Abstract: An application of fengycin family lipopeptides in pest control is provided, and Fengycin family lipopeptides are used for pest control, with especially strong killing effects on Homoptera and Coleoptera pests. A method is provided for treating seeds with fengycin to protect seeds and plant organs formed later from pests, so as to protect seeds from pests by coating the fengycin family lipopeptides on the surface of seeds.

Abstract: Described herein is a machine learning framework for facilitating engagements. In accordance with one aspect of the framework, a machine learning model is trained based on the training data. A recommendation associated with an opportunity record may then be generated using the trained machine learning model. Results of one or more actions performed in response to the recommendation may be collected and fed back to the machine learning model to be used as the training data.

Abstract: A formulation containing an A-decarbonized-5a-androstane compound for increasing white blood cells and use thereof. The A-decarbonized-5?-androstane compound can prevent, alleviate and improve the reduction in the number of white blood cells caused by chemotherapy or radiation therapy, and can be used for preparing a preparation or a composition, the preparation or the composition being used for (a) increasing the number of white blood cells or (b) preventing or treating leucopenia.

Abstract: Methods, systems, and computer-readable storage media for receiving input data including a set of sentences, each sentence including computer-readable text as a sequence of tokens, providing a memory network with coupled attentions (MNCA), the coupled attentions including an aspect attention and an opinion attention that are coupled by tensor operators for each sentence in the set of sentences, processing the input data through the MNCA to identify a set of aspect terms, and a set of opinion terms, and simultaneously assign a category to each aspect term and each opinion term from a set of categories, and outputting the set of aspect terms with respective categories, and the set of opinion terms with respective categories.

Abstract: Described herein is a machine learning framework for facilitating engagements. In accordance with one aspect of the framework, a machine learning model is trained based on the training data. A recommendation associated with an opportunity record may then be generated using the trained machine learning model. Results of one or more actions performed in response to the recommendation may be collected and fed back to the machine learning model to be used as the training data.

Abstract: Described herein is a framework to perform aspect-based sentiment analysis. In accordance with one aspect of the framework, initial word embeddings are generated from a training dataset. A predictive model is trained using the initial word embeddings. The trained predictive model may then be used to recognize one or more sequences of tokens in a current dataset.