Applying Bayesian model averaging for uncertainty estimation of input data in energy modelling

Background Energy scenarios that are used for policy advice have ecological and social impact on society. Policy measures that are based on modelling exercises may lead to far reaching financial and ecological consequences. The purpose of this study is to raise awareness that energy modelling results are accompanied with uncertainties that should be addressed explicitly. Methods With view to existing approaches of uncertainty assessment in energy economics and climate science, relevant requirements for an uncertainty assessment are defined. An uncertainty assessment should be explicit, independent of the assessor’s expertise, applicable to different models, including subjective quantitative and statistical quantitative aspects, intuitively understandable and be reproducible. Bayesian model averaging for input variables of energy models is discussed as method that satisfies these requirements. A definition of uncertainty based on posterior model probabilities of input variables to energy models is presented. Results The main findings are that (1) expert elicitation as predominant assessment method does not satisfy all requirements, (2) Bayesian model averaging for input variable modelling meets the requirements and allows evaluating a vast amount of potentially relevant influences on input variables and (3) posterior model probabilities of input variable models can be translated in uncertainty associated with the input variable. Conclusions An uncertainty assessment of energy scenarios is relevant if policy measures are (partially) based on modelling exercises. Potential implications of these findings include that energy scenarios could be associated with uncertainty that is presently neither assessed explicitly nor communicated adequately

Uncertainty analysis using Bayesian Model Averaging: a case study of input variables to energy models and inference to associated uncertainties of energy scenarios

Background Energy models are used to illustrate, calculate and evaluate energy futures under given assumptions. The results of energy models are energy scenarios representing uncertain energy futures. Methods The discussed approach for uncertainty quantification and evaluation is based on Bayesian Model Averaging for input variables to quantitative energy models. If the premise is accepted that the energy model results cannot be less uncertain than the input to energy models, the proposed approach provides a lower bound of associated uncertainty. The evaluation of model-based energy scenario uncertainty in terms of input variable uncertainty departing from a probabilistic assessment is discussed. Results The result is an explicit uncertainty quantification for input variables of energy models based on well-established measure and probability theory. The quantification of uncertainty helps assessing the predictive potential of energy scenarios used and allows an evaluation of possible consequences as promoted by energy scenarios in a highly uncertain economic, environmental, political and social target system. Conclusions If societal decisions are vested in computed model results, it is meaningful to accompany these with an uncertainty assessment. Bayesian Model Averaging (BMA) for input variables of energy models could add to the currently limited tools for uncertainty assessment of model-based energy scenarios

The Aims of Lifelong Learning: Age-Related Effects of Training on Wages and Job Security

This study analyses the effects of training participation on wages and perceived job security for employees of different ages. Based on data from the German Socio-Economic Panel, results indicate that only younger workers benefit from training by an increase in wages, whereas older employees' worries about losing their job are reduced. This observation can also be explained by the fact that goals of training courses are related to the age of participants. Moreover, I differentiate between workers who permanently and only occasionally participate in training. The results indicate that there seem to be decreasing marginal returns to training with respect to job security

The Making of Racial and Ethnic Categories: Official Statistics Reconsidered

One of the most striking features of the end of the twentieth century was the resurgence of the ethnic question in public debates, both in developing and in developed countries. Between conflicts and wars interpreted from an ethnic perspective (the Balkans and central Africa), nationalist struggles (the Basque country, Quebec and Belgium), and demands for recognition and political representation by new ethnic minorities resulting from immigration, every country is currently affected by what is commonly known as cultural pluralism (Hobsbawm 1993; Dieckhoff 2000; Faist 2009; Simon and Piché 2013). This ‘ethnic renewal’, to coin the expression used to qualify the growing interest for ethnic diversity in the 1960s in the US, is not only driven by a sort of obsession for cultural differences as an explanation for all kinds of social and political phenomenon. It derives from different legacies: from the increasing diversity of the population of countries that have undergone large immigration flows to the long lasting cohabitation of national minorities within modern Nation states, from the history of slavery to the post-colonial era. This resurgence or extension of the salience of ethnicity in most of the societies around the world can be found not only in public discourses, policy-making, scientific literature and popular representations, but also in the pivotal realm of statistics. Indeed, at the turn of century, an increasing number of countries are processing routinely data on ethnicity or race of their population. This is precisely what this book is about: ethnic and racial classifications in official statistics, as a reflection of the representations of population and an interpretation of social dynamics through different lenses

The Restriction of Zoonotic PERV Transmission by Human APOBEC3G

The human APOBEC3G protein is an innate anti-viral factor that can dominantly inhibit the replication of some endogenous and exogenous retroviruses. The prospects of purposefully harnessing such an anti-viral defense are under investigation. Here, long-term co-culture experiments were used to show that porcine endogenous retrovirus (PERV) transmission from pig to human cells is reduced to nearly undetectable levels by expressing human APOBEC3G in virus-producing pig kidney cells. Inhibition occurred by a deamination-independent mechanism, likely after particle production but before the virus could immortalize by integration into human genomic DNA. PERV inhibition did not require the DNA cytosine deaminase activity of APOBEC3G and, correspondingly, APOBEC3G-attributable hypermutations were not detected. In contrast, over-expression of the sole endogenous APOBEC3 protein of pigs failed to interfere significantly with PERV transmission. Together, these data constitute the first proof-of-principle demonstration that APOBEC3 proteins can be used to fortify the innate anti-viral defenses of cells to prevent the zoonotic transmission of an endogenous retrovirus. These studies suggest that human APOBEC3G-transgenic pigs will provide safer, PERV-less xenotransplantation resources and that analogous cross-species APOBEC3-dependent restriction strategies may be useful for thwarting other endogenous as well as exogenous retrovirus infections

Synergistic inhibition of APC/C by glucose and activated Ras proteins can be mediated by each of the Tpk1-3 proteins in Saccharomyces cerevisiae

Proteolysis triggered by the anaphase-promoting complex/cyclosome (APC/C) is essential for the progression through mitosis. APC/C is a highly conserved ubiquitin ligase whose activity is regulated during the cell cycle by various factors, including spindle checkpoint components and protein kinases. The cAMP-dependent protein kinase (PKA) was identified as negative regulator of APC/C in yeast and mammalian cells. In the yeast Saccharomyces cerevisiae, PKA activity is induced upon glucose addition or by activated Ras proteins. This study shows that glucose and the activated Ras2(Val19) protein synergistically inhibit APC/C function via the cAMP/PKA pathway in yeast. Remarkably, Ras2 proteins defective in the interaction with adenylate cyclase fail to influence APC/C, implying that its function is regulated exclusively by PKA, but not by alternative Ras pathways. Furthermore, it is shown that the three PKAs in yeast, Tpk1, Tpk2 and Tpk3, have redundant functions in regulating APC/C in response to glucose medium. Single or double deletions of TPK genes did not prevent inhibition of APC/C, suggesting that each of the Tpk proteins can take over this function. However, Tpk2 seems to inhibit APC/C function more efficiently than Tpk1 and Tpk3. Finally, evidence is provided that Cdc20 is involved in APC/C regulation by the cAMP/PKA pathway