Design Strategies for Hydroxyapatite-Based Materials to Enhance Their Catalytic Performance and Applicability.

Hydroxyapatite (HAP) is a green catalyst that has a wide range of applications in catalysis due to its high flexibility and multifunctionality. These properties allow HAP to accommodate a large number of catalyst modifications that can selectively improve the catalytic performance in target reactions. To date, many studies have been conducted to elucidate the effect of HAP modification on the catalytic activities for various reactions.

Deep Learning-Based Stroke Volume Estimation Outperforms Conventional Arterial Contour Method in Patients with Hemodynamic Instability.

Although the stroke volume (SV) estimation by arterial blood pressure has been widely used in clinical practice, its accuracy is questionable, especially during periods of hemodynamic instability. We aimed to create novel SV estimating model based on deep-learning (DL) method. A convolutional neural network was applied to estimate SV from arterial blood pressure waveform data recorded from liver transplantation (LT) surgeries.