39 resultados para Transferable Potentials


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Recent reports show that biogeochemical processes continue when the soil is frozen, but are limited by water availability. However, there is little knowledge about the interactive effects of soil and environmental variables on amounts of unfrozen water in frozen soils. The aims of this study were to determine the contributions of matric and osmotic potentials to the unfrozen water content of frozen soil. We determined the effects of matric and osmotic potential on unfrozen water contents of frozen mineral soil fractions (ranging from coarse sand to fine silt) at -7 degrees C, and estimated the contributions of these potentials to liquid water contents in samples from organic surface layers of boreal soils frozen at -4 degrees C. In the mineral soil fractions the unfrozen water contents appeared to be governed solely by the osmotic potential, but in the humus layers of the sampled boreal soils both the osmotic and matric potentials control unfrozen water content, with osmotic potential contributing 20 to 69% of the total water potential. We also determined pore size equivalents, where unfrozen water resides at -4 degrees C, and found a strong correlation between these equivalents and microbial CO2 production. The larger the pores in which the unfrozen water is found the larger the microbial activity that can be sustained. The osmotic potential may therefore be a key determinant of unfrozen water and carbon dynamics in frozen soil. (C) 2008 Elsevier B.V. All rights reserved.

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Analytical potential energy functions which are valid at all dissociation limits have been derived for the ground states of SO2 and O3. The procedure involves minimizing the errors between the observed vibrational spectra and spectra calculated by a variational procedure. Good agreement is obtained between the observed and calculated spectra for both molecules. Comparisons are made between anharmonic force fields, previously determined from the spectral data, and the force fields obtained by differentiating the derived analytical functions at the equilibrium configurations.

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Analytical potential energy functions are reported for HOX (X=F, Cl, Br, I). The surface for HOF predicts two metastable minima as well as the equilibrium configuration. These correspond to HFO (bent) and OHF (linear). Ab initio calculations performed for the HOF surface confirm these predictions. Comparisons are drawn between the two sets of results, and a vibrational analysis is undertaken for the hydrogen bonded OHF species. For HOCl, one further minimum is predicted, corresponding to HClO (bent), the parameters for which compare favourably with those reported from ab initio studies. In contrast, only the equilibrium configurations are predicted to be stable for HOBr and HOI.

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Orthogonal internal coordinates are defined which have useful properties for constructing the potential energy functions of triatomic molecules with two or three minima on the surface. The coordinates are used to obtain ground state potentials of ClOO and HOF, both of which have three minima.

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Ab initio calculations of the energy have been made at approximately 150 points on the two lowest singlet A' potential energy surfaces of the water molecule, 1A' and 1A', covering structures having D∞h, C∞v, C2v and Cs symmetries. The object was to obtain an ab initio surface of uniform accuracy over the whole three-dimensional coordinate space. Molecular orbitals were constructed from a double zeta plus Rydberg basis, and correlation was introduced by single and double excitations from multiconfiguration states which gave the correct dissociation behaviour. A two-valued analytical potential function has been constructed to fit these ab initio energy calculations. The adiabatic energies are given in our analytical function as the eigenvalues of a 2 2 matrix, whose diagonal elements define two diabatic surfaces. The off-diagonal element goes to zero for those configurations corresponding to surface intersections, so that our adiabatic surface exhibits the correct Σ/II conical intersections for linear configurations, and singlet/triplet intersections of the O + H2 dissociation fragments. The agreement between our analytical surface and experiment has been improved by using empirical diatomic potential curves in place of those derived from ab initio calculations.

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The atmospheric chemistry of several gases used in industrial applications, C4F9OC2H5 (HFE-7200), C4F9OCH3 (HFE-7100), C3F7OCH3 (HFE-7000) and C3F7CH2OH, has been studied. The discharge flow technique coupled with mass-spectrometric detection has been used to study the kinetics of their reactions with OH radicals as a function of temperature. The infrared spectra of the compounds have also been measured. The following Arrhenius expressions for the reactions were determined (in units of cm3 molecule-1 s-1): k(OH + HFE-7200) = (6.9+2.3-1.7) × 10-11 exp(-(2030 ± 190)/T); k(OH + HFE-7100) = (2.8+3.2-1.5) × 10-11 exp(-(2200 ± 490)/T); k(OH + HFE-7000) = (2.0+1.2-0.7) × 10-11 exp(-(2130 ± 290)/T); and k(OH + C3F7CH2OH) = (1.4+0.3-0.2) × 10-11 exp(-(1460 ± 120)/T). From the infrared spectra, radiative forcing efficiencies were determined and compared with earlier estimates in the literature. These were combined with the kinetic data to estimate 100-year time horizon global warming potentials relative to CO2 of 69, 337, 499 and 36 for HFE-7200, HFE-7100, HFE-7000 and CF3CF2CF2CH2OH, respectively.

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Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexical-semantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system's phase space.

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We investigated whether it is possible to control the temporal window of attention used to rapidly integrate visual information. To study the underlying neural mechanisms, we recorded ERPs in an attentional blink task, known to elicit Lag-1 sparing. Lag-1 sparing fosters joint integration of the two targets, evidenced by increased order errors. Short versus long integration windows were induced by showing participants mostly fast or slow stimuli. Participants expecting slow speed used a longer integration window, increasing joint integration. Difference waves showed an early (200 ms post-T2) negative and a late positive modulation (390 ms) in the fast group, but not in the slow group. The modulations suggest the creation of a separate event for T2, which is not needed in the slow group, where targets were often jointly integrated. This suggests that attention can be guided by global expectations of presentation speed within tens of milliseconds.

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The study of motor unit action potential (MUAP) activity from electrornyographic signals is an important stage on neurological investigations that aim to understand the state of the neuromuscular system. In this context, the identification and clustering of MUAPs that exhibit common characteristics, and the assessment of which data features are most relevant for the definition of such cluster structure are central issues. In this paper, we propose the application of an unsupervised Feature Relevance Determination (FRD) method to the analysis of experimental MUAPs obtained from healthy human subjects. In contrast to approaches that require the knowledge of a priori information from the data, this FRD method is embedded on a constrained mixture model, known as Generative Topographic Mapping, which simultaneously performs clustering and visualization of MUAPs. The experimental results of the analysis of a data set consisting of MUAPs measured from the surface of the First Dorsal Interosseous, a hand muscle, indicate that the MUAP features corresponding to the hyperpolarization period in the physisiological process of generation of muscle fibre action potentials are consistently estimated as the most relevant and, therefore, as those that should be paid preferential attention for the interpretation of the MUAP groupings.

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The identification and visualization of clusters formed by motor unit action potentials (MUAPs) is an essential step in investigations seeking to explain the control of the neuromuscular system. This work introduces the generative topographic mapping (GTM), a novel machine learning tool, for clustering of MUAPs, and also it extends the GTM technique to provide a way of visualizing MUAPs. The performance of GTM was compared to that of three other clustering methods: the self-organizing map (SOM), a Gaussian mixture model (GMM), and the neural-gas network (NGN). The results, based on the study of experimental MUAPs, showed that the rate of success of both GTM and SOM outperformed that of GMM and NGN, and also that GTM may in practice be used as a principled alternative to the SOM in the study of MUAPs. A visualization tool, which we called GTM grid, was devised for visualization of MUAPs lying in a high-dimensional space. The visualization provided by the GTM grid was compared to that obtained from principal component analysis (PCA). (c) 2005 Elsevier Ireland Ltd. All rights reserved.