Neoproterozoic Mafic-Ultramafic Intrusions from the Fanjingshan Region, South China: Implications for Subduction-Related Magmatism in the Jiangnan Fold Belt

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Neural network model of binaural hearing based on spatial feature extraction of the head related transfer function

In spatial hearing, complex valued head-related transfer function (HRTF) can be represented as a real valued head-related impulse response (HRIR). Using Karhunen-Loeve expansion, the spatial features of the normalized HRIRs on measurement space can be extracted as spatial character functions. A neural network model based on Von-Mises function is used to approximate the discrete spatial character function of HRIR. As a result, a time-domain binaural model is established and it fits the measured HRIRs well.published_or_final_versio

Detection and quantification of venous air embolism by wavelet analysis of Doppler heart sound

The wavelet analysis of the Doppler heart sound detected under controlled venous air embolism at sub-clinically and clinically significant volumes was studied in anaesthetized dogs. Signal processing with wavelet enhances the Dower of embolic signal and facilitates the simple detection and extraction of embolic heart beats by thresholding. The cumulative power of the extracted embolic heart beats is found to be linearly related to the volume of embolic air on the log-log scale, suggesting that it is feasible to estimate clinically significant volume of embolic air in human subjects by linearly extrapolating from sub-clinical embolic volumes.published_or_final_versio

A real-time monitor using wavelet analysis of the Doppler heart sound for the detection of venous air embolism

A fast detection algorithm for venous air embolism (VAE) was developed and implemented as a real-time monitor for detecting embolic heart sound and estimating embolic air volume. Its performance was evaluated under bolus injection of sub-clinical (0.0l to 0.80 ml) and continuous infusion of clinically significant (0.80 to 9.60 ml) air volumes in anaesthetized dogs. The clinically significant air emboli could be estimated based on the calibration curve obtained during sub-clinical VAE for a subject. The monitor also kept track of the cumulative embolic air volumes and alerted the anaesthetists once a predefined clinically significant embolic air volume was reached. As both humans and dogs share similar physiological conditions, our monitor for dogs are expected to be applicable to humans.published_or_final_versio

Effects of repetitive SSVEPs on EEG complexity using multiscale inherent fuzzy entropy

© 2019 Elsevier B.V. Multiscale inherent fuzzy entropy is an objective measurement of electroencephalography (EEG) complexity, reflecting the habituation of brain systems. Entropy dynamics are generally believed to reflect the ability of the brain to adapt to a visual stimulus environment. In this study, we explored repetitive steady-state visual evoked potential (SSVEP)-based EEG complexity by assessing multiscale inherent fuzzy entropy with relative measurements. We used a wearable EEG device with Oz and Fpz electrodes to collect EEG signals from 40 participants under the following three conditions: a resting state (closed-eyes (CE) and open-eyes (OE) stimulation with five 15-Hz CE SSVEPs and stimulation with five 20-Hz OE SSVEPs. We noted monotonic enhancement of occipital EEG relative complexity with increasing stimulus times in CE and OE conditions. The occipital EEG relative complexity was significantly higher for the fifth SSVEP than for the first SSEVP (FDR-adjusted p < 0.05). Similarly, the prefrontal EEG relative complexity tended to be significantly higher in the OE condition compared to that in the CE condition (FDR-adjusted p < 0.05). The results also indicate that multiscale inherent fuzzy entropy is superior to other competing multiscale-based entropy methods. In conclusion, EEG relative complexity increases with stimulus times, a finding that reflects the strong habituation of brain systems. These results suggest that multiscale inherent fuzzy entropy is an EEG pattern with which brain complexity can be assessed using repetitive SSVEP stimuli

Estimating black hole masses of blazars

Estimating black hole masses of blazars is still a big challenge. Because of the contamination of jets, using the previously suggested size -- continuum luminosity relation can overestimate the broad line region (BLR) size and black hole mass for radio-loud AGNs, including blazars. We propose a new relation between the BLR size and $H_{\beta}$ emission line luminosity and present evidences for using it to get more accurate black hole masses of radio-loud AGNs. For extremely radio-loud AGNs such as blazars with weak/absent emission lines, we suggest to use the fundamental plane relation of their elliptical host galaxies to estimate the central velocity dispersions and black hole masses, if their velocity dispersions are not known but the host galaxies can be mapped. The black hole masses of some well-known blazars, such as OJ 287, AO 0235+164 and 3C 66B, are obtained using these two methods and the M - $\sigma$ relation. The implications of their black hole masses on other related studies are also discussed.Comment: 7 pages, invited talk presented in the workshop on Multiwavelength Variability of Blazars (Guangzhou, China, Sept. 22-24, 2010). To be published in the Journal of Astrophysics and Astronom

Global financial crisis and job satisfaction of atypical workers : the case of Taiwan

Author name used in this publication: Bih-Hearn Virginia LeeAuthor name used in this publication: David Fu-Keung Ip2010-2011 > Academic research: not refereed > Publication in policy or professional journalAccepted ManuscriptPublishe

Pre-merger Electromagnetic Counterparts of Binary Compact Stars

We investigate emission signatures of binary compact star gravitational wave (GW) sources consisting of strongly magnetized neutron stars (NSs) and/or white dwarfs (WDs) in their late-time inspiral phase. Because of electromagnetic interactions between the magnetospheres of the two compact stars, a substantial amount of energy will be extracted, and the resultant power is expected to be ∼1038-1044 erg s-1 in the last few seconds before the two stars merge, when the binary system contains a NS with a surface magnetic field 1012 G. The induced electric field in the process can accelerate charged particles up to the EeV energy range. Synchrotron radiation is emitted from energetic electrons, with radiative energies reaching the GeV energy for binary NSs and the MeV energy for NS-WD or double WD binaries. In addition, a blackbody component is also presented, and it peaks at several to hundreds keV for binary NSs and at several keV for NS-WD or double WD binaries. The strong angular dependence of the synchrotron radiation and the isotropic nature of the blackbody radiation lead to distinguishable modulation patterns between the two emission components. If coherent curvature radiation is presented, fast radio bursts could be produced. These components provide unique simultaneous electromagnetic signatures as precursors of GW events associated with magnetized compact star mergers and short gamma-ray bursts (e.g., GRB 100717)

Potential Landscape and Probabilistic Flux of a Predator Prey Network

Predator-prey system, as an essential element of ecological dynamics, has been recently studied experimentally with synthetic biology. We developed a global probabilistic landscape and flux framework to explore a synthetic predator-prey network constructed with two Escherichia coli populations. We developed a self consistent mean field method to solve multidimensional problem and uncovered the potential landscape with Mexican hat ring valley shape for predator-prey oscillations. The landscape attracts the system down to the closed oscillation ring. The probability flux drives the coherent oscillations on the ring. Both the landscape and flux are essential for the stable and coherent oscillations. The landscape topography characterized by the barrier height from the top of Mexican hat to the closed ring valley provides a quantitative measure of global stability of system. The entropy production rate for the energy dissipation is less for smaller environmental fluctuations or perturbations. The global sensitivity analysis based on the landscape topography gives specific predictions for the effects of parameters on the stability and function of the system. This may provide some clues for the global stability, robustness, function and synthetic network design