Modeling photometric variations due to a global inhomogeneity on an obliquely rotating star: application to lightcurves of white dwarfs

We develop a general framework to compute photometric variations induced by the oblique rotation of a star with an axisymmetric inhomogeneous surface. We apply the framework to compute lightcurves of white dwarfs adopting two simple models of their surface inhomogeneity. Depending on the surface model and the location of the observer, the resulting lightcurve exhibits a departure from a purely sinusoidal curve that are observed for a fraction of white dwarfs. As a specific example, we fit our model to the observed phase-folded lightcurve of a fast-spinning white dwarf ZTF J190132.9+145808.7 (with the rotation period of 419s). We find that the size and obliquity angle of the spot responsible for the photometric variation are \dts \approx 60^\circ and \thetaS \approx 60^\circ or $90^\circ$, respectively, implying an interesting constraint on the surface distribution of the magnetic field on white dwarfs.Comment: 25 pages, 9 figures, accepted for publication in PAS

Preference Analysis Method Applying Relationship between Electroencephalogram Activities and Egogram in Prefrontal Cortex Activities : How to collaborate between engineering techniques and psychology

This paper introduces a method of preference analysis based on electroencephalogram (EEG) analysis of prefrontal cortex activity. The proposed method applies the relationship between EEG activity and the Egogram. The EEG senses a single point and records readings by means of a dry-type sensor and a small number of electrodes. The EEG analysis adapts the feature mining and the clustering on EEG patterns using a self-organizing map (SOM). EEG activity of the prefrontal cortex displays individual difference. To take the individual difference into account, we construct a feature vector for input modality of the SOM. The input vector for the SOM consists of the extracted EEG feature vector and a human character vector, which is the human character quantified through the ego analysis using psychological testing. In preprocessing, we extract the EEG feature vector by calculating the time average on each frequency band: θ, low-β, and high-β. To prove the effectiveness of the proposed method, we perform experiments using real EEG data. These results show that the accuracy rate of the EEG pattern classification is higher than it was before the improvement of the input vector

C. elegans PlexinA PLX-1 mediates a cell contact-dependent stop signal in vulval precursor cells

AbstractPLX-1 is a PlexinA transmembrane protein in Caenorhabditis elegans, and the transmembrane-type semaphorin, SMP-1, is a ligand for PLX-1. The SMP-1/PLX-1 system has been shown to be necessary for proper epidermal morphogenesis in the male tail and seam cells. Here, we show that the SMP-1/PLX-1 system also regulates vulval morphogenesis. In plx-1 and smp-1 mutants, hermaphrodites sometimes exhibit a protruding vulva or multiple vulva-like protrusions. Throughout the vulval development of plx-1 and smp-1 mutants, the arrangement of vulval cells is often disrupted. In the initial step of vulval morphogenesis, vulval precursor cells (VPCs) are generated normally but are subsequently arranged abnormally in mutants. Continuous observation revealed that plx-1 VPC fails to terminate longitudinal extension after making contact with neighbor VPCs. The arrangement defects of VPCs in plx-1 and smp-1 mutants are rescued by expressing the respective cDNA in VPCs. plx-1::egfp and smp-1::egfp transgenes are both expressed in all vulval cells, including VPCs, throughout vulval development. We propose that the SMP-1/PLX-1 system is responsible for a cell contact-mediated stop signal for VPC extension. Analyses using cell fate-specific markers showed that the arrangement defects of VPCs also affect cell fate specification and cell lineages, but in a relatively small fraction of plx-1 mutants

On the Characteristic Difference of Neoclassical Bootstrap Current and Its Effects on MHD Equilibria between CHS Heliotron/Torsatron and CHS-qa Quasi-Axisymmetric Stellarator

The characteristic difference of neoclassical bootstrap current and its effects on MHD equilibria are described for the CHS heliotron/torsatron and the CHS-qa quasi-axisymmetric stellarator. The direction of bootstrap current strongly depends on collisionality in CHS, whereas it does not in CHS-qa because of quasi-axisymmetry. In the CHS configuration, it appears that enhanced bumpy (Bs1) and sideband components of helical ripple (By1) play an important role in reducing the magnetic geometrical factor, which is a key factor in evaluating the value of bootstrap cuffent, and determining its polarity. The bootstrap current in CHS-qa is theoretically predicted to be larger than that in CHS and produces significant effects on the resulting rotational transform and magnetic shear. In the finite B plasmas, the magnetic well becomes deeper in both CHS and CHS-qa and its region is expanded in CHS. The existence of co-flowing bootstrap current makes the magnetic well shallow in comparison with that in currentless equilibrium

Method to Classify Matching Patterns between Music and Human’s Mood Using EEG Analysis Technique Considering Personality

In this paper we introduce a method to classify matching patterns between music and human mood using an electroencephalogram (EEG) analysis technique and considering personality. We analyse the EEG of the left prefrontal cortex by single-point sensing. The EEG recording device uses dry-type sensors. The feature vector is created by connecting the personality quantification results and the EEG features. Egograms—the Yatabe-Guilford personality inventory and a Kretschmer-type personality inventory are used to quantify personality. The EEG features are extracted using fast Fourier transform. Then, the matching patterns are classified using the k -nearest neighbour method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data

Preference Classification Method Using EEG Analysis Based on Gray Theory and Personality Analysis

This paper introduces a method to classify the preference patterns of sounds on the basis of an electroencephalogram (EEG) analysis and a personality analysis. We analyze the EEG of the left prefrontal cortex by single-point sensing. For EEG recording, a dry-type sensor and few electrodes were used. The proposed feature extraction method employs gray relational grade detection on the frequency bands of EEG and egogram. The gray relational grade is used for extracting the EEG feature. The egogram is extracted for quantifying the subject’s personality. The preference patterns generated when the subject is hearing a sound are classified using the nearest neighbor method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data. These results show that the accuracy rate of the preference classification using the proposed method is better than that using the method that does not to consider the subject’s personality

Preference Classification Method Using EEG Analysis Based on Gray Theory and Personality Analysis

This paper introduces a method to classify the preference patterns of sounds on the basis of an electroencephalogram (EEG) analysis and a personality analysis. We analyze the EEG of the left prefrontal cortex by single-point sensing. For EEG recording, a dry-type sensor and few electrodes were used. The proposed feature extraction method employs gray relational grade detection on the frequency bands of EEG and egogram. The gray relational grade is used for extracting the EEG feature. The egogram is extracted for quantifying the subject’s personality. The preference patterns generated when the subject is hearing a sound are classified using the nearest neighbor method. To show the effectiveness of the proposed method, we conduct experiments using real EEG data. These results show that the accuracy rate of the preference classification using the proposed method is better than that using the method that does not to consider the subject’s personality

Photo-excitation band-structure engineering of 2H-NbSe2_2 probed by time- and angle-resolved photoemission spectroscopy

We investigated the nonequilibrium electronic structure of 2H-NbSe$_2$ by time- and angle-resolved photoemission spectroscopy. We find that the band structure is distinctively modulated by strong photo-excitation, as indicated by the unusual increase in the photoelectron intensities around E$_F$. In order to gain insight into the observed photo-induced electronic state, we performed DFT calculations with modulated lattice structures, and found that the variation of the Se height from the Nb layer results in a significant change in the effective mass and band gap energy. We further study the momentum-dependent carrier dynamics. The results suggest that the relaxation is faster at the K-centered Fermi surface than at the $\Gamma$-centered Fermi surface, which can be attributed to the stronger electron-lattice coupling at the K-centered Fermi surface. Our demonstration of band structure engineering suggests a new role for light as a tool for controlling the functionalities of solid-state materials.Comment: 7 pages, 5 figure