Background: The risk of chronic diseases increases markedly with age and after menopause. An increase in bodily iron following menopause could contribute to this phenomenon of increased risk of chronic diseases. We aimed to investigate how various iron biomarkers change with advancing age, according to sex and menopausal status. Methods: We enrolled community-dwelling individuals with available information on ferritin, transferrin, iron, hepcidin, and soluble transferrin receptor levels from the Prevention of Renal and Vascular Endstage Disease study. The association of the iron biomarkers with age, sex, and menopausal status was investigated with linear regression models. Results: Mean (SD) age of the 5222 individuals (2680 women [51.3%], among whom 907 [33.8%] were premenopausal, 529 [19.7%] perimenopausal, and 785 [29.3%] postmenopausal), was 53.4 (12.0) years. Iron biomarkers showed a constant increase in women throughout their life course, in some cases at older ages surpassing values in men who, in turn, showed consistently higher levels of iron status compared to women in most age categories. Ferritin, hepcidin, and transferrin saturation levels were 3.03, 2.92, and 1.08-fold (all p < 0.001) higher in postmenopausal women compared to premenopausal. Conclusions: We found that iron accumulates differently depending on sex, age, and menopausal status. An increased iron status was identified in women, especially during and after menopause.

Researches on green data centers have defined guidelines and end-to-end methodologies to increase energy efficiency. Most of these approaches require a disrupting reengineering of the infrastructure and significant upfront investments. Smaller data centers need to reach green objectives with a more incremental approach. The EnergIT project proposes a methodology and related tools that support the incremental redesign of data centers toward greater energy efficiency based on three main levers: 1) physical repositioning of servers to optimize air flow circulation and cooling, enabling higher set temperatures of the cooling system; 2) replacement of server models; and 3) virtualization. This paper describes the approach and provides evidence on the effectiveness of the methodology by showing how the combined effect of the three levers has led to 62% reduction of energy consumption in a real case study.

Previous contributions in the empirical software engineering literature have consistently observed a quality degradation effect of proprietary code as a consequence of maintenance. This degradation effect, referred to as entropy effect, has been recognized to be responsible for significant increases in maintenance effort. In the Open Source context, the quality of code is a fundamental design principle. As a consequence, the maintenance effort of Open Source applications may not show a similar increasing trend over time. The goal of this paper is to empirically verify the entropy effect for a sample of 4,289 community Open Source application versions. Analyses are based on the comparison with an estimate of effort obtained with a traditional effort estimation model. Findings indicate that community Open Source applications show a slower growth of maintenance effort over time, and, therefore, are less subject to the entropy effect.

A quality degradation effect of proprietary code has been observed as a consequence of maintenance. This quality degradation effect, called entropy, is a cause for higher maintenance costs. In the Open Source context, the quality of code is a fundamental tenet of open software developers. As a consequence, the quality degradation principle measured by entropy cannot be assumed to be valid. The goal of the paper is to analyze the entropy of Open Source applications by measuring the evolution of maintenance costs over time. Analyses are based on cost data collected from a sample of 1251 Open Source application versions, compared with the costs estimated with a traditional model for proprietary software. Findings indicate that Open Source applications are less subject to entropy, have lower maintenance costs and also a lower need for maintenance interventions aimed at restoring quality. Finally, results show that a lower entropy is favored by greater functional simplicity.