Living on the water : a social innovation approach to flood adaptation planning in the river basin Eferding, Austria

In the summer of 2013, devastating floods caused heavy damage along various streams in central Europe. In the river basin Eferding in Austria, the Danube River reached record water levels and flooded hundreds of homes in the low-lying areas over night. The response of the government to resettle people has been heavily criticized by a local citizen initiative, leading to protests in front of the regional parliament. The demand for alternative solutions and for answers to the many questions to the cause of the extraordinary impact of the flood have been growing. The aim of this study is to analyze people’s attitudes towards social innovation thinking in the context of flood planning and to discuss the benefits of the concept of social innovation in this particular case. In such situations, according to the concept of social innovation, solutions that meet unmet needs of society and create new capabilities and better use of resources can occur. In search for resilient ways to adapt to the risk of floods, through a participatory action research approach, I engage with the local citizens and other stakeholders by simulating the idea creation process of social innovation. In a short video distributed via social media, I introduce a new way of living in the flood area. Subsequently, using a survey I assess people’s reaction towards the innovation presented in the video. The results show a great potential for change: people are highly receptive to rethinking flood adaptation and their way of living in the flood zone. Compassion is strong far beyond the immediately affected citizens, which advocates for more active involvement of many more people in order to shape the innovation to meet all stakeholders’ needs. However, as the topic splits the opinion of locals and the government, politics tends to impede the process. The use of the video and social media has proven highly efficient in breaking down barriers of communication: the complexity of the subject could be presented in an easily understandable way; social media provided a perfect platform for discussion and involving people. The study shows that people perceive innovation thinking rather positively. I therefore advocate for a more active use of the concept in similar complex contexts

Fine-Tuning Nonhomogeneous Regression for Probabilistic Precipitation Forecasts: Unanimous Predictions, Heavy Tails, and Link Functions

Raw ensemble forecasts of precipitation amounts and their forecast uncertainty have large errors, especially in mountainous regions where the modeled topography in the numerical weather prediction model and real topography differ most. Therefore, statistical postprocessing is typically applied to obtain automatically corrected weather forecasts. This study applies the nonhomogenous regression framework as a state-of-the-art ensemble postprocessing technique to predict a full forecast distribution and improves its forecast performance with three statistical refinements. First of all, a novel split-type approach effectively accounts for unanimous zero precipitation predictions of the global ensemble model of the ECMWF. Additionally, the statistical model uses a censored logistic distribution to deal with the heavy tails of precipitation amounts. Finally, it is investigated which are the most suitable link functions for the optimization of regression coefficients for the scale parameter. These three refinements are tested for 10 stations in a small area of the European Alps for lead times from +24 to +144 h and accumulation periods of 24 and 6 h. Together, they improve probabilistic forecasts for precipitation amounts as well as the probability of precipitation events over the default postprocessing method. The improvements are largest for the shorter accumulation periods and shorter lead times, where the information of unanimous ensemble predictions is more important. </jats:p

An intergenic non-coding RNA targets and regulates the ribosome in H. volcanii.

As translation is the final step in gene expression it is particularly important to understand the processes involved in translation regulation. It was shown in the last years that a class of RNA, the nonprotein-coding RNAs (ncRNAs), is involved in regulation of gene expression via various mechanisms (e.g. gene silencing by microRNAs). Almost all of these ncRNA discovered so far target the mRNA in order to modulate protein biosynthesis, this is rather unexpected considering the crucial role of the ribosome during gene expression. However, recent data from our laboratory showed that there is a new class of ncRNAs, which target the ribosome itself [Gebetsberger et al., 2012/ Pircher et al, 2014]. These so called ribosome-associated ncRNAs (rancRNAs) have an impact on translation regulation, mainly by interfering / modulating the rate of protein biosynthesis. The main goal of this project is to identify and describe novel potential regulatory rancRNAs in H. volcanii with the focus on intergenic candidates. Northern blot analyses already revealed interactions with the ribosome and showed differential expression of rancRNAs during different growth phases or under specific stress conditions. To investigate the biological relevance of these rancRNAs, knock-outs were generated in H. volcanii which were used for phenotypic characterization studies. The rancRNA s194 showed association with the 50S ribosomal subunit in vitro and in vivo and was capable of inhibiting peptide bond formation. These preliminary data for the rancRNA s194 make it an interesting candidate for further functional studies to identify the molecular mechanisms by which rancRNAs can modulate protein biosynthesis. Characterization of further rancRNA candidates are also underway

cDNA Library Generation for the Analysis of Small RNAs by High-Throughput Sequencing

The RNome of a cell is highly diverse and consists besides messenger RNAs (mRNAs), transfer RNAs (tRNAs), and ribosomal RNAs (rRNAs) also of other small and long transcript entities without apparent coding potential. This class of molecules, commonly referred to as non-protein-coding RNAs (ncRNAs), is involved in regulating numerous biological processes and thought to contribute to cellular complexity. Therefore, much effort is put into their identification and further functional characterization. Here we provide a cost-effective and reliable method for cDNA library construction of small RNAs in the size range of 20-500 residues. The effectiveness of the described method is demonstrated by the analysis of ribosome-associated small RNAs in the eukaryotic model organism Trypanosoma brucei

Consequential considerations when mapping tRNA fragments

We examine several of the choices that went into the design of tDRmapper, a recently reported tool for identifying transfer RNA (tRNA) fragments in deep sequencing data, evaluate them in the context of currently available knowledge, and discuss their potential impact on the output that the tool generates

The Chern-Simons current in systems of DNA-RNA transcriptions

A Chern-Simons current, coming from ghost and anti-ghost fields of supersymmetry theory, can be used to define a spectrum of gene expression in new time series data where a spinor field, as alternative representation of a gene, is adopted instead of using the standard alphabet sequence of bases $A, T, C, G, U$. After a general discussion on the use of supersymmetry in biological systems, we give examples of the use of supersymmetry for living organism, discuss the codon and anti-codon ghost fields and develop an algebraic construction for the trash DNA, the DNA area which does not seem active in biological systems. As a general result, all hidden states of codon can be computed by Chern-Simons 3 forms. Finally, we plot a time series of genetic variations of viral glycoprotein gene and host T-cell receptor gene by using a gene tensor correlation network related to the Chern-Simons current. An empirical analysis of genetic shift, in host cell receptor genes with separated cluster of gene and genetic drift in viral gene, is obtained by using a tensor correlation plot over time series data derived as the empirical mode decomposition of Chern-Simons current.Comment: 45 pages, 30 figures, 2 table

Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons

The spatiotemporal inhomogeneity of the total column NO2 amounts (TCN) in the Seoul Metropolitan Area (SMA), Korea, was quantitatively assessed through year-round (October 2019-May 2021) TROPOMI and ground-based Pandora measurements. The average TCN over the SMA was comparable to that of major Chinese megacities, being consistently high (&gt; 0.8 DU; Dobson Unit) during the daytime (10-17 local standard time). The autocorrelation scores of the Pandorameasured TCNs demonstrated high temporal variability attributed to the spatial inhomogeneity of NO2 emissions within the SMA and near-surface advection. Accordingly, the adequate temporal collocation range for Pandora measurements for the intercomparison with the satellite sensors was considered to be +/- 5 min to avoid significant uncertainty from the temporal variability (RMSE &lt; 0.1 DU, R-2 &gt; 0.96). TROPOMI showed better agreement with conventionally collocated Pandora measurements (0.73 &lt; R-2 &lt; 0.76, 26-29% negative bias) than the other two satellite sensors (OMI and OMPS) attributed to its highest spatial resolution. The application of the wind-based collocation revealed that the TROPOMI showed a greater negative bias on the upwind side, which was less affected by anthropogenic emissions from the urban area, than the downwind side, and the increasing distance of the TROPOMI pixel from Pandora was the most critical factor deteriorating the intercomparison scores. The FRESCO-S TROPOMI cloud algorithm update to FRESCO-wide yielded a general increase in TROPOMI TCN, especially in the partially cloudy pixels, leaving only 11% (downwind) and 29% (upwind) negative bias from coincident Pandora measurements. Furthermore, the wind-based collocation method revealed the spatial distribution pattern of NOX (NO + NO2) emissions in the SMA, with significant emission sources in the northeastern and southeastern sides of the ground-based Pandora site in Seoul

Stem cell function and stress response are controlled by protein synthesis.

Whether protein synthesis and cellular stress response pathways interact to control stem cell function is currently unknown. Here we show that mouse skin stem cells synthesize less protein than their immediate progenitors in vivo, even when forced to proliferate. Our analyses reveal that activation of stress response pathways drives both a global reduction of protein synthesis and altered translational programmes that together promote stem cell functions and tumorigenesis. Mechanistically, we show that inhibition of post-transcriptional cytosine-5 methylation locks tumour-initiating cells in this distinct translational inhibition programme. Paradoxically, this inhibition renders stem cells hypersensitive to cytotoxic stress, as tumour regeneration after treatment with 5-fluorouracil is blocked. Thus, stem cells must revoke translation inhibition pathways to regenerate a tissue or tumour.This work was funded by Cancer Research UK (CR-UK), Worldwide Cancer Research, the Medical Research Council (MRC), the European Research Council (ERC), and EMBO. Research in Michaela Frye's laboratory is supported by a core support grant from the Wellcome Trust and MRC to the Wellcome Trust-Medical Research Cambridge Stem Cell Institute.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/nature1828