ByMichael L. to those in government, school administration, and the general community, music education advocates have gained recognition for music as part of the core curriculum. M a r k ormer Senator Daniel Patrick Moynihan once said, "Knowledge is a form of capital, much of it formed by government investment in education. ... Politics hasbecome a process that deliberately seeks to effect such outcomes as who thinks what, who feels how."l In this statement, Moynihan verbalized the reason why music education needs to be its own advocate. Advocacy is the way that we as music educators can explain to policy makers, as well as to the general public, the reasons why our profession is important and why we need their support to continue serving the needs of society. As advocates, we need to tell the nation that music education is vital and dynamic. The apparent simplicity of this message belies the expertise and sophistication required to ensure ongoing support for the profession. Because many important developments, curricular and otherwise, result from public policy-laws, government policies, and regulations-advocacy is indispensable to music education. For as long as music has been a curricular subject in the United States, its direction and focus have been subject to controls imposed by public policies created by local school boards, state education agencies, and the federal government. Advocacy must ensure that such policies are crafted by informed judgments based on knowledge.

Advocacy for music education has become a major professional activity that is not always understood by music educators. Education decision makers - boards of education, legislators, government policy makers - must appreciate why music education is important to society so they can make informed decisions about any number of issues that affect music in schools. The principal voice for music education advocacy in the USA is the MENC: The National Association for Music Education, which provides a model for professional advocacy at the national level. Other countries have different models. It will be healthy for music educators to become familiar with models of successful advocacy in other countries.

We construct a 'reflexivity' index to measure the activity generated endogenously within a market for cryptocurrencies. For this purpose, we fit a univariate self-exciting Hawkes process with two classes of parametric kernels to high-frequency trading data. A parsimonious model of both endogenous and exogenous dynamics enables a direct comparison with exchanges for traditional asset classes, in terms of identified branching ratios. We also formulate a 'Hawkes disorder problem,' as generalization of the established Poisson disorder problem, and provide a simulation-based approach to determining an optimal observation horizon. Our analysis suggests that Bitcoin midprice dynamics feature long-memory properties, well explained by the power-law kernel, at a level of criticality similar to fiat-currency markets.

In this paper, we focus on the problem of minimizing a network of state facilities that provide essential public services (schools, offices, and hospitals). The goal is to reduce the size of the network in order to minimize the costs associated with it. However, it is essential that every customer should be able to access an appropriate service center within a reachable distance. This problem can arise in various scenarios, such as a government cutting back on public service spending in remote areas or as a reaction to changing demographics (population increase/decrease). In general, this task is NP-hard which makes the problem particularly hard to scale. Therefore, for larger problems, heuristic methods must be employed to find an approximation of the optimum. To solve this problem with satisfactory results, we have presented an enhanced version of the genetic algorithm based on war elimination and migration operations. This modification overcomes the well-known shortcoming of GAs when the population becomes gradually more and more similar, these results in a diversity decrease which in turn leads to a sub-optimal local minimum. We test the performance of the novel algorithm against the standard heuristic benchmarks on the widely accepted Beasley OR-library dataset for optimization problems. Finally, we provide a case study based on real data, where a municipality tries to minimize the number of schools in a region while satisfying accessibility and other region-specific constraints. INDEX TERMS Genetic algorithms, minimisation, public facilities, set covering problem, war elimination.

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