The rapid development of wellness smart devices and apps, such as Fitbit Coach and FitnessGenes, has triggered a wave of interaction on social networks. People communicate with and follow each other based on their wellness activities. Though such IoT devices and data provide a good motivation, they also expose users to threats due to the privacy leakage of social networks. Anonymization techniques are widely adopted to protect users' privacy during social data publishing and sharing. However, de-anonymization techniques are actively studied to identify weaknesses in current social network data-publishing mechanisms. In this paper, we conduct a comprehensive analysis on the typical structure-based social network de-anonymization algorithms. We aim to understand the de-anonymization approaches and disclose the impacts on their application performance caused by different factors, e.g., topology properties and anonymization methods adopted to sanitize original data. We design the analysis framework and define three experiment environments to evaluate a few factors' impacts on the target algorithms. Based on our analysis architecture, we simulate three typical de-anonymization algorithms and evaluate their performance under different pre-configured environments.
Abstract. With the development of molecular biology and gene-engineering technology, gene diagnosis has been an emerging approach for modern life sciences. Biological marker, recognized as the hot topic in the molecular and gene fields, has important values in early diagnosis, malignant tumour stage, treatment and therapeutic efficacy evaluation. The design of markers detection genetic circuit system for lung cancer is presented as a new method to provide basis for early warning and therapy. The system consists of three singlemarker detection circuits and an integration circuit. The single-marker detection circuit provides an instantaneous low level when target marker's concentration reaches the threshold. The integration circuit uses gene and gate to complete the output data fusion from single-marker detection circuit through logic operations to finish the combined detection. All the structure is modelled and analyzed by iBioSim through the biochemical reactions of different gene circuits. The experimental result indicates that the whole lung cancer detection system can realize joint detection of tumor markers with good stability and sensitivity.
There are over 8000 SCI (Science Citation Index) publications in the ISI (Institute for Scientific Information) Web of Knowledge database system. However, the publications are too many and it is difficult for new authors to choose the most suitable journals or periodicals to submit their research fruits of high level. So, some valuable information about SCI publications is collected, and the corresponding database is established. The records from this database are classified and counted. The statistical results show that the SCI publications information system is helpful to authors to issue papers.
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