Soliton sheets formed by interference of Bose-Einstein condensates in optical lattices

Soliton sheets which are formed by interference of Bose Einstein condensates occupying different single-particle states are observed in optical lattice potential. This structure consists of one-dimensional stationary solitons arranged periodically along the peaks of optical lattice (y direction) with the phase difference between the two sides of the soliton sheets is a linear function of y in each period, so we call it soliton sheet. A y component velocity difference exists between the two sides of the soliton sheet. Similar velocity distributions can be produced by the alignment of an infinite number of isotropic vortices along the peaks of the optical lattice. Their difference is that the soliton sheet structure is not limited by the number of phase singularities and can be generated even without phase singularities

Ionic blockade in a charged single-file water channel

The classical continuum theories fail to describe the ionic transport in Angstrom channels, where conduction deviates from Ohm's law, as attributed to dehydration/self-energy barrier and dissociation of Bjerrum ion-pairs in previous work. Here we found that the cations are strongly bound to the surface charge that blockade the ionic transport in a single-file water channel, causing nonlinear current-voltage responses. The presence of free ions significantly increased the probability of bound ions being released, resulting in an ionic current. We found that ionic conduction gradually becomes Ohmic as surface charge density increases, but the conduction amplitude decreased due to increased friction from bound ions. We rationalized the ionic transport by 1D Kramers' escape theory framework, which well described nonlinear ionic current, and the impact of surface charge density on turning to Ohmic system. Our results possibly provide an alternative view of ionic blockade in Angstrom channels

The influence and mechanism exploration of hydration environment on the stability of natural clay crude oil emulsion

The study investigated the effects and mechanisms of clay content, emulsion water content, pH, and metal cations on clay-crude oil emulsions. The results indicate the following: 1) At a water content of 50 V/V%, montmorillonite can form emulsions with crude oil at different concentrations, with the highest stability observed at 5 wt% content. In contrast, chlorite, illite, and kaolinite cannot form emulsions at low concentrations. 2) Under acidic conditions, montmorillonite, illite, and chlorite cannot form emulsions with crude oil, or the emulsions are highly unstable. However, kaolinite forms more stable emulsions under acidic conditions. In alkaline environments, emulsions formed by all clay minerals exhibit increased stability. 3) The order of the effectiveness of different metal cations in reducing the stability of montmorillonite-crude oil emulsions is K+ > Na+ > Mg2+ > Ca2+, while for chlorite, illite, and kaolinite, it is Mg2+ > Ca2+ > K+ > Na+. 4) The factors that influence the stability of clay-crude oil emulsions are the arrangement of clay particles in water and the dispersion capability of clay particles in water. The most significant influencing factor is the arrangement of clay particles in water

Maturation and Emigration of Single-Positive Thymocytes

T lymphopoiesis in the thymus was thought to be completed once it reaches the single positive (SP) stage, a stage when T cells are “fully mature” and waiting to be exported at random or follow a “first-in-first-out” manner. Recent evidence, however, has revealed that the newly generated SP thymocytes undergo a multistage maturation program in the thymic medulla. Such maturation is followed by a tightly regulated emigration process and a further postthymic maturation of recent thymic emigrants (RTEs). This review summarizes recent progress in the late stage T cell development. The regulation of this developmental process is discussed

Effects of Dietary <i>Lonicera flos</i> and <i>Sucutellaria baicalensis</i> Mixed Extracts Supplementation on Reproductive Performance, Umbilical Cord Blood Parameters, Colostrum Ingredients and Immunoglobulin Contents of Late-Pregnant Sows

The present study aimed to determine the effects of dietary Lonicera flos and Sucutellaria baicalensis mixed extract (LSE) supplementation during the late-pregnancy period on the reproductive performance, umbilical cord blood hematological parameters, umbilical cord serum biochemical parameters, immune indices, hormone levels, colostrum ingredients, and immunoglobulin contents of sows. A total of 40 hybrid pregnant sows were randomly assigned to the control group (CON; sows fed a basal diet) and LSE group (LSE; sows fed a basal diet supplemented with 500 g/t PE). The results indicated that dietary LSE supplementation significantly increased (p p p p < 0.05). In conclusion, dietary LSE supplementation in late-pregnancy sows could improve reproductive performance and colostrum quality, and could also regulate the levels of reproductive hormone in umbilical cord serum

Enzyme-photo-coupled catalytic systems

Efficient chemical transformation in a green, low-carbon way is crucial for the sustainable development of modern society. Enzyme-photo-coupled catalytic systems (EPCS) that integrate the exceptional selectivity of enzyme catalysis and the unique reactivity of photocatalysis hold great promise in solar-driven 'molecular editing'. However, the involvement of multiple components and catalytic processes challenged the design of efficient and stable EPCS. To show a clear picture of the complex catalytic system, in this review, we analyze EPCS from the perspective of system engineering. First, we disintegrate the complex system into four elementary components, and reorganize these components into biocatalytic and photocatalytic ensembles (BE and PE). By resolving current accessible systems, we identify that connectivity and compatibility between BE and PE are two crucial factors that govern the performance of EPCS. Then, we discuss the origin of undesirable connectivity and low compatibility, and deduce the possible solutions. Based on these understandings, we propose the designing principles of EPCS. Lastly, we provide a future perspective of EPCS

YPL-SLAM: A Simultaneous Localization and Mapping Algorithm for Point–line Fusion in Dynamic Environments

Simultaneous Localization and Mapping (SLAM) is one of the key technologies with which to address the autonomous navigation of mobile robots, utilizing environmental features to determine a robot’s position and create a map of its surroundings. Currently, visual SLAM algorithms typically yield precise and dependable outcomes in static environments, and many algorithms opt to filter out the feature points in dynamic regions. However, when there is an increase in the number of dynamic objects within the camera’s view, this approach might result in decreased accuracy or tracking failures. Therefore, this study proposes a solution called YPL-SLAM based on ORB-SLAM2. The solution adds a target recognition and region segmentation module to determine the dynamic region, potential dynamic region, and static region; determines the state of the potential dynamic region using the RANSAC method with polar geometric constraints; and removes the dynamic feature points. It then extracts the line features of the non-dynamic region and finally performs the point–line fusion optimization process using a weighted fusion strategy, considering the image dynamic score and the number of successful feature point–line matches, thus ensuring the system’s robustness and accuracy. A large number of experiments have been conducted using the publicly available TUM dataset to compare YPL-SLAM with globally leading SLAM algorithms. The results demonstrate that the new algorithm surpasses ORB-SLAM2 in terms of accuracy (with a maximum improvement of 96.1%) while also exhibiting a significantly enhanced operating speed compared to Dyna-SLAM

Unsupervised Domain Adaptation for Skeleton Recognition with Fourier Analysis

Unsupervised domain adaptation (UDA) methods have recently been explored for their use in skeleton recognition tasks. Much work along this line has been focusing on the “close set” problems, which often deviate from reality as human actions vary in application scenarios. Thus, there remains a need to thoroughly study the “open-set” problems with UDA methods for skeleton recognition, aiming to support those models capable of self-adapting to action changes in different scenarios. To this end, we delve into the “open-set” problems from a feature alignment perspective under UDA settings in reaching domain and class alignment. Specifically, the domain-wise alignment was achieved by the Maximum Mean Discrepancy (MMD) combined with supervision signals from the source domain, which form clear feature boundaries between the “known” and “unknown” classes. Then, the class-wise alignment was achieved by contrastive learning methods, which are distinguished from previous binary classification methods, in reaching compactness inside of “unknown” or “known” classes. Moreover, we conducted the Fourier Analysis during the evaluation phases to verify the model’s robustness. To our knowledge, we are the first to apply the Fourier Heatmap in UDA methods for skeleton recognition. The heatmap visualizes the model’s sensitivity steered for interpretability. Significant performance improvements are observed on the NTU and PKU datasets when adding the domain-wise alignment module to other contrastive learning methods. Furthermore, experimental results demonstrate that our approach, termed CStrCRL-UDA, is consistent with robustness and efficiency on these two benchmark datasets