Computational efficiency improvement for analyzing bending and tensile behavior of woven fabric using strain smoothing method

The tensile and bending behavior of woven fabrics are among the most important characteristics in complex deformation analysis and modelling of textile fabrics and they govern many aesthetics and performance aspects such as wrinkle/buckle, hand and drape. In this paper, a numerical method for analyzing of the tensile and bending behavior of plain-woven fabric structure was developed. The formulated model is based on the first-order shear deformation theory (FSDT) for a four-node quadrilateral element (Q4) and a strain smoothing method in finite elements, referred as a cell-based smoothed finite element method (CS-FEM). The physical and low-stress mechanical parameters of the fabric were obtained through the fabric objective measurement technology (FOM) using the Kawabata evaluation system for fabrics (KES-FB). The results show that the applied numerical method provides higher efficiency in computation in terms of central processing unit (CPU) time than the conventional finite element method (FEM) because the evaluation of compatible strain fields of Q4 element in CS-FEM model is constants, and it was also appropriated for numerical modelling and simulation of mechanical deformation behavior such as tensile and bending of woven fabric.The author (UMINHO/BPD/9/2017) and co-authors acknowledge the FCT funding from FCT – Foundation for Science and Technology within the scope of the project “PEST UID/CTM/00264; POCI-01-0145-FEDER-007136”

Efficient recovery-based error estimation for the smoothed finite element method for smooth and singular linear elasticity

[EN] An error control technique aimed to assess the quality of smoothed finite element approximations is presented in this paper. Finite element techniques based on strain smoothing appeared in 2007 were shown to provide significant advantages compared to conventional finite element approximations. In particular, a widely cited strength of such methods is improved accuracy for the same computational cost. Yet, few attempts have been made to directly assess the quality of the results obtained during the simulation by evaluating an estimate of the discretization error. Here we propose a recovery type error estimator based on an enhanced recovery technique. The salient features of the recovery are: enforcement of local equilibrium and, for singular problems a ¿smooth + singular¿ decomposition of the recovered stress. We evaluate the proposed estimator on a number of test cases from linear elastic structural mechanics and obtain efficient error estimations whose effectivities, both at local and global levels, are improved compared to recovery procedures not implementing these features.Stephane Bordas would like to thank the partial financial support of the Royal Academy of Engineering and of the Leverhulme Trust for his Senior Research Fellowship Towards the next generation surgical simulators as well as the financial support for Octavio A. Gonzalez-Estrada and Stephane Bordas from the UK Engineering Physical Science Research Council (EPSRC) under grant EP/G042705/1 Increased Reliability for Industrially Relevant Automatic Crack Growth Simulation with the eXtended Finite Element Method. Stephane Bordas also thanks partial financial support of the European Research Council Starting Independent Research Grant (ERC Stg grant agreement No. 279578) and the FP7 Initial Training Network Funding under grant number 289361 "Integrating Numerical Simulation and Geometric Design Technology, INSIST". This work has been carried out within the framework of the research project DPI2010-20542 of the Ministerio de Ciencia e Innovacion (Spain). The financial support from Universitat Politecnica de Valencia, PROMETEO/2012/023 and Generalitat Valenciana are also acknowledged.González Estrada, OA.; Natarajan, S.; J.J. Ródenas; Nguyen-Xuan, H.; Bordas, S. (2013). Efficient recovery-based error estimation for the smoothed finite element method for smooth and singular linear elasticity. Computational Mechanics. 52(1):37-52. https://doi.org/10.1007/s00466-012-0795-6S3752521Liu GR, Dai KY, Nguyen TT (2006) A smoothed finite element method for mechanics problems. 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High nuclear MSK1 is associated with longer survival in breast cancer patients

Purpose: Mitogen- and stress- activated kinases (MSKs) are important substrates of the mitogen-activated protein kinase (MAPK)-activated protein kinase family. MSK1 and MSK2 are both nuclear serine/threonine protein kinases, with MSK1 being suggested to potentially play a role in breast cancer cell proliferation, cell cycle progression, cell migration, invasion and tumour growth. The aim of the current study was to assess MSK1 protein expression in breast cancer tumour specimens, evaluating its prognostic significance. Methods: A large cohort of 1902 early stage invasive breast cancer patients was used to explore the expression of MSK1. Protein expression was examined using standard immunohistochemistry on tissue microarrays. Results: Low MSK1 protein expression was associated with younger age (P=0.004), higher tumour grade (P<0.001), higher Nottingham Prognostic Index scores (P=0.007), negative ER (P<0.001) and PR (P<0.001) status, and with triple-negative (P<0.001) and basal-like (P<0.001) phenotypes. Low MSK1 protein expression was significantly associated with shorter time to distant metastasis (P<0.001), and recurrence (P=0.013) and early death due to breast cancer (P=0.01). This association between high MSK1 expression and improved breast cancer-specific survival was observed in the whole cohort (P=0.009) and in the HER2 negative and non-basal like tumours (P=0.006 and P=0.024, respectively). Multivariate analysis including other prognostic variables indicated that MSK1 is not an independent marker of outcome. Conclusions: High MSK1 is associated with improved breast cancer-specific survival in early stage invasive breast cancer patients, and has additional prognostic value in HER2 negative and non-basal like disease. Although not an independent marker of outcome we believe such findings, and significant associations with well-established negative prognostic factors (age, grade, Nottingham Prognostic Index, hormone receptor status, time to distant metastasi

Incongruence in number–luminance congruency effects

Congruency tasks have provided support for an amodal magnitude system for magnitudes that have a “spatial” character, but conflicting results have been obtained for magnitudes that do not (e.g., luminance). In this study, we extricated the factors that underlie these number–luminance congruency effects and tested alternative explanations: (unsigned) luminance contrast and saliency. When luminance had to be compared under specific task conditions, we revealed, for the first time, a true influence of number on luminance judgments: Darker stimuli were consistently associated with numerically larger stimuli. However, when number had to be compared, luminance contrast, not luminance, influenced number judgments. Apparently, associations exist between number and luminance, as well as luminance contrast, of which the latter is probably stronger. Therefore, similar tasks, comprising exactly the same stimuli, can lead to distinct interference effects

Hedgehog Signaling in Tumor Cells Facilitates Osteoblast-Enhanced Osteolytic Metastases

The remodeling process in bone yields numerous cytokines and chemokines that mediate crosstalk between osteoblasts and osteoclasts and also serve to attract and support metastatic tumor cells. The metastatic tumor cells disturb the equilibrium in bone that manifests as skeletal complications. The Hedgehog (Hh) pathway plays an important role in skeletogenesis. We hypothesized that the Hh pathway mediates an interaction between tumor cells and osteoblasts and influences osteoblast differentiation in response to tumor cells. We have determined that breast tumor cells have an activated Hh pathway characterized by upregulation of the ligand, IHH and transcription factor GLI1. Breast cancer cells interact with osteoblasts and cause an enhanced differentiation of pre-osteoblasts to osteoblasts that express increased levels of the osteoclastogenesis factors, RANKL and PTHrP. There is sustained expression of osteoclast-promoting factors, RANKL and PTHrP, even after the osteoblast differentiation ceases and apoptosis sets in. Moreover, tumor cells that are deficient in Hh signaling are compromised in their ability to induce osteoblast differentiation and consequently are inefficient in causing osteolysis. The stimulation of osteoblast differentiation sets the stage for osteoclast differentiation and overall promotes osteolysis. Thus, in the process of developing newer therapeutic strategies against breast cancer metastasis to bone it would worthwhile to keep in mind the role of the Hh pathway in osteoblast differentiation in an otherwise predominant osteolytic phenomenon

Gene selection for classification of microarray data based on the Bayes error

<p>Abstract</p> <p>Background</p> <p>With DNA microarray data, selecting a compact subset of discriminative genes from thousands of genes is a critical step for accurate classification of phenotypes for, e.g., disease diagnosis. Several widely used gene selection methods often select top-ranked genes according to their individual discriminative power in classifying samples into distinct categories, without considering correlations among genes. A limitation of these gene selection methods is that they may result in gene sets with some redundancy and yield an unnecessary large number of candidate genes for classification analyses. Some latest studies show that incorporating gene to gene correlations into gene selection can remove redundant genes and improve classification accuracy.</p> <p>Results</p> <p>In this study, we propose a new method, Based Bayes error Filter (BBF), to select relevant genes and remove redundant genes in classification analyses of microarray data. The effectiveness and accuracy of this method is demonstrated through analyses of five publicly available microarray datasets. The results show that our gene selection method is capable of achieving better accuracies than previous studies, while being able to effectively select relevant genes, remove redundant genes and obtain efficient and small gene sets for sample classification purposes.</p> <p>Conclusion</p> <p>The proposed method can effectively identify a compact set of genes with high classification accuracy. This study also indicates that application of the Bayes error is a feasible and effective wayfor removing redundant genes in gene selection.</p

High Resolution Detection and Analysis of CpG Dinucleotides Methylation Using MBD-Seq Technology

Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis. We found that optimal efficiency of MBD-seq experiments was achieved by sequencing ∼100 million unique mapped tags from a combination of 500 mM and 1000 mM salt concentration elution in MCF-7 cells. Clonal bisulfite sequencing results showed that the methylation status of each CpG dinucleotides in the tested regions was accurately detected with high resolution using the proposed model. These results demonstrated the combination of MBD-seq and BALM could serve as a useful tool to investigate DNA methylome due to its low cost, high specificity, efficiency and resolution

The Chromatin Modifier MSK1/2 Suppresses Endocrine Cell Fates during Mouse Pancreatic Development

Type I diabetes is caused by loss of insulin-secreting beta cells. To identify novel, pharmacologically-targetable histone-modifying proteins that enhance beta cell production from pancreatic progenitors, we performed a screen for histone modifications induced by signal transduction pathways at key pancreatic genes. The screen led us to investigate the temporal dynamics of ser-28 phosphorylated histone H3 (H3S28ph) and its upstream kinases, MSK1 and MSK2 (MSK1/2). H3S28ph and MSK1/2 were enriched at the key endocrine and acinar promoters in E12.5 multipotent pancreatic progenitors. Pharmacological inhibition of MSK1/2 in embryonic pancreatic explants promoted the specification of endocrine fates, including the beta-cell lineage, while depleting acinar fates. Germline knockout of both Msk isoforms caused enhancement of alpha cells and a reduction in acinar differentiation, while monoallelic loss of Msk1 promoted beta cell mass. Our screen of chromatin state dynamics can be applied to other developmental contexts to reveal new pathways and approaches to modulate cell fates