Structural damage alarming and localization of cable-supported bridges using multi-novelty indices: A feasibility study

This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

Damage evaluation and damage localization of rock

Knowledge of damage accumulation and corresponding failure evolution are prerequisite for effective maintenance of civil engineering so as to avoid disaster. Based on statistical mesoscopic damage mechanics, it was revealed that there are three stages in the process of deformation, damage and failure of multiscale heterogeneous elastic-brittle medium. These are uniformly distributed damage, localized damage and catastrophic failure. In order to identify the transitions from scattering damage to macroscopically localized one, a condition for damage localization was given. The experiments of rock under uniaxial compression with the aid of observations of acoustic emission and speckle correlation do support the concept of localization. This provides a potential approach to properly evaluate damage accumulation in practice. In addition, it is found in the experiments that catastrophic failure displays critical sensitivity. This gives a helpful clue to the prediction of catastrophic failure. (C) 2004 Elsevier Ltd. All rights reserved.

Immunofluorescence detection and localization of B[a]P and TCDD in earthworm tissues

An immunohistochemical method using antibodies against polycyclic aromatic hydrocarbons (PAHs) and dioxins was developed on frozen tissue sections of the earthworm Eisenia andrei exposed to environmentally relevant concentrations of benzo[a]pyrene (B[a]P) (0.1, 10, 50 ppm) and 2,3,7,8-tetrachlorodibenzo-para-dioxin (TCDD) (0.01, 0.1, 2 ppb) in spiked standard soils. The concentrations of B[a]P and TCDD in E. andrei exposed to the same conditions were also measured using analytical chemical procedures. The results demonstrated that tissues of worms exposed to even minimal amount of B[a]P and TCDD reacted positively and specifically to anti-PAHs and -dioxins antibody. Immunofluorescence revealed a much more intense staining for the gut compared to the body wall; moreover, positively immunoreactive amoeboid coelomocytes were also observed, i.e. cells in which we have previously demonstrated the occurrence of genotoxic damage. The double immunolabelling with antibodies against B[a]P/TCDD and the lysosomal enzyme cathepsin D demonstrated the lysosomal accumulation of the organic xenobiotic compounds, in particular in the cells of the chloragogenous tissue as well as in coelomocytes, involved into detoxification and protection of animals against toxic chemicals. The method described is timesaving, not expensive and easily applicable.

Diversity and Localization of Bacterial Endosymbionts from Whitefly Species Collected in Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Mechanism of damage sensing and cell killing following the inhibition of nucleotide excision repair by fludarabine in quiescent cells

Inhibition of DNA repair by the nucleoside of fludarabine (F-ara-A) induces toxicity in quiescent human cells. The sensing and signaling mechanisms following DNA repair inhibition by F-ara-A are unknown. The central hypothesis of this project was that the mechanistic interaction of a DNA repair initiating agent and a nucleoside analog initiates an apoptotic signal in quiescent cells. The purpose of this research was to identify the sensing and signaling mechanism(s) that respond to DNA repair inhibition by F-ara-A. Lymphocytes were treated with F-ara-A, to accumulate the active triphosphate metabolite and subsequently DNA repair was activated by UV irradiation. Pre-incubation of lymphocytes with 3 μM F-ara-A inhibited DNA repair initiated by 2 J/m2 UV and induced greater than additive apoptosis after 24 h. Blocking the incorporation of F-ara-A nucleotide into repairing DNA using 30 μM aphidicolin considerably lowered the apoptotic response. ^ Wild-type quiescent cells showed a significant loss in viability than did cells lacking functional sensor kinase DNA-PKcs or p53 as measured by colony formation assays. The functional status of ATM did not appear to affect the apoptotic outcome. Immunoprecipitation studies showed an interaction between the catalytic sub-unit of DNA-PK and p53 following DNA repair inhibition. Confocal fluorescence microscopy studies have indicated the localization pattern of p53, DNA-PK and γ-H2AX in the nucleus following DNA damage. Foci formation by γ-H2AX was seen as an early event that is followed by interaction with DNA-PKcs. p53 serine-15 phosphorylation and accumulation were detected 2 h after treatment. Fas/Fas ligand expression increased significantly after repair inhibition and was dependent on the functional status of p53. Blocking the interaction between Fas and Fas ligand by neutralizing antibodies significantly rescued the apoptotic fraction of cells. ^ Collectively, these results suggest that incorporation of the nucleoside analog into repair patches is critical for cytotoxicity and that the DNA damage, while being sensed by DNA-PK, may induce apoptosis by a p53-mediated signaling mechanism. Based on the results, a model is proposed for the sensing of F-ara-A-induced DNA damage that includes γ-H2AX, DNA-PKcs, and p53. Targeting the cellular DNA repair mechanism can be a potential means of producing cytotoxicity in a quiescent population of neoplastic cells. These results also provide mechanistic support for the success of nucleoside analogs with cyclophosphamide or other agents that initiate excision repair processes, in the clinic. ^

Rad51 expression and localization in B cells carrying out class switch recombination.

Rad51 is a highly conserved eukaryotic homolog of the prokaryotic recombination protein RecA, which has been shown to function in both recombinational repair of DNA damage and meiotic recombination in yeast. In primary murine B cells cultured with lipopolysaccharide (LPS) to stimulate heavy chain class switch recombination, Rad51 protein levels are dramatically induced. Immunofluorescent microscopy shows that anti-Rad51 antibodies stain foci that are localized within the nuclei of switching B cells. Immunohistochemical analysis of splenic sections shows that clusters of cells that stain brightly with anti-Rad51 antibodies are evident within several days after primary immunization and that Rad51 staining in vivo is confined to B cells that are switching from expression of IgM to IgG antibodies. Following switch recombination, B cells populate splenic germinal centers, where somatic hypermutation and clonal proliferation occur. Germinal center B cells are not stained by anti-Rad51 antibodies. Rad51 expression is therefore not coincident with somatic hypermutation, nor does Rad51 expression correlate simply with cell proliferation. These data suggest that Rad51, or a highly related member of the conserved RecA family, may function in class switch recombination.

Review of vibration-based damage detection and condition assessment of bridge structures using structural health monitoring

As a part of vital infrastructure and transportation networks, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs always make the infrastructure owners difficult to undertake. Structural health monitoring (SHM) is set to assess condition and foresee probable failures of designated bridge(s), so as to monitor the structural health of the bridges. The SHM systems proposed recently are incorporated with Vibration-Based Damage Detection (VBDD) techniques, Statistical Methods and Signal processing techniques and have been regarded as efficient and economical ways to solve the problem. The recent development in damage detection and condition assessment techniques based on VBDD and statistical methods are reviewed. The VBDD methods based on changes in natural frequencies, curvature/strain modes, modal strain energy (MSE) dynamic flexibility, artificial neural networks (ANN) before and after damage and other signal processing methods like Wavelet techniques and empirical mode decomposition (EMD) / Hilbert spectrum methods are discussed here.

Structural health monitoring : vibration-based damage detection and condition assessment of bridges

Structural health is a vital aspect of infrastructure sustainability. As a part of a vital infrastructure and transportation network, bridge structures must function safely at all times. However, due to heavier and faster moving vehicular loads and function adjustment, such as Busway accommodation, many bridges are now operating at an overload beyond their design capacity. Additionally, the huge renovation and replacement costs are a difficult burden for infrastructure owners. The structural health monitoring (SHM) systems proposed recently are incorporated with vibration-based damage detection techniques, statistical methods and signal processing techniques and have been regarded as efficient and economical ways to assess bridge condition and foresee probable costly failures. In this chapter, the recent developments in damage detection and condition assessment techniques based on vibration-based damage detection and statistical methods are reviewed. The vibration-based damage detection methods based on changes in natural frequencies, curvature or strain modes, modal strain energy, dynamic flexibility, artificial neural networks, before and after damage, and other signal processing methods such as Wavelet techniques, empirical mode decomposition and Hilbert spectrum methods are discussed in this chapter.

Tubal damage, infertility and tubal ectopic pregnancy : chlamydia trachomatis and other microbial aetiologies

Infertility is a worldwide health problem with one in six couples suffering from this condition and with a major economic burden on the global healthcare industry. Estimates of the current global infertility rate suggest that 15% of couples are infertile (Zegers-Hochschild et al 2009) defined as: (1) failure to conceive after 12 months of unprotected sexual intercourse (i.e. infertility); (2) repeated implantation failure following ART cycles; or (3) recurrent miscarriage without difficulty conceiving (natural conceptions). Tubal factor infertility is among the leading causes of female factor infertility accounting for 7-9.8% of all female factor infertilities. Tubal disease directly causes from 36% to 85% of all cases of female factor infertility in developed and developing nations respectively and is associated with polymicrobial aetiologies. One of the leading global causes of tubal factor infertility is thought to be symptomatic (and asymptomatic in up to 70% cases) infection of the female reproductive tract with the sexually transmitted pathogen, Chlamydia trachomatis. Infection-related damage to the Fallopian tubes caused by Chlamydia accounts for more than 70% of cases of infertility in women from developing nations such as sub-Saharan Africa (Sharma et al 2009). Bacterial vaginosis, a condition associated with increased transmission of sexually transmitted infections including those caused by Neisseria gonorrhoeae and Mycoplasma genitalium is present in two thirds of women with pelvic inflammatory disease (PID). This review will focus on (1) the polymicrobial aetiologies of tubal factor infertility and (2) studies involved in screening for, and treatment and control of, Chlamydial infection to prevent PID and the associated sequelae of Fallopian tube inflammation that may lead to infertility and ectopic pregnancy.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Towards a controlled growth of self-assembled nanostructures: shaping, ordering and localization in Ge/Si heteroepitaxy.

The strain-induced self-assembly of suitable semiconductor pairs is an attractive natural route to nanofabrication. To bring to fruition their full potential for actual applications, individual nanostructures need to be combined into ordered patterns in which the location of each single unit is coupled with others and the surrounding environment. Within the Ge/Si model system, we analyze a number of examples of bottom-up strategies in which the shape, positioning, and actual growth mode of epitaxial nanostructures are tailored by manipulating the intrinsic physical processes of heteroepitaxy. The possibility of controlling elastic interactions and, hence, the configuration of self-assembled quantum dots by modulating surface orientation with the miscut angle is discussed. We focus on the use of atomic steps and step bunching as natural templates for nanodot clustering. Then, we consider several different patterning techniques which allow one to harness the natural self-organization dynamics of the system, such as: scanning tunneling nanolithography, focused ion beam and nanoindentation patterning. By analyzing the evolution of the dot assembly by scanning probe microscopy, we follow the pathway which leads to lateral ordering, discussing the thermodynamic and kinetic effects involved in selective nucleation on patterned substrates.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Fast power line detection and localization using steerable filter for active UAV guidance

In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

Changes in markers of muscle damage, inflammation and HSP70 after an Ironman triathlon race

We investigated the effects of an Ironman triathlon race on markers of muscle damage, inflammation and heat shock protein 70 (HSP70). Nine well-trained male triathletes (mean +/- SD age 34 +/- 5 years; VO(2peak) 66.4 ml kg(-1) min(-1)) participated in the 2004 Western Australia Ironman triathlon race (3.8 km swim, 180 km cycle, 42.2 km run). We assessed jump height, muscle strength and soreness, and collected venous blood samples 2 days before the race, within 30 min and 14-20 h after the race. Plasma samples were analysed for muscle proteins, acute phase proteins, cytokines, heat shock protein 70 (HSP70), and clinical biochemical variables related to dehydration, haemolysis, liver and renal functions. Muscular strength and jump height decreased significantly (P < 0.05) after the race, whereas muscle soreness and the plasma concentrations of muscle proteins increased. The cytokines interleukin (IL)-1 receptor antagonist, IL-6 and IL-10, and HSP70 increased markedly after the race, while IL-12p40 and granulocyte colony-stimulating factor (G-CSF) were also elevated. IL-4, IL-1beta and tumour necrosis factor-alpha did not change significantly, despite elevated C-reactive protein and serum amyloid protein A on the day after the race. Plasma creatinine, uric acid and total bilirubin concentrations and gamma-glutamyl transferase activity also changed after the race. In conclusion, despite evidence of muscle damage and an acute phase response after the race, the pro-inflammatory cytokine response was minimal and anti-inflammatory cytokines were induced. HSP70 is released into the circulation as a function of exercise duration.

Damage identification and condition assessment of building structures using frequency response functions and neural networks

This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.