3D Snapshot: Invertible Embedding of 3D Neural Representations in a Single Image.

3D neural rendering enables photo-realistic reconstruction of a specific scene by encoding discontinuous inputs into a neural representation. Despite the remarkable rendering results, the storage of network parameters is not transmission-friendly and not extendable to metaverse applications. In this paper, we propose an invertible neural rendering approach that enables generating an interactive 3D model from a single image (i.e., 3D Snapshot). Our idea is to distill a pre-trained neural rendering model (e.g., NeRF) into a visualizable image form that can then be easily inverted back to a neural network. To this end, we first present a neural image distillation method to optimize three neural planes for representing the original neural rendering model. However, this representation is noisy and visually meaningless. We thus propose a dynamic invertible neural network to embed this noisy representation into a plausible image representation of the scene. We demonstrate promising reconstruction quality quantitatively and qualitatively, by comparing to the original neural rendering model, as well as video-based invertible methods. On the other hand, our method can store dozens of NeRFs with a compact restoration network (5MB), and embedding each 3D scene takes up only 160KB of storage. More importantly, our approach is the first solution that allows embedding a neural rendering model into image representations, which enables applications like creating an interactive 3D model from a printed image in the metaverse.

Self-Assembly of Lamellae-in-Lamellae by Double-Tail Cationic Surfactants.

The molecular structures of surfactants play a pivotal role in influencing their self-assembly behaviors. In this work, using simulations and experiments, an unconventional hierarchically layered structure in the didodecyldimethylammonium bromide (DDAB)/water binary system: lamellae-in-lamellae is revealed, a new self-assembly structure in surfactant system. This self-assembly structure refers to a lamellar structure with a shorter periodic length (inner lamellae) embedded in a lamellar phase with a longer periodic length (outer lamellae). The normal vectors of these two lamellar regions orient perpendicularly. In addition, it is observed that this lamellar-in-lamellar phase disappears when the two tails of the cationic surfactants become longer. The formation of the lamellar-in-lamellar architecture arises from multiple interacting factors. The key element is that the short tails of the DDAB surfactants enhance hydrophilicity and rigidity, which facilitates the formation of the inner lamellae. Moreover, the lateral monolayer of the inner lamellae provides shielding from the water and prompts the formation of the outer lamellae. These findings indicate that molecular structures and flexibility can profoundly redirect the hierarchical self-assembly behaviors in amphiphilic systems. More broadly, this work presents a new strategy to deliberately program hierarchical nanomaterials by designing specific surfactant molecules to act as tunable scaffolds, reactors, and carriers.

Phase Behaviors of Dialkyldimethylammonium Bromide Bilayers.

Dialkyldimethylammonium bromide (2CnBr) surfactants in bilayer exhibit polymorphic phases and rich self-assembly behaviors. However, the effects of alkyl chain length on the phase behavior of the 2CnBr bilayer are still not completely understood. Herein, we investigate the 2CnBr bilayers by performing all-atom molecular dynamics simulations, taking into consideration the influence of temperature and initial interdigitated degree. Our findings indicate that DOAB (2C8Br) is challenging to remain in a bilayer structure, while DDAB (2C12Br) and DPAB (2C16Br) maintain bilayers in different phases. DDAB bilayers exhibit an interdigitated gel phase, and this phase structure enhances the stability and rigidity of the bilayer membrane. In contrast, DPAB bilayers show a ripple gel phase, which has better softness and ductility. The differences in phase behaviors can be attributed to a competition between the rigidity of the 2CnBr surfactants and the hydrophobic interaction of the alkyl tails. The results reveal the crucial role of the bilayer phase in determining the rigidity of bilayer membranes.

Long-Lived Weak Ion Pairs in Ionic Liquids: An Insight from All-Atom Molecular Dynamics Simulations.

The microstructure and local dynamics of ions in room-temperature ionic liquids (RTILs) have drawn a lot of attention due to their extensive potential applications in numerous fields. It is well-known that the widely used definitions of ion pairs (IPs) cannot reflect the full picture of RTILs. In this study, we find a universal residence time (τMR), which is regardless of the number of counterions in the first solvation shell in RTILs. Inspired by this, we propose a weak IP (WIP) model from a spatiotemporal perspective and demonstrate that the WIPs are long-lived and that their lifetimes obey a log-normal distribution, which is different from the literature. In addition, the electrostatic interactions are the main factors in the formation of WIPs, and the reorientations of ions are vital to the ruptures of WIPs. This research provides a new perspective for understanding the microstructural and dynamical properties of RTILs.

A comparative study of three different forecasting methods for trial of labor after cesarean section.

AIM: This study aims to establish a convenient and practical predelivery scoring system for trial of labor after cesarean section (TOLAC). METHODS: The data of 498 patients undergoing TOLAC were retrospectively studied. Indices with statistically significant differences, including cervical score, fetal weight, fetal pelvic index, body mass index and age, were selected. Combined with the presence of vaginal delivery history and indications of the previous cesarean section in these patients, three prenatal forecast scales for vaginal birth after cesarean (VBAC) were established. The receiver operating characteristic curve was drawn, and the best cut-off point was determined. Then, the areas under the curve of the three forecasting methods were compared. The scoring method with the largest area under the curve was considered the best method. RESULTS: The six indications of cesarean section used for the forecasting scale were as follows: cervical score, fetal weight, body mass index, age, presence of vaginal delivery history and the presence of previous obstructive dystocia. The scale that had the largest area under the curve was considered the best forecasting scale. CONCLUSION: The prenatal forecasting method for TOLAC was preliminarily investigated. It was determined that the scale with six indicators, such as the cervical score, could be used for the prenatal evaluation of TOLAC, providing a predictive basis for the possible success of the trial production for pregnant women. The method and process of VBAC section in our hospital was safe and effective.