Neural correlates of task switching in paternal 15q11-q13 deletion Prader-Willi syndrome

We report a first study of brain activity linked to task switching in individuals with Prader-Willi syndrome (PWS) PWS individuals show a specific cognitive deficit in task switching which may be associated with the display of temper outbursts and repetitive questioning The performance of participants with PWS and typically developing controls was matched in a cued task switching procedure and brain activity was contrasted on switching and non switching blocks using SARI Individuals with PWS did not show the typical frontal-parietal pattern of neural activity associated with switching blocks, with significantly reduced activation in regions of the posterior parietal and ventromedial prefrontal cortices We suggest that this is linked to a difficulty in PWS in setting appropriate attentional weights to enable task set reconfiguration In addition to this, PWS individuals did not show the typical pattern of deactivation, with significantly less deactivation in an anterior region of the ventromedial prefrontal cortex One plausible explanation for this is that individuals with PWS show dysfunction within the default mode network which has been linked to attentional control The data point to functional changes in the neural circuitry supporting task switching in PWS even when behavioural performance is matched to controls and thus highlight neural mechanisms that may be involved in a specific pathway between genes cognition and behaviour (C) 2010 Elsevier B V All rights reserved

An Informant Report Behavior Diary for Measuring Temper Outbursts in an Intervention Setting

Temper outbursts are associated with several psychological disorders and comprise a high priority for intervention. However, the low frequency of outbursts presents a challenge for valid measurement. In the present study an informant report behavior diary for measuring temper outbursts was developed and its validity assessed in a case series. Caregivers of 12 individuals with the neurodevelopmental disorder Prader-Willi syndrome (PWS, in which temper outbursts are common) completed a behavior diary over 4 weeks, and a structured interview. Heart rate and movement data were recorded during a sample of the days subject to diary reporting. Individuals with PWS completed self-report ratings of negative emotion experience. Behavior diaries showed high concordance with the component behaviors and duration of temper outbursts reported in structured interviews; but tended to report a lower frequency. For outbursts reported in diaries during physiological recording, heart rate was consistently elevated above a resting state baseline; and was comparable to that recorded during high physical activity. Available self-report data demonstrated correspondence with the diaries but few self-report data were produced. The present results provide critical proof of principle data supporting the concurrent validity of the ecologically valid, resource efficient diaries, which can be exploited in future research.

Quantum-state transfer in imperfect artificial spin networks

High-fidelity quantum computation and quantum state transfer are possible in short spin chains. We exploit a system based on a dispersive qubit-boson interaction to mimic XY coupling. In this model, the usually assumed nearest-neighbor coupling is no longer valid: all the qubits are mutually coupled. We analyze the performances of our model for quantum state transfer showing how preengineered coupling rates allow for nearly optimal state transfer. We address a setup of superconducting qubits coupled to a microstrip cavity in which our analysis may be applied.

An experimental investigation into the influence of user state and environment on fading characteristics in wireless body area networks at 2.45 GHz

Using seven strategically placed, time-synchronized bodyworn receivers covering the head, upper front and back torso, and the limbs, we have investigated the effect of user state: stationary or mobile and local environment: anechoic chamber, open office area and hallway upon first and second order statistics for on-body fading channels. Three candidate models were considered: Nakagami, Rice and lognormal. Using maximum likelihood estimation and the Akaike information criterion it was established that the Nakagami-m distribution best described small-scale fading for the majority of on-body channels over all the measurement scenarios. When the user was stationary, Nakagami-m parameters were found to be much greater than 1, irrespective of local surroundings. For mobile channels, Nakagami-m parameters significantly decreased, with channels in the open office area and hallway experiencing the worst fading conditions.

Reconstructing the quantum state of oscillator networks with a single qubit

We introduce a scheme to reconstruct arbitrary states of networks composed of quantum oscillators-e. g., the motionalstate of trapped ions or the radiation state of coupled cavities. The scheme involves minimal resources and minimal access, in the sense that it (i) requires only the interaction between a one-qubit probe and a single node of the network; (ii) provides the Weyl characteristic function of the network directly from the data, avoiding any tomographic transformation; (iii) involves the tuning of only one coupling parameter. In addition, we show that a number of quantum properties can be extracted without full reconstruction of the state. The scheme can be used for probing quantum simulations of anharmonic many-body systems and quantum computations with continuous variables. Experimental implementation with trapped ions is also discussed and shown to be within reach of current technology.

Per-Flow State Management Technique for High-Speed Networks

Flow processing is a fundamental element of stateful traffic classification and it has been recognized as an essential factor for delivering today’s application-aware network operations and security services. The basic function within a flow processing engine is to search and maintain a flow table, create new flow entries if no entry matches and associate each entry with flow states and actions for future queries. Network state information on a per-flow basis must be managed in an efficient way to enable Ethernet frame transmissions at 40 Gbit/s (Gbps) and 100 Gbps in the near future. This paper presents a hardware solution of flow state management for implementing large-scale flow tables on popular computer memories using DDR3 SDRAMs. Working with a dedicated flow lookup table at over 90 million lookups per second, the proposed system is able to manage 512-bit state information at run time.

Dynamical entanglement transfer for quantum-information networks

A key element in the architecture of a quantum-information processing network is a reliable physical interface between fields and qubits. We study a process of entanglement transfer engineering, where two remote qubits respectively interact with an entangled two-mode continuous-variable (CV) field. We quantify the entanglement induced in the qubit state at the expenses of the loss of entanglement in the CV system. We discuss the range of mixed entangled states which can be obtained with this setup. Furthermore, we suggest a protocol to determine the residual entangling power of the light fields inferring, thus, the entanglement left in the field modes which, after the interaction, are no longer in a Gaussian state. Two different setups are proposed: a cavity-QED system and an interface between superconducting qubits and field modes. We address in detail the practical difficulties inherent in these two proposals, showing that the latter is promising in many aspects.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Measuring the state of consciousness in a free-living diving sea turtle

We report on results from two types of data-logger attached to hawksbill turtles (Eretmochelys coriacea) in the breeding season at the Seychelles, Indian Ocean. Conventional time-depth recorders (TDRs) showed prolonged bouts of long dives to the seabed, consistent with benthic resting. This behaviour has been widely reported in sea turtles and appears to be a common feature for energy conservation. An Inter-Mandibular Angle Sensor (IMASEN) recorded mouth opening and buccal pumping by one turtle for 2.5 days. Buccal pumping occurred widely while the turtle was submerged, consistent with a function of olfactory sensory perception of the turtle's environment. However, buccal pumping stopped during the middle of long benthic dives consistent with the turtle entering a phase of sleep. It therefore appears that by recording buccal oscillations, it is possible to assess the state of consciousness of turtles allowing the eco-physiology of diving to be more fully explored. (C) 2007 Elsevier B.V. All rights reserved.

Dynamic Buffer Management for Multimedia Services in Beyond 3G Wireless Networks

This paper investigates a dynamic buffer man-agement scheme for QoS control of multimedia services in be-yond 3G wireless systems. The scheme is studied in the context of the state-of-the-art 3.5G system i.e. the High Speed Downlink Packet Access (HSDPA) which enhances 3G UMTS to support high-speed packet switched services. Unlike earlier systems, UMTS-evolved systems from HSDPA and beyond incorporate mechanisms such as packet scheduling and HARQ in the base station necessitating data buffering at the air interface. This introduces a potential bottleneck to end-to-end communication. Hence, buffer management at the air interface is crucial for end-to-end QoS support of multimedia services with multi-plexed parallel diverse flows such as video and data in the same end-user session. The dynamic buffer management scheme for HSDPA multimedia sessions with aggregated real-time and non real-time flows is investigated via extensive HSDPA simulations. The impact of the scheme on end-to-end traffic performance is evaluated with an example multimedia session comprising a real-time streaming flow concurrent with TCP-based non real-time flow. Results demonstrate that the scheme can guar-antee the end-to-end QoS of the real-time streaming flow, whilst simultaneously protecting the non real-time flow from starva-tion resulting in improved end-to-end throughput performance

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Power allocation strategies across N orthogonal channels for single-relay networks at both source and relay

We consider a wireless relay network with one source, one relay and one destination, where communications between nodes are preformed over N orthogonal channels. This, for example, is the case when orthogonal frequency division multiplexing is employed for data communications. Since the power available at the source and relay is limited, we study optimal power allocation strategies at the source and relay in order to maximize the overall source-destination capacity. Depending on the availability of the channel state information at both the source and relay or only at the relay, power allocation is performed at both the source and relay or only at the relay. Considering different setups for the problem, various optimization problems are formulated and solved. Some properties of the optimal solution are also proved.