National Institute of Technology, Numazu College

Abstract Neutrinos from supernovae, especially those emitted during the late phase of core collapse, are essential for understanding the final stages of massive star evolution. We have been dedicated to developing methods for the analysis of neutrinos emitted during the late phase and observed at Super-Kamiokande (SK). Our previous studies have successfully demonstrated the potential of various analysis methods in extracting essential physical properties; however, the lack of background consideration has limited their practical application. In this study, we address this issue by incorporating a realistic treatment of the experimental signal and background events with the on-going SK experiment. We therefore optimize our analysis framework to reflect realistic observational conditions, including both signal and background events. Using this framework we study several long-time supernova models, simulating the late phase neutrino observation in SK and focusing in particular on the identification of the last observed event. We discuss the possibility of model discrimination methods using timing information from this last observed event.

Abstract We investigate the influence of the effective nucleon mass on the equation of state (EOS), which is constructed for simulations of core-collapse supernovae and binary neutron star mergers, within the relativistic mean-field (RMF) framework. The study introduces a new RMF parameter set, TM1m, which is a modification of the TM1e model with an adjusted effective mass, maintaining the saturation properties of nuclear matter. The TM1m model, with a larger effective mass ratio (M */M ~ 0.8) compared to the TM1e model (M */M ~ 0.63), is employed to construct a new EOS table, EOS5. This EOS table is designed to offer insights into the influence of the effective nucleon mass on the EOS within a relativistic framework, particularly above the saturation density. The results of EOS5 are compared with those obtained from other models, including both relativistic and nonrelativistic approaches. The properties of cold neutron stars, calculated using the TM1m model, are compatible with the existence of a 2 M ⊙ pulsar and the latest constraints on the tidal deformability and radii of a canonical 1.4 M ⊙ neutron star, derived from astrophysical observations.

In this paper, we have developed an Autonomous Mobile Robot (AMR) system to support independent and comfortable living for elderly individuals requiring mild to moderate care (Support Levels 1 and 2, and Care Level 1). The AMR integrates LiDAR-based environmental recognition technology and a ROS2-based control system, enabling autonomous navigation and obstacle avoidance. Additionally, it features voice command recognition and manual control via a game controller for more intuitive operation. A battery management system and a graphical user interface (GUI) have also been developed to enhance operational efficiency. Experimental validation was conducted in the ”Sanpo no Sumai” model room at the Pharma Valley Center, confirming the effectiveness of voice-commanded task execution. However, unstable behavior was observed in narrow or complex pathways, indicating the need for further refinement. At the CareTEX Tokyo exhibition, industry professionals provided valuable feed-back, highlighting key areas for improvement, including enhanced environmental recognition, improved voice command accuracy, simplified operation, and extended battery life. Future research will focus on optimizing power management, ensuring a safe and user-friendly design, and improving long-term operational stability. These enhancements are expected to make the AMR a more practical and reliable system, contributing to elderly independence and reducing caregiver workload.

Developing non-noble metal catalysts with excellent NH3 synthesis activity at mild conditions is a long-term objective. The reported best catalysts require either laborious multiple steps and controlled environments to fabricate the catalysts or high temperatures and long times to activate the catalysts. This work reports a facile one-pot method to fabricate carbon-based Ba-promoted Co catalysts via the citric acid sol-gel method using metal nitrates as precursors and water as the solvent, which allows the metal ions to be incorporated into the carbon framework homogeneously. The obtained (Ba/Co)0.3/C catalyst shows an outstanding NH3 synthesis activity of 34 mmol gcat−1 h−1 (350 oC, 1.0 MPa) with excellent stability. In-depth characterizations reveal that Ba exists as BaO, which is homogeneously distributed on the carbon framework and around the Co metal nanoparticles. We uncover that by retarding the BaCO3 formation in the fresh catalyst, the reduction temperature and time can be greatly decreased (485 oC/4 h), which is a fundamental advantage in this method. Density functional theory and molecular dynamics simulations indeed support the experimental observations. We anticipate that this facile and economical strategy will resolve the issues in a broad field of heterogeneous catalyst research.

The current understanding of the mechanism of core-collapse supernovae (CCSNe), one of the most energetic events in the universe associated with the death of massive stars and the main formation channel of compact objects such as neutron stars and black holes, is reviewed for broad readers from different disciplines of science who may not be familiar with the object. Therefore, we emphasize the physical aspects than the results of individual model simulations, although large-scale high-fidelity simulations have played the most important roles in the progress we have witnessed in the past few decades. It is now believed that neutrinos are the most important agent in producing the commonest type of CCSNe. The so-called neutrino-heating mechanism will be the focus of this review and its crucial ingredients in micro- and macrophysics and in numerics will be explained one by one. We will also try to elucidate the remaining issues.

A new analysis method for supernova model identification using supernova neutrino observations in Super-Kamiokande (SK) is developed. This new method uses information on late-phase neutrinos observed in SK, such as the duration of supernova neutrino and average neutrino energy. In this paper, we report the evaluation results of the supernova identification performance, demonstrating 90% or more in identification performance.

In recent years, Japan has become a hyper-aged society, and accidents caused by falls and stumbles of dementia patients have been increasing. In previous research, a motion monitoring support system using depth sensors has been developed to reduce these accidents. However, among the five available depth sensors, Kinect2 and RealSense D455/L515 are no longer in production and are difficult to obtain. Therefore, we introduced a new depth sensor, TEDTOF manufactured by Tokyo Electron Device, and implemented it in the existing system. Two image filters and one image processing were used to reduce noise in the distance image obtained from the TEDTOF. In addition, a comparison experiment was conducted to discriminate the patient's condition among the five depth sensors used in this study. The results showed that TEDTOF had the best recognition accuracy and RealSense L515 had the lowest recognition accuracy.

Creating biobased polymer blends with outstanding properties, nanoscale morphology, shape-memory capability, and biocompatibility is very crucial and requires a fundamental understanding of the phase behavior, macromolecular structure, and biological compatibility of the polymer blends with living cells. It is very critical to understand the complex relationships among the polymer structure, morphology, and performance of multifunctional smart materials under conditions that they are likely to encounter during use, particularly in biomedical applications. Biobased semi-interpenetrating polymer networks of poly(ε-caprolactone) and epoxidized soybean oil with nanoscale morphology have been successfully synthesized via in situ cationic polymerization and compatibilization in a homogeneous solution. Varies analytical and characterization techniques, such as Fourier transform infrared spectroscopy, differential scanning calorimetry, dynamic mechanical analysis, transmission electron microscopy, X-ray scattering, cell toxicity, and shape-memory effects (SMEs), have been employed to understand the structure–properties relationship of these smart, biobased nanostructured polymer blends. The synthesized nano blends were nontoxic or biocompatible and supported attachment of human vein endothelial cells, showing their potential use in biomedical applications. The current versatile, low-cost strategy for synthesizing the nanoscale morphology of semi-interpenetrating polymer networks with SMEs and biocompatibility should be widely applicable for polymer systems. This study is also considered as a continuation to our efforts in the area of biobased polymers to develop innovative technologies to transform natural resources into smart multifunctional materials for a wide range of applications, including coatings, adhesives, and medical devices.