We present a novel topological classification of RNA secondary structures with pseudoknots. It is based on the topological genus of the circular diagram associated to the RNA base-pair structure. The genus is a
Hierarchy-based: Hierarchical clustering consists of structures called hierarchicaltrees. A hierarchical tree is a nested partition set represented by a tree diagram or adendrogram. The division of a tree at a specific stage generates a division into disjoint classes of K. If two groups are selecte...
In current in situ X-ray diffraction (XRD) techniques, data generation surpasses human analytical capabilities, potentially leading to the loss of insights. Automated techniques require human intervention, and lack the performance and adaptability requir
The structure diagram and operation process of intelligent network are shown in Fig. 4. At present, classifiers have been gradually improved and extended to form artificial intelligence (AI) agents [40] and even knowledge planes [41] for more powerful learning capabilities and deployment of more ...
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Schematic diagram of the public opinion supernetwork. Full size image Supernetwork of public opinion (SNP) An SNP is a multidimensional network composed of four-layer networks X and interlayer superedges SE, denoted as \({{{\mathrm{SNP}}} = \left\{ {N,\,{{{\mathrm{SE}}} \right\...
Classification is a key process for making data accessible to people that need it5. Maps are an efficient way to share large amounts of spatial data, but to be effective they must be underpinned by a classification framework that a) follows a clear and transparent rationale (transparency), b...
Scheme showing the complementary expression patterns of class I and class II maize NAS genes link to their specific physiological functions. The left panel shows the schematic diagram of putative physiological functions of ZmNASs during iron uptake and translocation of maize plant. The right panel sho...
K-MaxPooling schematic diagram. Full size image K-MaxPooling is improved based on traditional maximum pooling. It preserves the largest first K values in a set of eigenvalues and arranges them according to the original sequence of these eigenvalues. K-MaxPooling can retain the strength information...
Machine learning techniques can reveal hidden structures in large amounts of data and have the potential to replace analytical scientific methods. Electromagnetic simulations of photonic nanostructures often produce data in significant amounts, particularly when three-dimensional field distributions are calculat...