Local Competition, Inbreeding, and the Evolution of Sex-Biased Dispersal.

Using game theory, we developed a kin-selection model to investigate the consequences of local competition and inbreeding depression on the evolution of natal dispersal. Mating systems have the potential to favor strong sex biases in dispersal because sex differences in potential reproductive success affect the balance between local resource competition and local mate competition. No bias is expected when local competition equally affects males and females, as happens in monogamous systems and also in polygynous or promiscuous ones as long as female fitness is limited by extrinsic factors (breeding resources). In contrast, a male-biased dispersal is predicted when local mate competition exceeds local resource competition, as happens under polygyny/promiscuity when female fitness is limited by intrinsic factors (maximal rate of processing resources rather than resources themselves). This bias is reinforced by among-sex interactions: female philopatry enhances breeding opportunities for related males, while male dispersal decreases the chances that related females will inbreed. These results meet empirical patterns in mammals: polygynous/promiscuous species usually display a male-biased dispersal, while both sexes disperse in monogamous species. A parallel is drawn with sex-ratio theory, which also predicts biases toward the sex that suffers less from local competition. Optimal sex ratios and optimal sex-specific dispersal show mutual dependence, which argues for the development of coevolution models.

Financial constraints and the failure of innovation projects

Theoretical and empirical approaches have stressed the existence of financial constraints in innovative activities of firms. This paper analyses the role of financial obstacles on the likelihood of abandoning an innovation project. Although a large number of innovation projects are abandoned before their completion, the empirical evidence has focused on the determinants of innovation while failed projects have received little attention. Our analysis differentiates between internal and external barriers on the probability of abandoning a project and we examine whether the effects are different depending on the stage of the innovation process. In the empirical analysis carried out for a panel data of potential innovative Spanish firms for the period 2004-2010, we use a bivariate probit model to take into account the simultaneity of financial constraints and the decision to abandon an innovation project. Our results show that financial constraints most affect the probability of abandoning an innovation project during the concept stage and that low-technological manufacturing and non-KIS service sectors are more sensitive to financial constraints.

The Farm, the city, and the emergence of social security

We study the social, demographic and economic origins of social security. The data for the U.S. and for a cross section of countries suggest that urbanization and industrialization are associated with the rise of social insurance. We describe an OLG model in which demographics, technology, and social security are linked together in a political economy equilibrium. In the model economy, there are two locations (sectors), the farm (agricultural) and the city (industrial) and the decision to migrate from rural to urban locations is endogenous and linked to productivity differences between the two locations and survival probabilities. Farmers rely on land inheritance for their old age and do not support a pay-as-you-go social security system. With structural change, people migrate to the city, the land loses its importance and support for social security arises. We show that a calibrated version of this economy, where social security taxes are determined by majority voting, is consistent with the historical transformation in the United States.

Full Exploration of the Diels–Alder Cycloaddition on Metallofullerenes M3N@C80 (M=Sc, Lu, Gd): The D5h versus Ih Isomer and the Influence of the Metal Cluster

In this work a detailed investigation of the exohedral reactivity of the most important and abundant endohedral metallofullerene (EMF) is provided, that is, Sc3N@Ih-C80 and its D5h counterpart Sc3N@D5h-C80, and the (bio)chemically relevant lutetium- and gadolinium-based M3N@Ih/D5h-C80 EMFs (M=Sc, Lu, Gd). In particular, we analyze the thermodynamics and kinetics of the Diels–Alder cycloaddition of s-cis-1,3-butadiene on all the different bonds of the Ih-C80 and D5h-C80 cages and their endohedral derivatives. First, we discuss the thermodynamic and kinetic aspects of the cycloaddition reaction on the hollow fullerenes and the two isomers of Sc3N@C80. Afterwards, the effect of the nature of the metal nitride is analyzed in detail. In general, our BP86/TZP//BP86/DZP calculations indicate that [5,6] bonds are more reactive than [6,6] bonds for the two isomers. The [5,6] bond D5h-b, which is the most similar to the unique [5,6] bond type in the icosahedral cage, Ih-a, is the most reactive bond in M3N@D5h-C80 regardless of M. Sc3N@C80 and Lu3N@C80 give similar results; the regioselectivity is, however, significantly reduced for the larger and more electropositive M=Gd, as previously found in similar metallofullerenes. Calculations also show that the D5h isomer is more reactive from the kinetic point of view than the Ih one in all cases which is in good agreement with experiments

Subject-based steroid profiling and the determination of novel biomarkers for DHT and DHEA misuse in sports.

Doping with natural steroids can be detected by evaluating the urinary concentrations and ratios of several endogenous steroids. Since these biomarkers of steroid doping are known to present large inter-individual variations, monitoring of individual steroid profiles over time allows switching from population-based towards subject-based reference ranges for improved detection. In an Athlete Biological Passport (ABP), biomarkers data are collated throughout the athlete's sporting career and individual thresholds defined adaptively. For now, this approach has been validated on a limited number of markers of steroid doping, such as the testosterone (T) over epitestosterone (E) ratio to detect T misuse in athletes. Additional markers are required for other endogenous steroids like dihydrotestosterone (DHT) and dehydroepiandrosterone (DHEA). By combining comprehensive steroid profiles composed of 24 steroid concentrations with Bayesian inference techniques for longitudinal profiling, a selection was made for the detection of DHT and DHEA misuse. The biomarkers found were rated according to relative response, parameter stability, discriminative power, and maximal detection time. This analysis revealed DHT/E, DHT/5β-androstane-3α,17β-diol and 5α-androstane-3α,17β-diol/5β-androstane-3α,17β-diol as best biomarkers for DHT administration and DHEA/E, 16α-hydroxydehydroepiandrosterone/E, 7β-hydroxydehydroepiandrosterone/E and 5β-androstane-3α,17β-diol/5α-androstane-3α,17β-diol for DHEA. The selected biomarkers were found suitable for individual referencing. A drastic overall increase in sensitivity was obtained. The use of multiple markers as formalized in an Athlete Steroidal Passport (ASP) can provide firm evidence of doping with endogenous steroids.