Emotional Intelligence and risk taking in investment decision-making

Previous work on investment decision-making suggested that emotions prevent investors from taking risks and from investing in a rational way, whereas other work found that there is great variability in people’s ability to manage and use emotional feedbacks. We hypothesized that people with high trait emotional intelligence should be more willing, than people with low trait emotional intelligence, to accept risks when making an investment. Data supported a model in which trait emotional intelligence predicted willingness to invest both when the expected value is positive and when it is negative. The effect of trait emotional intelligence was significant even controlling for other variables, like attitude toward economic risk and money attitude. We believe that these results help improving the understanding of how emotions influence investors’ behavior and show that their role is not always detrimental but depends on the interplay between individual differences and situational factors

Data-based modeling of drug penetration relates human skin barrier function to the interplay of diffusivity and free-energy profiles

Based on experimental concentration depth profiles of the antiinflammatory drug dexamethasone in human skin, we model the time-dependent drug penetration by the 1D general diffusion equation that accounts for spatial variations in the diffusivity and free energy. For this, we numerically invert the diffusion equation and thereby obtain the diffusivity and the free-energy profiles of the drug as a function of skin depth without further model assumptions. As the only input, drug concentration profiles derived from X-ray microscopy at three consecutive times are used. For dexamethasone, skin barrier function is shown to rely on the combination of a substantially reduced drug diffusivity in the stratum corneum (the outermost epidermal layer), dominant at short times, and a pronounced free-energy barrier at the transition from the epidermis to the dermis underneath, which determines the drug distribution in the long-time limit. Our modeling approach, which is generally applicable to all kinds of barriers and diffusors, allows us to disentangle diffusivity from free-energetic effects. Thereby we can predict short-time drug penetration, where experimental measurements are not feasible, as well as long-time permeation, where ex vivo samples deteriorate, and thus span the entire timescales of biological barrier functioning

Mineria de datos en inteligencia de negocios

Este proyecto tiene por objetivos: [a] definir un marco teórico que permita determinar de qué manera, los sistemas inteligentes puede utilizarse para descubrir automáticamente descripciones cualitativas de una base de datos que mejoren la calidad de la inteligencia de negocio, [b] determinar la calidad (por contraste con expertos del dominio) del conocimiento cualitativo inferido automáticamente y [c] desarrollar técnicas y fases metodológicas que mejoren el proceso de minería de datos con énfasis en la inteligencia de negocio.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

The risk stratification of adverse neonatal outcomes in women with gestational diabetes (STRONG) study

Aims: To assess the risk of adverse neonatal outcomes in women with gestational diabetes (GDM) by identifying subgroups of women at higher risk to recognize the characteristics most associated with an excess of risk. Methods: Observational, retrospective, multicenter study involving consecutive women with GDM. To identify distinct and homogeneous subgroups of women at a higher risk, the RECursive Partitioning and AMalgamation (RECPAM) method was used. Overall, 2736 pregnancies complicated by GDM were analyzed. The main outcome measure was the occurrence of adverse neonatal outcomes in pregnancies complicated by GDM. Results: Among study participants (median age 36.8 years, pre-gestational BMI 24.8 kg/m2), six miscarriages, one neonatal death, but no maternal death was recorded. The occurrence of the cumulative adverse outcome (OR 2.48, 95% CI 1.59–3.87), large for gestational age (OR 3.99, 95% CI 2.40–6.63), fetal malformation (OR 2.66, 95% CI 1.00–7.18), and respiratory distress (OR 4.33, 95% CI 1.33–14.12) was associated with previous macrosomia. Large for gestational age was also associated with obesity (OR 1.46, 95% CI 1.00–2.15). Small for gestational age was associated with first trimester glucose levels (OR 1.96, 95% CI 1.04–3.69). Neonatal hypoglycemia was associated with overweight (OR 1.52, 95% CI 1.02–2.27) and obesity (OR 1.62, 95% CI 1.04–2.51). The RECPAM analysis identified high-risk subgroups mainly characterized by high pre-pregnancy BMI (OR 1.68, 95% CI 1.21–2.33 for obese; OR 1.38 95% CI 1.03–1.87 for overweight). Conclusions: A deep investigation on the factors associated with adverse neonatal outcomes requires a risk stratification. In particular, great attention must be paid to the prevention and treatment of obesity

Mineria de datos en inteligencia de negocios

Este proyecto tiene por objetivos: [a] definir un marco teórico que permita determinar de qué manera, los sistemas inteligentes puede utilizarse para descubrir automáticamente descripciones cualitativas de una base de datos que mejoren la calidad de la inteligencia de negocio, [b] determinar la calidad (por contraste con expertos del dominio) del conocimiento cualitativo inferido automáticamente y [c] desarrollar técnicas y fases metodológicas que mejoren el proceso de minería de datos con énfasis en la inteligencia de negocio.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Varying spin state composition by the choice of capping ligand in a family of molecular chains: detailed analysis of magnetic properties of chromium(III) horseshoes

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