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Body axis establishment is one of the earliest patterning events in plant embryogenesis. Asymmetric zygote division is critical for apical–basal axis formation in Arabidopsis (Arabidopsis thaliana). However, how the orientation of the cell division plane is regulated and its relation to apical–basal axis establishment and proper position of embryos in grasses remain poorly understood. By characterizing mutants of 3 rice (Oryza sativa) WUSCHEL HOMEOBOX9 (WOX9) genes, whose paralogs in Arabidopsis play essential roles in zygotic asymmetric cell division and cell fate determination, we found 2 kinds of independent embryonic defects: topsy-turvy embryos, in which apical–basal axis twists from being parallel to the longitudinal axis of the seed to being perpendicular; and organ-less embryos. In contrast to their Arabidopsis orthologs, OsWOX9s displayed dynamic distribution during embryo development. Both DWT1/OsWOX9A and DWL2/WOX9C play major roles in the apical–basal axis formation and initiation of stem cells. In addition, DWT1 has a distinct function in regulating the first few embryonic cell divisions to ensure the correct orientation of the embryo in the ovary. In summary, DWT1 acts in 2 steps during rice embryo pattern formation: the initial zygotic division, and with DWL2 to establish the main body axes and stem cell fate 2 to 3 d after pollination. A rice WOX transcription factor regulates the first few cell divisions to ensure correct embryo direction in the ovule and coregulates the establishment of the body axis and stem cell niche. [ABSTRACT FROM AUTHOR]

Sentiment word embedding has been extensively studied and used in sentiment analysis tasks. However, most existing models have failed to differentiate high‐frequency and low‐frequency words. Accordingly, the sentiment information of low‐frequency words is insufficiently captured, thus resulting in inaccurate sentiment word embedding and degradation of overall performance of sentiment analysis. A Bayesian estimation‐based sentiment word embedding (BESWE) model, which aims to precisely extract the sentiment information of low‐frequency words, has been proposed. In the model, a Bayesian estimator is constructed based on the co‐occurrence probabilities and sentiment probabilities of words, and a novel loss function is defined for sentiment word embedding learning. The experimental results based on the sentiment lexicons and Movie Review dataset show that BESWE outperforms many state‐of‐the‐art methods, for example, C&W, CBOW, GloVe, SE‐HyRank and DLJT1, in sentiment analysis tasks, which demonstrate that Bayesian estimation can effectively capture the sentiment information of low‐frequency words and integrate the sentiment information into the word embedding through the loss function. In addition, replacing the embedding of low‐frequency words in the state‐of‐the‐art methods with BESWE can significantly improve the performance of those methods in sentiment analysis tasks. [ABSTRACT FROM AUTHOR]

In this work, a new type of metamaterial absorber is proposed in the infrared region. This structure consists of metal-dielectric-metal. But the difference is that a square groove in the dielectric has been dug, and replaced by a metal. The simulated results show that this structure can achieve a broadband absorption. And the absorption bandwidth can be realized from 60.5 to 115.5 THz when the absorption efficiency is larger than 90%. And this structure is polarization-insensitive for incident electromagnetic waves. In addition, the structure can also achieve better absorption effect for a large incident angle, especially for TM polarized wave. What is more, a remarkably enhanced bandwidth can be realized by using a metal to fill the square groove which is dug in the dielectric. To further explain the mechanism of high absorption, the distribution of the electromagnetic field and power loss density at the resonance frequencies are analysed. And these novel properties make the absorbers have many applications including sensor, cloaking, etc. [ABSTRACT FROM PUBLISHER]