A novel integrated method of detection-grasping for specific object based on the box coordinate matching

To better care for the elderly and disabled, it is essential for service robots to have an effective fusion method of object detection and grasp estimation. However, limited research has been observed on the combination of object detection and grasp estimation. To overcome this technical difficulty, a novel integrated method of detection-grasping for specific object based on the box coordinate matching is proposed in this paper. Firstly, the SOLOv2 instance segmentation model is improved by adding channel attention module (CAM) and spatial attention module (SAM). Then, the atrous spatial pyramid pooling (ASPP) and CAM are added to the generative residual convolutional neural network (GR-CNN) model to optimize grasp estimation. Furthermore, a detection-grasping integrated algorithm based on box coordinate matching (DG-BCM) is proposed to obtain the fusion model of object detection and grasp estimation. For verification, experiments on object detection and grasp estimation are conducted separately to verify the superiority of improved models. Additionally, grasping tasks for several specific objects are implemented on a simulation platform, demonstrating the feasibility and effectiveness of DG-BCM algorithm proposed in this paper

Recent research progress on imbibition system of nanoparticle-surfactant dispersions

Nanotechnology has been increasingly applied in the petroleum industry in recent years. In particular, dispersions consisting of nanoparticles and surfactants have been widely investigated. The imbibition system compounded by nanoparticle and surfactant was found to display a high efficiency in enhancing oil recovery. This paper briefly reviews the factors influencing imbibition efficiency. At the same time, the application and mechanism of the imbibition system of nanoparticle-surfactant dispersion in the field of enhanced oil recovery are introduced. Additionally, the limitations and challenges that the imbibition system of nanoparticle-surfactant dispersions may face in enhanced oil recovery applications are put forward. The current work reveals that the imbibition system with nanoparticle-surfactant dispersion is an ideal candidate for enhanced oil recovery in tight and low-permeability reservoirs.Document Type: Invited reviewCited as: Shao, W., Yang, J., Wang, H., Chang, J., Wu, H., Hou, J. Recent research progress on imbibition system of nanoparticle-surfactant dispersions. Capillarity, 2023, 8(2): 34-44. https://doi.org/10.46690/capi.2023.08.0

Network Inference Using the Hub Model and Variants

Statistical network analysis primarily focuses on inferring the parameters of an observed network. In many applications, especially in the social sciences, the observed data is the groups formed by individual subjects. In these applications, the network is itself a parameter of a statistical model. Zhao and Weko (2019) propose a model-based approach, called the hub model, to infer implicit networks from grouping behavior. The hub model assumes that each member of the group is brought together by a member of the group called the hub. The set of members which can serve as a hub is called the hub set. The hub model belongs to the family of Bernoulli mixture models. Identifiability of Bernoulli mixture model parameters is a notoriously difficult problem. This paper proves identifiability of the hub model parameters and estimation consistency under mild conditions. Furthermore, this paper generalizes the hub model by introducing a model component that allows hubless groups in which individual nodes spontaneously appear independent of any other individual. We refer to this additional component as the null component. The new model bridges the gap between the hub model and the degenerate case of the mixture model -- the Bernoulli product. Identifiability and consistency are also proved for the new model. In addition, a penalized likelihood approach is proposed to estimate the hub set when it is unknown.Comment: arXiv admin note: substantial text overlap with arXiv:2004.0970

Identification of candidate gene for the defective kernel phenotype using bulked segregant RNA and exome capture sequencing methods in wheat

Wheat is a significant source of protein and starch worldwide. The defective kernel (Dek) mutant AK-3537, displaying a large hollow area in the endosperm and shrunken grain, was obtained through ethyl methane sulfonate (EMS) treatment of the wheat cultivar Aikang 58 (AK58). The mode of inheritance of the AK-3537 grain Dek phenotype was determined to be recessive with a specific statistical significance level. We used bulked segregant RNA-seq (BSR-seq), BSA-based exome capture sequencing (BSE-seq), and the ΔSNP-index algorithm to identify candidate regions for the grain Dek phenotype. Two major candidate regions, DCR1 (Dek candidate region 1) and DCR2, were identified on chromosome 7A between 279.98 and 287.93 Mb and 565.34 and 568.59 Mb, respectively. Based on transcriptome analysis and previous reports, we designed KASP genotyping assays based on SNP variations in the candidate regions and speculated that the candidate gene is TraesCS7A03G0625900 (HMGS-7A), which encodes a 3-hydroxy-3-methylglutaryl-CoA synthase. One SNP variation located at position 1,049 in the coding sequence (G>A) causes an amino acid change from Gly to Asp. The research suggests that functional changes in HMGS-7A may affect the expression of key enzyme genes involved in wheat starch syntheses, such as GBSSII and SSIIIa

Plant Defense Responses Induced by Two Herbivores and Consequences for Whitefly Bemisia tabaci

Diverse herbivores are known to induce various plant defenses. The plant defenses may detrimentally affect the performance and preference to subsequent herbivores on the same plant, such as affecting another insect’s feeding, settling, growth or oviposition. Here, we report two herbivores (mealybug Phenacoccus solenopsis and carmine spider mite Tetranychus cinnabarinus) which were used to pre-infest the cucumber to explore the impact on the plants and the later-colonizing species, whitefly Bemisia tabaci. The results showed that the whiteflies tended to select the treatments pre-infested by the mites, rather than the uninfected treatments. However, the result of treatments pre-infested by the mealybugs was opposite. Total number of eggs laid of whiteflies was related to their feeding preference. The results also showed that T. cinnabarinus were more likely to activate plant jasmonic acid (JA) regulated genes, while mealybugs were more likely to activate key genes regulated by salicylic acid (SA). The different plant defense activities on cucumbers may be one of the essential factors that affects the preference of B. tabaci. Moreover, the digestive enzymes and protective enzymes of the whitefly might play a substantial regulatory role in its settling and oviposition ability

Uncovering the dispersion history, adaptive evolution and selection of wheat in China

Wheat was introduced to China approximately 4500 years ago, where it adapted over a span of time to various environments in agro-ecological growing zones. We investigated 717 Chinese and 14 Iranian/Turkish geographically diverse, locally adapted wheat landraces with 27,933 DArTseq (for 717 landraces) and 312,831 Wheat660K (for a subset of 285 landraces) markers. This study highlights the adaptive evolutionary history of wheat cultivation in China. Environmental stresses and independent selection efforts have resulted in considerable genome-wide divergence at the population level in Chinese wheat landraces. In total, 148 regions of the wheat genome show signs of selection in at least one geographic area. Our data show adaptive events across geographic areas, from the xeric northwest to the mesic south, along and among homoeologous chromosomes, with fewer variations in the D genome than in the A and B genomes. Multiple variations in interdependent functional genes, such as regulatory and metabolic genes controlling germination and flowering time were characterized, showing clear allelic frequency changes corresponding to the dispersion of wheat in China. Population structure and selection data reveal that Chinese wheat spread from the northwestern Caspian Sea region to south China, adapting during its agricultural trajectory to increasingly mesic and warm climatic areas

An ancestral NB-LRR with duplicated 3'UTRs confers stripe rust resistance in wheat and barley.

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a global threat to wheat production. Aegilops tauschii, one of the wheat progenitors, carries the YrAS2388 locus for resistance to Pst on chromosome 4DS. We reveal that YrAS2388 encodes a typical nucleotide oligomerization domain-like receptor (NLR). The Pst-resistant allele YrAS2388R has duplicated 3' untranslated regions and is characterized by alternative splicing in the nucleotide-binding domain. Mutation of the YrAS2388R allele disrupts its resistance to Pst in synthetic hexaploid wheat; transgenic plants with YrAS2388R show resistance to eleven Pst races in common wheat and one race of P. striiformis f. sp. hordei in barley. The YrAS2388R allele occurs only in Ae. tauschii and the Ae. tauschii-derived synthetic wheat; it is absent in 100% (n = 461) of common wheat lines tested. The cloning of YrAS2388R will facilitate breeding for stripe rust resistance in wheat and other Triticeae species

SNP-revealed genetic diversity in wild emmer wheat correlates with ecological factors

Abstract Background Patterns of genetic diversity between and within natural plant populations and their driving forces are of great interest in evolutionary biology. However, few studies have been performed on the genetic structure and population divergence in wild emmer wheat using a large number of EST-related single nucleotide polymorphism (SNP) markers. Results In the present study, twenty-five natural wild emmer wheat populations representing a wide range of ecological conditions in Israel and Turkey were used. Genetic diversity and genetic structure were investigated using over 1,000 SNP markers. A moderate level of genetic diversity was detected due to the biallelic property of SNP markers. Clustering based on Bayesian model showed that grouping pattern is related to the geographical distribution of the wild emmer wheat. However, genetic differentiation between populations was not necessarily dependent on the geographical distances. A total of 33 outlier loci under positive selection were identified using a F ST -outlier method. Significant correlations between loci and ecogeographical factors were observed. Conclusions Natural selection appears to play a major role in generating adaptive structures in wild emmer wheat. SNP markers are appropriate for detecting selectively-channeled adaptive genetic diversity in natural populations of wild emmer wheat. This adaptive genetic diversity is significantly associated with ecological factors