663 resultados para Response prediction
Resumo:
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.
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An analytical solution is presented in this paper for the vibration response of a ribbed plate clamped on all its boundary edges by employing a travelling wave solution. A clamped ribbed plate test rig is also assembled in this study for the experimental investigation of the ribbed plate response and to provide verification results to the analytical solution. The dynamic characteristics and mode shapes of the ribbed plate are measured and compared to those obtained from the analytical solution and from finite element analysis (FEA). General good agreements are found between the results. Discrepancies between the computational and experimental results at low and high frequencies are also discussed. Explanations are offered in the study to disclose the mechanism causing the discrepancies. The dependency of the dynamic response of the ribbed plate on the distance between the excitation force and the rib is also investigated experimentally. It confirms the findings disclosed in a previous analytical study [T. R. Lin and J. Pan, A closed form solution for the dynamic response of finite ribbed plates. Journal of the Acoustical Society of America 119 (2006) 917-925] that the vibration response of a clamped ribbed plate due to a point force excitation is controlled by the plate stiffness when the source is more than a quarter plate bending wavelength away from the rib and from the plate boundary. The response is largely affected by the rib stiffness when the source location is less than a quarter bending wavelength away from the rib.
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This paper describes the vulnerability of masonry under shear; first the mechanisms of in-plane and out-of-plane shear performance of masonry are reviewed; both the unreinforced and lightly reinforced masonry wall systems are considered. Factors affecting the response of unreinforced and reinforced masonry to shear are described and the effect of the variability of those factors to the failure mode of masonry shear walls is also discussed. Some critique is provided on the existing design provisions in various masonry standards.
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In this paper I examine the recent arguments by Charles Foster, Jonathan Herring, Karen Melham and Tony Hope against the utility of the doctrine of double effect. One basis on which they reject the utility of the doctrine is their claim that it is notoriously difficult to apply what they identify as its 'core' component, namely, the distinction between intention and foresight. It is this contention that is the primarily focus of my article. I argue against this claim that the intention/foresight distinction remains a fundamental part of the law in those jurisdictions where intention remains an element of the offence of murder and that, accordingly, it is essential ro resolve the putative difficulties of applying the intention/foresight distinction so as to ensure the integrity of the law of murder. I argue that the main reasons advanced for the claim that the intention/foresight distinction is difficult to apply are ultimately unsustainable, and that the distinction is not as difficult to apply as the authors suggest.
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Corrosion is a common phenomenon and critical aspects of steel structural application. It affects the daily design, inspection and maintenance in structural engineering, especially for the heavy and complex industrial applications, where the steel structures are subjected to hash corrosive environments in combination of high working stress condition and often in open field and/or under high temperature production environments. In the paper, it presents the actual engineering application of advanced finite element methods in the predication of the structural integrity and robustness at a designed service life for the furnaces of alumina production, which was operated in the high temperature, corrosive environments and rotating with high working stress condition.
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Photochemistry has made significant contributions to our understanding of many important natural processes as well as the scientific discoveries of the man-made world. The measurements from such studies are often complex and may require advanced data interpretation with the use of multivariate or chemometrics methods. In general, such methods have been applied successfully for data display, classification, multivariate curve resolution and prediction in analytical chemistry, environmental chemistry, engineering, medical research and industry. However, in photochemistry, by comparison, applications of such multivariate approaches were found to be less frequent although a variety of methods have been used, especially with spectroscopic photochemical applications. The methods include Principal Component Analysis (PCA; data display), Partial Least Squares (PLS; prediction), Artificial Neural Networks (ANN; prediction) and several models for multivariate curve resolution related to Parallel Factor Analysis (PARAFAC; decomposition of complex responses). Applications of such methods are discussed in this overview and typical examples include photodegradation of herbicides, prediction of antibiotics in human fluids (fluorescence spectroscopy), non-destructive in- and on-line monitoring (near infrared spectroscopy) and fast-time resolution of spectroscopic signals from photochemical reactions. It is also quite clear from the literature that the scope of spectroscopic photochemistry was enhanced by the application of chemometrics. To highlight and encourage further applications of chemometrics in photochemistry, several additional chemometrics approaches are discussed using data collected by the authors. The use of a PCA biplot is illustrated with an analysis of a matrix containing data on the performance of photocatalysts developed for water splitting and hydrogen production. In addition, the applications of the Multi-Criteria Decision Making (MCDM) ranking methods and Fuzzy Clustering are demonstrated with an analysis of water quality data matrix. Other examples of topics include the application of simultaneous kinetic spectroscopic methods for prediction of pesticides, and the use of response fingerprinting approach for classification of medicinal preparations. In general, the overview endeavours to emphasise the advantages of chemometrics' interpretation of multivariate photochemical data, and an Appendix of references and summaries of common and less usual chemometrics methods noted in this work, is provided. Crown Copyright © 2010.
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BACKGROUND:Chlamydia trachomatis is a major cause of sexually transmitted disease in humans. Previous studies in both humans and animal models of chlamydial genital tract infection have suggested that the hormonal status of the genital tract epithelium at the time of exposure can influence the outcome of the chlamydial infection. We performed a whole genome transcriptional profiling study of C. trachomatis infection in ECC-1 cells under progesterone or estradiol treatment.RESULTS:Both hormone treatments caused a significant shift in the sub-set of genes expressed (25% of the transcriptome altered by more than 2-fold). Overall, estradiol treatment resulted in the down-regulation of 151 genes, including those associated with lipid and nucleotide metabolism. Of particular interest was the up-regulation in estradiol-supplemented cultures of six genes (omcB, trpB, cydA, cydB, pyk and yggV), which suggest a stress response similar to that reported previously in other models of chlamydial persistence. We also observed morphological changes consistent with a persistence response. By comparison, progesterone supplementation resulted in a general up-regulation of an energy utilising response.CONCLUSION:Our data shows for the first time, that the treatment of chlamydial host cells with key reproductive hormones such as progesterone and estradiol, results in significantly altered chlamydial gene expression profiles. It is likely that these chlamydial expression patterns are survival responses, evolved by the pathogen to enable it to overcome the host's innate immune response. The induction of chlamydial persistence is probably a key component of this survival response.
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Our cross-national field study of wine entrepreneurship in the “wrong” places provides some redress to the focus of the “regional advantage” literature on places that have already won and on the firms that benefit from “clusters” and other centers of industry advantage. Regional “disadvantage” is at best a shadowy afterthought to this literature. By poking around in these shadows, we help to synthesize and extend the incipient yet burgeoning literature on entrepreneurial “resourcefulness” and we contribute to the developing body of insights and theory pertinent to the numerous but often ignored firms and startups that mostly need to worry about how they will compete at all now if they are ever to have of chance of “winning” in the future. The core of our findings suggests that understandable – though contested – processes of ingenuity underlie entrepreneurial responses to regional disadvantage. Because we study entrepreneurship that from many angles simply does not make sense, we are also able to proffer a novel perspective on entrepreneurial sensemaking.
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Anthropometry is a simple and cost-efficient method for the assessment of body composition. However prediction equations to estimate body composition using anthropometry should be ‘population-specific’. Most popular body composition prediction equations for Japanese females were proposed more than 40 years ago and there is some concern regarding their usefulness in Japanese females living today. The aim of this study was to compare percentage body fat (%BF) estimated from anthropometry and dual energy x-ray absorptiometry (DXA) to examine the applicability of commonly used prediction equations in young Japanese females. Body composition of 139 Japanese females aged between 18 and 27 years of age (BMI range: 15.1–29.1 kg/m2) was measured using whole-body DXA (Lunar DPX-LIQ) scans. From anthropometric measurements %BF was estimated using four equations developed from Japanese females. The results showed that the traditionally employed prediction equations for anthropometry significantly (p<0.01) underestimate %BF of young Japanese females and therefore are not valid for the precise estimation of body composition. New %BF prediction equations were proposed from the DXA and anthropometry results. Application of the proposed equations may assist in more accurate assessment of body fatness in Japanese females living today.
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The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology
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The Bcl-2-associated athanogene (BAG) family is an evolutionarily conserved, multifunctional group of cochaperones that perform diverse cellular functions ranging from proliferation to growth arrest and cell death in yeast, in mammals, and, as recently observed, in plants. The Arabidopsis genome contains seven homologs of the BAG family, including four with domain organization similar to animal BAGs. In the present study we show that an Arabidopsis BAG, AtBAG7, is a uniquely localized endoplasmic reticulum (ER) BAG that is necessary for the proper maintenance of the unfolded protein response (UPR). AtBAG7was shown to interact directly in vivo with themolecular chaperone, AtBiP2, by bimolecular fluorescence complementation assays, and the interaction was confirmed by yeast two-hybrid assay. Treatment with an inducer of UPR, tunicamycin, resulted in accelerated cell death of AtBAG7-null mutants. Furthermore, AtBAG7 knockouts were sensitive to known ER stress stimuli, heat and cold. In these knockouts heat sensitivity was reverted successfully to the wild-type phenotype with the addition of the chemical chaperone, tauroursodexycholic acid (TUDCA). Real-time PCR of ER stress proteins indicated that the expression of the heat-shock protein, AtBiP3, is selectively up-regulated in AtBAG7-null mutants upon heat and cold stress. Our results reveal an unexpected diversity of the plant's BAG gene family and suggest that AtBAG7 is an essential component of the UPR during heat and cold tolerance, thus confirming the cytoprotective role of plant BAGs.
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Partially grouted wider reinforced masonry wall, built predominantly using face shell bedded hollow concrete blocks, is an economical structural system and is popularly used in the cyclonic areas; its out-of-plane response to lateral loading is well understood, unfortunately its inplane shear behaviour is less well understood as to the effect of partial gouting in intervening the load paths within the wall. For rational analysis of the wall clarification is sought as to whether the wall acts as a composite of unreinforced panels and reinforced cores or as a continuum of masonry embedded with reinforced at wider spacing. This paper reports the results of four full scale walls tested under inplane cyclic shear loading to provide some insight into the effect of the grout cores in altering the load paths within the wall. The global lateral load - lateral deflection hysteric curves as well as local responses of some critical zones of the shear walls are presented.
Evaluation cortical bone elasticity in response to pulse power excitation using ultrasonic technique
Resumo:
This paper presents the ultrasonic velocity measurement method which investigates the possible effects of high voltage high frequency pulsed power on cortical bone material elasticity. Before applying a pulsed power signal on a live bone, it is essential to determine the safe parameters of pulsed power applied on bone non-destructively. Therefore, the possible changes in cortical bone material elasticity due to a specified pulsed power excitation have been investigated. A controllable positive buck-boost converter with adjustable output voltage and frequency has been used to generate high voltage pulses (500V magnitude at 10 KHz frequency). To determine bone elasticity, an ultrasonic velocity measurement has been conducted on two groups of control (unexposed to pulse power but in the same environmental condition) and cortical bone samples exposed to pulsed power. Young’s modulus of cortical bone samples have been determined and compared before and after applying the pulsed power signal. After applying the high voltage pulses, no significant variation in elastic property of cortical bone specimens was found compared to the control. The result shows that pulsed power with nominated parameters can be applied on cortical bone tissue without any considerable negative effect on elasticity of bone material.
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Associations between young children's attributions of emotion at different points in a story, and with regard to their own prediction about the story's outcome, were investigated using two hypothetical scenarios of social and emotional challenge (social entry and negative event). First grade children (N = 250) showed an understanding that emotions are tied to situational cues by varying the emotions they attributed both between and within scenarios. Furthermore, emotions attributed to the main protagonist at the beginning of the scenarios were differentially associated with children's prediction of a positive or negative outcome and with the valence of the emotion attributed at the end of the scenario. Gender differences in responses to some items were also found. © 2010 The British Psychological Society.
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This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.