935 resultados para SYMPATHETIC COMPONENT
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This quantitative pilot study (n = 178), conducted in a large Brisbane teaching hospital in Australia, found autonomy to be the most important job component for registered nurses' job satisfaction. The actual level of satisfaction with autonomy was 4.6, on a scale of 1 for very dissatisfied to 7 for very satisfied. The mean for job satisfaction was 4.3, with the job components professional status and interaction adding most substantially to the result. There was discontentment with the other two job components, which were Cask requirements and organisational policies. Demographic comparisons showed that nurses who were preceptors had significantly less job satisfaction than the other nurses at the hospital. (C) 2001 Elsevier Science Ltd. All rights reserved.
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1 Previous studies have demonstrated that chronic pre-synaptic inhibition of transmitter release by morphine evokes a counter-adaptive response in the sympathetic nerve terminals that manifests itself as an increase in transmitter release during acute withdrawal. In the present study we examined the possibility that other pre-synaptically acting drugs such as clonidine also evoke a counter-adaptive response in the sympathetic nerve terminals. 2 In chronically saline treated (CST) preparations, clonidine (0.5 muM) completely abolished evoked transmitter release from sympathetic varicosities bathed in an extracellular calcium concentration ([Ca2+](o)) of 2 mM. The inhibitory effect of clonidine was reduced by increasing [Ca2+](o) from 2 to 4 mM and the stimulation frequency from 0.1 to 1 Hz. 3 The nerve terminal impulse (NTI) was not affected by concentrations of clonidine that completely abolished evoked transmitter release. 4 Sympathetic varicosities developed a tolerance to clonidine (0.5 muM) following 7-9 days of chronic exposure to clonidine. 5 Acute withdrawal of preparations following chronic clonidine treatment (CCT) resulted in a significant (P
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1 The effect of chronic morphine treatment (CMT) on sympathetic innervation of the mouse vas deferens and on alpha (2)-adrenoceptor mediated autoinhibition has been examined using intracellular recording of excitatory junction potentials (EJPs) and histochemistry. 2 In chronically saline treated (CST) preparations. morphine (1 muM) and the alpha (2)-adrenoceptor agonist (clonidine, 1 muM) decreased the mean amplitude of EJPs evoked with 0.03 Hz stimulation by 81+/-8% (n=16) and 92+/-6% (n=7) respectively. In CMT preparations, morphine (1 muM) and clonidine (1 muM) decreased mean EJP amplitude by 68+/-8% (n = 7) and 79+/-8% (n = 7) respectively. 3 When stimulating the sympathetic axons at 0.03 Hz. the mean EJP amplitude recorded from smooth muscles acutely withdrawn from CMT was four times greater than for CST smooth muscles (40.7+/-3.8 mV, n = 7 compared with 9.9+/-0.3 mV, n = 7). 4 Part of the increase in mean EJP amplitude following CMT was produced by a 31% increase in the density of sympathetic axons and varicosities innervating the smooth muscle. 5 Results from the present study indicate that the effectiveness of alpha (2)-adrenocrptor mediated autoinhibition is only slightly reduced in CMT preparations. Most of the cross tolerance which develops between morphine, clonidine and alpha (2)-adrenoceptor mediated autoinhibition occurs as a consequence of increased efficacy of neuromuscular transmission which is produced by an increase in the probability of transmitter release and an increase in the density of sympathetic innervation.
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We consider a two-component Bose-Einstein condensate in two spatially localized modes of a double-well potential, with periodic modulation of the tunnel coupling between the two modes. We treat the driven quantum field using a two-mode expansion and define the quantum dynamics in terms of the Floquet Operator for the time periodic Hamiltonian of the system. It has been shown that the corresponding semiclassical mean-field dynamics can exhibit regions of regular and chaotic motion. We show here that the quantum dynamics can exhibit dynamical tunneling between regions of regular motion, centered on fixed points (resonances) of the semiclassical dynamics.
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Although the sympathetic nervous system (SNS) plays a major role in mediating the peripheral stress response, due consideration is not usually given to the effects of prolonged stress on the SNS. The present study examined changes in neurotransmission in the SNS after exposure of mice (BALB/c) to stressful housing conditions. Focal extracellular recording of excitatory junction currents (EJCs) was used as a relative measure of neurotransmitter release from different regions of large surface areas of the mouse vas deferens. Mice were either group housed (control), isolation housed (social deprivation), group housed in a room containing rats (rat odor stress), or isolation housed in a room containing rats (concurrent stress). Social deprivation and concurrent stressors induced an increase of 30 and 335% in EJC amplitude, respectively. The success rate of recording EJCs from sets of varicosities in the concurrent stressor group was greater compared with all other groups. The present study has shown that some common animal housing conditions act as stressors and induce significant changes in sympathetic neurotransmission.
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This paper reports on the development of specific slicing techniques for functional programs and their use for the identification of possible coherent components from monolithic code. An associated tool is also introduced. This piece of research is part of a broader project on program understanding and re-engineering of legacy code supported by formal methods
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Over the last decade component-based software development arose as a promising paradigm to deal with the ever increasing complexity in software design, evolution and reuse. SHACC is a prototyping tool for component-based systems in which components are modelled coinductively as generalized Mealy machines. The prototype is built as a HASKELL library endowed with a graphical user interface developed in Swing
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The lack of a commonly accepted de nition of a software component, the proliferation of competing `standards' and component frameworks, is here to stay, raising the fundamental question in component-based development of how to cope in practice with heterogeneity. This paper reports on the design of a Component Repository aimed to give at least a partial answer to the above question. The repository was fully speci ed in Vdm and a working prototype is currently being used in an industrial environment
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It is known the power of ideas is tremendous. But there are employees in many companies who have good ideas but not put them into practice. On the other hand, there are many others who have good ideas and are encouraged to contribute their ideas for innovation in the company. This study attempts to identify factors that contribute to success in managing ideas and consequent business innovation. The method used was the case study applied to two companies. During the investigation, factors considered essential for the success of an idea management program were identified, of which we highlight, among others, evidences the results, involvement of the top management, establishment of goals and objectives; recognition; dissemination of good results. Companies with these implemented systems, capture the best ideas from their collaborators and apply them internally. This study intends to contribute to business innovation in enterprises through creation and idea management, mainly through collecting the best ideas of their own employees. The results of this study can be used to help improving deployed suggestions systems, as well as, all managers who wish to implement suggestions systems/ideas management systems.
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Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.
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Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.
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Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings
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Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings
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Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.