high-level quantum mechanical calculations in the density functional framework. The four periodic models used here were consistent with the experimental data and explained the presence of photoluminescence. (C) 2008 American Institute of Physics.
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A new approach based on a N-a cluster photoabsorption model is proposed for the understanding of the puzzling steady increase behavior of the 90Zr (e, α) yield measured at the National Bureau of Standards (NBS) within the Giant Dipole Resonance and quasideuteron energy range. The calculation takes into account the pre-equilibrium emissions of protons, neutrons and alpha particles in the framework of an extended version of the multicollisional intranuclear cascade model (MCMC). Another Monte Carlo based algorithm describes the statistical decay of the compound nucleus in terms of the competition between particle evaporation (p, n, d, α, 3He and t) and nuclear fission. The results reproduce quite successfully the 90Zr (e,α) yield, suggesting that emissions of a particles are essential for the interpretation of the exotic increase of the cross sections.