Role of Fiber Orientation in Atrial Arrythmogenesis

Electrical wave-front propagation in the atria is determined largely by local fiber orientation. Recent study suggests that atrial fibrillation (AF) progresses with enhanced anisotropy. In this work, a 3D rabbit atrial anatomical model at 20 × 20 × 20 μm3 resolution with realistic fiber orientation was constructed based on the novel contrast-enhanced micro-CT imaging. The Fenton-Karma cellular activation model was adapted to reproduce rabbit atrial action potential period of 80 ms. Diffusivities were estimated for longitudinal and transverse directions of the fiber orientation respectively. Pacing was conducted in the 3D anisotropic atrial model with a reducing S2 interval to facilitate initiation of atrial arrhythmia. Multiple simulations were conducted with varying values of diffusion anisotropy and stimulus locations to evaluate the role of anisotropy in initiating AF. Under physiological anisotropy conditions, a rapid right atrial activation was followed by the left atrial activation. Excitation waves reached the atrio-ventricular border where they terminated. Upon reduction of conduction heterogeneity, re-entry was initiated by the rapid pacing and the activation of both atrial chambers was almost simultaneous. Myofiber orientation is an effective mechanism for regulating atrial activation. Modification of myoarchitecture is proarrhythmic

Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generation

Generative Neural Radiance Fields (GNeRF) based 3D-aware GANs have demonstrated remarkable capabilities in generating high-quality images while maintaining strong 3D consistency. Notably, significant advancements have been made in the domain of face generation. However, most existing models prioritize view consistency over disentanglement, resulting in limited semantic/attribute control during generation. To address this limitation, we propose a conditional GNeRF model incorporating specific attribute labels as input to enhance the controllability and disentanglement abilities of 3D-aware generative models. Our approach builds upon a pre-trained 3D-aware face model, and we introduce a Training as Init and Optimizing for Tuning (TRIOT) method to train a conditional normalized flow module to enable the facial attribute editing, then optimize the latent vector to improve attribute-editing precision further. Our extensive experiments demonstrate that our model produces high-quality edits with superior view consistency while preserving non-target regions. Code is available at https://github.com/zhangqianhui/TT-GNeRF.Comment: 13 page

Surfactant Induced Reservoir Wettability Alteration: Recent Theoretical and Experimental Advances in Enhanced Oil Recovery

Reservoir wettability plays an important role in various oil recovery processes. The origin and evolution of reservoir wettability were critically reviewed to better understand the complexity of wettability due to interactions in crude oil-brine-rock system, with introduction of different wetting states and their influence on fluid distribution in pore spaces. The effect of wettability on oil recovery of waterflooding was then summarized from past and recent research to emphasize the importance of wettability in oil displacement by brine. The mechanism of wettability alteration by different surfactants in both carbonate and sandstone reservoirs was analyzed, concerning their distinct surface chemistry, and different interaction patterns of surfactants with components on rock surface. Other concerns such as the combined effect of wettability alteration and interfacial tension (IFT) reduction on the imbibition process was also taken into account. Generally, surfactant induced wettability alteration for enhanced oil recovery is still in the stage of laboratory investigation. The successful application of this technique relies on a comprehensive survey of target reservoir conditions, and could be expected especially in low permeability fractured reservoirs and forced imbibition process

3D-Aware Semantic-Guided Generative Model for Human Synthesis

Generative Neural Radiance Field (GNeRF) models, which extract implicit 3D representations from 2D images, have recently been shown to produce realistic images representing rigid/semi-rigid objects, such as human faces or cars. However, they usually struggle to generate high-quality images representing non-rigid objects, such as the human body, which is of a great interest for many computer graphics applications. This paper proposes a 3D-aware Semantic-Guided Generative Model (3D-SGAN) for human image synthesis, which combines a GNeRF with a texture generator. The former learns an implicit 3D representation of the human body and outputs a set of 2D semantic segmentation masks. The latter transforms these semantic masks into a real image, adding a realistic texture to the human appearance. Without requiring additional 3D information, our model can learn 3D human representations with a photo-realistic, controllable generation. Our experiments on the DeepFashion dataset show that 3D-SGAN significantly outperforms the most recent baselines. The code is available at https://github.com/zhangqianhui/3DSGANComment: ECCV 2022. 29 page

Study on different potato continuous cropping ways on rhizosphere soil nutrients and enzyme activities

To address the problem of food security, China produced potatoes as a staple food in 2015.However, there are increasing problems with continuous cropping production methods, potato continuous cropping has been inevitable.So it is necessary to research under the different potato continuous cropping ways, potato rhizosphere soil nutrients and enzyme activities which can direct potato fertilizer and ease potato continuous cropping obstacle. A two-growing season investigation was carried out during the spring and autumn of 2014 and 2015 to determine the different ways of potato continuous cropping on the overall growth of potatoes, soil nutrients, and enzyme activities. During continuous cropping nitrogen (N) content of rhizosphere soil was reduced; available potassium (Kav) was significantly reduced(p≤5%), especially in spring and autumn continuous cropping; and total phosphorus (Ptot) was reduced during the growth stage. However, the total potassium (Ktot), available phosphorus(Pav), and organic carbon (Ctot) increased before they decreased. For rhizosphere soil enzyme activities, urease initially increased and then decreased, and was lower in continuous cropping than multiple continuous cropping; in spring of 2015, invertase was the highest with continuous cropping. Catalase and polyphenol oxidase decreased initially before increasing. Continuous cropping in spring and autumn consumed more nutrients, especially potassium (K) than in spring. Therefore, potatoes planted in both spring and autumn enhanced the problems of continuous cropping. However, multiple continuous cropping that eased rhizosphere soil nutrient absorption and effectively improves soil nutrients and enzyme activities could provide an effective method for managing the negative impacts associated with continuous cropping