Dual-Encoder Transformer for Short-Term Photovoltaic Power Prediction Using Satellite Remote-Sensing Data

The penetration of photovoltaic (PV) energy has gained a significant increase in recent years because of its sustainable and clean characteristics. However, the uncertainty of PV power affected by variable weather poses challenges to an accurate short-term prediction, which is crucial for reliable power system operation. Existing methods focus on coupling satellite images with ground measurements to extract features using deep neural networks. However, a flexible predictive framework capable of handling these two data structures is still not well developed. The spatial and temporal features are merely concatenated and passed to the following layer of a neural network, which is incapable of utilizing the correlation between them. Therefore, we propose a novel dual-encoder transformer (DualET) for short-term PV power prediction. The dual encoders contain wavelet transform and series decomposition blocks to extract informative features from image and sequence data, respectively. Moreover, we propose a cross-domain attention module to learn the correlation between the temporal features and cloud information and modify the attention modules with the spare form and Fourier transform to improve their performance. The experiments on real-world datasets, including PV station data and satellite images, show that our model achieves better results than other models for short-term PV power prediction

Protecting Mobile Livelihoods: Actors’ Responses to the Emerging Health Challenges in Beijing and Tianjin

Drawing on extensive fieldwork in Beijing and Tianjin, and applying a livelihood framework combined with a well-being perspective, this article examines an important aspect of rural–urban migrants’ social protection in China, namely migrants’ health, in particular work safety and occupational health. It argues that migrant workers’ social rights to health and livelihoods are a fiercely contested domain of citizenship entailing aspects of exclusion, inclusion, and control and allocation of economic, social, and political resources. The article shows that in spite of the accelerated pace of legislation and consolidated efforts to reconstruct the welfare system in China in recent years, the new social security schemes have thus far, by and large, failed to protect migrant workers in a systematic manner. The issues raised in the article therefore call for greater academic attention and more effective public policy responses

Oxygen Vacancy-Reinforced Water-Assisted Proton Hopping for Enhanced Catalytic Hydrogenation

Water-assisted proton hopping (WAPH) has been intensively investigated for promoting the performance of metal oxide-supported catalysts for hydrogenation. However, the effects of the structure of the metal oxide support on WAPH have received little attention. Herein, we construct oxygen vacancy-bearing, MoO3–x-supported Pd nanoparticle catalysts (Pd/MoO3–x-R), where the oxygen vacancies can promote WAPH, thereby facilitating catalytic hydrogenation. The experimental results and theoretical calculations show that the oxygen vacancies favor the adsorption of water, which assists the proton hopping across the surface of the metal oxide, enhancing the catalytic hydrogenation. Our finding will provide a potential approach to the design of metal oxide-supported catalysts for hydrogenation