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.

Bcl-2 genes and growth factors in the pathology of ischaemic acute renal failure

For the past decade, an attempt has been made by many research groups to define the roles of the growing number of Bcl-2 gene family proteins in the apoptotic process. The Bcl-2 family consists of pro-apoptotic (or cell death) and anti-apoptotic (or cell survival) genes and it is the balance in expression between these gene lineages that may determine the death or survival of a cell. The majority of studies have analysed the role/s of the Bcl-2 genes in cancer development. Equally important is their role in normal tissue development, homeostasis and non-cancer disease states. Bcl-2 is crucial for normal development in the kidney, with a deficiency in Bcl-2 producing such malformation that renal failure and death result. As a corollary, its role in renal disease states in the adult has been sought. Ischaemia is one of the most common causes of both acute and chronic renal failure. The section of the kidney that is most susceptible to ischaemic damage is the outer zone of the outer medulla. Within this zone the proximal tubules are most sensitive and often die by necrosis or desquamate. In the distal nephron, apoptosis is the more common form of cell death. Recent results from our laboratory have indicated that ischaemia-induced acute renal failure is associated with up-regulation of two anti-apoptotic Bcl-2 proteins (Bcl-2 and Bcl-XL) in the damaged distal tubule and occasional up-regulation of Bax in the proximal tubule. The distal tubule is a known reservoir for several growth factors important to renal growth and repair, such as insulin-like growth factor-1 (IGF-1) and epidermal growth factor (EGF). One of the likely possibilities for the anti-cell death action of the Bcl-2 genes is that the protected distal cells may be able to produce growth factors that have a further reparative or protective role via an autocrine mechanism in the distal segment and a paracrine mechanism in the proximal cells. Both EGF and IGF-1 are also up-regulated in the surviving distal tubules and are detected in the surviving proximal tubules, where these growth factors are not usually synthesized. As a result, we have been using in vitro methods to test: (i) the relative sensitivities of renal distal and proximal epithelial cell populations to injury caused by mechanisms known to act in ischaemia-reperfusion; (ii) whether a Bcl-2 anti-apoptotic mechanism acts in these cells; and (iii) whether an autocrine and/or paracrine growth factor mechanism is initiated. The following review discusses the background to these studies as well as some of our preliminary results.

Interleukin-1β stimulates human renal fibroblast proliferation and matrix protein production by means of a transforming growth factor-β-dependent mechanism

One of the hallmarks of progressive renal disease is the development of tubulointerstitial fibrosis. This is frequently preceded by macrophage infiltration, raising the possibility that macrophages relay fibrogenic signals to resident tubulointerstitial cells. The aim of this study was to investigate the potentially fibrogenic role of interleukin-1beta (IL-1beta), a macrophage-derived inflammatory cytokine, on cortical fibroblasts (CFs). Primary cultures of human renal CFs were established and incubated for 24 hours in the presence or absence of IL-1beta. We found that IL-1beta significantly stimulated DNA synthesis (356.7% +/- 39% of control, P <.003), fibronectin secretion (261.8 +/- 11% of control, P <.005), collagen type 1 production, (release of procollagen type 1 C-terminal-peptide, 152.4% +/- 26% of control, P <.005), transforming growth factor-beta (TGF-beta) secretion (211% +/- 37% of control, P <.01), and nitric oxide (NO) production (342.8% +/- 69% of control, P <.002). TGF-beta (1 ng/mL) and the phorbol ester phorbol 12-myristate 13-acetate (PMA, 25 nmol/L) produced fibrogenic effects similar to those of IL-1beta. Neither a NO synthase inhibitor (N(G)-methyl-l-arginine, 1 mmol/L) nor a protein kinase C (PKC) inhibitor (bis-indolylmaleimide 1, 1 micromol/L) altered the enhanced level of fibronectin secretion or DNA synthesis seen in response to IL-1beta treatment. However, addition of a TGF-beta-neutralizing antibody significantly reduced IL-1beta-induced fibronectin secretion (IL-1beta + IgG, 262% +/- 72% vs IL-1beta + alphaTGF-beta 156% +/- 14%, P <.02), collagen type 1 production (IL-1beta + IgG, 176% +/- 28% vs IL-1beta + alphaTGF-beta, 120% +/- 14%, P <.005) and abrogated IL-1beta-induced DNA synthesis (245% +/- 49% vs 105% +/- 21%, P <.005). IL-1beta significantly stimulated CF DNA synthesis and production of fibronectin, collagen type 1, TGFbeta, and NO. The fibrogenic and proliferative action of IL-1beta on CF appears not to involve activation of PKC or production of NO but is at least partly TGFbeta-dependent.

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.

Emissions trading and the GATS financial services provisions : a case study of the Australian carbon pricing mechanism

Purpose The purpose of this paper is to determine whether greenhouse gas (GHG) tradeable instruments will be classified as financial products within the scope of the World Trade Organization (WTO) law and to explore the implications of this finding. Design/methodology/approach This purpose is achieved through examination of the units of the Australian Carbon Pricing Mechanism (CPM), namely eligible emissions units. These units are analysed through the lens of the definition of financial products provided in the General Agreement for Trade in Services (the GATS). Findings This paper finds that eligible emissions units will be classified as financial instruments, and therefore the provisions that govern their trade will be regulated by the GATS. Considering this, this paper explores the limitations that are introduced by the Australian legislation on the trade of eligible emissions units. Research limitations/implications This paper is limited in its analysis to the Australian CPM. In order to draw conclusions on the issues raised by this analysis it is necessary to consider the WTO requirements against an operating emissions trading scheme. The Australian CPM presents a contemporary model of an appropriate scheme. Originality/value The findings in this paper are crucial in a GHG constrained society. This is because emissions trading schemes are becoming popular measures for pricing GHG emissions, and for this reason the units that are traded and surrendered for emissions liabilities must be classified appropriately on a global scale. Failing to do this could result in differential treatment that may be contrary to the intentions of important global agreements, such as the WTO covered agreements.

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.

Process modelling and simulation of tissue damage during mechanical peeling of pumpkin as a tough skinned vegetable

Food waste is a current challenge that both developing and developed countries face. This project applied a novel combination of available methods in Mechanical, agricultural and food engineering to address these challenges. A systematic approach was devised to investigate possibilities of reducing food waste and increasing the efficiency of industry by applying engineering concepts and theories including experimental, mathematical and computational modelling methods. This study highlights the impact of comprehensive understanding of agricultural and food material response to the mechanical operations and its direct relation to the volume of food wasted globally.

Vulnerability and damage analysis of reinforced concrete framed buildings subjected to near field blast events

Terrorists usually target high occupancy iconic and public buildings using vehicle borne incendiary devices in order to claim a maximum number of lives and cause extensive damage to public property. While initial casualties are due to direct shock by the explosion, collapse of structural elements may extensively increase the total figure. Most of these buildings have been or are built without consideration of their vulnerability to such events. Therefore, the vulnerability and residual capacity assessment of buildings to deliberately exploded bombs is important to provide mitigation strategies to protect the buildings' occupants and the property. Explosive loads and their effects on a building have therefore attracted significant attention in the recent past. Comprehensive and economical design strategies must be developed for future construction. This research investigates the response and damage of reinforced concrete (RC) framed buildings together with their load bearing key structural components to a near field blast event. Finite element method (FEM) based analysis was used to investigate the structural framing system and components for global stability, followed by a rigorous analysis of key structural components for damage evaluation using the codes SAP2000 and LS DYNA respectively. The research involved four important areas in structural engineering. They are blast load determination, numerical modelling with FEM techniques, material performance under high strain rate and non-linear dynamic structural analysis. The response and damage of a RC framed building for different blast load scenarios were investigated. The blast influence region for a two dimensional RC frame was investigated for different load conditions and identified the critical region for each loading case. Two types of design methods are recommended for RC columns to provide superior residual capacities. They are RC columns detailing with multi-layer steel reinforcement cages and a composite columns including a central structural steel core. These are to provide post blast gravity load resisting capacity compared to typical RC column against a catastrophic collapse. Overall, this research broadens the current knowledge of blast and residual capacity analysis of RC framed structures and recommends methods to evaluate and mitigate blast impact on key elements of multi-storey buildings.

A recurrent network in the lateral amygdala : a mechanism for coincidence detection

Synaptic changes at sensory inputs to the dorsal nucleus of the lateral amygdala (LAd) play a key role in the acquisition and storage of associative fear memory. However, neither the temporal nor spatial architecture of the LAd network response to sensory signals is understood. We developed a method for the elucidation of network behavior. Using this approach, temporally patterned polysynaptic recurrent network responses were found in LAd (intra-LA), both in vitro and in vivo, in response to activation of thalamic sensory afferents. Potentiation of thalamic afferents resulted in a depression of intra-LA synaptic activity, indicating a homeostatic response to changes in synaptic strength within the LAd network. Additionally, the latencies of thalamic afferent triggered recurrent network activity within the LAd overlap with known later occurring cortical afferent latencies. Thus, this recurrent network may facilitate temporal coincidence of sensory afferents within LAd during associative learning.

Mechanism based emulation of dynamic simulation models : concept and application in hydrology

Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emulators, by providing efficient interpolation between outputs of deterministic simulation models, can considerably extend the field of applicability of such computationally demanding techniques. So far, the dominant techniques for developing emulators have been priors in the form of Gaussian stochastic processes (GASP) that were conditioned with a design data set of inputs and corresponding model outputs. In the context of dynamic models, this approach has two essential disadvantages: (i) these emulators do not consider our knowledge of the structure of the model, and (ii) they run into numerical difficulties if there are a large number of closely spaced input points as is often the case in the time dimension of dynamic models. To address both of these problems, a new concept of developing emulators for dynamic models is proposed. This concept is based on a prior that combines a simplified linear state space model of the temporal evolution of the dynamic model with Gaussian stochastic processes for the innovation terms as functions of model parameters and/or inputs. These innovation terms are intended to correct the error of the linear model at each output step. Conditioning this prior to the design data set is done by Kalman smoothing. This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small. The feasibility and potential difficulties of the proposed approach are demonstrated by the application to a simple hydrological model.

A multi-scaling approach to predict hydraulic damage of poromaterials

The purpose of this paper is to introduce the concept of hydraulic damage and its numerical integration. Unlike the common phenomenological continuum damage mechanics approaches, the procedure introduced in this paper relies on mature concepts of homogenization, linear fracture mechanics, and thermodynamics. The model is applied to the problem of fault reactivation within resource reservoirs. The results show that propagation of weaknesses is highly driven by the contrasts of properties in porous media. In particular, it is affected by the fracture toughness of host rocks. Hydraulic damage is diffused when it takes place within extended geological units and localized at interfaces and faults.