Admissibility of linear predictor in the extended growth curve model

In the present paper, we first give the definition of the extended growth curve model, then according to the definition of admissible linear predictor and some matrix properties, obtain the necessary and sufficient conditions for a linear predictor to be admissible in the classes of homogenous and inhomogeneous linear predictors, respectively

APETALA2 antagonizes the transcriptional activity of AGAMOUS in regulating floral stem cells in Arabidopsis thaliana.

APETALA2 (AP2) is best known for its function in the outer two floral whorls, where it specifies the identities of sepals and petals by restricting the expression of AGAMOUS (AG) to the inner two whorls in Arabidopsis thaliana. Here, we describe a role of AP2 in promoting the maintenance of floral stem cell fate, not by repressing AG transcription, but by antagonizing AG activity in the center of the flower. We performed a genetic screen with ag-10 plants, which exhibit a weak floral determinacy defect, and isolated a mutant with a strong floral determinacy defect. This mutant was found to harbor another mutation in AG and was named ag-11. We performed a genetic screen in the ag-11 background to isolate mutations that suppress the floral determinacy defect. Two suppressor mutants were found to harbor mutations in AP2. While AG is known to shut down the expression of the stem cell maintenance gene WUSCHEL (WUS) to terminate floral stem cell fate, AP2 promotes the expression of WUS. AP2 does not repress the transcription of AG in the inner two whorls, but instead counteracts AG activity

Progress and Development Trend of Space Intelligent Robot Technology

Since space intelligent robots are not restricted by physiological conditions, it is an attractive choice for the development of automation technology to use them for space exploration and utilization. It is currently the key development direction of the major space powers over the world. This paper first investigates the robotic manipulators and humanoid robot systems for space station applications and reviews theories and methods for robots to achieve large-range stable motion and intelligent dexterous manipulation. Then, the intelligent robot systems for on-orbit satellite maintenance are reviewed, and the related technologies of multirobot collaboration are analyzed. Finally, we investigate the intelligent robot systems for on-orbit assembly of large-scale spatial structures and summarize the technologies of modular assembly and on-orbit manufacture. Overall, this paper reviews the technological progress and development trends of space robots, which provides a good reference for further technical research in this field

Research on interface slippage of fiber reinforced composite ceramics

Based on the microscopic characteristics of fiber reinforced composite ceramics, the slippage stress at the interface of composite ceramics under external loading is analyzed. The relation between the applied strain of the triangular symmetrical eutectic and the load of composite ceramics is confirmed. And the maximum shear stress that the triangular symmetrical eutectic can endure is computed. The yield shear stress was calculated by the hardness and fracture toughness of composite ceramics. When the maximum shear stress which the triangular symmetrical eutectic can bear is equal to the yield shear stress, the slipping stress of micro-mechanical interface in composite ceramics is obtained. The results showed that fiber inclusions in the eutectic having smaller dimension and larger volume content would provide larger partial plastic deformation of composite ceramics

ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance

Most of ranking models are trained only with displayed items (most are hot items), but they are utilized to retrieve items in the entire space which consists of both displayed and non-displayed items (most are long-tail items). Due to the sample selection bias, the long-tail items lack sufficient records to learn good feature representations, i.e. data sparsity and cold start problems. The resultant distribution discrepancy between displayed and non-displayed items would cause poor long-tail performance. To this end, we propose an entire space adaptation model (ESAM) to address this problem from the perspective of domain adaptation (DA). ESAM regards displayed and non-displayed items as source and target domains respectively. Specifically, we design the attribute correlation alignment that considers the correlation between high-level attributes of the item to achieve distribution alignment. Furthermore, we introduce two effective regularization strategies, i.e. \textit{center-wise clustering} and \textit{self-training} to improve DA process. Without requiring any auxiliary information and auxiliary domains, ESAM transfers the knowledge from displayed items to non-displayed items for alleviating the distribution inconsistency. Experiments on two public datasets and a large-scale industrial dataset collected from Taobao demonstrate that ESAM achieves state-of-the-art performance, especially in the long-tail space. Besides, we deploy ESAM to the Taobao search engine, leading to significant improvement on online performance. The code is available at \url{https://github.com/A-bone1/ESAM.git}Comment: Accept by SIGIR-202