Kinesthesia in a sustained-attention driving task

This study investigated the effects of kinesthetic stimuli on brain activities during a sustained-attention task in an immersive driving simulator. Tonic and phasic brain responses on multiple timescales were analyzed using time-frequency analysis of electroencephalographic (EEG) sources identified by independent component analysis (ICA). Sorting EEG spectra with respect to reaction times (RT) to randomly introduced lane-departure events revealed distinct effects of kinesthetic stimuli on the brain under different performance levels. Experimental results indicated that EEG spectral dynamics highly correlated with performance lapses when driving involved kinesthetic feedback. Furthermore, in the realistic environment involving both visual and kinesthetic feedback, a transitive relationship of power spectra between optimal-, suboptimal-, and poor-performance groups was found predominately across most of the independent components. In contrast to the static environment with visual input only, kinesthetic feedback reduced theta-power augmentation in the central and frontal components when preparing for action and error monitoring, while strengthening alpha suppression in the central component while steering the wheel. In terms of behavior, subjects tended to have a short response time to process unexpected events with the assistance of kinesthesia, yet only when their performance was optimal. Decrease in attentional demand, facilitated by kinesthetic feedback, eventually significantly increased the reaction time in the suboptimal-performance state. Neurophysiological evidence of mutual relationships between behavioral performance and neurocognition in complex task paradigms and experimental environments, presented in this study, might elucidate our understanding of distributed brain dynamics, supporting natural human cognition and complex coordinated, multi-joint naturalistic behavior, and lead to improved understanding of brain-behavior relations in operating environments. © 2014 Elsevier Inc

Complete quantum teleportation using nuclear magnetic resonance

Quantum mechanics provides spectacular new information processing abilities (Bennett 1995, Preskill 1998). One of the most unexpected is a procedure called quantum teleportation (Bennett et al 1993) that allows the quantum state of a system to be transported from one location to another, without moving through the intervening space. Partial implementations of teleportation (Bouwmeester et al 1997, Boschi et al 1998) over macroscopic distances have been achieved using optical systems, but omit the final stage of the teleportation procedure. Here we report an experimental implementation of the full quantum teleportation operation over inter-atomic distances using liquid state nuclear magnetic resonance (NMR). The inclusion of the final stage enables for the first time a teleportation implementation which may be used as a subroutine in larger quantum computations, or for quantum communication. Our experiment also demonstrates the use of quantum process tomography, a procedure to completely characterize the dynamics of a quantum system. Finally, we demonstrate a controlled exploitation of decoherence as a tool to assist in the performance of an experiment.Comment: 15 pages, 2 figures. Minor differences between this and the published versio

An EEG-based perceptual function integration network for application to drowsy driving

© 2015 Elsevier B.V. All rights reserved. Drowsy driving is among the most critical causes of fatal crashes. Thus, the development of an effective algorithm for detecting a driver's cognitive state demands immediate attention. For decades, studies have observed clear evidence using electroencephalography that the brain's rhythmic activities fluctuate from alertness to drowsiness. Recognition of this physiological signal is the major consideration of neural engineering for designing a feasible countermeasure. This study proposed a perceptual function integration system which used spectral features from multiple independent brain sources for application to recognize the driver's vigilance state. The analysis of brain spectral dynamics demonstrated physiological evidenced that the activities of the multiple cortical sources were highly related to the changes of the vigilance state. The system performances showed a robust and improved accuracy as much as 88% higher than any of results performed by a single-source approach

Quantum Teleportation is a Universal Computational Primitive

We present a method to create a variety of interesting gates by teleporting quantum bits through special entangled states. This allows, for instance, the construction of a quantum computer based on just single qubit operations, Bell measurements, and GHZ states. We also present straightforward constructions of a wide variety of fault-tolerant quantum gates.Comment: 6 pages, REVTeX, 6 epsf figure

Effect of bilayer coupling on tunneling conductance of double-layer high T_c cuprates

Physical effects of bilayer coupling on the tunneling spectroscopy of high T$_{c}$ cuprates are investigated. The bilayer coupling separates the bonding and antibonding bands and leads to a splitting of the coherence peaks in the tunneling differential conductance. However, the coherence peak of the bonding band is strongly suppressed and broadened by the particle-hole asymmetry in the density of states and finite quasiparticle life-time, and is difficult to resolve by experiments. This gives a qualitative account why the bilayer splitting of the coherence peaks was not clearly observed in tunneling measurements of double-layer high-T$_c$ oxides.Comment: 4 pages, 3 figures, to be published in PR

Single channel wireless EEG device for real-time fatigue level detection

© 2015 IEEE. Driver fatigue problem is one of the important factors of traffic accidents. Recent years, many research had investigated that using EEG signals can effectively detect driver's drowsiness level. However, real-time monitoring system is required to apply these fatigue level detection techniques in the practical application, especially in the real-road driving. Therefore, it required less channels, portable and wireless, real-time monitoring and processing techniques for developing the real-time monitoring system. In this study, we develop a single channel wireless EEG device which can real-time detect driver's fatigue level on the mobile device such as smart phone or tablet. The developed device is investigated to obtain a better and precise understanding of brain activities of mental fatigue under driving, which is of great benefit for devolvement of detection of driving fatigue system. This system consists of a Bluetooth-enabled one channel EEG, a regression model, and smartphone, which was a platform recording and transforming the raw EEG data to useful driving status. In the experiment, this was a sustained-attention driving task to implement in a virtual-reality (VR) driving simulator. To training model and develop the system, we were performed for 15 subjects to study Electroencephalography (EEG) brain dynamics by using a mobile and wireless EEG device. Based on the outstanding training results, the leave-one-subject-out cross validation test obtained 90% fatigue detection accuracy. These results indicate that the combination of a smartphone and wireless EEG device constitutes an effective and easy wearable solution for detecting and preventing driver fatigue in real driving environments

Evolution of superconductivity in K2-xFe4+ySe5: Spectroscopic studies of X-ray absorption and emission.

This study investigates the evolution of superconductivity in K2-xFe4+ySe5 using temperature-dependent X-ray absorption and resonant inelastic X-ray scattering techniques. Magnetization measurements show that polycrystalline superconducting (SC) K1.9Fe4.2Se5 has a critical temperature (T c) of ∼31 K with a varying superconducting volume fraction, which strongly depends on its synthesis temperature. An increase in Fe-structural/vacancy disorder in SC samples with more Fe atoms occupying vacant 4d sites is found to be closely related to the decrease in the spin magnetic moment of Fe. Moreover, the nearest-neighbor Fe-Se bond length in SC samples exceeds that in the non-SC (NS) sample, K2Fe4Se5, which indicates a weaker hybridization between the Fe 3d and Se 4p states in SC samples. These results clearly demonstrate the correlations among the local electronic and atomic structures and the magnetic properties of K2-xFe4+ySe5 superconductors, providing deeper insight into the electron pairing mechanisms of superconductivity

An EEG-Based Fatigue Detection and Mitigation System

© 2016 World Scientific Publishing Company. Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual's internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant's EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha-and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject's cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments

Topics in Quantum Computers

I provide an introduction to quantum computers, describing how they might be realized using language accessible to a solid state physicist. A listing of the minimal requirements for creating a quantum computer is given. I also discuss several recent developments in the area of quantum error correction, a subject of importance not only to quantum computation, but also to some aspects of the foundations of quantum theory.Comment: 22 pages, Latex, 1 eps figure, Paper to be published in "Mesoscopic Electron Transport", edited by L. Kowenhoven, G. Schoen and L. Sohn, NATO ASI Series E, Kluwer Ac. Publ., Dordrecht. v2: typos in refrences fixe

Efficient simulation of the spatial transmission dynamics of influenza

Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs. © 2010 Tsai et al.published_or_final_versio