Various scalp and hair disorders distress numerous people. Severe scalp hair disorders have an adverse effect on appearance, self-confidence, and quality of life. Therefore, early and exact diagnosis of various scalp hair disorders is important for timely treatment. However, conventional manual examination method is time-consuming, objective, and labor-intensive. The presented study proposes an intelligent healthcare platform for identifying severity levels of six common scalp hair disorders such as dryness, oiliness, erythema, folliculitis, dandruff, and hair loss. To establish a suitable scalp image classification model, we tested three deep learning models (ResNet-152, EfficientNet-B6, and ViT-B/16). Among the three tested deep learning models, the ViT-B/16 model exhibited the best classification performance with an average accuracy of 78.31%. In addition, the attention rollout method was applied to explain the decision of the trained ViT-B/16 model and highlight approximate lesion areas with no additional annotation procedure. Finally, Scalp checker software was developed based on the trained ViT-B/16 model and the attention rollout method. Accordingly, this proposed platform facilitates objective monitoring states of the scalp and early diagnosis of hairy scalp problems.

Natamycin, a polyene macrolide antifungal, has long been used as a food preservative and is the only Food and Drug Administration (FDA)-approved topical treatment for fungal keratitis. While its safety is supported by specific ergosterol interaction and minimal systemic absorption, current research mainly focuses on short-term effects, often overlooking long-term, developmental, and microbiome-related impacts. In food applications, questions remain about cumulative exposure and potential disruptions to gut microbiota. For ophthalmology, advanced delivery methods like nanocarriers and hydrogels enhance drug penetration but may alter pharmacokinetics and pose formulation challenges. Regulatory approvals have historically depended on established safe use and limited toxicological data, emphasizing the need for more systematic evaluations. Zebrafish (Danio rerio) represent a promising yet underutilized model for addressing significant gaps in research, particularly in the realms of microbiome studies, ocular health, developmental processes, and multigenerational effects. When paired with omics technologies, zebrafish facilitate comprehensive system-level mapping of drug-induced outcomes. This review consolidates existing evidence and positions zebrafish as a vital translational link between in vitro assays, mammalian models, and clinical practice. Additionally, it proposes a framework to ensure the effective and scientifically supported use of natamycin in both food and medicinal applications.

Savonius wind turbines are increasingly considered for urban and building-integrated applications, where installation near walls or structural boundaries is often unavoidable. Under such near-wall conditions, wall-induced flow modification can significantly degrade aerodynamic performance depending on the turbine–wall distance and wall orientation relative to the incoming flow. However, most existing flow-control devices have been designed for free-stream conditions and lack adaptability to wall-affected inflow. To address this, this study experimentally investigates the aerodynamic influence of a downstream wall and proposes a passive flow-responsive curtain–guide system to mitigate performance degradation. Results show that close wall proximity reduces power output by up to 21% due to flow blockage. However, the introduction of a passive flow-responsive guide enables autonomous stabilization of the curtain within the optimal range, yielding consistent peak power coefficient increases of 13%–36% regardless of wall orientation. Particle image velocimetry confirms that these gains arise from flow redirection and a flow-induced torque-balance mechanism. Overall, the proposed passive system provides a simple and robust strategy for urban and building-integrated Savonius wind energy applications.

Surface irregularities can substantially modify local hemodynamics within coronary arteries. This study experimentally investigated the influence of controlled grooved surface geometries on pulsatile flow characteristics using idealized coronary-type stenosis models. Four transparent models were fabricated, consisting of a smooth control and three grooved surfaces with increasing groove amplitudes. Time-resolved particle image velocimetry was employed to quantify phase-averaged velocity fields, recirculation structures, and turbulent kinetic energy (TKE). The results showed that groove-induced surface irregularities enhanced jet deflection, near-wall recirculation, and in-plane cross-stream motion compared with the smooth stenosis model. As groove amplitude increased, downstream jet deflection became more pronounced, indicating a redistribution of velocity fluctuations in the post-stenotic region. In contrast, the smooth stenosis sustained a longer and more coherent jet structure. Increased groove amplitude also reduced the downstream extent and magnitude of measured planar TKE. These findings demonstrate that even small-scale surface features can significantly alter post-stenotic flow structures and the spatial development of turbulence under coronary-relevant pulsatile flow conditions.