Lay-up optimization for the hull of a racing sailing yacht

Deformability and buckling load of yacht hulls with fiber reinforced plastic sandwich structure depend on the stack sequence of the skins. In this work an optimization of fiber directions of the laminae for a racing yacht is proposed. This procedure has been divided into three parts (i.e. material characterization, surface model definition, lay-up optimization). First of all a set of unidirectional specimens has been realized, by using the same fibers and matrix (carbon/epoxy) used for the hull as well as the same procedure and workers, in order to characterize the material according to American Society for Testing and Materials (ASTM) Standard D3039, employing strain gage technique. In the second part, by means of an original software in Turbo-Pascal (which uses the half-width value matrix as an input) linked to Pro/ENGINEER, it has been possible to obtain the body plan and surface and finite element (FE) models of the sailing yacht for the subsequent analyses. In the third step, an optimization procedure that uses the results of FE structural analyses in three different sailing configurations is performed, with the aim of obtaining the fiber directions that are able to minimize the yacht deformability, also taking into account the buckling loads. An approximate analytical model has been used in conjunction with a sweep technique in order to evaluate the best of the solutions

Additional file 4: Table S3. of Transcriptomes of newly-isolated Trypanosoma brucei rhodesiense reveal hundreds of mRNAs that are co-regulated with stumpy-form markers

Raw poly(A)+ mRNA transcriptome data and calculations based on reads per million (RPM). Sheet 1: Alignment statistics and correlations between the different datasets, calculated from RPM using the unique gene set only. cBS: cultured Lister 427 bloodstream forms expressing the tet repressor from pHD1313. BT1-3: Tbr729; LW - new isolates; PC - cultured Lister 427 procyclic forms. Sheet 2: Read counts for all genes. Sheet 3: Data for unique gene list [39] with reads per million (RPM). Column R shows the regulation pattern according to a custom script. Samples giving significantly peak RPMs (relative to other samples) are indicated by “max” and troughs are indicated by “min”. The threshold was set at 2-fold. Sheet 4: Sheet 3 results, filtered to remove genes for which the maximum RPM value was less than 10. Column T shows correlation coefficients of the RPM results with PIP39 (Tb927.9.6090). Colour code for ratios: Blue is less than 0.25×, green is less than 0.5×, orange is greater than 2× and red is greater than 4×. Comparisons with other datasets are indicated as follows: ST/SL Kabani; stumpy/slender ratio from [6]; ST/SL BS Jensen - stumpy/slender ratio from [7]; SLvST mRNA Capewell and ST polysomes/mRNA Capewell - data from [13]; SG/cBS: salivary gland trypanosomes relative to cultured bloodstream forms from [30]; SG/PC: salivary gland trypanosomes [30] relative to our results for cultured Lister 427 procyclic forms. Sheet 5: calculated RPMs for selected recognised stumpy-form markers. Reads for the ESAG9s and the PAD genes are not unique and precise allocation to a particular variant was not attempted. Sheet 6: Genes showing increased RPM values in both LW032 and LW042 and metacyclic (salivary gland, SG) forms. Sheet 7: Genes showing reduced RPM values in both LW032 and LW042 and metacyclic (salivary gland, SG) forms. (XLSX 3928 kb

Additional file 6: Figure S2. of Transcriptomes of newly-isolated Trypanosoma brucei rhodesiense reveal hundreds of mRNAs that are co-regulated with stumpy-form markers

Heat map of the regulation factors (log2) for mRNAs that are increased in the LW032 and LW042 transcriptomes. Red is least and white is most. (PDF 617 kb

Additional file 1: Figure S1. of Transcriptomes of newly-isolated Trypanosoma brucei rhodesiense reveal hundreds of mRNAs that are co-regulated with stumpy-form markers

Reads per Kilobase per million reads (RPKMs) for the set of unique open reading frames: examples from the genomic sequence data. Open reading frames were separated into “bins” according to the measured RPKM. The number of open reading frames in each bin was then calculated. The plots show the results for three of the genome datasets. The modal values were assumed to represent the average RPKM for a single-copy gene. (PDF 414 kb

Methods to Determine the Transcriptomes of Trypanosomes in Mixtures with Mammalian Cells: The Effects of Parasite Purification and Selective cDNA Amplification

<div><p>Patterns of gene expression in cultured <i>Trypanosoma brucei</i> bloodstream and procyclic forms have been extensively characterized, and some comparisons have been made with trypanosomes grown to high parasitaemias in laboratory rodents. We do not know, however, to what extent these transcriptomes resemble those in infected Tsetse flies - or in humans or cattle, where parasitaemias are substantially lower. For clinical and field samples it is difficult to characterize parasite gene expression because of the large excess of host cell RNA. We have here examined two potential solutions to this problem for bloodstream form trypanosomes, assaying transcriptomes by high throughput cDNA sequencing (RNASeq). We first purified the parasites from blood of infected rats. We found that a red blood cell lysis procedure affected the transcriptome substantially more than purification using a DEAE cellulose column, but that too introduced significant distortions and variability. As an alternative, we specifically amplified parasite sequences from a mixture containing a 1000-fold excess of human RNA. We first purified polyadenylated RNA, then made trypanosome-specific cDNA by priming with a spliced leader primer. Finally, the cDNA was amplified using nested primers. The amplification procedure was able to produce samples in which 20% of sequence reads mapped to the trypanosome genome. Synthesis of the second cDNA strand with a spliced leader primer, followed by amplification, is sufficiently reproducible to allow comparison of different samples so long as they are all treated in the same way. However, SL priming distorted the abundances of the cDNA products and definitely cannot be used, by itself, to measure absolute mRNA levels. The amplification method might be suitable for clinical samples with low parasitaemias, and could also be adapted for other Kinetoplastids and to samples from infected vectors.</p></div

Effect of column purification and erythrocyte lysis on transcriptome profile reproducibility.

<p>A–B Buffy coat samples (BC). For each unique open reading frame, the reads per million (RPM) in replicate samples are plotted against each other - replicates 1 and 2 in A, and replicates 1 and 3 in B. The grey dotted line is the regression line for perfect correlation. C–D DEAE-purified samples (DE), plotted as in (A). E–F. Erythrocyte lysis samples (RL), plotted as in (A).</p

Column purification and erythrocyte lysis cause transcriptome changes.

<p>For each condition: buffy coat (BC), DEAE purification (DE) and erythrocyte lysis (RL), and for each unique open reading frame, the arithmetic mean for three independent experiments was calculated. A. Mean counts for DEAE samples compared with those for buffy coat samples. The diagonal dashed grey line is perfect correlation, and the solid grey line shows the linear regression line for which the formula is shown in the bottom right. B. Mean counts for erythrocyte lysis samples compared with those for buffy coat samples. Analysis as in (A).</p

Spliced leader priming leads to unevenly distributed reads.

<p>A. Reads were mapped across mRNAs, then each mRNA was normalised to a standard length of 1000. Around 1000 mRNAs of short (less than 1 kb) or long (>2.5 kb) lengths were selected, and the average read densities across the mRNAs were plotted for unamplified poly(A)+ mRNA (pA+), and samples T4 (spliced leader primed, unamplified) and TH4. B. The read distributions over four different genes are shown, using data from samples T4 and TH4. For each, the 5′-end of the mRNA is on the far left, and the open reading frame is filled black. The maximum read density is on the left-hand scale and the total number of reads is also indicated.</p

Amplification procedure.

<p>For explanation see text. A. RNA extraction; B. Mixing of trypanosome and HeLa RNA, if applicable; C. Location of cDNA primers; D. Location of SL reverse primer; E. Primers used for PCR; F. PCR product; G. Sheared PCR products; H. Sheared DNAs with Illumina adaptors; I. Sequence output; J. Sequences aligned to genome.</p

Reproducibility of spliced leader priming and amplification.

<p>Transcriptomes are represented as in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002806#pntd-0002806-g001" target="_blank">Figure 1</a>; results for individual experiments are compared. A. Reproducibility after spliced leader priming without amplification (sample T1 versus sample T2). B. Reproducibility after spliced leader priming without amplification (sample T3 versus sample T4). C. Reproducibility after spliced leader priming and amplification, using trypanosome RNA mixed with a 1000-fold excess of HeLa RNA (sample TH1 versus sample TH2). D. Reproducibility after spliced leader priming and amplification (sample TH3 versus sample TH4). E. Amplification affects read counts with a loss of some genes. The mean read counts for all unamplified samples (T1–T4) are plotted against those for all TH samples (TH1–TH4).</p