Most machine learning and deep learning algorithms can only use low-dimensional data as input, but the data that must be processed in practical applications is diverse and irregular. There are two main problems with big dynamic data. (1) The size of the embedding table grows linearly with the vocabulary size, resulting in massive memory consumption. (2) For different newly added vocabularies. To solve these two problems, this paper proposes a novel embedding algorithm that can learn attribute associations with entities based on deep and hash algorithms. Taking movie data as an example, the encoding method and the specific flow of the algorithm are presented in detail, and the effect of dynamic reuse of data models is realized. Compared with the four existing embedding algorithms which can fuse entity attribute information, the deep hash embedding algorithm proposed in this paper has obvious optimization of time and space complexity.

Halloysite nanotubes (HNTs) are natural occurring mineral clay nanotubes that have excellent application potential in different fields. However, HNTs are heterogeneous in size, surface charge and formation of surfacial hydrogen bond, which lead to weak affinity and aggregation at a certain extent. It is very important to modify the HNTs’ surface to expand its applications. In this review, the structural characteristics, performance and the related applications of surface-modified HNTs are reviewed. We focus on the surface-modified variation of HNTs, the effects of surface modification on the materials and related applications in various regions. In addition, future prospects and the meaning of surface modification were also discussed in HNTs studies. This review provides a reference for the application of HNTs modifications in the field of new nanomaterials.

Herbicide-resistant weed populations in numerous cropping systems pose a significant threat to global food security by reducing crop yields and increasing production costs. Multiple herbicide-resistant (MHR) Avena fatua L. (wild oat) plants with non-target site resistance (NTSR) mechanisms can express resistance to herbicides without previous exposure and are thus particularly troubling. Although precise molecular mechanisms for resistance to five different mechanisms of action are not clear, numerous transcription factors and stress-related proteins are preferentially subjected to constitutive post-translational modifications (PTMs) in MHR plants. Transient assays to quickly assess if changes to specific genes can change the MHR response will facilitate the development of new strategies to manage MHR weeds. Our study showed that the Barley Stripe Mosaic Virus (BSMV) mediated system can be an option for A sa-tiva (cultivated oat) and A. fatua (wild oat) functional analysis. The inoculation efficiency of this system ranged from 48% to 100%. Its efficacy was demonstrated by successfully knocking down phy-toene desaturase (PDS) expression and overexpressing green fluo-rescent protein (GFP), suggesting its potential for oat functional genomics.

Two new harziane diterpenes (1-2), five undescribed cyclonerane sesquiterpenes (3-7) and three known compounds, 11-cycloneren-3,7,10-triol (8), harziandione (9), and dehydroacetic acid (10) were isolated from Trichoderma hamatum b-3. Their structures were elucidated via comprehensive inspection of spectral evidences in HRESIMS, 1D and 2D NMR, the absolute configuration of 1-8 was confirmed by NMR, ECD calculation as well as Mosher's method. In vitro fungicidal activity showed that some compounds showed great inhibitory activity against pathogenic fungi including Fusarium graminearum, Sclerotinia sclerotiorum, Botrytis cinerea, and Rhizoctonia solani, among which compound 10 showed 100% inhibition of S. sclerotiorum and B. cinerea. In vivo activity test showed that compound 10 was 65.8% effective against B. cinerea and has the potential to be developed as a biocontrol pesticide.