Data-Driven Modeling of Landau Damping by Physics-Informed Neural Networks

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this study, we successfully construct a multi-moment fluid model with an implicit fluid closure included in the neural network using machine learning. The multi-moment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informed neural network (gPINN). The multi-moment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. For the first time, we introduce a new variant of the gPINN architecture, namely, gPINN$p$ to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN$p$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN$p$-constructed multi-moment fluid model offers the most accurate results. This work sheds new light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.Comment: 11 pages, 7 figure

PCR-Based Seamless Genome Editing with High Efficiency and Fidelity in <i>Escherichia coli</i>

Efficiency and fidelity are the key obstacles for genome editing toolboxes. In the present study, a PCR-based tandem repeat assisted genome editing (TRAGE) method with high efficiency and fidelity was developed. The design of TRAGE is based on the mechanism of repair of spontaneous double-strand breakage (DSB) via replication fork reactivation. First, cat-sacB cassette flanked by tandem repeat sequence was integrated into target site in chromosome assisted by Red enzymes. Then, for the excision of the cat-sacB cassette, only subculturing is needed. The developed method was successfully applied for seamlessly deleting, substituting and inserting targeted genes using PCR products. The effects of different manipulations including sucrose addition time, subculture times in LB with sucrose and stages of inoculation on the efficiency were investigated. With our recommended procedure, seamless excision of cat-sacB cassette can be realized in 48 h efficiently. We believe that the developed method has great potential for seamless genome editing in E. coli

Determinants of the Incidence of Hand, Foot and Mouth Disease in China Using Geographically Weighted Regression Models

Child population density and climate factors are potential determinants of the HFMD incidence in most areas in China. The strength and direction of association between these factors and the incidence of HFDM is spatially heterogeneous at the local geographic level, and child population density has a greater influence on the incidence of HFMD than the climate factors

EEG Feature Analysis Related to Situation Awareness Assessment and Discrimination

In order to discriminate situation awareness (SA) levels on the basis of SA-sensitive electroencephalography (EEG) features, the high-SA (HSA) group and low-SA (LSA) groups, which are representative of two SA levels, were classified according to the situation awareness global assessment technology (SAGAT) scores measured in the multi-attribute task battery (MATB) II tasks. Furthermore, three types of EEG features, namely, absolute power, relative power, and slow-wave/fast-wave (SW/FW), were explored using spectral analysis. In addition, repeated analysis of variance (ANOVA) was conducted in three brain regions (frontal, central, and parietal) &times; three brain lateralities (left, middle, and right) &times; two SA groups (LSA and HSA) to explore SA-sensitive EEG features. The statistical results indicate a significant difference between the two SA groups according to SAGAT scores; moreover, no significant difference was found for the absolute power of four waves (delta (&delta;), theta (&theta;), alpha (&alpha;), and beta (&beta;)). In addition, the LSA group had a significantly lower &beta; relative power than the HSA group in central and partial regions. Lastly, compared with the HSA group, the LSA group had higher &theta;/&beta; and (&theta; + &alpha;)/(&alpha; + &beta;) in all analyzed brain regions, higher &alpha;/&beta; in the parietal region, and higher (&theta; + &alpha;)/&beta; in all analyzed regions except for the left and right laterality in the frontal region. The above SA-sensitive EEG features were fed into principal component analysis (PCA) and the Bayes method to discriminate different SA groups, and the accuracies were 83.3% for the original validation and 70.8% for the cross-validation. The results provide a basis for real-time assessment and discrimination of SA by investigating EEG features, thus contributing to monitoring SA decrement that might lead to threats to flight safety

EEG Feature Analysis Related to Situation Awareness Assessment and Discrimination

In order to discriminate situation awareness (SA) levels on the basis of SA-sensitive electroencephalography (EEG) features, the high-SA (HSA) group and low-SA (LSA) groups, which are representative of two SA levels, were classified according to the situation awareness global assessment technology (SAGAT) scores measured in the multi-attribute task battery (MATB) II tasks. Furthermore, three types of EEG features, namely, absolute power, relative power, and slow-wave/fast-wave (SW/FW), were explored using spectral analysis. In addition, repeated analysis of variance (ANOVA) was conducted in three brain regions (frontal, central, and parietal) × three brain lateralities (left, middle, and right) × two SA groups (LSA and HSA) to explore SA-sensitive EEG features. The statistical results indicate a significant difference between the two SA groups according to SAGAT scores; moreover, no significant difference was found for the absolute power of four waves (delta (δ), theta (θ), alpha (α), and beta (β)). In addition, the LSA group had a significantly lower β relative power than the HSA group in central and partial regions. Lastly, compared with the HSA group, the LSA group had higher θ/β and (θ + α)/(α + β) in all analyzed brain regions, higher α/β in the parietal region, and higher (θ + α)/β in all analyzed regions except for the left and right laterality in the frontal region. The above SA-sensitive EEG features were fed into principal component analysis (PCA) and the Bayes method to discriminate different SA groups, and the accuracies were 83.3% for the original validation and 70.8% for the cross-validation. The results provide a basis for real-time assessment and discrimination of SA by investigating EEG features, thus contributing to monitoring SA decrement that might lead to threats to flight safety

Atomic-level imaging of zeolite local structures using electron ptychography

Zeolites are among the most important heterogeneous catalysts, widely employed in separation reaction, fine chemical production, and petroleum refining. Through rational design of the frameworks, zeolites with versatile functions can be synthesized. Local imaging of zeolite structures at the atomic scale, including the basic framework atoms (Si, Al, and O) and extra-framework cations, is necessary to understand the structure–function relationship of zeolites. Herein, we implemented electron ptychography into direct imaging of local structures of two zeolites, Na-LTA and ZSM-5. Not only all the framework atoms but also extra-framework Na+ cations with only 1/4 occupation probabilities in Na-LTA were directly observed. Local structures of ZSM-5 zeolites having guest molecules among channels with different orientations were also unraveled using different reconstruction algorithms. The approach presented here provides a new way to locally image zeolites structure, and it is expected to be an essential key for further studying and tuning zeolites active sites at the atomic level.This work was supported by the Major State Basic Research Development Program of China (2022YFA1603703, 2022YFA1506000), the National Natural Science Foundation of China (21835002, 22222108, 92045303, 12027804, 21727817), the Shanghai Science and Technology Plan (21DZ2260400), the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB37040303), the Spanish National Research Council (CSIC) through the i-COOP program (COOPA20470), and CℏEM, School of Physical Science and Technology, ShanghaiTech University (#EM02161943). A.M. also thanks the Spanish Ministry of Science (RYC2018-024561-I), DGA (E13_20R), and European Union’s Horizon 2020 research and innovation program under grant agreement No. 823717-ESTEEM3.Peer reviewe

Hydroxypropyltrimethyl ammonium chloride chitosan-based hydrogel as the split H5N1 mucosal adjuvant: Structure-activity relationship

In this study, 2-hydroxypropyltrimethyl ammonium chloride chitosan (HTCC)-based hydrogel was devised as a mucosal adjuvant for H5N1 vaccine. Aimed to investigate the structure activity relationship between HTCC hydrogel and immune response, we prepared a series of HTCC hydrogel with defined quaternization degrees (DQs, 0%, 21%, 41%, 60%, 80%). Results suggested that with DQ increasing, the positive charge and gelation time of HTCC hydrogel increased but the viscosity decreased. We applied in vivo imaging system and found that the moderate DQ 41% prolonged antigen residence time in nasal cavity, resulting in the most potent systemic responses (IgG, IgG1, IgG2a, HI). While, the lowest DQ 0% produced the best mucosal IgA antibody responses, most likely due to the closer contact with mucosa. Furthermore, the influence of animal gender was also discussed. These data add to the growing understanding of the relationship between physicochemical features of chitosan-based hydrogel and how they influence the immune responses

The <i>Arabidopsis</i> Receptor-like Kinase CAP1 Promotes Shoot Growth under Ammonium Stress

High levels of ammonium (NH4+) in soils inhibit plant growth and nitrogen utilization efficiency. Elucidating the underlying mechanisms of NH4+ toxicity is essential for alleviating the growth inhibition caused by high NH4+. Our previous work showed that [Ca2+]cyt-associated protein kinase 1 (CAP1) regulates root hair growth in response to NH4+ in Arabidopsis thaliana, and the cap1-1 mutant produces short root hairs under NH4+ stress conditions. However, it is unclear whether CAP1 functions in other physiological processes in response to NH4+. In the present study, we found that CAP1 also plays a role in attenuating NH4+ toxicity to promote shoot growth. The cap1-1 mutant produced smaller shoots with smaller epidermal cells compared with the wild type in response to NH4+ stress. Disruption of CAP1 enhanced the NH4+-mediated inhibition of the expression of cell enlargement-related genes. The cap1-1 mutant showed elevated reactive oxygen species (ROS) levels under NH4+ stress, as well as increased expression of respiratory burst oxidase homologue genes and decreased expression of catalase genes compared with the wild type. Our data reveal that CAP1 attenuates NH4+-induced shoot growth inhibition by promoting cell wall extensibility and ROS homeostasis, thereby highlighting the role of CAP1 in the NH4+ signal transduction pathway

Microstructures and Mechanical Properties of a Nanostructured Al-Zn-Mg-Cu-Zr-Sc Alloy under Natural Aging

Nanocrystalline (NC) structure can lead to the considerable strengthening of metals and alloys. Obtaining appropriate comprehensive mechanical properties is always the goal of metallic materials. Here, a nanostructured Al-Zn-Mg-Cu-Zr-Sc alloy was successfully processed by high-pressure torsion (HPT) followed by natural aging. The microstructures and mechanical properties of the naturally aged HPT alloy were analyzed. The results show that the naturally aged HPT alloy primarily consists of nanoscale grains (~98.8 nm), nano-sized precipitates (20–28 nm in size), and dislocations (1.16 × 1015 m−2), and exhibits a high tensile strength of 851 ± 6 MPa and appropriate elongation of 6.8 ± 0.2%. In addition, the multiple strengthening modes that were activated and contributed to the yield strength of the alloy were evaluated according to grain refinement strengthening, precipitation strengthening, and dislocation strengthening, and it is shown that grain refinement strengthening and precipitation strengthening are the main strengthening mechanisms. The results of this study provide an effective pathway for achieving the optimal strength–ductility match of materials and guiding the subsequent annealing treatment