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.

     

Ultra-fast microwave aided synthesis of gold nanocages and structural maneuver studies

Gold nanocages (AuNcgs) are well-studied,hollow,metallic nanostructures that have fascinated researchers in the fields of nanotechnology,materials science,photoelectronics,biotechnology,and medical science for the last decade.However,the time-consuming synthesis of AuNcgs has limited their widespread use in materials science and nano-biotechnology.A novel,ultra-fast,simple,and highly convenient method for the production of AuNcgs using microwave heating is demonstrated herein.This quick method of AuNcg synthesis requires mild laboratory conditions for large-scale production of AuNcgs.The microwave heating technique offers the advantage of precise mechanical control over the temperature and heating power,even for the shortest reaction period (i.e.,seconds).Microwave-synthesized AuNcgs were compared with conventionally synthesized AuNcgs.Structural maneuver studies employing the conventionally produced AuNcgs revealed the formation of screw dislocations and a shift in the lattice plane.Detailed characterization of the microwave-generated AuNcgs was performed using high resolution transmission electron microscopy (HRTEM),scanning electron microscopy (SEM),X-ray powder diffraction (XRD),and spectroscopic techniques.     

Numerical simulation of molding-defect formation during resin transfer molding

The present study investigated a numerical simulation of molding-defect formation during resin transfer molding using boundary element method and line dynamics. The proposed method enables to simulate small molding defects by increasing the node for required position during time evolution; thereby, the method computes high-resolution flow front without being affected by the initial mesh geometry. The method was applied to the radial injection RTM with single inlet, and it was confirmed by comparison with theoretical value based on Darcy’s law that the flow advancement was computed with high accuracy. In addition, the method was also applied to the flow advancement for inclusion problem with cylinder, and four-point injection problem. The simulated flow behavior, void formation, and shrinkage agreed with the results in references. Finally, the method was compared with experiments using two-point injection problem. The computed configuration of the flow front and weld line agreed well with the experimental results.     

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide-field-of-view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low-temperature low-cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light-sensitive organic semiconductor and charge-trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m⁻²), along with a responsivity as high as 1.6 A W⁻¹ (wavelength = 465 nm) for a dark current of 0.24 A m⁻² (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high-resolution 3D organic semiconductor devices.     

Enzyme structure with two catalytic sites for double-sieve selection of substrate

High-fidelity transfers of genetic information in the central dogma can be achieved by a reaction called editing. The crystal structure of an enzyme with editing activity in translation is presented here at 2.5 angstroms resolution. The enzyme, isoleucyl-transfer RNA synthetase, activates not only the cognate substrate L-isoleucine but also the minimally distinct L-valine in the first, aminoacylation step. Then, in a second, "editing" step, the synthetase itself rapidly hydrolyzes only the valylated products. For this two-step substrate selection, a "double-sieve" mechanism has already been proposed. The present crystal structures of the synthetase in complexes with L-isoleucine and L-valine demonstrate that the first sieve is on the aminoacylation domain containing the Rossmann fold, whereas the second, editing sieve exists on a globular beta-barrel domain that protrudes from the aminoacylation domain.     

Clinical experience of functional electrical stimulation in complete paraplegia

In the Riordan (bridle) transfer, the posterior tibialis muscle as motor is routed through the interosseous membrane and anastomosed into a "bridle" formed by the distal tibialis anterior and peroneus longus muscles. In theory, the bridle provides inversion/eversion balance even if the transfer effects only tenodesis. However, the procedure has been criticized because its insertion is not into bone. This review analyzes the use of bridle transfer in flaccid paresis involving musculature innervated by the peroneal nerve. Surgery was performed 1 to 3 years after injury for patients with traumatic etiology. Ten patients are reviewed at 61 months' mean follow-up. Eight patients had traumatic peroneal nerve loss. Two had neuromuscular etiology. Evaluation included review of records, telephone interviews, and physical examinations. Data on functional status included walking barefoot running, need for bracing, return to duty, and patient satisfaction. Physical examination recorded ankle position and motions, gait findings, and results of static electromyograms. All patients were able to walk barefoot, but 6 of 10 had a mild to moderate limp. Five patients returned to running initially; only two were able to keep running. Nine patients were brace-free initially (polio sequela required bracing initially), and four others returned to bracing. Of these, two experienced an acute "tearing" and dorsiflexion loss, one sustained a prolonged gradual loss of dorsiflexion, and one sustained a contralateral cerebrovascular accident. Only three of seven patients returned to active duty, and one is on jump status. All patients were satisfied with their initial result. Only two patients had no detectable swing phase problems (both returned to active duty). Five patients had peroneal nerve exploration with repair or neurolysis; two of them sustained complete transections. Postoperative electromyograms showed insignificant, if any, nerve return. The Riordan transfer works well for neuromuscular flaccid paresis and in patients with peroneal nerve injuries with low demands. It may stretch out over time to the point of acute failure in patients with high demands. Concurrent peroneal nerve exploration and repair did not seem to be beneficial in this small study.     

Design of a memory‐based prefilter supplementing a robust PID control system

For systems with uncertainties, lots of PID parameter tuning methods have been proposed from the view point of the robust stability theory. However, the control performance becomes conservative using robust PID controllers. In this paper, a new two‐degree‐of‐freedom (2DOF) controller, which can improve the tracking properties, is proposed for nonlinear systems. According to the proposed method, the prefilter is designed as the PD compensator whose control parameters are tuned by the idea of a memory‐based modeling (MBM) method. Since the MBM method is a type of local modeling methods for nonlinear systems, PD parameters can be tuned adequately in an online manner corresponding to nonlinear properties. Finally, the effectiveness of the newly proposed control scheme is numerically evaluated on a simulation example. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Efficient blind dereverberation and echo cancellation based on independent component analysis for actual acoustic signals

This letter presents a new algorithm for blind dereverberation and echo cancellation based on independent component analysis (ICA) for actual acoustic signals. We focus on frequency domain ICA (FD-ICA) because its computational cost and speed of learning convergence are sufficiently reasonable for practical applications such as hands-free speech recognition. In applying conventional FD-ICA as a preprocessing of automatic speech recognition in noisy environments, one of the most critical problems is how to cope with reverberations. To extract a clean signal from the reverberant observation, we model the separation process in the short-time Fourier transform domain and apply the multiple input/output inverse-filtering theorem (MINT) to the FD-ICA separation model. A naive implementation of this method is computationally expensive, because its time complexity is the second order of reverberation time. Therefore, the main issue in dereverberation is to reduce the high computational cost of ICA. In this letter, we reduce the computational complexity to the linear order of the reverberation time by using two techniques: (1) a separation model based on the independence of delayed observed signals with MINT and (2) spatial sphering for preprocessing. Experiments show that the computational cost grows in proportion to the linear order of the reverberation time and that our method improves the word correctness of automatic speech recognition by 10 to 20 points in a RT??= 670 ms reverberant environment.