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We report the detection of a giant planet orbiting a G-type giant star HD 167768 from radial velocity measurements using HIgh Dispersion Echelle Spectrograph (HIDES) at Okayama Astrophysical Observatory (OAO). HD 167768 has a mass of $1.08_{-0.12}^{+0.14} M_{\odot}$, a radius of $9.70_{-0.25}^{+0.25} R_{\odot}$, a metallicity of $\rm{[Fe/H]}=-0.67_{-0.08}^{+0.09}$, and a surface gravity of $\log g = 2.50_{-0.06}^{+0.06}$. The planet orbiting the star is a warm Jupiter, having a period of $20.6532_{-0.0032}^{+0.0032}\ \rm{d}$, a minimum mass of $0.85_{-0.11}^{+0.12}\ M_{\rm{J}}$, and an orbital semimajor axis of $0.1512_{-0.0063}^{+0.0058}\ \rm{au}$. The planet has one of the shortest orbital periods among those ever found around deeply evolved stars ($\log g < 3.5$) using radial velocity methods. The equilibrium temperature of the planet is $1874\ \rm{K}$, as high as a hot Jupiter. The radial velocities show two additional regular variations at $41\ \rm{d}$ and $95\ \rm{d}$, suggesting the possibility of outer companions in the system. Follow-up monitoring will enable validation of the periodicity. We also calculated the orbital evolution of HD 167768 b and found that the planet will be engulfed within 0.15\,Gyr., Accepted by Publications of the Astronomical Society of Japan, 9 pages, 7 figures, 2 tables

In this paper, we propose Car/Ride-Share (CRS), which is a new transportation service aiming at reducing the uneven distribution of cars in traditional carsharing service. The proposed service might be used as an alternative for buses in the case of congestion. In our model a car will depart from a bus stop at a university to a train station if there are a certain number of passengers (m) at the university who want to go to the station and one demand (e.g., a group of passengers) from the station to the university. The car will be taken over by the demand at the station and thus no parking lot is needed. We model the CRS service between the university and the train station by queueing model and analyze it using a GI/M/1-type Markov chain. Based on the analysis, we are able to find the optimal value of m which realizes the same mean waiting time while minimizing the operating cost of CRS. We also consider a price mechanism problem which gives a win-win solution for both passengers and CRS owners.

We describe the development of the practical manufacturing of Ensitrelvir, which was discovered as a SARS-CoV-2 antiviral candidate. Scalable synthetic methods of indazole, 1,2,4-triazole and 1,3,5-triazinone structures were established, and convergent couplings of these fragments enabled the development of a concise and efficient scale-up process to Ensitrelvir. In this process, introducing a meta-cresolyl moiety successfully enhanced the stability of intermediates. Compared to the initial route in the medicinal synthetic stage, the overall yield of the longest linear sequence (six steps) was improved by approximately 7-fold. Furthermore, nine out of the twelve isolated intermediates were crystallized directly from each reaction mixture without any extractive work-up (direct isolation). This led to an efficient and environmentally friendly manufacturing process that minimizes waste of organic solvents, reagents, and processing time. This practical process for manufacturing Ensitrelvir should contribute to protection against COVID-19.

We report the discovery of a triple-giant-planet system around an evolved star HD 184010 (HR 7421, HIP 96016). This discovery is based on observations from Okayama Planet Search Program, a precise radial velocity survey, undertaken at Okayama Astrophysical Observatory between 2004 April and 2021 June. The star is K0 type and located at beginning of the red-giant branch. It has a mass of $1.35_{-0.21}^{+0.19} M_{\odot}$, a radius of $4.86_{-0.49}^{+0.55} R_{\odot}$, and a surface gravity $\log g$ of $3.18_{-0.07}^{+0.08}$. The planetary system is composed of three giant planets in a compact configuration: The planets have minimum masses of $M_{\rm{b}}\sin i = 0.31_{-0.04}^{+0.03} M_{\rm{J}}$, $M_{\rm{c}}\sin i = 0.30_{-0.05}^{+0.04} M_{\rm{J}}$, and $M_{\rm{d}}\sin i = 0.45_{-0.06}^{+0.04} M_{\rm{J}}$, and orbital periods of $P_{\rm{b}}=286.6_{-0.7}^{+2.4}\ \rm{d}$, $P_{\rm{c}}=484.3_{-3.5}^{+5.5}\ \rm{d}$, and $P_{\rm{d}}=836.4_{-8.4}^{+8.4}\ \rm{d}$, respectively, which are derived from a triple Keplerian orbital fit to three sets of radial velocity data. The ratio of orbital periods are close to $P_{\rm{d}}:P_{\rm{c}}:P_{\rm{b}} \sim 21:12:7$, which means the period ratios between neighboring planets are both lower than $2:1$. The dynamical stability analysis reveals that the planets should have near-circular orbits. The system could remain stable over 1 Gyr, initialized from co-planar orbits, low eccentricities ($e=0.05$), and planet masses equal to the minimum mass derived from the best-fit circular orbit fitting. Besides, the planets are not likely in mean motion resonance. HD 184010 system is unique: it is the first system discovered to have a highly evolved star ($\log g < 3.5$ cgs) and more than two giant planets all with intermediate orbital periods ($10^2\ \rm{d} < P < 10^3\ \rm{d}$)., 20 pages, 5 figures, Published in PASJ

Tetrodotoxin (TTX) is a neurotoxic natural product that is an indispensable probe in neuroscience, a biosynthetic and ecological enigma, and a celebrated target of synthetic chemistry. Here, we present a stereoselective synthesis of TTX that proceeds in 22 steps from a glucose derivative. The central cyclohexane ring of TTX and its α-tertiary amine moiety were established by the intramolecular 1,3-dipolar cycloaddition of a nitrile oxide, followed by alkynyl addition to the resultant isoxazoline. A ruthenium-catalyzed hydroxylactonization set the stage for the formation of the dioxa-adamantane core. Installation of the guanidine, oxidation of a primary alcohol, and a late-stage epimerization gave a mixture of TTX and anhydro-TTX. This synthetic approach could give ready access to biologically active derivatives.

Power packets are proposed as a transmission unit that can deliver power and information simultaneously. They are transferred using the store-and-forward method of power routers. A system that achieves power supply/demand in this manner is called a power packet network (PPN). A PPN is expected to enhance structural robustness and operational reliability in an energy storage system (ESS) with recent diverse distributed sources. However, this technology is still in its early stage, and faces numerous challenges, such as high cost of implementation and complicated energy management. In this paper, we propose a novel power control based on decentralized algorithms for a PPN. Specifically, the power supply is triggered and managed by communications between power routers. We also discuss the mechanism of the decentralized algorithm for the operation of power packets and reveal the feasibility of the given control method and application by forming biased power flows on the consensus-based distribution.

We report the detection of radial velocity variations in nine evolved G- and K-type giant stars. The observations were conducted at Okayama Astrophysical Observatory. Planets or planet candidates can best explain these regular variations. However, a coincidence of near 280-day variability among five of them prevents us from fully ruling out stellar origins for some of the variations, since all nine stars behave similarly in stellar properties. In the planet hypotheses to the RV variations, the planets (including one candidate) may survive close to the boundary of the so-called "planet desert" around evolved stars, having orbital periods between 255 and 555 days. Besides, they are the least-massive giant planets detected around G- and K-type giant stars, with minimum masses between 0.45$M_{\rm{J}}$ and 1.34$M_{\rm{J}}$. We further investigated other hypotheses for our detection, yet none of them can better explain regular RV variation. With our detection, it is convinced that year-long regular variation with amplitude down to 15 $\rm{m\ s^{-1}}$ for G- and K-type giant stars is detectable. Moreover, we performed simulations to further confirm the detectability of planets around these stars. Finally, we explored giant planets around intermediate-mass stars, and likewise found a 4 Jupiter mass gap (e.g. Santo et al. 2017), which is probably a boundary of the giant planet population., 59 pages, 32 figures, 12 tables, accepted for publication in PASJ, all RVs will be available online as supplementary after the publication

Tetrodotoxin (TTX) is an indispensable probe in neuroscience, a biosynthetic and ecological enigma, and one of the most celebrated targets of synthetic chemistry. Here, we present a stereoselective synthesis of TTX that proceeds in 22 steps starting from a readily available glucose derivative. The central cyclohexane ring of TTX and its α-tertiary amine moiety was established via the intramolecular 1,3-dipolar cycloaddition of a nitrile oxide, followed by alkynyl addition to the resultant isoxazoline. After some carefully chosen protecting group manipulations, a ruthenium-catalyzed hydroxylactonization set the stage for the formation of its dioxa-adamantane core. Installation of the guanidine, oxidation of a primary alcohol, and late-stage epimerization of the resultant aldehyde gave a mixture of TTX and anhydro TTX. Our synthesis represents one of the most effective of TTX reported to date and could give ready access to biologically active derivatives.

Tetrodotoxin (TTX) is an indispensable probe in neuroscience, a biosynthetic and ecological enigma, and one of the most celebrated targets of synthetic chemistry. Here, we present a stereoselective synthesis of TTX that proceeds in 22 steps starting from a readily available glucose derivative. The central cyclohexane ring of TTX and its α-tertiary amine moiety was established via the intramolecular 1,3-dipolar cycloaddition of a nitrile oxide, followed by alkynyl addition to the resultant isoxazoline. After some carefully chosen protecting group manipulations, a ruthenium-catalyzed hydroxylactonization set the stage for the formation of its dioxa-adamantane core. Installation of the guanidine, oxidation of a primary alcohol, and late-stage epimerization of the resultant aldehyde gave a mixture of TTX and anhydro TTX. Our synthesis represents one of the most effective of TTX reported to date and could give ready access to biologically active derivatives.

Machine learning, applied to medical data, can uncover new knowledge and support medical practices. However, analyzing medical data by machine learning methods presents a trade-off between accuracy and privacy. To overcome the trade-off, we apply the data collaboration analysis method to medical data. This method using artificial dummy data enables analysis to compare distributed information without using the original data. The purpose of our experiment is to identify patients diagnosed with diabetes mellitus (DM), using 29,802 instances of real data obtained from the University of Tsukuba Hospital between 01/03/2013 and 30/09/2018. The whole data is divided into a number of datasets to simulate different hospitals. We propose the following improvements for the data collaboration analysis. (1) Making the dummy data which has a reality and (2) using non-linear reconverting functions into the comparable space. Both can be realized using the generative adversarial network (GAN) and Node2Vec, respectively. The improvement effects of dummy data with GAN scores more than 10% over the effects of dummy data with random numbers. Furthermore, the improvement effect of the re-conversion by Node2Vec with GAN anchor data scores about 20% higher than the linear method with random dummy data. Our results reveal that the data collaboration method with appropriate modifications, depending on data type, improves analysis performance.

In this research, we discuss Car/Ride-Share (CRS), which is a novel concept of Demand Responsive Transportation (DRT) aiming at reducing the uneven distribution of cars in traditional carsharing service and the congestion of cars and people. We model a scenario where CRS service is introduced between a spot (e.g., university, company, etc.) and its nearest train station by a bus company using queueing theory. Then, using an approximation model, we derive the probability density function of the required time (the sum of waiting and traveling times) for the customers considering the road congestion. Further, we show some numerical results of the distribution of the required time and discuss the effectiveness of CRS depending on road congestion. We confirm that the excessive introduction of CRS may be ineffective when the road is congested from the perspective of the required time.

Collecting large amounts of data is beneficial in machine learning to generate models that are less biased. There are many cases in which pieces of similar data are distributed among organizations, and it is difficult to integrate these data owing to issues involving privacy and cost. Integrating these distributed data without delivering the original data leads to the concept of data collaboration, which combines data held by different organizations in a secure manner. We propose a method in which a distance matrix of the original data obtained using common data among organizations is shared to learn neighbor information of the original data. Specifically, the proposed method robustly integrates distributed data, which is of as good quality as connected raw data, in cases where the amount of data in each organization is small and the data bias is large. In addition, the proposed method is applicable to data contaminated by noise. To demonstrate the effectiveness of the proposed method, we performed a classification task on open biological data divided into several pieces and found that the classification results for divided data were as precise as when all data were available. Finally, we show that the robustness of the method against noise improves the anonymity of the original data as a by-product.

Synthesis of a cis-decalin moiety, containing an oxa-bridged cis-decalin ring system (11-oxatricyclo(5.3.1.1,703,8)undecane), as a key intermediate of the total synthesis of luminamicin (1) was accomplished. One of the essential steps in our synthetic route is construction of a cis-decaline framework using a one-pot Michael addition-aldol reaction. Additionally, the bridged ether moiety was obtained by an intramolecular 1,6-oxa-Michael reaction of a conjugated aldehyde.

A power packet dispatching system is proposed to realize the function of power on demand. This system distributes electrical power in quantized form, which is called power processing. This system has extensibility and flexibility. Here, we propose to use the power packet dispatching system as the next generation power distribution system in self-established and closed system such as robots, cars, and aircrafts. This paper introduces the concept and the required researches to take the power packet dispatching system in practical phase from the total viewpoints of devices, circuits, power electronics, system control, computer network, and bio-inspired power consumption.

Power packet dispatching system is one of promising technologies for energy saving. To enhance this system, we propose an efficient algorithm for distributing power packets. As the first step, we consider the consensus dynamics in a network by assuming the state variable at each node as an amount of power. In addition, we assume that networks are switching, namely the topology of a network changes in time. These assumptions are effective for distributing power packets among power network systems in terms of decentralized control. We demonstrate numerical simulations for a small-scale network and discuss the results for an application to the power packet dispatching systems, such as variability of power storage at a node, control of power distribution over a network, and topology estimation from time series.

A power packet distribution network is expected to be one of the advanced power distribution systems, providing high controllability in both energy management and failure management. Regarding network operations, the power packet transmission is governed by switching operation within each of the routers. Here, the power distribution through power packets exhibits consensus-like dynamical behaviors. These features lead to the question of a consensus dynamics on switching topology and routing controls for appropriate power flows. Our approach to the above subjects is based on the dynamical modeling and the emulation of dynamics through the decentralized control of routers. The simulations on a ring-structure network, of the power distribution, reveal that the dynamical solution of the unbiased distribution is feasible via the decentralized control, while in the biased case, the result shows two behavioral fragments, which is quite different from the dynamical solution. In this discussion, we propose a decentralized algorithm that contains only fundamental functions for the packet transmission and is able to be redesigned or extended for further applications.

In this paper, we address the problem of reconstructing a time-domain signal (or a phase spectrogram) solely from a magnitude spectrogram. Since magnitude spectrograms do not contain phase information, we must restore or infer phase information to reconstruct a time-domain signal. One widely used approach for dealing with the signal reconstruction problem was proposed by Griffin and Lim. This method usually requires many iterations for the signal reconstruction process and depending on the inputs, it does not always produce high-quality audio signals. To overcome these shortcomings, we apply a learning-based approach to the signal reconstruction problem by modeling the signal reconstruction process using a deep neural network and training it using the idea of a generative adversarial network. Experimental evaluations revealed that our method was able to reconstruct signals faster with higher quality than the Griffin-Lim method.

Distributing power packets in a network is an efficient technique for supplying power to distributed loads. In the case that the amount of power is limited in a closed network system, the consensus algorithm can be useful for sharing the limited power resource in the system. For example, we consider a power network consisting of one power source and N(≫1) loads. We assume that each load has a buffer that can store the power for driving the load. It is important to efficiently share the limited power from the single source. One possible way for sharing power is as follows. First, all loads are divided into several clusters. Next, the power source sends power packets to each cluster by responding to the feedback information on how much power is required by the loads in the cluster. If the power demand of one load exceeds the power supply from the source, the deficient power is accommodated by the consensus algorithm among the buffers within the cluster. We discuss by numerical simulations how to cluster the loads in terms of the balance between the cost for distributing power from the source and the performance of loads.