Debunking The Hellenistic Myth: Why Christians Should Believe That God Is In Time

In this essay I will try to convince you: (1) that the question of God’s relation to time is of practical relevance for every believer (2) that the idea of God being outside time is a philosophically untenable concept which creates major clashes with Christian doctrine and therefore that every Christian should adopt some temporalist view of God To do that, I will present four arguments against the “outside time” view of God. I then briefly treat the question where the idea of God’s timelessness presumably came from and conclude with an outlook on problems that temporalist accounts of God must face

Sharing extended summary data from contemporary genetics studies is unlikely to threaten subject privacy

Background Starting from a forensic problem, Homer et al. showed that it was possible to detect if an individual contributes only 0.5% of the DNA in a pool. The finding was extended to prove the possibility of detecting whether a subject participated in a small homogeneous GWAS. We denote this as the detection of a subject belonging to a certain cohort (SBCC). Subsequently, Visscher and Hill showed that the power to detect SBCC signal for an ethnically homogeneous cohort depends roughly on the ratio of the number of independent markers and total sample size. However, it is not clear if the same holds for more ethnically diverse cohorts. Later, Masca et al. propose running as SBCC test a regression of departure from assumed population frequency of i) subject genotype on ii) cohort of interest frequency. They use simulations to show that the approach has better SBCC detection power than the original Homer method but is impeded by population stratification. Approach To investigate the possibility of SBCC detection in multi-ethnic cohorts, we generalize the Masca et al. approach by theoretically deriving the correlation between a subject genotype and the cohort reference allele frequencies (RAFs) for stratified cohorts. Based on the derived formula, we theoretically show that, due to background stratification noise, SBCC detection is unlikely even for mildly stratified cohorts of size greater than around a thousand subjects. Thus, for the vast majority of contemporary cohorts, the fear of compromising privacy via SBCC detection is unfounded

Complexity Estimates for Two Uncoupling Algorithms

Uncoupling algorithms transform a linear differential system of first order into one or several scalar differential equations. We examine two approaches to uncoupling: the cyclic-vector method (CVM) and the Danilevski-Barkatou-Z\"urcher algorithm (DBZ). We give tight size bounds on the scalar equations produced by CVM, and design a fast variant of CVM whose complexity is quasi-optimal with respect to the output size. We exhibit a strong structural link between CVM and DBZ enabling to show that, in the generic case, DBZ has polynomial complexity and that it produces a single equation, strongly related to the output of CVM. We prove that algorithm CVM is faster than DBZ by almost two orders of magnitude, and provide experimental results that validate the theoretical complexity analyses.Comment: To appear in Proceedings of ISSAC'13 (21/01/2013

THE LONG-RUN DETERMINANTS OF INVESTMENT: A DYNAMIC APPROACH FOR THE FUTURE ECONOMIC POLICIES

Investment is the sum of the purchases on newly produced capital, changes in business inventories referred to as inventory investment, and the purchases of new residential housing. The work covered by this study aims to identify the model that presents, in the best possible way, the method of investment’s calculation and to determine the factors of influence. In the first part, the investment is analyzed as a linear function dependent on the interest rate; and the second part implies a new model for determining long-term investments, but also an identification of the measures that would lead to increased investments.investment, interest rate, tax rate, fiscal policy