Bump extraction algorithm for variable amplitude fatigue loading

This paper presents the development of a fatigue mission synthesis algorithm, called Wavelet Bump Extraction (WBE), for summarising long records of fatigue road load data. This algorithm is used to extract fatigue damaging events or bumps in the record that cause the majority of the fatigue damage, whilst preserving the load cycle sequences. Bumps are identified from characteristic frequency bands in the load spectrum using the 12th order Daubechies wavelet. The bumps are combined to produce a mission signal which has equivalent signal statistics and fatigue damage to the original signal. The WBE accuracy has been evaluated by observing the cycle sequence effects of the bump loadings. The WBE was compared with the time domain fatigue data editing method, so that the effectiveness of WBE can be verified. Using WBE, a substantial compression of the load-time history could be achieved for the purpose of accelerated fatigue tests in the automotive industry

Mathematical models for somite formation

Somitogenesis is the process of division of the anterior–posterior vertebrate embryonic axis into similar morphological units known as somites. These segments generate the prepattern which guides formation of the vertebrae, ribs and other associated features of the body trunk. In this work, we review and discuss a series of mathematical models which account for different stages of somite formation. We begin by presenting current experimental information and mechanisms explaining somite formation, highlighting features which will be included in the models. For each model we outline the mathematical basis, show results of numerical simulations, discuss their successes and shortcomings and avenues for future exploration. We conclude with a brief discussion of the state of modeling in the field and current challenges which need to be overcome in order to further our understanding in this area

Mathematical models for somite formation

Somitogenesis is the process of division of the anterior–posterior vertebrate embryonic axis into similar morphological units known as somites. These segments generate the prepattern which guides formation of the vertebrae, ribs and other associated features of the body trunk. In this work, we review and discuss a series of mathematical models which account for different stages of somite formation. We begin by presenting current experimental information and mechanisms explaining somite formation, highlighting features which will be included in the models. For each model we outline the mathematical basis, show results of numerical simulations, discuss their successes and shortcomings and avenues for future exploration. We conclude with a brief discussion of the state of modeling in the field and current challenges which need to be overcome in order to further our understanding in this area

The 21Na(p,gamma)22Mg Reaction and Oxygen-Neon Novae

The 21Na(p,gamma)22Mg reaction is expected to play an important role in the nucleosynthesis of 22Na in Oxygen-Neon novae. The decay of 22Na leads to the emission of a characteristic 1.275 MeV gamma-ray line. This report provides the first direct measurement of the rate of this reaction using a radioactive 21Na beam, and discusses its astrophysical implications. The energy of the important state was measured to be E$_{c.m.}$= 205.7 $\pm$ 0.5 keV with a resonance strength $\omega\gamma = 1.03\pm0.16_{stat}\pm0.14_{sys}$ meV.Comment: Accepted for publication in Physical Review Letter

Single cell transcriptome analysis using next generation sequencing.

The heterogeneity of tissues, especially in cancer research, is a central issue in transcriptome analysis. In recent years, research has primarily focused on the development of methods for single cell analysis. Single cell analysis aims at gaining (novel) insights into biological processes of healthy and diseased cells. Some of the challenges in transcriptome analysis concern low abundance of sample starting material, necessary sample amplification steps and subsequent analysis. In this study, two fundamentally different approaches to amplification were compared using next-generation sequencing analysis: I. exponential amplification using polymerase-chain-reaction (PCR) and II. linear amplification. For both approaches, protocols for single cell extraction, cell lysis, cDNA synthesis, cDNA amplification and preparation of next-generation sequencing libraries were developed. We could successfully show that transcriptome analysis of low numbers of cells is feasible with both exponential and linear amplification. Using exponential amplification, the highest amplification rates up to 106 were possible. The reproducibility of results is a strength of the linear amplification method. The analysis of next generation sequencing data in single cell samples showed detectable expression in at least 16.000 genes. The variance between samples results in a need to work with a greater amount of biological replicates. In summary it can be said that single cell transcriptome analysis with next generation sequencing is possible but improvements leading to a higher yield of transcriptome reads is required. In the near future by comparing single cancer cells with healthy ones for example, a basis for improved prognosis and diagnosis can be realised

Correlation analysis of the transcriptome of growing leaves with mature leaf parameters in a maize RIL population

Background: To sustain the global requirements for food and renewable resources, unraveling the molecular networks underlying plant growth is becoming pivotal. Although several approaches to identify genes and networks involved in final organ size have been proven successful, our understanding remains fragmentary. Results: Here, we assessed variation in 103 lines of the Zea mays B73xH99 RIL population for a set of final leaf size and whole shoot traits at the seedling stage, complemented with measurements capturing growth dynamics, and cellular measurements. Most traits correlated well with the size of the division zone, implying that the molecular basis of final leaf size is already defined in dividing cells of growing leaves. Therefore, we searched for association between the transcriptional variation in dividing cells of the growing leaf and final leaf size and seedling biomass, allowing us to identify genes and processes correlated with the specific traits. A number of these genes have a known function in leaf development. Additionally, we illustrated that two independent mechanisms contribute to final leaf size, maximal growth rate and the duration of growth. Conclusions: Untangling complex traits such as leaf size by applying in-depth phenotyping allows us to define the relative contributions of the components and their mutual associations, facilitating dissection of the biological processes and regulatory networks underneath

Transcriptome changes and cAMP oscillations in an archaeal cell cycle

Background The cell cycle of all organisms includes mass increase by a factor of two, replication of the genetic material, segregation of the genome to different parts of the cell, and cell division into two daughter cells. It is tightly regulated and typically includes cell cycle-specific oscillations of the levels of transcripts, proteins, protein modifications, and signaling molecules. Until now cell cycle-specific transcriptome changes have been described for four eukaryotic species ranging from yeast to human, but only for two prokaryotic species. Similarly, oscillations of small signaling molecules have been identified in very few eukaryotic species, but not in any prokaryote. Results A synchronization procedure for the archaeon Halobacterium salinarum was optimized, so that nearly 100% of all cells divide in a time interval that is 1/4th of the generation time of exponentially growing cells. The method was used to characterize cell cycle-dependent transcriptome changes using a genome-wide DNA microarray. The transcript levels of 87 genes were found to be cell cycle-regulated, corresponding to 3% of all genes. They could be clustered into seven groups with different transcript level profiles. Cluster-specific sequence motifs were detected around the start of the genes that are predicted to be involved in cell cycle-specific transcriptional regulation. Notably, many cell cycle genes that have oscillating transcript levels in eukaryotes are not regulated on the transcriptional level in H. salinarum. Synchronized cultures were also used to identify putative small signaling molecules. H. salinarum was found to contain a basal cAMP concentration of 200 uM, considerably higher than that of yeast. The cAMP concentration is shortly induced directly prior to and after cell division, and thus cAMP probably is an important signal for cell cycle progression. Conclusions The analysis of cell cycle-specific transcriptome changes of H. salinarum allowed to identify a strategy of transcript level regulation that is different from all previously characterized species. The transcript levels of only 3% of all genes are regulated, a fraction that is considerably lower than has been reported for four eukaryotic species (6% - 28%) and for the bacterium C. crescentus (19%). It was shown that cAMP is present in significant concentrations in an archaeon, and the phylogenetic profile of the adenylate cyclase indicates that this signaling molecule is widely distributed in archaea. The occurrence of cell cycle-dependent oscillations of the cAMP concentration in an archaeon and in several eukaryotic species indicates that cAMP level changes might be a phylogenetically old signal for cell cycle progression

A mission synthesis algorithm for fatigue damage analysis

This paper presents a signal processing based algorithm, the Mildly Nonstationary Mission Synthesis (MNMS), which produces a short mission signal from long records of experimental data. The algorithm uses the Discrete Fourier Transform, Orthogonal Wavelet Transform and bump reinsertion procedures. In order to observe the algorithm effectiveness a fatigue damage case study was performed for a vehicle lower suspension arm using signals containing tensile and compressive preloading. The mission synthesis results were compared to the original road data in terms of both the global signal statistics and the fatigue damage variation as a function of compression ratio. Three bump reinsertion methods were used and evaluated. The methods differed in the manner in which bumps (shock events) from different wavelet groups (frequency bands) were synchronised during the reinsertion process. One method, based on time synchronised section reinsertion, produced the best results in terms of mission signal kurtosis, crest factor, root-mean-square level and power spectral density. For improved algorithm performance, bump selection was identified as the main control parameter requiring optimisation