Simple method of determining plasma impedance of streamer discharge in atmospheric air

For atmospheric streamer discharges using a lightning impulse generator, we demonstrate a method of determining the plasma impedance in a streamer region by analyzing the periodic attenuated discharge waveforms having high-frequency components. When the streamer region in the plasma can be treated as an equivalent series circuit model including resistance and inductance elements, the regression waveforms obtained by reducing and smoothing the discharge waveforms are analyzed in the equivalent circuit. We found that the streamer resistance increased exponentially with time after the discharge, whereas the streamer inductance and series impedance were constant at 4.0 Ω for longer than the first period of the discharge waveforms. Moreover, the slope of the regression curve increases more rapidly for the positive streamer resistance than for the negative resistance. Finally, the absolute values of the streamer impedance versus time were 3.3-19 Ω and 3.5-9.0 Ω for positive and negative discharges, respectively.     

The Visual Computing of Projector‐Camera Systems

This article focuses on real‐time image correction techniques that enable projector‐camera systems to display images onto screens that are not optimized for projections, such as geometrically complex, coloured and textured surfaces. It reviews hardware‐accelerated methods like pixel‐precise geometric warping, radiometric compensation, multi‐focal projection and the correction of general light modulation effects. Online and offline calibration as well as invisible coding methods are explained. Novel attempts in super‐resolution, high‐dynamic range and high‐speed projection are discussed. These techniques open a variety of new applications for projection displays. Some of them will also be presented in this report.     

Link Prediction based on Structural Properties of Online Social Networks

Question-Answering Bulletin Boards (QABB), such as Yahoo! Answers and Windows Live QnA, are gaining popularity recently. Questions are submitted on QABB and let somebody in the internet answer them. Communications on QABB connect users, and the overall connections can be regarded as a social network. If the evolution of social networks can be predicted, it is quite useful for encouraging communications among users. Link prediction on QABB can be used for recommendation to potential answerers. Previous approaches for link prediction based on structural properties do not take weights of links into account. This paper describes an improved method for predicting links based on weighted proximity measures of social networks. The method is based on an assumption that proximities between nodes can be estimated better by using both graph proximity measures and the weights of existing links in a social network. In order to show the effectiveness of our method, the data of Yahoo! Chiebukuro (Japanese Yahoo! Answers) are used for our experiments. The results show that our method outperforms previous approaches, especially when target social networks are sufficiently dense.

Transflective IPS‐LCD with improved reflective contrast ratio

Abstract— In order to improve the reflective contrast ratio of transflective IPS‐LCDs, a novel pixel design for a normally white reflective IPS has been proposed. In this design, the large‐inter‐electrode‐spacing layout using a novel driving method and a double‐layered electrode have effectively reduced the light leakage. By applying these two technologies, a transflective IPS‐LCD has been successfully demonstrated with a high contrast ratio (15:1) in the reflective mode and a wide‐viewing‐angle characteristic in the transmissive mode.     

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data.

     

Revolving Vernier Mechanism Controls Size of Linear Homomultimer

A new kind of the Vernier mechanism that is able to control the size of linear assembly of DNA origami nanostructures is proposed. The mechanism is realized by mechanical design of DNA origami, which consists of a hollow cylinder and a rotatable shaft in it connected through the same scaffold. This nanostructure stacks with each other by the shape complementarity at its top and bottom surfaces of the cylinder, while the number of stacking is limited by twisting angle of the shaft. Experiments have shown that the size distribution of multimeric assembly of the origami depends on the twisting angle of the shaft; the average lengths of the multimer are decamer, hexamer, and tetramer for 0°, 10°, and 20° twist, respectively. In summary, it is possible to affect the number of polymerization by adjusting the precise shape and movability of a molecular structure.     

Fetal heart rate patterns in postasphyxiated fetal lambs with brain damage

OBJECTIVE: We previously showed that in asphyxiated fetal lambs the duration of hypotension correlated well with the severity of histologic damage to the brain, whereas the duration of bradycardia did not. This study compares fetal heart rate patterns with the degree of histologic damage to the brain. STUDY DESIGN: Twelve chronically instrumented near-term fetal lambs were subjected to asphyxia by umbilical cord occlusion until fetal arterial pH was <6. 9 and base excess was <-20 mEq/L. An additional 4 fetuses served as sham-asphyxia controls. Fetal heart rate (from electrocardiogram), arterial blood pressure, fetal breathing movements, and electrocorticogram were continuously monitored before, during, and for 72 hours after asphyxia. Fetal brain histologic features were categorized as mild (group 1, n = 5), moderate (group 2, n = 4), and severe (group 3, n = 3). Long-term fetal heart rate variability expressed as amplitude range was assessed visually every 5 minutes from 30 minutes before asphyxia until 2 hours of recovery and at 6, 12, 24, 48, and 72 hours of recovery. RESULTS: Long-term fetal heart rate variability amplitude decreased from 32 +/- 17 beats/min (mean +/- SEM) preocclusion to 4 +/- 13 beats/min at the end of occlusion (P <.001) without significant differences among the 3 groups. During 10 to 45 minutes of recovery, the long-term variability of group 1 was significantly greater than that of groups 2 and 3. At 24 to 72 hours of recovery, the long-term variability of groups 1 and 2 was significantly higher than that of group 3, which was almost 0. The "checkmark" and sinusoidal fetal heart rate patterns were observed during the recovery period in groups 2 and 3. CONCLUSIONS: Decreased long-term fetal heart rate variability and the "checkmark" and sinusoidal fetal heart rate patterns were indicators of the severity of asphyxial histologic damage in the fetal brain.