Chuo University

In many countries and regions of Southeast Asia, meteorological observation networks remain sparse, and high-accuracy precipitation data with rapid latency which are crucial for disaster mitigation are still not operationally available. Existing satellite precipitation products include those from the Global Precipitation Measurement Mission (GPM), such as NASA IMERG, and the JAXA GSMaP products. However, the near-real-time versions IMERG Early Run, GSMaP NOW, and GSMaP NRT exhibit data latencies of approximately 4 h, 1 h, and 4 h, respectively. Moreover, their estimation accuracies differ, and the most rapid product, GSMaP NOW, still shows limitations even in the qualitative detection of heavy rainfall.Therefore, the objective of this study is to develop a near-real-time satellite precipitation product by integrating high-frequency infrared imagery from geostationary meteorological satellites with the GSMaP series. The datasets used include infrared imagery from the geostationary meteorological satellites Himawari‑8/9, microwave-based precipitation estimates from the GSMaP series, and elevation data derived from MERIT DEM. Precipitation estimation is performed using a deep-learning approach, in which infrared imagery, microwave precipitation data, and elevation data are used as input variables, and the output is a rainfall distribution with a spatial resolution of 2 km. The model is trained using meteorological radar data over Japan and subsequently applied to Southeast Asia.The estimated precipitation product has a spatial resolution of 2 km, a temporal resolution of 10 min, and a data latency of 1 h. The results demonstrate that the proposed product successfully reproduces the heavy rainfall event that occurred in southern Thailand in late November 2025 and outperforms the existing GSMaP products.

A bstract Holographic D-brane constructions, governed by the Dirac-Born-Infeld (DBI) action, play a central role in the AdS/CFT correspondence, particularly in applications to quantum chromodynamics and condensed matter systems. In this work, we demonstrate how to equip these bottom-up holographic models with dynamical boundary gauge fields, thereby introducing electromagnetic interactions into their dual field theory descriptions. As a direct application of this formalism, we compute the dispersion relations of the lowest quasinormal modes around both equilibrium and nonequilibrium steady states, and show that their behavior matches the predictions from hydrodynamics with dynamical U(1) symmetry.

Land use and land cover change (LULCC) constitutes a major challenge to sustainability worldwide. This also applies to Japan, where urbanization in coastal lowlands is contrasted with widespread agricultural abandonment in rural landscapes. In this systematic review we synthesized the main LULCC trajectories, their driving forces, and specific effects in Japan from 1994 to 2024. Following PRISMA guidelines, 158 peer-reviewed articles were analyzed using quantitative co-occurrence analyses, Chi-squared tests, and Sankey diagrams to map land-use flows. Two dominant and opposing trajectories were confirmed: urban expansion and agricultural abandonment. The most significant land transition flow involved the conversion of agricultural land to forests/natural vegetation, while the conversion of agricultural land to built-up areas came in second place. These transitions were primarily driven by economic and demographic factors, but reforestation trends were strongly influenced by policy and institutional factors (35.70%), reflecting national regreening initiatives. Ecological and biodiversity impacts of LULCC were the most often documented effects (>40% of records). While the published literature describes trends in land-use transformations, the mechanistic understanding of LULCC remains limited. There is an urgent need to move toward process-based predictive modeling that integrates socio-economic variables. Future policies should balance urban density management with the strategic use of rural abandonment for ecosystem services provision and climate mitigation.

In this work, we measure the infrared optical constants (n, κ) of topological insulator BiSb thin films using the reflectance-transmittance method. Using the obtained (n, κ), we reveal that Bi, Bi0.9Sb0.1, and Bi0.85Sb0.15 show absorption of about 30% for film thicknesses around 20 nm and a large refractive index ranging from 6 to 9 in the infrared region. Our results suggest that BiSb has strong potential as a material for MIR detectors.

Grinding with a disk grinder is an indispensable process in many workplaces, but dust exposure and vibration during operation can seriously affect workers’ health, creating a strong demand for automation. However, in non-routine grinding tasks, where the work environment and workpieces vary, fully automated operation has not yet been achieved. To address this issue, this study proposes a data collection system for the automation of non-routine grinding tasks that records and links the operator’s decisions and manipulations with the corresponding sensor information. In this paper, we focus on a grinding assist function as a key element of the proposed system. This function is required because it is not realistic for a human operator to finely adjust machining conditions in real time throughout the task, and its objective is to allow the machine side to autonomously maintain the machining conditions, including infeed, within an appropriate range. To realize this function, we focus on the acceleration acting on the disk grinder and monitor the total power of its spectrum during grinding. When the sum of the power spectrum shows a sudden increase, the state is regarded as resonant or self-excited vibration, and we propose a control logic that autonomously reduces the infeed in real time. A prototype grinding device was built, and experiments were conducted under conditions where the material removal gradually increased. The results demonstrate that the proposed logic can detect undesirable vibration, suppress the persistence of such vibration states, and restore a stable grinding condition.

This study explores the evolution of emotionality across small-group dynamics during an additional language (L+) classroom discussion at a Japanese university. Founded in analysis of a videorecording of Japanese students’ interactions in their L+ English, it examines the ways in which emotional togetherness arises through the actions of four learners. By employing a unique multimodal (pictorial) transcription and a narrative interpretation, the study evocatively captures how verbal and embodied cues collaboratively facilitate the emotional resonance of the group. The authors identify three primary mechanisms underpinning this shared emotionality: (1) the shift from English to the students’ native (i.e. Japanese) conversational style, marked by shorter, mutually-elaborative turns and increased aizuchi (backchanneling); (2) the instantiation of mutual transportable identities in the form of shared knowledge of popular culture, and; (3) the role of laughter in both expressing and confirming shared emotionality. While these factors appear to play a key role in the emergent outcome, the study clearly supports the need for more contextualized, dynamic research into the localized emergence and functions of group emotionality in additional language learning.

Adaptive handling of thick or composition-changing fluids is difficult for conventional pumps. In animals, the intestine addresses this challenge by switching between segmental mixing and peristaltic transport according to the physical state of the contents. We translate this principle into a silicone soft pump composed of four pneumatic chambers, each driven by its own phase oscillator. Two tunable factors govern the collective behaviour: (i) the coupling strength, which attempts to maintain neighbouring oscillators in a travelling-wave relationship, and (ii) the local sensor feedback, which forces each oscillator to correct the deformation error of its own chamber. Numerical bifurcation analysis and time-domain simulations show that when the two strengths are balanced within an intermediate range, the controller first generates an antiphase pattern that homogenises a viscous mixture, and then spontaneously shifts to a quarter-cycle travelling wave that drives the now-fluid contents downstream. We built a physical prototype and experimentally confirmed autonomous mode switching between two glycerol-based fluids of contrasting viscosity. These results demonstrate that a minimal, bioinspired, distributed controller can endow soft devices with adaptive, multifunctional pumping capability, thereby opening new routes to food-processing, biomedical, and chemical-handling systems that operate under uncertain conditions.