VITON: An Image-based Virtual Try-on Network

We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy. Conditioned upon a new clothing-agnostic yet descriptive person representation, our framework first generates a coarse synthesized image with the target clothing item overlaid on that same person in the same pose. We further enhance the initial blurry clothing area with a refinement network. The network is trained to learn how much detail to utilize from the target clothing item, and where to apply to the person in order to synthesize a photo-realistic image in which the target item deforms naturally with clear visual patterns. Experiments on our newly collected Zalando dataset demonstrate its promise in the image-based virtual try-on task over state-of-the-art generative models

Hydrogen as a Source of Flux Noise in SQUIDs

Superconducting qubits are hampered by flux noise produced by surface spins from a variety of microscopic sources. Recent experiments indicated that hydrogen (H) atoms may be one of those sources. Using density functional theory calculations, we report that H atoms either embedded in, or adsorbed on, an a-Al2O3(0001) surface have sizeable spin moments ranging from 0.81 to 0.87 uB with energy barriers for spin reorientation as low as ~10 mK. Furthermore, H adatoms on the surface attract gas molecules such as O2, producing new spin sources. We propose coating the surface with graphene to eliminate H-induced surface spins and to protect the surface from other adsorbates.Comment: 12 pages, 4 figure

Scalar Induced Gravitational Waves from Finslerian Inflation and Pulsar Timing Arrays Observations

The recent data from NANOGrav provide strong evidence of the existence of the \acp{SGWB}. We investigate \acp{SIGW} from Finslerian inflation as a potential source of stochastic gravitational wave background. Small-scale ($\lesssim$1 Mpc) statistically anisotropic primordial scalar perturbations can be generated in Finslerian inflation. The second order \acp{SIGW} from Finslerian inflation are also anisotropic on small scales. After spatially averaging the small-scale anisotropic \acp{SIGW}, we obtain the large-scale isotropic \acp{SGWB}. We find that the parameters of small-scale anisotropic primordial power spectrum generated by Finslerian inflation affect the \acp{PTA} observations of large-scale isotropic gravitational wave background

Quantitative prediction of palaeo-uplift reservoir control and favorable reservoir formation zones in Lufeng Depression

In this paper, taking the Lufeng Depression as the study object, the distribution characteristics and reservoir-controlling conditions of palaeo-uplift are analyzed from both qualitative and quantitative perspectives. The distribution characteristics of the three-level palaeo-uplift structural pattern are elucidated, which show that the palaeo-uplifts went through three structural evolutionary stages: Eocene, Early-Middle Miocene, and Late Miocene, with long-term inherited development characteristics. Palaeo-uplift controls the distribution of hydrocarbon planes, the direction of dominant hydrocarbon transport, the development of various traps, and the types of hydrocarbon reservoirs. Applying the principle and method of “multi-element matching reservoir formation model”, the corresponding geological and mathematical models are established, which indicate that 86.29% of the number of reservoirs are distributed on the top and slope of the palaeo-uplift, and the reserves and number decrease with the distance to the top of the palaeo-uplift. Based on the palaeo-uplift control model, four high-probability areas for palaeo-uplift control in the Wenchang and Enping Fms are predicted, which are mainly located in the Lufeng middle-low uplift, the Dongsha uplift, and uplifts within the depression.Cited as: Guo, B., Yu, F., Wang, Y., Li, H., Li, H., Wu, Z. Quantitative prediction of palaeo-uplift reservoir control and favorable reservoir formation zones in Lufeng Depression. Advances in Geo-Energy Research, 2022, 6(5): 426-437. https://doi.org/10.46690/ager.2022.05.0

Health status prediction for the elderly based on machine learning

Health and social care services are crucial to old people. The provision of services to the elderly with care needs requires more accurate predictions of the health status of the elderly to rationalize the allocation of the limited social care resources. The traditional analytical methods have proved incapable of predicting the demands of today's society, compared to which machine learning methods can more accurately capture the nonlinear relationships between the variables. To ascertain visually the performance of these machine learning methods regarding the prediction of the elderly's care needs, we designed and verified the experiment

Quantitative evaluation and models of hydrocarbon accumulation controlled by faults in the Pearl River Mouth Basin

The Pearl River Mouth Basin is the largest petroliferous basin in the northern South China Sea, where hydrocarbon accumulation is strongly controlled by fault activities. This study performed the quantitative evaluation of the effects of faults on hydrocarbon migration and accumulation in the basin. The results indicate that the critical values of vertical migration of middle-shallow hydrocarbon, including the active strength of faults and the ratio of fault throw to shale caprock thickness, were up to 10 m/Ma and 5, respectively. The lateral hydrocarbon migration efficiency of the unbreached relay zone was higher than that of the barely breached and strongly breached types. The lower critical value of shale gouge ratio for the clay sealing efficiency was 0.32. Additionally, the zones with the EW-trending transtensional faults were found to have unique dual functions of migration and stress sealing, suggesting that the linking fault positions play important roles in the lateral migration of hydrocarbons. Finally, seven hydrocarbon accumulation models controlled by faults in different tectonic settings were constructed to clarify the effects of faults on the vertical and lateral migrations of hydrocarbon. These models suggested that fine hydrocarbon exploration should be undertaken in the northeastern Baiyun Sag, and that middle-deep hydrocarbon exploration should be enhanced in the Enping, Huizhou, and southwestern Baiyun Sags.Cited as: Peng, G., Wu, Z., Dai, Y., Zhang, L., Yu, S., Wang, W., Pang, H. Quantitative evaluation and models of hydrocarbon accumulation controlled by faults in the Pearl River Mouth Basin. Advances in Geo-Energy Research, 2023, 8(2): 89-99. https://doi.org/10.46690/ager.2023.05.0