CLASSIFICATION OF BIPOLAR DISORDER, MAJOR DEPRESSIVE DISORDER, AND HEALTHY STATE USING VOICE

Objective: In this study, we propose a voice index to identify healthy individuals, patients with bipolar disorder, and patients with major depressive disorder using polytomous logistic regression analysis.Methods: Voice features were extracted from voices of healthy individuals and patients with mental disease. Polytomous logistic regression analysis was performed for some voice features.Results: With the prediction model obtained using the analysis, we identified subject groups and were able to classify subjects into three groups with 90.79% accuracy.Conclusion: These results show that the proposed index may be used as a new evaluation index to identify depression

High-Contrast Imaging of Intermediate-Mass Giants with Long-Term Radial Velocity Trends

A radial velocity (RV) survey for intermediate-mass giants has been operated for over a decade at Okayama Astrophysical Observatory (OAO). The OAO survey has revealed that some giants show long-term linear RV accelerations (RV trends), indicating the presence of outer companions. Direct imaging observations can help clarify what objects generate these RV trends. We present the results of high-contrast imaging observations of six intermediate-mass giants with long-term RV trends using the Subaru Telescope and HiCIAO camera. We detected co-moving companions to gamma Hya B (0.61+0.12 0.14 Stellar Mass), HD 5608 B (0.10 +/- 0.01 Stellar Mass), and HD 109272 B (0.28 +/- 0.06 Stellar Mass). For the remaining targets( Dra, 18 Del, and HD 14067) we exclude companions more massive than 30-60 M(sub Jup) at projected separations of 1-7. We examine whether these directly imaged companions or unidentified long-period companions can account for the RV trends observed around the six giants. We find that the Kozai mechanism can explain the high eccentricity of the inner planets Dra b, HD 5608 b, and HD 14067 b

Distinguish the Severity of Illness Associated with Novel Coronavirus (COVID-19) Infection via Sustained Vowel Speech Features

The authors are currently conducting research on methods to estimate psychiatric and neurological disorders from a voice by focusing on the features of speech. It is empirically known that numerous psychosomatic symptoms appear in voice biomarkers; in this study, we examined the effectiveness of distinguishing changes in the symptoms associated with novel coronavirus infection using speech features. Multiple speech features were extracted from the voice recordings, and, as a countermeasure against overfitting, we selected features using statistical analysis and feature selection methods utilizing pseudo data and built and verified machine learning algorithm models using LightGBM. Applying 5-fold cross-validation, and using three types of sustained vowel sounds of /Ah/, /Eh/, and /Uh/, we achieved a high performance (accuracy and AUC) of over 88% in distinguishing “asymptomatic or mild illness (symptoms)” and “moderate illness 1 (symptoms)”. Accordingly, the results suggest that the proposed index using voice (speech features) can likely be used in distinguishing the symptoms associated with novel coronavirus infection

Origin of the intense positive and moderate negative atmospheric electric field variations measured during and after Antarctic blizzards

There is an atmospheric electric field (AEF) or an electric potential gradient (PG) in fair weather between the Earth's surface and the mesosphere/ionosphere, which is positive. During blizzards/snowstorms in the polar regions, an intense positive AEF/PG in the order of 10(3)V/m of the same polarity in fair weather was observed using an electric field mill at 1.4 m in height. In contrast, a moderately negative AEF/PG variation after a blizzard was observed in 2015 at Syowa Station, Antarctica. The negative variation, where the magnitude ranged from tens to hundreds of V/m, gradually recovered into the positive AEF/PG for more than 40 min. According to various studies on blowing/drifting snow dynamics and electricity in laboratory experiments and field observations, snow particles colliding with the snow surface are charged, and the charge of suspended and saltating particles during the snowstorm is negative on average. To verify the AEF/PG observed during and after the blizzards, we numerically estimated the electric field surrounding the conductive sensor unit of the electric field mill using a three-dimensional Poisson equation. Under blizzard conditions, the polarity of the estimated AEF/PG was the opposite of that of the observed AEF/PG. From the noise study of the field mill, we deduced that the positive AEF/PG variations were caused by the collision of negatively charged snow particles with the electric probe on the sensor unit. Just after the blizzard, the number of snow particles measured at 4.4 m in height clearly decreased, and the camera image showed clear visibility. From this evidence, we modeled the suspended and saltating negatively charged snow particles that had fallen onto the ground surface and then constructed a charge layer of the snow particles softly attaching to the ground, which slowly discharged following the study on the electrical resistance of the powders. The three-dimensional Poisson calculation based on the model reproduced a moderately negative AEF/PG. Thus, we elucidated that the origins of the intense positive and moderate negative electric fields during and after blizzards are the charged snow particles colliding with the electric probe on the sensor unit and the negative snow layers softly attached to the ground, respectively. These results are applicable to studies on dust storm electrification on Mars' and Earth's deserts, snowstorm electrification in the polar regions, and high mountains, such as Mt. Fuji in Japan, and turbulent electrification for industrial dust, which provides the identification of intense electrification and storms

Origin of the intense positive and moderate negative atmospheric electric field variations measured during and after Antarctic blizzards

There is an atmospheric electric field (AEF) or an electric potential gradient (PG) in fair weather between the Earth's surface and the mesosphere/ionosphere, which is positive. During blizzards/snowstorms in the polar regions, an intense positive AEF/PG in the order of 10(3)V/m of the same polarity in fair weather was observed using an electric field mill at 1.4 m in height. In contrast, a moderately negative AEF/PG variation after a blizzard was observed in 2015 at Syowa Station, Antarctica. The negative variation, where the magnitude ranged from tens to hundreds of V/m, gradually recovered into the positive AEF/PG for more than 40 min. According to various studies on blowing/drifting snow dynamics and electricity in laboratory experiments and field observations, snow particles colliding with the snow surface are charged, and the charge of suspended and saltating particles during the snowstorm is negative on average. To verify the AEF/PG observed during and after the blizzards, we numerically estimated the electric field surrounding the conductive sensor unit of the electric field mill using a three-dimensional Poisson equation. Under blizzard conditions, the polarity of the estimated AEF/PG was the opposite of that of the observed AEF/PG. From the noise study of the field mill, we deduced that the positive AEF/PG variations were caused by the collision of negatively charged snow particles with the electric probe on the sensor unit. Just after the blizzard, the number of snow particles measured at 4.4 m in height clearly decreased, and the camera image showed clear visibility. From this evidence, we modeled the suspended and saltating negatively charged snow particles that had fallen onto the ground surface and then constructed a charge layer of the snow particles softly attaching to the ground, which slowly discharged following the study on the electrical resistance of the powders. The three-dimensional Poisson calculation based on the model reproduced a moderately negative AEF/PG. Thus, we elucidated that the origins of the intense positive and moderate negative electric fields during and after blizzards are the charged snow particles colliding with the electric probe on the sensor unit and the negative snow layers softly attached to the ground, respectively. These results are applicable to studies on dust storm electrification on Mars' and Earth's deserts, snowstorm electrification in the polar regions, and high mountains, such as Mt. Fuji in Japan, and turbulent electrification for industrial dust, which provides the identification of intense electrification and storms