Secondary Electron Yield of Electron Beam Welded Areas of SRF Cavities

Secondary Electron Emission (SEE) is a phenomenon that contributes to the total electron activity inside the Superconducting Radiofrequency (SRF) cavities during the accelerator operation. SEE is highly dependent on the state of the surface. During electron beam welding process, significant amount of heat is introduced into the material causing the microstructure change of Niobium (Nb). Currently, all simulation codes for field emission and multipacting are treating the inside of the cavity as a uniform, homogeneous surface. Due to its complex shape and fabricating procedure, and the sensitivity of the SEE on the surface state, it would be interesting to see if the Secondary Electron Yield (SEY) parameters vary in the surface area on and near the equator weld. For that purpose, we have developed experimental setup that can measure accurately the energy distribution of the SEY of coupon-like like samples. To test the influence of the weld area on the SEY of Nb, dedicated samples are made from a welded plate using electron beam welding parameters common for cavity fabrication. SEY data matrix of those samples will be presented

Effects of Plasma Processing on Secondary Electron Yield of Niobium Samples

Impurities deposited on the surface of Nb during both the forming and welding of accelerator cavities add to the imperfections of the sheet metal, which then affects the overall performance of the cavities. This leads to a drop in the Q factor and limits the maximum acceleration gradient achievable per unit length of the cavities. The performance can be improved either by adjusting the fabrication and preparation parameters, or by mitigating the effects of fabrication and preparation techniques used. We have developed the experimental setup to determine Secondary Electron Yield (SEY) from the surface of Nb samples. Our aim is to show the effect of plasma processing on the SEY of Nb. The setup measures the secondary electron energy distribution at various incident angles as measured between the electron beam and the surface of the sample. The goal is to determine the SEY on non-treated and plasma treated surface of electron beam welded samples. Here we describe the experimental setup, plasma treatment device, and fabrication and processing of the Nb samples

Transcription factor site dependencies in human, mouse and rat genomes

<p>Abstract</p> <p>Background</p> <p>It is known that transcription factors frequently act together to regulate gene expression in eukaryotes. In this paper we describe a computational analysis of transcription factor site dependencies in human, mouse and rat genomes.</p> <p>Results</p> <p>Our approach for quantifying tendencies of transcription factor binding sites to co-occur is based on a binding site scoring function which incorporates dependencies between positions, the use of information about the structural class of each transcription factor (major/minor groove binder), and also considered the possible implications of varying GC content of the sequences. Significant tendencies (dependencies) have been detected by non-parametric statistical methodology (permutation tests). Evaluation of obtained results has been performed in several ways: reports from literature (many of the significant dependencies between transcription factors have previously been confirmed experimentally); dependencies between transcription factors are not biased due to similarities in their DNA-binding sites; the number of dependent transcription factors that belong to the same functional and structural class is significantly higher than would be expected by chance; supporting evidence from GO clustering of targeting genes. Based on dependencies between two transcription factor binding sites (second-order dependencies), it is possible to construct higher-order dependencies (networks). Moreover results about transcription factor binding sites dependencies can be used for prediction of groups of dependent transcription factors on a given promoter sequence. Our results, as well as a scanning tool for predicting groups of dependent transcription factors binding sites are available on the Internet.</p> <p>Conclusion</p> <p>We show that the computational analysis of transcription factor site dependencies is a valuable complement to experimental approaches for discovering transcription regulatory interactions and networks. Scanning promoter sequences with dependent groups of transcription factor binding sites improve the quality of transcription factor predictions.</p

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs

Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. Results: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. Conclusions: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven

Dieselruß: Mikrostruktur und Oxidationskinetik

The engine internal emission reduction of commercial vehicles has been very im-pressive during the last ten years. The mass related reduction of the soot emission is a result of the reduced number of particles also with regard to those 96H30)6 with the mass 7098 u. The microstructures of soot particles are related to the chemical reactivity against the oxidizing agent nitrogen dioxide, NO2 by kinetic measurements. The obtained knowl-edge will be applied in the practice for minimizing the soot particle emission of diesel en-gines and for increasing the activity of exhaust aftertreatment with PM-KATâ and GD-KAT systems. The investigation of the formation and the properties of diesel soot of advanced commercial engines is just at the beginning. We expect that the chemical properties of the surface and the microstructure of soot emitted from advanced diesel engines will re-define toxicity (threshold value of secondary genotoxicity) and relevance of physical measurement methods

A selected bibliography on parameter optimization methods suitable for hybrid computation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68333/2/10.1177_003754976700800610.pd

N-gram analysis of 970 microbial organisms reveals presence of biological language models

<p>Abstract</p> <p>Background</p> <p>It has been suggested previously that genome and proteome sequences show characteristics typical of natural-language texts such as "signature-style" word usage indicative of authors or topics, and that the algorithms originally developed for natural language processing may therefore be applied to genome sequences to draw biologically relevant conclusions. Following this approach of 'biological language modeling', statistical n-gram analysis has been applied for comparative analysis of whole proteome sequences of 44 organisms. It has been shown that a few particular amino acid n-grams are found in abundance in one organism but occurring very rarely in other organisms, thereby serving as genome signatures. At that time proteomes of only 44 organisms were available, thereby limiting the generalization of this hypothesis. Today nearly 1,000 genome sequences and corresponding translated sequences are available, making it feasible to test the existence of biological language models over the evolutionary tree.</p> <p>Results</p> <p>We studied whole proteome sequences of 970 microbial organisms using n-gram frequencies and cross-perplexity employing the Biological Language Modeling Toolkit and Patternix Revelio toolkit. Genus-specific signatures were observed even in a simple unigram distribution. By taking statistical n-gram model of one organism as reference and computing cross-perplexity of all other microbial proteomes with it, cross-perplexity was found to be predictive of branch distance of the phylogenetic tree. For example, a 4-gram model from proteome of <it>Shigellae flexneri 2a</it>, which belongs to the <it>Gammaproteobacteria </it>class showed a self-perplexity of 15.34 while the cross-perplexity of other organisms was in the range of 15.59 to 29.5 and was proportional to their branching distance in the evolutionary tree from <it>S. flexneri</it>. The organisms of this genus, which happen to be pathotypes of <it>E.coli</it>, also have the closest perplexity values with <it>E. coli.</it></p> <p>Conclusion</p> <p>Whole proteome sequences of microbial organisms have been shown to contain particular n-gram sequences in abundance in one organism but occurring very rarely in other organisms, thereby serving as proteome signatures. Further it has also been shown that perplexity, a statistical measure of similarity of n-gram composition, can be used to predict evolutionary distance within a genus in the phylogenetic tree.</p

The ERA-EDTA Registry Annual Report 2018 : a summary

Background. The European Renal Association - European Dialysis and Transplant Association (ERA-EDTA) Registry collects data on kidney replacement therapy (KRT) via national and regional renal registries in Europe and countries bordering the Mediterranean Sea. This article summarizes the 2018 ERA-EDTA Registry Annual Report, and describes the epidemiology of KRT for kidney failure in 34 countries. Methods. Individual patient data on patients undergoing KRT in 2018 were provided by 34 national or regional renal registries and aggregated data by 17 registries. The incidence and prevalence of KRT, the kidney transplantation activity and the survival probabilities of these patients were calculated. Results. In 2018, the ERA-EDTA Registry covered a general population of 636 million people. Overall, the incidence of KRT for kidney failure was 129 per million population (p.m.p.), 62% of patients were men, 51% were >= 65years of age and 20% had diabetes mellitus as cause of kidney failure. Treatment modality at the onset of KRT was haemodialysis (HD) for 84%, peritoneal dialysis (PD) for 11% and pre-emptive kidney transplantation for 5% of patients. On 31 December 2018, the prevalence of KRT was 897 p.m.p., with 57% of patients on HD, 5% on PD and 38% living with a kidney transplant. The transplant rate in 2018 was 35 p.m.p.: 68% received a kidney from a deceased donor, 30% from a living donor and for 2% the donor source was unknown. For patients commencing dialysis during 2009-13, the unadjusted 5-year survival probability was 42.6%. For patients receiving a kidney transplant within this period, the unadjusted 5-year survival probability was 86.6% for recipients of deceased donor grafts and 93.9% for recipients of living donor grafts.Peer reviewe