FLOWS OF INFORMATION AND LANGUAGE IN ORGANIZATIONAL SETTINGS

Information flows are formed naturally or formally induced in organizational settings, passing from the strategic level to operational level, reflecting, and impacting in the processes that make up the organization, including the decision-making process and therefore the action strategies of organization. The management of organizational environments based on information requires careful attention to various kinds of languages used for communication between sectors and employees of the organization, whose goal is to share, disseminate and socialize the information produced in this environment.

Compton scattering spectrum as a source of information of normal and neoplastic breast tissues' composition

In this work we measured X-ray scatter spectra from normal and neoplastic breast tissues using photon energy of 17.44 key and a scattering angle of 90 degrees, in order to study the shape (FWHM) of the Compton peaks. The obtained results for FWHM were discussed in terms of composition and histological characteristics of each tissue type. The statistical analysis shows that the distribution of FWHM of normal adipose breast tissue clearly differs from all other investigated tissues. Comparison between experimental values of FWHM and effective atomic number revealed a strong correlation between them, showing that the FWHM values can be used to provide information about elemental composition of the tissues. (C) 2012 Elsevier Ltd. All rights reserved.

ACTIVE NETWORKS THAT MAXIMIZE THE AMOUNT OF INFORMATION TRANSMISSION

This work clarifies the relationship between network circuit (topology) and behavior (information transmission and synchronization) in active networks, e. g. neural networks. As an application, we show how to determine a network topology that is optimal for information transmission. By optimal, we mean that the network is able to transmit a large amount of information, it possesses a large number of communication channels, and it is robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.