Architecture for Living Neuronal Network Control of a mobile robot

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot – thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animat) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This paper details the components of the overall animat closed loop system architecture and reports on the evaluation of the results from preliminary real-life and simulated robot experiments.

Development of novel brush-type chiral stationary phases based on terpenoid selectors: HPLC evaluation and theoretical investigation of enantioselective binding interactions

The terpenoid chiral selectors dehydroabietic acid, 12,14-dinitrodehydroabietic acid and friedelin have been covalently linked to silica gel yielding three chiral stationary phases CSP 1, CSP 2 and CSP 3, respectively. The enantiodiscriminating capability of each one of these phases was evaluated by HPLC with four families of chiral aromatic compounds composed of alcohols, amines, phenylalanine and tryptophan amino acid derivatives and beta-lactams. The CSP 3 phase, containing a selector with a large friedelane backbone is particularly suitable for resolving free alcohols and their derivatives bearing fluorine substituents, while CSP 2 with a dehydroabietic architecture is the only phase that efficiently discriminates 1, 1'-binaphthol atropisomers. CSP 3 also gives efficient resolution of the free amines. All three phases resolve well the racemates of N-trifluoracetyl and N-3,5-dinitrobenzoyl phenylalanine amino acid ester derivatives. Good enantioseparation of beta-lactams and N-benzoyl tryptophan amino acid derivatives was achieved on CSP 1. In order to understand the structural factors that govern the chiral molecular recognition ability of these phases, molecular dynamics simulations were carried out in the gas phase with binary diastereomeric complexes formed by the selectors of CSP 1 and CSP 2 and several amino acid derivatives. Decomposition of molecular mechanics energies shows that van der Waals interactions dominate the formation of the diastereomeric transient complexes while the electrostatic binding interactions are primarily responsible for the enantioselective binding of the (R)- and (S)-analytes. Analysis of the hydrogen bonds shows that electrostatic interactions are mainly associated with the formation of N-(HO)-O-...=C enantio selective hydrogen bonds between the amide binding sites from the selectors and the carbonyl groups of the analytes. The role of mobile phase polarity, a mixture of n-hexane and propan-2-ol in different ratios, was also evaluated through molecular dynamics simulations in explicit solvent. (c) 2006 Elsevier Ltd. All rights reserved.

Architecture for neuronal cell control of a mobile robot

It is usually expected that the intelligent controlling mechanism of a robot is a computer system. Research is however now ongoing in which biological neural networks are being cultured and trained to act as the brain of an interactive real world robot - thereby either completely replacing or operating in a cooperative fashion with a computer system. Studying such neural systems can give a distinct insight into biological neural structures and therefore such research has immediate medical implications. In particular, the use of rodent primary dissociated cultured neuronal networks for the control of mobile `animals' (artificial animals, a contraction of animal and materials) is a novel approach to discovering the computational capabilities of networks of biological neurones. A dissociated culture of this nature requires appropriate embodiment in some form, to enable appropriate development in a controlled environment within which appropriate stimuli may be received via sensory data but ultimate influence over motor actions retained. The principal aims of the present research are to assess the computational and learning capacity of dissociated cultured neuronal networks with a view to advancing network level processing of artificial neural networks. This will be approached by the creation of an artificial hybrid system (animal) involving closed loop control of a mobile robot by a dissociated culture of rat neurons. This 'closed loop' interaction with the environment through both sensing and effecting will enable investigation of its learning capacity This paper details the components of the overall animat closed loop system and reports on the evaluation of the results from the experiments being carried out with regard to robot behaviour.

A parallel quantum histogram architecture

A parallel formulation of an algorithm for the histogram computation of n data items using an on-the-fly data decomposition and a novel quantum-like representation (QR) is developed. The QR transformation separates multiple data read operations from multiple bin update operations thereby making it easier to bind data items into their corresponding histogram bins. Under this model the steps required to compute the histogram is n/s + t steps, where s is a speedup factor and t is associated with pipeline latency. Here, we show that an overall speedup factor, s, is available for up to an eightfold acceleration. Our evaluation also shows that each one of these cells requires less area/time complexity compared to similar proposals found in the literature.