Effects of stitching on delamination of satin weave carbon-epoxy laminates under mode I, mode II and mixed-mode I/II loadings

The objective of the present study is to characterize the effect of modified chain stitching on the delamination growth under mixed-mode I/II loading conditions. Delamination toughness under mode I is experimentally determined, for unstitched and stitched laminates, by using untabbed and tabbed double cantilever beam (TDCB) tests. The effect of the reinforcing tabs on mode I toughness is investigated. Stitching improves the energy release rate (ERR) up to 4 times in mode I. Mode II delamination toughness is evaluated in end-notched flexure (ENF) tests. Different geometries of stitched specimens are tested. Crack propagation occurs without any failure of stitching yarns. The final crack length attains the mid-span or it stops before and the specimen breaks in bending. The ERR is initially low and gradually increases with crack length to very high values. The mixedmode delamination behaviour is investigated using a mixed-mode bending (MMB) test. For unstitched specimens, a simple mixed-mode criterion is identified. For stitched specimens, stitching yarns do not break during 25% of mode I ratio tests and the ERR increase is relatively small compared to unstitched values. For 70% and 50% of mode I ratios, failures of yarns are observed during crack propagation and tests are able to capture correctly the effect of the stitching: it clearly improves the ERR for these two mixed modes, as much as threefold

Comparison of System Call Representations for Intrusion Detection

Over the years, artificial neural networks have been applied successfully in many areas including IT security. Yet, neural networks can only process continuous input data. This is particularly challenging for security-related non-continuous data like system calls. This work focuses on four different options to preprocess sequences of system calls so that they can be processed by neural networks. These input options are based on one-hot encoding and learning word2vec or GloVe representations of system calls. As an additional option, we analyze if the mapping of system calls to their respective kernel modules is an adequate generalization step for (a) replacing system calls or (b) enhancing system call data with additional information regarding their context. However, when performing such preprocessing steps it is important to ensure that no relevant information is lost during the process. The overall objective of system call based intrusion detection is to categorize sequences of system calls as benign or malicious behavior. Therefore, this scenario is used to evaluate the different input options as a classification task. The results show, that each of the four different methods is a valid option when preprocessing input data, but the use of kernel modules only is not recommended because too much information is being lost during the mapping process.Comment: 12 pages, 1 figure, submitted to CISIS 201

Medium energy ion scattering (MEIS) study from the five-fold surface of icosahedral Ag-In-Yb quasicrystal

Medium energy ion scattering (MEIS) is employed to characterize the composition and structure of the five-fold surface of the icosahedral Ag42In42Yb16 quasicrystal. The composition of the surface after sputtering is dominated by Ag and In, and when the surface is annealed at temperatures approaching 430°C, Yb is restored at the surface. The composition is that expected from the bulk structure if the surface is formed at bulk planes involving the centre of rhombic triacontahedral clusters, the building blocks of the system. Structural analysis of MEIS results are also consistent with a surface after annealing that is in close agreement with bulk truncation intersecting the cluster centre

Factors associated with failed treatment : an analysis of 121,744 women embarking on their first IVF cycles

Peer reviewedPublisher PD

'Special K' and a loss of cell-to-cell adhesion in proximal tubule-derived epithelial cells: modulation of the adherens junction complex by ketamine

Ketamine, a mild hallucinogenic class C drug, is the fastest growing ‘party drug’ used by 16–24 year olds in the UK. As the recreational use of Ketamine increases we are beginning to see the signs of major renal and bladder complications. To date however, we know nothing of a role for Ketamine in modulating both structure and function of the human renal proximal tubule. In the current study we have used an established model cell line for human epithelial cells of the proximal tubule (HK2) to demonstrate that Ketamine evokes early changes in expression of proteins central to the adherens junction complex. Furthermore we use AFM single-cell force spectroscopy to assess if these changes functionally uncouple cells of the proximal tubule ahead of any overt loss in epithelial cell function. Our data suggests that Ketamine (24–48 hrs) produces gross changes in cell morphology and cytoskeletal architecture towards a fibrotic phenotype. These physical changes matched the concentration-dependent (0.1–1 mg/mL) cytotoxic effect of Ketamine and reflect a loss in expression of the key adherens junction proteins epithelial (E)- and neural (N)-cadherin and β-catenin. Down-regulation of protein expression does not involve the pro-fibrotic cytokine TGFβ, nor is it regulated by the usual increase in expression of Slug or Snail, the transcriptional regulators for E-cadherin. However, the loss in E-cadherin can be partially rescued pharmacologically by blocking p38 MAPK using SB203580. These data provide compelling evidence that Ketamine alters epithelial cell-to-cell adhesion and cell-coupling in the proximal kidney via a non-classical pro-fibrotic mechanism and the data provides the first indication that this illicit substance can have major implications on renal function. Understanding Ketamine-induced renal pathology may identify targets for future therapeutic intervention

Transgenic expression of the dicotyledonous pattern recognition receptor EFR in rice leads to ligand-dependent activation of defense responses

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo)-derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistance to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2, or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferatoractivator receptor (PPAR) a response in rat and human

The roles of endolithic fungi in bioerosion and disease in marine ecosystems. II. Potential facultatively parasitic anamorphic ascomycetes can cause disease in corals and molluscs

Anamorphic ascomycetes have been implicated as causative agents of diseases in tissues and skeletons of hard corals, in tissues of soft corals (sea fans) and in tissues and shells of molluscs. Opportunist marine fungal pathogens, such as Aspergillus sydowii, are important components of marine mycoplankton and are ubiquitous in the open oceans, intertidal zones and marine sediments. These fungi can cause infection in or at least can be associated with animals which live in these ecosystems. A. sydowii can produce toxins which inhibit photosynthesis in and the growth of coral zooxanthellae. The prevalence of many documented infections has increased in frequency and severity in recent decades with the changing impacts of physical and chemical factors, such as temperature, acidity and eutrophication. Changes in these factors are thought to cause significant loss of biodiversity in marine ecosystems on a global scale in general, and especially in coral reefs and shallow bays

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)