4 resultados para dominating set

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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This paper provides a model for the international market of credit ratings in order to promote transparency of rating methodologies and combat the oligopolistic market structure where Standard & Poor‘s, Moody‘s and Fitch Ratings collectively comprise approximately 85 percent of the market. For the German credit market this paper strongly advises the establishment of at least three centralistic credit rating agencies (CRAs), set up and run independently by the large bank institutions – „Großbanken“, „Sparkassen“ and „Genossenschaftsbanken“. By acting as CRAs, universal banks could not only decrease their costs but would also be able to increase competition and transparency. These new credit rating agencies would be subject to the Basel II internal ratings-based (IRB) surveillance standards that go far beyond the Basel II standard approach with its external ratings by the dominating three US-american CRAs. Due to the fact that the new Basle Accord has already been implemented in Europe, this model could be applied all over Europe and possibly even worldwide, assuming the US were to adopt the new capital adequacy rules. This would lead to an increase in the number of CRAs and hence to more competition, as the barriers to entry in the rating industry would not apply to these new institutions because of their expertise in the credit market. The fact that the IRB-criteria already have to be disclosed by law would make the methodologies transparent and subject to approval by national regulators such as the „Bundesanstalt für Finanzdienstleistungsaufsicht“ (BaFin) in Germany. Hence the requirement to set up a new monitoring committee in Europe would become obsolete.

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A fully relativistic four-component Dirac-Fock-Slater program for diatomics, with numerically given AO's as basis functions is presented. We discuss the problem of the errors due to the finite basis-set, and due to the influence of the negative energy solutions of the Dirac Hamiltonian. The negative continuum contributions are found to be very small.

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Moringa oleifera is becoming increasingly popular as an industrial crop due to its multitude of useful attributes as water purifier, nutritional supplement and biofuel feedstock. Given its tolerance to sub-optimal growing conditions, most of the current and anticipated cultivation areas are in medium to low rainfall areas. This study aimed to assess the effect of various irrigation levels on floral initiation, flowering and fruit set. Three treatments namely, a 900 mm (900IT), 600 mm (600IT) and 300 mm (300IT) per annum irrigation treatment were administered through drip irrigation, simulating three total annual rainfall amounts. Individual inflorescences from each treatment were tagged during floral initiation and monitored throughout until fruit set. Flower bud initiation was highest at the 300IT and lowest at the 900IT for two consecutive growing seasons. Fruit set on the other hand, decreased with the decrease in irrigation treatment. Floral abortion, reduced pollen viability as well as moisture stress in the style were contributing factors to the reduction in fruiting/yield observed at the 300IT. Moderate water stress prior to floral initiation could stimulate flower initiation, however, this should be followed by sufficient irrigation to ensure good pollination, fruit set and yield.

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Background: The most common application of imputation is to infer genotypes of a high-density panel of markers on animals that are genotyped for a low-density panel. However, the increase in accuracy of genomic predictions resulting from an increase in the number of markers tends to reach a plateau beyond a certain density. Another application of imputation is to increase the size of the training set with un-genotyped animals. This strategy can be particularly successful when a set of closely related individuals are genotyped. ----- Methods: Imputation on completely un-genotyped dams was performed using known genotypes from the sire of each dam, one offspring and the offspring’s sire. Two methods were applied based on either allele or haplotype frequencies to infer genotypes at ambiguous loci. Results of these methods and of two available software packages were compared. Quality of imputation under different population structures was assessed. The impact of using imputed dams to enlarge training sets on the accuracy of genomic predictions was evaluated for different populations, heritabilities and sizes of training sets. ----- Results: Imputation accuracy ranged from 0.52 to 0.93 depending on the population structure and the method used. The method that used allele frequencies performed better than the method based on haplotype frequencies. Accuracy of imputation was higher for populations with higher levels of linkage disequilibrium and with larger proportions of markers with more extreme allele frequencies. Inclusion of imputed dams in the training set increased the accuracy of genomic predictions. Gains in accuracy ranged from close to zero to 37.14%, depending on the simulated scenario. Generally, the larger the accuracy already obtained with the genotyped training set, the lower the increase in accuracy achieved by adding imputed dams. ----- Conclusions: Whenever a reference population resembling the family configuration considered here is available, imputation can be used to achieve an extra increase in accuracy of genomic predictions by enlarging the training set with completely un-genotyped dams. This strategy was shown to be particularly useful for populations with lower levels of linkage disequilibrium, for genomic selection on traits with low heritability, and for species or breeds for which the size of the reference population is limited.