Evolution of the edge states and corner states in a multilayer honeycomb valley-Hall topological metamaterial

The valley-Hall effect provides topological protection to a broad class of defects in valley-Hall photonic topological metamaterials. Unveiling precisely how such protection is achieved and its implications in practical implementations is paramount to move from fundamental science to applications. To this end, we investigate a honeycomb valley-Hall topological metamaterial and monitor the evolution of the topological valley-Hall edge states and higher-order corner states under different perturbation δR. The evolutions of the edge states of the armchair and zigzag interfaces are demonstrated, respectively. By adjusting the geometric parameters and introducing disturbances to break the inversion symmetry, we achieve the edge states with different modes including the conventional crossed edge state and the specific gapped edge state. It is found that the edge states of topological valley kinking will gradually separate with the increase of δR, and finally a complete gap between the edge states appears. The gap has rarely been reported previously in topological materials fabricated by printed circuit board technology. In addition, the higher-order topological corner states can also be observed in the proposed topological metamaterial. The higher-order topological phase is theoretically characterized by nontrivial bulk polarization and the Wannier centers. Our results show that the corner state localization becomes stronger with the increase of δR. It is expected that our results will provide a platform for the realization of optical topological insulators

Roles of sulfate-reducing bacteria in sustaining the diversity and stability of marine bacterial community

Microbes play central roles in ocean food webs and global biogeochemical processes. Yet, the information available regarding the highly diverse bacterial communities in these systems is not comprehensive. Here we investigated the diversity, assembly process, and species coexistence frequency of bacterial communities in seawater and sediment across ∼600 km of the eastern Chinese marginal seas using 16S rRNA gene amplicon sequencing. Our analyses showed that compared with seawater, bacterial communities in sediment possessed higher diversity and experienced tight phylogenetic distribution. Neutral model analysis showed that the relative contribution of stochastic processes to the assembly process of bacterial communities in sediment was lower than that in seawater. Functional prediction results showed that sulfate-reducing bacteria (SRB) were enriched in the core bacterial sub-communities. The bacterial diversities of both sediment and seawater were positively associated with the relative abundance of SRB. Co-occurrence analysis showed that bacteria in seawater exhibited a more complex interaction network and closer co-occurrence relationships than those in sediment. The SRB of seawater were centrally located in the network and played an essential role in sustaining the complex network. In addition, further analysis indicated that the SRB of seawater helped maintain the high stability of the bacterial network. Overall, this study provided further comprehensive information regarding the characteristics of bacterial communities in the ocean, and provides new insights into keystone taxa and their roles in sustaining microbial diversity and stability in ocean

The Murine Reg3a Stimulated by Lactobacillus casei Promotes Intestinal Cell Proliferation and Inhibits the Multiplication of Porcine Diarrhea Causative Agent in vitro

Lactobacillus casei (L. casei), a normal resident of the gastrointestinal tract of mammals, has been extensively studied over the past few decades for its probiotic properties in clinical and animal models. Some studies have shown that some bacterium of Lactobacillus stimulate the production of antimicrobial peptides in intestinal cells to clear enteric pathogens, however, which antimicrobial peptides are produced by L. casei stimulation and its function are still not completely understood. In this study, we investigated the changes of antimicrobial peptides’ expression after intragastric administration of L. casei to mice. The bioinformatics analysis revealed there were nine genes strongly associated with up-regulated DEGs. But, of these, only the antimicrobial peptide mReg3a gene was continuously up-regulated, which was also confirmed by qRT-PCR. We found out the mReg3a expressed in engineering E.coli promoted cell proliferation and wound healing proved by CCK-8 assay and wound healing assay. Moreover, the tight junction proteins ZO-1 and E-cadherin in mReg3a treatment group were significantly higher than that in the control group under the final concentration of 0.2 mg/ml both in Porcine intestinal epithelial cells (IPEC-J2) and Mouse intestinal epithelial cells (IEC-6) (p < 0.05). Surprisingly, the recombinant mReg3a not only inhibited Enterotoxigenic Escherichia coli (ETEC), but also reduced the copy number of the piglet diarrheal viruses, porcine epidemic diarrhea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV), and porcine rotavirus (PoRV), indicating the antimicrobial peptides mReg3a may be feed additives to resist the potential of the intestinal bacterial and viral diarrhea disease

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

A common variant near TGFBR3 is associated with primary open angle glaucoma

Primary open angle glaucoma (POAG), a major cause of blindness worldwide, is a complex disease with a significant genetic contribution. We performed Exome Array (Illumina) analysis on 3504 POAG cases and 9746 controls with replication of the most significant findings in 9173 POAG cases and 26 780 controls across 18 collections of Asian, African and European descent. Apart from confirming strong evidence of association at CDKN2B-AS1 (rs2157719 [G], odds ratio [OR] = 0.71, P = 2.81 × 10−33), we observed one SNP showing significant association to POAG (CDC7–TGFBR3 rs1192415, ORG-allele = 1.13, Pmeta = 1.60 × 10−8). This particular SNP has previously been shown to be strongly associated with optic disc area and vertical cup-to-disc ratio, which are regarded as glaucoma-related quantitative traits. Our study now extends this by directly implicating it in POAG disease pathogenesis

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Abstract Primary open angle glaucoma (POAG), a major cause of blindness worldwide, is a complex disease with a significant genetic contribution. We performed Exome Array ), we observed one SNP showing significant association to POAG (CDC7-TGFBR3 rs1192415, OR G-allele = 1.13, P meta = 1.60 × 10 −8 ). This particular SNP has previously been shown to be strongly associated with optic disc area and vertical cup-to-disc ratio, which are regarded as glaucoma-related quantitative traits. Our study now extends this by directly implicating it in POAG disease pathogenesis

Evaluation of Remote Sensing and Reanalysis Snow Depth Datasets over the Northern Hemisphere during 1980–2016

Snow cover is a key parameter of the climate system and its significant seasonal and annual variability have significant impacts on the surface energy balance and global water circulation. However, current snow depth datasets show large inconsistencies and uncertainties, which limit their applications in climate change projections and hydrological processes simulations. In this study, a comprehensive assessment of five hemispheric snow depth datasets was carried out against ground observations from 43,391 stations. The five snow depth datasets included three remote sensing datasets, i.e., Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), Advanced Microwave Scanning Radiometer-2 (AMSR2), Global Snow Monitoring for Climate Research (GlobSnow), and two reanalysis datasets, i.e., ERA-Interim and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Assessment results imply that the spatial distribution of GlobSnow and ERA-Interim exhibit overall better agreements with ground observations than other datasets. GlobSnow and ERA-Interim exhibit less uncertainty during the snow accumulation and ablation periods, respectively. In plain and forested regions, GlobSnow, ERA-Interim and MERRA-2 show better performances, while in mountain and forested mountain areas, GlobSnow exhibits the best performance. AMSR-E and AMSR2 agree better with ground observations in shallow snow condition (0–10 cm), while MERRA-2 shows more satisfying performance when snow depth exceeds 50 cm. These systematic and integrated understanding of the five representative snow depth datasets provides information on data selection and data refinement, as well as data fusion, which is our next work of interest