Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans.

Theories of instrumental learning are centred on understanding how success and failure are used to improve future decisions. These theories highlight a central role for reward prediction errors in updating the values associated with available actions. In animals, substantial evidence indicates that the neurotransmitter dopamine might have a key function in this type of learning, through its ability to modulate cortico-striatal synaptic efficacy. However, no direct evidence links dopamine, striatal activity and behavioural choice in humans. Here we show that, during instrumental learning, the magnitude of reward prediction error expressed in the striatum is modulated by the administration of drugs enhancing (3,4-dihydroxy-L-phenylalanine; L-DOPA) or reducing (haloperidol) dopaminergic function. Accordingly, subjects treated with L-DOPA have a greater propensity to choose the most rewarding action relative to subjects treated with haloperidol. Furthermore, incorporating the magnitude of the prediction errors into a standard action-value learning algorithm accurately reproduced subjects' behavioural choices under the different drug conditions. We conclude that dopamine-dependent modulation of striatal activity can account for how the human brain uses reward prediction errors to improve future decisions.

Predictive neural coding of reward preference involves dissociable responses in human ventral midbrain and ventral striatum.

Food preferences are acquired through experience and can exert strong influence on choice behavior. In order to choose which food to consume, it is necessary to maintain a predictive representation of the subjective value of the associated food stimulus. Here, we explore the neural mechanisms by which such predictive representations are learned through classical conditioning. Human subjects were scanned using fMRI while learning associations between arbitrary visual stimuli and subsequent delivery of one of five different food flavors. Using a temporal difference algorithm to model learning, we found predictive responses in the ventral midbrain and a part of ventral striatum (ventral putamen) that were related directly to subjects' actual behavioral preferences. These brain structures demonstrated divergent response profiles, with the ventral midbrain showing a linear response profile with preference, and the ventral striatum a bivalent response. These results provide insight into the neural mechanisms underlying human preference behavior.

Reynolds number effects on scalar dissipation rate transport and its modeling in turbulent premixed combustion

The effects of turbulent Reynolds number, Ret, on the transport of scalar dissipation rate of reaction progress variable in the context of Reynolds averaged Navier-Stokes simulations have been analyzed using three-dimensional simplified chemistry-based direct numerical simulation (DNS) data of freely propagating turbulent premixed flames with different values of Ret. Scaling arguments have been used to explain the effects of Ret on the turbulent transport, scalar-turbulence interaction, and the combined reaction and molecular dissipation terms. Suitable modifications to the models for these terms have been proposed to account for Ret effects, and the model parameters include explicit Ret dependence. These expressions approach expected asymptotic limits for large values of Ret. However, turbulent Reynolds number Ret does not seem to have any major effects on the modeling of the term arising from density variation. Copyright © Taylor and Francis Group, LLC.

The high strain rate response of Ultra High Molecular-weight Polyethylene: From fibre to laminate

The effect of strain rate upon the uniaxial response of Ultra High Molecular-weight Polyethylene (UHMWPE) fibres, yarns and laminates of lay-up [0/90]48 has been measured in both the 0/90 and ±45 configurations. The tensile strength of the matrix-dominated ±45 laminate is two orders of magnitude less than that of the fibre-dominated 0/90 laminate, and is more sensitive to strain rate. A piezoelectric force sensor device was developed to obtain the high strain rate data, and this achieved a rise time of less than 1 μs. It is found that the failure strength (and failure strain) of the yarn is almost insensitive to strain rate within the range (10 -1-103 s-1). At low strain rates (below 10 -1 s-1), creep of the yarn dominates and the failure strain increases with diminishing strain rate. The tensile strength of the dry yarn exceeds that of the laminate by about 20%. Tests on single fibres exceed the strength of the yarn by 20%. © 2013 Elsevier Ltd. All rights reserved.

UEGO based measurement of EGR rate and residual gas fraction

A technique is presented for measuring the exhaust gas recirculation (EGR) and residual gas fraction (RGF) using a fast UEGO based O2 measurement of the manifold or in-cylinder gases, and of the exhaust gases. The technique has some advantages over the more common CO2-based method. In the case of an RGF measurement, fuel interference must be eliminated and special fuelling arrangements are is required. It is shown how a UEGO-based measurement, though sensitive to reactive species in the exhaust (such as H 2), as a system reports EGR/ RGF rates faithfully. Preliminary tests showed that EGR and RGF measurements using the O2 approach agreed well with CO2-based measurements. Copyright © 2011 SAE International.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Modeling of strain rate effects on clay in simple shear

The response of clay is highly dependent on straining and loading rate. To obtain a realistic prediction of the response for time dependent problems, it is essential to use a model that accounts for rate effects in the stress-strain-strength properties of soils. The proposed model has been expanded from the existing SIMPLE DSS framework to account for the strain rate effects on clays in simple shear conditions. In accordance with the findings in the existing literature, soil response displays a unique relationship between shear strength and strain rate. The predicting model is illustrated with a limited test data. Copyright ASCE 2006.

Precursor flow rate manipulation for the controlled fabrication of twin-free GaAs nanowires on silicon substrates

Vertically oriented GaAs nanowires (NWs) are grown on Si(111) substrates using metal-organic chemical vapor deposition. Controlled epitaxial growth along the 111 direction is demonstrated following the deposition of thin GaAs buffer layers and the elimination of structural defects, such as twin defects and stacking faults, is found for high growth rates. By systematically manipulating the AsH 3 (group-V) and TMGa (group-III) precursor flow rates, it is found that the TMGa flow rate has the most significant effect on the nanowire quality. After capping the minimal tapering and twin-free GaAs NWs with an AlGaAs shell, long exciton lifetimes (over 700ps) are obtained for high TMGa flow rate samples. It is observed that the Ga adatom concentration significantly affects the growth of GaAs NWs, with a high concentration and rapid growth leading to desirable characteristics for optoelectronic nanowire device applications including improved morphology, crystal structure and optical performance. © 2012 IOP Publishing Ltd.

Unexpected benefits of rapid growth rate for III-V nanowires.

In conventional planar growth of bulk III-V materials, a slow growth rate favors high crystallographic quality, optical quality, and purity of the resulting material. Surprisingly, we observe exactly the opposite effect for Au-assisted GaAs nanowire growth. By employing a rapid growth rate, the resulting nanowires are markedly less tapered, are free of planar crystallographic defects, and have very high purity with minimal intrinsic dopant incorporation. Importantly, carrier lifetimes are not adversely affected. These results reveal intriguing behavior in the growth of nanoscale materials, and represent a significant advance toward the rational growth of nanowires for device applications.

Application of scalar dissipation rate model to siemens DLE combustors

The standard design process for the Siemens Industrial Turbomachinery, Lincoln, Dry Low Emissions combustion systems has adopted the Eddy Dissipation Model with Finite Rate Chemistry for reacting computational fluid dynamics simulations. The major drawbacks of this model have been the over-prediction of temperature and lack of species data limiting the applicability of the model. A novel combustion model referred to as the Scalar Dissipation Rate Model has been developed recently based on a flamelet type assumption. Previous attempts to adopt the flamelet philosophy with alternative closure models have failed, with the prediction of unphysical phenomenon. The Scalar Dissipation Rate Model (SDRM) was developed from a physical understanding of scalar dissipation rate, signifying the rate of mixing of hot and cold fluids at scales relevant to sustain combustion, in flames and was validated using direct numerical simulations data and experimental measurements. This paper reports on the first industrial application of the SDRM to SITL DLE combustion system. Previous applications have considered ideally premixed laboratory scale flames. The industrial application differs significantly in the complexity of the geometry, unmixedness and operating pressures. The model was implemented into ANSYS-CFX using their inbuilt command language. Simulations were run transiently using Scale Adaptive Simulation turbulence model, which switches between Large Eddy Simulation and Unsteady Reynolds Averaged Navier Stokes using a blending function. The model was validated in a research SITL DLE combustion system prior to being applied to the actual industrial geometry at real operating conditions. This system consists of the SGT-100 burner with a glass square-sectioned combustor allowing for detailed diagnostics. This paper shows the successful validation of the SDRM against time averaged temperature and velocity within measurement errors. The successful validation allowed application of the SDRM to the SGT-100 twin shaft at the relevant full load conditions. Limited validation data was available due to the complexity of measurement in the real geometry. Comparison of surface temperatures and combustor exit temperature profiles showed an improvement compared to EDM/FRC model. Furthermore, no unphysical phenomena were predicted. This paper presents the successful application of the SDRM to the industrial combustion system. The model shows a marked improvement in the prediction of temperature over the EDM/FRC model previously used. This is of significant importance in the future applications of combustion CFD for understanding of hardware mechanical integrity, combustion emissions and dynamics of the flame. Copyright © 2012 by ASME.