Brain networks for temporal adaptation, anticipation, and sensory-motor integration in rhythmic human behavior

Human interaction often requires the precise yet flexible interpersonal coordination of rhythmic behavior, as in group music making. The present fMRI study investigates the functional brain networks that may facilitate such behavior by enabling temporal adaptation (error correction), prediction, and the monitoring and integration of information about ‘self’ and the external environment. Participants were required to synchronize finger taps with computer-controlled auditory sequences that were presented either at a globally steady tempo with local adaptations to the participants' tap timing (Virtual Partner task) or with gradual tempo accelerations and decelerations but without adaptation (Tempo Change task). Connectome-based predictive modelling was used to examine patterns of brain functional connectivity related to individual differences in behavioral performance and parameter estimates from the adaptation and anticipation model (ADAM) of sensorimotor synchronization for these two tasks under conditions of varying cognitive load. Results revealed distinct but overlapping brain networks associated with ADAM-derived estimates of temporal adaptation, anticipation, and the integration of self-controlled and externally controlled processes across task conditions. The partial overlap between ADAM networks suggests common hub regions that modulate functional connectivity within and between the brain's resting-state networks and additional sensory-motor regions and subcortical structures in a manner reflecting coordination skill. Such network reconfiguration might facilitate sensorimotor synchronization by enabling shifts in focus on internal and external information, and, in social contexts requiring interpersonal coordination, variations in the degree of simultaneous integration and segregation of these information sources in internal models that support self, other, and joint action planning and prediction

Laboratory experiments on cohesive soil bed fluidization by water waves

Part I. Relationships between the rate of bed fluidization and the rate of wave energy dissipation, by Jingzhi Feng and Ashish J. Mehta and Part II. In-situ rheometry for determining the dynamic response of bed, by David J.A. Williams and P. Rhodri Williams. A series of preliminary laboratory flume experiments were carried out to examine the time-dependent behavior of a cohesive soil bed subjected to progressive, monochromatic waves. The bed was an aqueous, 50/50 (by weight) mixture of a kaolinite and an attapulgite placed in a plexiglass trench. The nominal bed thickness was 16 cm with density ranging from 1170 to 1380 kg/m 3, and water above was 16 to 20 cm deep. Waves of design height ranging from 2 to 8 cm and a nominal frequency of 1 Hz were run for durations up to 2970 min. Part I of this report describes experiments meant to examine the rate at which the bed became fluidized, and its relation to the rate of wave energy dissipation. Part II gives results on in-situ rheometry used to track the associated changes in bed rigidity. Temporal and spatial changes of the effective stress were measured during the course of wave action, and from these changes the bed fluidization rate was calculated. A wave-mud interaction model developed in a companion study was employed to calculate the rate of wave energy dissipation. The dependence of the rate of fluidization on the rate of energy dissipation was then explored. Fluidization, which seemingly proceeded down from the bed surface, occurred as a result of the loss of structural integrity of the soil matrix through a buildup of the excess pore pressure and the associated loss of effective stress. The rate of fluidization was typically greater at the beginning of wave action and apparently approached zero with time. This trend coincided with the approach of the rate of energy dissipation to a constant value. In general it was also observed that, for a given wave frequency, the larger the wave height the faster the rate of fluidization and thicker the fluid mud layer formed. On the other hand, increasing the time of bed consolidation prior to wave action decreased the fluidization rate due to greater bed rigidity. Upon cessation of wave action structural recovery followed. Dynamic rigidity was measured by specially designed, in situ shearometers placed in the bed at appropriate elevations to determine the time-dependence of the storage and loss moduli, G' and G", of the viscoelastic clay mixture under 1 Hz waves. As the inter-particle bonds of the space-filling, bed material matrix weakened, the shear propagation velocity decreased measurably. Consequently, G' decreased and G" increased as a transition from dynamically more elastic to more viscous response occurred. These preliminary experiments have demonstrated the validity of the particular rheometric technique used, and the critical need for synchronous, in-situ measurements of pore pressures and moduli characterizing bed rheology in studies on mud fluidization. This study was supported by WES contract DACW39-90-K-0010. (This document contains 151 pages.

Instrumentation and Virtual Library for Air Pollution Monitoring

In this work a data acquisition board (DAQB) with data transfer by serial port and the associated virtual library included into LabVIEW software are presented. The DAQB developed around a National Semiconductor LM 12458 device, have the capability to perform tasks that diminish the host processor work and is capable to communicate with the host computer by using a set of drivers associated. Highly integrated device circuit that has into it the most components of the board, facility in data handling, good metrological performance and a very low cost are the benefits of the proposed system. Using the LabView environment, we have realized a virtual instrument able to get from the prototype data acquisition board for environmental monitoring parameters the information about air pollution factors like CO, H2S, SO2, NO, NO2 etc. In order to get effective information about those factors and the monitoring points, this intelligent measurement system, compound from portable computer, and gas detector. This system can be used to map the information about the air pollution factors dispersion in order to answer to the needs of residential and industrial areas expansion

Securing IEEE P1687 On-chip Instrumentation Access Using PUF

As the complexity of VLSI designs grows, the amount of embedded instrumentation in system-on-a-chip designs increases at an exponential rate. Such structures serve various purposes throughout the life-cycle of VLSI circuits, e.g. in post-silicon validation and debug, production test and diagnosis, as well as during in-field test and maintenance. Reliable access mechanisms for embedded instruments are therefore key to rapid chip development and secure system maintenance. Reconfigurable scan networks defined by IEEE Std. P1687 emerge as a scalable and cost-effective access medium for on-chip instrumentation. The accessibility offered by reconfigurable scan networks contradicts security and safety requirements for embedded instrumentation. Embedded instrumentation is an integral system component that remains functional throughout the lifetime of a chip. To prevent harmful activities, such as tampering with safety-critical systems, and reduce the risk of intellectual property infringement, the access to embedded instrumentation requires protection. This thesis provides a novel, Physical Unclonable Function (PUF) based secure access method for on-chip instruments which enhances the security of IJTAG network at low hardware cost and with less routing congestion

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

Neural Network Detection of Fatigue Crack Growth in Riveted Joints Using Acoustic Emission

The purpose of this research was to demonstrate the capability of neural networks to discriminate between individual acoustic emission (AE) signals originating from crack growth and rivet rubbing (fretting) in aluminum lap joints. AE waveforms were recorded during tensile fatigue cycling of six notched and riveted 7075-T6 specimens using a broadband piezoelectric transducer and a computer interfaced oscilloscope. The source of 1,311 signals was identified based on triggering logic, amplitude relationships, and time of arrival data collected from the broad-band transducer and three additional 300 Hz resonant transducers bonded to the specimens. The power spectrum of each waveform was calculated and normalized to correct for variable specimen geometry and wave propagation effects. In order to determine the variation between individual signals of the same class, the normalized spectra were clustered onto a two-dimensional feature space using a Kohonen self organizing map (SOM). Then 132 crack growth and 137 rivet rubbing spectra were used to train a back-propagation neural network to provide automatic pattern classification. Although there was some overlap between the clusters mapped in the Kohonen feature space, the trained back-propagation neural network was able to classify the remaining 463 crack growth signals with a 94% accuracy and the 367 rivet rubbing signals with a 99% accuracy

Remote Hardware-In-the-Loop Measurement System for Electrolyser Characterization

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The installation of facilities replicating the realworld condition is often required for carrying out meaningful tests on new devices and for collecting data with the aim to create realistic device model. However, these facilities require huge investments, as well as areas where they can be properly installed. In this paper, we present a test infrastructure exploiting the concept of Remote Power Hardware-In-the-Loop (RPHIL), applied for characterizing the performances of a 8kW Proton Exchange Membrane (PEM) electrolyser installed at the Hanze University of Applied Sciences in Groningen (The Netherlands). The electrolyser is subjected to different test conditions imposed both locally and remotely. The results show that this measurement procedure is effective and can open new perspectives in the way to share and exploit the existing research infrastructure in Europe