Financial crises, debt overhang, and firm growth in transition economies

We examine the effects of the global financial crisis of 2008 and the European debt crisis of 2011 on the relationship between capital structure, investments, and performance for Eastern European companies. While the existing literature documents how firms\u2019 investments are sensitive to the availability of internal funds and to debt holdings, we further investigate whether this investment sensitivity also translates in different levels of performance, and document that capital structure indeed has both a direct and an indirect effect, mediated by the capital expenditure channel. We show that firms with higher financial flexibility experience higher investments and returns on capital. Over-levered firms instead suffer from a debt overhang condition, forcing them to curb investments, and consequently experiencing lower performance. Overall, we provide evidence on the importance of capital structure and financial flexibility on investments and performance, showing the real consequences of the debt overhang condition on firm value creation. Firms should therefore aim at maintaining adequate financial flexibility in order to be able to pursue future profitable investment opportunities, and avoid the under-investment problem arising from a debt overhang situation

Fragile Watermarking of 3D Models in Transformed Domain

This paper presents an algorithm aimed at the integrity protection of 3D models represented as a set of vertices and polygons. The proposed method defines a procedure to perform a fragile watermarking of the vertices’ data, namely 3D coordinates and polygons, introducing a very small error in the vertices’ coordinates. The watermark bit string is embedded into a secret vector space defined by the Karhunen–Loève transform derived from a key image. Experimental results show the good performance of the method and its security

Query Rewriting in Itemset Mining

Abstract. In recent years, researchers have begun to study inductive databases, a new generation of databases for leveraging decision support applications. In this context, the user interacts with the DBMS using advanced, constraint-based languages for data mining where constraints have been specifically introduced to increase the relevance of the results and, at the same time, to reduce its volume. In this paper we study the problem of mining frequent itemsets using an inductive database 1 . We propose a technique for query answering which consists in rewriting the query in terms of union and intersection of the result sets of other queries, previously executed and materialized. Unfortunately, the exploitation of past queries is not always applicable. We then present sufficient conditions for the optimization to apply and show that these conditions are strictly connected with the presence of functional dependencies between the attributes involved in the queries. We show some experiments on an initial prototype of an optimizer which demonstrates that this approach to query answering is not only viable but in many practical cases absolutely necessary since it reduces drastically the execution time

Recent highlights in the synthesis of highly functionalized pyrimidines

n/