450 resultados para Damage Identification
Resumo:
Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.
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We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.
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This report presents observations, findings, and recommendations from an engineering reconnaissance trip following the May 20th, 2013 tornado that struck Moore, Oklahoma. A team of faculty, research scientists, professional engineers, and civil engineering students were tasked with investigating and documenting the performance of critical facility buildings and residences, (IBC Occupancy Category II, III, and IV), in Moore, OK. The Enhanced Fujita (EF) 5 tornado created a 17-mile long damage swath destroying over 12,000 buildings and killing 24 people. The total economic loss from this single event was estimated at $3 billion. The May 20th tornado was the third major tornado to hit Moore in the previous 15 years.
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This study investigated interactions of protein-cleaving enzymes (or proteases) that promote prostate cancer progression. It provides the first evidence of a novel regulatory network of protease activity at the surface of cells. The proteases kallikrein-related peptidases 4 and 14, and matrix metalloproteinases 3 and 9 are cleaved at the cell surface by the cell surface proteases hepsin and TMPRSS2. These cleavage events potentially regulate activation of downstream targets of kallikrein 4 and 14 such as cell surface signalling via the protease-activated receptors (PARs) and cell growth-promoting factors such as hepatocyte-growth factor.
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Children are particularly susceptible to air pollution and schools are examples of urban microenvironments that can account for a large portion of children’s exposure to airborne particles. Thus this paper aimed to determine the sources of primary airborne particles that children are exposed to at school by analyzing selected organic molecular markers at 11 urban schools in Brisbane, Australia. Positive matrix factorization analysis identified four sources at the schools: vehicle emissions, biomass burning, meat cooking and plant wax emissions accounting for 45%, 29%, 16% and 7%, of the organic carbon respectively. Biomass burning peaked in winter due to prescribed burning of bushland around Brisbane. Overall, the results indicated that both local (traffic) and regional (biomass burning) sources of primary organic aerosols influence the levels of ambient particles that children are exposed at the schools. These results have implications for potential control strategies for mitigating exposure at schools.
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This thesis in software engineering presents a novel automated framework to identify similar operations utilized by multiple algorithms for solving related computing problems. It provides a new effective solution to perform multi-application based algorithm analysis, employing fundamentally light-weight static analysis techniques compared to the state-of-art approaches. Significant performance improvements are achieved across the objective algorithms through enhancing the efficiency of the identified similar operations, targeting discrete application domains.
Resumo:
Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.
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A major virulence factor for Yersinia pseudotuberculosis is lipopolysaccharide, including O-polysaccharide (OPS). Currently, the OPS based serotyping scheme for Y. pseudotuberculosis includes 21 known O-serotypes, with genetic and structural data available for 17 of them. The completion of the OPS structures and genetics of this species will enable the visualization of relationships between O-serotypes and allow for analysis of the evolutionary processes within the species that give rise to new serotypes. Here we present the OPS structure and gene cluster of serotype O:12, thus adding one more to the set of completed serotypes, and show that this serotype is present in both Y. pseudotuberculosis and the newly identified Y. similis species. The O:12 structure is shown to include two rare sugars: 4-C[(R)-1-hydroxyethyl]-3,6-dideoxy-d-xylo-hexose (d-yersiniose) and 6-deoxy-l-glucopyranose (l-quinovose). We have identified a novel putative guanine diphosphate (GDP)-l-fucose 4-epimerase gene and propose a pathway for the synthesis of GDP-l-quinovose, which extends the known GDP-l-fucose pathway.
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It has been well established nationally and internationally that fatigue-related driving is an important contributory factor in fatal and serious injury crashes. The purpose of this report was to survey a large, representative sample of residents living in both the NSW and ACT to ask about their experience of fatigue and their involvement in fatigue-related crashes and incidents. This will provide valuable data about the number and characteristics of fatigue-related crashes and incidents of ACT residents. Specifically this study assessed the prevalence of incidents of fatigue-related driving for residents of NSW and the ACT, the characteristics surrounding the incident, if the report would fit within the NSW, QLD, or ATSB proxy definition or if it would fall outside of the proxy definition...
Resumo:
Purpose To compare small nerve fiber damage in the central cornea and whorl area in participants with diabetic peripheral neuropathy (DPN) and to examine the accuracy of evaluating these 2 anatomical sites for the diagnosis of DPN. Methods A cohort of 187 participants (107 with type 1 diabetes and 80 controls) was enrolled. The neuropathy disability score (NDS) was used for the identification of DPN. The corneal nerve fiber length at the central cornea (CNFLcenter) and whorl (CNFLwhorl) was quantified using corneal confocal microscopy and a fully automated morphometric technique and compared according to the DPN status. Receiver operating characteristic analyses were used to compare the accuracy of the 2 corneal locations for the diagnosis of DPN. Results CNFLcenter and CNFLwhorl were able to differentiate all 3 groups (diabetic participants with and without DPN and controls) (P < 0.001). There was a weak but significant linear relationship for CNFLcenter and CNFLwhorl versus NDS (P < 0.001); however, the corneal location x NDS interaction was not statistically significant (P = 0.17). The area under the receiver operating characteristic curve was similar for CNFLcenter and CNFLwhorl (0.76 and 0.77, respectively, P = 0.98). The sensitivity and specificity of the cutoff points were 0.9 and 0.5 for CNFLcenter and 0.8 and 0.6 for CNFLwhorl. Conclusions Small nerve fiber pathology is comparable at the central and whorl anatomical sites of the cornea. Quantification of CNFL from the corneal center is as accurate as CNFL quantification of the whorl area for the diagnosis of DPN.
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Summary This manual was developed to guide a move towards common standards for undertaking and reporting research microscopy for malaria parasite detection, identification and quantification. It contains procedures based on agreed quality assurance standards for research malaria microscopy defined at a consultation of: TDR, the Special Programme for Research and Training in Tropical Diseases; the Worldwide Antimalarial Resistance Network (WWARN), United Kingdom; the Foundation for Innovative New Diagnostics (FIND), Switzerland; the Centers for Disease Control and Prevention (CDC), USA; the Kenya Medical Research Institute (KEMRI) and later expanded to include Amref Health Africa (Kenya); the Eijkman-Oxford Clinical Research Unit (EOCRU), Indonesia; Institut Pasteur du Cambodge (IPC); Institut de recherche pour le Développement (IRD), Senegal; the Global Good and Intellectual Ventures Laboratory (GG-IVL), USA; the Mahidol-Oxford Tropical Medicine Research Unit (MORU), Thailand; Queensland University of Technology (QUT), Australia, and the Shoklo Malaria Research Unit (SMRU), Thailand. These collaborating institutions commit to adhering to these standards in published research studies. It is hoped that they will form a solid basis for the wider adoption of standardized reference microscopy protocols for malaria research.
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Germline mutations in BRCA1 predispose carriers to a high incidence of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through critical roles in DNA repair, cell cycle arrest and transcriptional control. A major question has been why BRCA1 loss or mutation leads to tumors mainly in estrogen-regulated tissues, given that BRCA1 has essential functions in all cell types. Here we report that estrogen and estrogen metabolites can cause DNA double strand breaks (DSB) in estrogen receptor-α negative breast cells and that BRCA1 is required to repair these DSBs to prevent metabolite-induced genomic instability. We found that BRCA1 also regulates estrogen metabolism and metabolite-mediated DNA damage by repressing the transcription of estrogen-metabolising enzymes, such as CYP1A1, in breast cells. Lastly, we used a knock-in human cell model with a heterozygous BRCA1 pathogenic mutation to show how BRCA1 haploinsufficiency affects these processes. Our findings provide pivotal new insights into why BRCA1 mutation drives the formation of tumours in estrogen-regulated tissues, despite the general role of BRCA1 in DNA repair in all cell types.
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Platinum chemotherapeutic agents such as cisplatin are currently used in the treatment of various malignancies such as lung cancer. However, their efficacy is significantly hindered by the development of resistance during treatment. While a number of factors have been reported that contribute to the onset of this resistance phenotype, alterations in the DNA repair capacity of damaged cells is now recognised as an important factor in mediating this phenomenon. The mode of action of cisplatin has been linked to its ability to crosslink purine bases on the DNA, thereby interfering with DNA repair mechanisms and inducing DNA damage. Following DNA damage, cells respond by activating a DNA-damage response that either leads to repair of the lesion by the cell thereby promoting resistance to the drug, or cell death via activation of the apoptotic response. Therefore, DNA repair is a vital target to improving cancer therapy and reduce the resistance of tumour cells to DNA damaging agents currently used in the treatment of cancer patients. To date, despite the numerous findings that differential expression of components of the various DNA repair pathways correlate with response to cisplatin, translation of such findings in the clinical setting are still warranted. The identification of alterations in specific proteins and pathways that contribute to these unique DNA repair pathways in cisplatin resistant cancer cells may potentially lead to a renewed interest in the development of rational novel therapies for cisplatin resistant cancers, in particular, lung cancer.