Alternative indices of political freedoms, property rights, and political instability for Zambia

This paper presents new institutional measures for Zambia. Coverage is of political rights and freedoms, of property rights, and of political instability. The sample period is from 1947 to 2007. Comparison of the indices with directly comparable Zimbabwean and Malawian series, shows strong sources of divergence in institutional conditions. The paper also considers interaction amongst the institutional measures, and between the institutional measures and measures of economic development. We find that there is an association among the institutional variables, with the various rights dimensions moving together, and being negatively associated with political instability. The evidence further suggests that the institutional measures are associated benevolently with economic development. In this sense the indicators of the present paper therefore conform to the precepts of the new institutional economicsInstitutions, Political freedom, Property rights, Political Instability and Zambia

Traceability for Model Driven, Software Product Line Engineering

Traceability is an important challenge for software organizations. This is true for traditional software development and even more so in new approaches that introduce more variety of artefacts such as Model Driven development or Software Product Lines. In this paper we look at some aspect of the interaction of Traceability, Model Driven development and Software Product Line

Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle.

Background: Single-step genomic best linear unbiased prediction (SSGBLUP) is a comprehensive method for genomic prediction. Point estimates of marker effects from SSGBLUP are often used for genome-wide association studies (GWAS) without a formal framework of hypothesis testing. Our objective was to implement p-values for singlemarker GWAS studies within the single-step GWAS (SSGWAS) framework by deriving computational algorithms and procedures, and by applying these to a large beef cattle population. Methods: P-values were obtained based on the prediction error (co)variances for single nucleotide polymorphisms (SNPs), which were obtained from the prediction error (co)variances of genomic predictions based on the inverse of the coefficient matrix and formulas to estimate SNP effects. Results: Computation of p-values took a negligible time for a dataset with almost 2 million animals in the pedigree and 1424 genotyped sires, and no inflation of statistics was observed. The SNPs that passed the Bonferroni threshold of 10-5.9 were the same as those that explained the highest proportion of additive genetic variance, but even at the same significance levels and effects, some of them explained less genetic variance due to lower allele frequency. Conclusions: The use of a p-value for SSGWAS is a very general and efficient strategy to identify quantitative trait loci (QTL). It can be used for complex datasets such as those used in animal breeding, where only a proportion of the pedigreed animals are genotyped

Temperature dependence of the electron spin g factor in GaAs

The temperature dependence of the electron spin $g$ factor in GaAs is investigated experimentally and theoretically. Experimentally, the $g$ factor was measured using time-resolved Faraday rotation due to Larmor precession of electron spins in the temperature range between 4.5 K and 190 K. The experiment shows an almost linear increase of the $g$ value with the temperature. This result is in good agreement with other measurements based on photoluminescence quantum beats and time-resolved Kerr rotation up to room temperature. The experimental data are described theoretically taking into account a diminishing fundamental energy gap in GaAs due to lattice thermal dilatation and nonparabolicity of the conduction band calculated using a five-level kp model. At higher temperatures electrons populate higher Landau levels and the average $g$ factor is obtained from a summation over many levels. A very good description of the experimental data is obtained indicating that the observed increase of the spin $g$ factor with the temperature is predominantly due to band's nonparabolicity.Comment: 6 pages 4 figure