Improving biomedical Named Entity Recognition with additional external contexts.

OBJECTIVE: Biomedical Named Entity Recognition (bio NER) is the task of recognizing named entities in biomedical texts. This paper introduces a new model that addresses bio NER by considering additional external contexts. Different from prior methods that mainly use original input sequences for sequence labeling, the model takes into account additional contexts to enhance the representation of entities in the original sequences, since additional contexts can provide enhanced information for the concept explanation of biomedical entities. METHODS: To exploit an additional context, given an original input sequence, the model first retrieves the relevant sentences from PubMed and then ranks the retrieved sentences to form the contexts. It next combines the context with the original input sequence to form a new enhanced sequence. The original and new enhanced sequences are fed into PubMedBERT for learning feature representation. To obtain more fine-grained features, the model stacks a BiLSTM layer on top of PubMedBERT. The final named entity label prediction is done by using a CRF layer. The model is jointly trained in an end-to-end manner to take advantage of the additional context for NER of the original sequence. RESULTS: Experimental results on six biomedical datasets show that the proposed model achieves promising performance compared to strong baselines and confirms the contribution of additional contexts for bio NER. CONCLUSION: The promising results confirm three important points. First, the additional context from PubMed helps to improve the quality of the recognition of biomedical entities. Second, PubMed is more appropriate than the Google search engine for providing relevant information of bio NER. Finally, more relevant sentences from the context are more beneficial than irrelevant ones to provide enhanced information for the original input sequences. The model is flexible to integrate any additional context types for the NER task.

Fate of Residual Pesticides in Fruit and Vegetable Waste (FVW) Processing.

Plants need to be protected against pests and diseases, so as to assure an adequate production, and therefore to contribute to food security. However, some of the used pesticides are harmful compounds, and thus the right balance between the need to increase food production with the need to ensure the safety of people, food and the environment must be struck. In particular, when dealing with fruit and vegetable wastes, their content in agrochemicals should be monitored, especially in peel and skins, and eventually minimized before or during further processing to separate or concentrate bioactive compounds from it. The general objective of this review is to investigate initial levels of pesticide residues and their potential reduction through further processing for some of the most contaminated fruit and vegetable wastes. Focus will be placed on extraction and drying processes being amid the main processing steps used in the recuperation of bioactive compounds from fruit and vegetable wastes.