Neural Dynamics Underlying Impaired Autonomic and Conditioned Responses Following Amygdala and Orbitofrontal Lesions

A neural model is presented that explains how outcome-specific learning modulates affect, decision-making and Pavlovian conditioned approach responses. The model addresses how brain regions responsible for affective learning and habit learning interact, and answers a central question: What are the relative contributions of the amygdala and orbitofrontal cortex to emotion and behavior? In the model, the amygdala calculates outcome value while the orbitofrontal cortex influences attention and conditioned responding by assigning value information to stimuli. Model simulations replicate autonomic, electrophysiological, and behavioral data associated with three tasks commonly used to assay these phenomena: Food consumption, Pavlovian conditioning, and visual discrimination. Interactions of the basal ganglia and amygdala with sensory and orbitofrontal cortices enable the model to replicate the complex pattern of spared and impaired behavioral and emotional capacities seen following lesions of the amygdala and orbitofrontal cortex.

A Neural Network of Adaptively Timed Reinforcement Learning and Hippocampal Dynamics

A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal cells, and NMDA receptors. This circuit forms part of a model neural system for the coordinated control of recognition learning, reinforcement learning, and motor learning, whose properties clarify how an animal can learn to acquire a delayed reward. Behavioral and neural data are summarized in support of each processing stage of the system. The relevant anatomical sites are in thalamus, neocortex, hippocampus, hypothalamus, amygdala, and cerebellum. Cerebellar influences on motor learning are distinguished from hippocampal influences on adaptive timing of reinforcement learning. The model simulates how damage to the hippocampal formation disrupts adaptive timing, eliminates attentional blocking, and causes symptoms of medial temporal amnesia. It suggests how normal acquisition of subcortical emotional conditioning can occur after cortical ablation, even though extinction of emotional conditioning is retarded by cortical ablation. The model simulates how increasing the duration of an unconditioned stimulus increases the amplitude of emotional conditioning, but does not change adaptive timing; and how an increase in the intensity of a conditioned stimulus "speeds up the clock", but an increase in the intensity of an unconditioned stimulus does not. Computer simulations of the model fit parametric conditioning data, including a Weber law property and an inverted U property. Both primary and secondary adaptively timed conditioning are simulated, as are data concerning conditioning using multiple interstimulus intervals (ISIs), gradually or abruptly changing ISis, partial reinforcement, and multiple stimuli that lead to time-averaging of responses. Neurobiologically testable predictions are made to facilitate further tests of the model.

Steady flow dynamics during granular impact.

We study experimentally and computationally the dynamics of granular flow during impacts where intruders strike a collection of disks from above. In the regime where granular force dynamics are much more rapid than the intruder motion, we find that the particle flow near the intruder is proportional to the instantaneous intruder speed; it is essentially constant when normalized by that speed. The granular flow is nearly divergence free and remains in balance with the intruder, despite the latter's rapid deceleration. Simulations indicate that this observation is insensitive to grain properties, which can be explained by the separation of time scales between intergrain force dynamics and intruder dynamics. Assuming there is a comparable separation of time scales, we expect that our results are applicable to a broad class of dynamic or transient granular flows. Our results suggest that descriptions of static-in-time granular flows might be extended or modified to describe these dynamic flows. Additionally, we find that accurate grain-grain interactions are not necessary to correctly capture the granular flow in this regime.

Modelling the nano-scale phenomena in condensed matter physics via computer-based numerical simulations

A review of the atomistic modelling of the behaviour of nano-scale structures and processes via molecular dynamics (MD) simulation method of a canonical ensemble is presented. Three areas of application in condensed matter physics are considered. We focus on the adhesive and indentation properties of the solid surfaces in nano-contacts, the nucleation and growth of nano-phase metallic and semi-conducting atomic and molecular films on supporting substrates, and the nano- and multi-scale crack propagation properties of metallic lattices. A set of simulations selected from these fields are discussed, together with a brief introduction to the methodology of the MD simulation. The pertinent inter-atomic potentials that model the energetics of the metallic and semi-conducting systems are also given.

A non-Newtonian computational fluid dynamics study of the stencil printing process

This paper describes the application of computational fluid dynamics (CFD) to simulate the macroscopic bulk motion of solder paste ahead of a moving squeegee blade in the stencil printing process during the manufacture of electronic components. The successful outcome of the stencil printing process is dependent on the interaction of numerous process parameters. A better understanding of these parameters is required to determine their relation to print quality and improve guidelines for process optimization. Various modelling techniques have arisen to analyse the flow behaviour of solder paste, including macroscopic studies of the whole mass of paste as well as microstructural analyses of the motion of individual solder particles suspended in the carrier fluid. This work builds on the knowledge gained to date from earlier analytical models and CFD investigations by considering the important non-Newtonian rheological properties of solder pastes which have been neglected in previous macroscopic studies. Pressure and velocity distributions are obtained from both Newtonian and non-Newtonian CFD simulations and evaluated against each other as well as existing established analytical models. Significant differences between the results are observed, which demonstrate the importance of modelling non-Newtonian properties for realistic representation of the flow behaviour of solder paste.

Modeling the dynamics of electromagnetically agitated metallurgical flows: levitation, cold crucible, aluminium electrolysis, etc.

We present practical modelling techniques for electromagnetically agitated liquid metal flows involving dynamic change of the fluid volume and shape during melting and the free surface oscillation. Typically the electromagnetic field is strongly coupled to the free surface dynamics and the heat-mass transfer. Accurate pseudo-spectral code and the k-omega turbulence model modified for complex and transitional flows with free surfaces are used for these simulations. The considered examples include magnetic suspension melting, induction scull remelting (cold crucible), levitation and aluminium electrolysis cells. The process control and the energy savings issues are analysed.

Low Reynolds number turbulence models for accurate thermal simulations of electronic components

The electronics industry and the problems associated with the cooling of microelectronic equipment are developing rapidly. Thermal engineers now find it necessary to consider the complex area of equipment cooling at some level. This continually growing industry also faces heightened pressure from consumers to provide electronic product miniaturization, which in itself increases the demand for accurate thermal management predictions to assure product reliability. Computational fluid dynamics (CFD) is considered a powerful and almost essential tool for the design, development and optimization of engineering applications. CFD is now widely used within the electronics packaging design community to thermally characterize the performance of both the electronic component and system environment. This paper discusses CFD results for a large variety of investigated turbulence models. Comparison against experimental data illustrates the predictive accuracy of currently used models and highlights the growing demand for greater mathematical modelling accuracy with regards to thermal characterization. Also a newly formulated low Reynolds number (i.e. transitional) turbulence model is proposed with emphasis on hybrid techniques.

Mathematical modelling of the behaviour of granular material in a computational fluid dynamics framework using micro-mechanical models

In this paper, a Computational Fluid Dynamics framework is presented for the modelling of key processes which involve granular material (i.e. segregation, degradation, caking). Appropriate physical models and sophisticated algorithms have been developed for the correct representation of the different material components in a granular mixture. The various processes, which arise from the micromechanical properties of the different mixture species can be obtained and parametrised in a DEM / experimental framework, thus enabling the continuum theory to correctly account for the micromechanical properties of a granular system. The present study establishes the link between the micromechanics and continuum theory and demonstrates the model capabilities in simulations of processes which are of great importance to the process engineering industry and involve granular materials in complex geometries.

Seasonal plankton dynamics along a cross-shelf gradient off northern Spain

The development of population models able to reproduce the dynamics of zooplankton is a central issue when trying to understand how a changing environment would affect zooplankton in the future. Using 10 years of monthly data on phytoplankton and zooplankton abundance in the Bay of Biscay from the IEO's RADIALES time-series programme, we built non-parametric Generalized Additive Models (GAMs) able to reproduce the dynamics of plankton on the basis of environmental factors (nutrients, temperature, upwelling and photoperiod). We found that the interaction between these two plankton components is approximately linear, whereas the effects of environmental factors are non-linear. With the inclusion of the environmental variability, the main seasonal and inter-annual dynamic patterns observed within the studied plankton assemblage indicate the prevalence of bottom-up regulatory control. The statistically deduced models were used to simulate the dynamics of the phytoplankton and zooplankton. A good agreement between observations and simulations was obtained, especially for zooplankton. We are presently developing spatio-temporal GAM models for the North Sea based on the Continuous Plankton Recorder database.

ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels

The ERSEM model is one of the most established ecosystem models for the lower trophic levels of the marine food-web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North-Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic part of the marine ecosystem, including the microbial food-web, the carbonate system and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case-studies of mesocosm type simulations, water column implementations and a brief example of a full-scale application for the North-West European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

Role of zooplankton dynamics for Southern Ocean phytoplankton biomass and global biogeochemical cycles

Global ocean biogeochemistry models currently employed in climate change projections use highly simplified representations of pelagic food webs. These food webs do not necessarily include critical pathways by which ecosystems interact with ocean biogeochemistry and climate. Here we present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types (PFTs); six types of phytoplankton, three types of zooplankton, and heterotrophic bacteria. We improved the representation of zooplankton dynamics in our model through (a) the explicit inclusion of large, slow-growing zooplankton, and (b) the introduction of trophic cascades among the three zooplankton types. We use the model to quantitatively assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean High Nutrient Low Chlorophyll (HNLC) region during summer. When model simulations do not represent crustacean macrozooplankton grazing, they systematically overestimate Southern Ocean chlorophyll biomass during the summer, even when there was no iron deposition from dust. When model simulations included the developments of the zooplankton component, the simulation of phytoplankton biomass improved and the high chlorophyll summer bias in the Southern Ocean HNLC region largely disappeared. Our model results suggest that the observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community rather than iron limitation. This result has implications for the representation of global biogeochemical cycles in models as zooplankton faecal pellets sink rapidly and partly control the carbon export to the intermediate and deep ocean.

ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels

The European Regional Seas Ecosystem Model (ERSEM) is one of the most established ecosystem models for the lower trophic levels of the marine food web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic parts of the marine ecosystem, including the microbial food web, the carbonate system, and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case studies of mesocosm-type simulations, water column implementations, and a brief example of a full-scale application for the north-western European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

Free energy and molecular dynamics calculations for the cubic-tetragonal phase transition in zirconia

The high-temperature cubic-tetragonal phase transition of pure stoichiometric zirconia is studied by molecular dynamics (MD) simulations and within the framework of the Landau theory of phase transformations. The interatomic forces are calculated using an empirical, self-consistent, orthogonal tight-binding model, which includes atomic polarizabilities up to the quadrupolar level. A first set of standard MD calculations shows that, on increasing temperature, one particular vibrational frequency softens. The temperature evolution of the free-energy surfaces around the phase transition is then studied with a second set of calculations. These combine the thermodynamic integration technique with constrained MD simulations. The results seem to support the thesis of a second-order phase transition but with unusual, very anharmonic behavior above the transition temperature.

Surface alloying and mixing at the Mn/Fe(001) interface: Real-time photoelectron spectroscopy and modified embedded atom simulations

Structural and magnetic properties of thin Mn films on the Fe(001) surface have been investigated by a combination of photoelectron spectroscopy and computer simulation in the temperature range 300 Kless than or equal toTless than or equal to750 K. Room-temperature as deposited Mn overlayers are found to be ferromagnetic up to 2.5-monolayer (ML) coverage, with a magnetic moment parallel to that of the iron substrate. The Mn atomic moment decreases with increasing coverage, and thicker samples (4-ML and 4.5-ML coverage) are antiferromagnetic. Photoemission measurements performed while the system temperature is rising at constant rate (dT/dtsimilar to0.5 K/s) detect the first signs of Mn-Fe interdiffusion at T=450 K, and reveal a broad temperature range (610 Kless than or equal toTless than or equal to680 K) in which the interface appears to be stable. Interdiffusion resumes at Tgreater than or equal to680 K. Molecular dynamics and Monte Carlo simulations allow us to attribute the stability plateau at 610 Kless than or equal toTless than or equal to680 K to the formation of a single-layer MnFe surface alloy with a 2x2 unit cell and a checkerboard distribution of Mn and Fe atoms. X-ray-absorption spectroscopy and analysis of the dichroic signal show that the alloy has a ferromagnetic spin structure, collinear with that of the substrate. The magnetic moments of Mn and Fe atoms in the alloy are estimated to be 0.8mu(B) and 1.1mu(B), respectively.

Kinetics of phase transformations in a model with metastable fluid-fluid separation: A molecular dynamics study

By molecular dynamics (MD) simulations we study the crystallization process in a model system whose particles interact by a spherical pair potential with a narrow and deep attractive well adjacent to a hard repulsive core. The phase diagram of the model displays a solid-fluid equilibrium, with a metastable fluid-fluid separation. Our computations are restricted to fairly small systems (from 2592 to 10368 particles) and cover long simulation times, with constant energy trajectories extending up to 76x10(6) MD steps. By progressively reducing the system temperature below the solid-fluid line, we first observe the metastable fluid-fluid separation, occurring readily and almost reversibly upon crossing the corresponding line in the phase diagram. The nucleation of the crystal phase takes place when the system is in the two-fluid metastable region. Analysis of the temperature dependence of the nucleation time allows us to estimate directly the nucleation free energy barrier. The results are compared with the predictions of classical nucleation theory. The critical nucleus is identified, and its structure is found to be predominantly fcc. Following nucleation, the solid phase grows steadily across the system, incorporating a large number of localized and extended defects. We discuss the relaxation processes taking place both during and after the crystallization stage. The relevance of our simulation for the kinetics of protein crystallization under normal experimental conditions is discussed. (C) 2002 American Institute of Physics.