TIER: Text-Image Encoder-based Regression for AIGC Image Quality Assessment

Recently, AIGC image quality assessment (AIGCIQA), which aims to assess the quality of AI-generated images (AIGIs) from a human perception perspective, has emerged as a new topic in computer vision. Unlike common image quality assessment tasks where images are derived from original ones distorted by noise, blur, and compression, \textit{etc.}, in AIGCIQA tasks, images are typically generated by generative models using text prompts. Considerable efforts have been made in the past years to advance AIGCIQA. However, most existing AIGCIQA methods regress predicted scores directly from individual generated images, overlooking the information contained in the text prompts of these images. This oversight partially limits the performance of these AIGCIQA methods. To address this issue, we propose a text-image encoder-based regression (TIER) framework. Specifically, we process the generated images and their corresponding text prompts as inputs, utilizing a text encoder and an image encoder to extract features from these text prompts and generated images, respectively. To demonstrate the effectiveness of our proposed TIER method, we conduct extensive experiments on several mainstream AIGCIQA databases, including AGIQA-1K, AGIQA-3K, and AIGCIQA2023. The experimental results indicate that our proposed TIER method generally demonstrates superior performance compared to baseline in most cases.Comment: 12 pages, 8 figures. arXiv admin note: text overlap with arXiv:2312.0589

SWBT: Similarity Weighted Behavior Transformer with the Imperfect Demonstration for Robotic Manipulation

Imitation learning (IL), aiming to learn optimal control policies from expert demonstrations, has been an effective method for robot manipulation tasks. However, previous IL methods either only use expensive expert demonstrations and omit imperfect demonstrations or rely on interacting with the environment and learning from online experiences. In the context of robotic manipulation, we aim to conquer the above two challenges and propose a novel framework named Similarity Weighted Behavior Transformer (SWBT). SWBT effectively learn from both expert and imperfect demonstrations without interaction with environments. We reveal that the easy-to-get imperfect demonstrations, such as forward and inverse dynamics, significantly enhance the network by learning fruitful information. To the best of our knowledge, we are the first to attempt to integrate imperfect demonstrations into the offline imitation learning setting for robot manipulation tasks. Extensive experiments on the ManiSkill2 benchmark built on the high-fidelity Sapien simulator and real-world robotic manipulation tasks demonstrated that the proposed method can extract better features and improve the success rates for all tasks. Our code will be released upon acceptance of the paper.Comment: 8 pages, 5 figure

Visual Robotic Manipulation with Depth-Aware Pretraining

Recent work on visual representation learning has shown to be efficient for robotic manipulation tasks. However, most existing works pretrained the visual backbone solely on 2D images or egocentric videos, ignoring the fact that robots learn to act in 3D space, which is hard to learn from 2D observation. In this paper, we examine the effectiveness of pretraining for vision backbone with public-available large-scale 3D data to improve manipulation policy learning. Our method, namely Depth-aware Pretraining for Robotics (DPR), enables an RGB-only backbone to learn 3D scene representations from self-supervised contrastive learning, where depth information serves as auxiliary knowledge. No 3D information is necessary during manipulation policy learning and inference, making our model enjoy both efficiency and effectiveness in 3D space manipulation. Furthermore, we introduce a new way to inject robots' proprioception into the policy networks that makes the manipulation model robust and generalizable. We demonstrate in experiments that our proposed framework improves performance on unseen objects and visual environments for various robotics tasks on both simulated and real robots.Comment: submitted to ICRA202

Object-Centric Instruction Augmentation for Robotic Manipulation

Humans interpret scenes by recognizing both the identities and positions of objects in their observations. For a robot to perform tasks such as \enquote{pick and place}, understanding both what the objects are and where they are located is crucial. While the former has been extensively discussed in the literature that uses the large language model to enrich the text descriptions, the latter remains underexplored. In this work, we introduce the \textit{Object-Centric Instruction Augmentation (OCI)} framework to augment highly semantic and information-dense language instruction with position cues. We utilize a Multi-modal Large Language Model (MLLM) to weave knowledge of object locations into natural language instruction, thus aiding the policy network in mastering actions for versatile manipulation. Additionally, we present a feature reuse mechanism to integrate the vision-language features from off-the-shelf pre-trained MLLM into policy networks. Through a series of simulated and real-world robotic tasks, we demonstrate that robotic manipulator imitation policies trained with our enhanced instructions outperform those relying solely on traditional language instructions.Comment: accepted to ICRA202

Language-Conditioned Robotic Manipulation with Fast and Slow Thinking

The language-conditioned robotic manipulation aims to transfer natural language instructions into executable actions, from simple pick-and-place to tasks requiring intent recognition and visual reasoning. Inspired by the dual process theory in cognitive science, which suggests two parallel systems of fast and slow thinking in human decision-making, we introduce Robotics with Fast and Slow Thinking (RFST), a framework that mimics human cognitive architecture to classify tasks and makes decisions on two systems based on instruction types. Our RFST consists of two key components: 1) an instruction discriminator to determine which system should be activated based on the current user instruction, and 2) a slow-thinking system that is comprised of a fine-tuned vision language model aligned with the policy networks, which allows the robot to recognize user intention or perform reasoning tasks. To assess our methodology, we built a dataset featuring real-world trajectories, capturing actions ranging from spontaneous impulses to tasks requiring deliberate contemplation. Our results, both in simulation and real-world scenarios, confirm that our approach adeptly manages intricate tasks that demand intent recognition and reasoning. The project is available at https://jlm-z.github.io/RSFT/Comment: accepted to ICRA202

Expression divergence of expansin genes drive the heteroblasty in Ceratopteris chingii

AVAILABILITY OF DATA AND MATERIALS : The PacBio full-length sequencing dataset generated for this work is accessible through NCBI Sequence Read Archive (SRA) under accession number PRJNA924672 [74]. The Illumina RNA-seq dataset is accessible through NCBI SRA accession number PRJNA924581 [75].ADDITIONAL FILE 1. FIG. S1. Density distribution of raw reads and full-length non-chimeric reads obtained by PacBio Iso-seq. FIG. S2. RT-PCR validation of nine high-confident gene models. FIG. S3. The UpSet plot summarizes the presence of genes in five databases. FIG. S4. The pie diagrams showing the number of transcription factors in different families. FIG. S5. GO enrichment analysis of differentially expressed genes in the comparisons of sporophyll-S1 vs trophophyll-S2, sporophyll-S2 vs trophophyll-S1, and sporophyll-S2 vs trophophyll-S2. FIG. S6. Heatmap showing the differential and non-differential expression of the expansin genes in different pairwise comparisons as obtained from transcriptome analysis. FIG. S7. Phylogenetic tree of expansins in C. chingii and A. thaliana, built with Maximum likelihood. FIG. S8. Analysis of conserved domains of the CcEXP proteins. FIG. S9. Phylogenetic profiling of four groups of expansin genes in 19 species. FIG. S10. Bar plots showing the differentially expressed expansin genes in pteridophyte-specific groups. FIG. S11. GO enrichment analysis of genes that were identified to be significantly coexpressed with CcEXP genes. FIG. S12. Heatmap showing the member number of transcription factors in different families that are coexpressed with at least one CcEXP gene in the four groups. FIG. S13. Yeast two-hybrid assay showing how CcFL01489 interacts with three transcription factor (CcFL09745, CcFL03547, and CcFL06843). FIG. S14. Gene coexpression networks of CrEXP (A) and AtEXP (B) genes of the different groups. FIG. S15. GO enrichment analysis of genes that were identified to be significantly coexpressed with AtEXP (A) and CcEXP (B) genes in group IV.ADDITIONAL FILE 2. TABLE S1. EXP genes in C. chingii. TABLE S2. Topology of EXP gene tree of 19 species. TABLE S3. Correlation coefficient of FPKM and relative expression in CcEXP genes. TABLE S4. Summer of lncRNA targeted genes. TABLE S5. Summary of the RNA-Seq samples in this study. TABLE S6. Summary of the RT-PCR primer for validating the splicing events. TABLE S7. Summary of the qRT-PCR primer for expansin genes. TABLE S8. Summer of Yeast two-hybrid primer.BACKGROUND : Sterile-fertile heteroblasty is a common phenomenon observed in ferns, where the leaf shape of a fern sporophyll, responsible for sporangium production, differs from that of a regular trophophyll. However, due to the large size and complexity of most fern genomes, the molecular mechanisms that regulate the formation of these functionally different heteroblasty have remained elusive. To shed light on these mechanisms, we generated a full-length transcriptome of Ceratopteris chingii with PacBio Iso-Seq from five tissue samples. By integrating Illumina-based sequencing short reads, we identified the genes exhibiting the most significant differential expression between sporophylls and trophophylls. RESULTS : The long reads were assembled, resulting in a total of 24,024 gene models. The differential expressed genes between heteroblasty primarily involved reproduction and cell wall composition, with a particular focus on expansin genes. Reconstructing the phylogeny of expansin genes across 19 plant species, ranging from green algae to seed plants, we identified four ortholog groups for expansins. The observed high expression of expansin genes in the young sporophylls of C. chingii emphasizes their role in the development of heteroblastic leaves. Through gene coexpression analysis, we identified highly divergent expressions of expansin genes both within and between species. CONCLUSIONS : The specific regulatory interactions and accompanying expression patterns of expansin genes are associated with variations in leaf shapes between sporophylls and trophophylls.The Strategic Priority Research Program of the Chinese Academy of Sciences, the National Natural Science Foundation of China, the Fonds Wetenschappelijk Onderzoek-Vlaanderen (FWO) and UGent BOF.https://bmcbiol.biomedcentral.comam2024BiochemistryGeneticsMicrobiology and Plant PathologySDG-15:Life on lan

Soil diazotrophic abundance, diversity, and community assembly mechanisms significantly differ between glacier riparian wetlands and their adjacent alpine meadows

Global warming can trigger dramatic glacier area shrinkage and change the flux of glacial runoff, leading to the expansion and subsequent retreat of riparian wetlands. This elicits the interconversion of riparian wetlands and their adjacent ecosystems (e.g., alpine meadows), probably significantly impacting ecosystem nitrogen input by changing soil diazotrophic communities. However, the soil diazotrophic community differences between glacial riparian wetlands and their adjacent ecosystems remain largely unexplored. Here, soils were collected from riparian wetlands and their adjacent alpine meadows at six locations from glacier foreland to lake mouth along a typical Tibetan glacial river in the Namtso watershed. The abundance and diversity of soil diazotrophs were determined by real-time PCR and amplicon sequencing based on nifH gene. The soil diazotrophic community assembly mechanisms were analyzed via iCAMP, a recently developed null model-based method. The results showed that compared with the riparian wetlands, the abundance and diversity of the diazotrophs in the alpine meadow soils significantly decreased. The soil diazotrophic community profiles also significantly differed between the riparian wetlands and alpine meadows. For example, compared with the alpine meadows, the relative abundance of chemoheterotrophic and sulfate-respiration diazotrophs was significantly higher in the riparian wetland soils. In contrast, the diazotrophs related to ureolysis, photoautotrophy, and denitrification were significantly enriched in the alpine meadow soils. The iCAMP analysis showed that the assembly of soil diazotrophic community was mainly controlled by drift and dispersal limitation. Compared with the riparian wetlands, the assembly of the alpine meadow soil diazotrophic community was more affected by dispersal limitation and homogeneous selection. These findings suggest that the conversion of riparian wetlands and alpine meadows can significantly alter soil diazotrophic community and probably the ecosystem nitrogen input mechanisms, highlighting the enormous effects of climate change on alpine ecosystems

Sleep Status and the Associated Factors: A Large Cross-Sectional Study in Shaanxi Province, China

This study aimed at investigating the sleep status and its associated factors in Shaanxi province, China. We conducted a cross-sectional study among 11,399 subjects in Shaanxi Province, China. Data were collected via spot field questionnaire surveys. The contents included demographic characteristics, sleep status, lifestyles, disease history and other associated factors. Logistic regression analysis was used to estimate the effect of associated factors on sleep quality. A total of 11,036 subjects were included in the final analysis. In total, 12.8% of the participants had bad or very bad sleep. In the last month, 8.4% of the participants had difficulty in initiating sleep, 7.6% of the participants had difficulty in maintaining sleep, 8.8% of the participants suffered from awakening earlier and 10.3% of the participants had the problem of feeling sleepy during the day ≥3 times per week. Poorer sleep quality was associated with being female, being unmarried or without cohabiting with a boyfriend/girlfriend, being divorced or widowed, heart diseases, musculoskeletal diseases, concerns about their own health, drinking alcohol, taking hypnotics, and a longer daily screen time. Better sleep quality was associated with medium education level, high family monthly income, good self-reported health status, and having breakfast regularly. In conclusion, more than one in ten people did not sleep well and suffered from different sleep problems in Shaanxi, China. Sleep quality was associated with sex, marital status, educational level, family monthly income, heart disease, musculoskeletal diseases, degree of concerning about their own health, self-reported health status, drinking alcohol, having breakfast, taking hypnotics and daily screen time

Expression divergence of expansin genes drive the heteroblasty in Ceratopteris chingii

Abstract Background Sterile-fertile heteroblasty is a common phenomenon observed in ferns, where the leaf shape of a fern sporophyll, responsible for sporangium production, differs from that of a regular trophophyll. However, due to the large size and complexity of most fern genomes, the molecular mechanisms that regulate the formation of these functionally different heteroblasty have remained elusive. To shed light on these mechanisms, we generated a full-length transcriptome of Ceratopteris chingii with PacBio Iso-Seq from five tissue samples. By integrating Illumina-based sequencing short reads, we identified the genes exhibiting the most significant differential expression between sporophylls and trophophylls. Results The long reads were assembled, resulting in a total of 24,024 gene models. The differential expressed genes between heteroblasty primarily involved reproduction and cell wall composition, with a particular focus on expansin genes. Reconstructing the phylogeny of expansin genes across 19 plant species, ranging from green algae to seed plants, we identified four ortholog groups for expansins. The observed high expression of expansin genes in the young sporophylls of C. chingii emphasizes their role in the development of heteroblastic leaves. Through gene coexpression analysis, we identified highly divergent expressions of expansin genes both within and between species. Conclusions The specific regulatory interactions and accompanying expression patterns of expansin genes are associated with variations in leaf shapes between sporophylls and trophophylls. </jats:sec

Increased litter input significantly changed the total and active microbial communities in degraded grassland soils

Purpose Increasing organic matter input and phosphorus fertilization are employed extensively to restore degraded grasslands. Nevertheless, little is known about their effects on microbes, especially on active microbial populations. Therefore, this study is aimed at examining the short-term influences of litter and phosphorus addition on microbes in degraded grassland soils. Materials and methods A microcosm experiment was established using soils sampled from a heavily degraded Tibetan alpine meadow. The experiment used a two-way factorial design with grass litter and phosphorus addition as the main factors. Microbial abundance and rDNA transcriptional activity were assessed through quantitative PCR. Total and active microbial community profiles were measured using DNA- and RNA-based MiSeq sequencing, respectively. Results and discussion As shown in this study, litter addition significantly increased microbial rDNA transcriptional activity and fungal abundance, but it decreased microbial α-diversity. However, prokaryote abundance was unaffected by the litter addition. Total and active soil microbial community profiles and interaction patterns were also significantly altered by litter addition. The relative abundance of copiotrophic and oligotrophic microbial lineages significantly increased and decreased, respectively, in the soils with litter addition. Functional predictions suggested that litter addition might significantly increase the abundance of pathogens, as well as microbes related to nitrogen fixation, denitrification, and chitinolysis, while decreasing nitrifier abundance. In contrast, no significant effects of the phosphorus addition on soil microbes were observed. Conclusions These findings highlight the significant effects of increasing litter input on total and active soil microbial communities and suggest that microbial responses should be considered when restoring degraded grasslands by increasing organic matter input