Adipokines and Sexual Hormones Associated with the Components of the Metabolic Syndrome in Pharmacologically Untreated Subjects: Data from the Brisighella Heart Study

We evaluated the association of the sex hormone pattern and the serum level of the main adipokines to metabolic syndrome (MS) and its components in 199 pharmacologically untreated subjects. Men and women included in the age-class subgroups were matched for body mass index, waist circumference, blood pressure, heart rate, fasting plasma glucose, and plasma lipids. Men without MS had significantly lower leptin/adiponectin ratio than men with MS. Women without MS had lower leptin and leptin/adiponectin ratio than women with MS but had significantly higher adiponectin, estrone, and dehydroepiandrosterone levels. In men, the leptin/adiponectin ratio is the main factor associated to MS diagnosis (OR: 3.36, 95% CI 1.40–8.08), while in women adiponectin alone appears to be a protective factor (OR: 0.87, 95% CI 0.79–0.95). In conclusion, in a sample of pharmacologically untreated subjects, leptin/adiponectin ratio seems to be the factor more strongly associated to MS and its components

Exploiting damped techniques for nonlinear conjugate gradient methods

In this paper we propose the use of damped techniques within Nonlinear Conjugate Gradient (NCG) methods. Damped techniques were introduced by Powell and recently reproposed by Al-Baali and till now, only applied in the framework of quasi–Newton methods. We extend their use to NCG methods in large scale unconstrained optimization, aiming at possibly improving the efficiency and the robustness of the latter methods, especially when solving difficult problems. We consider both unpreconditioned and Preconditioned NCG (PNCG). In the latter case, we embed damped techniques within a class of preconditioners based on quasi–Newton updates. Our purpose is to possibly provide efficient preconditioners which approximate, in some sense, the inverse of the Hessian matrix, while still preserving information provided by the secant equation or some of its modifications. The results of an extensive numerical experience highlights that the proposed approach is quite promising

Who do you blame in local finance? An analysis of municipal financing in Italy

We study the effect of introducing a less transparent tax tool for the financing of local governments. A political agency model suggests that politicians with stronger re-electoral incentives would raise more tax revenues and use more the less transparent tax tool to enhance their probability of re-election. This prediction is tested by studying a reform that in 1999 allowed Italian municipalities to partially substitute a more accountable source of tax revenue (the property tax) with a less transparent one (a surcharge on the personal income tax of residents). Exploiting the existence of a term limit for mayors, we use a Difference in Difference approach, to estimate how mayors facing re-electoral concerns reacted to the introduction of the less transparent tax tool compared to mayors facing term limit. We find results in line with theory. We also show that the reduction in the property tax is larger in smaller municipalities and in municipalities with lower level of social capital. The normative implications are then discussed

Iterative Grossone-Based Computation of Negative Curvature Directions in Large-Scale Optimization

We consider an iterative computation of negative curvature directions, in large-scale unconstrained optimization frameworks, needed for ensuring the convergence toward stationary pointswhich satisfy second-order necessary optimality conditions. We show that to the latter purpose, we can fruitfully couple the conjugate gradient (CG) method with a recently introduced approach involving the use of the numeral called Grossone. In particular, recalling that in principle the CG method is well posed onlywhen solving positive definite linear systems, our proposal exploits the use of grossone to enhance theperformance of the CG, allowing the computation of negative curvature directions in the indefinite case, too. Our overall method could be used to significantly generalize the theory in state-of-the-art literature. Moreover, it straightforwardly allows the solution of Newton’s equation in optimization frameworks, even in nonconvex problems. We remark that our iterative procedure to compute a negative curvature direction does not require the storage of any matrix, simply needing to store a couple of vectors. This definitely represents an advance with respect to current results in the literature