In the non-terrestrial network (NTN) being considered for Beyond 5G (B5G), high-altitude platform systems (HAPS) and low earth orbit (LEO) satellites will be used as communication platforms. This paper proposes a feeder link in HAPS and LEO using the THz band from the viewpoint of high speed and high capacity. the THz band feeder link has the feature of ensuring link performance even in cloudy or light rain compared to free space optical (FSO). In this paper, the link budget is clarified by estimating the propagation loss under various weather conditions based on the ITU-R model and other models. Based on the results, throughput evaluation results for each modulation scheme are presented.

Boron dust particles were injected by an impurity powder dropper to improve plasma confinement and perform wall conditioning in the Large Helical Device. A fast-framing camera for monitoring dust particle trajectories in the peripheral plasma detected a change in the ablation positions of the dust particles depending on the plasma density and heating power. An analysis using a three-dimensional edge plasma simulation code (EMC3-EIRENE) and a dust transport simulation code (DUSTT) was applied to understand these observations. The simulations proved that the dust particle trajectories are more deflected toward the outboard side of the torus by the effect of the plasma flow in an upper divertor leg for higher plasma densities and higher plasma heating powers. The simulation successfully reproduced observations of the change in the ablation positions in the peripheral plasma.

The elasticity problem of plates with holes is a classic problem in structural engineering and has significant implications for various industrial applications. Traditional numerical methods, such as finite element (FEM) analysis, require substantial computational resources and expertise. To solve this problem, we propose an innovative approach, a physics-informed neural network (PINN) -based surrogate model for solving elasticity problems in plates with holes. By training the PINN model on a dataset generated from FEM simulations with plates of different holes, we achieve accurate predictions of the stress and deformation fields, eliminating the need for laborious FEM computations. Our results demonstrate that the PINN-based surrogate model offers a computationally efficient and reliable approach for analyzing plates with holes of various sizes.

The group-wise updating technique is one of the techniques for improving the accuracy of an approximate solution of Block Krylov subspace methods. This technique improves the accuracy of the approximate solution by grouping update terms of a recurrence relation. However, the number of update terms affects the performance of the Block Krylov subspace methods. This paper proposes a variable grouping strategy that does not fix the number of update terms to be grouped. Moreover, we incorporate the proposed strategy into the Block product-type iterative methods and evaluate its performance through numerical experiments.

The bending and twisting deformations of biopolymers have attracted considerable interests. In this paper, we propose a ladder-type polymer chain minimal model which describes DNA-like polymers’ bending and twisting elasticities within the framework of coarse-grained molecular dynamics simulation. Applying the model for a loop extrusion process, which introduces loop and twist on the chain, we obtained the stable twisted loop structures and observed the conversion between bend-elastic and twist-elastic energies. Moreover, we computed the linking number, a topological invariant for wound and twisted structures with fixed ends, and confirmed that the energy conversion proceeds under conservation of the linking number.

The strength of electromagnetic interaction between a relativistic beam and its surrounding environment in a particle accelerator can be characterized by the coupling impedance. Recently, the physics-informed neural networks (PINN) have been introduced into the impedance modeling in accelerator physics. Total-field (TF) and scattered-field (SF) formulations are available in calculating the coupling impedance with PINN. In this paper, direct comparison of the two PINNs based on the TF and SF formulations is presented with application to an elliptical vacuum chamber with practical geometry parameters. The numbers of iterations for the training processes and the accuracy of indirect space charge impedance are assessed for the two different PINNs in this comparison.

Sub-terahertz band from 100 GHz to 300 GHz has gained attention for many applications. The leaky wave antennas have been studied for sub-terahertz antenna for the requirement of high gain and beam scanning. The leaky wave antenna can change the beam direction by sweeping frequency. This paper presents the design method of the unit cell of sub-terahertz leaky wave antenna for the sidelobe reduction. The circular patch with the microstrip line is employed for the unit cell shape on dielectric substrate for the ease of fabrication. The unit cell can produce the leaky wave radiation and control the power of leaky wave per unit cell by adjusting the dimensions for sidelobe level reduction. The sub terahertz leaky wave antenna with 100-unit cell is demonstrated in the simulation. The simulation result shows the designed leaky wave antenna achieves beam scanning and sidelobe reduction with the operating frequency from 152-164 GHz.

Several studies have shown that when observing objects through binocular parallax virtual reality devices such as head-mounted displays (HMDs) and CAVE systems, observers perceive the size of virtual objects to be smaller than the size of real objects. The purpose of this study is to clarify this visual mechanism while taking into account the influence of individual differences in interpupillary distance. The three parameters that influence size perception are the interpupillary distance of the observer, the distance between the cameras that render the stereoscopic virtual space, and the distance between the lenses of the HMD. In this experiment, all of these values were adjusted to those of the participants. The results showed that regardless of the shape of the object, it was perceived to be approximately 7.7 to 11.1% smaller than its actual size. Furthermore, it was suggested that participants did not perceive the objects as smaller due to perceiving them at different distances. Instead, it was proposed that they might have perceived the objects as smaller, even though they perceived the distances to the objects somewhat accurately.

With the global outbreak of COVID-19, it is necessary to acquire social network structures that can achieve both infectious disease control and socio-economic activities. The purpose of this article is to exploratively reveal such network structures and to realize a method to obtain them. Our method consists of two steps. First, in order to survey which networks can achieve both two objectives, we conduct two simulations that model these phenomena on various networks, and investigate which network features are strongly related to these efficiencies. Next, we search for the optimal network structure using the genetic algorithm, whose evaluation function is set to the obtained features. From the results of the survey of network features, it was found that large clustering coefficients and small maximum eigenvalues of the adjacency matrix are important for the two objectives. For the problem set up to simulate actual changes in social network structure for infection control of COVID-19, optimization of these network features using the genetic algorithm was performed, and it was confirmed that our method can obtain network structures that achieve the two objectives in some cases.

Recently, much attention has been paid to the methods for circuit analysis using wavelet transform. In particular, we have proposed the method to analyze the nonlinear circuits using Haar wavelet transform. In this paper, we propose the method to analyze the steady-state periodic solutions of the nonlinear circuits with non-polynomial nonlinearity using Haar wavelet transform by applying simple deformation of nonlinear function, and confirm the effectiveness of the proposed method.

In nuclear medicine, assessing residual radioactivity before patient release is essential. It is typically assessed by radiation detection with a survey meter. This protocol inadvertently exposes to radiation and requires proficiency in the use of the survey meter. This study developed a mixed reality system designed to provide exposure-free training during patient release examination. This system involves a virtual radiation source with visualized radiation emission on the corresponding part of the human mannequin. The time response characteristics of the survey meter to changes with the time constant in addition to the source distance were simulated in realtime.

A magnetically semi-implicit finite-difference time-domain (FDTD) scheme based on the scattered-field formulation in cylindrical grids is presented. This semi-implicit FDTD scheme has a longitudinally zero-dispersion property and calculates only the electromagnetic field (wake field) scattered on the walls of an axially symmetric accelerator structure. As a result, the presented scheme does not include directly an ultra-relativistic bunch current in its formulation. This scheme is applied to the wake field simulation of a beam dechirper with a realistic model of bunch charge density. A linear chirp at the uniform part of the charge distribution is reproduced in this simulation. Dependencies of the dechiper length and the geometry parameters of rectangular corrugation on the wake potential are discussed in a parameter study with the presented FDTD scheme.

The dynamical network biomarker (DNB) theory detects early warning signals at the transition state (pre-disease state) in complex biological systems. The DNB theory has been applied to microarray data in several diseases. However, this theory has not yet been extensively to limited single-cell RNA sequencing (scRNA-seq) data. The main problem arises from missing values causing a standard deviation of zero, resulting in the calculation of correlation coefficients impossible in the DNB theory. The present study introduces pseudobulk and Gaussian noise to missing values in the scRNA-seq data to avoid division by zero. Without compromising the data characteristics, these two techniques detected previously missed genes for the DNB analysis and, thus, successfully expanded the scope of the DNB theory.

A thickness of cesium (Cs) layer on a plasma grid like ITER scaled negative ion source is estimated by using a physical model to control Cs distribution inside the negative ion source. It is found that it is important to take a plasma operation conditions such as duty into account, to understand the Cs behavior in the negative ion source.

Trees under power transmission lines effectively shield the human body from electric field exposure. We numerically analyze the electrostatically induced steady-state current that flows through the human body near a tree under three-phase transmission lines and quantitatively investigate the reduction ratio (RR) of the induced current owing to the tree. Stochastic tree models that consider the detailed shapes of branches and leaves are created by controlling the growth direction of the branches using random numbers. Moreover, we create simple-shaped tree models with dimensions similar to those of the stochastic tree models. Comparison of induced currents and RRs calculated using these tree models confirms that the simple-shaped tree model tends to overestimate the RR.

Among research of origin of life, vesicles are often studied as protocells. Fatty acids are synthesized abiotically, and their properties have been investigated as one of the most promising candidates for protocell membranes. Magnesium ions Mg²⁺ in particular are thought to have played an important role for ribozymes. However, it has been found that in the presence of magnesium ions, protocells of pure fatty acids cannot exist or retain its contents. In this study, we analyzed the response of fatty acid bilayers to Mg²⁺ using molecular dynamics simulations to elucidate the mechanism of vesicle destabilization. In the results, tighter packing of fatty acid molecules was shown. It was also found that adding Mg²⁺ causes attraction between ionized fatty acid molecules. These results suggest that the destabilization of fatty acid vesicles by Mg²⁺ may be due to pore formation by shrinkage of the outer leaflet of the vesicles.

The phase contrast image has higher sensitivity to materials with light elements than the conventional absorption contrast. The phase image is obtained by computer processing of the measured fringe image. The Fourier transform method is known as a method to obtain a phase image from a single fringe image. However, the method cannot produce images with high spatial resolution. In this study, we present a method to obtain phase images with high spatial resolution using machine learning.

In this study, we propose a new feedback control model for insect flight maneuverability, and conduct the numerical analysis using the proposed model. In the proposed model, the feedback control based on the observation for actual insects is introduced to the partitioned analysis model for the wing-body interaction, where the flapping wings and the surrounding air flow coupling is monolithically formulated using a finite element method such that the wing’s characteristic motions are simulated stably, while the one-way coupling from the wings to the body is used assuming a perturbation from the quasi-steady flight state. The roll control, on which we focus here, in our numerical result shows the good agreement with the body’s attitude control of an actual insect observed in the previous experiment. In our future work, we will elucidate a maneuverability mechanism of controlling body’s attitudes in insect flapping flight using the proposed model.

In X-ray irradiation, decreasing oxygen concentration correlates with a reduction in radiosensitivity. However, this effect is minimal in heavy ion irradiation due to the generation of oxygen along the ion track, called as the "oxygen in the heavy ion track hypothesis." We verified this hypothesis using Geant4-DNA by calculating oxygen generation and time change in distribution for 35 MeV/u and 200 MeV/u carbon ions, and 1 MeV electrons within a cell nucleus. The results showed, under hypoxic conditions (0% dissolved oxygen), the oxygen concentration increased to a maximum of 3.7% in a localized region around the track, persisting for about 100 ns after the penetration of 35 MeV/u carbon ion, while the increase for 1 MeV electrons was negligible. This finding supports the validity of the oxygen in the heavy ion track hypothesis.

The purpose of this study is to introduce a novel mobile Material Extrusion-based Additive Manufacturing (MEAM) machine designed to achieve complex and large scale fabrication without the constraints of size limitations. This is implemented by integrating a MEAM mechanism onto a multi-legged robot. This study also proposes methods for motion and material extrusion planning of the mobile MEAM machine and evaluates these methods through fundamental experiments. The results show that the accuracy of the fabrication is significantly dependent on the effectiveness of the motion planning and the accuracy of the robot control.

We are developing an Emergency Rescue Evacuation Support System (ERESS) to support evacuation in the occurrence of a localized disaster. This system automatically detects disasters quickly using only mobile terminals equipped with multiple sensors, such as smartphones, and provides real-time disaster information to disaster evacuees. In this paper, we propose a new disaster detection method that combines sensor information and human detection in order to improve the reliability of the detection method. The proposed method enhances the reliability of disaster occurrence detection and enables prompt notification of the occurrence of the disaster for disaster evacuees who are not facing the disaster. To demonstrate the effectiveness of the proposed method, we evaluate its performance through demonstration experiments.