Stable 3-dimensional Vortex Families Consistent with Jovian Observations Including the Great Red Spot

Detailed observations of the velocities of Jovian vortices exist at only one height in the atmosphere, so their vertical structures are poorly understood. This motivates this study that computes stable 3-dimensional, long-lived planetary vortices that satisfy the equations of motion. We solve the anelastic equations with a high-resolution pseudo-spectral method using the observed Jovian atmospheric temperatures and zonal flow. We examine several families of vortices and find that {\it constant-vorticity} vortices, which have nearly-uniform vorticity as a function of height and horizontal areas that go to zero at their tops and bottoms, converge to stable vortices that look like the Great Red Spot (GRS) and other Jovian anticyclones. In contrast, the {\it constant-area} vortices proposed in previous studies, which have nearly-uniform areas as a function of height and vertical vorticities that go to zero at their tops and bottoms, are far from equilibrium, break apart, and converge to {\it constant-vorticity} vortices. Our late-time vortices show unexpected properties. Vortices that are initially non-hollow become hollow (i.e., have local minima of vertical vorticity at their centers), which is a feature of the GRS that cannot be explained with 2-dimensional simulations. The central axes of the final vortices align with the planetary-spin axis even if they initially align with the local direction of gravity. We present scaling laws for how vortex properties change with the Rossby number and other non-dimensional parameters. We analytically prove that the horizontal mid-plane of a stable vortex must lie at a height above the top of the convective zone

Simulation for non-point source pollution based on QUAL2E in the Jinghe River, Shaanxi Province, China

Wang, J., Huo, A., Hu, A., Zhang, X., & Wu, Y. (March-April, 2017). Simulation for non-point source pollution based on QUAL2E in the Jinghe River, Shaanxi Province, China. Water Technology and Sciences (in Spanish), 8(2), 117-126. Water pollution in river basins is significantly influenced by point-source and non-point-source pollutants. Compared with point-source pollutants, the identification and quantification of non-point-source pollutants are critical but difficult issues in water environmental pollution studies. The Jinghe River is one of the main tributaries of the Weihe River. However, the non-point-source pollution of this river is not well understood. In order to analyze the sources of pointand non-point loads to river water, the river water quality model QUAL2E and Principal Component Analysis (PCA) & Factor Analysis (FA) were applied simultaneously to calculate the point- and non-point-source loads of ammonia nitrogen and nitrate nitrogen, respectively, in dry and wet seasons from 2002 to 2007. The results show that NO3 - -N can be associated with point-source pollution, such as domestic sewage in dry seasons, but non-point-source pollution generated by precipitation in wet seasons. NH4 +-N can be associated with point-source pollution throughout the year. The methods applied in this research provide reliable results on non-point-source pollution caused by storm runoff

Uncertainty-inspired Open Set Learning for Retinal Anomaly Identification

Failure to recognize samples from the classes unseen during training is a major limit of artificial intelligence (AI) in real-world implementation of retinal anomaly classification. To resolve this obstacle, we propose an uncertainty-inspired open-set (UIOS) model which was trained with fundus images of 9 common retinal conditions. Besides the probability of each category, UIOS also calculates an uncertainty score to express its confidence. Our UIOS model with thresholding strategy achieved an F1 score of 99.55%, 97.01% and 91.91% for the internal testing set, external testing set and non-typical testing set, respectively, compared to the F1 score of 92.20%, 80.69% and 64.74% by the standard AI model. Furthermore, UIOS correctly predicted high uncertainty scores, which prompted the need for a manual check, in the datasets of rare retinal diseases, low-quality fundus images, and non-fundus images. This work provides a robust method for real-world screening of retinal anomalies

Utilizing virtual arts in reforming market players’ behavior to invest in sustainability projects

Abstract This study investigates the influence of the expansion of the virtual arts market on private sustainable investment in China spanning the years 1985 to 2021, employing the autoregressive distributed lag model. The results indicate that a 1% rise in the virtual arts market correlates with a short-term surge of around 0.46% in private sustainable investment, with a lasting increase of 0.38%. Furthermore, factors such as social inclusion, privatization, economic size, financial development, and renewable deployment significantly shape private sustainable investment patterns. Noteworthy policy recommendations arising from these findings include the integration of sustainability topics into educational curricula, the establishment of online platforms dedicated to sustainable virtual arts, the cultivation of green financing markets, and the promotion of collaborations among virtual arts institutions with a specific emphasis on sustainability

Application of a Modified Generative Adversarial Network in the Superresolution Reconstruction of Ancient Murals

Considering the problems of low resolution and rough details in existing mural images, this paper proposes a superresolution reconstruction algorithm for enhancing artistic mural images, thereby optimizing mural images. The algorithm takes a generative adversarial network (GAN) as the framework. First, a convolutional neural network (CNN) is used to extract image feature information, and then, the features are mapped to the high-resolution image space of the same size as the original image. Finally, the reconstructed high-resolution image is output to complete the design of the generative network. Then, a CNN with deep and residual modules is used for image feature extraction to determine whether the output of the generative network is an authentic, high-resolution mural image. In detail, the depth of the network increases, the residual module is introduced, the batch standardization of the network convolution layer is deleted, and the subpixel convolution is used to realize upsampling. Additionally, a combination of multiple loss functions and staged construction of the network model is adopted to further optimize the mural image. A mural dataset is set up by the current team. Compared with several existing image superresolution algorithms, the peak signal-to-noise ratio (PSNR) of the proposed algorithm increases by an average of 1.2–3.3 dB and the structural similarity (SSIM) increases by 0.04 = 0.13; it is also superior to other algorithms in terms of subjective scoring. The proposed method in this study is effective in the superresolution reconstruction of mural images, which contributes to the further optimization of ancient mural images

Nonhomogeneous poisson process model of summer high temperature extremes over China

In this study, nonhomogeneous Poisson process (NHPP) models arising from the extreme value theory have been fitted to summer high temperature extremes (HTEs) at 321 meteorological stations over China. The seasonality and six prominent atmospheric teleconnection patterns in Northern Hemisphere are incorporated in the NHPP models reflecting the non-stationarity of occurrence rate in Poisson process of HTEs. In addition, Poisson regression model has also been applied to link HTEs and these teleconnection patterns. The linkages of HTEs and teleconnection patterns have been identified in both NHPP modeling and Poisson regression. Composite maps of differences of 500-hPa geopotential height and wind fields in the positive and negative phases of teleconnection patterns are constructed to show the impacts of atmospheric circulation patterns on extreme heat events. The spatial pattern of the associated anticyclonic or cyclonic circulations with teleconnection patterns partly explains the spatial variability of the occurrences of summer HTEs over China