This study introduces recent efforts of the Architectural Institute of Japan (AIJ) to develop guidelines for largeeddy simulation (LES) of pedestrian wind environments (PWEs). Reynolds-averaged Navier-Stokes (RANS) models have been widely used for predicting urban wind environments following best practice guidelines (BPGs) by Franke et al. [Int J Environ Pollut 44, 1-4 (2011)] and Tominaga et al. [J Wind Eng Ind Aerodyn 96 (10-11), 1749-1761 (2008)]. Although RANS models can predict mean wind velocity and some turbulence statistics based on empirical assumptions, LES provides higher accuracy in resolving transient turbulence structures larger than the grid scale. With increasing urbanization, understanding instantaneous complex wind and wind-related phenomena around buildings is essential for ensuring pedestrian wind comfort and safety. However, LES applications face challenges owing to a lack of BPGs. This study outlines key recommendations for simulation setups and post-processing, including domain size, building modeling, grid generation, boundary conditions, turbulence modeling, discretization, convergence criteria, and reliability evaluation. Additionally, new benchmark cases are provided to support validation for PWEs. The AIJ working group systematically evaluated LES performance across urban scenarios to ensure practical applicability while balancing computational costs. These guidelines aim to enhance prediction reliability, thereby contributing to the standardization of LES applications for PWE and advancement of computational wind engineering.
Mobile brain-body imaging (MoBI) using EEG and motion capture allows us to study brain activity during natural tasks. While MoBI research has focused on gait and walking, we introduce three-ball cascade juggling as a new paradigm to explore sensorimotor brain dynamics. Successful juggling depends on tracking ball trajectories to guide motor planning. Since jugglers emphasize the apex position during learning, we hypothesized that trial-to-trial variations in apex position relate to brain activity, particularly in superior parietal regions involved in spatial attention. Our findings support this: variations in apex position correlated with 10-15 Hz alpha and low beta power in sources compatible with superior parietal cortex. The precise frequency band and timing varied across the three spatial directions. Additionally, lateral apex variations were encoded in a mirror-symmetric manner relative to the body midline. This study demonstrates the feasibility of using MoBI to investigate brain dynamics in complex motor tasks and provides insight into how the brain represents the critical ball apex position, laying the foundation for future research on its role in motor control and catch timing.
Depression has increasingly become a serious public health issue, with students and working professionals often among the most affected. Academic demands and financial challenges have been identified as key stressors, and recent global surveys show a noticeable rise in depression rates among young people, partly due to heavier workloads and reduced social support. In this study, logistic regression is applied to perform binary classification of depressive tendencies using the publicly available “Playground Series S4E11” dataset from Kaggle. This dataset contains demographic details along with academic and psychological indicators. The analysis followed a structured process—covering data cleaning, feature transformation, and training of the logistic regression model. Evaluation of the model using accuracy, recall, and Receiver Operating Characteristic-Area Under Curve (ROC-AUC) produced scores of 84%, 88%, and 0.913, respectively. Among the input variables, suicidal thoughts, academic or work pressure, and financial stress were identified as the most influential indicators. These findings indicate that even relatively simple and transparent models can serve as effective tools for the early identification of depression. When incorporated into digital systems, such approaches could help deliver timely support within educational institutions and healthcare environments.
Emotions are inherently dynamic processes, often conceptualized through metaphors that convey movement and transformation, such as "anger rose" or "love blossomed." Previous research has centered on metaphorical cross-domain mappings of emotion nouns, but how those mappings differ across successive phases of an emotional experience remains largely unexplored. This study addresses this gap by analyzing metaphorical expressions in corpora to reveal the dynamic nature of emotional conceptualization. Adopting a "related-event approach," we investigate emotion nouns in Japanese and English corresponding to nine emotions (LOVE, FEAR, ANGER, SADNESS, HAPPINESS, PRIDE, SURPRISE, LUST, and SHAME). Examining metaphorical expressions that depict a sequence of mental movements - emergence, existence, intensification, and revelation - as well as their source concepts, we show that emotion metaphors differ significantly across these phases: Japanese tends to emphasize emergence and revelation, whereas English favors existence and intensification. Our findings shed light on the interaction of typological, cognitive, and cultural factors in shaping emotion concepts and provide a more fine-grained understanding of emotion dynamics across different languages. Future research could further illuminate other dynamic aspects of emotion, such as duration and variability, by using time-series data on emotion expressions.
We report an electrochromic (EC) device that uses a cellulose sheet as a coloration layer. Devices with an indium tin oxide (ITO)-nanoparticle (NP)-modified electrode showed an improved current response owing to the large surface area. In contrast, a poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT:PSS)-modified electrode enabled low-voltage operation and multicolor switching of the device. After the device operation, the cellulose layer was recovered and reassembled into a new device. This modular design enables a reversible color change with a reusable coloration layer, offering a sustainable strategy for paper-based electronics.
