Abstract

Abstract
This study investigates the sustainability reporting practices of companies based in the Nordic and the Mediterranean European countries for the period 2013-2015. Its purpose is to analyse to what extent, if any, are there differences in these practices. It seeks to capture the influence of national institutions and firm specific characteristics in sustainability reporting. Non-parametric statistics are used to analyse some factors which influence disclosure, namely country, industry affiliation, type of property, listing status and size. In accordance with the theoretical frame used, that of the varieties of capitalism approach, findings suggest that in general companies from Mediterranean European countries present higher levels of engagement with the Global Reporting Initiative.

Abstract
Purpose: The purpose of this paper is to compare the way in which gender and propensity to risk are associated in two samples, one of entrepreneurs and the other of non-entrepreneurs, while controlling for other factors, namely, national cultures. Design/methodology/approach: On the basis of data from 19 advanced countries, and by using two different samples, one of entrepreneurs and the other of non-entrepreneurs, the authors have used logistical regression analysis to analyse the relation between gender and propensity to risk has been used. Findings: Findings suggest that gender and culture are much stronger in influencing risk propensity among non-entrepreneurs than among entrepreneurs. Originality/value: Instead of analysing the effects of propensity to risk in entrepreneurship, as is usually done, the authors study some of its determinants, highlighting the differences between men and women.

Abstract
The problem of joint estimation of parameters and state of continuous time systems using discrete time observations is addressed. The plant parameters are assumed to be modeled by a Wiener process. The a priori probability density function (pdf) of an extended state that comprises the plant state variables and the parameters is propagated in time using an approximate solution of the Fokker-Planck equation that relies on Trotter's formula for semigroup decomposition. The a posteriori (i. e., given the observations) pdf is then computed at the observation instants using Bayes law.

Abstract
Autoregressive Moving Average (ARMA) time series model fitting is a procedure often based on aggregate data, where parameter estimation plays a key role. Therefore, we analyze the effect of temporal aggregation on the accuracy of parameter estimation of mixed ARMA and MA models. We derive the expressions required to compute the parameter values of the aggregate models as functions of the basic model parameters in order to compare their estimation accuracy. To this end, a simulation experiment shows that aggregation causes a severe accuracy loss that increases with the order of aggregation, leading to poor accuracy.

Abstract
Dysfunction of arteriovenous access for hemodialysis is a challenge for the vascular surgeon. Some patients have complex vascular access with problems that are difficult to solve. Careful analysis of the vascular network with ultrasound and dissection of the veins during surgery can help to identify the best option for each access. We introduce and discuss the case of creation of a radio-cephalic fistula with outflow into the brachial vein in 64-year-old hemodialysis male patient. This technique enables extending fistula patency, arterializing the brachial vein, and improves cost efficiency.