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A radial basis probabilistic process neuron (RBPPN) and radial basis probabilistic process neural network (RBPPNN) model are proposed to fuse a priori knowledge for application to time-varying signal pattern classification. RBPPN inputs were multi-channel time-varying signals and a generalized inner product was used to perform spatio-temporal aggregation of input signals in the kernel. Typical signal samples from various pattern subsets in the sample set were used as kernel center functions, which use morphological distribution characteristics and combination relationships to implicitly express prior knowledge for the signal category. The exponential probability function was used as the activation function to achieve kernel transformation and RBPPN probability output. The RBPPNN is composed of process signal input layers, an RBPPN hidden layer, a pattern layer, and a Softmax classifier developed through stacking. Generalized inner product operations were used to conduct probability similarity measurements of distribution characteristics between process signals. The pattern layer selectivity summed inputs from the RBPPN hidden layer to the pattern layer according to the category of the kernel center function. Its outputs were then used as inputs in the Softmax classifier. The proposed RBPPNN information processing mechanism was extended to the time domain, and through learning time-varying signal training samples, achieved extraction, expression, and information association of time-varying signal characteristics, as well as direct classification. It can improve the deficiencies of existing neural networks, such as a complete large-scale training dataset is needed, and the information processing flow is complex. In this paper, the properties of the RBPPNN are analyzed and a specific learning algorithm is presented which synthesizes dynamic time warping, dynamic C-means clustering, and the mean square error algorithm. A series of 12-lead electrocardiogram (ECG) signals were used for classification testing of heart disease diagnosis results. The ECG classification accuracy across ten disease types was 75.52% and sinus arrhythmia was identified with an accuracy of 86.75%, verifying the effectiveness of the model and algorithm.

The construction of a high-order shape function is a key and difficulty for unstructured grid mesh and sliding boundary problems. In this paper, a construction method of space-time absolute nodal coordinate formulation quadrilateral cable (SACQ) is proposed, and the accuracy of the SACQ element is studied and verified with three different applications. First, the shape function of SACQ is constructed with spatiotemporal reduction coordinates, and the action integral of SACQ is composed with the Lagrangian function and discrete with perspective transformation. Second, the numerical convergence region is discussed and determined with the Courant number. Furthermore, a space-time nodal dislocation and its relation with the Courant number are studied. The simulation and verification are focusing on some realistic problems. Finally, a one-sided impact, a free-flexible pendulum, a taut string with a sliding boundary and a deployable guyed mast under an impact transverse wave are simulated. In these problems, an unstructured grid meshed with SACQ has similar energy convergence and accuracy to a structured grid but shows better efficiency.

Collecting information about fracture attributes through outcrops measurement is crucial for analyzing the scale, distribution, orientation, and spatial arrangement of fractures. The emergence of digital outcrop models (DOMs) provides a new technology for quantitative interpretation of fractures. However, large-scale DOMs pose additional challenges to the practical application, particularly in the interpretation of geological elements (e.g. fractures). This research proposes a workflow for fracture characteristics interpretation based on DOMs. First, DOMs are generated using light detection and ranging scanning technology. Then, a 3D visualization platform is developed based on OpenSceneGraph. We use level-of-detail technology to reconstruct DOMs for multiscale fast visualization of large-scale models. Finally, in order to realize the quantitative interpretation of fractures, we propose the best-plane fitting and the feature information (orientation, length, spacing, etc.) extraction methods for two types of fractures (exposed fracture walls and fracture traces). The proposed methods are applied to extract attributes of fractures in Dengying Formation (second member), Ebian, Xianfeng, southwest Sichuan Basin, China. The results provide the basis for reservoir evaluation in this area.

BackgroundHeart failure (HF) guidelines recommend routine testing for iron deficiency (ID) and, for those with ID, intravenous iron if the left ventricular ejection fraction is <50%. Guideline adherence to these recommendations by cardiologists in China is unknown.Methods and resultsAn independent academic web-based survey was designed and distributed via social networks to cardiologists across China. Overall, 1342 cardiologists (median age 34 years, IQR 30–39, 51% women) from all provinces of China completed this survey. More than half were unaware of the need to screen for ID in HF and did not do so routinely in their clinical practice. Approximately 80% were not familiar with the diagnostic criteria for ID in HF guidelines, and only 0.8% recognised transferrin saturation <20% as an independent marker of ID. Regarding iron repletion, only 14% preferred intravenous to oral iron for correcting ID compared with 68% favouring oral iron. Three-quarters were unfamiliar with methods for calculating intravenous iron dose. Furthermore, over 80% were unaware that current guidelines only recommend ferric carboxymaltose or ferric derisomaltose for correcting ID. The main barriers to using intravenous iron were lack of knowledge and experience. Despite such poor awareness and practice, most cardiologists were interested in learning more about managing ID in HF.ConclusionsIn this nationwide survey of cardiologists in China, we identified large gaps in both knowledge and management of ID. This survey will help guide the development of educational programmes to improve care for patients with HF and ID in China.