Efficient Fine Arrhythmia Detection Based on DCG P-T Features.

Due to the high mortality associated with heart disease, there is an urgent demand for advanced detection of abnormal heart beats. The use of dynamic electrocardiogram (DCG) provides a useful indicator of heart condition from long-term monitoring techniques commonly used in the clinic. However, accurately distinguishing sparse abnormal heart beats from large DCG data sets remains difficult. Herein, we propose an efficient fine solution based on 11 geometrical features of the DCG PQRST(P-T) waves and an improved hierarchical clustering method for arrhythmia detection. Data sets selected from MIT-BIH are used to validate the effectiveness of this approach. Experimental results show that the detection procedure of arrhythmia is fast and with accurate clustering.

Enhancing subsurface multiphase flow simulation with Fourier neural operator.

Accurate numerical modeling of multiphase flow in subsurface oil and gas reservoirs is critical for optimizing hydrocarbon recovery. However, traditional physics-based algorithms face substantial computational hurdles due to the need for fine grid resolution and the inherent geological heterogeneity. To overcome these challenges, data-driven surrogate models solving the flow governing partial differential equations (PDEs) offer a promising alternative to enhance the efficiency of hydrocarbon production operations. In this study, we employ the Fourier Neural Operator (FNO) to extract spectral information from the reservoir properties, thereby facilitating the solution of coupled porous flow PDEs. Our focus is on two-phase flow dynamics, specifically exploring how water injection enhances reservoir pressure and displaces oil. This scenario involves solving a set of nonlinearly coupled PDEs with highly heterogeneous coefficients. Numerical results demonstrate that the developed FNO accurately predicts the reservoir pressure distributions. We further observe that the FNO's zero-shot super-resolution capability is sensitive to abrupt local changes in the reservoir pressure near injection and production wells. To enhance its accuracy, we propose a multi-fidelity FNO model that exhibits better adaptability across various grid configurations. After moderate training on graphics processing units (GPUs), the FNO achieves a speedup of three orders of magnitude compared to traditional numerical PDE solvers. Our experiments confirm the FNO's potential to replace repetitive physics-based simulations, significantly advancing computational efficiency in the uncertainty quantification of reservoir performance.

Effects of ibutilide on canine cardiac pacing threshold and on induction rates of atrial fibrillation.

This study aims to observe the effects of ibutilide on canine cardiac pacing threshold and on induction rates of atrial fibrillation. Eighteen mongrel dogs were anesthetized and administrated with ibutilide. The pacing thresholds and induction rates of atrial fibrillation were measured with and without ibutilide (10-min infusion dose was 0.10 mg kg(-1), followed by a maintaining dose of 0.01 mg min(-1) 30 min later). This study found that ibutilide increases pacing thresholds in dogs. Moreover, there were significant differences between pacing thresholds with and without ibutilide (P < 0.05). Further, ibutilide significantly reduces the induction rates of atrial fibrillation (P < 0.05). Our findings indicate that pacing voltage changes should be closely monitored in patients taking anti-arrhythmic drugs, who are treated with cardiac stimulation or have undergone pacemaker implantation. We also found that ibutilide is an effective drug in preventing or controlling atrial fibrillation.