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Video super-resolution, which aims at producing a highresolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we propose a novel method that can effectively incorporate temporal information in a hierarchical way. The input sequence is divided into several groups, with each one corresponding to a kind of frame rate. These groups provide complementary information to recover missing details in the reference frame, which is further integrated with an attention module and a deep intra-group fusion module. In addition, a fast spatial alignment is proposed to handle videos with large motion. Extensive results demonstrate the capability of the proposed model in handling videos with various motion. It achieves favorable performance against state-of-the-art methods on several benchmark datasets. Code is available at https://github.com/junpan19/VSR_TGA.

Weather forecasting is important for science and society. At present, the most accurate forecast system is the numerical weather prediction (NWP) method, which represents atmospheric states as discretized grids and numerically solves partial differential equations that describe the transition between those states1. However, this procedure is computationally expensive. Recently, artificial-intelligence-based methods2 have shown potential in accelerating weather forecasting by orders of magnitude, but the forecast accuracy is still significantly lower than that of NWP methods. Here we introduce an artificial-intelligence-based method for accurate, medium-range global weather forecasting. We show that three-dimensional deep networks equipped with Earth-specific priors are effective at dealing with complex patterns in weather data, and that a hierarchical temporal aggregation strategy reduces accumulation errors in medium-range forecasting. Trained on 39 years of global data, our program, Pangu-Weather, obtains stronger deterministic forecast results on reanalysis data in all tested variables when compared with the world’s best NWP system, the operational integrated forecasting system of the European Centre for Medium-Range Weather Forecasts (ECMWF)3. Our method also works well with extreme weather forecasts and ensemble forecasts. When initialized with reanalysis data, the accuracy of tracking tropical cyclones is also higher than that of ECMWF-HRES.

The finite-difference time-domain method can provide broadband results if the excitation source is a pulse. This demands that the parameters of modeled materials have to be applicable over broad frequency bands. We optimize the modified Debye model parameters for gold, silver, copper, platinum, and aluminum using a large-scale nonlinear optimization algorithm. The complex relative permittivities calculated using the optimized parameters agree well with experimental values over broad frequency bands. The associated root-mean-square deviations are 0.49%, 3.52%, 4.13%, 1.64%, and 0.66%, respectively. We also provide an example of broadband calculations. The obtained broadband results are verified by a series of steady-state calculations.

Alkalides with large nonlinear optical (NLO) responses exhibit broad applications in the electro-optical device field. In the present work, based on alkali (Li and Na) in conjunction with alkaline-earth (Ca) atoms doped into facially polarized all-cis 1,2,3,4,5,6-hexafluorocyclohexane (C6F6H6), we first reported two facially polarized Janus-type alkalides as an external electric field (EEF)-induced second order NLO switches M–LCaL–M (M = Li or Na, L = C6F6H6). The two 4s electrons of the Ca atom are, respectively, pushed out by the negative fluorocarbon face of one L and each of them concentrate on one alkali atom and combine with the s electron of the later to form excess electron pair. Owing to the two excess electron pairs [highest occupied molecular orbital (HOMO) and HOMO – 1], the novel alkalides M––LCa2+L–M– is formed. Interestingly, with continuous increasing of EEF magnitude, the centrosymmetric M––LCa2+L–M– bearing two excess electron pairs is obviously broken and a long-range charge transfer is exhibited gradually from one end of the alkali atom through the middle LCaL to the other end of it. Meanwhile, the influence of EEF brings a large static electronic first hyperpolarizability from 0 (EEF = 0, off form) to 59 826 (M = Li, EEF = 19 × 10–4 au, on form) or 64 231 au (M = Na, EEF = 12 × 10–4 au, on form). They also have the largest vibrational first hyperpolarizabilities (on form). These results show that alkalides M––LCa2+L–M– have potential application for NLO materials as well as exhibit advantages such as high sensitivity, being fast, and having reversible switching.

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