Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and Retention

Scene Graph Generation (SGG) offers a structured representation critical in many computer vision applications. Traditional SGG approaches, however, are limited by a closed-set assumption, restricting their ability to recognize only predefined object and relation categories. To overcome this, we categorize SGG scenarios into four distinct settings based on the node and edge: Closed-set SGG, Open Vocabulary (object) Detection-based SGG (OvD-SGG), Open Vocabulary Relation-based SGG (OvR-SGG), and Open Vocabulary Detection + Relation-based SGG (OvD+R-SGG). While object-centric open vocabulary SGG has been studied recently, the more challenging problem of relation-involved open-vocabulary SGG remains relatively unexplored. To fill this gap, we propose a unified framework named OvSGTR towards fully open vocabulary SGG from a holistic view. The proposed framework is an end-toend transformer architecture, which learns a visual-concept alignment for both nodes and edges, enabling the model to recognize unseen categories. For the more challenging settings of relation-involved open vocabulary SGG, the proposed approach integrates relation-aware pre-training utilizing image-caption data and retains visual-concept alignment through knowledge distillation. Comprehensive experimental results on the Visual Genome benchmark demonstrate the effectiveness and superiority of the proposed framework.Comment: 10 pages, 4 figures, 6 table

Fast-ParC: Position Aware Global Kernel for ConvNets and ViTs

Transformer models have made tremendous progress in various fields in recent years. In the field of computer vision, vision transformers (ViTs) also become strong alternatives to convolutional neural networks (ConvNets), yet they have not been able to replace ConvNets since both have their own merits. For instance, ViTs are good at extracting global features with attention mechanisms while ConvNets are more efficient in modeling local relationships due to their strong inductive bias. A natural idea that arises is to combine the strengths of both ConvNets and ViTs to design new structures. In this paper, we propose a new basic neural network operator named position-aware circular convolution (ParC) and its accelerated version Fast-ParC. The ParC operator can capture global features by using a global kernel and circular convolution while keeping location sensitiveness by employing position embeddings. Our Fast-ParC further reduces the O(n2) time complexity of ParC to O(n log n) using Fast Fourier Transform. This acceleration makes it possible to use global convolution in the early stages of models with large feature maps, yet still maintains the overall computational cost comparable with using 3x3 or 7x7 kernels. The proposed operation can be used in a plug-and-play manner to 1) convert ViTs to pure-ConvNet architecture to enjoy wider hardware support and achieve higher inference speed; 2) replacing traditional convolutions in the deep stage of ConvNets to improve accuracy by enlarging the effective receptive field. Experiment results show that our ParC op can effectively enlarge the receptive field of traditional ConvNets, and adopting the proposed op benefits both ViTs and ConvNet models on all three popular vision tasks, image classification, objectComment: 19 pages, 8 figures, 11 tables. A preliminary version of this paper has been published in ECCV 2022 and it can be find in arXiv:2203.0395

Screening high potassium efficiency potato genotypes and physiological responses at different potassium levels

Potato (Solanum tuberosum L.) growth and production is highly dependent on potassium (K) levels in the soil. Southwest China is the largest potato production region but it has low availability of soil potassium. To assess the genetic variation in K use efficiency, 20 potato genotypes were collected to compare the yield and K content in a pot experiment. Moreover, ‘Huayu-5’ and ‘Zhongshu-19’ were cultivated in five K applications to investigate the K distribution and sucrose in different organs. The results indicated that there were highly significant effects of K, genotype and K×G interactions on tuber yield, plant and tuber K content, plant K uptake efficiency and K harvest index. Cluster analysis classified 20 potato genotypes into four types: DH (high efficiency at low and high K application), LKH (high efficiency at low K application), HKH (high efficiency at high K application) and DL (low efficiency at low and high K application). The potassium distribution percentage in the tubers of the potassium-efficient genotype was higher than that of the potassium-inefficient genotype under low potassium application. The sucrose content in the tuber gently declined as the application of K rose in both cultivars, and that in the tuber of ‘Huayu-5’ was higher than that in ‘Zhongshu-19’. ‘Huayu-5’ reached the highest yield when the potassium application was 159.45 kg ha-1, and ‘Zhongshu-19’ reached the highest yield when the potassium application was 281.4 kg ha-1. This study indicated that genetic variation for K utilization efficiency existed among 20 genotypes, and yield in low K application and relative yield were suitable criteria for screening K utilization efficiency genotypes

MLVA genotyping of Chinese human Brucella melitensis biovar 1, 2 and 3 isolates

<p>Abstract</p> <p>Background</p> <p>Since 1950, <it>Brucella melitensis </it>has been the predominant strain associated with human brucellosis in China. In this study we investigated the genotypic characteristics of <it>B. melitensis </it>isolates from China using a multiple-locus variable-number tandem-repeat analysis (MLVA) and evaluated the utility of MLVA with regards to epidemiological trace-back investigation.</p> <p>Results</p> <p>A total of 105 <it>B. melitensis </it>strains isolated from throughout China were divided into 69 MLVA types using MLVA-16. Nei's genetic diversity indices for the various loci ranged between 0.00 - 0.84. 12 out 16 loci were the low diversity with values < 0.2 and the most discriminatory markers were bruce16 and bruce30 with a diversity index of > 0.75 and containing 8 and 7 alleles, respectively. Many isolates were single-locus or double-locus variants of closely related <it>B. melitensis </it>isolates from different regions, including the north and south of China. Using panel 1, the majority of strains (84/105) were genotype 42 clustering to the 'East Mediterranean' <it>B. melitensis </it>group. Chinese <it>B. melitensis </it>are classified in limited number of closely related genotypes showing variation mainly at the panel 2B loci.</p> <p>Conclusion</p> <p>The MLVA-16 assay can be useful to reveal the predominant genotypes and strain relatedness in endemic or non-endemic regions of brucellosis. However it is not suitable for biovar differentiation of <it>B. melitensis</it>. Genotype 42 is widely distributed throughout China during a long time. Bruce 16 and bruce 30 in panel 2B markers are most useful for typing Chinese isolates.</p

Genomic analyses provide insights into peach local adaptation and responses to climate change

The environment has constantly shaped plant genomes, but the genetic bases underlying how plants adapt to environmental influences remain largely unknown. We constructed a high-density genomic variation map of 263 geographically representative peach landraces and wild relatives. A combination of whole-genome selection scans and genome-wide environmental association studies (GWEAS) was performed to reveal the genomic bases of peach adaptation to diverse climates. A total of 2092 selective sweeps that underlie local adaptation to both mild and extreme climates were identified, including 339 sweeps conferring genomic pattern of adaptation to high altitudes. Using genome-wide environmental association studies (GWEAS), a total of 2755 genomic loci strongly associated with 51 specific environmental variables were detected. The molecular mechanism underlying adaptive evolution of high drought, strong UVB, cold hardiness, sugar content, flesh color, and bloom date were revealed. Finally, based on 30 yr of observation, a candidate gene associated with bloom date advance, representing peach responses to global warming, was identified. Collectively, our study provides insights into molecular bases of how environments have shaped peach genomes by natural selection and adds candidate genes for future studies on evolutionary genetics, adaptation to climate changes, and breeding.info:eu-repo/semantics/publishedVersio

Chromosome-level genome assemblies of four wild peach species provide insights into genome evolution and genetic basis of stress resistance

[Background] Peach (Prunus persica) is an economically important stone fruit crop in Rosaceae and widely cultivated in temperate and subtropical regions, emerging as an excellent material to study the interaction between plant and environment. During its genus, there are four wild species of peach, all living in harsh environments. For example, one of the wild species, P. mira, originates from the Qinghai-Tibet Plateau (QTP) and exhibits strong cold/ultraviolet ray environmental adaptations. Although remarkable progresses in the gene discovery of fruit quality-related traits in peach using previous assembled genome were obtained, genomic basis of the response of these wild species to different geographical environments remains unclear.[Results] To uncover key genes regulating adaptability in different species and analyze the role of genetic variations in resistance formation, we performed de novo genome assembling of four wild relatives of peach (P. persica), P. mira, P. davidiana, P. kansuensis, and P. ferganensis and resequenced 175 peach varieties. The phylogenetic tree showed that the divergence time of P. mira and other wild relatives of peach was 11.5 million years ago, which was consistent with the drastic crustal movement of QTP. Abundant genetic variations were identified in four wild species when compared to P. persica, and the results showed that plant-pathogen interaction pathways were enriched in genes containing small insertions and deletions and copy number variations in all four wild relatives of peach. Then, the data were used to identify new genes and variations regulating resistance. For example, presence/absence variations which result from a hybridization event that occurred between P. mira and P. dulcis enhanced the resistance of their putative hybrid, P. davidiana. Using bulked segregant analysis, we located the nematode resistance locus of P. kansuensis in chromosome 2. Within the mapping region, a deletion in the promoter of one NBS-LRR gene was found to involve the resistance by regulating gene expression. Furthermore, combined with RNA-seq and selective sweeps analysis, we proposed that a deletion in the promoter of one CBF gene was essential for high-altitude adaptation of P. mira through increasing its resistance to low temperature.[Conclusions] In general, the reference genomes assembled in the study facilitate our understanding of resistance mechanism of perennial fruit crops, and provide valuable resources for future breeding and improvement.This work was supported by the National Key Research and Development Program (2019YFD1000203), the Agricultural Science and Technology Innovation Program (CAAS-ASTIP-2019-ZFRI-01), and National Horticulture Germplasm Resources Center.Peer reviewe

CdSe Quantum Dot (QD)-Induced Morphological and Functional Impairments to Liver in Mice

Quantum dots (QDs), as unique nanoparticle probes, have been used in in vivo fluorescence imaging such as cancers. Due to the novel characteristics in fluorescence, QDs represent a family of promising substances to be used in experimental and clinical imaging. Thus far, the toxicity and harmful health effects from exposure (including environmental exposure) to QDs are not recognized, but are largely concerned by the public. To assess the biological effects of QDs, we established a mouse model of acute and chronic exposure to QDs. Results from the present study suggested that QD particles could readily spread into various organs, and liver was the major organ for QD accumulation in mice from both the acute and chronic exposure. QDs caused significant impairments to livers from mice with both acute and chronic QD exposure as reflected by morphological alternation to the hepatic lobules and increased oxidative stress. Moreover, QDs remarkably induced the production of intracellular reactive oxygen species (ROS) along with cytotoxicity, as characterized by a significant increase of the malondialdehyde (MDA) level within hepatocytes. However, the increase of the MDA level in response to QD treatment could be partially blunted by the pre-treatment of cells with beta-mercaptoethanol (β-ME). These data suggested ROS played a crucial role in causing oxidative stress-associated cellular damage from QD exposure; nevertheless other unidentified mediators might also be involved in QD-mediated cellular impairments. Importantly, we demonstrated that the hepatoxicity caused by QDs in vivo and in vitro was much greater than that induced by cadmium ions at a similar or even a higher dose. Taken together, the mechanism underlying QD-mediated biological influences might derive from the toxicity of QD particles themselves, and from free cadmium ions liberated from QDs as well