Quasar Black Hole Masses from Velocity Dispersions

Much progress has been made in measuring black hole (BH) masses in (non-active) galactic nuclei using the tight correlation between stellar velocity dispersions (sigma) in galaxies and the mass of their central BH. The use of this correlation in quasars, however, is hampered by the difficulty in measuring sigma in host galaxies that tend to be overpowered by their bright nuclei. We discuss results from a project that focuses on z~0.3 quasars suffering from heavy extinction at shorter wavelengths. This makes it possible to obtain clean spectra of the hosts in the spectral regions of interest, while broad lines (like H-alpha) are still visible at longer wavelengths. We compare BH masses obtained from velocity dispersions to those obtained from the broad line region and thus probe the evolution of this relation and BH growth with redshift and luminosity. Our preliminary results show an offset between the position of our objects and the local relation, in the sense that red quasars have, on average, lower velocity dispersions than local galaxies. We discuss possible biases and systematic errors that may affect our results.Comment: 4 pages, to appear in the proceedings of the 2nd Kolkata conference on Observational Evidence for Black Holes in the Universe, ed. S. Chakrabarti (AIP

Common stochastic trends and aggregation in heterogeneous panels

In nonstationary heterogeneous panels where the number of units is finite and where each unit cointegrates, a large number of conditions needs to be satisfied for cointegration to be preserved in the aggregate relationship. In reality, the conditions most likely will not hold. This paper takes a closer look at what happens when the conditions are violated. In this case, the question of whether an aggregate relationship is observationally equivalent to a cointegrating equation is of particular interest. We derive a measure of the degree of noncointegration of the aggregate estimates, and we explore its asymptotic properties

Contracts and Insurance Group Formation by Myopic Players

This paper employs a cooperative approach to insurance group formation problems.The insurance group formation is analyzed in terms of stability with respect to one-person deviations.Depending on the exact contractual setting, three stability concepts are proposed: individual, contractual and compensation stability.When we apply our general framework to the standard insurance setting of Rothschild and Stiglitz (1976), we find that, in each type of contractual setting, there are stable individually rational pooling outcomes while, on the contrary, individually rational separating outcomes are not stable.

Process Mining for Dynamic Modeling of Smart Manufacturing Systems: Data Requirements

Modern manufacturing systems can benefit from the use of digital tools to support both short- and long-term decisions. Meanwhile, such systems reached a high level of complexity and are frequently subject to modifications that can quickly make the digital tools obsolete. In this context, the ability to dynamically generate models of production systems is essential to guarantee their exploitation on the shop-floors as decision-support systems. The literature offers approaches for generating digital models based on real-time data streams. These models can represent a system more precisely at any point in time, as they are continuously updated based on the data. However, most approaches consider only isolated aspects of systems (e.g., reliability models) and focus on a specific modeling purpose (e.g., material flow identification). The research challenge is therefore to develop a novel framework that systematically enables the combination of models extracted through different process mining algorithms. To tackle this challenge, it is critical to define the requirements that enable the emergence of automated modeling and simulation tasks. In this paper, we therefore derive and define data requirements for the models that need to be extracted. We include aspects such as the structure of the manufacturing system and the behavior of its machines. The paper aims at guiding practitioners in designing coherent data structures to enable the coupling of model generation techniques within the digital support system of manufacturing companies

Electrochemical Treatment of Arsenic in Drinking Water: Effect of Initial As3+ Concentration, pH, and Conductivity on the Kinetics of Oxidation

Many technologies for the treatment of arsenic-containing drinking water are available, but most of them are more effective on arsenic oxidized forms. Therefore, the pre-oxidation of As3+ is necessary. The electrochemical processes represent a very promising method due to the simultaneous oxidation of compounds using electrochemical conditions and the reactive radicals produced. In this work, As3+ oxidation was experimentally studied at a pilot scale using an electrochemical oxidation cell (voltage: 10 V; current: 1.7 A). The effect of the initial arsenite concentration, pH, and conductivity of drinking water on the oxidation of As3+ into As5+ was investigated. The results showed that the initial As3+ concentration strongly directly influences the oxidation process. Increasing the initial arsenite concentration from 500 to 5000 µg L−1, the pseudo-first order kinetic constant (k) strongly decreased from 0.521 to 0.038 min−1, and after 10 min, only 21.3% of As3+ was oxidized (vs. 99.9% in the case of As3+ equal to 500 µg L−1). Slightly alkaline conditions (pH = 8) favored the electrochemical oxidation into As5+, while the process was partially inhibited in the presence of a more alkaline or acidic pH. The increase in conductivity up to 2000 µS cm−1 enhanced the kinetic of the oxidation, despite remaining on the same order of magnitude as in the case of conductivity equal to 700 µS cm−1. After 10 min, 99.9 and 95% of As3+ was oxidized, respectively. It is the opinion of the authors that the influence of other operational factors, such as voltage and current density, and the impact of the high concentration of other pollutants should be deeply studied in order to optimize the process, especially in the case of an application at full scale. However, these results provide helpful indications to future research having highlighted the influence of initial As3+ concentration, pH, and conductivity on the electrochemical oxidation of arsenic

Finding an Effective Metric Used for Bijective S-Box Generation by Genetic Algorithms

In cryptography, S-box is a basic component of symmetric key algorithms which performs nonlinear substitution. S-boxes need to be highly nonlinear, so that the cipher can resist linear cryptanalysis. The main criteria for cryptographically strong (n × n) S-box are: • High non linearity; • High algebraic degree; • Balanced structure; • Good auto correlation properties. Our task was to give some suggestions for finding an effective metric used for generation bijective optimal S-Box. Because of the given problem’s complexity, our group considered different approaches and we gave a few suggestions for problem solving