Translation of EEG spatial filters from resting to motor imagery using independent component analysis.

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) often use spatial filters to improve signal-to-noise ratio of task-related EEG activities. To obtain robust spatial filters, large amounts of labeled data, which are often expensive and labor-intensive to obtain, need to be collected in a training procedure before online BCI control. Several studies have recently developed zero-training methods using a session-to-session scenario in order to alleviate this problem. To our knowledge, a state-to-state translation, which applies spatial filters derived from one state to another, has never been reported. This study proposes a state-to-state, zero-training method to construct spatial filters for extracting EEG changes induced by motor imagery. Independent component analysis (ICA) was separately applied to the multi-channel EEG in the resting and the motor imagery states to obtain motor-related spatial filters. The resultant spatial filters were then applied to single-trial EEG to differentiate left- and right-hand imagery movements. On a motor imagery dataset collected from nine subjects, comparable classification accuracies were obtained by using ICA-based spatial filters derived from the two states (motor imagery: 87.0%, resting: 85.9%), which were both significantly higher than the accuracy achieved by using monopolar scalp EEG data (80.4%). The proposed method considerably increases the practicality of BCI systems in real-world environments because it is less sensitive to electrode misalignment across different sessions or days and does not require annotated pilot data to derive spatial filters

Pseudomonas aeruginosa bacteremia in patients undergoing liver transplantation: An emerging problem

In our institution, Pseudomonas aeruginosa bacteremia appeared to occur with increasing frequency in patients undergoing liver transplantation. We thus conducted a prospective study to define risk factors and outcome in these patients. Over a 19-month period 6% of liver transplants were followed by Pseudomonas bacteremia. The mean age was 46 years (range, 24 to 67 years). The interval between transplantation and onset of bacteremia was 3 to 372 days (mean, 80). The incidence of Pseudomonas bacteremia in liver transplants was three times that of other transplants (heart, lung, kidney). Ninety one percent of infections were nosocomial. Polymicrobial bacteremia occurred in 30% of episodes. The portal of entry was respiratory in 30%, abdominal in 35%, and biliary in 13%. Four patients had recurrent Pseudomonas bacteremia: liver abscess (1), biliary obstruction (2), subhepatic abscess (1). Survival at 14 days was 70%. Survival rates were significantly lower for patients with hypotension, on mechanical ventilators, and increasing severity of illness (p < 0.05). Survival was higher when bacteremia occurred within the first 30 days after transplantation compared to after 30 days. A large number (43.4%) of Pseudomonas bacteremias occurred after transplant surgery or biliary tract manipulation, while the patient was receiving a prophylactic regimen of cefotaxime and ampicillin. P. aeruginosa is an important pathogen in the liver transplant recipient; prevention may be possible for a subgroup of patients with the use of prophylactic antibiotics with activity against P. aeruginosa

Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- ever, VAE using other types of spectral features such as mel- cepstral coefficients (MCCs), which are related to human per- ception and have been widely used in VC, have not been prop- erly investigated. Instead of using one specific type of spectral feature, it is expected that VAE may benefit from using multi- ple types of spectral features simultaneously, thereby improving the capability of VAE for VC. To this end, we propose a novel VAE framework (called cross-domain VAE, CDVAE) for VC. Specifically, the proposed framework utilizes both STRAIGHT spectra and MCCs by explicitly regularizing multiple objectives in order to constrain the behavior of the learned encoder and de- coder. Experimental results demonstrate that the proposed CD- VAE framework outperforms the conventional VAE framework in terms of subjective tests.Comment: Accepted to ISCSLP 201

Negotiation Style Comparisons by Gender among Greater China

As the economics within Greater China become more internally linked together, it becomes increasingly important to understand the nuances of each culture encompassed by this term. There is very little comparing the negotiation styles of Chinese who live in Taiwan, Hong Kong, and Mainland China among themselves. To fill the gap, the present research focuses on negotiations style comparison by gender among Chinese in Taiwan, Hong Kong, and Mainland China. The population was chosen from public companies listed under the stock markets. Data was collected using an online survey technique. SPSS was used to conduct data analyses, and a variety of statistical measures were used, including descriptive statistics and MANOVA, and coefficient alphas was reported for modified instruments in order to address reliability and validity of the instrument. The study found that only the factual negotiation style showed a significant relationship with gender among the three regions. The researcher suggests that the negotiators still need to be trained in body language, strategies, temper control, international manners, and customs. A better knowledge of negotiation should be helpful in understanding business and in realizing which negotiation styles are most appropriate for a particular country. The appropriate negotiation skills can bring more competitive advantages and benefits

Anisotropic electron-phonon coupling on a two-dimensional isotropic fermi contour [Gamma-bar] surface state of Be(0001)

Here, we studied an isotropic, free-electron-like 2D electronic band structure system--the Be(0001) [Gamma-bar] surface state. We revealed that the EPC on Be(0001) is anisotropic. Mass enhancement factors are closely related to the strength of the electron-phonon coupling (EPC). Large values of mass enhancement factors represent a strong EPC. For beryllium, the mass enhancement factors, [lambda], of the surfaces are large when compared with the bulk values. However, the reported values of [lambda] of the surfaces are inconsistent among the values obtained from different experiments or theories. One of the possible reasons is that [lambda] is strongly k -dependent. We did systematic measurements to understand that the inconsistency originated from the anisotropic nature of the EPC on the Be(0001) surface. The details of EPC are described by Eliashberg function (ELF) --so called coupling function. This function describes the coupling between the electron and phonon as a function of energy and momentum. To understand the EPC, ELF is required to be extracted from angle-resolved photoemission spectroscopy experimental data. With a set of extra-high quality data, we accurately extracted the ELF for the Be(0001) [Gamma-bar] surface state for the first time. With comparison to the measured bulk and surface phonon density of states, we found that the bulk phonon contributes to the high energy part of the ELF; while the surface phonon contributes to the low energy part of the ELF. The contribution from the surface phonon to [lambda] is found to be about 77%, equals to 0.72 out of the total value of 0.94. To quantitatively extract [lambda] we did simulations to understand the effects from the linear approximation used for analyzing data--from the energy and momentum resolutions in instruments and from the noise in the data.We concluded that (a) the linear approximation can work in a very wide range; (b) the momentum resolution plays a minor role in determining [lambda] ; (c) the energy resolution would severely distort the extracted dispersion near the Fermi energy and kink, hence, affecting the resulting [lambda] ; and (d) [lambda] is robust against the noise