Advanced eddy current test signal analysis for steam generator tube defect classification and characterization

Eddy Current Testing (ECT) is a Non-Destructive Examination (NDE) technique that is widely used in power generating plants (both nuclear and fossil) to test the integrity of heat exchanger (HX) and steam generator (SG) tubing. Specifically for this research, laboratory-generated, flawed tubing data were examined The tubing data were acquired from the EPRI NDE Center, Charlotte, NC. The data are catalogued in the Performance Demonstration Database (POD) which is used as a training manual for certification. The specific subset of the data used in this dissertation has an Examination Technique Specification Sheet (ETSS) and a blueprint of the flawed tube specimens. The purpose of this dissertation is to develop and implement an automated method for the classification and an advanced characterization of defects in HX and SG tubing. These two improvements enhanced the robustness of characterization as compared to traditional bobbin-coil ECT data analysis methods. A more robust classification and characterization of the tube flaw insitu (while the SG is on-line but not when the plant is operating), should provide valuable information to the power industry. The following is a summary of the original contributions of this dissertation research. 1. Development of a feature extraction program acquiring relevant information from both the mixed, absolute and differential ECTD Flaw Signal (ECTDFS). 2. Application of the Continuous Wavelet Transformation (CWT) to extract more information from the mixed, complex differential ECTDFS. 3. Utilization of Image Processing (IP) techniques to extract the information contained in the generated CWT. 4. Classification of the ECTDFSs, using the compressed feature vector and a Bayes classification system. 5. Development of an upper bound for the probability of classification error, using the Bhattacharyya distance, for the Bayesian classification. 6. Tube defect characterization based on the classified flaw-type to enhance characterization 7. Development of a diagnostic software system EddyC and user\u27s guide. The important results of the application of the method are listed. The CWT contains at least enough information to correctly classify the flaws 64% of the time using the IP features. The Bayes classification system, using only the CWT generated features (after PCA compression), correctly identified 64% of the ECTD flaws. The Bayes classification system correctly identified 7 5% of the ECTD flaws using cross validation utilizing all the generated features after PCA compression. Initial template matching results (from the PDD database) yielded correct classification of 69%. The B-distances parallel and bound the percent misclassified cases. The calculated B-distance for 15 PCs were O and 14.22% bounding the 1.1% incorrectly classified. But, these Gaussian-based calculated B-distances may be inaccurate due to non-Gaussian features. The number of outliers seems to have an inverse relationship with the number of misclassifications. Characterization yielded an average error of 12.76 %. This excluded the results from flaw-type 1 (Thinning). The following are the conclusions reached from this research. A feature extraction program acquiring relevant information from both the mixed, absolute and differential data was successfully implemented. The CWT was utilized to extract more information from the mixed, complex differential data. Image Processing techniques used to extract the information contained in the generated CWT, classified the data with a high success rate. The data were accurately classified, utilizing the compressed feature vector and using a Bayes classification system. An estimation of the upper bound for the probability of error, using the Bhattacharyya distance, was successfully applied to the Bayesian classification. The classified data were separated according to flaw-type (classification) to enhance characterization. The characterization routine used dedicated, flaw-type specific ANNs that made the characterization of the tube flaw more robust. The inclusion of outliers may help complete the feature space so that classification accuracy is increased. Given that the eddy current test signals appear very similar, there may not be sufficient information to make an extremely accurate (\u3e 95%) classification or an advanced characterization using this system. It is necessary to have a larger database fore more accurate system learning

Sleep Induction by Mechanosensory Stimulation in Drosophila.

People tend to fall asleep when gently rocked or vibrated. Experimental studies have shown that rocking promotes sleep in humans and mice. However, the mechanisms underlying the phenomenon are not well understood. A habituation model proposes that habituation, a form of non-associative learning, mediates sleep induction by monotonous stimulation. Here, we show that gentle vibration promotes sleep in Drosophila in part through habituation. Vibration-induced sleep (VIS) leads to increased homeostatic sleep credit and reduced arousability, and can be suppressed by heightened arousal or reduced GABA signaling. Multiple mechanosensory organs mediate VIS, and the magnitude of VIS depends on vibration frequency and genetic background. Sleep induction improves over successive blocks of vibration. Furthermore, training with continuous vibration does not generalize to intermittent vibration, demonstrating stimulus specificity, a characteristic of habituation. Our findings suggest that habituation plays a significant role in sleep induction by vibration

Localization and abundance analysis of human lncRNAs at single-cell and single-molecule resolution

Background: Long non-coding RNAs (lncRNAs) have been implicated in diverse biological processes. In contrast to extensive genomic annotation of lncRNA transcripts, far fewer have been characterized for subcellular localization and cell-to-cell variability. Addressing this requires systematic, direct visualization of lncRNAs in single cells at single-molecule resolution. Results: We use single-molecule RNA-FISH to systematically quantify and categorize the subcellular localization patterns of a representative set of 61 lncRNAs in three different cell types. Our survey yields high-resolution quantification and stringent validation of the number and spatial positions of these lncRNA, with an mRNA set for comparison. Using this highly quantitative image-based dataset, we observe a variety of subcellular localization patterns, ranging from bright sub-nuclear foci to almost exclusively cytoplasmic localization. We also find that the low abundance of lncRNAs observed from cell population measurements cannot be explained by high expression in a small subset of ‘jackpot’ cells. Additionally, nuclear lncRNA foci dissolve during mitosis and become widely dispersed, suggesting these lncRNAs are not mitotic bookmarking factors. Moreover, we see that divergently transcribed lncRNAs do not always correlate with their cognate mRNA, nor do they have a characteristic localization pattern. Conclusions: Our systematic, high-resolution survey of lncRNA localization reveals aspects of lncRNAs that are similar to mRNAs, such as cell-to-cell variability, but also several distinct properties. These characteristics may correspond to particular functional roles. Our study also provides a quantitative description of lncRNAs at the single-cell level and a universally applicable framework for future study and validation of lncRNAs. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0586-4) contains supplementary material, which is available to authorized users

Topological organization of multichromosomal regions by the long intergenic noncoding RNA Firre

RNA, including long noncoding RNA (lncRNA), is known to be an abundant and important structural component of the nuclear matrix. However, the molecular identities, functional roles and localization dynamics of lncRNAs that influence nuclear architecture remain poorly understood. Here, we describe one lncRNA, Firre, that interacts with the nuclear-matrix factor hnRNPU through a 156-bp repeating sequence and localizes across an ~5-Mb domain on the X chromosome. We further observed Firre localization across five distinct trans-chromosomal loci, which reside in spatial proximity to the Firre genomic locus on the X chromosome. Both genetic deletion of the Firre locus and knockdown of hnRNPU resulted in loss of colocalization of these trans-chromosomal interacting loci. Thus, our data suggest a model in which lncRNAs such as Firre can interface with and modulate nuclear architecture across chromosomes

Automated Analysis Of Experience-Dependent Sensory Response Behavior In Caenorhabditis Elegans

Understanding how the internal state of an organism affects its response to stimuli is an important question of biology and key to understanding human neurobehavioral problems. With its tractable 302 neuron nervous system and complex behavioral repertoire, the roundworm Caenorhabditis elegans is well suited for neurobehavioral studies. In this work, I investigate the modulation of C. elegans touch response. The traditional gentle and harsh (nociceptive) touch assays involve manually delivering a stimulus to 1 mm long animals using an eyebrow or a metal wire, respectively. Using these simple assays, researchers have identified the genes and mechanoreceptor neurons mediating gentle and harsh touch. However, these are two separate manual assays limited in throughput and repeatability of the stimulus. First, I created a multiplexed microfluidic assay that allows gentle and harsh touch response behavior to be compared quantitatively in the same assay. I found that the threshold of harsh touch is about five times the threshold of gentle touch and that, while both responses habituate to repeated stimuli, the gentle touch response depends on the location of the previous touch, while the harsh touch response does not. I also found that gentle touch response is not affected by pre-stimulus velocity. Neuromodulatory states like sleep and stress can also affect touch response. Next, I examined how the response to cellular stressors, which causes an EGF-mediated recovery quiescence called stress-induced sleep (SIS), affects the mechanosensory response. Normally touch causes increased locomotor activity followed by return to baseline behavior. During this study, I observed a period of about 45 seconds of increased quiescence following the initial locomotor response. This behavior had not been documented in the literature, so I named it post-response quiescence (PRQ). I found that PRQ is upregulated following EGF overexpression, mediated, like sleep, by neuropeptide signaling, and requires the sleep active neurons ALA and RIS. While these observations suggested a form of sleep homeostasis, I found that PRQ does not meet two of the four behavioral criteria of sleep: it is not accompanied by a decrease in arousability, and it is not itself under homeostatic regulation. C. elegans touch response is known to be an escape response, and the presence of predator kairomone is known to affect C. elegans behavior. Because of the prevalence of quiescent behavior (freezing and tonic immobility) in vertebrate threat responses, and its upregulation during stress, I argue that PRQ may be a stress-modulated defensive freezing behavior in C. elegans

Automated Analysis of Experience-Dependent Sensory Response Behavior in Caenorhabditis elegans

Understanding how the internal state of an organism affects its response to stimuli is an important question of biology and key to understanding human neurobehavioral problems. With its tractable 302 neuron nervous system and complex behavioral repertoire, the roundworm Caenorhabditis elegans is well suited for neurobehavioral studies. In this work, I investigate the modulation of C. elegans touch response. The traditional gentle and harsh (nociceptive) touch assays involve manually delivering a stimulus to 1 mm long animals using an eyebrow or a metal wire, respectively. Using these simple assays, researchers have identified the genes and mechanoreceptor neurons mediating gentle and harsh touch. However, these are two separate manual assays limited in throughput and repeatability of the stimulus. First, I created a multiplexed microfluidic assay that allows gentle and harsh touch response behavior to be compared quantitatively in the same assay. I found that the threshold of harsh touch is about five times the threshold of gentle touch and that, while both responses habituate to repeated stimuli, the gentle touch response depends on the location of the previous touch, while the harsh touch response does not. I also found that gentle touch response is not affected by pre-stimulus velocity. Neuromodulatory states like sleep and stress can also affect touch response. Next, I examined how the response to cellular stressors, which causes an EGF-mediated recovery quiescence called stress-induced sleep (SIS), affects the mechanosensory response. Normally touch causes increased locomotor activity followed by return to baseline behavior. During this study, I observed a period of about 45 seconds of increased quiescence following the initial locomotor response. This behavior had not been documented in the literature, so I named it post-response quiescence (PRQ). I found that PRQ is upregulated following EGF overexpression, mediated, like sleep, by neuropeptide signaling, and requires the sleep active neurons ALA and RIS. While these observations suggested a form of sleep homeostasis, I found that PRQ does not meet two of the four behavioral criteria of sleep: it is not accompanied by a decrease in arousability, and it is not itself under homeostatic regulation. C. elegans touch response is known to be an escape response, and the presence of predator kairomone is known to affect C. elegans behavior. Because of the prevalence of quiescent behavior (freezing and tonic immobility) in vertebrate threat responses, and its upregulation during stress, I argue that PRQ may be a stress-modulated defensive freezing behavior in C. elegans