Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese

The tremendous success of CLIP (Radford et al., 2021) has promoted the research and application of contrastive learning for vision-language pretraining. In this work, we construct a large-scale dataset of image-text pairs in Chinese, where most data are retrieved from publicly available datasets, and we pretrain Chinese CLIP models on the new dataset. We develop 5 Chinese CLIP models of multiple sizes, spanning from 77 to 958 million parameters. Furthermore, we propose a two-stage pretraining method, where the model is first trained with the image encoder frozen and then trained with all parameters being optimized, to achieve enhanced model performance. Our comprehensive experiments demonstrate that Chinese CLIP can achieve the state-of-the-art performance on MUGE, Flickr30K-CN, and COCO-CN in the setups of zero-shot learning and finetuning, and it is able to achieve competitive performance in zero-shot image classification based on the evaluation on the ELEVATER benchmark (Li et al., 2022). We have released our codes, models, and demos in https://github.com/OFA-Sys/Chinese-CLI

Identification of Single Nucleotide Polymorphisms Associated with Hyperproduction of Alpha-Toxin in Staphylococcus aureus

The virulence factor α-toxin (hla) is needed by Staphylococcus aureus in order to cause infections in both animals and humans. Although the complicated regulation of hla expression has been well studied in human S. aureus isolates, the mechanisms of of hla regulation in bovine S. aureus isolates remain undefined. In this study, we found that many bovine S. aureus isolates, including the RF122 strain, generate dramatic amounts of α-toxin in vitro compared with human clinical S. aureus isolates, including MRSA WCUH29 and MRSA USA300. To elucidate potential regulatory mechanisms, we analyzed the hla promoter regions and identified predominant single nucleotide polymorphisms (SNPs) at positions −376, −483, and −484 from the start codon in α-toxin hyper-producing isolates. Using site-directed mutagenesis and hla promoter-gfp-luxABCDE dual reporter approaches, we demonstrated that the SNPs contribute to the differential control of hla expression among bovine and human S. aureus isolates. Using a DNA affinity assay, gel-shift assays and a null mutant, we identified and revealed that an hla positive regulator, SarZ, contributes to the involvement of the SNPs in mediating hla expression. In addition, we found that the bovine S. aureus isolate RF122 exhibits higher transcription levels of hla positive regulators, including agrA, saeR, arlR and sarZ, but a lower expression level of hla repressor rot compared to the human S. aureus isolate WCUH29. Our results indicate α-toxin hyperproduction in bovine S. aureus is a multifactorial process, influenced at both the genomic and transcriptional levels. Moreover, the identification of predominant SNPs in the hla promoter region may provide a novel method for genotyping the S. aureus isolates

Template Route to Chemically Engineering Cavities at Nanoscale: A Case Study of Zn(OH)2 Template

A size-controlled Zn(OH)2 template is used as a case study to explain the chemical strategy that can be executed to chemically engineering various nanoscale cavities. Zn(OH)2 octahedron with 8 vertices and 14 edges is fabricated via a low temperature solution route. The size can be tuned from 1 to 30 μm by changing the reaction conditions. Two methods can be selected for the hollow process without loss of the original shape of Zn(OH)2 template. Ion-replacement reaction is suitable for fabrication of hollow sulfides based on the solubility difference between Zn(OH)2 and products. Controlled chemical deposition is utilized to coat an oxide layer on the surface of Zn(OH)2 template. The abundant hydroxyl groups on Zn(OH)2 afford strong coordination ability with cations and help to the coating of a shell layer. The rudimental Zn(OH)2 core is eliminated with ammonia solution. In addition, ZnO-based heterostructures possessing better chemical or physical properties can also be prepared via this unique templating process. Room-temperature photoluminescence spectra of the heterostructures and hollow structures are also shown to study their optical properties

The C-Terminal Domain of the Novel Essential Protein Gcp Is Critical for Interaction with Another Essential Protein YeaZ of Staphylococcus aureus

Previous studies have demonstrated that the novel protein Gcp is essential for the viability of various bacterial species including Staphylococcus aureus; however, the reason why it is required for bacterial growth remains unclear. In order to explore the potential mechanisms of this essentiality, we performed RT-PCR analysis and revealed that the gcp gene (sa1854) was co-transcribed with sa1855, yeaZ (sa1856) and sa1857 genes, indicating these genes are located in the same operon. Furthermore, we demonstrated that Gcp interacts with YeaZ using a yeast two-hybrid (Y2H) system and in vitro pull down assays. To characterize the Gcp-YeaZ interaction, we performed alanine scanning mutagenesis on the residues of C-terminal segment of Gcp. We found that the mutations of the C-terminal Y317-F322 region abolished the interaction of Gcp and YeaZ, and the mutations of the D324-N329 and S332-Y336 regions alleviated Gcp binding to YeaZ. More importantly, we demonstrated that these key regions of Gcp are also necessary for the bacterial survival since these mutated Gcp could not complement the depletion of endogenous Gcp. Taken together, our data suggest that the interaction of Gcp and YeaZ may contribute to the essentiality of Gcp for S. aureus survival. Our findings provide new insights into the potential mechanisms and biological functions of this novel essential protein

A New Urban Waterlogging Simulation Method Based on Multi-Factor Correlation

Waterlogging simulation is a key technology for solving urban waterlogging problems. The current waterlogging modeling process is relatively complex and requires high basic data, which is not conducive to rapid modeling and popularization. In this study, we evaluated the correlation between rainfall and waterlogging water using the following factors: terrain, evaporation, infiltration, pipe drainage capacity, and river flood water level. By quantifying the influence value of each factor on rainfall, we established a simplified model for fast calculation of waterlogging depth through input rainfall. Waterlogging data was collected from Guangzhou, China to set up the multi-factor correlation model, and verify the simulation results of the model. After the original rainfall is added/deducted, the added/loss value, the relationship between net rainfall, and maximum water depth is better than that between original rainfall and maximum water depth. Establishing a stable multi-factor correlation model for a waterlogging point requires at least three historical waterlogging event data for parameter calibration by sensitivity analysis. Comparing the simulation of four waterlogging points, the multi-factor correlation model (error = −13%) presented the least error in simulating the maximum water volume, followed by the Mike Urban model (error = −19%), and finally the SWMM model (error = 20%). Furthermore, the multi-factor correlation model and SWMM model required the least calculation time (less than 1 s), followed by the Mike Urban model (About half a minute). By analyzing the waterlogging data of Guangzhou, 42 waterlogging points with modeling conditions were screened out to further validate the multi-factor correlation model. Each waterlogging point was modeled based on the historical field, and the last rainstorm was used for model verification. The mean error of the comparison between the simulated maximum waterlogging and the measured maximum waterlogging was 3%, and the R2 value was 0.718. In summary, the multi-factor correlation model requires fewer basic data, has a simple modeling process and wide applicability, and makes it easy to realize the intelligent parameter adjustment, which is more suitable for the urgent requirements of current urban waterlogging prediction. The model results may prove accurate and provide scientific decision support for the prevention and control of urban waterlogging

Optimal Decision-Making Model of Agricultural Product Information Based on Three-Way Decision Theory

As an effective heuristic method, three-way decision theory gives a new semantic interpretation to the three fields of the rough set, which has a huge application space. To classify the information of agricultural products more accurately under certain thresholds, this paper first makes a comprehensive evaluation of the decision, particularly the influence of the attributes of the event itself on the results and their interactions. By using fuzzy sets corresponding to membership and non-membership degree, this paper analyzes and puts forward two cases of proportional correlation coefficients in the transformation of a delayed decision domain, and selects the corresponding coefficients to compare the results directly. Finally, consumers can conveniently grasp product attribute information to make decisions. On this basis, this paper analyzed the standard data to verify the accuracy of the model. After that, the proposed algorithm, based on three decision-making agricultural product information classification processing, is applied to the relevant data of agricultural products. The experimental results showed that the algorithm can obtain more accurate results through a more straightforward calculation process. It can be concluded that the algorithm proposed in this paper can enable people to make more convenient and accurate decisions based on product attribute information

Identification of a Novel Essential Two-Component Signal Transduction System, YhcSR, in Staphylococcus aureus

Two-component signal transduction systems play an important role in the ability of bacteria to adapt to various environments by sensing changes in their habitat and by altering gene expression. In this study, we report a novel two-component system, YhcSR, in Staphylococcus aureus which is required for bacterial growth in vitro. We found that the down-regulation of yhcSR expression by induced yhcS antisense RNA can inhibit and terminate bacterial growth. Moreover, without complementary yhcS or yhcR, no viable yhcS or yhcR gene replacement mutant was recoverable. Collectively, these results demonstrated that the YhcSR regulatory system is indispensable for S. aureus growth in culture. Moreover, induced yhcS antisense RNA selectively increased bacterial susceptibility to phosphomycin. These data suggest that YhcSR probably modulates the expression of genes critical for bacterial survival and may be a potential target for the development of novel antibacterial agents

Identification and Validation of a Novel Antibacterial Compound MZ-01 against Methicillin-Resistant Staphylococcus aureus

The discovery of new classes of antibiotics is slow, and it is being greatly outpaced by the development of bacterial resistance. This disparity places us in an increasingly vulnerable position because we are running out of safe and effective therapeutic options to treat antibiotic-resistant infections. This is exemplified by the emergence and persistence of hospital-acquired and community-associated methicillin-resistant S. aureus (MRSA), which has markedly narrowed our options for treating life-threatening staph infections. Thus, there is an urgent need to develop novel, potent, preventive, and therapeutic agents. In our current study, we performed a whole-cell screening assay of synthetic libraries for antibacterial activity and identified a novel molecule, MZ-01. MZ-01 exhibited potent bactericidal activity against Gram-positive bacterial pathogens, including MRSA, Streptococcus pyogenes, and Streptococcus pneumoniae, at low concentrations. MZ-01 killed and lysed both the late exponential phase of an S. aureus population and bacteria inside mammalian cells. Furthermore, MZ-01 exhibited low cytotoxicity. These results indicate that MZ-01 is a promising scaffold to guide the development of novel, potent antibacterial agents against multidrug-resistant Gram-positive bacterial pathogens such as MRSA