This study starts from the counterintuitive question of how we can render conventional stiff, nonstretchable, and even brittle materials sufficiently conformable to fully wrap curved surfaces, such as spheres, without failure. Here, we extend the geometrical design method of computational origami to wrapping. Our computational wrapping approach provides a robust and reliable method for fabricating conformal devices for arbitrary curved surfaces with a computationally designed nonpolyhedral developable net. This computer-aided design transforms two-dimensional (2D)–based materials, such as Si wafers and steel sheets, into various targeted conformal structures that can fully wrap desired 3D structures without fracture or severe plastic deformation. We further demonstrate that our computational wrapping approach enables a design platform that can transform conventional nonstretchable 2D-based devices, such as electroluminescent lighting and flexible batteries, into conformal 3D curved devices.

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A balanced microstrip quad-band bandpass filter (BPF) with independently controllable frequencies, controllable fractional bandwidths (FBWs) and high selectivity is designed in this paper. The proposed BPF is achieved by employing two pairs of folded asymmetric stub-loaded resonators (FASLRs) and balanced microstrip/slotline transition structures (MSTSs). The center frequencies of the four differential-mode (DM) passbands can be controlled independently by changing the electrical lengths of each FASLR. A novel interdigital coupled line is firstly proposed to enhance source-load coupling further, which contributes to a higher selectivity. Meanwhile, the DM passbands are independent of the CM responses, which significantly simplifies the design procedure. In addition, eight transmission zeros (TZs) are generated to improve the selectivity of the four passbands obviously. The measured results of the fabricated balanced BPF centered at 2.48/3.45/5.17/5.78 GHz agree well with the simulated ones, which validates the proposed design method well.INDEX TERMS Asymmetric stub-loaded resonators, balanced BPF, microstrip/slotline transition structures (MSTSs), interdigital coupled line, quad-band.

Urban rail transit passenger flow forecasting is an important basis for station design, passenger flow organization, and train operation plan optimization. In this work, we combined the artificial fish swarm and improved particle swarm optimization (AFSA-PSO) algorithms. Taking the Window of the World station of the Shenzhen Metro Line 1 as an example, subway passenger flow prediction research was carried out. The AFSA-PSO algorithm successfully preserved the fast convergence and strong traceability of the original algorithm through particle self-adjustment and dynamic weights, and it effectively overcame its shortcomings, such as the tendency to fall into local optimum and lower convergence speed. In addition to accurately predicting normal passenger flow, the algorithm can also effectively identify and predict the large-scale tourist attractions passenger flow as it has strong applicability and robustness. Compared with single PSO or AFSA algorithms, the new algorithm has better prediction effects, such as faster convergence, lower average absolute percentage error, and a higher correlation coefficient with real values.

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