[Design of Wearable Wireless Health Monitoring System and Status Recognition Algorithm].

A wearable wireless health monitoring system for drug addicts in compulsory rehabilitation centers was proposed. The system can continuously monitor multiple physiological parameters of drug addicts in real time, and issue early warning information when abnormal physiological parameters occur, so as to play the role of timely medical practice. In addition, this study proposes a convolutional neural network (CNN)model, which can evaluate the health status of drug addicts based on multiple physiological parameters. Experiments show that the model can be applied to the task of body state recognition in the open physiological parameter data set, and the recognition accuracy can reach up to 100% in a single physiological parameter data set; when the whole physiological data set is used, the recognition accuracy can reach 99.1%. The recognition accuracy exceeds the performance of the traditional pattern recognition method on this task, which verifies the superiority of the model.

Development of a Novel Shallow Liquid Interface Exposure System for MWCNT Toxicity Assessment.

Increasing applications of multiwalled carbon nanotubes (MWCNT) lead to significant occupational exposure and potential health concerns. Toxicity of MWCNT should be carefully elucidated since the conventional (CON) method with fully immersed condition fails to mimic the air-liquid interface (ALI) in airways. Additionally, quantification of MWCNT in cells was a real challenge. Currently available ALI exposure devices are costly, posing problems to conducting in vitro evaluations for emerging nanomaterials. A novel system, consisting of a shaker fluidized-bed atomizer (SFA) and electrostatic shallow liquid interface (ESLI) exposure chamber, has been developed for investigating nanotoxicity of well-dispersed pristine-MWCNT (pMWCNT) and carboxylized-MWCNT (cMWCNT). After 24-h exposure, LDH, MCP-1, IL-1ß, IL-6, and TNF-α releases were determined, and cell uptakes were quantified according to the molybdenum content in cells. Biological responses triggered by SLI exposure are obviously more sensitive compared with those caused by CON exposure at equivalent doses. Exposure dose-dependent release of LDH and IL-6 was highlighted in A549 cells, indicating higher cytotoxicity and inflammatory responses of cMWCNT attributed to its shorter length, smaller size, and higher cell uptake. Cell-associated dose-dependent release of LDH and IL-6 was highlighted in RAW264.7 cells, revealing the higher adverse health risk of pMWCNT due to frustrated phagocytosis and its much higher molybdenum content. These results suggest that inherent characteristics of cells and distinct physicochemical properties of pMWCNT and cMWCNT lead to either exposure dose-dependent or cell-associated dose-dependent responses. Notably, the SLI is superior to the CON exposure method and well suited for nanotoxicity assessment of different MWCNTs.

Users' participation and social influence during information spreading on Twitter.

Online Social Networks generate a prodigious wealth of real-time information at an incessant rate. In this paper we study the empirical data that crawled from Twitter to describe the topology and information spreading dynamics of Online Social Networks. We propose a measurement with three measures to state the efforts of users on Twitter to get their information spreading, based on the unique mechanisms for information retransmission on Twitter. It is noticed that small fraction of users with special performance on participation can gain great influence, while most other users play a role as middleware during the information propagation. Thus a community analysis is performed and four categories of users are found with different kinds of participation that cause the information dissemination dynamics. These suggest that exiting topological measures alone may reflect little about the influence of individuals and provide new insights for information spreading.