SSL for Auditory ERP-Based BCI

A brain–computer interface (BCI) is a communication tool that analyzes neural activity and relays the translated commands to carry out actions. In recent years, semi-supervised learning (SSL) has attracted attention for visual event-related potential (ERP)-based BCIs and motor-imagery BCIs as an effective technique that can adapt to the variations in patterns among subjects and trials. The applications of the SSL techniques are expected to improve the performance of auditory ERP-based BCIs as well. However, there is no conclusive evidence supporting the positive effect of SSL techniques on auditory ERP-based BCIs. If the positive effect could be verified, it will be helpful for the BCI community. In this study, we assessed the effects of SSL techniques on two public auditory BCI datasets—AMUSE and PASS2D—using the following machine learning algorithms: step-wise linear discriminant analysis, shrinkage linear discriminant analysis, spatial temporal discriminant analysis, and least-squares support vector machine. These backbone classifiers were firstly trained by labeled data and incrementally updated by unlabeled data in every trial of testing data based on SSL approach. Although a few data of the datasets were negatively affected, most data were apparently improved by SSL in all cases. The overall accuracy was logarithmically increased with every additional unlabeled data. This study supports the positive effect of SSL techniques and encourages future researchers to apply them to auditory ERP-based BCIs

A Case of Giant Cystic Lymphangioma of the Retroperitoneal Origin.

A case of cystic lymphangioma of the retroperitoneal region was presented.Giant cystic mass,which was found in the left upper quadrant of the abdomen,exhibited particular roentogenologic signs simulating a large cyst arising from the tail of the pancreas,and was subsequently diagnosed as cystic lymphangioma upon histological examination.Presence of another congenital anomaly,duplication of the left renal pelvis and ureter,seemed to favour the embryonal theory for the causation of retroperitoneal cystic lymphangioma

Three-dimensional porous graphene networks expand graphene-based electronic device applications

In recent years, there has been increasing demand for 3D porous graphene structures with excellent 2D characteristics and great potential. As one avenue, several approaches for fabricating 3D porous graphene network structures have been proposed to realize multi-functional graphene materials with 2D graphene structures. Herein, we overview characteristics of 3D porous graphene for applications in future electronic devices along with physical insights into “2D to 3D graphene”, in which the characters of 2D graphene such as massless Dirac fermions are well preserved. The present review thus summarizes recent 3D porous graphene studies with a perspective for providing new and board applications of graphene in electronic devices

Distance determination of molecular clouds in the 1st quadrant of the Galactic plane using deep learning : I. Method and Results

Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as the distance to a molecular cloud. However, there is a problem in that for the inner Galaxy, two different solutions, the ``Near'' solution, and the ``Far'' solution, can be derived simultaneously. We attempted to construct a two-class (``Near'' or ``Far'') inference model using a Convolutional Neural Network (CNN), a form of deep learning that can capture spatial features generally. In this study, we used the CO dataset toward the 1st quadrant of the Galactic plane obtained with the Nobeyama 45-m radio telescope (l = 62-10 degree, |b| < 1 degree). In the model, we applied the three-dimensional distribution (position-position-velocity) of the 12CO (J=1-0) emissions as the main input. The dataset with ``Near'' or ``Far'' annotation was made from the HII region catalog of the infrared astronomy satellite WISE to train the model. As a result, we could construct a CNN model with a 76% accuracy rate on the training dataset. By using the model, we determined the distance to molecular clouds identified by the CLUMPFIND algorithm. We found that the mass of the molecular clouds with a distance of < 8.15 kpc identified in the 12CO data follows a power-law distribution with an index of about -2.3 in the mass range of M >10^3 Msun. Also, the detailed molecular gas distribution of the Galaxy as seen from the Galactic North pole was determined.Comment: 29 pages, 12 figure

Variety of the Wave Change in Compound Muscle Action Potential in an Animal Model

Study DesignAnimal study.PurposeTo review the present warning point criteria of the compound muscle action potential (CMAP) and investigate new criteria for spinal surgery safety using an animal model.Overview of LiteratureLittle is known about correlation palesis and amplitude of spinal cord monitoring.MethodsAfter laminectomy of the tenth thoracic spinal lamina, 2-140 g force was delivered to the spinal cord with a tension gage to create a bilateral contusion injury. The study morphology change of the CMAP wave and locomotor scale were evaluated for one month.ResultsFour different types of wave morphology changes were observed: no change, amplitude decrease only, morphology change only, and amplitude and morphology change. Amplitude and morphology changed simultaneously and significantly as the injury force increased (p<0.05) Locomotor scale in the amplitude and morphology group worsened more than the other groups.ConclusionsAmplitude and morphology change of the CMAP wave exists and could be the key of the alarm point in CMAP

Efficacy of Anal Needle Electrodes for Intraoperative Spinal Cord Monitoring with Transcranial Muscle Action Potentials

Study Design Retrospective study. Purpose To examine the relationship between postoperative bowel bladder disorder (BBD) and the efficacy of needle electrodes for the external anal sphincter (EAS) in intraoperative spinal cord monitoring with transcranial muscle action potentials (Tc-MsEP). Overview of Literature Spinal surgery for spina bifida, spinal cord tumor, and spinal tethered cord syndrome has a high rate of postoperative BBD. Monitoring of the EAS with Tc-MsEP is frequently performed during spinal surgery. We initially used plug-surface electrodes for this purpose, but have more recently switched to needle electrodes for the monitoring of the EAS. To date, there has been no comparison between the utility of these electrodes. Methods Waveform derivation, exacerbation of postoperative BBD, and sensitivity and specificity for prediction of BBD by 70% amplitude reduction of EAS activity using needle and plug-surface electrodes were investigated in 239 spine surgeries. The cut-off for the % drop in amplitude for BBD prediction was determined for EAS monitoring using a needle electrode. Results The overall rate of postoperative BBD aggravation was 7.1% (17/239 cases), with the individual rates using needle and plug-surface electrodes being 6.9% (8/116) and 7.3% (9/123), respectively. The waveform derivation rate was significantly higher using needle electrodes (91.3% [106/116] vs. 76.4% [94/123], p <0.01). In patients with baseline waveform detection, the sensitivity and specificity for postoperative BBD were similar in the two groups. With needle electrodes, a cutoff amplitude of Tc-MsEP for the EAS at the end of surgery of 25% of the baseline amplitude had a sensitivity of 89% and specificity of 82% for the prediction of postoperative BBD aggravation. Conclusions The significantly higher waveform derivation rate using needle electrodes suggests that these electrodes are effective for monitoring the EAS in spinal surgery in cases with preoperative BBD

Corrosion Behavior of SUS 304L Steel in pH 13 NaOH Solution

In order to investigate the corrosion behavior of SUS 304L steel in alkaline solutions, linear sweep voltammogram measurements were performed in NaOH solutions at pH 12 and 13 at 333 K. Constant potential electrolysis was carried out in an NaOH solution at 333 K at pH 13 from 5 to 20 hours. The surface analysis of the samples before and after the constant potential electrolysis was performed by atomic force microscopy, X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy. The XPS measurements of the samples before the electrolysis showed that Fe and Cr oxide films were formed on the SUS 304L stainless steel surface, and the presence of FeOOH, CrOOH and Ni(OH)2 on the surface was confirmed after the electrolysis. It is suggested that the dissolved metal ions from the SUS 304L surface reacted with OH− and formed a precipitated film on the surface in the alkaline environment