ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation

In addition to the unprecedented ability in imaginary creation, large text-to-image models are expected to take customized concepts in image generation. Existing works generally learn such concepts in an optimization-based manner, yet bringing excessive computation or memory burden. In this paper, we instead propose a learning-based encoder, which consists of a global and a local mapping networks for fast and accurate customized text-to-image generation. In specific, the global mapping network projects the hierarchical features of a given image into multiple new words in the textual word embedding space, i.e., one primary word for well-editable concept and other auxiliary words to exclude irrelevant disturbances (e.g., background). In the meantime, a local mapping network injects the encoded patch features into cross attention layers to provide omitted details, without sacrificing the editability of primary concepts. We compare our method with existing optimization-based approaches on a variety of user-defined concepts, and demonstrate that our method enables high-fidelity inversion and more robust editability with a significantly faster encoding process. Our code is publicly available at https://github.com/csyxwei/ELITE.Comment: Accepted by ICCV 2023, oral presentation. Code: https://github.com/csyxwei/ELIT

Ref-Diff: Zero-shot Referring Image Segmentation with Generative Models

Zero-shot referring image segmentation is a challenging task because it aims to find an instance segmentation mask based on the given referring descriptions, without training on this type of paired data. Current zero-shot methods mainly focus on using pre-trained discriminative models (e.g., CLIP). However, we have observed that generative models (e.g., Stable Diffusion) have potentially understood the relationships between various visual elements and text descriptions, which are rarely investigated in this task. In this work, we introduce a novel Referring Diffusional segmentor (Ref-Diff) for this task, which leverages the fine-grained multi-modal information from generative models. We demonstrate that without a proposal generator, a generative model alone can achieve comparable performance to existing SOTA weakly-supervised models. When we combine both generative and discriminative models, our Ref-Diff outperforms these competing methods by a significant margin. This indicates that generative models are also beneficial for this task and can complement discriminative models for better referring segmentation. Our code is publicly available at https://github.com/kodenii/Ref-Diff

Research on synchronverter-based regenerative braking energy feedback system of urban rail transit

Generally running with frequent braking over short distances, the urban rail transit train generates great quantities of regenerative braking energy (RBE). The RBE feedback system can effectively recycle RBE and give it back to the AC grid. However, the lack of damp and inertia of generators makes conventional PWM RBE feedback system more sensitive to power fluctuations. To address this issue, a synchronverter-based RBE feedback system of urban rail transit is designed in this paper. First, the structure of the feedback system is presented. Then, the synchronverter-based control strategy with greater flexibility and higher stability is fully discussed. Furthermore, the parameter design of the system is analyzed in detail. Finally, simulation results and experimental results are provided to show the good dynamic performance of the system. Using this synchronverter-based approach, the system supplies traction power to the traction network when the train accelerates and gives the RBE back to the AC grid when the train brakes, in light of the variation of the DC bus voltage. Moreover, the system can be self-synchronized with the AC grid and make corresponding power management on the basis of changes in the voltage amplitude as well as the frequency of the grid. In this sense, the RBE feedback system becomes more flexible, effective and robust

Sclerotinia sclerotiorum Thioredoxin Reductase Is Required for Oxidative Stress Tolerance, Virulence, and Sclerotial Development

Sclerotinia sclerotiorum is a destructive ascomycete plant pathogen with worldwide distribution. Extensive research on different aspects of this pathogen’s capability to cause disease will help to uncover clues about new ways to safely control Sclerotinia diseases. The thioredoxin (Trx) system consists of Trx and thioredoxin reductase (TrxR), which play critical roles in maintenance of cellular redox homeostasis. In this study, we functionally characterized a gene encoding a TrxR (SsTrr1) in S. sclerotiorum. The amino acids of SsTrr1 exhibited high similarity with reported TrxRs in plant pathogens and targeted silencing of SsTrr1 lead to a decrease in TrxR activities of mycelium. SsTrr1 showed high expression levels during hyphae growth, and the levels decreased at the different stages of sclerotial development. SsTrr1 gene-silenced strains produced a smaller number of larger sclerotia on potato dextrose agar medium. The observations were consistent with the inhibitory effects on sclerotial development by the TrxR inhibitor, anrunofin. The expression of SsTrr1 showed a dramatic increase under the oxidative stress and the hyphal growth of gene-silenced strains showed more sensitivity to H2O2. SsTrr1 gene-silenced strains also showed impaired virulence in different hosts. Taken together, our results suggest that SsTrr1 encodes a TrxR that is of great important for oxidative stress tolerance, virulence, and sclerotial development of S. sclerotiorum

Nitrogen rather than streamflow regulates the growth of riparian trees

In arid and semiarid regions, riparian forests are crucial for maintaining ecological biodiversity and sustainability, and supporting social and economic development. For the typical arid and semiarid ecosystem, streamflow variability is thought to be the dominant factor influencing the vulnerability and evolution of the riparian forests, which often leads to the neglect of other potentially important factors such as nutrient availability and transport. Here, we measured annual stable nitrogen isotopes (δ15N) and nitrogen concentrations (N%) in the tree rings of Populus euphratica Oliv. (Euphrates poplar) over a 90 year period (1920–2012), collected from the lower researches of the inland Heihe River, northwestern China. Coupling with our previous dual-isotope (δ13C and δ18O) chronologies and estimated intrinsic water-use efficiency (iWUE), we examined the linkages between tree-ring δ15N and δ18O, iWUE, streamflow, and then explored the contributions of each to tree growth during the study period. Our results show that after 1975, a statistically significant correlation between tree-ring δ15N and river streamflow appears, indicating the river as a potential carrier of nitrogen from the upper and middle reaches to the lower research trees. In addition, the linkage between tree-ring δ15N and iWUE suggests substantial influence of carbon and nitrogen together on photosynthesis and transpiration of trees, although this connection become decoupled since AD 1986. The commonality analysis revealed that the nitrogen impacts indicated by tree-ring δ15N on tree growth cannot be ignored when evaluating riparian forest development. The fertilization effects caused by rising CO2 concentration complicate the nitrogen constraints on tree growth during the later part of the past century. Our results have potentially broad implications for identifying the limited factors for dryland forest ecosystems that are susceptible to natural water resource variations and human activities

Characterization of a Novel blaKLUC Variant With Reduced β-Lactam Resistance From an IncA/C Group Plasmid in a Clinical Klebsiella pneumoniae Isolate

Similar to other CTX-M family enzymes, KLUC is a recently identified and emerging determinant of cefotaxime resistance that has been recovered from at least three Enterobacteriaceae species, including Kluyvera cryocrescens, Escherichia coli, and Enterobacter cloacae. Whether this extended-spectrum β-lactamase (ESBL) has been disseminated among commonly isolated Enterobacteriaceae is worthy of further investigation. In this study, we screened 739 nosocomial Enterobacteriaceae isolates (240 Klebsiella pneumoniae and 499 E. coli strains) and found that one K. pneumoniae and four E. coli isolates harbored the blaKLUC gene. Three blaKLUC determinants isolated from E. coli were entirely identical to a blaKLUC-3 gene previously recovered in the same hospital. PFGE of four blaKLUC-harboring E. coli strains showed that prevalence of these determinants was most likely mediated by horizontal gene transfer but not clonal dissemination. However, the variant isolated from K. pneumoniae belonged to a novel member of the KLUC enzyme group. This newly identified enzyme (KLUC-5) has an amino acid substitution compared with previously identified KLUC-1 (G18S) and KLUC-3 (G240D). Antimicrobial susceptibility tests showed that KLUC-5 significantly reduced resistance activity to almost all the selected antimicrobials compared to previously identified KLUC-3. Site-directed mutagenesis showed that blaKLUC-5-D240G and blaKLUC-5-S18G significantly enhanced the MIC against its best substrate. Conjugation and S1-PFGE indicated that blaKLUC-5 was located on a transferable plasmid, which was further decoded by single-molecule, real-time sequencing. Comparative genome analysis showed that its backbone exhibited genetic homology to the IncA/C incompatibility group plasmids. A transposable element, ISEcp1, was detected 256-bp upstream of the blaKLUC-5 gene; this location was inconsistent with the previously identified blaKLUC-1 but congruent with the variants recovered from E. coli in the same hospital. These data provide evidence of the increasingly emerging KLUC group of ESBLs in China