Abstract
The aim of this study was to identify and validate distinct patterns of vascular aging, focusing on a novel high-risk vascular aging (HRVA) cluster. Key biomarkers such as aortic pulse wave velocity, glycated hemoglobin, pulse pressure, and advanced glycation end-products were used to enhance cardiovascular risk stratification and explore implications for targeted interventions. Data from multiple studies were integrated, and K-means clustering identified three vascular aging patterns: healthy vascular aging (HVA), early vascular aging (EVA), and high-risk vascular aging (HRVA). ROC analysis determined optimal thresholds for key biomarkers. ANOVA and Chi-square tests evaluated differences and associations across clusters, supported by contingency tables and residual analysis. The HRVA cluster exhibited significantly elevated biomarker levels compared to the HVA and EVA clusters. Statistically significant differences were observed across clusters (p <=\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\le $$\end{document} 0.001), confirmed by ANOVA. Chi-square tests revealed strong associations between cluster membership and categorical variables, further validating the distinct profiles. The HRVA group demonstrated a particularly high risk of adverse cardiovascular events, emphasizing the clinical relevance. The identification of the HRVA cluster provides new insights into vascular aging, suggesting the need for intensive, personalized interventions. Future research should focus on validating these clusters longitudinally and exploring genetic, environmental, and lifestyle factors to improve cardiovascular outcomes.

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Maintaining frequency stability is one of the biggest challenges facing future power systems, due to the increasing penetration levels of inverter-based renewable resources. This investigation experimentally validates the frequency provision capabilities of a real Polymer Electrolyte Membrane (PEM) hydrogen electrolyser (HE) using a power hardware-in-the-loop (PHIL) setup. The PHIL consists of a custom 3-level interleaved buck converter and a hardware platform for real-time control of the converter and conducting grid simulation, associated with the modelling of the future Iberian Peninsula (IP) and Continental Europe (CE) systems. The investigation had the aim of validating earlier simulation work and testing new responses from the electrolyser when providing different frequency services at different provision volumes. The experimental results corroborate earlier simulation results and capture extra electrolyser dynamics as the double-layer capacitance effect, which was absent in the simulations. Frequency Containment Reserve (FCR) and Fast Frequency Response (FFR) were provided successfully from the HE at different provision percentages, enhancing the nadir and the rate of change of frequency (RoCoF) in the power system when facing a large disturbance compared to conventional support only. The results verify that HE can surely contribute to frequency services, paving the way for future grid support studies beyond simulations.

Abstract
This work focuses on designing nonlinear control algorithms for dual half-bridge converters (DHBs). We propose a two-layer controller to regulate the current and voltage of the DHB. The first layer utilizes a change in the control variable to obtain a quasi-linear representation of the DHB, allowing for the application of simple linear controllers to regulate current and power flow. The second layer employs a nonlinear control allocation algorithm to select control actions that fulfill (pseudo) power setpoints specified by the first control layer; it also minimizes peak-to-peak currents in the DHB and enforces voltage balance constraints. We apply the DHB and this new control strategy to manage power flow in a hybrid energy storage system comprising of a battery and supercapacitors. Numerical simulation results demonstrate that, in comparison with state-of-the-art approaches, our control algorithm is capable of maintaining good transient behavior over a wide operating range, while reducing peak-to-peak current by up to 80%.

Abstract