Doing Their Job

This chapter systematically explicates how intermediaries construct the value of cultural goods to better understand the entrepreneurial implications of their functions. Three key properties of cultural goods—high symbolism, proliferation, and subjectivity—juxtaposed against three key valuation elements—categories, criteria, and standards—define the specific functions that intermediaries perform. Intermediaries make cultural goods visible through introduction, the sharing of information. They also instruct consumers, that is, they decode the symbolic meaning and value of the good. Finally, intermediaries perform the inclusion function, selectively validating the quality of certain cultural goods. These functions, although neither sharply demarcated nor linearly executed, result in a value pyramid, where goods at the highest apex of quality fetch either very high aggregate sales or individual prices. Operating as an entrepreneurial intermediary—pioneering or otherwise—that performs one or more of these functions brings different sets of challenges and has different implications for effective market creation.

Probabilist Set Inversion using Pseudo-Intervals Arithmetic

<pre><!--StartFragment-->In this paper, we present how to use an interval arithmetic framework based on free algebra construction, in order to build better defined inclusion function for interval semi-group and for its associated vector space. One introduces the <span>psi</span>-algorithm, which performs set inversion of functions and exhibits some numerical examples developed with the python programming langage<!--EndFragment--></pre>.

The Dynamic Analysis of Multibody Systems with Uncertain Parameters Using Interval Method

The theoretical and computational aspects of interval methodology based on Chebyshev polynomials for modeling multibody dynamic systems in the presence of parametric uncertainties are proposed, where the uncertain parameters are modeled by uncertain-but-bounded interval variables which only need the bounds of uncertain parameters, not necessarily knowing the probabilistic distribution. The Chebyshev inclusion function which employs the truncated Chevbyshev series expansion to approximate the original function is proposed. Based on Chebyshev inclusion function, the algorithm for solving the nonlinear equations with interval parameters is proposed. Combining the HHT-I3 method, this algorithm is used to calculate the multibody systems dynamic response which is governed by differential algebraic equations (DAEs). A numerical example that is a slider-crank with uncertain parameters is presented, which shows that the novel methodology can control the overestimation effectively and is computationally faster than the scanning method.