Semantic 3D-aware Portrait Synthesis and Manipulation Based on Compositional Neural Radiance Field

Recently 3D-aware GAN methods with neural radiance field have developed rapidly. However, current methods model the whole image as an overall neural radiance field, which limits the partial semantic editability of synthetic results. Since NeRF renders an image pixel by pixel, it is possible to split NeRF in the spatial dimension. We propose a Compositional Neural Radiance Field (CNeRF) for semantic 3D-aware portrait synthesis and manipulation. CNeRF divides the image by semantic regions and learns an independent neural radiance field for each region, and finally fuses them and renders the complete image. Thus we can manipulate the synthesized semantic regions independently, while fixing the other parts unchanged. Furthermore, CNeRF is also designed to decouple shape and texture within each semantic region. Compared to state-of-the-art 3D-aware GAN methods, our approach enables fine-grained semantic region manipulation, while maintaining high-quality 3D-consistent synthesis. The ablation studies show the effectiveness of the structure and loss function used by our method. In addition real image inversion and cartoon portrait 3D editing experiments demonstrate the application potential of our method.Comment: Accepted by AAAI2023 Ora

A Multiobjective Robust Scheduling Optimization Mode for Multienergy Hybrid System Integrated by Wind Power, Solar Photovoltaic Power, and Pumped Storage Power

Wind power plant (WPP), photovoltaic generators (PV), cell-gas turbine (CGT), and pumped storage power station (PHSP) are integrated into multienergy hybrid system (MEHS). Firstly, this paper presents MEHS structure and constructs a scheduling model with the objective functions of maximum economic benefit and minimum power output fluctuation. Secondly, in order to relieve the uncertainty influence of WPP and PV on system, robust stochastic theory is introduced to describe uncertainty and propose a multiobjective stochastic scheduling optimization mode by transforming constraint conditions with uncertain variables. Finally, a 9.6 MW WPP, a 6.5 MW PV, three CGT units, and an upper reservoir with 10 MW·h equivalent capacity are chosen as simulation system. The results show MEHS system can achieve the best operation result by using the multienergy hybrid generation characteristic. PHSP could shave peak and fill valley of load curve by optimizing pumping storage and inflowing generating behaviors based on the load supply and demand status and the available power of WPP and PV. Robust coefficients can relieve the uncertainty of WPP and PV and provide flexible scheduling decision tools for decision-makers with different risk attitudes by setting different robust coefficients, which could maximize economic benefits and minimize operation risks at the same time

DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation

Text-driven image manipulation remains challenging in training or inference flexibility. Conditional generative models depend heavily on expensive annotated training data. Meanwhile, recent frameworks, which leverage pre-trained vision-language models, are limited by either per text-prompt optimization or inference-time hyper-parameters tuning. In this work, we propose a novel framework named \textit{DeltaEdit} to address these problems. Our key idea is to investigate and identify a space, namely delta image and text space that has well-aligned distribution between CLIP visual feature differences of two images and CLIP textual embedding differences of source and target texts. Based on the CLIP delta space, the DeltaEdit network is designed to map the CLIP visual features differences to the editing directions of StyleGAN at training phase. Then, in inference phase, DeltaEdit predicts the StyleGAN's editing directions from the differences of the CLIP textual features. In this way, DeltaEdit is trained in a text-free manner. Once trained, it can well generalize to various text prompts for zero-shot inference without bells and whistles. Code is available at https://github.com/Yueming6568/DeltaEdit.Comment: Accepted by CVPR2023. Code is available at https://github.com/Yueming6568/DeltaEdi

Diethyl 4-(4,5-dihydro­furan-2-yl)-3,5-di­methyl-1-phenyl-1,4-dihydro­pyrazine-2,6-dicarboxyl­ate

In the title compound, C22H26N2O5, the central 1,4-dihydro­pyrazine ring adopts a boat conformation, while the benzene ring and the two disordered components of the furan ring are inclined at angles of 77.9 (5) and 61.9 (7)°. Three of the C atoms of the furan ring are disordered over two positions with occupancies of 0.655 (18) and 0.345 (18). In the crystal structure, weak inter­molecular C—H⋯O hydrogen bonds link the mol­ecules into chains propagating in [010]

Cybernetic basis and system practice of remote sensing and spatial information science

Cybernetics provides a new set of ideas and methods for the study of modern science, and it has been fully applied in many areas. However, few people have introduced cybernetics into the field of remote sensing. The paper is based on the imaging process of remote sensing system, introducing cybernetics into the field of remote sensing, establishing a space-time closed-loop control theory for the actual operation of remote sensing. The paper made the process of spatial information coherently, and improved the comprehensive efficiency of the space information from acquisition, procession, transformation to application. We not only describes the application of cybernetics in remote sensing platform control, sensor control, data processing control, but also in whole system of remote sensing imaging process control. We achieve the information of output back to the input to control the efficient operation of the entire system. This breakthrough combination of cybernetics science and remote sensing science will improve remote sensing science to a higher level

Protective effect of Radix Bupleuri extract against liver cirrhosis in rats

Purpose: To explore the effect of Radix Bupleuri extract (RBE) on diethylnitrosamine (DEN)-induced liver cirrhosis in rats.Methods: Rats were injected with DEN once a week for 8 weeks to induce liver cirrhosis. Some DENinduced rats were also treated with RBE, which was obtained by extracting dried Radix Bupleuri in water, for 8 weeks. Afterwards, biochemical indices and oxidative stress markers were assessed.Results: RBE significantly decreased serum concentrations of both alanine transaminase (137.3 ± 4.4 U/L, p < 0.01) and aspartate aminotransaminase (152.1 ± 3.4 U/L, p < 0.01) in DEN-induced rats at week 8. In addition, RBE significantly decreased malondialdehyde (0.13 ± 0.02 umol/L, p < 0.01) and superoxide dismutase (0.73 ± 0.04 U/mg protein, p < 0.01) levels in DEN-induced rats (p < 0.01).Conclusion: RBE exhibits a protective effect against DEN-induced liver cirrhosis in rats. Thus, it may have the potential to be used to treat liver cirrhosis in clinical settings.Keywords: Radix Bupleuri, Liver cirrhosis, Anti-oxidant, Diethylnitrosamine, Alanine transaminase, Aspartate aminotransaminas