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

Generation of short hard X-ray pulses of tailored duration using a M\"ossbauer source

We theoretically investigate a scheme for generations of single hard X-ray pulses of controllable duration in the range of 1 ns - 100 ns from a radioactive M\"ossbauer source. The scheme uses a magnetically perturbed $^{57}$FeBO$_3$ crystal illuminated with recoilless 14.4 keV photons from a radioisotope $^{57}$Co nuclide. Such compact X-ray source is useful for the extension of quantum optics to 10 keV energy scale which has been spotlighted in recent years. So far, experimental achievements are mostly performed in synchrotron radiation facilities. However, tabletop and portable hard X-ray sources are still limited for time-resolved measurements and for implementing coherent controls over nuclear quantum optics systems. The availability of compact hard X-ray sources may become the engine to apply schemes of quantum information down to the subatomic scale. We demonstrate that the present method is versatile and provides an economic solution utilizing a M\"ossbauer source to perform time-resolved nuclear scattering, to produce suitable pulses for photon storage and to flexibly generate X-ray single-photon entanglement.Comment: 8 pages, 6 figure

Experimental Study on Side Resistance of Energy Pile in Winter-mode Operation

In the present work, the side resistance of an energy pile subjected to a significant number of thermal cycles in saturated Kaolin clay was investigated through small-scale pile tests, direct shear tests, and triaxial tests. Before applying compressive load, relative shearing displacement, or deviator stress, up to 36 cooling/heating cycles were performed on the soil-foundation interface and soil. The thermal cycle was below the average ground temperature in temperate zones to simulate the winter-mode operation. In small-scale pile tests, the long-term behavior of the pile was observed in terms of temperature distribution and pore water pressure in soil, and a 15% relative settlement criterion was adopted to define the failure load. In direct shear tests, failure is taken to correspond to the maximum shear stress attained, or shear stress at 10% relative shear displacement. In triaxial tests, failure is taken to correspond to the maximum deviator stress attained, or deviator stress at 15% axial strain. If soil is subjected to long-term temperature cycling, however, time plays an essential role in affecting mechanical performances. Therefore, under ambient temperature, a series of tests were carried out in direct shear tests and triaxial tests to analyze the effect of time of which is referred to as an aging influence. The results show that the pile subjected to temperature cycling has weaker side resistance than the isothermal pile tested at room temperature due to soil erosion by condensate water, but this is not the case for the soil-foundation interface in the direct shear test. In direct shear tests and triaxial tests, although the heating/cooling cycles induced the clay to have a significant contraction, the elapsed time of temperature cycling is the main factor for increasing the resistance to shear deformation

DEBT OVERHANG, FINANCIAL SECTOR DEVELOPMENT AND ECONOMIC GROWTH

This paper uses panel data of 20 high external debt countries selected from Asia and Latin-America to investigate the financial sector development-debt-growth nexus within the framework of an endogenous growth and financial development mechanism. First, we found that among 20 high external debt countries, the external debt-to-GDP ratio is significantly negatively correlated with economic growth rates, indicating that excessive debt is detrimental to the growth of an economy. Second, we introduced the simultaneous GMM equations between financial sector development and economic growth to evaluate the interaction effects among economic growth, external debt, and financial sector development. In empirical results, we find that the negative impact of high debt on growth appears to operate through a strong negative effect, in terms of compulsion to resort to financially repressive policies. In addition, we also find a two-way relationship between financial sector development and economic growth.Debt Overhang Hypothesis, Dynamic Panel Data, Dynamic GMM, Financial Sector Development, Economic Growth

Soft Methodology for Cost-and-error Sensitive Classification

Many real-world data mining applications need varying cost for different types of classification errors and thus call for cost-sensitive classification algorithms. Existing algorithms for cost-sensitive classification are successful in terms of minimizing the cost, but can result in a high error rate as the trade-off. The high error rate holds back the practical use of those algorithms. In this paper, we propose a novel cost-sensitive classification methodology that takes both the cost and the error rate into account. The methodology, called soft cost-sensitive classification, is established from a multicriteria optimization problem of the cost and the error rate, and can be viewed as regularizing cost-sensitive classification with the error rate. The simple methodology allows immediate improvements of existing cost-sensitive classification algorithms. Experiments on the benchmark and the real-world data sets show that our proposed methodology indeed achieves lower test error rates and similar (sometimes lower) test costs than existing cost-sensitive classification algorithms. We also demonstrate that the methodology can be extended for considering the weighted error rate instead of the original error rate. This extension is useful for tackling unbalanced classification problems.Comment: A shorter version appeared in KDD '1