Meteor Radar Study of Ionospheric Wind at Kyoto

This paper describes the results of meteor radar observations which have been carried out at Kyoto University since December, 1977. The radar, a coherent pulse doppler radar with a transmitting frequency of 31.57 MHz and a nominal peak power of 10 kW, is able to detect wind fields at meteor regions of 80-110 km. The solar semidiurnal tide generally dominates the wind oscillations at these heights, while a diurnal tide of comparable magnitude reveals itself in a less regular manner. Some anomalies in the amplitude and phase characteristics of the tides are shown, which might be related to a possible interaction with winds and waves, or to some disturbed conditions in the earth's atmosphere. Also planetary scale waves such as quasi-2-day oscillations and resonantly magnified gravity-mode waves have also been found there. Hence, the meteor radar, together with its cooperation with other observations, will helps us understand the dynamical process of atmospheric waves on a global scale

Development of Convolutional Neural Networks for an Electron-Tracking Compton Camera

Electron-tracking Compton camera, which is a complete Compton camera with tracking Compton scattering electron by a gas micro time projection chamber, is expected to open up MeV gamma-ray astronomy. The technical challenge for achieving several degrees of the point spread function is the precise determination of the electron-recoil direction and the scattering position from track images. We attempted to reconstruct these parameters using convolutional neural networks. Two network models were designed to predict the recoil direction and the scattering position. These models marked 41$~$degrees of the angular resolution and 2.1$~$mm of the position resolution for 75$~$keV electron simulation data in Argon-based gas at 2$~$atm pressure. In addition, the point spread function of ETCC was improved to 15$~$degrees from 22$~$degrees for experimental data of 662$~$keV gamma-ray source. These performances greatly surpassed that using the traditional analysis

A statistical study of convective and dynamic instabilities in the polar upper mesosphere above Tromsø

We have studied the convective (or static) and dynamic instabilities between 80 and 100 km above Tromsø (69.6° N, 19.2° E) using temperature and wind data of 6 min and 1 km resolutions primarily almost over a solar cycle obtained with the sodium lidar at Tromsø. First, we have calculated Brunt–Väisälä frequency (N) for 339 nights obtained from October 2010 to December 2019, and the Richardson number (Ri) for 210 nights obtained between October 2012 to December 2019. Second, using those values (N and Ri), we have calculated probabilities of the convective instability (N2<0) and the dynamic instability (0≤Ri<0.25) that can be used for proxies for evaluating the atmospheric stability. The probability of the convective instability varies from about 1% to 24% with a mean value of 9%, and that of the dynamic instability varies from 4 to 20% with a mean value of 10%. Third, we have compared these probabilities with the F10.7 index and local K-index. The probability of the convective instability shows a dependence (its correlation coefcient of 0.45) of the geomagnetic activity (local K-index) between 94 and 100 km, suggesting an auroral infuence on the atmospheric stability. The probability of the dynamic instability shows a solar cycle dependence (its correlation coefcient being 0.54). The probability of the dynamic instability shows the dependence of the 12 h wave amplitude (meridional and zonal wind components) (C.C.=0.52). The averaged potential energy of gravity waves shows decrease with height between 81 and 89 km, suggesting that dissipation of gravity waves plays an important role (at least partly) in causing the convective instability below 89 km. The probability of the convective instability at Tromsø appears to be higher than that at middle/low latitudes, while the probability of the dynamic instability is similar to that at middle/low latitudes

Random regression for modeling soybean plant response to irrigation changes using time-series multispectral data

Plant response to drought is an important yield-related trait under abiotic stress, but the method for measuring and modeling plant responses in a time series has not been fully established. The objective of this study was to develop a method to measure and model plant response to irrigation changes using time-series multispectral (MS) data. We evaluated 178 soybean (Glycine max (L.) Merr.) accessions under three irrigation treatments at the Arid Land Research Center, Tottori University, Japan in 2019, 2020 and 2021. The irrigation treatments included W5: watering for 5 d followed by no watering 5 d, W10: watering for 10 d followed by no watering 10 d, D10: no watering for 10 d followed by watering 10 d, and D: no watering. To capture the plant responses to irrigation changes, time-series MS data were collected by unmanned aerial vehicle during the irrigation/non-irrigation switch of each irrigation treatment. We built a random regression model (RRM) for each of combination of treatment by year using the time-series MS data. To test the accuracy of the information captured by RRM, we evaluated the coefficient of variation (CV) of fresh shoot weight of all accessions under a total of nine different drought conditions as an indicator of plant’s stability under drought stresses. We built a genomic prediction model (MTRRM model) using the genetic random regression coefficients of RRM as secondary traits and evaluated the accuracy of each model for predicting CV. In 2020 and 2021,the mean prediction accuracies of MTRRM models built in the changing irrigation treatments (r = 0.44 and 0.49, respectively) were higher than that in the continuous drought treatment (r = 0.34 and 0.44, respectively) in the same year. When the CV was predicted using the MTRRM model across 2020 and 2021 in the changing irrigation treatment, the mean prediction accuracy (r = 0.46) was 42% higher than that of the simple genomic prediction model (r =0.32). The results suggest that this RRM method using the time-series MS data can effectively capture the genetic variation of plant response to drought

Thermal Infrared Imaging Experiments of C-Type Asteroid 162173 Ryugu on Hayabusa2

The thermal infrared imager TIR onboard Hayabusa2 has been developed to investigate thermo-physical properties of C-type, near-Earth asteroid 162173 Ryugu. TIR is one of the remote science instruments on Hayabusa2 designed to understand the nature of a volatile-rich solar system small body, but it also has significant mission objectives to provide information on surface physical properties and conditions for sampling site selection as well as the assessment of safe landing operations. TIR is based on a two-dimensional uncooled micro-bolometer array inherited from the Longwave Infrared Camera LIR on Akatsuki (Fukuhara et al., 2011). TIR takes images of thermal infrared emission in 8 to 12 μm with a field of view of 16×12∘ and a spatial resolution of 0.05∘ per pixel. TIR covers the temperature range from 150 to 460 K, including the well calibrated range from 230 to 420 K. Temperature accuracy is within 2 K or better for summed images, and the relative accuracy or noise equivalent temperature difference (NETD) at each of pixels is 0.4 K or lower for the well-calibrated temperature range. TIR takes a couple of images with shutter open and closed, the corresponding dark frame, and provides a true thermal image by dark frame subtraction. Data processing involves summation of multiple images, image processing including the StarPixel compression (Hihara et al., 2014), and transfer to the data recorder in the spacecraft digital electronics (DE). We report the scientific and mission objectives of TIR, the requirements and constraints for the instrument specifications, the designed instrumentation and the pre-flight and in-flight performances of TIR, as well as its observation plan during the Hayabusa2 mission

Plant viruses and viroids in Japan

An increasing number of plant viruses and viroids have been reported from all over the world due largely to metavirogenomics approaches with technological innovation. Herein, the official changes of virus taxonomy, including the establishment of megataxonomy and amendments of the codes of virus classification and nomenclature, recently made by the International Committee on Taxonomy of Viruses were summarized. The continued efforts of the plant virology community of Japan to index all plant viruses and viroids occurring in Japan, which represent 407 viruses, including 303 virus species and 104 unclassified viruses, and 25 viroids, including 20 species and 5 unclassified viroids, as of October 2021, were also introduced. These viruses and viroids are collectively classified into 81 genera within 26 families of 3 kingdoms (Shotokuvirae, Orthornavirae, Pararnavirae) across 2 realms (Monodnaviria and Riboviria). This review also overviewed how Japan’s plant virus/viroid studies have contributed to advance virus/viroid taxonomy