Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Genetic determinants of glucose-6-phosphate dehydrogenase activity in Kenya

Background: The relationship between glucose-6-phosphate dehydrogenase (G6PD) deficiency and clinical phenomena such as primaquine-sensitivity and protection from severe malaria remains poorly defined, with past association studies yielding inconsistent and conflicting results. One possibility is that examination of a single genetic variant might underestimate the presence of true effects in the presence of unrecognized functional allelic diversity. Methods: We systematically examined this possibility in Kenya, conducting a fine-mapping association study of erythrocyte G6PD activity in 1828 Kenyan children across 30 polymorphisms at or around the G6PD locus. Results: We demonstrate a strong functional role for c.202G>A (rs1050828), which accounts for the majority of variance in enzyme activity observed (P=1.5 × 10-200, additive model). Additionally, we identify other common variants that exert smaller, intercorrelated effects independent of c.202G>A, and haplotype analyses suggest that each variant tags one of two haplotype motifs that are opposite in sequence identity and effect direction. We posit that these effects are of biological and possible clinical significance, specifically noting that c.376A>G (rs1050829) augments 202AG heterozygote risk for deficiency trait by two-fold (OR = 2.11 [1.12 - 3.84], P=0.014). Conclusions: Our results suggest that c.202G>A is responsible for the majority of the observed prevalence of G6PD deficiency trait in Kenya, but also identify a novel role for c.376A>G as a genetic modifier which marks a common haplotype that augments the risk conferred to 202AG heterozygotes, suggesting that variation at both loci merits consideration in genetic association studies probing G6PD deficiency-associated clinical phenotypes. </p

Higher education and unemployment in Europe : an analysis of the academic subject and national effects

This paper examines the impact of an academic degree and field of study on short and long-term unemployment across Europe (EU15). Labour Force Survey (LFS) data on over half a million individuals are utilised for that purpose. The harmonized LFS classification of level of education and field of study overcomes past problems of comparability across Europe. The study analyses (i) the effect of an academic degree at a European level, (ii) the specific effect of 14 academic subjects and (iii) country specific effects. The results indicate that an academic degree is more effective on reducing the likelihood of short-term than long-term unemployment. This general pattern even though it is observed for most of the academic subjects its levels show significant variation across disciplines and countries

Agricultural land use disrupts biodiversity mediation of virus infections in wild plant populations

Human alteration of natural habitats may change the processes governing species interactions in wild communities. Wild populations are increasingly impacted by agricultural intensification, yet it is unknown whether this alters biodiversity mediation of disease dynamics. We investigated the association between plant diversity (species richness, diversity) and infection risk (virus richness, prevalence) in populations of Plantago lanceolata in natural landscapes as well as those occurring at the edges of cultivated fields. Altogether, 27 P. lanceolata populations were surveyed for population characteristics and sampled for PCR detection of five recently characterized viruses. We find that plant species richness and diversity correlated negatively with virus infection prevalence. Virus species richness declined with increasing plant diversity and richness in natural populations while in agricultural edge populations species richness was moderately higher, and not associated with plant richness. This difference was not explained by changes in host richness between these two habitats, suggesting potential pathogen spill‐over and increased transmission of viruses across the agro‐ecological interface. Host population connectivity significantly decreased virus infection prevalence. We conclude that human use of landscapes may change the ecological laws by which natural communities are formed with far reaching implications for ecosystem functioning and disease

Bayesian Generalized Probability Calculus for Density Matrices

One of the main concepts in quantum physics is a density matrix, which is a symmetric positive definite matrix of trace one. Finite probability distributions can be seen as a special case when the density matrix is restricted to be diagonal. We develop a probability calculus based on these more general distributions that includes definitions of joints, conditionals and formulas that relate these, including analogs of the Theorem of Total Probability and various Bayes rules for the calculation of posterior density matrices. The resulting calculus parallels the familiar "conventional" probability calculus and always retains the latter as a special case when all matrices are diagonal. We motivate both the conventional and the generalized Bayes rule with a minimum relative entropy principle, where the Kullbach-Leibler version gives the conventional Bayes rule and Umegaki's quantum relative entropy the new Bayes rule for density matrices. Whereas the conventional Bayesian methods maintain uncertainty about which model has the highest data likelihood, the generalization maintains uncertainty about which unit direction has the largest variance. Surprisingly the bounds also generalize: as in the conventional setting we upper bound the negative log likelihood of the data by the negative log likelihood of the MAP estimator

Experience of a Preventive Experiment : Spatial Social Mixing in Post-World War II Housing Estates in Helsinki, Finland

The contingent of large housing estates built in the 1960s and 1970s accounts for almost a half of all high-rises in Finland. The primary ideology in their genesis was to combine industrially prefabricated urban housing development with the surrounding forest landscape—together with a policy of spatial social mixing—to prevent social disorder and segregation. These policies seemed to work as intended until the early 1990s, but have since proved to be insufficient. With Western integration and new information and communication-based economic growth, new trends of population differentiation have emerged. As new wealth has moved out to the fringes of cities, the large housing estates have declined socio-economically—and have been enriched ethnically. This differentiation is structurally produced, works through the regional housing market and, as such, is beyond the scope of the preventive policies pursued. Recent attempts at controlling the regional markets and new forms of spatial social mixing have so far proved difficult.The contingent of large housing estates built in the 1960s and 1970s accounts for almost a half of all high-rises in Finland. The primary ideology in their genesis was to combine industrially prefabricated urban housing development with the surrounding forest landscape—together with a policy of spatial social mixing—to prevent social disorder and segregation. These policies seemed to work as intended until the early 1990s, but have since proved to be insufficient. With Western integration and new information and communication-based economic growth, new trends of population differentiation have emerged. As new wealth has moved out to the fringes of cities, the large housing estates have declined socio-economically—and have been enriched ethnically. This differentiation is structurally produced, works through the regional housing market and, as such, is beyond the scope of the preventive policies pursued. Recent attempts at controlling the regional markets and new forms of spatial social mixing have so far proved difficult.Peer reviewe