Japan is a super-aged society where community group multicomponent exercise is widely implemented, yet the age at which a fixed, low-frequency exercise dose no longer offsets functional decline is unclear. We examined 6-year trainability and explored "zero-change" ages in frail older women. Twenty community-dwelling frail women (80-86 years) participated in a once-weekly 90 min multicomponent exercise program for 6 years. Nine physical tests were assessed at baseline (Pre), 6 months, and annually. Overall time effects were tested using repeated-measures ANOVA and generalized estimating equations, with planned paired t-tests versus Pre. Age-specific annual percent changes (%/year) from Pre to each follow-up were annualized, grouped by age at follow-up (81-91 years), and tested against 0%/year. Separately, regression analyses related age to annual percent change across seven consecutive intervals to estimate "zero-change age" (predicted change = 0%). Time effects were significant for all nine measures (all p <= 0.032). Chair stand, 10 m fast/zigzag walk, supine-to-stand, maximal 5-step length, and 10-times knee lift generally improved in the early follow-up, whereas handgrip strength and sit-and-reach declined over time. In 6/9 tests, annual percent change diminished with advancing age; estimated zero-change ages ranged from approximate to 82 years (maximal 5-step length) to approximate to 88 years (chair stand and one-leg stance). Attendance remained high (approximate to 90%). In this single-arm community program, several mobility-related functions improved or were maintained in frail women in their early 80s, whereas reduced trainability beyond the mid-80s may limit further protection. Threshold ages are exploratory statistical estimates; controlled trials are warranted.
Diffusive motion is a fundamental transport mechanism in physical and biological systems, governing dynamics across a wide range of scales-from molecular transport to animal foraging. In many complex systems, however, diffusion deviates from classical Brownian behaviour, exhibiting striking phenomena such as Brownian yet non-Gaussian diffusion (BYNGD) and anomalous diffusion. BYNGD describes a frequently observed statistical feature characterised by the coexistence of linear mean-square displacement (MSD) and non-Gaussian displacement distributions. Anomalous diffusion, in contrast, involves a nonlinear time dependence of the MSD and often reflects mechanisms such as trapping, viscoelasticity, heterogeneity, or active processes. Both phenomena challenge the conventional framework based on constant diffusivity and Gaussian statistics. This review focuses on the theoretical modelling of such behaviour via the Langevin equation with fluctuating diffusivity (LEFD)-a flexible stochastic framework that captures essential features of diffusion in heterogeneous media. LEFD not only accounts for BYNGD but also naturally encompasses a wide range of anomalous transport phenomena, including subdiffusion, ageing, and weak ergodicity breaking. Ergodicity is discussed in terms of the correspondence between time and ensemble averages, as well as the trajectory-to-trajectory variability of time-averaged observables. The review further highlights the empirical relevance of LEFD and related models in explaining diverse experimental observations and underscores their value to uncovering the physical mechanisms governing transport in complex systems.
Deep learning-based image semantic segmentation techniques have made great strides in recent years. However, they still need large amounts of finely annotated image data, and generalizing the model from known classes to unknown ones remains a challenge. Most of the work on few-shot semantic segmentation techniques deals with the support set by directly utilizing images and masks for feature fusion. That tends to make the model not pay enough attention to the less-sample category, leading to missed detections. To alleviate this problem, in this paper, we propose the Region Select Enhancement Network, a novel structural model composed of base and meta learner, based on the perspective of metric learning and data enhancement. We employ an additional base learner to individually recognize targets within the base class, utilizing the recognition results of the base class as background-guided features for the final target. We then effectively fuse the outputs of the base learner and meta learner to produce accurate target images. Notably, unlike the common meta learner, we add a separate target category selection enhancement branch to the meta learner, augmenting the target features with known information from the support set. This further reduces background interference, thereby improving the model’s generalization ability. We conducted experiments on Cityscapes- 3^i , a few-shot outdoor dataset constructed from labeled images in the Cityscapes dataset, to validate the effectiveness of our method.
Design philosophy by Steven Holl shows his interest in the spatial experience aspect of architecture in the way people perceive space. This study focuses on the composition of spatial connections in 18 residential projects. The objective is to clarify the continuity of the living room through floor plan classification and matrix analysis, which is highly relevant in that it helps bridge the gap in understanding the functional and structural mechanisms inherent in architectural design theory, particularly in the projects. As a result, the residential projects can be classified into four categories in terms of continuity of living room, and it has a unique type of expression in their residential projects. This study is limited to analyzing only the first-floor plan and does not examine other drawings, such as sectional or elevation views, nor does it consider other residential projects. Therefore, the analysis has limitations. This study classified and discussed the continuity and spatial connections within the living room, thereby contributing to the discourse on design methodology in relation to architectural theory and phenomenology.
Thermoelectric materials have attracted attention for converting industrial waste heat into electricity, improving energy efficiency, and reducing environmental impact. While conventional thermoelectric materials operate at low to moderate temperatures ( ≤ 500 °C), options for higher temperatures ( ≥ 700 °C) remain limited. Here, we explore weathered biotite (WB), a layered clay mineral, as a high-temperature thermoelectric. Recent experiments suggest notable performance at high temperature. However, the mechanisms governing transport in WB have not been clarified yet. In this study, we focus on electrical conductivity, emphasizing ionic conductivity. Using first-principles calculations and nudged elastic band analysis, we evaluate adiabatic migration barriers for interlayer ion diffusion. We find that, at equilibrium interlayer spacing, barriers are large. But they dramatically drop under moderate interlayer swelling. In particular, the barriers for K reach ∼0.4 eV. These results indicate the feasibility of ionic conduction in WB.
