39 resultados para potassium derivative


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In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

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The thermal decomposition of the complex K-4[Ni(NO2)6]center dot H2O has been investigated over the temperature range 25-600 degrees C by a combination of infrared spectroscopy, powder X-ray diffraction, FAB-mass spectrometry and elemental analysis. The first stage of reaction is loss of water and isomerisation of one of the coordinated nitro groups to form the complex K-4 [Ni(NO2)(4) (ONO)]center dot NO2. At temperatures around 200 degrees C the remaining nitro groups within the complex isomerise to the chelating nitrite form and this process acts as a precursor to the loss of NO2 gas at temperatures above 270 degrees C. The product, which is stable up to 600 degrees C, is the complex K-4[Ni(ONO)(4)]center dot NO2, where the nickel atom is formally in the +1 oxidation state. (c) 2005 Elsevier B.V. All rights reserved.

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Two controlled microcosm experiments aimed at a critical re-assessment of the contributions of divergent arbuscular mycorrhizal (AM) fungi to plant mineral nutrition were established that specifically targeted Plantago lanceolata–Glomus intraradices (B.B/E) and –Gigaspora margarita (BEG 34) symbioses developed in a native, nutrient limited, coastal dune soil. Plant tissue nitrogen (N), phosphorus (P) and potassium (K) status as well as plant growth parameters and levels of mycorrhizal colonization were assessed at harvest. In addition to the general well-established mycorrhizal facilitation of P uptake, the study was able to demonstrate a G. intraradices-specific contribution to improved plant nitrogen and potassium nutrition. In the two respective experiments, G. intraradices-inoculated plants had 27.8% and 40.8% more total N and 55.8% and 23.3% more total K when compared to Gi. margarita inoculated counterparts. Dissimilar overall contribution of the two isolates to plant nutrition was identified in AM-genus specific differences in plant tissue N:P:K ratios. G. intraradices inoculated and non-mycorrhizal plants generally exhibited N:P:K ratios indicative of P limitation whereas for Gi.margarita mycorrhizal plants, corresponding ratios strongly implied either N or K limitation. The study provides further evidence highlighting AM functional biodiversity in respect to plant nutrient limitation experienced by mycorrhizal P. lanceolata in an ecologically relevant soil system.

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In order to build up a multicomponent system able to perform useful light-induced functions, a dithienylethene-bridged heterodinuclear metal complex (Ru/Os) has been prepared. The compound was characterized and its photophysical properties studied in detail.

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A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

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A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

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Ross divides prima facie duties into derivative and foundational ones, but seems to understand the notion of a derivative prima facie duty in two very different ways. Sometimes he understands them in a non-eliminativist way. According to this understanding, basic prima facie duties ground distinct derivative ones. According to the eliminativist understanding, basic duties do not ground distinct derivative duties, but replace (eliminate) them. On the eliminativist view, discovering that a prima facie duty is derivative is discovering that it is not genuine. The genuine one is the basic one. I argue that Ross is best understood as an eliminativist.

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The synthesis and characterisation of the complexes [η2-{2-H-1-(Me3SiC ≡ C)-C60}Co2(CO)6] (2)} and [η-2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2η-C5H5)2] (3)} is reported, together with a single-crystal molecular structure for (3). This provides the first structural data for an acyclic metal derivative of [60]-fullerene.

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For linear multivariable time-invariant continuous or discrete-time singular systems it is customary to use a proportional feedback control in order to achieve a desired closed loop behaviour. Derivative feedback is rarely considered. This paper examines how derivative feedback in descriptor systems can be used to alter the structure of the system pencil under various controllability conditions. It is shown that derivative and proportional feedback controls can be constructed such that the closed loop system has a given form and is also regular and has index at most 1. This property ensures the solvability of the resulting system of dynamic-algebraic equations. The construction procedures used to establish the theory are based only on orthogonal matrix decompositions and can therefore be implemented in a numerically stable way. The problem of pole placement with derivative feedback alone and in combination with proportional state feedback is also investigated. A computational algorithm for improving the “conditioning” of the regularized closed loop system is derived.

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Background: In rat middle cerebral and mesenteric arteries the KCa2.3 component of endothelium-dependent hyperpolarization (EDH) is lost following stimulation of thromboxane (TP) receptors, an effect that may contribute to the endothelial dysfunction associated with cardiovascular disease. In cerebral arteries, KCa2.3 loss is associated with NO synthase inhibition, but is restored if TP receptors are blocked. The Rho/Rho kinase pathway is central for TP signalling and statins indirectly inhibit this pathway. The possibility that Rho kinase inhibition and statins sustain KCa2.3 hyperpolarization was investigated in rat middle cerebral arteries (MCA). Methods: MCAs were mounted in a wire myograph. The PAR2 agonist, SLIGRL was used to stimulate EDH responses, assessed by simultaneous measurement of smooth muscle membrane potential and tension. TP expression was assessed with rt-PCR and immunofluorescence. Results: Immunofluorescence detected TP in the endothelial cell layer of MCA. Vasoconstriction to the TP agonist, U46619 was reduced by Rho kinase inhibition. TP receptor stimulation lead to loss of KCa2.3 mediated hyperpolarization, an effect that was reversed by Rho kinase inhibitors or simvastatin. KCa2.3 activity was lost in L-NAME-treated arteries, but was restored by Rho kinase inhibition or statin treatment. The restorative effect of simvastatin was blocked after incubation with geranylgeranyl-pyrophosphate to circumvent loss of isoprenylation. Conclusions: Rho/Rho kinase signalling following TP stimulation and L-NAME regulates endothelial cell KCa2.3 function. The ability of statins to prevent isoprenylation and perhaps inhibit of Rho restores/protects the input of KCa2.3 to EDH in the MCA, and represents a beneficial pleiotropic effect of statin treatment.

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The application of antibodies to living cells has the potential to modulate the function of specific proteins by virtue of their high specificity. This specificity has proven effective in determining the involvement of many proteins in neuronal function where specific agonists and antagonists do not exist, e.g. ion channel subunits. We discuss a way to utilise subunit specific antibodies to target individual channel subunits in electrophysiological experiments to determine functional roles within native neurones. Utilising this approach, we have investigated the role of the voltage-gated potassium channel Kv3.1b subunit within a region of the brainstem important in the regulation of autonomic function. We provide some useful control experiments in order to help validate this method. We conclude that antibodies can be extremely valuable in determining the functions of specific proteins in living neurones in neuroscience research.

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Voltage-gated potassium (Kv) channels are essential components of neuronal excitability. The Kv3.4 channel protein is widely distributed throughout the central nervous system (CNS), where it can form heteromeric or homomeric Kv3 channels. Electrophysiological studies reported here highlight a functional role for this channel protein within neurons of the dorsal vagal nucleus (DVN). Current clamp experiments revealed that blood depressing substance (BDS) and intracellular dialysis of an anti-Kv3.4 antibody prolonged the action potential duration. In addition, a BDS sensitive, voltage-dependent, slowly inactivating outward current was observed in voltage clamp recordings from DVN neurons. Electrical stimulation of the solitary tract evoked EPSPs and IPSPs in DVN neurons and BDS increased the average amplitude and decreased the paired pulse ratio, consistent with a presynaptic site of action. This presynaptic modulation was action potential dependent as revealed by ongoing synaptic activity. Given the role of the Kv3 proteins in shaping neuronal excitability, these data highlight a role for homomeric Kv3.4 channels in spike timing and neurotransmitter release in low frequency firing neurons of the DVN.