Regulation of tyrosine hydroxylase and aromatic L-amino acid decarboxylase by dopaminergic drugs

We provide evidence that dopamine receptors differentially modulate tyrosine hydroxylase and aromatic L-amino acid decarboxylase in the mouse striatum. The dopamine D1 receptor family (D1-like) antagonist, R(+)-7-chloro-8-hydroxy-3-methyl-1-phenyl-2,3,4,5-tetrahydro-1 H-3-benazepine (SCH 23390), elevated aromatic L-amino acid decarboxylase activity and protein content in striatum, as well as the mRNA for the enzyme in midbrain. The dopamine D1-like receptor agonist, (+/-)-1-phenyl-2,3,4,5-tetrahydro-(1 H)-3-benzazepine-7,8-diol (SKF 38393), had no effect on aromatic L-amino acid decarboxylase. The dopamine D1-like drugs had no effect on tyrosine hydroxylase. In contrast, the dopamine D2 receptor family (D2-like) antagonists haloperidol and spiperone elevated both tyrosine hydroxylase and aromatic L-amino acid decarboxylase activities. The increase in aromatic L-amino acid decarboxylase activity was accompanied by elevated enzyme protein content but not mRNA. The dopamine D2-like receptor agonists, bromocriptine, quinpirole and (+/-)-7-hydroxydipropylaminotetralin (7-OH-DPAT), all decreased striatal tyrosine hydroxylase. Under the conditions used, bromocriptine and 7-OH-DPAT, but not quinpirole, decreased aromatic L-amino acid decarboxylase activity of striatum. Both the dopamine D1- and D2-like receptor antagonists enhanced the turnover of striatal dopamine to differing degrees, as judged by the ratio of acid metabolites of dopamine to dopamine. Taken together our results indicate that aromatic L-amino acid decarboxylase can be modulated independently of tyrosine hydroxylase.     

Fault-accommodation with intelligent sensors

Optimal sensor fault-accommodation is considered for faults modelled by an increase in measurement noise. This noise is taken to be bounded and its probabilistic properties unknown. It is assumed that intelligent (e.g. self-validating) instrumentation is in use and estimates of the noise bounds are available. The fault-tolerant controller is designed to optimize a noise rejection and a nominal reference tracking index and leads to a mixed norm minimization problem (l₁/l₂). We exploit known results and a particular feedback configuration to show that it is possible to optimize simultaneously without a trade-off the two performance indices. The results are applied to systems where the presence of auxiliary measurements allows for an optimal fault-accommodation strategy. Using properties of the optimal solution, we define a factorization for the optimal controller alternative to the Youla parametrization, leading to an algorithm which is optimal, transparent and efficient.     

Tracking trajectories of the cart-pendulum system

The problem of tracking a periodic trajectory of the well-known cart-pendulum system is solved. After a change of coordinates and a change of feedback, the equations of this system are nonlinear but feedforward. This property is extensively used to carry out for this system the design of uniformly asymptotically stabilizing time-varying state feedbacks by using the forwarding approach.     

An efficient assumed strain element model with six DOF per node for geometrically non-linear shells

The present paper describes an assumed strain finite element model with six degrees of freedom per node designed for geometrically non-linear shell analysis. An important feature of the present paper is the discussion on the spurious kinematic modes and the assumed strain field in the geometrically non-linear setting. The kinematics of deformation is described by using vector components in contrast to the conventional formulation which requires the use of trigonometric functions of rotational angles. Accordingly, converged solutions can be obtained for load or displacement increments that are much larger than possible with the conventional formulation with rotational angles. In addition, a detailed study of the spurious kinematic modes and the choice of assumed strain field reveals that the same assumed strain field can be used for both geometrically linear and non-linear cases to alleviate element locking while maintaining kinematic stability. It is strongly recommended that the element models, described in the present paper, be used instead of the conventional shell element models that employ rotational angles.     

Proton and hydrogen formation by cyclohexyl benzene during overcharge of Li-ion batteries

This study provides experimental evidence for proton and hydrogen formation caused by the anodic electropolymerization of cyclohexyl benzene (CHB), which is a popular electrolyte additive for overcharge protection of lithium-ion batteries (LIBs). It is found that considerable H₂ evolution is observed in overcharged LiCoO₂/graphite cells, especially when CHB is included as an electrolyte additive. In order to confirm the proton generation during the CHB oxidation, Pt/Pt-rotating ring disc electrode (RRDE) measurements are performed in 1 M Li(C₂F₅SO₂)₂N ethylene carbonate/ethyl methyl carbonate (1/2, v/v) solutions with and without CHB. The cathodic ring current is intimately correlated to the anodic disc current, and the cathodic reaction at the ring is determined to be the reduction of the proton. The proton generation efficiency during the CHB oxidation is as high as 90%. Proton liberation is also observed during the anodic decomposition of the electrolyte solvents, although it occurs in a much less stoichiometric way compared with that during the CHB oxidation.     

A time aggregation approach to Markov decision processes

We propose a time aggregation approach for the solution of infinite horizon average cost Markov decision processes via policy iteration. In this approach, policy update is only carried out when the process visits a subset of the state space. As in state aggregation, this approach leads to a reduced state space, which may lead to a substantial reduction in computational and storage requirements, especially for problems with certain structural properties. However, in contrast to state aggregation, which generally results in an approximate model due to the loss of Markov property, time aggregation suffers no loss of accuracy, because the Markov property is preserved. Single sample path-based estimation algorithms are developed that allow the time aggregation approach to be implemented on-line for practical systems. Some numerical and simulation examples are presented to illustrate the ideas and potential computational savings.     

Algorithm for finding all k nearest neighbors

A very simple algorithm for computing all k nearest neighbors in 2-D is presented. The method does not rely on complicated forms of tessellation, it only requires simple data binning for fast range searching. Its applications range from scattered data interpolation to reverse engineering.