Sufficient Scope in Current Aircraft Technology Developments?

Air travel demand is growing worldwide with an approximate worldwide long term average of 5 to 6% annually. This growth has both very positive and negative effects. Aviation is deeply embedded in our society. Dramatic decrease in ticket prices has brought to many the possibility of reaching many destinations worldwide in a day’s travel. It is claimed by some that the negative effects – such as noise pollution and greenhouse gas emissions - will not become more problematic in the future, because technologies are being developed that will compensate them. The starting point of this research is to discover whether this claim concerning the potential of current aircraft technology developments is true. In other words: is the current development in aircraft technology capable to contribute to a sustainable development in the aviation sector by keeping current positive effects, while mitigating the negative effects? Existing research on this issue is mostly trend research, focussing at the average technology efficiency increase and extrapolating this to the future. In a context where multiple actors have to decide about what to do, this extrapolation is not enough. An aggregated number does not reveal the concrete options and causal relations behind it. This paper, therefore, introduces the open and explicit method of systems analysis to answer the question if (and if so, how) new aircraft technology can mitigate the adverse effects of an increasing air travel demand, while keeping the benefits. It presents analytical results in terms of numbers and score cards in order to feed the policy process that eventually should lead to policy in order to solve the problem. In light of the results of the systems analysis, this paper concludes that current developments in aircraft technology are not sufficient to mitigate the adverse effects of growth. Our research suggests that the combination of the efficiency improvement rate, the growth rate of the demand for air travel, and the long replacement times for older technology do in fact not cancel each other out. In order to achieve a sustainable development in the aviation sector, this systems analysis approach shows the limited (though important) influence technology can have on the full concept of sustainable development. We suggest to not only invest more into developing ever better technologies, but to also search for non-technical solutions in order to address the full concept of sustainable development

Special Editorial Issue EJTIR

Globalisation and economic growth have led to aviation’s deep incorporation into our society. People and goods can be transported almost anywhere on the globe in a relatively short time and at relatively low prices. The rate of growth in air traffic demand has for decades been higher than that of the world economy. As world population increases, economic growth and ongoing globalisation are expected to continue fuelling air traffic’s explosive growth (Walker et al, 2008). As a result the large aircraft manufacturers in the world, Airbus and Boeing, specify in their market forecast annual growth percentages of around 5 to 6%. Since late 2008, the economic crisis has significantly reduced the demand for aviation (IATA, 2008; 2009). However, most authors consider this slowdown to be but temporary. In many occasions in the past, aviation demand growth curbed but growth figures always relatively quickly recovered picking up the growth lines followed before the crisis. The latest occasion has been the recovery in 2004 from the period of stagnation following the attacks on the World Trade Centre in New York City in 2001. In the majority of designed future scenarios for air traffic, the increasing demand for air traffic is expected to continue. This continuing growth will have some valuable effects, but also some drawbacks

Mach-Zehnder fiber interferometer test of the anisotropy of the speed of light

Two optical fiber Mach-Zehnder interferometers were constructed in an environment with a temperature stabilization of better than 1 mK per day. One interferometer with a length of 12 m optical fiber in each arm with the main direction of the arms perpendicular to each other. Another with a length of 2 m optical fiber in each arm where the main direction of the arms are parallel as a control. In each arm 1 m of fiber was wound around a ring made of piezo material enabling the control of the length of the arms by means of a voltage. The influence of the temperature on the optical phase difference between the interferometer arms was measured. It is attributed to the temperature change induced variation of the interaction region of the optical fiber couplers. Further, the influence of rotation of the interferometers at the Earth surface on the observed phase differences was determined. For one interferometer (with the long and perpendicular arms) it was found that the phase difference depends on the azimuth of the interferometer. For the other one (with the short and parallel arms) no relevant dependence on the azimuth has been measured.Comment: Errata: data of interferometers were interchange

Timing of Banks' Loan Loss Provisioning During the Crisis

We estimate a panel error correction model for loan loss provisions, using unique supervisory data on flow of funds into and out of the allowance for loan losses of 25 Dutch banks in the post-2008 crisis period. We find that these banks aim for an allowance of 49% of impaired loans. In the short run, however, the adjustment of the allowance is only 29% of the change in impaired loans. The deviation from the target is made up by (a) larger additions to allowances in subsequent quarters and (b) smaller reversals of allowances when loan losses do not materialize. After one quarter, the adjustment toward the target level is 34% and after four quarters is 81%. For individual banks, there are substantial differences in timing of provisioning for bad loan losses. We present two model-based metrics that inform supervisors on the extent to which banks' short-term provisioning behaviour is out of sync with their target levels

WormQTL HD—a web database for linking human disease to natural variation data in C. elegans

Interactions between proteins are highly conserved across species. As a result, the molecular basis of multiple diseases affecting humans can be studied in model organisms that offer many alternative experimental opportunities. One such organism— Caenorhabditis elegans—has been used to produce much molecular quantitative genetics and systems biology data over the past decade. We present WormQTLHD (Human Disease), a database that quantitatively and systematically links expression Quantitative Trait Loci (eQTL) findings in C. elegans to gene–disease associations in man. WormQTLHD, available online at http://www.wormqtl-hd.org, is a user-friendly set of tools to reveal functionally coherent, evolutionary conserved gene networks. These can be used to predict novel gene-to-gene associations and the functions of genes underlying the disease of interest. We created a new database that links C. elegans eQTL data sets to human diseases (34 337 gene–disease associations from OMIM, DGA, GWAS Central and NHGRI GWAS Catalogue) based on overlapping sets of orthologous genes associated to phenotypes in these two species. We utilized QTL results, high-throughput molecular phenotypes, classical phenotypes and genotype data covering different developmental stages and environments from WormQTL database. All software is available as open source, built on MOLGENIS and xQTL workbench

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)