Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

Database-assisted global metabolomics profiling of pleural effusion induced by tuberculosis and malignancy

Database-assisted global metabolomics has received growing attention due to its capability for unbiased identification of metabolites in various biological samples.Herein,we established a mass spectrometry(MS)-based database-assisted global metabolomics method and investigated metabolic distance between pleural effusion induced by tuberculosis and malignancy,which are difficult to be distinguished due to their similar clinical symptoms.The present method utilized a liquid chromatography(LC) system coupled with high resolution mass spectrometry(MS) working on full scan and data dependent mode for data acquisition.Unbiased identification of metabolites was performed through mass spectral searching and then confirmed by using authentic standards.As a result,a total of 194 endogenous metabolites were identified and 33 metabolites were found to be differentiated between tuberculous and malignant pleural effusions.These metabolites involved in tryptophan catabolism,bile acid biosynthesis,and β-oxidation of fatty acids,provided non-invasive biomarkers for differentiation of the pleural effusion samples with high sensitivity and specificity.