Differential encoding of losses and gains in the human striatum.

Studies on human monetary prediction and decision making emphasize the role of the striatum in encoding prediction errors for financial reward. However, less is known about how the brain encodes financial loss. Using Pavlovian conditioning of visual cues to outcomes that simultaneously incorporate the chance of financial reward and loss, we show that striatal activation reflects positively signed prediction errors for both. Furthermore, we show functional segregation within the striatum, with more anterior regions showing relative selectivity for rewards and more posterior regions for losses. These findings mirror the anteroposterior valence-specific gradient reported in rodents and endorse the role of the striatum in aversive motivational learning about financial losses, illustrating functional and anatomical consistencies with primary aversive outcomes such as pain.

The effect of a twin tunnel on the propagation of ground-borne vibration from an underground railway

Accurate predictions of ground-borne vibration levels in the vicinity of an underground railway are greatly sought after in modern urban centres. Yet the complexity involved in simulating the underground environment means that it is necessary to make simplifying assumptions about this system. One such commonly made assumption is to ignore the effects of neighbouring tunnels, despite the fact that many underground railway lines consist of twin-bored tunnels, one for the outbound direction and one for the inbound direction. This paper presents a unique model for two tunnels embedded in a homogeneous, elastic fullspace. Each of these tunnels is subject to both known, dynamic train forces and dynamic cavity forces. The net forces acting on the tunnels are written as the sum of those tractions acting on the invert of a single tunnel, and those tractions that represent the motion induced by the neighbouring tunnel. By apportioning the tractions in this way, the vibration response of a two-tunnel system is written as a linear combination of displacement fields produced by a single-tunnel system. Using Fourier decomposition, forces are partitioned into symmetric and antisymmetric modenumber components to minimise computation times. The significance of the interactions between two tunnels is quantified by calculating the insertion gains, in both the vertical and horizontal directions, that result from the existence of a second tunnel. The insertion-gain results are shown to be localised and highly dependent on frequency, tunnel orientation and tunnel thickness. At some locations, the magnitude of these insertion gains is greater than 20 dB. This demonstrates that a high degree of inaccuracy exists in any surface vibration prediction model that includes only one of the two tunnels. This novel two-tunnel solution represents a significant contribution to the existing body of research into vibration from underground railways, as it shows that the second tunnel has a significant influence on the accuracy of vibration predictions for underground railways. © 2011 Elsevier Ltd. All rights reserved.

Implications of local lifecycle analyses and low carbon fuel standard design on gasohol transportation fuels

State and regional policies, such as low carbon fuel standards (LCFSs), increasingly mandate that transportation fuels be examined according to their greenhouse gas (GHG) emissions. We investigate whether such policies benefit from determining fuel carbon intensities (FCIs) locally to account for variations in fuel production and to stimulate improvements in FCI. In this study, we examine the FCI of transportation fuels on a lifecycle basis within a specific state, Minnesota, and compare the results to FCIs using national averages. Using data compiled from 18 refineries over an 11-year period, we find that ethanol production is highly variable, resulting in a 42% difference between carbon intensities. Historical data suggests that lower FCIs are possible through incremental improvements in refining efficiency and the use of biomass for processing heat. Stochastic modeling of the corn ethanol FCI shows that gains in certainty due to knowledge of specific refinery inputs are overwhelmed by uncertainty in parameters external to the refiner, including impacts of fertilization and land use change. The LCA results are incorporated into multiple policy scenarios to demonstrate the effect of policy configurations on the use of alternative fuels. These results provide a contrast between volumetric mandates and LCFSs. © 2011 Elsevier Ltd.

An advanced multi-configuration stator well cooling test facility

Optimisation of cooling systems within gas turbine engines is of great interest to engine manufacturers seeking gains in performance, efficiency and component life. The effectiveness of coolant delivery is governed by complex flows within the stator wells and the interaction of main annulus and cooling air in the vicinity of the rim seals. This paper reports the development of a test facility which allows the interaction of cooling air and main gas paths to be measured at conditions representative of those found in modern gas turbine engines. The test facility features a two stage turbine with an overall pressure ratio of approximately 2.6:1. Hot air is supplied to the main annulus using a Rolls-Royce Dart compressor driven by an aero-derivative engine plant. Cooling air can be delivered to the stator wells at multiple locations and at a range of flow rates which cover bulk ingestion through to bulk egress. The facility has been designed with adaptable geometry to enable rapid changes of cooling air path configuration. The coolant delivery system allows swift and accurate changes to the flow settings such that thermal transients may be performed. Particular attention has been focused on obtaining high accuracy data, using a radio telemetry system, as well as thorough through-calibration practices. Temperature measurements can now be made on both rotating and stationary discs with a long term uncertainty in the region of 0.3 K. A gas concentration measurement system has also been developed to obtain direct measurement of re-ingestion and rim seal exchange flows. High resolution displacement sensors have been installed in order to measure hot running geometry. This paper documents the commissioning of a test facility which is unique in terms of rapid configuration changes, non-dimensional engine matching and the instrumentation density and resolution. Example data for each of the measurement systems is presented. This includes the effect of coolant flow rate on the metal temperatures within the upstream cavity of the turbine stator well, the axial displacement of the rotor assembly during a commissioning test, and the effect of coolant flow rate on mixing in the downstream cavity of the stator well. Copyright © 2010 by ASME.

Outage probability of the gaussian MIMO free-space optical channel with PPM

Atmospheric effects can significantly degrade the reliability of free-space optical communications. One such effect is scintillation, caused by atmospheric turbulence, refers to random fluctuations in the irradiance and phase of the received laser beam. In this paper we inv stigate the use of multiple lasers and multiple apertures to mitigate scintillation. Since the scintillation process is slow, we adopt a block fading channel model and study the outage probability under the assumptions of orthogonal pulse-position modulation and non-ideal photodetection. Assuming perfect receiver channel state information (CSI), we derive the signal-to-noise ratio (SNR) exponents for the cases when the scintillation is lognormal, exponential and gammagamma distributed, which cover a wide range of atmospheric turbulence conditions. Furthermore, when CSI is also available at the transmitter, we illustrate very large gains in SNR are possible (in some cases larger than 15 dB) by adapting the transmitted power. Under a long-term power constraint, we outline fundamental design criteria via a simple expression that relates the required number of lasers and apertures for a given code rate and number of codeword blocks to completely remove system outages. Copyright © 2009 IEEE.

Fundamental atrium design for natural ventilation

An atrium is a central feature of many modern naturally ventilated building designs. The atrium fills with warm air from the adjoining storeys: this air may be further warmed by direct solar heating in the atrium, and the deep warm layer enhances the flow. In this paper we focus on the degree of flow enhancement achieved by an atrium which is itself 'ventilated' directly, by a low-level connection to the exterior. A theoretical model is developed to predict the steady stack-driven displacement flow and thermal stratification in the building, due to heat gains in the storey and solar gains in the atrium, and compared with the results of laboratory experiments. Direct ventilation of the atrium is detrimental to the ventilation of the storey and the best design is identified as a compromise that provides adequate ventilation of both spaces. We identify extremes of design for which an atrium provides no significant enhancement of the flow, and show that an atrium only enhances the flow in the storey if its upper opening is of an intermediate size, and its lower opening is sufficiently small. © 2003 Elsevier Science Ltd. All rights reserved.

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/.

Polarization and temperature dependence of photoluminescence from zincblende and wurtzite InP nanowires

We use polarization-resolved and temperature-dependent photoluminescence of single zincblende (ZB) (cubic) and wurtzite (WZ) (hexagonal) InP nanowires to probe differences in selection rules and bandgaps between these two semiconductor nanostructures. The WZ nanowires exhibit a bandgap 80 meV higher in energy than the ZB nanowires. The temperature dependence of the PL is similar but not identical for the WZ and ZB nanowires. We find that ZB nanowires exhibit strong polarization parallel to the nanowire axis, while the WZ nanowires exhibit polarized emission perpendicular to the nanowire axis. This behavior is interpreted in terms of the different selection rules for WZ and ZB crystal structures. © 2007 American Institute of Physics.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.