Effective field theories have been widely used in nuclear physics. This volume is devoted to exploring the intricate structure of compact-star matter inaccessible directly from QCD. It is principally anchored on hidden symmetries and topology presumed to be encoded in QCD. It differs from standard effective field theory and energy density functional approaches in that it exploits renormalization-group flow in the complex 'vacuum' sliding with density inferred from topology change identified as a manifestation of baryon-quark continuity in dense matter. It makes a variety of predictions that drastically differ from the conventional treatments that could be tested by upcoming terrestrial and astrophysical experiments.This monograph recounts how to go, in one unique field theoretic formalism in terms of hadronic degrees of freedom, from finite nuclei to dense compact-star matter that could be explored in RIB-type machines in nuclear physics as well as in LIGO-type gravity waves in astrophysics.

Public performance-accountability nexus is a hot topic in recent research, but we know little about its antecedents and consequences in developing countries and transition economies. Are top-down appointed political elites taken accountable for public service performance in authoritarian nations like China? The question is theoretically and empirically examined in the book. I argue that government cadres are appropriately appraised and promoted even with the lame democracy. Using a novel dataset and event history analysis method, I test the performance-based political promotion tournament theory and its contingent features. I find that career advancement of provincial leading officials is positively influenced by public service performance but not by economic performance. The effect is stronger for Party secretaries than governors, for central connected officials than local officials, for younger than older, and for short tenure in office than long serving. The performance-promotion nexus in relatively weak and contingent on contextual attributes, suggesting performance-based reform should be deepened to make local agents accountable for public service delivery and responsiveness.

Providing the first truly comprehensive overview of Network Tomography - a novel network monitoring approach that makes use of inference techniques to reconstruct the internal network state from external vantage points - this rigorous yet accessible treatment of the fundamental theory and algorithms of network tomography covers the most prominent results demonstrated on real-world data, including identifiability conditions, measurement design algorithms, and network state inference algorithms, alongside practical tools for applying these techniques to real-world network management. It describes the main types of mathematical problems, along with their solutions and properties, and emphasizes the actions that can be taken to improve the accuracy of network tomography. With proofs and derivations introduced in an accessible language for easy understanding, this is an essential resource for professional engineers, academic researchers, and graduate students in network management and network science.