ADOPTING LEED CERTIFICATION IN LODGING FACILITIES: GREENING THE HOSPITALITY INDUSTRY

The research intended to analyze the adoption process of the green certification "Leadership in Energy and Environmental Design" (LEED) from the hotel sector establishments that has already adopted it. For its concretization it was proceeded a bibliographical research, secondary fact-gathering in journals, institutional sites and documentaries, and primary fact-gathering by means of semi structured interviews carried out with responsible people of the certified hotels and of the responsible entity of the certification in Brazil (Green Building Council Brazil). There were 21 interviewee, being 02 of the GBC Brazil and 19 of means of lodging (31% of the certified). For data analysis, it was utilized content analysis technique with the aid of ATLAS.ti software. The results permitted to identify the chronology of the processes of certification and the profile of the hotel categories that adopt the LEED program. Beyond that, the interviews enabled the discussion of the initial motivations for seeking the certification, as well the advantages and the obstacles perceived regarding its adoption.

PFGE characterisation and adhesion ability of Listeria monocytogenes isolates obtained from bovine carcasses and beef processing facilities

Listeria monocytogenes is a pathogen capable of adhering to many surfaces and forming biofilms, which may explain its persistence in food processing environments. This study aimed to genetically characterise L monocytogenes isolates obtained from bovine carcasses and beef processing facilities and to evaluate their adhesion abilities. DNA from 29 L monocytogenes isolates was subjected to enzymatic restriction digestion (Ascii and Apal), and two clusters were identified for serotypes 4b and 112a, with similarities of 48% and 68%. respectively. The adhesion ability of the isolates was tested considering: inoculum concentration, culture media, carbohydrate source, NaCl concentration, incubation temperature, and pH. Each isolate was tested at 10(8) CFU mL(-1) and classified according to its adhesion ability as weak (8 isolates). moderate (17) or strong (4). The isolates showed higher adhesion capability in non-diluted culture media, media at pH 7.0, incubation at 25 degrees C and 37 degrees C, and media with NaCl at 5% and 7%. No relevant differences were observed for adhesion ability with respect to the carbohydrate source. The results indicated a wide diversity of PFGE profiles of persistent L monocytogenes isolates, without relation to their adhesion characteristics. Also, it was observed that stressing conditions did not enhance the adhesion profile of the isolates. (C) 2012 Elsevier Ltd. All rights reserved.

Mutual Information Rate and Bounds for It

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Universal behavior of the Shannon mutual information of critical quantum chains

We consider the Shannon mutual information of subsystems of critical quantum chains in their ground states. Our results indicate a universal leading behavior for large subsystem sizes. Moreover, as happens with the entanglement entropy, its finite-size behavior yields the conformal anomaly c of the underlying conformal field theory governing the long-distance physics of the quantum chain. We study analytically a chain of coupled harmonic oscillators and numerically the Q-state Potts models (Q = 2, 3, and 4), the XXZ quantum chain, and the spin-1 Fateev-Zamolodchikov model. The Shannon mutual information is a quantity easily computed, and our results indicate that for relatively small lattice sizes, its finite-size behavior already detects the universality class of quantum critical behavior.