Copper(II) complexes of mono-anionic glutamate: anionic influence in the variations of molecular and supramolecular structures

Three new polynuclear copper(II) complexes of singly deprotonated L-glutamic acid (L-glu), {[Cu(bipy)(2)][Cu(bipy)(L-glu)H2O](2)(BF4)(4)center dot(H2O)(3)}(n) (1), {[Cu(bipy)(L-glu)H2O][Cu(bipy)(L-glu)(ClO4)]( ClO4)center dot(H2O)(2)}(n) ((2)) and [Cu(phen)(L-glu)H2O](2)(NO3)(2)center dot(H2O)(4) (3) (bipy = 2,2-bipyridine, phen = 1,10-phenanthroline), were synthesized in acidic pH (ca. 2.5) and characterized structurally. In all the complexes, L-glutamic acid acts as a bidentate chelating ligand, leaving the protonated carboxylic acid free. Both in 1 and 2, two different types of species [Cu(bipy)(2)](BF4)(2) and [Cu(bipy)(L-glu)H2O] BF4 for 1 and [Cu(bipy)(L-glu)H2O]ClO4 and [Cu(bipy)(L-glu)(ClO4)] for 2 coexist in the solid state. In complex 1, the [C( bipy)(L-glu)H2O]+ units are joined together by syn-anti carboxylate bridges to form an enantiopure (M) helical chain and the [Cu(bipy)(2)](2+) presents a very rare example of the four-coordinate distorted tetrahedral geometry of Cu(II). In complex 2, the [Cu(bipy)(L gluClO(4))] units are joined together by weakly coordinating perchlorate ions to form a 1D polymeric chain while the [Cu(bipy)(L-glu)H2O]+ units remain as mononuclear species. The different coordinating ability of the two counter anions along with their involvement in the H-bonding network seems likely to be responsible for the difference in the final polymeric structures in the two compounds. Variable-temperature (2-300 K) magnetic susceptibility measurements show negligible coupling for both the complexes. The structure of 3 consists of two independent monomeric [Cu(phen)(L-glu)H2O]+ cations, two nitrate anions and four water molecules. The copper atom occupies a five-coordinate square pyramidal environment with a water molecule in the axial position.

The role of visual and nonvisual information in the control of locomotion

During locomotion, retinal flow, gaze angle, and vestibular information can contribute to one's perception of self-motion. Their respective roles were investigated during active steering: Retinal flow and gaze angle were biased by altering the visual information during computer-simulated locomotion, and vestibular information was controlled through use of a motorized chair that rotated the participant around his or her vertical axis. Chair rotation was made appropriate for the steering response of the participant or made inappropriate by rotating a proportion of the veridical amount. Large steering errors resulted from selective manipulation of retinal flow and gaze angle, and the pattern of errors provided strong evidence for an additive model of combination. Vestibular information had little or no effect on steering performance, suggesting that vestibular signals are not integrated with visual information for the control of steering at these speeds.

The psychological, neurochemical and functional neuroanatomical mediators of the effects of positive and negative mood on executive functions

In this review we evaluate the cognitive and neural effects of positive and negative mood on executive function. Mild manipulations of negative mood appear to have little effect on cognitive control processes, whereas positive mood impairs aspects of updating, planning and switching. These cognitive effects may be linked to neurochemistry: with positive mood effects mediated by dopamine while negative mood effects may be mediated by serotonin levels. Current evidence on the effects of mood on regional brain activity during executive functions, indicates that the prefrontal cortex is a recurrent site of integration between mood and cognition. We conclude that there is a disparity between the importance of this topic and awareness of how mood affects, executive functions in the brain. Most behavioural and neuroimaging studies of executive function in normal samples do not explore the potential role of variations in mood, yet the evidence we outline indicates that even mild fluctuations in mood can have a significant influence on neural activation and cognition. (c) 2006 Elsevier Ltd. All rights reserved.

Processing of faces and emotional expressions in infants at risk of social phobia

Individuals with social phobia display social information processing biases yet their aetiological significance is unclear. Infants of mothers with social phobia and control infants' responses were assessed at 10 days, 10 and 16 weeks, and 10 months to faces versus non-faces, variations in intensity of emotional expressions, and gaze direction. Infant temperament and maternal behaviours were also assessed. Both groups showed a preference for faces over non-faces at 10 days and 10 weeks, and full faces over profiles at 16 weeks; they also looked more to high vs. low intensity angry faces at 10 weeks, and fearful faces at 10 months; however, index infants' initial orientation and overall looking to high-intensity fear faces was relatively less than controls at 10 weeks. This was not explained by infant temperament or maternal behaviours. The findings suggest that offspring of mothers with social phobia show processing biases to emotional expressions in infancy.

Reach & grasp therapy: Design and control of a 9-DOF robotic neuro-rehabilitation system

This paper presents the Gentle/G integrated system for reach & grasp therapy retraining following brain injury. The design, control and integration of an experimental grasp assistance unit is described for use in robot assisted stroke rehabilitation. The grasp assist unit is intended to work with the hardware and software of the Gentle/S robot although the hardware could be adapted to other rehabilitation applications. When used with the Gentle/S robot a total of 6 active and 3 passive degrees of freedom are available to provide active, active assist or passive grasp retraining in combination with reaching movements in a reach-grasp-transfer-release sequence.

Theory of mind and attentional bias to facial emotional expressions: A preliminary study

Theory of mind ability has been associated with performance in interpersonal interactions and has been found to influence aspects such as emotion recognition, social competence, and social anxiety. Being able to attribute mental states to others requires attention to subtle communication cues such as facial emotional expressions. Decoding and interpreting emotions expressed by the face, especially those with negative valence, are essential skills to successful social interaction. The current study explored the association between theory of mind skills and attentional bias to facial emotional expressions. According to the study hypothesis, individuals with poor theory of mind skills showed preferential attention to negative faces over both non-negative faces and neutral objects. Tentative explanations for the findings are offered emphasizing the potential adaptive role of vigilance for threat as a way of allocating a limited capacity to interpret others’ mental states to obtain as much information as possible about potential danger in the social environment.

A hyperstable neural network for the modelling and control of nonlinear systems

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.

Dynamic recurrent neural network for system identification and control

A dynamic recurrent neural network (DRNN) that can be viewed as a generalisation of the Hopfield neural network is proposed to identify and control a class of control affine systems. In this approach, the identified network is used in the context of the differential geometric control to synthesise a state feedback that cancels the nonlinear terms of the plant yielding a linear plant which can then be controlled using a standard PID controller.

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.

Autonomous ship collision free trajectory navigation and control algorithms

A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.

Application of a novel optimal control algorithm to a benchmark fed-batch fermentation process

A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimisation and Parameter Estimation (DISOPE) which has been designed to achieve the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A method based on Broyden's ideas is used for approximating some derivative trajectories required. Ways for handling con straints on both manipulated and state variables are described. Further, a method for coping with batch-to- batch dynamic variations in the process, which are common in practice, is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch processes. The algorithm is success fully applied to a benchmark problem consisting of the input profile optimisation of a fed-batch fermentation process.