TFMKC: Tuning-Free Multiple Kernel Clustering Coupled With Diverse Partition Fusion.

Clustering is a popular research pipeline in unsupervised learning to find potential groupings. As a representative paradigm in multiple kernel clustering (MKC), late fusion-based models learn a consistent partition across multiple base kernels. Despite their promising performance, a common concern is the limited representation capacity caused by the inflexible fusion mechanism.

3D printing of hierarchically micro/nanostructured electrodes for high-performance rechargeable batteries.

3D printing, also known as additive manufacturing, is capable of fabricating 3D hierarchical micro/nanostructures by depositing a layer-upon-layer of precursor materials and solvent-based inks under the assistance of computer-aided design (CAD) files. 3D printing has been employed to construct 3D hierarchically micro/nanostructured electrodes for rechargeable batteries, endowing them with high specific surface areas, short ion transport lengths, and high mass loading. This review summarizes the advantages and limitations of various 3D printing methods and presents the recent developments of 3D-printed electrodes in rechargeable batteries, such as lithium-ion batteries, sodium-ion batteries, and lithium-sulfur batteries.

Wavelet Scattering Transform for ECG Beat Classification.

An electrocardiogram (ECG) records the electrical activity of the heart; it contains rich pathological information on cardiovascular diseases, such as arrhythmia. However, it is difficult to visually analyze ECG signals due to their complexity and nonlinearity. The wavelet scattering transform can generate translation-invariant and deformation-stable representations of ECG signals through cascades of wavelet convolutions with nonlinear modulus and averaging operators.