Climate change projections show shrinking deep-water ecosystems with implications for biodiversity and aquaculture in the Northwest Pacific.

The increased availability of environmental data with depth deriving from remote-sensing-based datasets permits more comprehensive modelling of the distribution of marine ecosystems in space and time. This research tests the potential of such objective modelling of marine ecosystems in four dimensions, spatial and temporal, to provide projections of how climate change may affect biodiversity, including aquaculture. This approach could be replicated for any regional seas. The Bohai Sea, Yellow Sea, and East China Sea (BYECS) are marginal seas in the Northwest Pacific bounded by China, Korea, and Japan. Despite providing important ecological and economic services, their ecological conditions and ecosystems distribution have not yet been systematically mapped. This analysis used 13 marine environmental variables, measured on a three-dimensional and monthly basis during 1993-2019, to classify and map the BYECS region by k-means clustering using cosine similarity as distance function. There were 13 distinct areas identified that fit the definition of "ecosystems" that is, enduring regions demarcated by environmental characteristics. Of these 13 ecosystems, the Yellow Sea Cold Water (YSCW) Ecosystem is significant in relation to seasonal species composition and the newly developing deep-sea salmon caging aquaculture in the region. Projections of the potential size of this water mass under various climate-change scenarios based on analysis using the Non-Parametric Probabilistic Ecological Niche (NPPEN) model show that its volume may decrease 31 %-66 % in the future. Such a decrease would have impacts on the seasonal species' abundances in the BYECS marginal sea region and threaten the deep-sea cold-water salmon farming.

Health Informatics Scientists' Perception About Big Data Technology.

The aim of this paper is to present the perceptions of the Health Informatics Scientists about the Big Data Technology in Healthcare. An empirical study was conducted among 46 scientists to assess their knowledge about the Big Data Technology and their perceptions about using this technology in healthcare. Based on the study findings, 86.7% of the scientists had knowledge of Big data Technology. Furthermore, 59.1% of the scientists believed that Big Data Technology refers to structured data. Additionally, 100% of the population believed that Big Data Technology can be implemented in Healthcare. Finally, the majority does not know any cases of use of Big Data Technology in Greece while 57,8% of the them mentioned that they knew use cases of the Big Data Technology abroad.

Research Status and Implications of Foreign Medical Automatic Question Answering System / 医学信息学杂志

The paper analyzes the documents related to the foreign medical automatic Question Answering (QA) system,and compares the differences between automatic QA and traditional network information retrieval,describes the automatic QA system in the aspects of application researches,common tools and relevant technologies.Combining foreign related researches,it also discusses the current key problems of medical automatic QA system and the implications for China in order to offer reference for further research.