Spaceability and algebrability of sets of nowhere integrable functions

We show that the set of Lebesgue integrable functions in $[0,1]$ which are nowhere essentially bounded is spaceable, improving a result from [F. J. Garc\'{i}a-Pacheco, M. Mart\'{i}n, and J. B. Seoane-Sep\'ulveda. \textit{Lineability, spaceability, and algebrability of certain subsets of function spaces,} Taiwanese J. Math., \textbf{13} (2009), no. 4, 1257--1269], and that it is strongly $\mathfrak{c}$-algebrable. We prove strong $\mathfrak{c}$-algebrability and non-separable spaceability of the set of functions of bounded variation which have a dense set of jump discontinuities. Applications to sets of Lebesgue-nowhere-Riemann integrable and Riemann-nowhere-Newton integrable functions are presented as corollaries. In addition we prove that the set of Kurzweil integrable functions which are not Lebesgue integrable is spaceable (in the Alexievicz norm) but not 1-algebrable. We also show that there exists an infinite dimensional vector space $S$ of differentiable functions such that each element of the $C([0,1])$-closure of $S$ is a primitive to a Kurzweil integrable function, in connection to a classic spaceability result from [V. I. Gurariy, \textit{Subspaces and bases in spaces of continuous functions (Russian),} Dokl. Akad. Nauk SSSR, \textbf{167} (1966), 971-973].Comment: Accepted for publication in 201

Financial liberalization and the capital account : Thailand, 1988-97

The authors examine Thailand's macro-economy and micro-economy for the period 1988-97 to assess the extent to which the country's mix of macroeconomic and financial sector policies contributed to its economic crisis in 1997. They conclude that the crisis was fundamentally one of private sector debt, rooted in private behavior that affected the magnitude and composition of investment and how it was financed. Unlike the Latin American debt crisis, the Thai crisis was not caused by excessive sovereign borrowing. Financial sector weakness--including inadequate regulation and supervision, implicit deposit insurance, concentrated ownership structures, and poor accounting and disclosure--combined with liberalization of the financial sector and capital accounts, increased vulnerability by creating incentives for risk-taking by financial institutions. Many macroeconomic fundamentals were strong, but the combination of tight monetary policy and an inflexible exchange rate created strong incentives for residents to expose themselves to excessive foreign exchange and liquidity risks. Weak corporate governance, including close corporate links to the banking sector, encouraged risky investments and over-diversification in the corporate sector.Payment Systems&Infrastructure,Financial Intermediation,Banks&Banking Reform,International Terrorism&Counterterrorism,Economic Theory&Research,Banks&Banking Reform,Financial Intermediation,Economic Theory&Research,International Terrorism&Counterterrorism,Financial Economics

Stability analysis of a grid-connected VSC controlled by SPC

In the near future a large part of traditional generation based on conventional synchronous machines (SM) will be replaced by renewable generation based on voltage source converters (VSC). In this sense, power system operators have begun to demand VSC-based power plants be able to participate in the frequency and voltage regulation, and are also interested in services like inertia emulation and damping of power oscillation, functions that today are carried out by large synchronous generators. Therefore, several studies have suggested new ways to control voltage source converters, that try to emulate the behavior of synchronous generators and are known generically as Virtual Synchronous Machines. The synchronous power controller (SPC) is a flexible solution that emulates the classical swing equation of a synchronous machine and improves its response. The SPC inherits the advantages of conventional synchronous generators, while it fixes many of its drawbacks. In this work, a sensitivity analysis of a VSC connected to the grid and controlled by SPC is performed. In this sense, a non-linear mathematical model of the system is first developed. This non-linear model is then linearized, obtaining a linear model from which the eigenvalues and sensitivities of the system to some relevant parameters are calculated. Finally, time-domain simulations are performed to confirm the results of the sensitivity analysis.Postprint (author's final draft