Practical guidance on the application of R-K integration method in finite element analysis of creep damage problem

A practical user guidance of Runge-Kutta (R-K) integration method with the context of non-linear time dependent finite element analysis (FEA) was proposed in this paper. Following the literature review of different integration method within the finite element analysis framework, detailed numerical experiments were conducted to find out the right balance between computing accuracy and efficiency. It contributes to knowledge to the numerical analysis software development in general and specific to computational creep damage mechanics

The development of finite element software for creep deformation and damage analysis of weldment

This paper presents the development of finite element software for creep deformation and damage analysis of weldment. The development and benchmark test of the software under plane stress, plane strain, axisymmetric, and 3 dimensional cases were reported in previous work [1]. This paper primarily consists of two parts: 1) the structure of the new FE software and the existing FE library applied in obtaining such computational tool via an approach for stress and field variable updating; 2) the development and validation of stress update; and 3) the development of validation of multi-material zones version. This paper contributes to the computational creep damage mechanics in general and particular to the design and the development of finite element software for creep damage analysis of multi-material zone

Dys-regulated Gene Expression Networks by Meta-Analysis of Microarray Data on Oral Squamous Cell Carcinoma

Background: Oral squamous cell carcinoma (OSCC) is the sixth most common type of carcinoma worldwide. Development of OSCC is a multi-step process involving genes related to cell cycle, growth control, apoptosis, DNA damage response and other cellular regulators. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of OSCC gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets has opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated.

Results: In this work we performed a meta-analysis on four microarray and four datasets of gene expression data on OSCC in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Sixteen dys-regulated pathways implicated in OSCC were mined out from the four published datasets, and most importantly three pathways were first reported. Those regulatory pathways and biological processes which are significantly enriched have been investigated by means of literatures and meanwhile, four genes of the maximally altered pathways, ECM-receptor interaction, were validated and identified by qRT-PCR as a possible candidate of aggressiveness of OSCC.

Conclusion: we have developed a robust method for analyzing pathways altered in OSCC using three expression array data sets. This study sets a stage for the further discovery of the basic mechanisms that may underlie a diseased state and would help in identifying critical nodes in the pathway that can be targeted for diagnosis and therapeutic intervention. In addition, those who are interested in our approach can obtain the software package (MATLAB platform) by email freely

Using tweets to help sentence compression for news highlights generation

We explore using relevant tweets of a given news article to help sentence com-pression for generating compressive news highlights. We extend an unsupervised dependency-tree based sentence compres-sion approach by incorporating tweet in-formation to weight the tree edge in terms of informativeness and syntactic impor-tance. The experimental results on a pub-lic corpus that contains both news arti-cles and relevant tweets show that our pro-posed tweets guided sentence compres-sion method can improve the summariza-tion performance significantly compared to the baseline generic sentence compres-sion method.