FEM calibrated ARMAX model updating method for time domain damage identification

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. To do this, a finite element model of a steel pipe laid on the soil is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then built and calibrated. The calibrated ARMAX model is used to identify different damage scenarios through model updating process using clonal selection algorithm (CSA). The results demonstrate the application potential of the proposed method in identifying the pipeline conditions. To further verify its performance, laboratory tests of a steel pipe laid on the soil with and without soil support (free span damage) are carried out. The identification results of pipe-soil system show that the proposed method is capable of identifying damagein a complex structural system. Therefore, it can be applied to identifying pipeline conditions.

The P-Loop domain of yeast Clp1 mediates interactions between CF IA and CPF factors in Pre-mRNA 3′ end formation

 Cleavage factor IA (CF IA), cleavage and polyadenylation factor (CPF), constitute major protein complexes required for pre-mRNA 3' end formation in yeast. The Clp1 protein associates with Pcf11, Rna15 and Rna14 in CF IA but its functional role remained unclear. Clp1 carries an evolutionarily conserved P-loop motif that was previously shown to bind ATP. Interestingly, human and archaean Clp1 homologues, but not the yeast protein, carry 5' RNA kinase activity. We show that depletion of Clp1 in yeast promoted defective 3' end formation and RNA polymerase II termination; however, cells expressing Clp1 with mutant P-loops displayed only minor defects in gene expression. Similarly, purified and reconstituted mutant CF IA factors that interfered with ATP binding complemented CF IA depleted extracts in coupled in vitro transcription/3' end processing reactions. We found that Clp1 was required to assemble recombinant CF IA and that certain P-loop mutants failed to interact with the CF IA subunit Pcf11. In contrast, mutations in Clp1 enhanced binding to the 3' endonuclease Ysh1 that is a component of CPF. Our results support a structural role for the Clp1 P-loop motif. ATP binding by Clp1 likely contributes to CF IA formation and cross-factor interactions during the dynamic process of 3' end formation.

Novel Z-Domain precoding method for blind separation of spatially correlated signals

In this paper, we address the problem of blind separation of spatially correlated signals, which is encountered in some emerging applications, e.g., distributed wireless sensor networks and wireless surveillance systems. We preprocess the source signals in transmitters prior to transmission. Specifically, the source signals are first filtered by a set of properly designed precoders and then the coded signals are transmitted. On the receiving side, the Z-domain features of the precoders are exploited to separate the coded signals, from which the source signals are recovered. Based on the proposed precoders, a closed-form algorithm is derived to estimate the coded signals and the source signals. Unlike traditional blind source separation approaches, the proposed method does not require the source signals to be uncorrelated, sparse, or nonnegative. Compared with the existing precoder-based approach, the new method uses precoders with much lower order, which reduces the delay in data transmission and is easier to implement in practice.

Dynamically searching for a domain for protein function prediction

The availability of large amounts of protein-protein interaction (PPI) data makes it feasible to use computational approaches to predict protein functions. The base of existing computational approaches is to exploit the known function information of annotated proteins in the PPI data to predict functions of un-annotated proteins. However, these approaches consider the prediction domain (i.e. the set of proteins from which the functions are predicted) as unchangeable during the prediction procedure. This may lead to valuable information being overwhelmed by the unavoidable noise information in the PPI data when predicting protein functions, and in turn, the prediction results will be distorted. In this paper, we propose a novel method to dynamically predict protein functions from the PPI data. Our method regards the function prediction as a dynamic process of finding a suitable prediction domain, from which representative functions of the domain are selected to predict functions of un-annotated proteins. Our method exploits the topological structural information of a PPI network and the semantic relationship between protein functions to measure the relationship between proteins, dynamically select a suitable prediction domain and predict functions. The evaluation on real PPI datasets demonstrated the effectiveness of our proposed method, and generated better prediction results.

Multitasking: multiple, domain-specific cognitive functions in a virtual environment

Multitasking among three or more different tasks is a ubiquitous requirement of everyday cognition, yet rarely is it addressed in research on healthy adults who have had no specific training in multitasking skills. Participants completed a set of diverse subtasks within a simulated shopping mall and office environment, the Edinburgh Virtual Errands Test (EVET). The aim was to investigate how different cognitive functions, such as planning, retrospective and prospective memory, and visuospatial and verbal working memory, contribute to everyday multitasking. Subtasks were chosen to be diverse, and predictions were derived from a statistical model of everyday multitasking impairments associated with frontal-lobe lesions (Burgess, Veitch, de Lacy Costello, & Shallice, 2000b). Multiple regression indicated significant independent contributions from measures of retrospective memory, visuospatial working memory, and online planning, but not from independent measures of prospective memory or verbal working memory. Structural equation modelling showed that the best fit to the data arose from three underlying constructs, with Memory and Planning having a weak link, but with both having a strong directional pathway to an Intent construct that reflected implementation of intentions. Participants who followed their preprepared plan achieved higher scores than those who altered their plan during multitask performance. This was true regardless of whether the plan was efficient or poor. These results substantially develop and extend the Burgess et al. (2000b) model to healthy adults and yield new insight into the poorly understood area of everyday multitasking. The findings also point to the utility of using virtual environments for investigating this form of complex human cognition.

Toughening epoxy thermosets with block ionomers : the role of phase domain size

Herein we report a novel approach to toughen epoxy thermosets using a block ionomer, i.e., sulfonated polystyrene-block-poly(ethylene-co-butylene)-block- polystyrene (SSEBS). SSEBS was synthesized by sulfonation of SEBS with 67 wt % polystyrene (PS). Phase morphology of the epoxy/SSEBS blends can be controlled at either nanometer or micrometer scale by simply adjusting the sulfonation degree of SSEBS. It has been found that there exists a critical degree of sulfonation (10.8 mol %) forming nanostructures in these epoxy/SSEBS blends. Above this critical value, macrophase separation can be avoided and only microphase separation occurs, yielding transparent nanostructured blends. All epoxy/SSEBS blends display increased fracture toughness compared to neat epoxy. But the toughening efficiency varies with the phase domain size, and their correlation has been established over a broad range of length scales from nanometers to a few micrometers. In the nanostructured blends with SSEBS of high sulfonation degrees, the fracture toughness decreases with decreasing size of the phase domains. In the macrophase-separated blends, only a slight improvement in toughness can be obtained with SSEBS of low sulfonation degrees. The epoxy blend with submicrometer phase domains in the range 0.05-1.0 μm containing SSEBS of a moderate degree of sulfonation (5.8 mol %) displays the maximum toughness. This study has clearly clarified the role of phase domain size on toughening efficiency in epoxy thermosets.

Versican processing by a disintegrin-like and metalloproteinase domain with thrombospondin-1 repeats proteinases-5 and -15 facilitates myoblast fusion

Skeletal muscle development and regeneration requires the fusion of myoblasts into multinucleated myotubes. Because the enzymatic proteolysis of a hyaluronan and versican-rich matrix by ADAMTS versicanases is required for developmental morphogenesis, we hypothesized that the clearance of versican may facilitate the fusion of myoblasts during myogenesis. Here, we used transgenic mice and an in vitro model of myoblast fusion, C2C12 cells, to determine a potential role for ADAMTS versicanases. Versican processing was observed during in vivo myogenesis at the time when myoblasts were fusing to form multinucleated myotubes. Relevant ADAMTS genes, chief among them Adamts5 and Adamts15, were expressed both in developing embryonic muscle and differentiating C2C12 cells. Reducing the levels of Adamts5 mRNA in vitro impaired myoblast fusion, which could be rescued with catalytically active but not the inactive forms of ADAMTS5 or ADAMTS15. The addition of inactive ADAMTS5, ADAMTS15, or full-length V1 versican effectively impaired myoblast fusion. Finally, the expansion of a hyaluronan and versican-rich matrix was observed upon reducing the levels of Adamts5 mRNA in myoblasts. These data indicate that these ADAMTS proteinases contribute to the formation of multinucleated myotubes such as is necessary for both skeletal muscle development and during regeneration, by remodeling a versican-rich pericellular matrix of myoblasts. Our study identifies a possible pathway to target for the improvement of myogenesis in a plethora of diseases including cancer cachexia, sarcopenia, and muscular dystrophy.

Biosynthesis and expression of a disintegrin-like and metalloproteinase domain with thrombospondin-1 repeats-15

Background
ADAMTS proteoglycanases show proteolytic activity toward versican and other proteoglycans.

Results
ADAMTS15, which cleaves versican, is expressed during early cardiac development and during musculoskeletal development.

Conclusion
With unique and overlapping biological properties, ADAMTS15 is likely to have cooperative roles with other members of the ADAMTS proteoglycanase clade.

Significance
Versican cleavage has profound effects on developmental morphogenesis and regulates cancer cell behavior.

Potassium channel modulation by a toxin domain in matrix metalloprotease

Peptide toxins found in a wide array of venoms block K+ channels, causing profound physiological and pathological effects. Here we describe the first functional K+ channel-blocking toxin domain in a mammalian protein. MMP23 (matrix metalloprotease 23) contains a domain (MMP23TxD) that is evolutionarily related to peptide toxins from sea anemones. MMP23TxD shows close structural similarity to the sea anemone toxins BgK and ShK. Moreover, this domain blocks K+ channels in the nanomolar to low micromolar range (Kv1.6 > Kv1.3 > Kv1.1 = Kv3.2 > Kv1.4, in decreasing order of potency) while sparing other K+ channels (Kv1.2, Kv1.5, Kv1.7, and KCa3.1). Full-length MMP23 suppresses K+ channels by co-localizing with and trapping MMP23TxD-sensitive channels in the ER. Our results provide clues to the structure and function of the vast family of proteins that contain domains related to sea anemone toxins. Evolutionary pressure to maintain a channel-modulatory function may contribute to the conservation of this domain throughout the plant and animal kingdoms.

Acquisition of domain ontology from relational schemes based on reverse engineering

Acquisition of domain ontology from database has been of catholic concern. This paper, taking relational schemes as example, analyzes how to identify the information about the structure of relational schemes in legacy systems. Then, it presents twelve extraction rules, which facilitate the obtaining of terms and relations from the relational schemes. Finally, it uses the EER diagram to further obtain semantic information from relational schemes for refining ontology model. The development method of domain ontology based on reverse engineering is a supplement to forward engineering. The union of the two development methods is certainly beneficial for the designers of domain ontology. © 2009 IEEE.