In this paper we apply techniques of complex network analysis to data sources representing public funding programs and discuss the importance of the considered indicators for program evaluation. Starting from the Open Data repository of the 2007-2013
Italian Program Programma Operativo Nazionale Ricerca e Competitivit`a (PON R&C), we build a set of data models and perform network analysis over them. We discuss the obtained experimental results outlining interesting new perspectives that emerge from the application of the proposed methods to the socio-economical evaluation of funded programs.
The lowest dimensional gluon condensate $G_2$ is analyzed at finite temperature and chemical potential using a holographic model of QCD with conformal invariance broken by a background dilaton. Starting from the free energy of the model, the thermody
namical quantities needed to determine the $T$ and $mu$ dependence of the gluon condensate are evaluated. At high temperature the gluon condensate is independent of chemical potential. Moreover, at $mu=0$ and in the string frame, the temporal and spatial Wilson loops at low temperature are computed; they are related to the (chromo) electric and magnetic components of $G_2$, respectively. The $T$-dependence of the two components is separately determined.
