Semiquantum versus semiclassical mechanics for simple nonlinear systems

Quantum mechanics has been formulated in phase space, with the Wigner function as the representative of the quantum density operator, and classical mechanics has been formulated in Hilbert space, with the Groenewold operator as the representative of the classical Liouville density function. Semiclassical approximations to the quantum evolution of the Wigner function have been defined, enabling the quantum evolution to be approached from a classical starting point. Now analogous semiquantum approximations to the classical evolution of the Groenewold operator are defined, enabling the classical evolution to be approached from a quantum starting point. Simple nonlinear systems with one degree of freedom are considered, whose Hamiltonians are polynomials in the Hamiltonian of the simple harmonic oscillator. The behavior of expectation values of simple observables and of eigenvalues of the Groenewold operator are calculated numerically and compared for the various semiclassical and semiquantum approximations.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Satellite observation and climate system model simulation of the St. Lawrence Island polynya

The St. Lawrence Island polynya (SLIP) is a commonly occurring winter phenomenon in the Bering Sea, in which dense saline water produced during new ice formation is thought to flow northward through the Bering Strait to help maintain the Arctic Ocean halocline. Winter darkness and inclement weather conditions have made continuous in situ and remote observation of this polynya difficult. However, imagery acquired from the European Space Agency ERS-1 Synthetic Aperture Radar (SAR) has allowed observation of the St. Lawrence Island polynya using both the imagery and derived ice displacement products. With the development of ARCSyM, a high resolution regional model of the Arctic atmosphere/sea ice system, simulation of the SLIP in a climate model is now possible. Intercomparisons between remotely sensed products and simulations can lead to additional insight into the SLIP formation process. Low resolution SAR, SSM/I and AVHRR infrared imagery for the St. Lawrence Island region are compared with the results of a model simulation for the period of 24-27 February 1992. The imagery illustrates a polynya event (polynya opening). With the northerly winds strong and consistent over several days, the coupled model captures the SLIP event with moderate accuracy. However, the introduction of a stability dependent atmosphere-ice drag coefficient, which allows feedbacks between atmospheric stability, open water, and air-ice drag, produces a more accurate simulation of the SLIP in comparison to satellite imagery. Model experiments show that the polynya event is forced primarily by changes in atmospheric circulation followed by persistent favorable conditions: ocean surface currents are found to have a small but positive impact on the simulation which is enhanced when wind forcing is weak or variable.

Role of galectin-1 in the olfactory nervous system

The olfactory nervous system is responsible for the detection of odors. Primary sensory olfactory neurons are located in a neuroepithelial sheet lining the nasal cavity. The axons from these neurons converge on to discrete loci or glomeruli in the olfactory bulb. Each glomerulus consists of the termination of thousands of primary axons on the dendrites of second-order olfactory neurons. What are the molecular mechanisms which guide growing olfactory axons to select sites in the olfactory bulb? We have shown that subpopulations of these axons differentially express cell surface carbohydrates and that these different subpopulations target and terminate in particular regions of the olfactory bulb. Interestingly, the olfactory neurons and glial components in the olfactory pathway between the nose and brain express galectin-1. By using in vitro assays of neurite outgrowth we found that both galectin-1 and it's ligands were capable of specifically stimulating neurite elongation. Examination of the olfactory system in galectin-1 null mutants revealed that a subpopulation of axons failed to navigate to their target site in the olfactory bulb. This is the first phenotypic effect observed in galectin-1 null mutants and indicates that galectin-1 has a role in the growth and/or guidance of a subpopulation of axons in the olfactory system during development.

Plasminogen activator system in osteoclasts

To determine which genes of the plasminogen activator (PA) system were expressed in osteoclasts, RNA extracted from microisolated mouse osteoclasts was used as template for reverse transcribed polymerase chain reaction (RT-PCR) with gene-specific primer pairs, Using this approach, the expression of RNAs for tissue-type plasminogen activator, urokinase-type plasminogen activator, plasminogen activator inhibitor-1, plasminogen activator inhibitor-2, protease nexin, and urokinase receptor isoform 1 (uPAR1) were detected in mouse osteoclasts. The expression of uPAR RNA in osteoclasts was confirmed by in situ hybridization with a uPAR1 probe, RNA encoding the uPAR isoform 2 was not detected in mouse osteoclasts, but a novel unspliced uPAR RNA variant was detected in these cells, The novel uPAR variant and uPAR1 RNA were also detected in mouse calvarial osteoblasts, kidney, muscle, and the mouse macrophage cell line J774A.1 by RT-PCR The presence of RNAs for most of the components of the PA system in osteoclasts suggests that it may have a functional role in this cell type.

Presence of novel N-CAM glycoforms in the rat olfactory system

The functional activity of the neural cell adhesion molecule N-CAM can be modulated by posttranslational modifications such as glycosylation. For instance, the long polysialic acid side chains of N-CAM alter the adhesion properties of the protein backbone. In the present study, we identified two novel carbohydrates present on N-CAM, NOC-3 and NOC-4. Both carbohydrates were detected on N-CAM glycoforms expressed by subpopulations of primary sensory olfactory neurons in the rat olfactory system. Based on the expression of NOC-3 and NOC-4 and the olfactory marker protein (OMP), four independent subpopulations of primary sensory olfactory neurons were characterized. These neurons expressed: both NOC-3 and NOC-4 but not OMP; both NOC-4 and OMP but not NOC-3; NOC-3, NOC-4, and OMP together; and OMP alone. The NOC-3- and NOC-4-expressing neurons were widely dispersed in the olfactory neuroepithelium lining the nasal cavity. The axons of NOC-4 expressing neurons innervated all glomeruli in the olfactory bulb, whereas the NOC-3 expressing axons terminated in a discrete subset of glomeruli scattered throughout the whole olfactory bulb. We propose that both NOC-3 and NOC-4 are part of a chemical code of olfactory neurons which is used in establishing the topography of connections between the olfactory neuroepithelium and the olfactory bulb. (C) 1997 John Wiley & Sons, Inc.

The formal representation of process system modelling assumptions and their implications

In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and methods for checking them are described. It is shown on a simple example how different modelling assumptions act on the model equations and their effect on the differential index of the resulted model is also indicated.

Egr transcription factors in the nervous system

The Egr proteins, Egr-1, Egr-2, Egr-3 and Egr-4, are closely related members of a subclass of immediate early gene-encoded, inducible transcription factors. They share a highly homologous DNA-binding domain which recognises an identical DNA response element. In addition, they have several less-well conserved structural features in common. As immediate early proteins, the Egr transcription factors are rapidly induced by diverse extracellular stimuli within the nervous system in a discretely controlled manner. The basal expression of the Egr proteins in the developing and adult rat brain and the induction of Egr proteins by neurotransmitter analogue stimulation, physiological mimetic and brain injury paradigms is reviewed. We review evidence indicating that Egr proteins are subject to tight differential control through diverse mechanisms at several levels of regulation. These include transcriptional, translational and posttranslational (including glycosylation, phosphorylation and redox) mechanisms and protein-protein interaction. Ultimately the differentially co-ordinated Egr response may lead to discrete effects on target gene expression. Some of the known target genes of Egr proteins and functions of the Egr proteins in different cell types are also highlighted. Future directions for research into the control and function of the different Egr proteins are also explored. (C) 1997 Elsevier Science Ltd.

Quantum signatures of chaos in the dynamics of a trapped ion

We show how a nonlinear chaotic system, the parametrically kicked nonlinear oscillator, may be realized in the dynamics of a trapped, laser-cooled ion, interacting with a sequence of standing-wave pulses. Unlike the original optical scheme [G. J. Milburn and C.A. Holmes, Phys. Rev. A 44, 4704 (1991)], the trapped ion enables strongly quantum dynamics with minimal dissipation. This should permit an experimental test of one of the quantum signatures of chaos: irregular collapse and revival dynamics of the average vibrational energy.