Jiangyong Wang

Hemifusus tuba (Gmelin, 1791) is a commercial marine gastropod that undergoes an ontogenetic dietary transition from egg-capsule nutrition (lecithotrophy) to herbivory and finally to lifelong carnivory. How associated microbiota respond to this feeding habit transition remained largely unexplored. Here, we characterized taxonomic composition, diversity and functional prediction of associated microbiota in H. tuba across three dietary stages (CK, egg-capsule nutrition or lecithotrophic; He, herbivory; Ca, carnivory) using 16S rRNA amplicon sequencing. A total of 457,412 high-quality reads from 14 libraries were clustered into 12,091 OTUs, identifying 811 genera within 38 phyla. And five dominant phyla ( Proteobacteria , Bacteroidota , Firmicutes , Actinobacteriota , and Planctomycetota ) accounted for 99% of total abundance and formed the core microbiota. Alpha diversity increased from CK to He and peaked in Ca, whereas beta diversity analyses consistently separated Ca from CK and He, indicating microbiota restructuring following the transition to carnivory. During the feeding habit transition, Proteobacteria and Planctomycetota increased, while Bacteroidota , Firmicutes , and Actinobacteriota declined. LEfSe identified Hyphomicrobiales / Bradyrhizobiaceae , Burkholderiales / Betaproteobacteria , and Rhodobacterales / Roseobacteraceae as biomarkers for CK, He, and Ca, respectively. PICRUSt2 functional predictions indicated that CK enriched for tryptophan and butyrate metabolism and fatty acid degradation, whereas Ca appeared to be enriched for methane and pyruvate metabolism and the TCA cycle. These diet-associated microbiome shifts might facilitate nutrient utilization and energy metabolism during feeding habit transition, and provided microbial candidates for feed optimization in H. tuba domestication.

In order to study the symptoms and pathogenesis mechanism of Crassostrea hongkongensis infected with polychaete ciliates, the polychaete ciliate was identified by molecular identification, the mantle tissues of infected oysters and healthy oysters were observed by light microscope and transmission electron microscope, and the gill tissues of infected and healthy oyster were observed by transmission electron microscope. The symptoms of infected oysters were black mud tubes filling the inner and outer surfaces of the shell, ulceration of the soft body, darkening of the color, atrophy and erosion of the mantle and other tissues, and an increase in mucus. Micropathological changes included tearing of connective tissue, dissolution, disappearing crest protrusions, an increase in secretory cells, Cytoplasmic pyknosis, nuclear membrane rupture, contraction and dissolution of nuclei, and partial or complete disappearance of organelles. Additionally, the secretory cells of infected individuals showed nuclear aberration and some secretory granules overflowed.

Sputter depth profiling has been widely used for analyzing the in-depth compositional distribution in thin films. However, due to the unavoidable distortions in sputter depth profiling, the quantitative analysis of measured depth profiling data requires a modeling approach. By estimating parameters such as the original film structure, roughness, elemental sputtering rate, and mixing length, we can fit a model to the experimental data and correct for these distortions. This allows us to obtain a more accurate representation of the original film structure. In this paper, two methods—the simulated annealing algorithm and the golden section search algorithm—are proposed for obtaining automatically and accurately the sputtering-induced roughness that often occurs upon depth profiling of polycrystalline films. When comparing these two methods, the golden section search algorithm demonstrates superior efficiency and precision under low-noise conditions, thereby reducing computational time and error. While, under high-noise conditions, the simulated annealing algorithm achieves greater accuracy at the cost of significantly higher computational time. As an example, the measured Auger electron spectroscopy depth profiling data of 4 × Si(15 nm)/Al(15 nm)/Si(100) multilayers are used for obtaining automatically the sputtering-induced roughness by these two methods. It is suggested that the golden section method offers an effective balance between computational time and accuracy.

In this paper, a method for the dynamic optimization of the iteration step τ in Newton’s method is proposed, based on the golden section search algorithm. This method combines the total variation-Tikhonov regularization, Newton’s method, and the L-curve criterion by the simulated annealing algorithm for reconstruction of the original nano layer structure directly from the measured depth profiling data. The golden section search algorithm finds the optimal value for each iteration step and makes the iteration procedure to converge quickly with high computational efficiency. The deconvolution results show that the total deconvolution speed is improved by nearly 154 times with a deconvolution error of 8.7 × 10−14% as compared to the previous studies with a constant of τ, indicating an excellent reconstruction of the original “square-wave like” layer structure. In addition, this method could deal with the depth profiling data containing sputtering-induced roughness and/or Gaussian noise. Finally, this method is applied for the reconstruction of the original layer structure from the measured Auger electron spectroscopy depth profiling data of 4 × Si(15 nm)/Al(15 nm)/Si(100).

To ensure the operational reliability of MMC valve, it is necessary to conduct short circuit and overcurrent turn-off tests before leaving the factory to investigate its ability to withstand critical stresses under actual working conditions and the correctness of its design. However, the existing test methods have a large volume of test devices, complex processes, and need for separate tests to verify the reliability of the devices. Therefore, with the goal of reducing device volume, cost, and completing multiple tests with a single device, a synthetic method based on an equivalent current source is proposed. Firstly, the DC bipolar short circuit current stress model is analyzed, and based on this, the device topology and its principle are proposed. Then, based on the experimental topology, a simulation model is built and a composite test of 8GW MMC valve short circuit and overcurrent turn-off is conducted. The result indicates the feasibility of the proposed experimental method.

This comment is a summary of scientifically evident shortcomings of the so-called recoil-mixing-roughness (RMR)-model proposed in several publications by Kudriavtsev et al. in order to describe the formation of sputter depth profiles of concentration.

Numerical research is done on grain boundary diffusion of Cu-Ni bilayer thin films. Together, the composition-dependent interdiffusion coefficient and the position of the grain boundary are considered. Fick’s second law provides a quantitative assessment of the effects of grain size, volume, grain boundary diffusion coefficient, diffusion temperature, and time on the depth profile. Regarding the situation where the plateau values of the Ni concentration in the Cu layer and the Cu concentration in the Ni layer are almost the same for the case where the Ni intrinsic diffusion coefficient is significantly bigger than that for Cu, a detailed explanation is provided. We may produce a profile that is like the direct volume diffusion profile with a relative inaccuracy of 7.53% by using a method that is provided to eliminate the impacts of grain boundaries and grain size on the grain boundary diffusion profile. For most of the circumstances covered in this study, the technique is effective. The transformation of the grain boundary diffusion profile yields a composition-dependent interdiffusion coefficient, and the calculation’s outcome is consistent with the theoretical conclusion drawn from the Darken equation. Thin films of Cu (150 nm)/Ni (150 nm)/SiOx/Si (100 nm) were produced as examples, and Auger electron spectroscopy was used to determine the respective depth profiles. The calculated diffusion parameters, namely, the pre-exponential factor and the activation energy, are well within the bounds of the available data.