Damage diagnosis for complex steel truss bridges using multi-layer genetic algorithm

Considerate amount of research has proposed optimization-based approaches employing various vibration parameters for structural damage diagnosis. The damage detection by these methods is in fact a result of updating the analytical structural model in line with the current physical model. The feasibility of these approaches has been proven. But most of the verification has been done on simple structures, such as beams or plates. In the application on a complex structure, like steel truss bridges, a traditional optimization process will cost massive computational resources and lengthy convergence. This study presents a multi-layer genetic algorithm (ML-GA) to overcome the problem. Unlike the tedious convergence process in a conventional damage optimization process, in each layer, the proposed algorithm divides the GA’s population into groups with a less number of damage candidates; then, the converged population in each group evolves as an initial population of the next layer, where the groups merge to larger groups. In a damage detection process featuring ML-GA, as parallel computation can be implemented, the optimization performance and computational efficiency can be enhanced. In order to assess the proposed algorithm, the modal strain energy correlation (MSEC) has been considered as the objective function. Several damage scenarios of a complex steel truss bridge’s finite element model have been employed to evaluate the effectiveness and performance of ML-GA, against a conventional GA. In both single- and multiple damage scenarios, the analytical and experimental study shows that the MSEC index has achieved excellent damage indication and efficiency using the proposed ML-GA, whereas the conventional GA only converges at a local solution.

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.

Cutaneous markers of photo-damage and risk of basal cell carcinoma of the skin : a meta-analysis

BACKGROUND: Epidemiologic research has demonstrated that cutaneous markers of photo-damage are associated with risk of basal cell carcinoma (BCC). However there has been no previous attempt to calculate pooled risk estimates. METHODS: We conducted a systematic review and meta-analysis after extracting relevant studies published up to January 2013 from five electronic databases. Eligible studies were those that permitted quantitative assessment of the association between histologically-confirmed BCC and actinic keratoses, solar elastosis, solar lentigines, or telangiectasia. RESULTS: Seven eligible studies were identified and summary odds ratios (OR) were calculated using both random and quality effects models. Having more than ten actinic keratoses was most strongly associated with BCC, conferring up to a 5-fold increase in risk (OR: 4.97; 95% CI: 3.26, 7.58). Other factors, including solar elastosis, solar lentigines, and telangiectasia had weaker but positive associations with BCC with ORs around 1.5. CONCLUSIONS: Markers of chronic photo-damage are positively associated with BCC. The presence of actinic keratoses was the most strongly associated with BCC of the markers examined. IMPACT: This work highlights the relatively modest association between markers of chronic ultraviolet exposure and BCC.

Damage assessment in beams and plates using variations in modal properties

Damage detection using modal properties is a widely accepted method. However, quantifying such damage using modal properties is still not well established. With this in mind, a research project is presently underway towards the development of a procedure to detect, locate and quantify damage in structural components using the variations in modal properties. A novel vibration based parameter called Vibration based Damage Index is introduced into the damage assessment procedure. This paper presents the early part of the research project which treats flexural members. The proposed procedure is validated using experimental data and/or theoretical techniques and illustrated through application. Outcomes of this research highlight the ability of the proposed procedure to successfully detect, locate and quantify damage in flexural structural components using the modal properties of the first few modes.

Cyclin A/CDK2 regulates multiple G2 phase pathways

The cell cycle is a carefully choreographed series of phases that when executed successfully will allow the complete replication of the genome and the equal division of the genome and other cellular content into two independent daughter cells. The inability of the cell to execute cell division successfully can result in either checkpoint activation to allow repair and/or apoptosis and/or mutations/errors that may or may not lead to tumourgenesis. Cyclin A/CDK2 is the primary cyclin/CDK regulating G2 phase progression of the cell cycle. Cyclin A/CDK2 activity peaks in G2 phase and its inhibition causes a G2 phase delay that we have termed 'the cyclin A/CDK2 dependent G2 delay'. Understanding the key pathways that are involved in the cyclin A/CDK2 dependent G2 delay has been the primary focus of this study. Characterising the cyclin A/CDK2 dependent G2 delay revealed accumulated levels of the inactive form of the mitotic regulator, cyclin B/CDK1. Surprisingly, there was also increased microtubule nucleation at the centrosomes, and the centrosomes stained for markers of cyclin B/CDK1 activity. Both microtubule nucleation at the centrosomes and phosphoprotein markers were lost with short-term treatment of CDK1/2 inhibition. Cyclin A/CDK2 localised at the centrosomes in late G2 phase after separation of the centrosomes but before the start of prophase. Thus G2 phase cyclin A/CDK2 controls the timing of entry into mitosis by controlling the subsequent activation of cyclin B/CDK1, but also has an unexpected role in coordinating the activation of cyclin B/CDK1 at the centrosome and in the nucleus. In addition to regulating the timing of cyclin B/CDK1 activation and entry into mitosis in the unperturbed cell cycle, cyclin A/CDK2 also was shown to have a role in G2 phase checkpoint recovery. Known G2 phase regulators were investigated to determine whether they had a role in imposing the cyclin A/ CDK2 dependent G2 delay. Examination of the critical G2 checkpoint arrest protein, Chk1, which also has a role during unperturbed G2/M phases revealed the presence of activated Chk1 in G2 phase, in a range of cell lines. Activated Chk1 levels were shown to accumulate in cyclin A/CDK2 depleted/inhibited cells. Further investigations revealed that Chk1, but not Chk2, depletion could reverse the cyclin A/CDK2 dependent G2 delay. It was confirmed that the accumulative activation of Chk1 was not a consequence of DNA damage induced by cyclin A depletion. The potential of cyclin A/CDK2 to regulate Chk1 revealed that the inhibitory phosphorylations, Ser286 and Ser301, were not directly catalysed by cyclin A/CDK2 in G2 phase to regulate mitotic entry. It appeared that the ability of cyclin A/CDK2 to regulate cyclin B/CDK1 activation impacted cyclin B/CDK1s phosphorylation of Chk1 on Ser286 and Ser301, thereby contributing to the delay in G2/M phase progression. Chk1 inhibition/depletion partially abrogated the cyclin A/CDK2 dependent G2 delay, and was less effective in abrogating G2 phase checkpoint suggesting that other cyclin A/CDK2 dependent mechanisms contributed to these roles of cyclin A/CDK2. In an attempt to identify these other contributing factors another G2/M phase regulator known to be regulated by cyclin A/CDK2, Cdh1 and its substrates Plk1 and Claspin were examined. Cdh1 levels were reduced in cyclin A/CDK2 depleted/inhibited cells although this had little effect on Plk1, a known Cdh1 substrate. However, the level of another substrate, Claspin, was increased. Cdh1 depletion mimicked the effect of cyclin A depletion but to a weaker extent and was sufficient at increasing Claspin levels similar to the increase caused by cyclin A depletion. Co-depletion of cyclin A and Claspin blocked the accumulation of activated Chk1 normally seen with cyclin A depletion alone. However Claspin depletion alone did not reduce the cyclin A/CDK2 dependent G2 delay but this is likely to be a result of inhibition of S phase roles of Claspin. Together, these data suggest that cyclin A/CDK2 regulates a number of different mechanisms that contribute to G2/M phase progression. Here it has been demonstrated that in normal G2/M progression and possibly to a lesser extent in G2 phase checkpoint recovery, cyclin A/CDK2 regulates the level of Cdh1 which in turn affects at least one of its substrates, Claspin, and consequently results in the increased level of activated Chk1 observed. However, the involvement of Cdh1 and Claspin alone does not explain the G2 phase delay observed with cyclin A/CDK2 depletion/inhibition. It is likely that other mechanisms, possibly including cyclin A/CDK2 regulation of Wee1 and FoxM1, as reported by others, combine with the mechanism described here to regulate normal G2/M phase progression and G2 phase checkpoint recovery. These findings support the critical role for cyclin A/CDK2 in regulating progression into mitosis and suggest that upstream regulators of cyclin A/CDK2 activation will also be critical controllers of this cell cycle transition. The pathways that work to co-ordinate cell cycle progression are very intricate and deciphering these pathways, required for normal cell cycle progression, is key to understanding tumour development. By understanding cell cycle regulatory pathways it will allow the identification of the pathway/s and their mechanism/s that become affected in tumourgenesis. This will lead to the development of better targeted therapies, inferring better efficacy with fewer side effects than commonly seen with the use of traditional therapies, such as chemotherapy. Furthermore, this has the potential to positively impact the development of personalised medicines and the customisation of healthcare.

Evaluation of the alkaline comet assay and urinary 3-methyladenine excretion for monitoring DNA damage in melanoma patients treated with dacarbazine and tamoxifen

Purpose: To develop, using dacarbazine as a model, reliable techniques for measuring DNA damage and repair as pharmacodynamic endpoints for patients receiving chemotherapy. Methods: A group of 39 patients with malignant melanoma were treated with dacarbazine 1 g/m2 i.v. every 21 days. Tamoxifen 20 mg daily was commenced 24 h after the first infusion and continued until 3 weeks after the last cycle of chemotherapy. DNA strand breaks formed during dacarbazine-induced DNA damage and repair were measured in individual cells by the alkaline comet assay. DNA methyl adducts were quantified by measuring urinary 3-methyladenine (3-MeA) excretion using immunoaffinity ELISA. Venous blood was taken on cycles 1 and 2 for separation of peripheral blood lymphocytes (PBLs) for measurement of DNA strand breaks. Results: Wide interpatient variation in PBL DNA strand breaks occurred following chemotherapy, with a peak at 4 h (median 26.6 h, interquartile range 14.75- 40.5 h) and incomplete repair by 24 h. Similarly, there was a range of 3-MeA excretion with peak levels 4-10 h after chemotherapy (median 33 nmol/h, interquartile range 20.448.65 nmol/h). Peak 3-MeA excretion was positively correlated with DNA strand breaks at 4 h (Spearman's correlation coefficient, r = 0.39, P = 0.036) and 24 h (r = 0.46, P = 0.01). Drug-induced emesis correlated with PBL DNA strand breaks (Mann Whitney U-test, P = 0.03) but not with peak 3-MeA excretion. Conclusions: DNA damage and repair following cytotoxic chemotherapy can be measured in vivo by the alkaline comet assay and by urinary 3-MeA excretion in patients receiving chemotherapy.

Fatigue damage initiation life prediction for heterogeneous metals

In particle-strengthened metallic alloys, fatigue damage incubates at inclusion particles near the surface or at the change of geometries. Micromechanical simulation of inclusions such that the fatigue damage incubation mechanisms can be categorized. As micro-plasticity gradient field around different inclusions is different, a novel concept for nonlocal evaluation of micro-plasticity intensity is introduced. The effects of void aspects ration and spatial distributions are quantified for fatigue incubation life in the high-cycle fatigue regime. At last, these effects are integrated based on the statistical facts of inclusions to predict the fatigue life of structural components.

Modal flexibility method for structural damage detection in suspension bridges

Suspension bridges meet the steadily growing demand for lighter and longer bridges in today’s infrastructure systems. These bridges are designed to have long life spans, but with age, their main cables and hangers could suffer from corrosion and fatigue. There is a need for a simple and reliable procedure to detect and locate such damage, so that appropriate retrofitting can be carried out to prevent bridge failure. Damage in a structure causes changes in its properties (mass, damping and stiffness) which in turn will cause changes in its vibration characteristics (natural frequencies, modal damping and mode shapes). Methods based on modal flexibility, which depends on both the natural frequencies and mode shapes, have the potential for damage detection. They have been applied successfully to beam and plate elements, trusses and simple structures in reinforced concrete and steel. However very limited applications for damage detection in suspension bridges have been identified to date. This paper examines the potential of modal flexibility methods for damage detection and localization of a suspension bridge under different damage scenarios in the main cables and hangers using numerical simulation techniques. Validated finite element model (FEM) of a suspension bridge is used to acquire mass normalized mode shape vectors and natural frequencies at intact and damaged states. Damage scenarios will be simulated in the validated FE models by varying stiffness of the damaged structural members. The capability of damage index based on modal flexibility to detect and locate damage is evaluated. Results confirm that modal flexibility based methods have the ability to successfully identify damage in suspension bridge main cables and hangers.

Damage detection in cable structures using vibration characteristics

Cable structures find many applications such as in power transmission, in anchors and especially in bridges. They serve as major load bearing elements in suspension bridges, which are capable of spanning long distances. All bridges, including suspension bridges, are designed to have long service lives. However, during this long life, they become vulnerable to damage due to changes in loadings, deterioration with age and random action such as impacts. The main cables are more vulnerable to corrosion and fatigue, compared to the other bridge components, and consequently reduces the serviceability and ultimate capacity of the bridge. Detecting and locating such damage at the earliest stage is challenging in the current structural health monitoring (SHM) systems of long span suspension bridges. Damage or deterioration of a structure alters its stiffness, mass and damping properties which in turn modify its vibration characteristics. This phenomenon can therefore be used to detect damage in a structure. The modal flexibility, which depends on the vibration characteristics of a structure, has been identified as a successful damage indicator in beam and plate elements, trusses and simple structures in reinforced concrete and steel. Successful application of the modal flexibility phenomenon to detect and locate the damage in suspension bridge main cables has received limited attention in recent research work. This paper, therefore examines the potential of the modal flexibility based Damage Index (DI) for detecting and locating damage in the main cable of a suspension bridge under four different damage scenarios. Towards this end, a numerical model of a suspension bridge cable was developed to extract the modal parameters at both damaged and undamaged states. Damage scenarios considered in this study with varied location and severity were simulated by changing stiffness at particular locations of the cable model. Results confirm that the DI has the potential to successfully detect and locate damage in suspension bridge main cables. This simple method can therefore enable bridge engineers and managers to detect and locate damage in suspension bridges at an early stage, minimize expensive retrofitting and prevent bridge collapse.

Effects of wireless sensor network uncertainties on output-only modal-based damage identification

The use of Wireless Sensor Networks (WSNs) for Structural Health Monitoring (SHM) has become a promising approach due to many advantages such as low cost, fast and flexible deployment. However, inherent technical issues such as data synchronization error and data loss have prevented these distinct systems from being extensively used. Recently, several SHM-oriented WSNs have been proposed and believed to be able to overcome a large number of technical uncertainties. Nevertheless, there is limited research examining effects of uncertainties of generic WSN platform and verifying the capability of SHM-oriented WSNs, particularly on demanding SHM applications like modal analysis and damage identification of real civil structures. This article first reviews the major technical uncertainties of both generic and SHM-oriented WSN platforms and efforts of SHM research community to cope with them. Then, effects of the most inherent WSN uncertainty on the first level of a common Output-only Modal-based Damage Identification (OMDI) approach are intensively investigated. Experimental accelerations collected by a wired sensory system on a benchmark civil structure are initially used as clean data before being contaminated with different levels of data pollutants to simulate practical uncertainties in both WSN platforms. Statistical analyses are comprehensively employed in order to uncover the distribution pattern of the uncertainty influence on the OMDI approach. The result of this research shows that uncertainties of generic WSNs can cause serious impact for level 1 OMDI methods utilizing mode shapes. It also proves that SHM-WSN can substantially lessen the impact and obtain truly structural information without having used costly computation solutions.

Cellular stress triggers the human topoisomerase I damage response independently of DNA damage in a p53 controlled manner

The 'human topoisomerase I (htopoI) damage response' was reported to be triggered by various kinds of DNA lesions. Also, a high and persistent level of htopoI cleavage complexes correlated with apoptosis. In the present study, we demonstrate that DNA damage-independent induction of cell death using colcemid and tumor necrosis factor is also accompanied by a strong htopoI response that correlates with the onset of apoptotic hallmarks. Consequently, these results suggest that htopoI cleavage complex formation may be caused by signaling pathways independent of the kind of cellular stress. Thus, protein interactions or signaling cascades induced by DNA damage or cellular stress might lead to the formation of stabilized cleavage complexes rather than the DNA lesion itself. Finally, we show that p53 not only plays a key role in the regulation of the htopoI response to UV-C irradiation but also to treatment with colcemid.

The human topoisomerase I damage response plays a role in apoptosis

Previous studies have shown that human topoisomerase I cleavage complexes form as a response to various DNA damages in vivo, the so called human topoisomerase I “damage response”. It was suggested that this damage response may play a role in DNA repair as well as in apoptosis, but only very few investigations have been done and the significance of the damage response still remains unclear. Here we demonstrate that human topoisomerase I cleavage complexes induced by high doses of UV irradiation are highly stable for up to 48 h. Furthermore, we show that human topoisomerase I cleavage complexes correlate with apoptosis. However, at low UV doses the cleavage complex level was very low and the complexes were repaired. Surprisingly, we found that high levels of stable cleavage complexes were not only found in UV-irradiated cells but also in untreated cells that underwent apoptosis. A possible role of human topoisomerase I in apoptosis is discussed.

Controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.