Fabricating colloidal crystals and construction of ordered nanostructures

Colloidal crystals of polymeric or inorganic microspheres are of extensive interest due to their potential applications in such as sensing, optics, photonic bandgap and surface patterning. The article highlights a set of approaches developed in our group, which are efficient to prepare colloidal crystals with ordered voids, patterned colloidal crystals on non-planar surfaces, heterogeneous colloidal crystals of different building blocks, colloidal crystals composed of non-spherical polyhedrons, and colloidal crystals of non-close-packed colloidal microspheres in particular. The use of these colloidal crystals as templates for different microstructures range from nanoscale to micron-scale is also summarized

Correlative Channel-Aware Fusion for Multi-View Time Series Classification

Multi-view time series classification (MVTSC) aims to improve the performance by fusing the distinctive temporal information from multiple views. Existing methods mainly focus on fusing multi-view information at an early stage, e.g., by learning a common feature subspace among multiple views. However, these early fusion methods may not fully exploit the unique temporal patterns of each view in complicated time series. Moreover, the label correlations of multiple views, which are critical to boost-ing, are usually under-explored for the MVTSC problem. To address the aforementioned issues, we propose a Correlative Channel-Aware Fusion (C2AF) network. First, C2AF extracts comprehensive and robust temporal patterns by a two-stream structured encoder for each view, and captures the intra-view and inter-view label correlations with a graph-based correlation matrix. Second, a channel-aware learnable fusion mechanism is implemented through convolutional neural networks to further explore the global correlative patterns. These two steps are trained end-to-end in the proposed C2AF network. Extensive experimental results on three real-world datasets demonstrate the superiority of our approach over the state-of-the-art methods. A detailed ablation study is also provided to show the effectiveness of each model component

On the Pulse Shaping for Delay-Doppler Communications

In this paper, we study the pulse shaping for delay-Doppler (DD) communications. We start with constructing a basis function in the DD domain following the properties of the Zak transform. Particularly, we show that the constructed basis functions are globally quasi-periodic while locally twisted-shifted, and their significance in time and frequency domains are then revealed. We further analyze the ambiguity function of the basis function, and show that fully localized ambiguity function can be achieved by constructing the basis function using periodic signals. More importantly, we prove that time and frequency truncating such basis functions naturally leads to approximate delay and Doppler orthogonalities, if the truncating windows are periodic within the support. Motivated by this, we propose a DD Nyquist pulse shaping scheme considering signals with periodicity. Finally, our conclusions are verified by using various strictly or approximately periodic pulses