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Background: The asymptomatic onset and extremely high mortality rate of aortic aneurysm (AA) highlight the urgency of early detection and timely intervention. The alteration of retinal vascular features (RVFs) can reflect the systemic vascular properties, and be widely used as the biomarker for cardiovascular disease risk prediction. Therefore, we aimed to investigate associations of RVFs with AA and its progression.

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Mixing different metal ions at the B site of ABX perovskites offers a promising approach for addressing challenges related to toxicity, stability and performance in optoelectronic applications. One such example is CsPbSnBr which addresses the toxicity issue posed by lead while allowing us to tune optoelectronic properties such as the band gap. In this work, nearly monodisperse CsPbSnBr quantum dots (QDs) were synthesized with variable Pb/Sn compositions, CsPbBr, CsPbSnBr and CsPbSnBr.

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Objective: This study investigated upper limb kinematics and muscle co-activation in wheelchair tennis players during the forehand stroke. By analyzing linear and angular kinematic variables alongside muscle co-activation patterns, the study aimed to provide insights into the biomechanical mechanisms supporting forehand stroke performance.

Method: Fifteen professional male wheelchair tennis players (height: 163.

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Climate change has exacerbated precipitation variability, profoundly impacting vegetation dynamics and community structures in arid ecosystems. There remains a notable knowledge gap regarding the ecological effects of altered precipitation on crassulacean acid metabolism (CAM) plants and their interactions with other photosynthetic types. This study investigated the response of the typical obligate CAM plant Orostachys fimbriata to extended watering intervals (WI4-WI8) and various competitive patterns (M-M) with the C grass Melilotus officinalis and the C grass Setaria viridis through greenhouse experiments.

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"Multimodal Sleep Signal Tensor Decomposition and Hidden Markov Modeling for Temazepam-Induced Anomalies Across Age Groups".

J Neurosci Methods

January 2025

School of Electrical and Computer Engineering, Gallogly College of Engineering, University of Oklahoma, Norman, OK 73019, USA.

Background: Recent advances in multimodal signal analysis enable the identification of subtle drug-induced anomalies in sleep that traditional methods often miss.

New Method: We develop and introduce the Dynamic Representation of Multimodal Activity and Markov States (DREAMS) framework, which embeds explainable artificial intelligence (XAI) techniques to model hidden state transitions during sleep using tensorized EEG, EMG, and EOG signals from 22 subjects across three age groups (18-29, 30-49, and 50-66 years). By combining Tucker decomposition with probabilistic Hidden Markov Modeling, we quantified age-specific, temazepam-induced hidden states and significant differences in transition probabilities.

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