This paper elaborates the hypothesis that the unique demography and sociology of Ashkenazim in medieval Europe selected for intelligence. Ashkenazi literacy, economic specialization, and closure to inward gene flow led to a social environment in which there was high fitness payoff to intelligence, specifically verbal and mathematical intelligence but not spatial ability. As with any regime of strong directional selection on a quantitative trait, genetic variants that were otherwise fitness reducing rose in frequency. In particular we propose that the well-known clusters of Ashkenazi genetic diseases, the sphingolipid cluster and the DNA repair cluster in particular, increase intelligence in heterozygotes. Other Ashkenazi disorders are known to increase intelligence. Although these disorders have been attributed to a bottleneck in Ashkenazi history and consequent genetic drift, there is no evidence of any bottleneck. Gene frequencies at a large number of autosomal loci show that if there was a bottleneck then subsequent gene flow from Europeans must have been very large, obliterating the effects of any bottleneck. The clustering of the disorders in only a few pathways and the presence at elevated frequency of more than one deleterious allele at many of them could not have been produced by drift. Instead these are signatures of strong and recent natural selection.

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This paper presents an adaptive Gaussian Mixture Model (aGMM) formulation for performing multiple-step probabilistic state predictions using a nonparametric Gaussian Process (GP) regression model. The presented prediction algorithm is applicable to any dynamic system that is challenging to model parametrically, but where data is available. Gaussian mixture elements are propagated through the GP by analytically evaluating expectation integrals for the moments of the output distribution. Two metrics are presented and compared for adaptively splitting the initial state distribution into a sum of Gaussians to reduce the effect of nonlinearities on prediction accuracy: (1) an analytical evaluation of the excess kurtosis which measures the non-Gaussianity of the output distribution, and (2) a weighted least-squares regression model which evaluates the local nonlinearity of the GP mapping with respect to the input distribution. In addition, an on-the-fly data selection method is presented to reduce the computational complexity associated with analytically evaluating the higher-order moments of the GP output distribution. The proposed adaptive GP-aGMM formulation is applied to the case of anticipating driver behavior at road intersections using a GP driver behavior model in combination with a parametric vehicle model. Prediction performance for this scenario is evaluated using driving data collected from three human subjects navigating a standard four-way intersection. Results demonstrate that the presented prediction algorithm is capable of accurately capturing multimodal behavior in the GP training data.

Summary In the present study, we have investigated the molecular structure and biosynthesis during development of the donkey capsule, which replaces the zona pellucida and envelops the conceptus during the 2nd and 3rd weeks of gestation, before uterine attachment, and compared it with that of the horse. Amino acid analysis of capsules from accurately aged donkey conceptuses indicated that the polypeptide backbone of the constituent glycoproteins was very similar in both species. Carbohydrate analysis and lectin histochemical staining showed that, as in the horse, the major sugars present were sialic acid, N‐acetylgalactosamine and galactose. However, the donkey capsule contained substantially lower amounts of sialic acid. Removal of the covalently‐bound O‐linked carbohydrate by β‐elimination indicated that the donkey capsule resembles that of the horse in being O‐glycosylated mainly on threonine residues. The dry masses of donkey capsules remained low between Days 8.5 and 11.5, and increased rapidly with blastocyst expansion up to Day 17.5, as in the horse. However, the maximum capsular weight attained in the donkey (2.5 mg) was only half that of the horse and the decline in capsule weight up to Day 22.5, shortly before its disappearance, was steeper and occurred earlier. A monoclonal antibody (OC‐1), which reacts with a developmentally regulated epitope in the horse capsule, cross‐reacted strongly with both the capsule and trophoblast in frozen sections of donkey conceptuses. The differences in OC‐1‐reactive antigen expression in the donkey trophoblast mirrored those observed for the increase in capsular dry mass. The biochemical and developmental similarities observed between the capsule of the donkey and the horse suggest that this structure has been highly conserved in equids.