Ritsumeikan University

Female athletes frequently experience lateral ankle sprains (LAS) during unilateral jump-landing activities and face a significant risk of recurrent ankle injury. LAS has been associated with reduced diaphragm contractility and altered breathing mechanics. The diaphragm and breathing mechanics are crucial for mitigating landing impact, which is typically impaired in individuals with LAS. Given this connection, innovative rehabilitation approaches that address dysfunctional breathing mechanics may be warranted. To date, no research has investigated associations between breathing mechanics and landing kinetics in adolescent female athletes with LAS. This study aimed to compare ground reaction force (GRF) and dynamic stability during a single-leg stabilization task between female athletes with a history of LAS who exhibited diaphragmatic breathing patterns and those who had dysfunctional breathing patterns. Case-control study. Two hundred eighty-three competitive female athletes with a previous history of LAS were recruited from middle school, high school, and Division I college teams. The Hi-Lo test was utilized to categorize participants as dysfunctional breathers or diaphragmatic breathers according to their breathing patterns. Each participant completed 3 trials of a single-leg drop-landing task. Normalized peak vertical and posterior GRF data were extracted, and the average loading rate was calculated from the normalized vertical GRF. The norm of the horizontal component of the GRF was used to calculate time to stabilization. Forty female athletes with LAS history (14.1%) were classified as diaphragmatic breathers, and 243 (85.9%) were classified as dysfunctional breathers. Female athletes with LAS history who exhibited dysfunctional breathing patterns demonstrated a greater peak posterior GRF (P = .01) and longer time to stabilization (P = .04) compared with those who had diaphragmatic breathing patterns. Dysfunctional breathing patterns may contribute to decreased dynamic stability and force attenuation capabilities during single-leg landing tasks following LAS. Assessing the biomechanical dimension of breathing patterns may help clinicians identify patient-specific impairments in individuals with LAS, particularly those with deficits in dynamic postural stability and force attenuation.

This paper investigates the length of the repeating decimal part when a fraction is expressed in decimal form. First, it provides a detailed explanation of how to calculate the length of the repeating decimal when the denominator of the fraction is a power of a prime number. Then, by factorizing the denominator into its prime factors and determining the repeating decimal length for each prime factor, the paper concludes that the overall repeating decimal length is the least common multiple of these lengths. Furthermore, it examines the conditions under which the repeating decimal length equals the denominator minus 1 and discusses whether such fractions exist in infinite quantity. This topic is connected to an unsolved problem posed by Gauss in the 18th century and is also closely related to the important question of whether cyclic numbers exist in infinite quantity.

Over the last two decades, substantial progress has been made in our understanding of the mechanisms of animacy recognition, the ability to detect the presence of living entities in the environment (Pavlova, 2012;Lorenzi and Vallortigara, 2021). This is conceivably one of the most vital abilities that an animal should possess, as it allows proper alertness toward probable interactions, or, more specifically, prompt identification of others as valuable social companions, mates, prey, or predators. We have understood that animacy detectors operate from the very beginning after birth (Bidet-Ildei et al., 2014;Di Giorgio et al., 2017) and we have started to elucidate the underlying mechanisms of some of these 'life detectors' (Buiatti et al., 2019;Kobylkov et a., 2024;Romagnano et al., 2024), mostly with respect to the selection of faces as well as face-like non-faces from similar patterns. The study of animacy is of broad interest because the brains of all vertebrates -and possibly also some invertebrates-seem to be predisposed to tell apart animate and non-animate entities. This basic, ontological ability to select animate entities has a profound impact on the development of the brain and mind.First and foremost, animacy detection mechanisms are the bricks for building up the social brain. A growing body of evidence suggests that the lack or delayed development of animacy detectors is ultimately associated with neurodevelopmental disorders such as autism spectrum disorders (Jones and Klin, 2013;Pavlova et al., 2017;Shultz et al., 2018;Di Giorgio et al., 2021;Lorenzi et al., 2019;Galli et al., 2025). Detection of animacy also sets the stage for recognition of agency (e.g., when agents exhibit motion which is reciprocally contingent in space and time; Lemaire et al., 2022), in other words, the understanding that an animate entity may possess social characteristics such as desires, beliefs and goals, a cognitive capacity commonly dubbed as "theory of mind". Intriguingly, the distinction between animate and non-animate objects is at the foundation of intuitive dualism and essentialism (Bloom, 2004). The animate-inanimate distinction is foundational because it is the earliest cognitive division that links animacy/agency to minds and kinds to hidden essences, from which intuitive dualism and essentialism naturally emerge. Again, some fascinating evidence has been collected in recent years for attenuated dualism and essentialism in people who show reduced expression (or over-expression) of animacy and agency detectors (Berent et al., 2022;Berent and Hooley, 2025). Implication for the origins of beliefs, in particular religious beliefs have been harassed with regards to the animate/inanimate distinction (Bloom, 2004;Girotto et al., 2014;Vallortigara, 2012). Dynamic signals from the body and faces substantially contribute to inferring social characteristics, for instance, recognizing familiar individuals. Lander and Bennets synthesize psychological research showing that identity recognition is not solely based on static features (e.g., face structure) but also on dynamic cues such as facial movements, body actions, and vocal dynamics. This is consistent with recent neurobiological evidence that dynamic faces are processed via a cortical pathway distinct from that used for static faces in the human brain (Prabhakar et al., 2025). In this Topic, Shen et al. suggest that understanding point-light biological motion processing benefits from analysis 'through the lens of animate motion processing ' in the context of how the life-detection system is hardwired in the brain. Setogawa et al. show that, alongside faces, evolutionary salient threats such as snakes are processed via a fast, subcortical pathway. While previous studies have emphasized the role of this pathway in coarse and fast processing of facial expression (Inagaki et al., 2023), they extend this framework by showing that subcortical-prefrontal circuits conserved between human and non-human primates are tuned to threatening animacy cues.By using mobile EEG recording techniques, Soto et al. found that body posture selectively modulates early visual cortical processing but does not alter higher-level face processing, suggesting the robustness of face-sensitive neural mechanisms across bodily states.In a nutshell, the work presented in this Research Topic nicely dovetails with and enriches the initial line of research on perceiving of animacy and inferring social signals. Yet we are far from understanding which mechanisms underlying the perception of animacy are common for animals and which of them are unique/specific for humans. Moreover, there is still a lack of cross-cultural, developmental (including healthy aging), and gender (a social construct reflecting social roles and norms)/sex (a biological construct). One of the most prominent assets for future studies seems to be the assessment of animacy processing in cross-disease clinical research that contributes to a fundamental understanding of animacy signals in typical development and their impairments.

A defining feature of circadian clocks that enables adaptation to Earth's rotation is their ability to sustain an approximately 24 h period with precision, regardless of environmental factors such as temperature. This remarkable reliability of circadian timing can be reconstituted in vitro using only three cyanobacterial clock proteins: KaiA, KaiB, and KaiC. In vivo circadian rhythms, however, are governed not only by this Kai protein-based oscillator but also by transcription-translation feedback loops and additional clock components. The contribution of the Kai protein-based circadian oscillator to the overall reliability of the in vivo circadian rhythm remains unclear. In this study, we compared over 20 KaiC period mutants with periods ranging from 15 to 60 h under in vitro and in vivo conditions. In both cases, the period was insensitive to environmental conditions, suggesting a compensatory mechanism independent of metabolic state or rhythm amplitude. The ATPase activity of KaiC, the pacemaker of the cyanobacterial circadian clock, exhibited a stronger correlation with in vitro circadian frequency than in vivo circadian frequency. These results indicate that the KaiC ATPase-driven protein-based circadian oscillator inherently encodes a reliable circadian period independent of rhythm amplitude or environmental conditions. This intrinsic property likely plays a critical role in preserving the precision and stability of circadian timing in vivo while being influenced by the intracellular environment.

Volcanic hazard assessments are in part constrained by understanding the past behaviour of a volcano (e.g., eruptive frequency and magnitude), this is largely reconstructed using tephra deposits preserved proximal to source. However, these near-vent eruption records are often fragmentary and incomplete owing to burial and erosion processes, thus hampering the accuracy of hazard assessments. Here, we capitalise on the potential of long, undisturbed records of ash fall events preserved in East Asian marine and lacustrine sedimentary archives, typically positioned >100 km from volcanic sources, to plug the gaps in near-source eruption records. The extraction and identification of microscopic ash layers (cryptotephra) from sedimentary archives is adopted to provide important constraints on the timing of mid-intensity explosive eruptions, which are frequently under-reported at source.Following detailed cryptotephra investigations, we present a new eruption record captured by high-resolution sediment cores collected from the Sea of Japan spanning approximately the last 200,000 years. Detailed geochemical fingerprinting is used to assign tephra and cryptotephra deposits to volcanic source, and where possible to known eruption units, some of which are the target of zircon double-dating (ZDD). Furthermore, the chemical signatures are used to link the Sea of Japan tephra layers to those preserved in the precisely dated sediments of Lake Suigetsu (Honshu Island), providing important chronological constraints on our newly developed eruption record. Our investigations provide evidence of near-vent under-reporting of explosive eruptions and new insights into the repose periods between pre-historic eruptions at specific volcanoes.

Development of large-scale rock friction apparatus started around 2010 at National Research Institute for Earth Science and Disaster Resilience (NIED) in Japan (Fukuyama et al., 2014, NIED Rep.). Until now, three generations of the apparatus have already been developed, whose sliding area ranges from 1.5 m to 6.0 m in length. The purpose of this project was to investigate the rock frictional properties and earthquake rupture process at various sliding scales. There are two important characteristics in these apparatuses. One is that the nucleation zone size can be generated within the sliding fault area. The other is that the nucleation process can be spatially monitored by local strain measurement array installed close to the sliding surfaces. When nucleation zone is confined to the experimental fault surfaces, the whole rupture process from initiation to termination could be able to be observed in the experiments (Yamashita et al., 2026, EGU). Using these apparatuses, many kinds of large-scale rock friction experiments have been conducted. Through such experimental research, the following results have been reported. 1) The spatial distribution of strength on the fault surface is heterogeneous, which had not been properly considered by small-scale experiments (Yamashita et al., 2015, Nature). 2) Such spatial heterogeneity of strength on the fault surface could contribute to the fault-size dependence of macroscopic rock friction as well as the rich spectrum of rupture behaviors, which are quite important for the modeling of earthquake generation process (Xu et al., 2023, Nat. Geosci.). Especially, due to high-speed loading (~1 mm/s) and long-distance sliding (~40 cm), ten-decimeter-scale heterogeneity on the fault surface could be generated, which is found to play an important role in large-scale friction experiments (Yamashita et al., 2018, Tectonophys.). In addition to these spatially heterogeneous fault friction experiments, rupture propagation has been investigated in detail to investigate the fracture energy (Okubo et al., 2026, EGU; Matsumoto et al., 2026, EGU). In the near future, we expect that such large-scale rock friction experiments would contribute significantly to seismology, especially, physics of earthquake generation process, by establishing new constitutive law(s) of the rock friction through the usage of dense arrays of near-fault observations.

Image quality assessment (IQA) is a field that focuses on evaluating the quality of images, playing a crucial role in various image processing and/or computer vision applications. Traditional full-reference (FR) IQA algorithms struggle with an accurate perceptual quality evaluation due in part to their reliance on handcrafted features and simple mathematical functions to calculate the elementwise distance between the reference and distorted images. Although deep-learning-based FR IQA methods have shown advantages in providing a certain degree of tolerance to texture resampling, their performances are still limited by the redundant model parameters and ineffective quality-aware feature extraction/representation. To address this issue, in this paper, we propose a multi-modal dual-attention FR IQA algorithm based on combining a global-and-local image structure analysis with text information interpreted by the widely used large language model. Specifically, the proposed multi-modal dual-attention network consists of four modules. First, a global-and-local feature extraction module was employed to extract the quality-aware features from the reference and distorted images, which were then realigned along the spatial and channel dimensions by a feature fusion module. To take into account both the channel and spatial attentions and thus increase the model capacity in representing long-range dependencies among different image areas, a feature enhancement module was designed to encode the spatial information along two directions, based on which the direction-aware attention maps with position information were generated. Finally, the text prior knowledge interpreted by the contrastive language-image pre-training (CLIP) model was embedded to assist the attention-based prediction module for quality estimation. Experimental results on four benchmark datasets demonstrate the effectiveness of our model as compared with other state-of-the-art FR IQA methods. The code is available at https://vinelab.jp/m2da/.

Robotic systems operating in real-world environments often suffer from concept shift, where the input-output relationship changes due to latent environmental factors that are not directly observable. Conventional adaptation methods update model parameters, which may cause catastrophic forgetting and incur high computational cost. This paper proposes a latent Trend ID-based framework for few-shot adaptation in non-stationary environments. Instead of modifying model weights, a low-dimensional environmental state, referred to as the Trend ID, is estimated via backpropagation while the model parameters remain fixed. To prevent overfitting caused by per-sample latent variables, we introduce temporal regularization and a state transition model that enforces smooth evolution of the latent space. Experiments on a quantitative food grasping task demonstrate that the learned Trend IDs are distributed across distinct regions of the latent space with temporally consistent trajectories, and that few-shot adaptation to unseen environments is achieved without modifying model parameters. The proposed framework provides a scalable and interpretable solution for robotics applications operating across diverse and evolving environments.

ABSTRACT Financial constraints are a pervasive concern for consumers, shaping spending patterns and psychological coping mechanisms. While previous research has primarily focused on behavioral adaptations, this study explores a cognitive mechanism: thought suppression. We propose that consumers experiencing financial constraints intentionally suppress thoughts related to their financial difficulties and spending desires to alleviate psychological discomfort. However, consistent with the ironic process theory, this suppression may trigger a rebound effect, where suppressed thoughts resurface with greater intensity when external cues, such as sales promotions, are encountered. Across three longitudinal studies, we investigate how financial constraints impact suppression and the conditions under which rebound effects occur. Study 1 shows that financially constrained consumers suppress purchase‐related thoughts. Study 2 demonstrates that this suppression results from conscious effort and mediates the relationship between financial constraints and thought suppression. Study 3 reveals that suppressed thoughts resurface in response to sales promotions, particularly among consumers with high indulgence tendencies, resulting in a cognitive rebound effect. These findings contribute to the literature on financial constraints and thought suppression, offering practical insights for marketers.

Abstract We consider the zeta function associated with the time evolution matrix of a bipartite walk on a bipartite graph and derive a formula for its absolute zeta function. Furthermore, we give formulas for the absolute zeta functions of the zeta functions of the time evolution matrices of bipartite walks on the complete bipartite graph and an even cycle graph. As an application, we obtain formulas for the absolute zeta functions of the zeta functions of the Grover matrices of the complete bipartite graph and an even cycle graph.