71 resultados para phase rule one component


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When analysing the secretome of the plant pathogen Pseudomonas syringae pv. tomato (Pst) DC3000, we identified hemolysin co-regulated protein (Hcp) as one of the secreted proteins. Hcp is assumed to be an extracellular component of the type VI secretion system (T6SS). Two copies of hcp genes are present in the Pst DC3000 genome, hcp1 (PSPTO_2539) and hcp2 (PSPTO_5435). We studied the expression patterns of hcp genes and tested the fitness of hcp knock-out mutants in host plant colonization and in inter-microbial competition. We found that the hcp2 gene is expressed, most actively at the stationary growth phase, and that the Hcp2 protein is secreted via T6SS and appears in the culture medium as covalently linked dimers. Expression of hcp2 is not induced in planta and it does not contribute to virulence or colonisation in tomato or Arabidopsis plants. Instead, hcp2 is required for survival in competition with enterobacteria and yeasts, and its function is associated with suppression of the growth of these competitors. This is the first report on bacterial T6SS-associated genes functioning in competition against yeast. Our results suggest that the T6SS of P. syringae may play an important role in bacterial fitness, allowing this plant pathogen to survive in conditions where it has to compete with other micro-organisms for resources.

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The Um Sohryngkew section of Meghalaya, NE India, located 800–1000 km from the Deccan volcanic province, is one of the most complete Cretaceous–Tertiary boundary (KTB) transitions worldwide with all defining and supporting criteria present: mass extinction of planktic foraminifera, first appearance of Danian species, δ13C shift, Ir anomaly (12 ppb) and KTB red layer. The geochemical signature of the KTB layer indicates not only an extraterrestrial signal (Ni and all Platinum Group Elements (PGEs)) of a second impact that postdates Chicxulub, but also a significant component resulting from condensed sedimentation (P), redox fluctuations (As, Co, Fe, Pb, Zn, and to a lesser extent Ni and Cu) and volcanism. From the late Maastrichtian C29r into the early Danian, a humid climate prevailed (kaolinite: 40–60%, detrital minerals: 50–80%). During the latest Maastrichtian, periodic acid rains (carbonate dissolution; CIA index: 70–80) associated with pulsed Deccan eruptions and strong continental weathering resulted in mesotrophic waters. The resulting super-stressed environmental conditions led to the demise of nearly all planktic foraminiferal species and blooms (> 95%) of the disaster opportunist Guembelitria cretacea. These data reveal that detrimental marine conditions prevailed surrounding the Deccan volcanic province during the main phase of eruptions in C29r below the KTB. Ultimately these environmental conditions led to regionally early extinctions followed by global extinctions at the KTB.

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Monoclonal antibodies specific for phase 1 ("i" antigen), phase 2 ("1,2" antigen) and common epitopes of the flagellins of Salmonella enterica serotype Typhimurium were raised. Having confirmed their specificity, the monoclonal antibodies were used to develop semi-quantitative ELISAs in order to assess the relative expression of the two phases by strains of Typhimurium. The majority of Typhimurium strains representative of a wide cross-section of definitive types from animal and environmental sources preferentially expressed phase 1 antigen in vitro. DT40 strains were unique in expressing phase 2 preferentially. The ratio of phase 1 to phase 2 expressed by strains tended to be constant for any one strain when strains were grown on a number of conventional laboratory media. However, the ratio of phases was shown to be modulated by incubation at 42 degreesC and buffering media at pH values, notably 4.5, other than neutral. Selenite broth and Rambach media repressed flagellation. Crown Copyright (C) 2001 Published by Elsevier Science B.V. All rights reserved.

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In a world where data is captured on a large scale the major challenge for data mining algorithms is to be able to scale up to large datasets. There are two main approaches to inducing classification rules, one is the divide and conquer approach, also known as the top down induction of decision trees; the other approach is called the separate and conquer approach. A considerable amount of work has been done on scaling up the divide and conquer approach. However, very little work has been conducted on scaling up the separate and conquer approach.In this work we describe a parallel framework that allows the parallelisation of a certain family of separate and conquer algorithms, the Prism family. Parallelisation helps the Prism family of algorithms to harvest additional computer resources in a network of computers in order to make the induction of classification rules scale better on large datasets. Our framework also incorporates a pre-pruning facility for parallel Prism algorithms.

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Induction of classification rules is one of the most important technologies in data mining. Most of the work in this field has concentrated on the Top Down Induction of Decision Trees (TDIDT) approach. However, alternative approaches have been developed such as the Prism algorithm for inducing modular rules. Prism often produces qualitatively better rules than TDIDT but suffers from higher computational requirements. We investigate approaches that have been developed to minimize the computational requirements of TDIDT, in order to find analogous approaches that could reduce the computational requirements of Prism.

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The fast increase in the size and number of databases demands data mining approaches that are scalable to large amounts of data. This has led to the exploration of parallel computing technologies in order to perform data mining tasks concurrently using several processors. Parallelization seems to be a natural and cost-effective way to scale up data mining technologies. One of the most important of these data mining technologies is the classification of newly recorded data. This paper surveys advances in parallelization in the field of classification rule induction.

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Advances in hardware and software in the past decade allow to capture, record and process fast data streams at a large scale. The research area of data stream mining has emerged as a consequence from these advances in order to cope with the real time analysis of potentially large and changing data streams. Examples of data streams include Google searches, credit card transactions, telemetric data and data of continuous chemical production processes. In some cases the data can be processed in batches by traditional data mining approaches. However, in some applications it is required to analyse the data in real time as soon as it is being captured. Such cases are for example if the data stream is infinite, fast changing, or simply too large in size to be stored. One of the most important data mining techniques on data streams is classification. This involves training the classifier on the data stream in real time and adapting it to concept drifts. Most data stream classifiers are based on decision trees. However, it is well known in the data mining community that there is no single optimal algorithm. An algorithm may work well on one or several datasets but badly on others. This paper introduces eRules, a new rule based adaptive classifier for data streams, based on an evolving set of Rules. eRules induces a set of rules that is constantly evaluated and adapted to changes in the data stream by adding new and removing old rules. It is different from the more popular decision tree based classifiers as it tends to leave data instances rather unclassified than forcing a classification that could be wrong. The ongoing development of eRules aims to improve its accuracy further through dynamic parameter setting which will also address the problem of changing feature domain values.

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Three new MnIII complexes, {[Mn-2(salen)(2)(OCn)](ClO4)}(n) (1), {[Mn-2(salen)(2)(OPh)](ClO4)}(n) (2) and {[Mn-2(salen)(2)(OBz)](ClO4)}(2) (3) (where salen = N,N'-bis(salicylidene)-1,2-diaminoethane dianion, OCn = cinnamate, OPh = phenylacetate and OBz = benzoate), have been synthesized and characterized structurally and magnetically. The crystal structures reveal that all three structures contain syn-anti carboxylatebridged dimeric [Mn-2(salen)(2)(OOCR)](+) cations (OOCR = bridging carboxylate) that are joined together by weak Mn center dot center dot center dot O(phenoxo) interactions to form infinite alternating chain structures in 1 and 2, but the relatively long Mn center dot center dot center dot O(phenoxo) distance [3.621(2)angstrom] in 3 restricts this structure to tetranuclear units. Magnetic studies showed that 1 and 2 exhibited magnetic long-range order at T-N = 4.0 and 4.6 K (T-N = Neel transition temperature), respectively, to give spin-canted antiferromagnetic structures. Antiferromagnetic coupling was also observed in 3 but no peaks were recorded in the field-cooled magnetization (FCM) or zero-field-cooled magnetization (ZFCM) data, indicating that 3 remained paramagnetic down to 2 K. This dominant antiferromagnetic coupling is attributed to the carboxylate bridges. The ferromagnetic coupling expected due to the Mn-O(phenoxo)center dot center dot center dot Mn bridge plays an auxiliary role in the magnetic chain, but is an essential component of the bulk magnetic properties of the material.

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The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2005 and 2007. These minima have not been predicted in the IPCC AR4 report, suggesting that the sea ice component of climate models should more realistically represent the processes controlling the sea ice mass balance. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds accumulate on the surface of sea ice from snow and sea ice melt and their presence reduces the albedo of the ice cover, leading to further melt. Toward the end of the melt season, melt ponds cover up to 50% of the sea ice surface. We have developed a melt pond evolution theory. Here, we have incorporated this melt pond theory into the Los Alamos CICE sea ice model, which has required us to include the refreezing of melt ponds. We present results showing that the presence, or otherwise, of a representation of melt ponds has a significant effect on the predicted sea ice thickness and extent. We also present a sensitivity study to uncertainty in the sea ice permeability, number of thickness categories in the model representation, meltwater redistribution scheme, and pond albedo. We conclude with a recommendation that our melt pond scheme is included in sea ice models, and the number of thickness categories should be increased and concentrated at lower thicknesses.

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In terms of evolution, the strategy of catching prey would have been an important part of survival in a constantly changing environment. A prediction mechanism would have developed to compensate for any delay in the sensory-motor system. In a previous study, “proactive control” was found, in which the motion of the hands preceded the virtual moving target. These results implied that the positive phase shift of the hand motion represents the proactive nature of the visual-motor control system, which attempts to minimize the brief error in the hand motion when the target changes position unexpectedly. In our study, a visual target moves in circle (13 cm diameter) on a computer screen, and each subject is asked to keep track of the target’s motion by the motion of a cursor. As the frequency of the target increases, a rhythmic component was found in the velocity of the cursor in spite of the fact that the velocity of the target was constant. The generation of a rhythmic component cannot be explained simply as a feedback mechanism for the phase shifts of the target and cursor in a sensory-motor system. Therefore, it implies that the rhythmic component was generated to predict the velocity of the target, which is a feed-forward mechanism in the sensory-motor system. Here, we discuss the generation of the rhythmic component and its roll in the feed-forward mechanism.

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Stakeholder analysis plays a critical role in business analysis. However, the majority of the stakeholder identification and analysis methods focus on the activities and processes and ignore the artefacts being processed by human beings. By focusing on the outputs of the organisation, an artefact-centric view helps create a network of artefacts, and a component-based structure of the organisation and its supply chain participants. Since the relationship is based on the components, i.e. after the stakeholders are identified, the interdependency between stakeholders and the focal organisation can be measured. Each stakeholder is associated with two types of dependency, namely the stakeholder’s dependency on the focal organisation and the focal organisation’s dependency on the stakeholder. We identify three factors for each type of dependency and propose the equations that calculate the dependency indexes. Once both types of the dependency indexes are calculated, each stakeholder can be placed and categorised into one of the four groups, namely critical stakeholder, mutual benefits stakeholder, replaceable stakeholder, and easy care stakeholder. The mutual dependency grid and the dependency gap analysis, which further investigates the priority of each stakeholder by calculating the weighted dependency gap between the focal organisation and the stakeholder, subsequently help the focal organisation to better understand its stakeholders and manage its stakeholder relationships.

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Time-resolved kinetic studies of silylene, SiH2, generated by laser flash photolysis of 1-silacyclopent-3-ene and phenylsilane, have been carried out to obtain rate constants for its bimolecular reactions with methanol, ethanol, 1-propanol, 1-butanol and 2-methyl-1-butanol. The reactions were studied in the gas phase over the pressure range 1-100 Torr in SF6 bath gas, at room temperature. In the study with methanol several buffer gases were used. All five reactions showed pressure dependences characteristic of third body assisted association reactions. The rate constant pressure dependences were modelled using RRKM theory, based on Eo values of the association complexes obtained by ab initio calculation (G3 level). Transition state models were adjusted to fit experimental fall-off curves and extrapolated to obtain k∞ values in the range 1.9 to 4.5 × 10-10 cm3 molecule-1 s-1. These numbers, corresponding to the true bimolecular rate constants, indicate efficiencies of between 16 and 67% of the collision rates for these reactions. In the reaction of SiH2 + MeOH there is a small kinetic component to the rate which is second order in MeOH (at low total pressures). This suggests an additional catalysed reaction pathway, which is supported by the ab initio calculations. These calculations have been used to define specific MeOH-for-H2O substitution effects on this catalytic pathway. Where possible our experimental and theoretical results are compared with those of previous studies.

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The structures of 2-hydroxybenzamide(C7H7NO2) and 2-methoxybenzamide (C8H9NO2) have been determined in the gas-phase by electron diffraction using results from quantum chemical calculations to inform restraints used on the structural parameters. Theoretical methods (HF and MP2/6-311+G(d,p)) predict four stable conformers for both 2-hydroxybenzamide and 2-methoxybenzamide. For both compounds, evidence for intramolecular hydrogen bonding is presented. In 2-hydroxybenzamide, the observed hydrogen bonded fragment is between the hydroxyl and carbonyl groups, while in 2-methoxybenzamide, the hydrogen bonded fragment is between one of the hydrogen atoms of the amide group and the methoxy oxygen atom.

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Using a discrete wavelet transform with a Meyer wavelet basis, we present a new quantitative algorithm for determining the onset time of Pi1 and Pi2 ULF waves in the nightside ionosphere with ∼20- to 40-s resolution at substorm expansion phase onset. We validate the algorithm by comparing both the ULF wave onset time and location to the optical onset determined by the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE)–Far Ultraviolet Imager (FUV) instrument. In each of the six events analyzed, five substorm onsets and one pseudobreakup, the ULF onset is observed prior to the global optical onset observed by IMAGE at a station closely conjugate to the optical onset. The observed ULF onset times expand both latitudinally and longitudinally away from an epicenter of ULF wave power in the ionosphere. We further discuss the utility of the algorithm for diagnosing pseudobreakups and the relationship of the ULF onset epicenter to the meridians of elements of the substorm current wedge. The importance of the technique for establishing the causal sequence of events at substorm onset, especially in support of the multisatellite Time History of Events and Macroscale Interactions During Substorms (THEMIS) mission, is also described.

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The concept of slow vortical dynamics and its role in theoretical understanding is central to geophysical fluid dynamics. It leads, for example, to “potential vorticity thinking” (Hoskins et al. 1985). Mathematically, one imagines an invariant manifold within the phase space of solutions, called the slow manifold (Leith 1980; Lorenz 1980), to which the dynamics are constrained. Whether this slow manifold truly exists has been a major subject of inquiry over the past 20 years. It has become clear that an exact slow manifold is an exceptional case, restricted to steady or perhaps temporally periodic flows (Warn 1997). Thus the concept of a “fuzzy slow manifold” (Warn and Ménard 1986) has been suggested. The idea is that nearly slow dynamics will occur in a stochastic layer about the putative slow manifold. The natural question then is, how thick is this layer? In a recent paper, Ford et al. (2000) argue that Lighthill emission—the spontaneous emission of freely propagating acoustic waves by unsteady vortical flows—is applicable to the problem of balance, with the Mach number Ma replaced by the Froude number F, and that it is a fundamental mechanism for this fuzziness. They consider the rotating shallow-water equations and find emission of inertia–gravity waves at O(F2). This is rather surprising at first sight, because several studies of balanced dynamics with the rotating shallow-water equations have gone beyond second order in F, and found only an exponentially small unbalanced component (Warn and Ménard 1986; Lorenz and Krishnamurthy 1987; Bokhove and Shepherd 1996; Wirosoetisno and Shepherd 2000). We have no technical objection to the analysis of Ford et al. (2000), but wish to point out that it depends crucially on R 1, where R is the Rossby number. This condition requires the ratio of the characteristic length scale of the flow L to the Rossby deformation radius LR to go to zero in the limit F → 0. This is the low Froude number scaling of Charney (1963), which, while originally designed for the Tropics, has been argued to be also relevant to mesoscale dynamics (Riley et al. 1981). If L/LR is fixed, however, then F → 0 implies R → 0, which is the standard quasigeostrophic scaling of Charney (1948; see, e.g., Pedlosky 1987). In this limit there is reason to expect the fuzziness of the slow manifold to be “exponentially thin,” and balance to be much more accurate than is consistent with (algebraic) Lighthill emission.