56 resultados para Isomorphic classification of C(K, X) spaces
Resumo:
The complexes [Ru(1-C=C-1,10-C2B8H9)(dppe)Cp*] (3a), [Ru(1-C C-1,12-C2B10H11)(dppe)-Cp*] (3b), [{Ru(dppe)Cp*}(2){mu-1,10-(C C)(2)-1,10-C2B8H8}] (4a) and [{Ru(dppe)Cp*}(2){mu-1,12-(C C)2- 1,12-C2B10-H-10}] (4b), which form a representative series of mono- and bimetallic acetylide complexes featuring 10- and 12-vertex carboranes embedded within the dethynyl bridging ligand, have been prepared and structurally characterized. In addition, these compounds have been examined spectroscopically (UV-is-NIR, IR) in all accessible redox states. The significant separation of the two, one-electron anodic waves observed in the cyclic voltammograms of the bimetallic complexes 4a and 4b is largely independent of the nature of the electrolyte and is attributed to stabilization of the intermediate redox products [4a](+) and [4b](+) through interactions between the metal centers across a distance of ca. 12.5 angstrom. The mono-oxidized bimetallic complexes (4a](+) and [4b](+) exhibit spectroscopic properties consistent with a description of these species in terms of valence-localized (class II) mixed-valence compounds, including a unique low-energy electronic absorption band, attributed to an, IVCT-type transition that tails into the IR region. DFT calculations with model systems [4a-H](+) and [4b-H](+) featuring simplified ligand sets reproduce the observed spectroscopic data and localized electronic structures for the mixed-valence cations [4a](+) and [4b](+).
Resumo:
The co-adsorption of CO and O on the unreconstructed (1 x 1) phase of Ir {100} was examined by low energy electron diffraction (LEED) and temperature programmed desorption (TPD). When CO is adsorbed at 188 K onto the Ir{100} surface precovered with 0.5 ML O, a mixed c(4 x 2)-(2O + CO) overlayer is formed. All CO is oxidised upon heating and desorbs as CO2 in three distinct stages at 230 K, 330 K and 430 K in a 2:1:2 ratio. The excess oxygen left on the surface after all CO has reacted forms an overlayer with a LEED pattern with p(2 x 10) periodicity. This overlayer consists of stripes with a local p(2 x 1)-O arrangement of oxygen atoms separated by stripes of uncovered It. When CO is adsorbed at 300 K onto the surface precovered with 0.5 ML O an apparent (2 x 2) LEED pattern is observed. LEED IV analysis reveals that this pattern is a superposition of diffraction patterns from islands of c(2 x 2)-CO and p(2 x 1)-O structures on the surface. Heating this co-adsorbed overlayer leads to the desorption of CO, in two stages at 330 K and 430 K; the excess CO (0.1 ML) desorbs at 590 K. LEED IV structural analysis of the mixed c(4 x 2) O and CO overlayer shows that both the CO molecules and the O atoms occupy bridge sites. The O atoms show significant lateral displacements of 0.14 angstrom away from the CO molecules; the C-O bond is slightly expanded with respect to the gas phase (1.19 angstrom); the modifications of the Ir substrate with respect to the bulk-terminated surface are very small. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
Asymmetric hydrogenation of C=C bonds is of the highest importance in organic synthesis, and such reactions are currently carried out with organometallic homogeneous catalysts. Achieving heterogeneous metal-catalyzed hydrogenation, a highly desirable goal, necessitates forcing the crucial enantiodifferentiating step to take place at the metal surface. By synthesis and application of six chiral sulfide ligands that anchor robustly to Pd nanoparticles and resist displacement, we have for the first time accomplished heterogeneous enantioselective catalytic hydrogenation of isophorone. High resolution XPS data established that ligand adsorption from solution occurred exclusively on the Pd nanoparticles and not on the carbon support. All ligands contained a pyrrolidine nitrogen to enable their interaction with the isophorone substrate while the sulfide functionality provided the required interaction with the Pd surface. Enantioselective turnover numbers of up to similar to 100 product molecules per ligand molecule were found with a very large variation in asymmetric induction between ligands: observed enantiomeric excesses increased with increasing size of the alkyl group in the sulfide. This likely reflects varying degrees of ligand dispersion on the surface: bulky substituent groups hinder close approach of ligand molecules to each other, inhibiting close-packed island formation, favoring dispersion as separate molecules, and leading to effective asymmetric induction. Conversely, small substituents favor island formation leading to very low asymmetric induction. Enantioselective reaction most likely involves initial formation of an enamine or iminium species, confirmed by use of an analogous tertiary amine, which leads to racemic product. Ligand rigidity and resistance to self-assembled monolayer formation are important attributes that should be designed into improved chiral modifiers.
Resumo:
In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aperture (SAR) imagery data under the Multiplicative Model. The observed data, therefore, is assumed to obey a G(A)(0) (alpha; gamma, n) law, where the parameter n is related to the speckle noise, and (alpha, gamma) are related to the ground truth, giving information about the background. Therefore, maps generated by the estimation of (alpha, gamma) in each coordinate can be used as the input for classification methods. Maximum likelihood estimators are derived and used to form estimated parameter maps. This estimation can be hampered by the presence of corner reflectors, man-made objects used to calibrate SAR images that produce large return values. In order to alleviate this contamination, robust (M) estimators are also derived for the universal model. Gaussian Maximum Likelihood classification is used to obtain maps using hard-to-deal-with simulated data, and the superiority of robust estimation is quantitatively assessed.
Resumo:
Mannitol is a polymorphic pharmaceutical excipient, which commonly exists in three forms: alpha, beta and delta. Each polymorph has a needle-like morphology, which can give preferred orientation effects when analysed by X-ray powder diffractometry (XRPD) thus providing difficulties for quantitative XRPD assessments. The occurrence of preferred orientation may be demonstrated by sample rotation and the consequent effects on X-ray data can be minimised by reducing the particle size. Using two particle size ranges (less than 125 and 125–500�microns), binary mixtures of beta and delta mannitol were prepared and the delta component was quantified. Samples were assayed in either a static or rotating sampling accessory. Rotation and reducing the particle size range to less than�125 microns halved the limits of detection and quantitation to 1 and 3.6%, respectively. Numerous potential sources of assay errors were investigated; sample packing and mixing errors contributed the greatest source of variation. However, the rotation of samples for both particle size ranges reduced the majority of assay errors examined. This study shows that coupling sample rotation with a particle size reduction minimises preferred orientation effects on assay accuracy, allowing discrimination of two very similar polymorphs at around the 1% level
Resumo:
This paper reviews the ways that quality can be assessed in standing waters, a subject that has hitherto attracted little attention but which is now a legal requirement in Europe. It describes a scheme for the assessment and monitoring of water and ecological quality in standing waters greater than about I ha in area in England & Wales although it is generally relevant to North-west Europe. Thirteen hydrological, chemical and biological variables are used to characterise the standing water body in any current sampling. These are lake volume, maximum depth, onductivity, Secchi disc transparency, pH, total alkalinity, calcium ion concentration, total N concentration,winter total oxidised inorganic nitrogen (effectively nitrate) concentration, total P concentration, potential maximum chlorophyll a concentration, a score based on the nature of the submerged and emergent plant community, and the presence or absence of a fish community. Inter alia these variables are key indicators of the state of eutrophication, acidification, salinisation and infilling of a water body.
Resumo:
Background: Since their inception, Twitter and related microblogging systems have provided a rich source of information for researchers and have attracted interest in their affordances and use. Since 2009 PubMed has included 123 journal articles on medicine and Twitter, but no overview exists as to how the field uses Twitter in research. // Objective: This paper aims to identify published work relating to Twitter indexed by PubMed, and then to classify it. This classification will provide a framework in which future researchers will be able to position their work, and to provide an understanding of the current reach of research using Twitter in medical disciplines. Limiting the study to papers indexed by PubMed ensures the work provides a reproducible benchmark. // Methods: Papers, indexed by PubMed, on Twitter and related topics were identified and reviewed. The papers were then qualitatively classified based on the paper’s title and abstract to determine their focus. The work that was Twitter focused was studied in detail to determine what data, if any, it was based on, and from this a categorization of the data set size used in the studies was developed. Using open coded content analysis additional important categories were also identified, relating to the primary methodology, domain and aspect. // Results: As of 2012, PubMed comprises more than 21 million citations from biomedical literature, and from these a corpus of 134 potentially Twitter related papers were identified, eleven of which were subsequently found not to be relevant. There were no papers prior to 2009 relating to microblogging, a term first used in 2006. Of the remaining 123 papers which mentioned Twitter, thirty were focussed on Twitter (the others referring to it tangentially). The early Twitter focussed papers introduced the topic and highlighted the potential, not carrying out any form of data analysis. The majority of published papers used analytic techniques to sort through thousands, if not millions, of individual tweets, often depending on automated tools to do so. Our analysis demonstrates that researchers are starting to use knowledge discovery methods and data mining techniques to understand vast quantities of tweets: the study of Twitter is becoming quantitative research. // Conclusions: This work is to the best of our knowledge the first overview study of medical related research based on Twitter and related microblogging. We have used five dimensions to categorise published medical related research on Twitter. This classification provides a framework within which researchers studying development and use of Twitter within medical related research, and those undertaking comparative studies of research relating to Twitter in the area of medicine and beyond, can position and ground their work.
Resumo:
The bewildering complexity of cortical microcircuits at the single cell level gives rise to surprisingly robust emergent activity patterns at the level of laminar and columnar local field potentials (LFPs) in response to targeted local stimuli. Here we report the results of our multivariate data-analytic approach based on simultaneous multi-site recordings using micro-electrode-array chips for investigation of the microcircuitary of rat somatosensory (barrel) cortex. We find high repeatability of stimulus-induced responses, and typical spatial distributions of LFP responses to stimuli in supragranular, granular, and infragranular layers, where the last form a particularly distinct class. Population spikes appear to travel with about 33 cm/s from granular to infragranular layers. Responses within barrel related columns have different profiles than those in neighbouring columns to the left or interchangeably to the right. Variations between slices occur, but can be minimized by strictly obeying controlled experimental protocols. Cluster analysis on normalized recordings indicates specific spatial distributions of time series reflecting the location of sources and sinks independent of the stimulus layer. Although the precise correspondences between single cell activity and LFPs are still far from clear, a sophisticated neuroinformatics approach in combination with multi-site LFP recordings in the standardized slice preparation is suitable for comparing normal conditions to genetically or pharmacologically altered situations based on real cortical microcircuitry.
Resumo:
Information was collated on the seed storage behaviour of 67 tree species native to the Amazon rainforest of Brazil; 38 appeared to show orthodox, 23 recalcitrant and six intermediate seed storage behaviour. A double-criteria key based on thousand-seed weight and seed moisture content at shedding to estimate likely seed storage behaviour, developed previously, showed good agreement with the above classifications. The key can aid seed storage behaviour identification considerably.
Resumo:
We present an analysis of a cusp ion step, observed by the Defense Meteorological Satellite Program (DMSP) F10 spacecraft, between two poleward moving events of enhanced ionospheric electron temperature, observed by the European Incoherent Scatter (EISCAT) radar. From the ions detected by the satellite, the variation of the reconnection rate is computed for assumed distances along the open-closed field line separatrix from the satellite to the X line, do. Comparison with the onset times of the associated ionospheric events allows this distance to be estimated, but with an uncertainty due to the determination of the low-energy cutoff of the ion velocity distribution function, ƒ(ν). Nevertheless, the reconnection site is shown to be on the dayside magnetopause, consistent with the reconnection model of the cusp during southward interplanetary magnetic field (IMF). Analysis of the time series of distribution function at constant energies, ƒ(ts), shows that the best estimate of the distance do is 14.5±2 RE. This is consistent with various magnetopause observations of the signatures of reconnection for southward IMF. The ion precipitation is used to reconstruct the field-parallel part of the Cowley D ion distribution function injected into the open low-latitude boundary layer in the vicinity of the X line. From this reconstruction, the field-aligned component of the magnetosheath flow is found to be only −55±65 km s−1 near the X line, which means either that the reconnection X line is near the stagnation region at the nose of the magnetosphere, or that it is closely aligned with the magnetosheath flow streamline which is orthogonal to the magnetosheath field, or both. In addition, the sheath Alfvén speed at the X line is found to be 220±45 km s−1, and the speed with which newly opened field lines are ejected from the X line is 165±30 km s−1. We show that the inferred magnetic field, plasma density, and temperature of the sheath near the X line are consistent with a near-subsolar reconnection site and confirm that the magnetosheath field makes a large angle (>58°) with the X line.
Resumo:
This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.
Resumo:
Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting bloom occurrence in lakes and rivers. In this paper existing key models of cyanobacteria are reviewed, evaluated and classified. Two major groups emerge: deterministic mathematical and artificial neural network models. Mathematical models can be further subcategorized into those models concerned with impounded water bodies and those concerned with rivers. Most existing models focus on a single aspect such as the growth of transport mechanisms, but there are a few models which couple both.